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Napping and Sleep

Permanent Link: http://ufdc.ufl.edu/UFE0021003/00001

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Title: Napping and Sleep An Actigraphic Study of a Sample of Community-Dwelling Older Adults
Physical Description: 1 online resource (79 p.)
Language: english
Creator: Dautovich, Natalie D
Publisher: University of Florida
Place of Publication: Gainesville, Fla.
Publication Date: 2007

Subjects

Subjects / Keywords: actigraphy, adults, napping, objective, older, sleep, subjective
Psychology -- Dissertations, Academic -- UF
Genre: Psychology thesis, M.S.
bibliography   ( marcgt )
theses   ( marcgt )
government publication (state, provincial, terriorial, dependent)   ( marcgt )
born-digital   ( sobekcm )
Electronic Thesis or Dissertation

Notes

Abstract: Individuals face many challenges as they age and a common complaint is difficulty sleeping. Nocturnal sleep disturbances in older adults have been associated with a number of factors including daytime napping. The main aim of the study was to examine the relationship between napping and sleeping behaviors in a sample of community-dwelling older adults. The relationships between both subjective (sleep diary) and objective (actigraphy) napping and sleep variables were examined. Innovations of the study included the use of both subjective and objective measures of napping and sleep, an extended data collection period, the examination of the multiple components of napping behavior (frequency, duration, and time of day), and the study of a sleep classification system in relation to napping behavior. Consistent with previous findings, napping was found to have a differential relationship with sleep. Subjectively measured nap frequency and duration were found to be negatively correlated with objectively measured total sleep time, objectively measured sleep efficiency, and subjectively measured total sleep time. Objectively measured nap frequency, duration, and time of day of napping were found to be unrelated to both subjective and objective sleep. An analysis of categories of time of day of napping revealed that individuals who napped both in the daytime and evening compared to those who napped only in the daytime showed a decrease in objectively measured sleep onset latency, a decrease in wake time after sleep onset, and an increase in sleep efficiency. Finally, the four sleep subtypes (noncomplaining good sleepers, complaining good sleepers, noncomplaining poor sleepers, and complaining poor sleepers) were not differentiated by their subjectively or objectively measured napping behavior. The results suggest that 1) it is difficult to uniformly state the direction of the relationship between napping and sleep and 2) the mode of measurement (objective and subjective) plays an important role in determining this relationship.
General Note: In the series University of Florida Digital Collections.
General Note: Includes vita.
Bibliography: Includes bibliographical references.
Source of Description: Description based on online resource; title from PDF title page.
Source of Description: This bibliographic record is available under the Creative Commons CC0 public domain dedication. The University of Florida Libraries, as creator of this bibliographic record, has waived all rights to it worldwide under copyright law, including all related and neighboring rights, to the extent allowed by law.
Statement of Responsibility: by Natalie D Dautovich.
Thesis: Thesis (M.S.)--University of Florida, 2007.
Local: Adviser: McCrae, Christina S.

Record Information

Source Institution: UFRGP
Rights Management: Applicable rights reserved.
Classification: lcc - LD1780 2007
System ID: UFE0021003:00001

Permanent Link: http://ufdc.ufl.edu/UFE0021003/00001

Material Information

Title: Napping and Sleep An Actigraphic Study of a Sample of Community-Dwelling Older Adults
Physical Description: 1 online resource (79 p.)
Language: english
Creator: Dautovich, Natalie D
Publisher: University of Florida
Place of Publication: Gainesville, Fla.
Publication Date: 2007

Subjects

Subjects / Keywords: actigraphy, adults, napping, objective, older, sleep, subjective
Psychology -- Dissertations, Academic -- UF
Genre: Psychology thesis, M.S.
bibliography   ( marcgt )
theses   ( marcgt )
government publication (state, provincial, terriorial, dependent)   ( marcgt )
born-digital   ( sobekcm )
Electronic Thesis or Dissertation

Notes

Abstract: Individuals face many challenges as they age and a common complaint is difficulty sleeping. Nocturnal sleep disturbances in older adults have been associated with a number of factors including daytime napping. The main aim of the study was to examine the relationship between napping and sleeping behaviors in a sample of community-dwelling older adults. The relationships between both subjective (sleep diary) and objective (actigraphy) napping and sleep variables were examined. Innovations of the study included the use of both subjective and objective measures of napping and sleep, an extended data collection period, the examination of the multiple components of napping behavior (frequency, duration, and time of day), and the study of a sleep classification system in relation to napping behavior. Consistent with previous findings, napping was found to have a differential relationship with sleep. Subjectively measured nap frequency and duration were found to be negatively correlated with objectively measured total sleep time, objectively measured sleep efficiency, and subjectively measured total sleep time. Objectively measured nap frequency, duration, and time of day of napping were found to be unrelated to both subjective and objective sleep. An analysis of categories of time of day of napping revealed that individuals who napped both in the daytime and evening compared to those who napped only in the daytime showed a decrease in objectively measured sleep onset latency, a decrease in wake time after sleep onset, and an increase in sleep efficiency. Finally, the four sleep subtypes (noncomplaining good sleepers, complaining good sleepers, noncomplaining poor sleepers, and complaining poor sleepers) were not differentiated by their subjectively or objectively measured napping behavior. The results suggest that 1) it is difficult to uniformly state the direction of the relationship between napping and sleep and 2) the mode of measurement (objective and subjective) plays an important role in determining this relationship.
General Note: In the series University of Florida Digital Collections.
General Note: Includes vita.
Bibliography: Includes bibliographical references.
Source of Description: Description based on online resource; title from PDF title page.
Source of Description: This bibliographic record is available under the Creative Commons CC0 public domain dedication. The University of Florida Libraries, as creator of this bibliographic record, has waived all rights to it worldwide under copyright law, including all related and neighboring rights, to the extent allowed by law.
Statement of Responsibility: by Natalie D Dautovich.
Thesis: Thesis (M.S.)--University of Florida, 2007.
Local: Adviser: McCrae, Christina S.

Record Information

Source Institution: UFRGP
Rights Management: Applicable rights reserved.
Classification: lcc - LD1780 2007
System ID: UFE0021003:00001


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NAPPING AND SLEEP: AN ACTIGRAPHIC STUDY OF A SAMPLE OF
COMMUNITY DWELLING OLDER ADULTS






















By

NATALIE DEIDRE DAUTOVICH


A THESIS PRESENTED TO THE GRADUATE SCHOOL
OF THE UNIVERSITY OF FLORIDA IN PARTIAL FULFILLMENT
OF THE REQUIREMENTS FOR THE DEGREE OF
MASTER OF SCIENCE

UNIVERSITY OF FLORIDA

2007






























O 2007 Natalie Dautovich









ACKNOWLEDGMENTS

I would like to acknowledge my mentor, Dr. Christina McCrae, for her support throughout

the completion of the proj ect. Additionally, I would like to thank both Dr. Christina McCrae and

Dr. Meredeth Rowe for the generous use of their database and their guidance. I would like to

thank my parents, Mike and Angella Dautovich, and my sister, Sonia Dautovich, for their

ongoing support, encouragement, and belief in my ability to complete this project. Finally, I

would like to especially acknowledge the emotional support from David Sams.












TABLE OF CONTENTS


page

ACKNOWLEDGMENTS .............. ...............3.....


LIST OF TABLES ................ ...............7............ ....


LIST OF flGURES .............. ...............8.....


AB S TRAC T ......_ ................. ............_........9


CHAPTER


1 INTRODUCTION ................. ...............11.......... ......


2 REVIEW OF THE LITERATURE ................. ...............12.......... ....


Insomnia and Older Adults ................. ...............12................

Napping Behavior in Older Adults ................. ...............13........... ...
Prevalence and Duration of Napping .............. ...............13....
Time of Day of Napping............... ...............1
Evening Napping ................ .. ........... ...... ........ ... ...........1
Theoretical Link between Napping and Sleep in Older Adults ................. ... .. ............ ........16
Prior Research: Association between Napping and Sleeping Behavior in Older Adults .......17
Measurement of Sleep--Obj ectively ................. ...............19................
Polysomnography ............ ....._._. ...............19.....
Actigraphy .................... ..... ..............2
Measurement of Sleep--Subj ectively ........._.._.._ ...._.._....._._ ...........2
Sleep Diary .................... ...............20.
Sleep Classifieation System .............. ...............21....
Measurement of Napping .............. .......... ....... .........2
Obj ectively Measured Napping (Actigraphy) ................. .........__ ....... 21..... ...
Subj ectively Measured Napping (Sleep Diary) ................. ........._.. ...... 22.........
Innovations of Research ................. .......__. ........._.. ...._... ....._. .......22


3 STATEMENT OF PURPOSE............... ...............24


Specific Aim 1 .............. ...............24....
Sub aim 1.1a.............. ...............24..
Sub aim 1.1Ib ............ _...... ._ ...............24...
Subaim 1.2a ................. ...............24....... .....
Sub aim 1.2b ................. ...............25....... .....
Subaim 1.3a.............. ...............25..
Subaim 1.3b ................. ........... ...............25......

Hypothesis for Specific Aim 1 .............. ...............25....
Specify c Aim 2 .............. ...............26....
Subaim 2.1la ................ ...............26................












Subaim 2.Ib ........._...... ....._.._ ...............26.....

Hypothesis for Specific Aim 2 .............. ...............26....

4 M ETHODS .............. ...............28....


Procedure .............. ...............28....
Participants .............. ...............29....
M measures ........._..... ... .... ..._._ ... .... ...............29.

Operati onalizati on of Sleep Vari ables ........._.. ...._._..... ...............29.
Obj ective sleep variables ........._..... ...._... ...............29....
Subjective sleep variables .............. ...............3 1....
Operationalization of Nap Variables ................. .....___ ......_. ...........3
Obj ective nap variables ........._.._.. ...._... ...............32...
Subj ective nap variables ........._..... ...._... ...............34....
Demographics and Health survey ........._....._ ...._.._......_._ ...........3
Cognitive Impairment............... ...............3
Daytime Functioning Measures............... ...... ...................3
Beck depression inventory--second edition (BDI-II) ................. ......................37
State-trait anxiety inventory, form Y1 (STAI) ................. ............................37
Epworth sleepiness scale (ESS) .............. ...............38....
Fatigue severity scale (FSS) ....._................... ...............38. ...
Data Analysis............... ...............38
Specific Aim 1 .............. ...............38....
Subaim 1.1a............... ...............39..
Subaim 1.1b............... ...............40..
Subaim 1.2a ................. ...............40........... ....
Subaim 1.2b ................. ...............40........... ....
Subaim 1.3a............... ...............41..
Subaim 1.3b ................. ...............41................

Specific Aim 2............... ...............42...
Subaim 2.1a............... ...............42..
Subaim 2.1b............... ...............42..


5 RE SULT S .............. ...............44....


Characteri stics of Napping B behavior within the Sample ................. ................. ....__. 44
Specific A im 1 .............. .. ......... .. .. .... ... ..............4
Subjective Napping and Objective Sleep (Subaim 1.1a)............... ...............45.
Subj ective Napping and Subj ective Sleep (Subaim 1.1b) ................ ............ .........46
Obj ective Napping and Obj ective Sleep (Subaim 1.2a) ................. ................ ...._.46
Objective Napping and Subjective Sleep (Subaim 1.2b) .............. .......... .............4
Nap Categories: Day and Evening Nappers versus Daytime Nappers (Subaim 1.3a)....47
Nap Categories: Day and Evening Nappers versus Daytime Nappers (Subaim 1.3b)....48
Specific A im 2 .............. .......... .. ..... ..................4
Sleep Subtypes and Obj ective Napping (Subaim 2. 1a) ................. ........................49
Sleep Subtypes and Subj ective Napping (Subaim 2.1Ib) ................. .......................49











6 DI SCUS SSION ................. ...............5.. 5......... ....


Review of Study Findings ............... .......... ....... .. .......5
Characteristics of Napping Behavior within the Sample .............. .....................5
Subjective Napping and Objective Sleep (Subaim 1.1a)............... ...............60.
Subj ective Napping and Subj ective Sleep (Subaim 1.1b) ........._._. .... ..._.__..........61
Obj ective Napping and Obj ective Sleep (Subaim 1.2a) ......____ ..... ... ._ ..............61
Objective Napping and Subjective Sleep (Subaim 1.2b) .............. ......... ..............6
Nap Categories: Day and Evening Nappers versus Daytime Nappers (Sub aim 1.3a) ....63
Nap Categories: Day and Evening Nappers versus Daytime Nappers (Subaim 1.3b)....64
Four Sleep Subtypes (Specific Aim 2) .............. ...............65....
Study Limitations............... ...............6
Im plications .................. ... .. ... ... .......6
Implications for Theory and Research .............. ...............67....
Clinical Implications .............. ...............67....
Future Directions .............. ...............68....
Conclusions............... ..............6

APPENDIX

A EXAMPLE OF SLEEP DIARY ........._..__ .... .___ ...............70...

B HEALTH SURVEY .............. ...............71....

LIST OF REFERENCES ........._.._ ......___ ...............72....

BIOGRAPHICAL SKETCH .............. ...............79....










LIST OF TABLES


Table page

5-1 Mean nap frequency, duration, and time of day as measured by actigraphy and sleep
di ari es ........._._._.. ...___.. ...............50....

5-2 Correlations of sleep diary napping, actigraphy sleep, and sleep diary sleep variables
with the canonical variate .............. ...............52....

5-3 Means and standard deviations for the time of day of nap groups for obj ective sleep .....53

5-4 Means and standard deviations for the time of day of nap groups for subj ective sleep ....54










LIST OF FIGURES


Figure page

5-1 Percentage of total naps taken by all participants that occurred during each half-hour
interval of the 24-hour clock ................. ...............51........... ...









Abstract of Thesis Presented to the Graduate School
of the University of Florida in Partial Fulfillment of the
Requirements for the Degree of Master of Science

NAPPING AND SLEEP: AN ACTIGRAPHIC STUDY OF A SAMPLE OF COMMUNITY
DWELLING OLDER ADULTS

By

Natalie Dautovich

December 2007

Chair: Christina McCrae
Major: Psychology

Individuals face many challenges as they age and a common complaint is difficulty

sleeping. Nocturnal sleep disturbances in older adults have been associated with a number of

factors including daytime napping. The main aim of the study was to examine the relationship

between napping and sleeping behaviors in a sample of community-dwelling older adults. The

relationships between both subj ective (sleep diary) and obj ective (actigraphy) napping and sleep

variables were examined. Innovations of the study included the use of both subjective and

obj ective measures of napping and sleep, an extended data collection period, the examination of

the multiple components of napping behavior (frequency, duration, and time of day), and the

study of a sleep classification system in relation to napping behavior. Consistent with previous

findings, napping was found to have a differential relationship with sleep. Subj ectively

measured nap frequency and duration were found to be negatively correlated with obj ectively

measured total sleep time, objectively measured sleep efficiency, and subjectively measured total

sleep time. Obj ectively measured nap frequency, duration, and time of day of napping were

found to be unrelated to both subj ective and obj ective sleep. An analysis of categories of time of

day of napping revealed that individuals who napped both in the daytime and evening compared

to those who napped only in the daytime showed a decrease in obj ectively measured sleep onset









latency, a decrease in wake time after sleep onset, and an increase in sleep efficiency. Finally,

the four sleep subtypes (noncomplaining good sleepers, complaining good sleepers,

noncomplaining poor sleepers, and complaining poor sleepers) were not differentiated by their

subjectively or objectively measured napping behavior. The results suggest that 1) it is difficult

to uniformly state the direction of the relationship between napping and sleep and 2) the mode of

measurement (objective and subj ective) plays an important role in determining this relationship.









CHAPTER 1
INTTRODUCTION

Individuals face many challenges as they age. One of these challenges is difficulty

sleeping or insomnia. Sleep complaints are multifactorial in origin and one of the factors that is

associated with nocturnal sleep complaints is napping. Although napping has been studied in

relation to sleep since the 1960s, the association between napping and sleep remains unclear.

The discrepancies in previous research on the relationship between napping and sleep in

older adults may be due in part to the multifactorial nature of napping and sleep. Additionally,

methodological limitations of the previous studies may partially account for these

inconsistencies. Within the prior literature, the multifaceted nature of napping behavior

(frequency, duration, time of day) has not been studied simultaneously in healthy and older

adults diagnosed with insomnia. Additionally, napping and sleep behavior have not been

observed for longer than one week using both obj ective and subj ective measures of napping and

sleep. Finally, napping has not been studied in relation to a variety of sleep subtypes.

Traditionally, studies have only compared good sleepers and individuals diagnosed with

insomnia. These limitations will be addressed by the present study.

The present study examines the relationship between obj ectively and subjectively

measured napping and sleep. Additionally, the relationship between napping and four subtypes

of good and poor sleepers is examined. By addressing methodological limitations of previous

research, the current study aims to further specify the nature of the relationship between napping

and sleep in older adults.



Note: For detailed specific aims, see Chapter 3.









CHAPTER 2
REVIEW OF THE LITERATURE

Insomnia and Older Adults

Individuals age 65 and older represent the fastest growing segment of the population.

According to the U.S. Census Bureau (2000a), the percentage of older adults in the population is

predicted to increase by more than 20% by the year 2030 (an increase from 4% in 1900). A

significant challenge facing individuals as they age is difficulty sleeping. Fifty-seven percent of

older adults complain of some difficulty sleeping (Kryger, Monj an, Bliwise, & Ancoli-Israel,

2004). Insomnia is the most common of sleep complaints with estimates ranging from 15-65%

(Ohayon, 2002). Insomnia involves difficulty initiating or maintaining sleep that causes

significant distress for the individual resulting in impaired social or occupational functioning

(American Psychiatric Association [APA], 2000). The impact of insomnia on older adults is

significant. The effects range from a minimum impact of daytime fatigue and decreased mood

(APA, 2000) to decreased quality of life, impaired cognitive functioning, increased risk for falls,

accidents, medical illness, and long-term care placement (Foley et al., 1995; Pollack, Perlick,

Linsner, Wenston, & Hsieh, 1990). Finally, insomnia places a huge economic burden on society.

The estimated costs for directly treating insomnia in 1995 exceeded $13.9 billion (Walsh &

Engelhardt, 1999).

Effective treatment interventions are required to mitigate the significant impact of

insomnia on individuals and society. Understanding the etiology of insomnia enables the

development of efficacious interventions. A basic factor implicated in the cause of insomnia is

age-related changes in sleep. Specifically, the architecture of sleep changes with age. Sleep

becomes structurally lighter with more time devoted to the lighter stages of sleep (stages 1 and 2)

and less time spent in deeper or slow wave sleep (stages 3 and 4; Feinberg, 1974; Hayashi &









Endo, 1982). Additionally, older adults experience less total sleep time and more awakenings

(Evans & Rogers, 1994), and longer sleep onset (i.e. the amount of time it takes to fall asleep;

Lichstein & Morin, 2000). Despite the structural changes in sleep affecting the majority of older

adults, sleep complaints are not universal. Health, situational, and psychological factors combine

and add to ontogenetic changes affecting sleep. Consequently, sleep complaints are

multifactorial in origin (Lichstein & Morin, 2000).

Napping Behavior in Older Adults

One of the situational factors associated with insomnia among the elderly is napping.

Napping is defined as "any short sleep episode" out of bed (American Sleep Disorders

Association, 1997). The out of bed sleep period does not have to be of a maximum or minimum

duration to be labeled as a nap (The International Classification of Sleep Disorders, 1990).

Prevalence and Duration of Napping

Napping is prevalent in older adults, with one in four individuals engaging in a daily nap

(Beh, 1994; Foley et al., 1995). The frequency and duration of naps in older adults varies

according to the methodology used to record napping behaviors. Using self-report, Buysee and

colleagues (1992) found that on average, older adults engaged in 3.4 naps over a two-week

period while an actigraphic study of healthy older adults without sleeping difficulties found

76.6% of participants napped at least once during a one-week recording period (Yoon, Kripke,

Youngstedt, & Elliott, 2003a).

In terms of nap duration in older adults, Yoon and colleagues (2003a) found that in a

sample of healthy older adults the average napping duration was 23.3 minutes while the average

nap duration in a study of postmenopausal women was 3 1.3 minutes (Yoon, Kripke, Elliot, &

Langer, 2004). In Shirota and colleagues' (2002) study of napping behavior in elderly

participants, there was not a significant difference between high and low volitional (a measure of









mental vigorousness) elderly participants in terms of their in nap duration. On average, high

volitional individuals napped for 36 minutes a day and low volitional individuals napped for 44

minutes a day. Using a different measure of napping duration, Jean-Louis, Kripke, Assmus, and

Langer (2000) found that on average, over a 24-hour period, older adults napped for 45 minutes.

Interestingly the 45 minute total nap time accounted for 10% of their total 24-hour sleep (Jean-

Louis et al., 2000). In summary, previous research has found that on average, older adults

engage in one nap per week, with the average duration of naps ranging from 23.3 to 45 minutes

per day.

Although napping behavior is prevalent in older adults, it is variable. While many older

adults report napping behaviors, a number do not. Buysee and colleagues (1992) found that

according to sleep diaries, approximately thirty-six percent of a sample of older adults reported

no naps during a two-week recording time. Additionally, there may be significant variability

between napping behaviors occurring on the weekday compared to the weekend. In the same

study Buysee and colleagues (1992) found a significant difference between the frequency of

napping behavior during the week and on the weekend, with more naps occurring on average

during the week. Longitudinal assessment of napping behavior is more likely to capture the

variability of napping behavior in older adults.

Time of Day of Napping

The time of day of napping is an important component of napping behavior in part

because the time of day the nap occurs may moderate the hypothesized association between

napping and sleep. A theoretical explanation for the association between time of day of napping

and nocturnal sleep is that naps taken later in the day contain more slow wave sleep than naps

taken earlier in the day (Yoon et al., 2003b). Considering that slow wave sleep provides the









most restorative sleep, by engaging in naps at a later point during the day individuals may

engage in a deeper sleep that meets more of their nocturnal sleep needs.

A number of studies have calculated the average time of day of naps. Shirota and

colleagues (2002) found that there was not a significant difference in the average time of day of

naps of both high and low volitional elderly participants. On average, high volitional individuals

began their naps at 13:34 and low volitional individuals began their naps at 13:38. Although

there were no significant differences in the timing of the naps, high volitional individuals took

their naps as their activity levels were decreasing whereas low volitional individuals took their

naps as their activity levels were increasing. Elderly participants reported napping slightly later

in the afternoon (14:42) in the study by Buysee and colleagues (1992) and reported no significant

difference in the timing of naps during the week compared to on the weekend. Napping 'peaks'

were observed at three times during the day in a study of postmenopausal women (Yoon, 2004).

The highest peak occurred approximately one hour before bedtime, the second approximately 8

or 9 hours after wake-up time, and the smallest peak 2 hours after wake-up time. These peaks

corresponded with the clock times of 22:00, 15:00/16:00, and 09:00. In summary, in the studies

that reported the average time of day of naps, the average time of day of naps was variable

ranging from 13:34 to 22:00.

Evening Napping

In addition to studying the relationship between out-of-bed sleep in general and nocturnal

sleep, a number of researchers have identified a subset of napping behavior the evening nap.

Previous research defines evening naps as out-of-bed sleep that occurs within the timeframe of

two hours to just before bedtime (Yoon et al., 2003b). Evening naps may impact sleep by

causing earlier awakenings, earlier illumination exposure, and consequently causing a phase









advance of the circadian system (Buxton, L'Hermite-Baleriaux, Turek, & van Cauter, 2000;

Yoon et al., 2003a.)

The frequency of evening napping appears to increase with age (Jean-Louis et al., 2000;

Monk, Buysse, Carrier, Billy, & Rose, 2001; Yoon,et al., 2003b). In a paper by Yoon and

colleagues (2003b), the evening nap timeframe corresponded to the clock-time of 20:3 8 22:3 8.

In a study of post-menopausal women, Yoon and colleagues (2004) found that the average

evening nap duration was 7.75 minutes. This duration contrasts with an average daytime nap

duration of 31.3 minutes in the same study. Ancoli-Israel, Kripke, Mason, and Kaplan (1985)

found that in a sample of individuals diagnosed with sleep apnea, periodic limb movements

(PLM), or no diagnosis, 45% of elderly participants engaged in evening naps. The frequency of

evening naps ranged from 3-5 per evening and the duration ranged from 5 to 18 minutes. Yoon

and colleagues (2003b) found that 52% of the sample engaged in at least one evening nap per

week. Considering the prevalence of evening napping among the elderly, it is important to

assess this napping behavior among older adults. Additionally, considering the unique

characteristics of evening naps reported in previous studies (e.g. higher frequency and shorter

duration) it may be informative to examine evening naps separately from daytime naps.

Theoretical Link between Napping and Sleep in Older Adults

In addition to studying the characteristics of napping behavior in older adults, several

theoretical explanations have been provided to account for the association between napping and

nighttime sleep. Borbely (1982) advanced two biological mechanisms to explain the relationship

between napping and sleep. The circadian system, controlled by an internal pacemaker within

the hypothalamus, regulates sleepiness and wakefulness within a 24-hour rhythm. The second

mechanism, the homeostatic drive, results in an increasing motivation towards sleepiness during

periods of wakefulness. Older adults may experience a decreased homeostatic drive (accounting









for less deeper sleep during the night and increased number of awakenings) that results in a

decreased drive towards wakefulness during the day. Buysee and colleagues (1992)

hypothesized that napping disrupts both the circadian system and the homeostatic drive, resulting

in an increase of polyphasic sleep. Consequently, older adults experience more fragmented

patterns of daytime and nocturnal sleep compared to younger adults (Hays, Blazer, & Foley,

1996).

An alternate theoretical explanation for the increasing number of naps as individuals age is

that daytime sleep propensities may no longer be being masked by social obligations among the

elderly (Jean-Louis et al., 2000). Although older adults may maintain high levels of activity

during retirement, the less compulsory nature of these activities may provide increased

opportunities for daytime napping behavior.

Prior Research: Association between Napping and Sleeping Behavior in Older Adults

Despite the theoretical basis for the relationship between napping and sleep, previous

research is mixed regarding the strength or existence of this relationship. Several studies have

found that napping behavior is associated with impaired nocturnal sleep. Frequency of napping

was associated with increased risk of sleep complaint (Hays et al., 1996) while duration (Beh,

1994) of napping was negatively correlated with nocturnal sleep length. Yoon and colleagues

(2003a) examined the relationship between time of day of napping (evening naps), wake times,

and nocturnal sleep length. Older adults who engaged in evening naps within a timeframe of two

hours to bedtime were found to have significantly earlier wake-up times (undesirable for older

adults) and decreased total sleep time. Yoon and colleagues (2003b) also compared the sleep

onset and offset times of older adults with or without evening naps. There was a significant

difference in the sleep offset times with individuals who engaged in an evening nap awakening

on average 54 minutes earlier than those who did not engage in an evening nap. No significant









differences were reported in nocturnal sleep between those who napped and did not nap as

measured by sleep diaries but a significantly lower total sleep time was recorded by

polysomnography for those who engaged in naps (Monk et al., 2001). Finally, a significantly

longer sleep onset latency was observed in individuals who napped compared to those in a

sedentary condition (Campbell, Murphy, & Stauble, 2005).

In contrast to the negative relationship between napping behavior and sleep variables, a

small number of recent studies suggest a positive association between napping behavior and

sleep quality. Studies involving the Okinawa elders of Japan have found that prescribed napping

of 30 minute duration between the hours of one and three in the afternoon was significantly

associated with decreased wake time after sleep onset and improved sleep efficiency (sleep

efficiency refers to the percentage of time in bed that is spent sleeping; Tanaka et al., 2002).

Additionally, napping in the afternoon reduced the average evening nap duration from 39 to 11

minutes (Tanaka et al., 2001). Another study involving the Okinawa elders found that a higher

percentage of elderly participants in the rural areas took a daily nap (55.2%) compared to elderly

participants in the urban areas (32.4%). The rural elderly had significantly fewer sleep

complaints and a significantly lower sleep health risk index (an analysis of sleep health including

sleep disturbances, parasomnia, apnea, difficulty waking, and difficulty falling asleep; Arakawa,

Tanaka, Toguchi, Shirakawa, & Taira, 2002). Similarly, Foley and colleagues (1995) found that

an increase in napping frequency was accompanied by an overall decrease in sleep complaints

and frequent nappers (>2 naps per two week period) reported shorter sleep onset latency

compared to less frequent nappers (< 2 naps per two week period; Buysee et al., 1992).

Additionally, several studies have reported a significant increase in 24-hour total sleep time for

individuals who nap compared to those who do not (Campbell et al., 2005; Monk et al., 2001).









Finally, a large portion of the available literature on napping has found no relationship

between napping and sleep. Good and poor sleepers did not differ in terms of napping frequency

(Bliwise, 1992; Morin & Gramling, 1989), napping duration (Aber & Webb, 1986), or both

napping frequency and duration (Johnston, Landis, Lentz, & Shaver, 2001; Morgan, Healey, &

Healey, 1989; Morin & Gramling, 1989). Similarily, Jean-Louis and colleagues (2000) found

that afternoon and evening naps were not associated with nocturnal sleep duration, sleep

efficiency, or total wake time. Contrasting with the improved sleep associated with napping as

reported using sleep diaries, Buysee and colleagues (1992) found no significant difference

between frequent and infrequent nappers in terms of polysomnographic sleep variables.

Measurement of Sleep-Objectively

Polysomnography

Some of the discrepancies in previous findings result in part from differing methods of

measuring sleep. Sleep can be assessed using objective and subjective methods. Considering the

variations in the previous findings, both subj ective and obj ective approaches will be used in the

current study.

The traditional 'gold standard' for objectively measuring sleep is polysomnography (PSG).

This procedure provides the most thorough and obj ective diagnosis of sleep disorders other than

insomnia (Lichstein & Morin, 2000). Polysomnography assesses sleep by recording brain waves

(electroencephalography EEG), eye movements (electro-oculography EOG), chin muscle

tone (chin and anterior tibialis electromyography EMG), respiratory effort, airflow, oximetry,

and electrical activity of the heart (electrocardiography ECG). Despite the thoroughness of this

procedure, there are several limitations for its use with older adults. The procedure typically

occurs in a laboratory setting. This setting may be uncomfortable for older adults and may not

resemble their natural sleep environment (Libman, Creti, Levy, Brender, & Fichten, 1997).









Interestingly, individuals with sleep problems often sleep better away from their own home due

to a lack of association between poor sleep and the new environment. Therefore, assessing an

individual's sleep away from home may result in an overestimation of their sleep quality. Also,

the customary two night duration of a PSG study may not capture the highly variable nature of

older adult sleep (Edinger, Marsh, McCall, Erwin, & Lininger, 1991). Finally, the cost of PSG

for a large sample size can be prohibitive.

Actigraphy

Considering the limitations associated with the use of PSG, another obj ective measure of

sleep, actigraphy, was employed in the current study. Actigraphy, used for over 25 years,

involves the wearing of a wristwatch-like device, typically on the nondominant wrist. In contrast

with PSG, actigraphy is relatively inexpensive, enables the individual to remain in their natural

environment, and can record data continuously for up to 14 days. There are several actigraphic

devices available for use. The Actiwatch-L@ (Mini Mitter Co. Inc., 2001) was chosen because it

utilizes the most up-to-date technology (i.e. digital integration) and has been validated with

healthy older adults with insomnia (Mini Mitter Co. Inc., 2001).

Measurement of Sleep--Subj ectively

Assessment of subj ective appraisals of sleep can complement the obj ective data collected

using actigraphy. Sleep diaries were used to subj ectively measure sleep in the study.

Additionally, participants were classified into four sleep subtypes using sleep diary and other

self-report information.

Sleep Diary

Sleep diaries are a self-report description of sleeping behaviors recorded on a written log

by the participant. Example behaviors that the participant may report include the time he or she









goes to bed, the amount of time required to fall asleep, and the number of awakenings during the

night. The diaries are typically completed in the morning once the participant wakes up.

Sleep Classification System

A number of self-identified poor sleepers do not experience objectively poor sleep as

measured by polysomnography or actigraphy. Interesting, these individuals do not differ from

individuals obj ectively diagnosed with insomnia in terms of the symptoms experienced

(Lichstein, Wilson, Noe, Aguillard, & Bellue, 1994). The diagnostic label for this condition is

sleep state misperception (American Sleep Disorders Association, 1997), but it is commonly

referred to as subj ective insomnia. Considering that clinicians focus their treatment on the

complaint aspect of insomnia, the study of subj ective insomnia is critical.

McCrae and colleagues (2005) developed a classification system for identifying

individuals based on subjective complaints and subjective sleep quantity. Individuals are

classified into one of four sleep subtypes based upon the following criteria: 1) subj ective

complaint of insomnia, 2) duration of insomnia complaint, 3) daytime functioning, and 4) sleep

pattern as measured by the sleep diaries. The classification system resulted in four sleep

subtypes: noncomplaining good sleepers, complaining good sleepers, noncomplaining poor

sleepers, and complaining poor sleepers (insomniacs) (Figure 2-1).

Measurement of Napping

Objectively Measured Napping (Actigraphy)

Previous studies have found that older adults often underreport their napping behavior.

Comparing subj ective reports and EEG recordings of napping behavior, Jean-Louis and

colleagues (2000) found that volunteers correctly reported only 3 8% of their afternoon-evening

napping periods (with a false-positive reporting rate of 19%). Yoon and colleagues (2003a)

found that only 22.6% of older evening nappers reported their evening naps in sleep diaries. The










present study addresses some of the concerns associated with the self-reporting of naps by older

adults by using an obj ective measurement of napping, the Actiwatch-L" (Mini Mitter Co. Inc).

In addition to the sleep parameters, a number of napping parameters can be derived from the

Actiwatch data.

Subjectively Measured Napping (Sleep Diary)

In addition to obj ectively measured napping, it is possible to subj ectively estimate napping

using sleep diaries. Participants report on the number of minutes they spent napping for each

day.

Innovations of Research

Despite the accumulation of research over four decades, the association between napping

and sleep remains unspecified. Several methodological limitations may account for the lack of

consensus. These shortcomings will be addressed by the current study.

Previous research has relied heavily on surveys or self-report sleep diaries to assess

napping and sleep behavior in older adults. Studies of sleep patterns in postmenopausal women

and healthy older adults reported that 62 77% of napping behavior was unreported when

compared to obj ective measures of sleep (actigraphy and polysomnography; Jean-Louis et al.,

2000; Yoon et al., 2003a). This limitation will be addressed in the current study by the use of an

obj ective measure (actigraphy) of both napping and sleep, in addition to subj ective measures

(sleep diary), in order to more accurately assess napping and sleep behavior.

An additional limitation involves the variability inherent in napping and sleep behavior in

older adults. Approximately 50% of older adults engage in napping behavior only one to two

days per week (Beh, 1994). Napping and sleep behavior also varies from weekday to weekend

(Buysse et al., 1992) with napping occurring more frequently during the week than on the

weekends. The typical data collection period in previous research ranges from one to two days









to a maximum of six days. Limited data collection periods may not accurately capture the

variability in older adult napping and sleep behavior. The current study will address this

limitation by extending the data collection period to 12 consecutive days.

Furthermore, prior research has typically examined the components of napping behavior in

isolation. The current study aims to assess the differential impact of the three components of

napping behavior (frequency, duration, and time of day) on sleep quantity.

Additionally, the current study will use a classification system for the study of sleep and

napping. Sleep subtypes (a combination of qualitative and quantitative subj ective estimates of

sleep) will be examined for the first time in relation to napping behavior. This will allow for the

simultaneous study of both healthy individuals and those diagnosed with insomnia within the

same study.

Although these limitations have been addressed individually in previous research, this is

the first study to simultaneously address these limitations.



Insomnia Criteria

Yes No


Yes individuals complaining
Complaints with insomnia good

sleep problem
duration
daytime functioning
SN o n o n c o m p l a i n i n g n o n c o m p l a i n i n gs e p r
poor good
sleepers sleepers

Figure 2-1. Visual depiction of sleep classification system.









CHAPTER 3
STATEMENT OF PURPOSE

The main obj ective of the study is to examine the relationship between napping and

sleeping behavior in older adults. Napping behavior will be studied 1) in relation to obj ectively

and subjectively measured sleep quantity and 2) in relation to the four sleep subtypes. The two

main obj ectives will be achieved through specific aims and associated subaims.

Specific Aim 1

The first specific aim is to investigate the relationship between napping behaviors and

sleep quantity.

Subaim 1.1a

To investigate the relationship between subj ectively measured napping behaviors

frequencys and durations as measured by sleep diaries) and objective sleep quantity as measured

by actigraphy (total sleep time, sleep onset latency, wake time after sleep onset, and sleep

efficiency, the sub scripts "s" and "o" are used to distinguish between the subjective and

objective sleep variables). See Chapter four for operational definitions of the napping and sleep

variables.

Subaim 1.1b

To investigate the relationship between subj ectively measured napping behaviors

frequencys and durations as measured by sleep diaries) and subjective sleep quantity as

measured by the sleep diaries (total sleep times, sleep onset latency, wake time after sleep onset,

and sleep efficiencys.

Subaim 1.2a

To investigate the relationship between obj ectively measured napping behaviors

frequencyy, duration, and time of dayo as measured by actigraphy) and obj ective sleep quantity









as measured by actigraphy (total sleep time, sleep onset latency, wake time after sleep onset,

and sleep efficiencyo).

Subaim 1.2b

To investigate the relationship between obj ectively measured napping behaviors

frequencyy, duration, and time of dayo as measured by actigraphy) and subj ective sleep quantity

as measured by the sleep diaries (total sleep times, sleep onset latency, wake time after sleep

onset, and sleep efficiencys).

Subaim 1.3a

To investigate the relationship between time of day of napping categories (day and evening

nappers versus daytime nappers) and obj ective sleep quantity as measured by actigraphy (total

sleep time, sleep onset latency, wake time after sleep onset, and sleep efficiencyo.

Subaim 1.3b

To investigate the relationship between time of day of napping categories (day and evening

nappers versus daytime nappers) and subj ective sleep quantity as measured by the sleep diaries

(total sleep times, sleep onset latency, wake time after sleep onset, and sleep efficiencys).

Hypothesis for Specific Aim 1

The hypothesis for the first specific aim is that both the subjective and obj ective napping

variables (frequencyois, durationois, and time of day of napping) will be most strongly correlated

with the sleep quantity variable of total time spent asleep for both obj ective and subj ective sleep

quantity .

Previous research has found significant associations between frequency (Hays et al., 1996),

duration (Beh, 1994), and time of day (Yoon et al., 2003a) of napping and various sleep

variables. Considering that prior research is mixed regarding the direction of the relationship

between the napping and sleep variables, the direction of the proposed relationship between










napping and sleep cannot be predicted for the present study. Since total sleep time has been

found to be the single best indicator of sleep quantity (Lichstein & Morin, 2000), it is

hypothesized that the napping variables will most strongly be associated with total sleep time.

Specific Aim 2

The second specific aim is to identify the differences between the four sleep subtypes

(noncomplaining good sleepers, complaining good sleepers, noncomplaining poor sleepers, and

complaining poor sleepers) in terms of their napping behavior (frequencyois, durationois, and time

of day of napping) as measured by actigraphy and sleep diaries.

Subaim 2.1a

Investigate the extent to which the four sleep subtypes (noncomplaining good sleepers,

complaining good sleepers, noncomplaining poor sleepers, and complaining poor sleepers) differ

in terms of their obj ectively measured napping behavior frequencyy, duration, and time of dayo

as measured by actigraphy).

Subaim 2.1b

Investigate the extent to which the four sleep subtypes (noncomplaining good sleepers,

complaining good sleepers, noncomplaining poor sleepers, and complaining poor sleepers) differ

in terms of their subj ectively measured napping behavior frequencys and durations as measured

by sleep diaries).

Hypothesis for Specific Aim 2

The hypothesis for the second specific aim is that both subj ective and obj ective napping

variables (frequencyois, durationois, and time of day of napping) will be differentially related to

the four sleep subtypes. This aim is exploratory in that the sleep subtypes have not been studied

previously in relation to napping behavior. Previous research has demonstrated a relationship

between the four sleep subtypes and sleep behavior. Complaining good sleepers were found to









have poorer subj ective sleep quantity in comparison to noncomplaining good sleepers.

Specifically, complaining poor sleepers had a greater number of awakenings, greater wake time

after sleep onset, poorer sleep efficiency, and more total wake time. The four sleep subtypes also

differed in terms of obj ective sleep quantity. Complaining poor sleepers had greater sleep onset

latency, poorer sleep efficiency, and greater total wake time (McCrae et al., 2005).









CHAPTER 4
METHOD S

Procedure

A secondary data analysis was performed using data collected during a study conducted by

McCrae and Rowe (2003). A convenience sample was recruited from the North Florida area. A

variety of recruitment techniques were employed including media advertisements, community

groups, and flyers. Recruitment materials described the research as a study of sleep patterns in

the elderly. Participants were compensated $30 for their participation. Interested individuals

were screened in two phases to determine if they met the criteria for inclusion. Phase one

consisted of a brief telephone interview (15-20 minutes), and phase two involved an in-person

interview either in the individual's home (76%) or at a local continuing care retirement center

(24%).

Individuals were excluded on the basis of six exclusionary criteria: 1) age younger than 60

years; 2) self-report of sleep disorder diagnoses other than insomnia (e.g., sleep apnea or

narcolepsy); 3) self-report of sleep symptoms indicative of sleep diagnoses other than insomnia

(e.g., heavy snoring, gasping for breath, leg j erks, daytime sleep attacks); 4) presence of severe

psychiatric disorders (e.g., thought disorders or depression); 5) cognitive impairment (e.g.,

scoring in the impaired range on three or more subtests of the Cognistat); 6) use of psychotropic

or other medications know to alter sleep (e.g., beta-blockers); and 7) medical conditions that

impaired independent daily functioning (McCrae et al., 2005).

Data were collected at three periods during the study: baseline, end of first week, and end

of second week. During the initial 1-1V/2 hour interview, participants read and signed an

informed consent form approved by the University of Florida Institutional Review Board. Once

consent was obtained, the Cognistat, and the demographics and health survey were administered









by a member of the research team. At this time, both the sleep diaries and the Actiwatch-L"

were explained to the participants. The participants were advised to complete the sleep diaries

and wear the Actiwatch-L" continuously for 14 days. At the end of the first week, the sleep

diaries were collected from the participants and the data was downloaded from the Actiwatch-

L". At the end of the second week, the final week of sleep diaries and Actiwatch-L" data were

collected. The Beck Depression Inventory-Second Edition, State-Trait Anxiety Inventory, State-

Form Y1, and the PANAS were also completed at this time.

Participants

Of the 1 16 individuals recruited, 103 were enrolled in the study. Thirteen individuals were

ineligible to participate in the study due to age, dementia, medication, and sleep apnea diagnosis.

The mean age of the participants was 72.81 years (SD = 7. 12). The majority of participants were

European Caucasian (96%), female (66%), college educated (75%; M~= 16.34 years, SD = 2.92),

and married (59%). All of the participants lived in their own homes during the study.

Measures

Overviews of the nap and sleep variables, the demographics and health survey, the

Cognistat, and the measures of daytime functioning are presented below. Additional information

on the methodology for assessing napping and sleep is presented in the literature review.

Operationalization of Sleep Variables

Objective sleep variables

Objective sleep was measured using the Actiwatch-L". Within the Actiwatch-L", data is

sampled 32 times per second over a 30 second epoch using an omnidirectional, piezoelectric

accelerometer with a sensitivity of > 0.01 g-force. A sum of the peak activity counts for each 30

second epoch is downloaded to a PC and then analyzed by Actiware-Sleep vol. 3.3. (Mini Mitter

Co. Inc., 2001). Three sensitivity settings (high, medium, and low) are provided by the software









for detecting wake/sleep periods. A high sensitivity setting was used in the current study since it

provides high correlations with PSG measured total sleep time (.95) for healthy older adults

(Colling et al., 2000) and for total sleep time (.73) and sleep onset latency (.93) for individuals

with insomnia (Cook et al., 2004). Additonally, actigraphy has valid criterion-validity when

compared to PSG (.80) and high test-retest reliability (0.92; Ancoli-Israel et al., 2003).

A validated algorithm is used to identify the activity of each epoch as wake or sleep

(Oakley, 1997). With the high sensitivity setting, the threshold for wake is 20 activity counts. If

the peak activity count for an epoch is > 20, the epoch will be scored as wake. If the peak

activity count for an epoch is < 20, the wake/sleep determination is made based on the activity

that occurs in the two minute period surrounding the epoch. The wake/sleep determination if the

activity count is < 20 is made based on following equation:

Total Activity for Epoch A = EA-4 (.04) + EA-3 (.04) + EA-2 (.20) + EA-1 (.20) + E (2) +

EA+1 (.20) + EA+2 (.20) + EA+3 (.04) + EA+4 (.04)

where A = # of activity counts for the epoch being scored; EA +/- 1-4 = Of activity counts in

adj acent epochs. If the Total Activity for Epoch A (weighted sum of activity counts) exceeded

the threshold value of 20, then Epoch A is scored as wake; otherwise, it is scored as sleep

(McCrae et al., 2005).

Using the Actiware-Sleep vol. 3.3. software (Mini Mitter Co. Inc., 2001), a number of

sleep parameters are derived from the data including total sleep time, total wake time, sleep

efficiency, and sleep onset latency. The definitions of the objective sleep variables used in the

study are: sleep onset latency (interval between bedtime and sleep start); total sleep time (sum

of all sleep epochs within a sleep period); sleep efficiency (ratio of total sleep time to total time

spent in bed x 100); and wake time after sleep onset (time spent awake after initial sleep onset









until last awakening). The subscripts "s" and "o" are used to distinguish between the subj ective

and objective sleep variables.

Subjective sleep variables

Sleep diary. Subjective sleep quantity was measured using sleep diaries. The sleep diary

(Lichstein, Riedel, & Means, 1999) was completed by each participant each morning for 14 days

(see Appendix A). Although data was collected for 14 days, the first and last days of data were

eliminated from the analysis as the actigraphy data for those days was incomplete. Four

subjective sleep estimates were derived from the sleep diary data: sleep onset latency (initial

time from lights out until sleep onset); wake time after sleep onset (time spent awake after initial

sleep onset until last awakening); total sleep times (computed by subtracting total wake time

from time in bed); and sleep efficiency (a ratio of total sleep time to total time spent in bed x

100).

Sleep classification system. The second subjective measurement of sleep that was

employed was the sleep classification system. The specific criteria used to create the four sleep

subtypes within the system are as follows. The criteria used to assess the three complaints and

insomnia are: 1) subj ective complaint of insomnia as indicated by affirmative responses to the

following items on the demographics and health questionnaire: "Do you have a sleep problem?

yes or no. If yes, describe (e.g., trouble falling asleep, long or frequent awakenings, sleep

apnea)."; 2) duration of complaint for at least 6 months as indicated by response to the item on

the demographics and health questionnaire: "How long have you had this sleep problem?"; and

3) impaired daytime functioning as indicated by scoring in the impaired range on at least one of

the following measures: STAI > 36, BDI > 9, ESS > 7.3, or FSS > 5.4.

Participants were categorized as poor sleepers if they reported at least 3 nights a week of:

(1) sleep onset latency >30 minutes or (2) wake time after sleep onset > 30 minutes. This criteria









for insomnia has been validated and is consistent with those commonly cited in the insomnia

treatment literature (Lichstein, Durrence, Taylor, Bush, & Riedel, 2003). Individuals diagnosed

with subj ective insomnia correspond with sleep subtype of complaining good sleepers.

Operationalization of Nap Variables

Objective nap variables

Napping was measured objectively using actigraphy. Methodological questions have

arisen regarding the sensitivity of actigraphy to distinguish between inactivity due to napping

versus inactivity due to resting or the removal of the watch. Interestingly, the sensitivity setting

(high) validated for determining sleep bouts in older adults is not applicable for identifying

napping behavior in older adults. The use of a threshold of 20 activity counts per 30 second

epoch results in an overestimation of daytime napping behavior. This is due in part to the

misidentification of levels of inactivity (resting/watch removal) as sleep bouts. Therefore, an

even higher sensitivity setting is required in order to differentiate mere inactivity from napping

behaviors. In the present study a sensitivity setting of 12 enabled the detection of naps identified

by participants in their sleep diaries.

Additionally, concerns about differentiating resting and watch removal from napping can

be addressed by examining narratives in the participants' sleep diaries (e.g. "watch removed

from 6-8 p.m.") and applying Webster' s rules (Webster, Kripke, Messin, Mullaney, &

Wyborney, 1982) to distinguish between resting/watch removal and napping behavior.

Specifically, Webster's rules involve rescoring small wake periods surrounded by sleep periods

as 'sleep' and rescoring small sleep periods surrounded by wake periods as 'wake'. An

additional method to be used in the study for differentiating 'watch off' periods from naps

involves increasing the sensitivity level to the highest setting (0) and noting which periods are

still identified as naps at this setting. If a period of inactivity is labeled as a nap at the highest









setting, the nap should be eliminated from the analysis. An activity count of 'O' contains less

activity then would be required for human sleep and actually represents 'watch off' intervals (M.

Reed, Minimitter, personal communication, June 6, 2005).

Finally, in order to encompass the range in the duration of naps of 5 to 45 minutes found in

previous research, naps that ranged in duration from 5 to 180 minutes were included in the

analysis.

Frequency as measured by actigraphy. Frequency refers to the total number of periods

during the day (as measured by actigraphy) that were scored as sleep. The total number of

inactive periods during the day was averaged over 12 days to create the nap frequencyy'

variable.

Duration as measured by actigraphy. Duration refers to the total time in minutes that

the actigraph was scored as sleep for discrete nap periods throughout the daytime. If there were

multiple naps of different durations during the day, the mean nap duration for each day was

calculated for each participant. An overall mean nap durationn' was calculated by averaging the

average daily nap durations over 12 days.

Time of day. Time of day was determined from the actigraphy data by converting the

time each nap occurred into 24-hour clock time. The 'time of dayo' variable was created by

summing the time of day of all naps for each participant and dividing by the number of naps for

each participant. Subj ective measures of the time of day of naps could not be determined from

the information gathered by the sleep diary.

The above mentioned operationalization of time of day of napping involves averaging the

time of day of naps for each participant and dividing by the total number of naps. While this

calculation may accurately describe the time of day for nappers who consistently nap at the same









time each day, it may not accurately describe the time of day for more variable nappers. If a

participant naps both in the morning and the evening, for example, averaging the time of day

naps would suggest that they typically nap in the afternoon. In addition to the analysis of a

continuous measurement of time of day of napping (subaims 1.2a and 1.2b), a categorical

measurement was used that identified individuals who napped in the daytime versus the evening.

Time of day nap categories (used in subaim 1.3) were created by aggregating participants

who napped during both the day and evening into the 'day and evening nap' group and

participants who solely napped during the daytime into the 'daytime nap' group. Evening naps

have been previously defined as out-of-bed sleep that occurs within the timeframe of within two

hours to just before bed (Yoon et al., 2003b). A similar inclusion criteria was used in this study

where a nap was labeled an evening nap if it occurred within two hours of the individual's

bedtime for the day being considered.

Subjective nap variables

Two subj ective estimates of napping behavior can be derived using the sleep diary:

frequency and durations (the sub script 's' denotes subj ectively measured napping). The 'nap'

section of the sleep diary provides a place for the individual to record the total number of

minutes spent napping prior to bedtime for each day.

Frequency as measured by sleep diaries. Frequency was determined from sleep diaries

by summing the number of naps that were self-reported over 12 days and dividing by 12 to

create the nap frequencyy' variable.

Duration as measured by sleep diaries. Duration was derived from the sleep diary data

by summing the total nap time reported for each nap on the sleep diary and dividing by the total

number of days for which a nap was reported in order to create the nap 'durations' variable.

Importantly, sleep diary nap durations differs from actigraphy nap duration in that it refers to the









average total daily nap duration, while the actigraphy nap duration refers to the average nap

duration for each nap.

Although according to many participants the sleep diary nap duration typically reflects the

duration for a single nap (they reported engaging in only one nap per day) it cannot be discerned

whether the duration reported on the sleep diary refers to the average total daily nap duration or

the average duration of individual naps.

Although the possibility exists that the duration and durations variables may be referring to

different constructs, it is important to retain these variables for a couple of reasons. First, nap

duration as recorded by sleep diaries is the traditional and most commonly employed method of

assessing nap duration among the literature. Therefore, by retaining this variable in the study it

will be possible to compare our results to previous findings. Additionally, sleep diaries are the

method most commonly used by sleep clinicians to assess client's sleeping behavior. Hence, the

inclusion of sleep diaries in the present study will provide information that may have

implications for the provision of treatment by clinicians. Second, nap duration as recorded by

actigraphy provides the most sensitive estimate of nap duration. This method ensures that the nap

duration that is recorded captures the duration of individual naps. Consequently, the information

provided by both of these variables is valuable to the study.

Demographics and Health survey

This survey consists of 13 items collecting information on demographics, sleep disorder

symptoms, physical health, and mental health (Lichstein et al., 2004) (see Appendix B). Health

conditions were assessed as the number of conditions selected from the following list: heart

attack, other heart problems, cancer, AIDS, hypertension, neurological disorder (seizures,

Parkinson' s), breathing disorder (asthma, emphysema, allergies), urinary problems (kidney

disease, prostate problems), diabetes, pain (arthritis, back pain, migraines), and gastrointestinal









disorders (stomach, irritable bowels, ulcers, gastric reflux). Self-report sleep questions on the

survey contained information on whether the participant had a sleep problem and if they or a bed

partner noticed heavy snoring, difficulty breathing or gasping for breath, frequent leg jerks,

restlessness before sleep onset, sleep attacks during the day, or paralysis at sleep onset. If they

answered yes to any of these problems, they were asked to describe the problem and indicate

how often and for how long the symptoms had occurred.

Cognitive Impairment

Participants were screened for cognitive impairment using the Cognistat (The

Neurobehavioral Cognitive Status Examination; Mueller, Kiernan, & Langston, 2001). This

measure contains ten subscales measuring the domains of: orientation and attention, language,

visual memory and constructional ability, verbal memory, calculations, reasoning, and judgment.

Each domain area is initially assessed using a 'screen' item (e.g., a three stage command, "Turn

over the paper, hand me the pen, and point to your nose"). If the participant does not correctly

answer the screen item a set of follow-up items of increasing difficulty are administered. The

test takes approximately 20 minutes to administer. Individuals who scored in the impaired range

on three or more of the ten subscales were excluded from the study. The Cognistat has been

found to more sensitively detect cognitive-impairment than the Mini-Mental State Exam (Fields,

Fulop, Sachs, Strain, & Fillit, 1992) and to effectively differentiate between impairment due to

psychiatric illness versus impairment due to organic cognitive impairment (Wiederman &

Morgan, 1995). Interrater reliability was found to range from 0.997 to 1.00 (Cunic & Denny,

2001).










Daytime Functioning Measures

Beck depression inventory--second edition (BDI-II)

Depression was measured using the Beck Depression Inventory-Second Edition (BDI-II;

Beck, Steer, & Garbin, 1996). This is a 21-item measure with a scale ranging from 0-3

measuring the severity of depressive symptoms (3 being the most severe). Scores range from 0 -

63. Scores within the 0 13 range indicate none or minimal depression, 14 to 19 indicate mild

depression, 20 to 28 indicate moderate depression, and 29 to 63 indicate severe depression.

Participants were asked to respond to the questions based on the previous two weeks. The BDI-

II has demonstrated sufficient internal consistency reliability (.90) and concurrent validity (.69 -

.76) (Storch, Roberti, & Roth, 2004). In the present study, the boundary scores for mild

depression were used as the cutoffs for evidence of a daytime functioning complaint (BDI-II >

13).

State-trait anxiety inventory, form Y1 (STAI)

Anxiety was measured using the Stait-Trait Anxiety Inventory Form Y1 (STAl-Y1;

Spielberger, Gorsuch, Lushene, Vagg, & Jacobs, 1983). This is a 20-item measure with a 4-

point scale indicating how often the statement is true. Scores range from 20 80 with higher

scores indicating greater maladjustment. The scale assesses how often the individual

experienced apprehension, tension, nervousness, and worry during the previous two weeks. The

STAl-Y1 has a test-retest reliability coefficient of .92 and adequate criterion validity (>.70;

Spielberger, 1989). Scores greater than 36 were used as evidence of a daytime functioning

complaint. This cutoff was chosen, because a score of 37 is 1 SD below the mean for psychiatric

inpatients with a primary diagnosis of anxiety (Spielberger, Gorsuch, Lushene, Vagg, & Jacobs,

1983).










Epworth sleepiness scale (ESS)

The Epworth Sleepiness Scale (ESS; Johns, 1991) measures trait daytime sleepiness. For

eight common, quiet daytime activities (e.g. watching television) respondents indicate how likely

they are to fall asleep. The responses are based on the previous two weeks. Responses range

from 0 (would never doze) to 3 (high chance of dozing). Total scores range from 0 to 24, with

the higher scores indicating greater daytime sleepiness. Although adequate norms for the ESS

are not available, Johns and Hocking (1997) administered the ESS to 331 corporate employees.

They reported that normal sleepers scored, M~= 4.6, SD = 2.8. Additionally, insomnia

complaints were positively correlated with the ESS. Scores greater than 7.3 were used as

evidence of a daytime functioning complaint. This cutoff was chosen, because it is 1 SD above

the reported mean for normal sleepers.

Fatigue severity scale (FSS)

The Fatigue Severity Scale (FSS; Krupp, LaRocca, Muir-Nash, & Steinberg, 1989)

consists of 9 items assessing the experience of fatigue in different aspects of living. Responses

range from 1 (strongly disagree) to 7 (strongly agree). Responses are averaged across the nine

items, yielding a possible score range of 1 to 7. While normative data on the FSS are limited,

Lichstein, Means, Noe, and Aguillard (1997) found individuals with insomnia seeking treatment

at a sleep disorders center averaged 6.0 (SD = 0.5) on the FSS. A complaint of daytime function

was supported by scores greater than 5.4. This cutoff was chosen, because it is 1 SD below the

reported mean for persons seeking treatment for insomnia.

Data Analysis

Specific Aim 1

The first specific aim is to investigate the relationship between napping behaviors and

sleep quantity.









Subaim 1.1a

To investigate the relationship between subj ectively measured napping behaviors

frequencys and durations as measured by sleep diaries) and objective sleep quantity as measured

by actigraphy (total sleep time, sleep onset latency, wake time after sleep onset, and sleep

efficiencyo.

Data analysis. A Canonical Correlation Analysis will be conducted to examine the

interrelationships among the two metric independent variables of subj ectively measured napping

frequencys and durations as measured by sleep diaries) and the multiple metric dependent

variables of sleep quantity as assessed by actigraphy (total sleep time, sleep onset latency, wake

time after sleep onset, and sleep efficiencyo.

A canonical correlation analysis was chosen because 1) the use of a multivariate analysis

such as canonical correlation analysis controls for the inflation of experimentwise error rates and

2) canonical correlation analysis allows for the derivation of an optimal linear combination

between a set of multiple independent variables and a set of multiple dependent variables (Afifl

and Clark, 1996). Considering that canonical correlation analysis is a large-sample method

potentially requiring 15 to 20 participants per measured variable (Barcikowshi & Stevens, 1975),

and considering the conceptual distinctions between obj ectively and subj ectively napping and

sleep, four separate analyses will be conducted for obj ectively and subj ectively measured

napping and obj ectively and subj ectively measured sleep.

Canonical correlation analysis is particularly suited for analyzing this aim in that it allows

for both an overall examination of the magnitude of the relationships that may exist between

napping and sleep and the measurement of the relative contribution of each variable to the

overall relationship between napping and sleep.









Subaim 1.1b

To investigate the relationship between subj ectively measured napping behaviors

frequencys and durations as measured by sleep diaries) and subjective sleep quantity as

measured by the sleep diaries (total sleep times, sleep onset latency, wake time after sleep onset,

and sleep efficiencys.

Data analysis. A Canonical Correlation Analysis will be conducted to examine the

interrelationships among the two metric independent variables of subj ectively measured napping

frequencys and durations as measured by sleep diaries) and the multiple metric dependent

variables of sleep quality as assessed by sleep diaries (total sleep times, sleep onset latency,

wake time after sleep onset, and sleep efficiencys.

Subaim 1.2a

To investigate the relationship between obj ectively measured napping behaviors

frequencyy, duration, and time of dayo as measured by actigraphy) and obj ective sleep quantity

as measured by actigraphy (total sleep time, sleep onset latency, wake time after sleep onset,

and sleep efficiencyo.

Data analysis. A Canonical Correlation Analysis will be conducted to examine the

interrelationships among the multiple metric independent variables of obj ectively measured

napping frequencyy, duration, and time of dayo as measured by actigraphy) and the multiple

metric dependent variables of sleep quantity as assessed by actigraphy (total sleep time, sleep

onset latency, wake time after sleep onset, and sleep efficiencyo.

Subaim 1.2b

To investigate the relationship between obj ectively measured napping behaviors

frequencyy, duration, and time of dayo as measured by actigraphy) and subj ective sleep quantity









as measured by the sleep diaries (total sleep times, wake time after sleep onset, total wake times,

and sleep efficiencys.

Data analysis. A Canonical Correlation Analysis will be conducted to examine the

interrelationships among the multiple metric independent variables of obj ectively measured

napping frequencyy, duration, and time of dayo as measured by actigraphy) and the multiple

metric dependent variables of sleep quantity as assessed by sleep diaries (total sleep times, sleep

onset latency, wake time after sleep onset, and sleep efficiencys.

Subaim 1.3a

To investigate the relationship between time of day of napping categories (day and evening

nappers versus daytime nappers) and obj ective sleep quantity as measured by actigraphy (total

sleep time, sleep onset latency, wake time after sleep onset, and sleep efficiencyo.

Data analysis. A Multivariate Analysis of Variance (MANOVA) will be conducted to

examine the differences between the two non-metric independent variables (daytime and evening

nappers and daytime nappers) in terms of the multiple metric dependent variables of obj ective

sleep quantity as measured by actigraphy (total sleep time, sleep onset latency, wake time after

sleep onset, and sleep efficiencyo.

Subaim 1.3b

To investigate the relationship between time of day of napping categories (day and evening

nappers versus daytime nappers) and subj ective sleep quantity as measured by the sleep diaries

(total sleep times, sleep onset latency, wake time after sleep onset, and sleep efficiencys.

Data analysis. A Multivariate Analysis of Variance (MANOVA) will be conducted to

examine the differences between the two non-metric independent variables (daytime and evening

nappers and daytime nappers) in terms of the multiple metric dependent variables of subj ective










sleep quantity as measured by the sleep diaries (total sleep times, sleep onset latency, wake time

after sleep onset, and sleep efficiencys.

Specific Aim 2

The second specific aim is to identify the differences between the four sleep subtypes

(noncomplaining good sleepers, complaining good sleepers, noncomplaining poor sleepers, and

complaining poor sleepers) in terms of their napping behavior (frequencyois, durationois, and time

of day of napping) as measured by actigraphy and sleep diaries.

Subaim 2.1a

Investigate the extent to which the four sleep subtypes (noncomplaining good sleepers,

complaining good sleepers, noncomplaining poor sleepers, and complaining poor sleepers) differ

in terms of their obj ectively measured napping behavior frequencyy, duration, and time of dayo

as measured by actigraphy).

Data analysis. A Multivariate Analysis of Variance (MANOVA) will be conducted to

examine the differences between the four nonmetric independent variables (noncomplaining

good sleepers, complaining good sleepers, noncomplaining poor sleepers, and complaining poor

sleepers) in terms of the multiple metric dependent variables of obj ectively measured napping

behavior frequencyy, duration, and time of dayo as measured by actigraphy).

Subaim 2.1b

Investigate the extent to which the four sleep subtypes (noncomplaining good sleepers,

complaining good sleepers, noncomplaining poor sleepers, and complaining poor sleepers) differ

in terms of their subj ectively measured napping behavior frequencys and durations as measured

by sleep diaries).

Data analysis. A Multivariate Analysis of Variance (MANOVA) will be conducted to

examine the differences between the four nonmetric independent variables (noncomplaining










good sleepers, complaining good sleepers, noncomplaining poor sleepers, and complaining poor

sleepers) in terms of the two metric dependent variables of subj ectively measured napping

behavior frequencys and durations as measured by sleep diaries).









CHAPTER 5
RESULTS

The main objective of the study was to examine the relationship between napping and

sleeping behavior in older adults. The main obj ective was achieved by examining napping

behavior in relation to 1) objectively and subj ectively measured sleep quantity and 2) in relation

to the four sleep subtypes. The two main obj ectives were achieved through specific aims and

associated subaims. The results will be discussed separately for each subaim. Descriptive

results of the characteristics of napping behavior of the sample are presented at the beginning of

the results section.

Characteristics of Napping Behavior within the Sample

Three separate napping variables (frequencyois, durationois, and time of dayo) were

collected during the study. Two of the napping variables (frequencyois and durationois) were

collected using both objective (actigraphy) and subjective (sleep diary) methods. The third

variable, time of dayo of napping, was collected using actigraphy. See Chapter 4 for operational

definitions of the variables. Three individuals were excluded from the following analyses

because they did not engage in naps during the course of the study.

In terms of napping frequency, individuals engaged, on average, in 12 naps over the 12

day period as measured by actigraphy (see Table 5-1 for means, ranges, and standard deviations

of the nap variables). In contrast, the participants self-reported napping (according to sleep

diaries) on average, four out of the 12 days. According to actigraphy, the maximum number of

naps recorded was 43 naps, indicating an average daily maximum of four naps. For the

subjective sleep diary data, the maximum number of naps reported over the 12-day period was

ten naps, with one nap per day as the maximum daily nap frequency.









The average nap duration recorded by actigraphy was 12 minutes and 26 seconds. The

average nap durations reported by sleep diary (indicating the average total daily nap duration)

was 18 minutes. The average nap duration recorded using actigraphy ranged from 0 to 17

minutes. The average nap durations reported by sleep diaries ranged from 0 to 152 minutes.

A paired samples t test was conducted to evaluate whether the frequency and duration of

naps reported by actigraphy and sleep diaries were significantly different. The results indicated

that the nap frequency as measured by actigraphy was significantly higher than the nap

frequency recorded using sleep diaries (t [99] = -8.11, p < .001, r12 = 0.40). Conversely, the nap

durations reported by sleep diaries was significantly longer than the nap durations recorded using

actigraphy (t [97] = -2.58, p < .05, r12 = 0.06).

In terms of the time of day of napping, the peak time of day of naps (the mode nap time of

day for all naps of all participants) recorded by actigraphy occurred between 20:30 and 21:00

p.m. (see Figure 5-1 for the time of day of all naps). The average time of day of naps was

between 14:30 and 15:00. Forty-seven percent of all of the naps occurred after 6 p.m. Fifty-

eight percent of the sample engaged in an evening nap (a nap that occurred within two hours of

bedtime) and 85% engaged in a daytime nap. All the participants who engaged in an evening

nap, on average, also napped during the day.

Specific Aim 1

The first specific aim was to investigate the relationship between napping behaviors and

sleep quantity.

Subjective Napping and Objective Sleep (Subaim 1.1a)

A canonical correlation analysis was conducted with subj ectively measured napping

behaviors frequencys and durations as measured by sleep diary) as the independent variable set

and objective sleep quantity as measured by actigraphy (total sleep time, sleep onset latency,









wake time after sleep onset, and sleep efficiencyo) as the dependent variable set. Of the two

possible pairs of canonical variates, the first canonical correlation was statistically significant

(Wilk's A = .78, p < .01). The canonical correlation was .46 and accounted for 21% of the

variance in the pair of variates. Table 5-1 shows the canonical coefficients and the structure

correlations for the napping and sleep variables. According to a cutoff correlation of .35 for

interpretation (Tabachnik & Fidell, 1989), nap durations, frequency, total sleep time, and sleep

efficiencyo were the variables that contributed the most to the canonical variate. Individuals who

engaged in a shorter nap duration and a smaller number of naps as measured by sleep diaries

experienced longer total sleep time and a higher sleep efficiency as measured by actigraphy.

Subjective Napping and Subjective Sleep (Subaim 1.1b)

As in subaim 1.1a, a canonical correlation analysis was conducted to investigate subaim

1.1b. The independent variable set consisted of the subjectively measured napping behaviors

frequencys and durations as measured by sleep diaries) and the dependent variable set consisted

of the subj ective sleep quantity variables (total sleep times, sleep onset latency, wake time after

sleep onset, and sleep efficiency) as measured by the sleep diaries. The first canonical

correlation of 0.42 was significant (Wilk' s A = .80, p < .01) and accounted for 18% of the

variance in the pair of variates. Nap frequency, durations, and total sleep times contributed most

to the canonical variate (Table 5-2). The greater the number of naps and the longer the duration

of naps, the shorter the total sleep times.

Objective Napping and Objective Sleep (Subaim 1.2a)

A canonical correlation analysis was conducted with obj ectively measured napping

behaviors frequencyy, duration, and time of dayo as measured by actigraphy) as the independent

variable set and objective sleep quantity as measured by actigraphy (total sleep time, sleep onset

latency, wake time after sleep onset, and sleep efficiency) as the dependent variable set.









Obj ectively measured napping behaviors were not found to be significantly related to obj ectively

measured sleep quantity (Wilk's A= .88, p > .05).

Objective Napping and Subjective Sleep (Subaim 1.2b)

A canonical correlation analysis was conducted to examine the relationship between the set

of independent variables (obj ectively measured napping behaviors frequency, duration, and

time of dayo as measured by actigraphy) and the set of dependent variables (total sleep times,

sleep onset latency, wake time after sleep onset, and sleep efficiency as measured by sleep

diaries). Obj ectively measured napping behaviors were not found to be significantly related to

subjectively measured sleep quantity (Wilk's A = .92, p > .05).

Nap Categories: Day and Evening Nappers versus Daytime Nappers (Subaim 1.3a)

Based on a distribution within the sample of 58% of the participants engaging in both a

daytime and evening nap, and 27% of the sample engaging solely in daytime naps, the

participants were divided into two groups: 1) day and evening nappers and 2) daytime nappers.

A comparison involving participants who solely napped during the evening was not conducted as

all of the participants who engaged in an evening nap also napped during the day.

A 2 (time of day of nap group) x 4 (obj ectively measured sleep quantity) MANOVA was

performed to examine differences in objectively measured sleep among the two nap groups. A

MANOVA, as opposed to a univariate analysis of variance, was employed in the study since it

adequately controls for the experimentwise error rate and takes into account the correlations

among the dependent variables (Stevens, 1986). Separate MANOVAs were performed for each

of the subaims as is recommended when the outcome variables are conceptually clustered

(Stevens, 1986).

There was a significant main effect for the nap groups [Wilk's A = .81, F(4, 77) = 4.82, p

< .01, '12 = 0. 19]. For the size of the effect, eta-square is roughly equivalent to the R2 USed in









multiple regression (Grimm & Yarnold, 1995). According to Cohen (1977), for effect sizes

measured via R2 Of Similar indices, an effect size of .09 is considered medium and an effect size

of .25 or greater is considered large. Therefore, the eta-square of 0. 19 suggests a medium main-

effect for nap groups.

Univariate tests revealed significant differences for sleep onset latency [F (1, 80) = 4.37, p

< .05, '12 = 0.05], wake time after sleep onset [F (1, 80) = 14.27, p < .001, r12 = 0. 15], and sleep

efficiencyo [F (1, 80) = 12.01, p < .01, r12 = 0.13], see Table 5-3 for means and standard

deviations. Individuals who napped in the daytime and the evening had significantly less sleep

onset latency (21 minutes), less wake time after sleep onset (7 minutes), and greater sleep

efficiency (5%) as measured by actigraphy compared to those who only napped during the

daytime. The size of the effect for the univariate tests ranged from small (for sleep onset

latency) to medium (for wake time after sleep onset and for sleep efficiency).

Nap Categories: Day and Evening Nappers versus Daytime Nappers (Subaim 1.3b)

A 2 (time of day of nap group) x 4 (subj ectively measured sleep quantity) MANOVA was

performed to examine differences in subj ectively measured sleep among the two nap groups.

There was not a significant main effect for the nap groups [Wilk' s A = .93, F(12, 222.535) =

0.50, p > .05, r12 = 0.25]. This result indicates that there was not a significant difference between

the two nap groups (evening and daytime and daytime nappers) in terms of their subj ective sleep

quantity (see Table 5-4 for means and standard deviations).

Specific Aim 2

The second specific aim was to identify the differences between the four sleep subtypes

(noncomplaining good sleepers, complaining good sleepers, noncomplaining poor sleepers, and

complaining poor sleepers) in terms of their napping behavior.









Sleep Subtypes and Objective Napping (Subaim 2.1a)

A 4 (sleep subtype) x 3 frequencyy, duration, and time of dayo ) MANOVA was

performed to examine differences in obj ectively measured napping behavior among the four

sleep subtypes. The multivariate main effect was non-significant [Wilk' s A = .93, F(9, 228.92)

=.78, p > .05, r12 = 0.02] indicating that the four sleep subtypes do not differ in terms of the

frequency, duration, and time of dayo of napping as measured by actigraphy.

Sleep Subtypes and Subjective Napping (Subaim 2.1b)

A 4 (sleep subtype) x 2 (subj ectively measured napping behavior) MANOVA was

performed to examine differences in subj ectively measured napping behavior among the four

sleep subtypes. The multivariate effect was non-significant [Wilk's A = .97, F(6, 186) = .43, p >

.05, '12 = 0.01] indicating that the four sleep subtypes do not significantly differ in terms of the

frequency and durations of their naps as measured by sleep diaries.









Table 5-1. Mean nap frequency, duration, and time of day as measured by actigraphy and sleep
diaries
Minimum Maximum
Nap variable MSD value value

Nap frequencyoa 11.71 9.21 0 43.00
Nap frequencysa 4.26 3.31 0 10.00
Nap durationob 12.44 1.96 0 17.00
Nap durationsb 18.11 21.91 0 152.14
Time of day of napso 0.62 9.87E-02 .33 .95
aFrequency refers to the total number of naps summed over 12 days
bDuration refers to the average nap length
























O 4-




O
1




o



Tieo ay(4hurcok

Fiue51 ecnaeo oa astknb l priiat htocre uigec afhu
inevlo h 2-orcok










Table 5-2. Correlations of sleep diary napping, actigraphy
with the canonical variate
Napping and sleep
Variable (subaim 1.1a)
Canonical Canonical
structure coefficient
coefficient


sleep, and sleep diary sleep variables


Napping and sleeps
(subaim 1.1b)
Canonical Canonical
structure coefficient
coefficient


Sleep Diary Napping
frequency
durations

Sleep Diary Sleep
total sleep times
sleep onset latency
wake time after sleep
onsets
sleep efficiency


-.72
-1.00


-.00
-1.00


.79
.99


-.89
.07
.15


.16
.88


-1.33
.34
.33

1.10


Actinraphy Sleep
total sleep time .98 .72
sleep onset latency -.28 .12
wake time after sleep .07 .55
onset
sleep efficiency .49 .59
Note. Structure coefficients for aim 1.2a and 1.2b are omitted from this table because the
canonical variate was not significant.
Subscript 's' denotes subjectively measured variables and subscript 'o' denotes objectively
measured variables.











Table 5-3. Means and standard deviations for the time of day of nap groups for obj ective sleep
Actigraphy sleep variables
SOL WASO SE TST (minutes)


Group M SD
Daytime naps 26.50* 13.01
Daytime and 20.00* 12.28
evening naps

*p < .05. **p < .01. ***p < .001


SD
24.65
21.99


M SD
382 43.04
393 58.71


M
72.82***
51.43***


M
76.80**
81.95**










Table 5-4. Means and standard deviations for the time of day of nap groups for subj ective sleep
Sleep Diary sleep variables
SOL WASO SE TST (minutes)

Group M SD M SD M SD M SD
Daytime naps 25.61 16.74 25.19 23.50 86.05 6.65 430 46.89
Daytime and 23.92 19.73 28.72 26.28 84.97 9.43 408 69.02
evening naps









CHAPTER 6
DISCUSSION

The main focus of the study was to examine the relationship between subj ectively and

obj ectively measured napping and sleeping behavior in a sample of community-dwelling older

adults. Although a number of previous studies have examined this relationship, the association

between napping and sleep remains unspecified. The present study sought to further define the

relationship between napping and sleep by addressing several methodological limitations of the

previous research. These limitations were addressed through the introduction of several

innovations including: 1) the use of both subj ective and obj ective measures of nap and sleep

behavior, 2) capturing the inherent variability in sleep and napping behavior with an extended

data collection period, 3) examining multiple aspects of napping behavior (frequency, duration,

and time of day), and 4) using a classification of sleep subtypes, studying napping behavior

simultaneously in both healthy individuals and those diagnosed with insomnia. The goal of the

study was to further specify the relationship between napping and sleep through the use of the

abovementioned innovations.

A common theme that emerged during the study was the complexity of the relationship

between objectively and subjectively measured variables. Both objective (actigraphy) and

subjective (sleep diary) measures were employed for the napping and sleep variables. The

multiple subaims of the study allowed for various combinations of the subj ective and obj ective

variables. Depending on the mode of study (objective or subjective), napping had a differential

association with nocturnal sleep. The results suggest that the relationship between napping and

sleep may be moderated by the mode of measurement.

The differential results associated with obj ective and subj ective measurement illustrate the

differences between perceptions and obj ective assessment of sleep previously reported in the









literature. Poor sleepers have both underreported (Lichstein and Johnson, 1991) and

overestimated (Morin, 1993) their sleep problems in comparison to PSG results. The fact that

poor sleepers can inaccurately estimate their sleep problems suggests that the lack of correlation

between obj ective and self-report measures may be due to an information processing issue rather

than motivational factors (i.e. overestimating wake time in order to portray a severe sleep

problem; Lichstein and Morin, 2000). The distinction between the perception and obj ective

assessment of sleep is further illustrated by the diagnostic entity of 'sleep state misperception'

(American Sleep Disorders, 1997). This diagnosis, as represented by the sleep subtype group of

complaining good sleepers, involves complaints of insomnia without obj ective evidence of sleep

problems. The existence of a condition such as sleep state misperception suggests that the

experience of insomnia is affected both by perceptions of and the existence of obj ectively

measured poor sleep. In fact, it has been suggested that unlike asymptomatic diseases such as

hypertension which require tests for verification, it is the complaint aspect of insomnia that is of

interest to researchers and clinicians (Lichstein and Morin, 2000). The results from this study

replicate previous results on the differences between subj ective and obj ective assessment of sleep

and extend the Hield of research to include differences in the subj ective and obj ective assessment

of napping.

The Einal chapter is organized into four maj or sections. First the results will be reviewed

and interpreted for each of the study's specific aims. Second, the limitations of the study will be

considered. Third, the theoretical and clinical implications of the study will be presented.

Finally, future research directions stemming from the Eindings of the study will be proposed.

Review of Study Findings

The main objective of the study was to examine the relationship between napping and

sleep in a sample of community-dwelling older adults. This obj ective was achieved through the










analysis of obj ective (actigraphy) and subjective (sleep diary) measures of napping and sleep.

The Eindings are discussed in terms of the two broader aims of the study and the associated

subaims. In addition, descriptive analyses of the characteristic napping behavior of the sample

are discussed.

Characteristics of Napping Behavior within the Sample

In order to interpret further analyses of napping behavior, it is helpful to Birst describe the

characteristics of the naps taken by the sample. These characteristics were collected using both

subj ective and obj ective methods. For the obj ective assessment of napping, the participants,

engaged in, on average, one nap per day (nap frequency), with an average nap duration of

approximately 12 minutes. While the peak time of day for naps for the sample was between 8:30

and 9:00 p.m., the average time of day of naps was between 2:30 and 3:00 p.m. For the

subjective assessment of napping, the participants self-reported napping on average 4 out of the

12 days of assessment (nap frequency). The average self-reported nap duration was 18 minutes.

Interestingly, there were significant differences between the subj ective and obj ective

measures of nap frequency and duration. A greater average frequency of napping was identified

by actigraphy while a greater average duration of napping was reported by sleep diaries. The

time of day of naps could not be compared across subj ective and obj ective data as only obj ective

data was collected.

In terms of nap frequency, the subj ectively reported average nap frequency of 4 naps over

a twelve day period is consistent with previously reported results (Buysee et al., 1992). The

frequency of naps recorded using actigraphy (12 over a 12 day period) is considerably higher

than previously reported results. A possible explanation for the significantly higher frequency of

naps assessed by actigraphy is that actigraphy may be capturing a greater number of evening

naps than sleep diary. Yoon and colleagues (2003a) found only 22.6% of evening nappers










reported their evening naps in their sleep diaries. Additionally, large discrepancies in napping

have been found between sleep diaries and PSG recordings (Jean-Louis, 2000). Corroborating

these studies are anecdotal evidence from our participants suggesting that they tend not to record

brief evening naps as a 'nap' on their sleep diary.

Additionally, the lack of elevated nap frequencies in previous studies may be due to the

fact evening nap frequencies were not reported by the researchers (Yoon et al., 2003a; Yoon et

al., 2003b; Yoon et al., 2004). If this data had been reported, elevated frequencies such as those

captured in the present study may have been observed.

In terms of nap duration, previous studies have reported average nap durations ranging

from 23.3 to 45 minutes per day (Jean-Louis et al., 2000; Shirota et al., 2002; Yoon et al., 2003a;

Yoon et al., 2004). The average nap durations reported both by objective and subjective

measures in this study are comparatively lower than previously reported results. An explanation

for the much lower obj ectively measured average nap duration (12 minutes) is that the inclusion

of evening naps (typically of shorter duration than daytime naps; Ancoli-Israel, 1985; Yoon,

2004;) would decrease the mean duration. While the sleep diary nap duration (18 minutes) is

less than previously reported averages, it is still comparable to the lower range of average

durations reported in the literature review (23.5 minutes). It is important to note that the

subjective and objective duration variables were measuring different constructs. While duration

as measured by actigraphy recorded the average duration for individual naps, durations as

measured by sleep diaries reported the average daily duration for naps.

The final nap variable that was measured was time of day of napping. Both an average

time of day of naps (between 2:30 and 3:00 p.m.) and an alternate measure of time of day, the

peak time of day of naps, were calculated. The peak time of day of naps (a calculation of the









mode nap time of day for all naps of all participants) occurred between 8:30 and 9:00 p.m. This

is consistent with previous studies that have found the evening to be the most characteristic time

of day of napping for older samples (Ancoli-Isreal et al., 1985; Jean-Louis et al., 2000; Yoon et

al., 2003a, 2004). Therefore, this study replicates previous findings indicating evening naps are

prevalent in older adults.

Several theoretical explanations for the large number of evening naps within the sample

exist. First, napping during the evening may represent an advance in circadian rhythms in older

adults. Some older adults experience a 'phase advance' resulting in earlier bedtimes and earlier

waketimes (Van Cauter, Leproult, & Kupfer, 1996; Van Coevorden et al., 1991; Yoon et al.,

2003a). Therefore, out-of-bed sleep in the evening could represent the start of the nocturnal

sleep period for some older adults.

An alternate explanation is that napping during the evening may represent a weakening of

the alerting signal from the suprachiasmatic nucleus (Yoon et al., 2004). The suprachiasmatic

nucleus is involved in generating a 24-hour rhythm for several bodily functions, including sleep.

Action potentials within the suprachiasmatic nucleus fire in a 24-hour rhythm and reach a

maximum firing at mid-day and then fall again at night. It is possible that evening naps could

result from a premature drop in the firing of action potentials within the suprachiasmatic nucleus.

As a result, evening naps may occur because the altertness of the individual is being

insufficiently maintained. Finally, it is possible that increased evening naps within the sample

could reflect greater sleep needs or trait sleepiness.

Each of these theoretical explanations for the prevalence of evening naps among the

sample have different implications for nocturnal sleep. If the individual is experiencing a phase

advance, napping in the evening could meet some of their nocturnal sleep need and may be









reflected in an earlier wake time and/or greater wake time after sleep onset. Similarly, if the

individual naps during the evening due to a decrease in alertness, the sleep may meet some of

their nocturnal sleep need and result in greater wake time after sleep onset and/or earlier wake

times. Alternatively, if evening naps are resulting from greater sleep needs or trait sleepiness, by

napping during the evening the individual could meet some of their sleep need without

compromising their nocturnal sleep quality. Each of these explanations, or combinations of the

explanations, could be implicated in the association between napping and sleep reflecting the

complexity of the relationship between napping and sleep behavior.

Subjective Napping and Objective Sleep (Subaim 1.1a)

Individuals who engaged in naps of shorter duration and engaged in naps less frequently

had greater total sleep time and a higher sleep efficiency. Greater total sleep time and higher

sleep efficiency are both indicative of improved nocturnal sleep quantity.

This result is consistent with the hypothesis that subj ective napping variables frequencys

and durations) would be most strongly correlated with the sleep quantity variable of total time

spent asleep. The hypothesis was non-directional because previous findings indicated that

napping duration and frequency were both positively and negatively associated with nocturnal

sleep. The current result supports the portion of prior findings that found higher frequencies

(Hays et al., 1996; Monk, 2001) and longer duration (Beh, 1994) of napping are associated with

an increased risk of sleep complaint. Within the present sample the negative relationship

between napping and sleep was replicated. Decreased napping (frequency and duration) was

correlated with increased sleep quantity (total sleep time and sleep efficiency)

Interestingly, the objective sleep variable of sleep efficiency was found to be significantly

related to the napping variables. Although this relationship was not accounted for in the

hypothesis, the association makes sense conceptually. Sleep efficiency consists of a ratio of total









time spent asleep to total time spent in bed. Considering that an increase in total sleep time was

associated with a decrease in napping duration and frequency, it follows that sleep efficiency

(which is composed in part from total sleep time) would also be implicated in the relationship

between napping and sleep.

Subjective Napping and Subjective Sleep (Subaim 1.1b)

As the frequency and duration of naps increased, the total sleep time decreased. This result

suggests that worse nocturnal sleep quantity as measured by sleep diaries is associated with

increased napping (frequency and duration) as measured by sleep diaries. This result is

consistent with the hypothesis that the napping variables frequencys and durations) would be

most strongly correlated with total sleep time. Additionally, the negative association between

napping behaviors and nocturnal sleep demonstrated by this aim is consistent with previous

research (Beh, 1994; Hays et al., 1996; Monk, 2001).

Interestingly, the napping variables were not significantly associated with subj ectively

measured sleep efficiency, but were associated with obj ectively measured sleep efficiency.

Using the same sample, McCrae and colleagues (2005) found that subj ective measures of sleep

efficiency were not significantly correlated with objective measures of sleep efficiency. The

differences in the canonical variates derived for subj ective napping and obj ective and subj ective

sleep may be the result of the differences between obj ectively measured and self-reported sleep.

Objective Napping and Objective Sleep (Subaim 1.2a)

While subj ectively measured napping was found to be significantly correlated with both

obj ective and subj ective sleep quantity, there was no significant relationship between the

objective napping variables and objective sleep quantity. This result is contrary to our

hypothesis. While the direction of the relationship between napping and sleep was not predicted,

it was hypothesized that such a relationship would exist. The lack of a relationship is consistent









with previous findings that have shown nap frequency (Bliwise, 1992; Buysee et al., 1992;

Morin et al., 1989), duration (Aber & Webb, 1986), and both nap frequency and duration

(Johnston, Landis, Lentz, & Shaver, 2001; Morgan, Healey, & Healey, 1989; Morin & Gramling,

1989) failed to differentiate between good and poor sleepers.

Two likely explanations exist for the lack of relationship between obj ective napping and

sleep. First, it is possible that the lack of significant interrelationships between these variables

reflects a genuine lack of relationship between obj ectively measured daytime napping variables

and objective sleep. As previous research has shown, several studies have failed to detect a

relationship between napping and sleep. An alternative explanation is that actigraphy, with the

use of a novel application for analyzing napping, is not a reliable measure of napping behavior.

This methodological concern will be discussed further under the limitations portion of the

discussion.

Objective Napping and Subjective Sleep (Subaim 1.2b)

Similar to the relationship between objective napping and objective sleep, obj ectively

measured napping was found to be unrelated to subjectively measured sleep. This result is

inconsistent with the hypothesis that obj ectively measured napping would be significantly

associated with subj ectively measured total sleep time. This result is consistent with a number of

studies that have failed to find a significant relationship between napping and sleep (Bliwise,

1992; Buysee et al., 1992; Morin et al., 1989; Aber & Webb, 1986; Johnston, Landis, Lentz, &

Shaver, 2001; Morgan, Healey, & Healey, 1989; Morin & Gramling, 1989). As suggested

obj ective napping and obj ective sleep, the lack of findings may reflect a genuine lack of

relationship between obj ectively measured napping and sleep, or may be due to a methodological

limitation associated with the use of actigraphy to assess napping behavior. It is problematic to

make the assertion that napping is or is not associated with nocturnal sleep. The presence or









absence of a relationship between napping and sleep appears to vary depending on the

methodology of assessment used. The difference in the relationship between subj ective and

obj ective napping and sleep is further reinforced by the fact that while all of the subj ective nap

variables were significant, none of the obj ective nap variables were.

Nap Categories: Day and Evening Nappers versus Daytime Nappers (Subaim 1.3a)

Considering the difficulty in capturing variable napping behavior with a single average

time of day of naps variable, a categorical measurement was used in addition to the analysis of a

continuous measurement of time of day. Individuals were divided into two groups those who

napped during the daytime and those who napped during the daytime and evening.

There was a significant difference found between those who napped during the day and

those who napped both during the day and evening in terms of their obj ective sleep quantity.

Essentially, those who napped during both the day and evening had significantly less wake time

during the night. On average, day and evening nappers fell asleep 21 minutes faster than day

nappers and were awake for seven less minutes during the night. Additionally, day and evening

nappers had higher average sleep efficiencies (5% higher) compared to day nappers. The

reduced wake time during the night for those who napped during the day and evening suggests

that these individuals had greater consolidation of nocturnal sleep compared to day nappers.

This result is consistent with the hypothesis that obj ective napping would be significantly

associated with obj ective sleep. This result differs from those that were obtained for subaims

1.1a and 1.1b in that increases of the napping variable (naps that occurred both in the day and

evening) was associated with improved sleep whereas the earlier results suggested the opposite.

This result also conflicts with conventional sleep hygiene recommendations that suggest

individuals avoid napping altogether or restrict naps to before noon (Lichstein & Morin, 2000).

The positive association between napping and sleep is consistent with previous literature









(Arakawa et al., 2002; Buysee et al., 1992; Foely et al., 1995; Tanaka et al., 2002). This result is

innovative in that for the first time nappers were divided into groups based on the portion of the

day (am/pm) that the naps occurred. Furthermore, the results are clinically significant in addition

to being statistically significant. A decrease in the average time to fall asleep of 21 minutes and

an increase in sleep efficiency of 5% can have clinical significance for elderly sleepers. An

average wake time after sleep onset of greater than 3 1 minutes can result in a diagnosis of

insomnia. Therefore, a decrease in sleep onset latency of21 minutes could have a significant

impact on an individual's sleep.

Possible interpretations of this finding are 1) older adults who engaged in both daytime and

evening naps do experience better obj ectively measured nocturnal sleep and 2) the individuals

who comprised the day and evening nap group may have greater sleep needs or trait sleepiness.

Interestingly, obj ectively measured napping was not significantly related to obj ective or

subjective sleep when it was analyzed as a continuous variable. The categorical approach to

analyzing time of day of napping used in this subaim may more accurately capture the

differential association between time of day of napping and sleep.

Nap Categories: Day and Evening Nappers versus Daytime Nappers (Subaim 1.3b)

There was no significant difference between the day and evening and the day nap groups in

terms of their subj ective sleep. This result is not consistent with the hypothesis that napping

would be significantly (positively or negatively) associated with sleep. While a lack of

relationship between napping and sleep has been reported in previous studies (Bliwise, 1992;

Buysee et al., 1992; Morin et al., 1989; Aber & Webb, 1986; Johnston, Landis, Lentz, & Shaver,

2001; Morgan, Healey, & Healey, 1989; Morin & Gramling, 1989), this result is surprising

considering the significant association found in subaim 1.3a.









Four Sleep Subtypes (Specific Aim 2)

The second specific aim involved identifying the differences between the four sleep

subtypes (noncomplaining good sleepers, complaining good sleepers, noncomplaining poor

sleepers, and complaining poor sleepers) in terms of their napping behavior (frequencyois,

durationois, and time of day of napping) as measured by actigraphy and sleep diaries.

The four sleep subtypes did not differ in terms of the frequencyois, durationois, and time of

day of napping. This aim was exploratory in that the four sleep subtypes had not previously

been studied in relation to napping behavior. Hence, an association between the sleep subtypes

and the nap variables was not hypothesized.

This aim allowed for the examination of a sleep classification system (McCrae et al., 2005)

in relation to napping. The sleep subtypes are unique in that they classify individuals based on

both subj ective quantitative and qualitative estimates of sleep. The results suggest that regardless

of whether poor sleep is based on qualitative estimates of sleep (complaining good sleepers), or

quantitative estimates of sleep (noncomplaining good sleepers), these different experiences of

insomnia are not differentially associated with the frequency, duration, or time of day of naps.

Study Limitations

Limitations of the present study include restricted generalizability of results, an inability to

determine the direction of the association between napping and sleep, and methodological

concerns. The use of a convenience sample restricted the diversity of the sample. The

participants were primarily European Caucasian, college educated, and resided in their own

homes. The homogeneity of the sample prevents reliable generalization to a diverse population.

Additionally, individuals were excluded from the study if they presented with sleep disorders

other than insomnia (e.g. sleep apnea, periodic leg movements). Approximately one half of the

elderly population experience one or both of these conditions (Ancoli-Israel, Kripke, Mason, &









Kaplan, 1985). Previous research has examined the relationship between napping and

respiration. Carskadon and colleagues (1982) have found an association between nocturnal

breathing disturbances and the degree of daytime sleepiness. Buysee and colleagues (1992)

found no main effect of napping frequency on an index for sleep apnea (AHI) or for periodic

limb movements. Unfortunately, the relationship between breathing disorders or periodic limb

movements and napping could not be explored in the current study as individuals with these

conditions were excluded from participating in the study. Consequently, the results of the

current study cannot be extended to a significant portion of the population diagnosed with other

sleep complaints.

Because the observations in the current study are derived from cross-sectional data it is

impossible to make any causal conclusions about the relationship between napping and sleep.

Although there are underlying biological mechanisms to explain the relationship between

napping and sleep (circadian rhythm and homeostatic drive), these mechanisms may work bi-

directionally. Hence, although significant relationships between napping and sleep were

observed, we cannot determine if this relationship is unidirectional (napping impacts sleep, sleep

impacts napping) or bi-directional (napping and sleep both impact each other).

Finally, noticeable differences in the relationship between napping and sleep were

observed depending on the methodology used to study napping. While these differences may

accurately reflect the relationship between napping and sleep, it is also possible that the observed

differences may in part be due to methodological limitations of the napping measures. Two

measures (obj ective and subj ective) were employed in the study. Strengths and weaknesses were

associated with each measure. While actigraphy provides a sensitive measure of the individual

napping behavior of each participant, it is a novel approach that has not previously been applied









to the study of napping behavior. Consequently, a limitation of the study is the use of a measure

that has limited reliability data. Additionally, while many precautions were taken to prevent the

misidentifieation of 'watch-off' periods as napping, it is possible that there were modest

inaccuracies in the differentiation of wake/sleep periods. There are also limitations associated

with the use of sleep diaries to assess napping behavior. Although sleep diaries are traditionally

used to measure napping behavior, they have limited utility for assessing duration of napping and

frequently, do not assess time of day of napping, and result in the underreporting of evening

naps.

Implications

Implications for Theory and Research

A maj or implication for future research on napping and sleep involves the mode of

measurement employed. This study was the first to compare multiple variables of napping and

sleep using both subjective and objective measures. Accordingly, there were significant

differences in the relationship between the constructs of napping and sleep depending on the

mode of measurement (obj ective and subj ective). The Eindings show that the study of the

relationship between napping and sleep is further complicated by the methodology used. It

would be helpful for future research to make a point of explicitly describing the methodology

used and to recognize the strengths and weaknesses associated with each alternative.

Clinical Implications

In addition to exploring the theoretical association between napping and sleep, there are

clinical implications for further defining this relationship. The services provided by health care

professionals are beginning to reflect the changing U.S. demographics. Currently, 68% of

psychologists provide services to older adults (Qualls, Segal, Norman, Niederehe, & Gallagher-

Thompson, 2002). The existing number of psychologists providing services to older adults will









need to more than double to meet the growing demands of the aging population (Gatz & Finkel,

1995). In order to effectively assess and treat older adults, clinicians will need to understand the

age-related changes (e.g. difficulty sleeping) that impact this population.

Considering the prevalence of insomnia among older adults (15 65%), there is a need to

develop and implement treatments that target this disorder. Cognitive-behavioral treatments

(CBT) are often employed to target insomnia in older adults. The restriction or elimination of

napping b ehavi or i s a common element of the sleep hygi ene component of cognitive-b ehavi oral

treatments (CBT) for insomnia (Lichstein & Morin, 2000). Interestingly, the empirical basis for

this treatment recommendation is unclear. The results from the present study suggest that the

relationship between napping and sleep varies and a uniform recommendation to

restrict/eliminate napping may not meet the needs of older adults with insomnia. Additionally,

there are implications for the selection of measures to assess napping behavior. The results

suggest that differential relationships between the client' s napping behavior and sleep could be

revealed depending on the mode of measurement (subj ective or obj ective).

Future Directions

The results of the present study provide many potential directions for future research.

First, considering the role that methodology played in the study of napping and sleep, future

research is needed in order to establish reliability data for both obj ective and subj ective measures

of napping. Second, future research could further define the relationship between napping and

sleep by examining the intraindividual variability of napping and sleep data. It is possible that

there are individual differences in the relationship between napping and sleep and these

individual differences may explain the lack of consensus in the field regarding the relationship

between daytime naps and sleep. Third, it would be helpful to examine the role of cognitions as

a possible mediator of the relationship between napping and sleep. There are differing opinions









as to the costs/benefits associated with daytime napping. Additionally, cultural issues play a role

(e.g. the siesta nap is considered a necessity in some cultures). A considerable amount of

research has examined the role of cognitions in exacerbating insomnia among older adults. It

would be helpful to extend this body of research by examining the role of cognitions about

napping and the subsequent impact of these cognitions on nocturnal sleep.

Conclusions

This study enabled the examination of the relationship between napping and sleeping

behaviors in a sample of community-dwelling older adults. Not unlike previous research, the

findings from this study were mixed regarding the relationship between napping and sleep.

Depending on the mode of measurement employed (subj ective or obj ective) napping was found

to be associated with impaired nocturnal sleep, improved nocturnal sleep, and found to be

unrelated to nocturnal sleep. Additionally, the prevalence of evening naps within samples of

older adults was replicated in the current study. A strength of the study was the unobtrusive

assessment of the elderly participants within their home environment. The use of actigraphy as

opposed to PSG preserved the ecological validity of the study by allowing participants to engage

in their typical activities while participating in the study.










APPENDIX A
EXAMPLE OF SLEEP DIARY

BASELINE TX POST-TX


FOLLOW-UP


Please answer the following questionnaire WHEN YOU AWAKE IN THE MORNING. Enter yesterday's day
and date and provide the information to describe your sleep the night before. Definitions explaining each line of the
questionnaire are given below.

EXAMPLE
yesterday's day TUES
yesterday's date 10/14/97


day 1 day 2 day 3 day 4 day 5 day 6 day 7


1. NAP (yesterday) 70

2. BEDTIME (last night) 10:55

3. TIME TO FALL 65
ASLEEP
4. # AWAKENINGS 4

5. WAKE TIME (middle of 110
night)
6. FINAL WAKE-UP 6:05

7. OUT OF BED 7:10


8. QUALITY RATING* 2

9. BEDTIME Halcion

MEDICATION 0.25 mg

(include amount & time) 10:40 pm




*Pick one number below to indicate your overall QUALITY RATING or satisfaction with your sleep.

1. very poor, 2. poor, 3. fair, 4. good, 5. excellent

Figure A-1. Sleep Diary (Lichstein, Riedel, & Means, 1999) used during the study.












APPENDIX B
HEALTH SURVEY




FilAL 1Hi 511lh t

Please PRINT and Yunnly ALL Information

ID#: ___ eight Weight



1. Do you hav a sleepproblem? yes or no
If yes~, deanset Ir e mtrnubi AIjng adeepC. awgr or frequent aakenings. sleep~ apneay:



If yes. on average, how many nights per week do you have this problem?

Howr lonrr hase ?cou had thes sleep probism? _~ eas_ months

2. Please: islicare wherber you or yur bed partner have notced any of the following:
Ar youl a heavy snorer? yes no
Do you have diffcu~ly breathing or gasp for breath during sleep? yes as~
Do your togs jcrk frequently during sleep or d they Fool restless before sleep onset? yes no
Do you hav sleep antacks during the day or paralysis as skcep onset? yes no
If yes to any- of the questions under #2, please explain and indicate how often symPtomsr occur:




3. Indicate with a check mark if you hate ah fo llow ing health problems. andl put the IIumber2 of years you'v had each problem:
In.Yeam

Elearrdisease
Cancer
AIDS
High blood pressure
Neurological disease (ex: seizures, Parkinson's)
Breathing Problems (e: asthma, emphysema)
Ulriniary problems (ex- kidney disease, prostate problems)
Diabetles
Chronic Pain (ex: arthritis, back pain, migraines)
Grastraintestinal (ex: stomach, irritable b~owls, ulcers)
4. Please list any mental health disorders you have and the number of years you've had the disorrderls)




5. Lis I ny oIber health probhlems von hale land the number of ers~ sou've had the problm).


6. Medical and mental health disorders may disrupt sleep. Medicatica may also disturb sleep. Please list ny-
disorder or mnedication that affects yorm sleep and describe how it affects sleep,










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BIOGRAPHICAL SKETCH

Natalie Dautovich obtained her Bachelor of Arts degree with distinction at the University

of Alberta in Edmonton, Alberta, Canada. She is currently enrolled in the doctoral program in

counseling psychology through the Department of Psychology at the University of Florida. She

is a member of the Sleep Research Lab.





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1 NAPPING AND SLEEP: AN ACTIGRAP HIC STUDY OF A SAMPLE OF COMMUNITY DWELLING OLDER ADULTS By NATALIE DEIDRE DAUTOVICH A THESIS PRESENTED TO THE GRADUATE SCHOOL OF THE UNIVERSITY OF FLOR IDA IN PARTIAL FULFILLMENT OF THE REQUIREMENTS FOR THE DEGREE OF MASTER OF SCIENCE UNIVERSITY OF FLORIDA 2007

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2 2007 Natalie Dautovich

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3 ACKNOWLEDGMENTS I would like to acknowledge my mentor, Dr. Christina McCr ae, for her support throughout the completion of the project. Additionally, I wo uld like to thank both Dr. Christina McCrae and Dr. Meredeth Rowe for the generous use of thei r database and their guida nce. I would like to thank my parents, Mike and Angella Dautovich, and my sist er, Sonia Dautovich, for their ongoing support, encouragement, and belief in my ab ility to complete this project. Finally, I would like to especially acknowledge the emotional support from David Sams.

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4 TABLE OF CONTENTS page ACKNOWLEDGMENTS...............................................................................................................3 LIST OF TABLES................................................................................................................. ..........7 LIST OF fIGURES................................................................................................................ ..........8 ABSTRACT....................................................................................................................... ..............9 CHAPTER 1 INTRODUCTION..................................................................................................................11 2 REVIEW OF THE LITERATURE........................................................................................12 Insomnia and Older Adults.....................................................................................................12 Napping Behavior in Older Adults.........................................................................................13 Prevalence and Duration of Napping..............................................................................13 Time of Day of Napping..................................................................................................14 Evening Napping.............................................................................................................15 Theoretical Link between Napping and Sleep in Older Adults..............................................16 Prior Research: Association between Napping and Sleeping Behavior in Older Adults.......17 Measurement of SleepObjectively......................................................................................19 Polysomnography............................................................................................................19 Actigraphy..................................................................................................................... ..20 Measurement of SleepSubjectively....................................................................................20 Sleep Diary.................................................................................................................... ..20 Sleep Classification System............................................................................................21 Measurement of Napping.......................................................................................................21 Objectively Measured Napping (Actigraphy).................................................................21 Subjectively Measured Napping (Sleep Diary)...............................................................22 Innovations of Research........................................................................................................ .22 3 STATEMENT OF PURPOSE................................................................................................24 Specific Aim 1................................................................................................................. .......24 Subaim 1.1a.................................................................................................................... .24 Subaim 1.1b.................................................................................................................... .24 Subaim 1.2a.................................................................................................................... .24 Subaim 1.2b.................................................................................................................... .25 Subaim 1.3a.................................................................................................................... .25 Subaim 1.3b.................................................................................................................... .25 Hypothesis for Specific Aim 1...............................................................................................25 Specific Aim 2................................................................................................................. .......26 Subaim 2.1a.................................................................................................................... .26

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5 Subaim 2.1b.................................................................................................................... .26 Hypothesis for Specific Aim 2...............................................................................................26 4 METHODS........................................................................................................................ .....28 Procedure...................................................................................................................... ..........28 Participants................................................................................................................... ..........29 Measures....................................................................................................................... ..........29 Operationalization of Sleep Variables.............................................................................29 Objective sleep variables..........................................................................................29 Subjective sleep variables........................................................................................31 Operationalization of Nap Variables...............................................................................32 Objective nap variables............................................................................................32 Subjective nap variables...........................................................................................34 Demographics and Health survey....................................................................................35 Cognitive Impairment......................................................................................................36 Daytime Functioning Measures.......................................................................................37 Beck depression inventor ysecond edition (BDI-II)..............................................37 State-trait anxiety inve ntory, form Y1 (STAI).........................................................37 Epworth sleepiness scale (ESS)...............................................................................38 Fatigue severity scale (FSS).....................................................................................38 Data Analysis.................................................................................................................. ........38 Specific Aim 1.................................................................................................................38 Subaim 1.1a..............................................................................................................39 Subaim 1.1b..............................................................................................................40 Subaim 1.2a..............................................................................................................40 Subaim 1.2b..............................................................................................................40 Subaim 1.3a..............................................................................................................41 Subaim 1.3b..............................................................................................................41 Specific Aim 2.................................................................................................................42 Subaim 2.1a..............................................................................................................42 Subaim 2.1b..............................................................................................................42 5 RESULTS........................................................................................................................ .......44 Characteristics of Napping Be havior within the Sample........................................................44 Specific Aim 1................................................................................................................. .......45 Subjective Napping and Obj ective Sleep (Subaim 1.1a).................................................45 Subjective Napping and Subjective Sleep (Subaim 1.1b)...............................................46 Objective Napping and Objective Sleep (Subaim 1.2a)..................................................46 Objective Napping and Subjective Sleep (Subaim 1.2b)................................................47 Nap Categories: Day and Evening Nappers versus Daytime Nappers (Subaim 1.3a)....47 Nap Categories: Day and Evening Nappers versus Daytime Nappers (Subaim 1.3b)....48 Specific Aim 2................................................................................................................. .......48 Sleep Subtypes and Objective Napping (Subaim 2.1a)...................................................49 Sleep Subtypes and Subjective Napping (Subaim 2.1b).................................................49

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6 6 DISCUSSION..................................................................................................................... ....55 Review of Study Findings......................................................................................................56 Characteristics of Napping Be havior within the Sample................................................57 Subjective Napping and Obj ective Sleep (Subaim 1.1a).................................................60 Subjective Napping and Subjective Sleep (Subaim 1.1b)...............................................61 Objective Napping and Objective Sleep (Subaim 1.2a)..................................................61 Objective Napping and Subjective Sleep (Subaim 1.2b)................................................62 Nap Categories: Day and Evening Nappers versus Daytime Nappers (Subaim 1.3a)....63 Nap Categories: Day and Evening Nappers versus Daytime Nappers (Subaim 1.3b)....64 Four Sleep Subtypes (Specific Aim 2)............................................................................65 Study Limitations.............................................................................................................. ......65 Implications................................................................................................................... .........67 Implications for Theory and Research............................................................................67 Clinical Implications.......................................................................................................67 Future Directions.............................................................................................................. ......68 Conclusions.................................................................................................................... .........69 APPENDIX A EXAMPLE OF SLEEP DIARY.............................................................................................70 B HEALTH SURVEY...............................................................................................................71 LIST OF REFERENCES............................................................................................................. ..72 BIOGRAPHICAL SKETCH.........................................................................................................79

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7 LIST OF TABLES Table page 5-1 Mean nap frequency, duration, and time of day as measured by actigraphy and sleep diaries........................................................................................................................ .........50 5-2 Correlations of sleep diary napping, actig raphy sleep, and sleep diary sleep variables with the canonical variate..................................................................................................52 5-3 Means and standard deviations for the time of day of nap groups for objective sleep .....53 5-4 Means and standard deviations for the time of day of nap groups for subjective sleep....54

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8 LIST OF FIGURES Figure page 5-1 Percentage of total naps taken by all part icipants that occurred during each half-hour interval of the 24-hour clock..............................................................................................51

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9 Abstract of Thesis Presen ted to the Graduate School of the University of Florida in Partial Fulfillment of the Requirements for the Degree of Master of Science NAPPING AND SLEEP: AN ACTIGRAPHIC ST UDY OF A SAMPLE OF COMMUNITY DWELLING OLDER ADULTS By Natalie Dautovich December 2007 Chair: Christina McCrae Major: Psychology Individuals face many challenges as they age and a common complaint is difficulty sleeping. Nocturnal sleep disturbances in older a dults have been associated with a number of factors including daytime napping. The main ai m of the study was to examine the relationship between napping and sleeping behaviors in a sa mple of community-dwelling older adults. The relationships between both subjec tive (sleep diary) and objective (actigraphy) napping and sleep variables were examined. Innovations of the study included the use of both subjective and objective measures of napping and sleep, an exte nded data collection period, the examination of the multiple components of napping behavior (f requency, duration, and time of day), and the study of a sleep classification system in relation to napping behavior. Consistent with previous findings, napping was found to have a differentia l relationship with sleep. Subjectively measured nap frequency and duration were found to be negatively correlated with objectively measured total sleep time, objectiv ely measured sleep efficiency, and subjectively measured total sleep time. Objectively measured nap freque ncy, duration, and time of day of napping were found to be unrelated to both subj ective and objective sleep. An an alysis of categories of time of day of napping revealed that i ndividuals who napped both in th e daytime and evening compared to those who napped only in the daytime showed a decrease in objectively measured sleep onset

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10 latency, a decrease in wake time after sleep onset, and an increase in sleep efficiency. Finally, the four sleep subtypes (noncomplaining good sleepers, complaining good sleepers, noncomplaining poor sleepers, and complaining poor sleepers) were not differentiated by their subjectively or objectively measured napping behavior. The results suggest that 1) it is difficult to uniformly state the direction of the relations hip between napping and sleep and 2) the mode of measurement (objective and subjecti ve) plays an important role in determining this relationship.

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11 CHAPTER 1 INTRODUCTION Individuals face many challenges as they age. One of these challenges is difficulty sleeping or insomnia. Sleep complaints are multifactorial in origin and one of the factors that is associated with nocturnal sleep complaints is napping. Although napping has been studied in relation to sleep since the 1960s, the association between na pping and sleep remains unclear. The discrepancies in previous research on the relationship between napping and sleep in older adults may be due in part to the multifact orial nature of napping and sleep. Additionally, methodological limitations of the previous studies may partially account for these inconsistencies. Within the prior literature, the multifaceted nature of napping behavior (frequency, duration, time of day) has not been studied simultaneously in healthy and older adults diagnosed with insomnia. Additionally, napping and sleep behavior have not been observed for longer than one week using both obj ective and subjective measures of napping and sleep. Finally, napping has not b een studied in relation to a variety of sleep subtypes. Traditionally, studies have only compared good sleepers and individuals diagnosed with insomnia. These limitations will be addressed by the present study. The present study examines the relations hip between objectively and subjectively measured napping and sleep. Additionally, the re lationship between napping and four subtypes of good and poor sleepers is examined. By a ddressing methodological limitations of previous research, the current study aims to further specif y the nature of the rela tionship between napping and sleep in older adults. ________________ Note: For detailed specific aims, see Chapter 3.

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12 CHAPTER 2 REVIEW OF THE LITERATURE Insomnia and Older Adults Individuals age 65 and older represent the fastest growing segmen t of the population. According to the U.S. Census Bureau (2000a), the percentage of older adu lts in the population is predicted to increase by more than 20% by th e year 2030 (an increase from 4% in 1900). A significant challenge facing individu als as they age is difficulty sl eeping. Fifty-seven percent of older adults complain of some difficulty sleep ing (Kryger, Monjan, Bliw ise, & Ancoli-Israel, 2004). Insomnia is the most common of sleep complaints with estimates ranging from 15-65% (Ohayon, 2002). Insomnia involves difficulty in itiating or maintaining sleep that causes significant distress for the indivi dual resulting in impaired soci al or occupational functioning (American Psychiatric Association [APA], 2000). The impact of insomnia on older adults is significant. The effects range from a minimum impact of daytime fatigue and decreased mood (APA, 2000) to decreased quality of life, impaired cognitive functioning, increased risk for falls, accidents, medical illness, and long-term care pl acement (Foley et al., 1995; Pollack, Perlick, Linsner, Wenston, & Hsieh, 1990). Finally, inso mnia places a huge economic burden on society. The estimated costs for directly treating in somnia in 1995 exceeded $13.9 billion (Walsh & Engelhardt, 1999). Effective treatment interventions are requi red to mitigate the significant impact of insomnia on individuals and society. Understa nding the etiology of insomnia enables the development of efficacious interventions. A basic f actor implicated in the cause of insomnia is age-related changes in sleep. Sp ecifically, the archite cture of sleep changes with age. Sleep becomes structurally lighter with more time devoted to the lighter stages of sleep (stages 1 and 2) and less time spent in deeper or slow wave sl eep (stages 3 and 4; Fe inberg, 1974; Hayashi &

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13 Endo, 1982). Additionally, older adults experience less total sleep time and more awakenings (Evans & Rogers, 1994), and longer sleep onset (i.e the amount of time it takes to fall asleep; Lichstein & Morin, 2000). Despite the structural changes in sleep affecting the majority of older adults, sleep complaints are not un iversal. Health, situational, and psychological factors combine and add to ontogenetic changes affecting sl eep. Consequently, sleep complaints are multifactorial in origin (L ichstein & Morin, 2000). Napping Behavior in Older Adults One of the situational factor s associated with insomnia among the elderly is napping. Napping is defined as any short sleep epis ode out of bed (American Sleep Disorders Association, 1997). The out of bed sleep period do es not have to be of a maximum or minimum duration to be labeled as a nap (The Interna tional Classification of Sleep Disorders, 1990). Prevalence and Duration of Napping Napping is prevalent in older adults, with one in four individuals e ngaging in a daily nap (Beh, 1994; Foley et al., 1995). Th e frequency and duration of na ps in older adults varies according to the methodology used to record napping behaviors. Using self-report, Buysee and colleagues (1992) found that on av erage, older adults engaged in 3.4 naps over a two-week period while an actigraphic study of healthy older adults without sleeping difficulties found 76.6% of participants napped at least once dur ing a one-week recording period (Yoon, Kripke, Youngstedt, & Elliott, 2003a). In terms of nap duration in older adults, Yoon and colle agues (2003a) found that in a sample of healthy older adults the average na pping duration was 23.3 minu tes while the average nap duration in a study of postmenopausal women was 31.3 minutes (Yoon, Kripke, Elliot, & Langer, 2004). In Shirota and colleagues (2002) study of napping be havior in elderly participants, there was not a significant differenc e between high and low vo litional (a measure of

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14 mental vigorousness) elderly partic ipants in terms of their in nap duration. On average, high volitional individuals na pped for 36 minutes a day and low volitional individuals napped for 44 minutes a day. Using a different measure of na pping duration, Jean-Louis, Kripke, Assmus, and Langer (2000) found that on average, over a 24-h our period, older adults napped for 45 minutes. Interestingly the 45 minute total nap time account ed for 10% of their total 24-hour sleep (JeanLouis et al., 2000). In summary, previous research has found th at on average, older adults engage in one nap per week, with the average duration of naps ranging from 23.3 to 45 minutes per day. Although napping behavior is prevalent in olde r adults, it is variable. While many older adults report napping behaviors, a number do not. Buysee and colleagues (1992) found that according to sleep diaries, approximately thirty-six percent of a sample of older adults reported no naps during a two-week recording time. A dditionally, there may be significant variability between napping behaviors occurring on the wee kday compared to the weekend. In the same study Buysee and colleagues (1992) found a signi ficant difference between the frequency of napping behavior during the week and on the we ekend, with more naps occurring on average during the week. Longitudinal asse ssment of napping behavior is more likely to capture the variability of napping beha vior in older adults. Time of Day of Napping The time of day of napping is an importa nt component of nappi ng behavior in part because the time of day the nap occurs may m oderate the hypothesized association between napping and sleep. A theoretical explanation for the association between time of day of napping and nocturnal sleep is that naps taken later in the day contain mo re slow wave sleep than naps taken earlier in the day (Yoon et al., 2003b). Considering that slow wave sleep provides the

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15 most restorative sleep, by engaging in naps at a later point during th e day individuals may engage in a deeper sleep that meets more of their nocturnal sleep needs. A number of studies have cal culated the average time of day of naps. Shirota and colleagues (2002) found that there was not a significant difference in the average time of day of naps of both high and low volitional elderly particip ants. On average, high volitional individuals began their naps at 13:34 and low volitional individuals began their naps at 13:38. Although there were no significant differe nces in the timing of the naps high volitional individuals took their naps as their activity levels were decrea sing whereas low volitional individuals took their naps as their activity levels were increasing. Elderly participants reported napping slightly later in the afternoon (14:42) in th e study by Buysee and colleagues ( 1992) and reported no significant difference in the timing of naps during the week compared to on the weekend. Napping peaks were observed at three times during the day in a study of postmenopausal women (Yoon, 2004). The highest peak occurred approximately one hour before bedtime, the second approximately 8 or 9 hours after wake-up time, and the smallest peak 2 hours after wake-u p time. These peaks corresponded with the clock times of 22:00, 15:00 /16:00, and 09:00. In summary, in the studies that reported the average time of day of naps, the average time of day of naps was variable ranging from 13:34 to 22:00. Evening Napping In addition to studying the relationship between out-of-bed sleep in general and nocturnal sleep, a number of researchers have identified a subset of napping behavior the evening nap. Previous research defines evening naps as out-of-b ed sleep that occurs within the timeframe of two hours to just before bedtime (Yoon et al ., 2003b). Evening naps may impact sleep by causing earlier awakenings, earlier illuminati on exposure, and consequently causing a phase

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16 advance of the circadian system (Buxton, L Hermite-Baleriaux, Ture k, & van Cauter, 2000; Yoon et al., 2003a.) The frequency of evening napping appears to increase with age (Jean-Louis et al., 2000; Monk, Buysse, Carrier, Billy, & Rose, 2001; Yoon,et al., 2003b). In a paper by Yoon and colleagues (2003b), the evening na p timeframe corresponded to the clock-time of 20:38 22:38. In a study of post-menopausal women, Yoon and colleagues (2004) found that the average evening nap duration was 7.75 minutes. This dura tion contrasts with an average daytime nap duration of 31.3 minutes in the same study. An coli-Israel, Kripke, Mason, and Kaplan (1985) found that in a sample of indi viduals diagnosed with sleep apnea, periodic limb movements (PLM), or no diagnosis, 45% of elderly participants engaged in evening naps. The frequency of evening naps ranged from 3-5 per evening and th e duration ranged from 5 to 18 minutes. Yoon and colleagues (2003b) found that 52% of the samp le engaged in at leas t one evening nap per week. Considering the prevalence of evening napping among the elderly, it is important to assess this napping behavior among older ad ults. Additionally, considering the unique characteristics of evening naps reported in pr evious studies (e.g. higher frequency and shorter duration) it may be informative to examine ev ening naps separately from daytime naps. Theoretical Link between Napping and Sleep in Older Adults In addition to studying the characteristics of napping behavior in older adults, several theoretical explanations have been provided to account for the association between napping and nighttime sleep. Borbly (1982) advanced two bi ological mechanisms to explain the relationship between napping and sleep. The circadian system controlled by an internal pacemaker within the hypothalamus, regulates sleepiness and wake fulness within a 24-hour rhythm. The second mechanism, the homeostatic drive, results in an increasing motivation towards sleepiness during periods of wakefulness. Older adults may e xperience a decreased homeostatic drive (accounting

PAGE 17

17 for less deeper sleep during the night and increased number of awakenings) that results in a decreased drive towards wakefulness duri ng the day. Buysee and colleagues (1992) hypothesized that napping disrupts both the circadian system and the homeostatic drive, resulting in an increase of polyphasic sleep. Consequently, older adults experience more fragmented patterns of daytime and nocturnal sleep comp ared to younger adults (Hays, Blazer, & Foley, 1996). An alternate theoretical explanation for the in creasing number of naps as individuals age is that daytime sleep propensities may no longer be being masked by social obligations among the elderly (Jean-Louis et al., 2000). Although older adults may maintain high levels of activity during retirement, the less compulsory nature of these activities may provide increased opportunities for daytime napping behavior. Prior Research: Association between Napping and Sleeping Behavior in Older Adults Despite the theoretical basis for the relati onship between napping and sleep, previous research is mixed regarding the st rength or existence of this rela tionship. Several studies have found that napping behavior is a ssociated with impaired nocturnal sleep. Frequency of napping was associated with increased risk of sleep co mplaint (Hays et al., 1996) while duration (Beh, 1994) of napping was negatively correlated with nocturnal sleep length. Yoon and colleagues (2003a) examined the relationship between time of day of napping (evening naps), wake times, and nocturnal sleep length. Older adults who enga ged in evening naps within a timeframe of two hours to bedtime were found to have significantly earlier wake-up times (undesirable for older adults) and decreased total sleep time. Yoon and colleagues ( 2003b) also compared the sleep onset and offset times of older adults with or without evening naps. There was a significant difference in the sleep offset times with indivi duals who engaged in an evening nap awakening on average 54 minutes earlier than those who did not engage in an evening nap. No significant

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18 differences were reported in nocturnal sleep between those who napped and did not nap as measured by sleep diaries but a significan tly lower total sleep time was recorded by polysomnography for those who engaged in naps (Monk et al., 2001). Finally, a significantly longer sleep onset latency was observed in indi viduals who napped compared to those in a sedentary condition (Campbell, Murphy, & Stauble, 2005). In contrast to the negative relationship be tween napping behavior and sleep variables, a small number of recent studies suggest a posit ive association between napping behavior and sleep quality. Studies involving the Okinawa elders of Japa n have found that prescribed napping of 30 minute duration between the hours of one and three in th e afternoon was significantly associated with decreased wake time after sleep onset and improved slee p efficiency (sleep efficiency refers to the percentage of time in be d that is spent sleeping; Tanaka et al., 2002). Additionally, napping in the afte rnoon reduced the average even ing nap duration from 39 to 11 minutes (Tanaka et al., 2001). Another study in volving the Okinawa elders found that a higher percentage of elderly participan ts in the rural areas took a daily nap (55.2%) compared to elderly participants in the urban areas (32.4%). The rural elderly had significantly fewer sleep complaints and a significantly lower sleep health ri sk index (an analysis of sleep health including sleep disturbances, parasomnia, apnea, difficulty waking, and difficulty falling asleep; Arakawa, Tanaka, Toguchi, Shirakawa, & Taira, 2002). Si milarly, Foley and colleagues (1995) found that an increase in napping frequency was accompanied by an overall decrease in sleep complaints and frequent nappers (>2 naps per two week period) reported shorter sleep onset latency compared to less frequent nappers (< 2 naps per two week peri od; Buysee et al., 1992). Additionally, several studies have reported a significant increase in 24-hour total sleep time for individuals who nap compared to those who do not (Campbell et al., 2005; Monk et al., 2001).

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19 Finally, a large portion of the available l iterature on napping ha s found no relationship between napping and sleep. Good and poor sleeper s did not differ in terms of napping frequency (Bliwise, 1992; Morin & Gramling, 1989), na pping duration (Aber & Webb, 1986), or both napping frequency and duration (Johnston, Landis, Lentz, & Shaver, 2001; Morgan, Healey, & Healey, 1989; Morin & Gramling, 1989). Simila rily, Jean-Louis and co lleagues (2000) found that afternoon and evening naps were not associated with nocturnal sleep duration, sleep efficiency, or total wake time. Contrasting wi th the improved sleep associated with napping as reported using sleep diaries, Buysee and co lleagues (1992) found no significant difference between frequent and infrequent nappers in terms of polysomnogra phic sleep variables. Measurement of SleepObjectively Polysomnography Some of the discrepancies in previous findi ngs result in part fro m differing methods of measuring sleep. Sleep can be assessed using obj ective and subjective methods. Considering the variations in the previous findings, both subjective and objective approaches will be used in the current study. The traditional gold standard for objectivel y measuring sleep is polysomnography (PSG). This procedure provides the most thorough and objective diagnosis of sleep disorders other than insomnia (Lichstein & Morin, 2000). Polysomn ography assesses sleep by recording brain waves (electroencephalography EEG), eye movements (electro-oculography EOG), chin muscle tone (chin and anterior tibialis electromyography EMG), re spiratory effort, airflow, oximetry, and electrical activity of the he art (electrocardiography ECG). Despite the thoroughness of this procedure, there are several limitations for its us e with older adults. The procedure typically occurs in a laboratory setting. This setting may be uncomfortable for older adults and may not resemble their natural sleep environment (Lib man, Creti, Levy, Brender, & Fichten, 1997).

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20 Interestingly, individuals with sleep problems often sleep better away from their own home due to a lack of association between poor sleep and the new environment. Therefore, assessing an individuals sleep away from ho me may result in an overestima tion of their sleep quality. Also, the customary two night duration of a PSG study ma y not capture the highly variable nature of older adult sleep (Edinger, Marsh, McCall, Erwin, & Lininger, 1991). Finally, the cost of PSG for a large sample size can be prohibitive. Actigraphy Considering the limitations associated with the use of PSG, another objective measure of sleep, actigraphy, was employed in the current study. Actigraphy, used for over 25 years, involves the wearing of a wristwat ch-like device, typically on the nondominant wrist. In contrast with PSG, actigraphy is relatively in expensive, enables the individua l to remain in their natural environment, and can record data continuously fo r up to 14 days. There are several actigraphic devices available for use. Th e Actiwatch-L (Mini Mi tter Co. Inc., 2001) was chosen because it utilizes the most up-to-date technology (i.e. digi tal integration) and ha s been validated with healthy older adults with insomnia (Mini Mitter Co. Inc., 2001). Measurement of SleepSubjectively Assessment of subjective appraisals of sleep can complement the objective data collected using actigraphy. Sleep diaries were used to subjectively measure sleep in the study. Additionally, participants were classified into four sleep subtypes usi ng sleep diary and other self-report information. Sleep Diary Sleep diaries are a self-report description of sleeping behaviors recorded on a written log by the participant. Example behaviors that the pa rticipant may report include the time he or she

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21 goes to bed, the amount of time required to fall as leep, and the number of awakenings during the night. The diaries are typically completed in the morning once the participant wakes up. Sleep Classification System A number of self-identified poor sleepers do not experience objectively poor sleep as measured by polysomnography or actigraphy. Inte resting, these individu als do not differ from individuals objectively diagnosed with insomn ia in terms of the symptoms experienced (Lichstein, Wilson, Noe, Aguillard, & Bellue, 1994) The diagnostic label for this condition is sleep state misperception (American Sleep Diso rders Association, 1997), but it is commonly referred to as subjective insomnia. Consideri ng that clinicians focus their treatment on the complaint aspect of insomnia, the study of subjective insomnia is critical. McCrae and colleagues (2005) developed a classification system for identifying individuals based on subjective complaints and subjective sleep quantity. Individuals are classified into one of four sleep subtypes based upon the fo llowing criteria: 1) subjective complaint of insomnia, 2) duration of insomnia complaint, 3) daytime functioning, and 4) sleep pattern as measured by the sleep diaries. The classification system resulted in four sleep subtypes: noncomplaining good sleepers, comp laining good sleepers, noncomplaining poor sleepers, and complaining poor sleepe rs (insomniacs) (Figure 2-1). Measurement of Napping Objectively Measured Napping (Actigraphy) Previous studies have found that older adults often underreport their napping behavior. Comparing subjective reports and EEG record ings of napping behavior, Jean-Louis and colleagues (2000) found that volunt eers correctly reported only 38% of their afternoon-evening napping periods (with a false-positive reporting rate of 19%). Yoon and colleagues (2003a) found that only 22.6% of older evening nappers repor ted their evening naps in sleep diaries. The

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22 present study addresses some of the concerns associated with th e self-reporting of naps by older adults by using an objective meas urement of napping, the Actiwatch-L (Mini Mitter Co. Inc). In addition to the sleep parameters, a number of napping parameters can be derived from the Actiwatch data. Subjectively Measured Napping (Sleep Diary) In addition to objectively measured napping, it is possible to subjectively estimate napping using sleep diaries. Participants report on th e number of minutes they spent napping for each day. Innovations of Research Despite the accumulation of research over four decades, the association between napping and sleep remains unspecified. Several methodol ogical limitations may account for the lack of consensus. These shortcomings will be addressed by the current study. Previous research has relied heavily on surv eys or self-report sleep diaries to assess napping and sleep behavior in ol der adults. Studies of sleep patterns in postmenopausal women and healthy older adults reported that 62 77% of napping behavior was unreported when compared to objective measures of sleep (ac tigraphy and polysomnography; Jean-Louis et al., 2000; Yoon et al., 2003a). This limitation will be addressed in the current study by the use of an objective measure (actig raphy) of both napping and sleep, in addition to subjective measures (sleep diary), in order to more accurate ly assess napping and sleep behavior. An additional limitation involves the variability inherent in napping and sleep behavior in older adults. Approximately 50% of older adults engage in napping behavior only one to two days per week (Beh, 1994). Napping and sleep be havior also varies fr om weekday to weekend (Buysse et al., 1992) with napping occurring more frequently during the week than on the weekends. The typical data colle ction period in previous research ranges from one to two days

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23 to a maximum of six days. Limited data collection periods may not accurately capture the variability in older adult napping and sleep be havior. The current study will address this limitation by extending the data collecti on period to 12 consecutive days. Furthermore, prior research has typically ex amined the components of napping behavior in isolation. The current study aims to assess the differential impact of the three components of napping behavior (frequency, duration, a nd time of day) on sleep quantity. Additionally, the current study w ill use a classification system for the study of sleep and napping. Sleep subtypes (a combination of qualita tive and quantitative subjective estimates of sleep) will be examined for the first time in rela tion to napping behavior. This will allow for the simultaneous study of both healthy individuals a nd those diagnosed with insomnia within the same study. Although these limitations have been addressed i ndividually in previous research, this is the first study to simultaneously address these limitations. Insomnia Criteria Yes No Complaints Yes individuals with insomnia complaining good sleepers No noncomplaining poor sleepers noncomplaining good sleepers Figure 2-1. Visual depiction of sleep classification system. sleep problem duration daytime functioning

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24 CHAPTER 3 STATEMENT OF PURPOSE The main objective of the study is to examine the rela tionship between napping and sleeping behavior in older adults. Napping behavior will be studied 1) in relation to objectively and subjectively measured sleep quantity and 2) in relation to the four sleep subtypes. The two main objectives will be achieved through sp ecific aims and associated subaims. Specific Aim 1 The first specific aim is to investigate th e relationship between napping behaviors and sleep quantity. Subaim 1.1a To investigate the relationship betwee n subjectively measured napping behaviors (frequencys and durations as measured by sleep diaries) and objective sleep quantity as measured by actigraphy (total sleep timeo, sleep onset latencyo, wake time after sleep onseto, and sleep efficiencyo; the subscripts s and o are used to distinguish between the subjective and objective sleep variables). See Chapter four for operational definitions of the napping and sleep variables. Subaim 1.1b To investigate the relationship betwee n subjectively measured napping behaviors (frequencys and durations as measured by sleep diaries) and subjective sleep quantity as measured by the sleep diaries (total sleep times, sleep onset latencys, wake time after sleep onsets, and sleep efficiencys). Subaim 1.2a To investigate the relationship betwee n objectively measured napping behaviors (frequencyo, durationo, and time of dayo as measured by actigraphy) and objective sleep quantity

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25 as measured by actigraphy (total sleep timeo, sleep onset latencyo, wake time after sleep onseto, and sleep efficiencyo). Subaim 1.2b To investigate the relationship betwee n objectively measured napping behaviors (frequencyo, durationo, and time of dayo as measured by actigraphy) and subjective sleep quantity as measured by the sleep diaries (total sleep times, sleep onset latencys, wake time after sleep onsets, and sleep efficiencys). Subaim 1.3a To investigate the relationship between time of day of napping categories (day and evening nappers versus daytime nappers) and objective sl eep quantity as measured by actigraphy (total sleep timeo, sleep onset latencyo, wake time after sleep onseto, and sleep efficiencyo). Subaim 1.3b To investigate the relationship between time of day of napping categories (day and evening nappers versus daytime nappers) and subjective sleep quantity as measured by the sleep diaries (total sleep times, sleep onset latencys, wake time after sleep onsets, and sleep efficiencys). Hypothesis for Specific Aim 1 The hypothesis for the first specific aim is th at both the subjectiv e and objective napping variables (frequencyo/s, durationo/s, and time of day of nappingo) will be most strongly correlated with the sleep quantity variable of total time sp ent asleep for both objective and subjective sleep quantity. Previous research has found significant associ ations between frequency (Hays et al., 1996), duration (Beh, 1994), and time of day (Yoon et al., 2003a) of napping and various sleep variables. Considering that pr ior research is mixed regarding the direction of the relationship between the napping and sleep va riables, the direction of th e proposed relationship between

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26 napping and sleep cannot be predicted for the present study. Since total sleep time has been found to be the single best i ndicator of sleep quantity (Lic hstein & Morin, 2000), it is hypothesized that the napping variab les will most strongly be asso ciated with total sleep time. Specific Aim 2 The second specific aim is to identify the di fferences between the four sleep subtypes (noncomplaining good sleepers, complaining good sleepers, noncomplaining poor sleepers, and complaining poor sleepers) in terms of their napping behavior (frequencyo/s, durationo/s, and time of day of nappingo) as measured by actigraphy and sleep diaries. Subaim 2.1a Investigate the extent to which the four sleep subtypes (noncompl aining good sleepers, complaining good sleepers, noncomplaining poor sleep ers, and complaining poor sleepers) differ in terms of their obj ectively measured napping behavior (frequencyo, durationo, and time of dayo as measured by actigraphy). Subaim 2.1b Investigate the extent to which the four sleep subtypes (noncompl aining good sleepers, complaining good sleepers, noncomplaining poor sleep ers, and complaining poor sleepers) differ in terms of their subjectively m easured napping behavior (frequencys and durations as measured by sleep diaries). Hypothesis for Specific Aim 2 The hypothesis for the second specific aim is that both subjective and objective napping variables (frequencyo/s, durationo/s, and time of day of nappingo) will be differentially related to the four sleep subtypes. This ai m is exploratory in that the sleep subtypes have not been studied previously in relation to napping behavior. Previous research has demonstrated a relationship between the four sleep subtypes and sleep beha vior. Complaining good sleepers were found to

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27 have poorer subjective sleep quantity in co mparison to noncomplaining good sleepers. Specifically, complaining poor sleepers had a grea ter number of awakenings, greater wake time after sleep onset, poorer sleep efficiency, and more total wake time. The four sleep subtypes also differed in terms of objective sleep quantity. Co mplaining poor sleepers had greater sleep onset latency, poorer sleep efficiency, and greater total wake time (McCrae et al., 2005).

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28 CHAPTER 4 METHODS Procedure A secondary data analysis was performed us ing data collected during a study conducted by McCrae and Rowe (2003). A convenience sample wa s recruited from the North Florida area. A variety of recruitment techniques were employe d including media adve rtisements, community groups, and flyers. Recruitment materials describe d the research as a stu dy of sleep patterns in the elderly. Participants were compensated $30 for their participation. Interested individuals were screened in two phases to determine if they met the crit eria for inclusion. Phase one consisted of a brief telephone interview (15 minutes), and phase two involved an in-person interview either in the individuals home (76%) or at a local continuing care retirement center (24%). Individuals were excluded on th e basis of six exclusionary criteria: 1) age younger than 60 years; 2) self-report of sleep disorder diagnoses other than insomnia (e.g., sleep apnea or narcolepsy); 3) self-report of sleep symptoms i ndicative of sleep diagnoses other than insomnia (e.g., heavy snoring, gasping for brea th, leg jerks, daytime sleep at tacks); 4) presence of severe psychiatric disorders (e.g., t hought disorders or depression); 5) cognitive impairment (e.g., scoring in the impaired range on three or more s ubtests of the Cognistat); 6) use of psychotropic or other medications know to alter sleep (e.g., be ta-blockers); and 7) medical conditions that impaired independent daily func tioning (McCrae et al., 2005). Data were collected at three periods during th e study: baseline, end of first week, and end of second week. During the in itial 1 hour interview, part icipants read and signed an informed consent form approved by the University of Florida Institutiona l Review Board. Once consent was obtained, the Cognistat and the demographics and hea lth survey were administered

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29 by a member of the research team At this time, both the sleep diaries and the Actiwatch-L were explained to the participants. The particip ants were advised to complete the sleep diaries and wear the Actiwatch-L continuously for 14 days. At the end of the first week, the sleep diaries were collected from the participants a nd the data was downloaded from the ActiwatchL. At the end of the second week, the fi nal week of sleep di aries and Actiwatch-L data were collected. The Beck Depression Inventory-Seco nd Edition, State-Trait A nxiety Inventory, StateForm Y1, and the PANAS were also completed at this time. Participants Of the 116 individuals recruited, 103 were enrolled in the study. Thirteen individuals were ineligible to participate in the study due to age, dementia, medication, and sleep apnea diagnosis. The mean age of the participants was 72.81 years ( SD = 7.12). The majority of participants were European Caucasian (96%), female (66%), college educated (75%; M = 16.34 years, SD = 2.92), and married (59%). All of the participants lived in their own homes during the study. Measures Overviews of the nap and sleep variables, the demographics and health survey, the Cognistat, and the measures of daytime functioni ng are presented below. Additional information on the methodology for assessing napping and sleep is presented in the literature review. Operationalization of Sleep Variables Objective sleep variables Objective sleep was measured using the Actiwatch-L. Within the Actiwatch-L, data is sampled 32 times per second over a 30 second epoc h using an omnidirectional, piezoelectric accelerometer with a sensitivity of > 0.01 g-force. A sum of the peak activity counts for each 30 second epoch is downloaded to a PC and then an alyzed by Actiware-Sleep vol. 3.3. (Mini Mitter Co. Inc., 2001). Three sensitivity settings (hi gh, medium, and low) are provided by the software

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30 for detecting wake/sleep periods. A high sensitivity setting was us ed in the current study since it provides high correlations with PSG measured to tal sleep time (.95) for healthy older adults (Colling et al., 2000) and for total sleep time (.73) and sleep onset latency (.93) for individuals with insomnia (Cook et al., 2004). Additonally, actigraphy has valid cr iterion-validity when compared to PSG (.80) and high test-retest re liability (0.92; Ancoli -Israel et al., 2003). A validated algorithm is used to identify th e activity of each epoch as wake or sleep (Oakley, 1997). With the high sensit ivity setting, the threshold for wake is 20 activity counts. If the peak activity count for an epoch is > 20, the epoch will be scored as wake. If the peak activity count for an epoch is < 20, the wake/sle ep determination is made based on the activity that occurs in the two minute period surrounding th e epoch. The wake/sleep determination if the activity count is < 20 is made based on following equation: Total Activity for Epoch A = EA-4 (.04) + EA-3 (.04) + EA-2 (.20) + EA-1 (.20) + E (2) + EA+1 (.20) + EA+2 (.20) + EA+3 (.04) + EA+4 (.04) where A = # of activity counts for the epoch being scored; EA +/1-4 = # of activity counts in adjacent epochs. If the Total Activity for E poch A (weighted sum of activity counts) exceeded the threshold value of 20, then Epoch A is scored as wake; otherwise, it is scored as sleep (McCrae et al., 2005). Using the Actiware-Sleep vol. 3.3. software (Mini Mitter Co. Inc., 2001), a number of sleep parameters are derived from the data including total sleep time, total wake time, sleep efficiency, and sleep onset latency. The definiti ons of the objective sleep variables used in the study are: sleep onset latencyo (interval between bedtime and sleep start); total sleep timeo (sum of all sleep epochs within a sleep period); sleep efficiencyo (ratio of total sleep time to total time spent in bed x 100); and wake time after sleep onseto (time spent awake afte r initial sleep onset

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31 until last awakening). The subscripts s and o are used to distinguish between the subjective and objective sleep variables. Subjective sleep variables Sleep diary. Subjective sleep quantity was measured using sleep diaries. The sleep diary (Lichstein, Riedel, & Means, 1999) was completed by each participant each morning for 14 days (see Appendix A). Although data was collected for 14 days, the first and last days of data were eliminated from the analysis as the actigra phy data for those days was incomplete. Four subjective sleep estimates were derived from the sleep diary data: sleep onset latencys (initial time from lights out until sleep ons et); wake time after sleep onsets (time spent awake after initial sleep onset until last awakening); total sleep times (computed by subtracting total wake time from time in bed); and sleep efficiencys (a ratio of total sleep time to total time spent in bed x 100). Sleep classification system. The second subjective measurement of sleep that was employed was the sleep classification system. The sp ecific criteria used to create the four sleep subtypes within the system are as follows. The criteria used to assess the three complaints and insomnia are: 1) subjective complaint of insomn ia as indicated by affirm ative responses to the following items on the demographics and health questionnaire: Do you have a sleep problem? yes or no. If yes, describe (e.g., trouble fall ing asleep, long or frequent awakenings, sleep apnea).; 2) duration of complain t for at least 6 months as in dicated by response to the item on the demographics and health questionnaire: H ow long have you had this sleep problem?; and 3) impaired daytime functioning as indicated by sc oring in the impaired ra nge on at least one of the following measures: STAI > 36, BDI > 9, ESS > 7.3, or FSS > 5.4. Participants were categorized as poor sleepers if they reported at least 3 nights a week of: (1) sleep onset latency > 30 minutes or (2) wake time after sl eep onset > 30 minutes. This criteria

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32 for insomnia has been validated and is consiste nt with those commonly cited in the insomnia treatment literature (Lichstein, Durrence, Taylor Bush, & Riedel, 2003). Individuals diagnosed with subjective insomnia correspond with sleep subtype of comp laining good sleepers. Operationalization of Nap Variables Objective nap variables Napping was measured objectively using ac tigraphy. Methodological questions have arisen regarding the sensitivity of actigraphy to distinguish between inac tivity due to napping versus inactivity due to resting or the removal of the watch. Interestingly, the sensitivity setting (high) validated for determining sleep bouts in older adults is not a pplicable for identifying napping behavior in older adults. The use of a threshold of 20 activ ity counts per 30 second epoch results in an overestimation of daytime na pping behavior. This is due in part to the misidentification of levels of in activity (resting/watch removal) as sleep bouts. Therefore, an even higher sensitivity setting is required in order to different iate mere inactivity from napping behaviors. In the present study a sensitivity settin g of 12 enabled the detection of naps identified by participants in their sleep diaries. Additionally, concerns about differentiating resting and watch removal from napping can be addressed by examining narratives in the pa rticipants sleep diaries (e.g. watch removed from 6-8 p.m.) and applying Websters ru les (Webster, Kripke, Messin, Mullaney, & Wyborney, 1982) to distinguish between restin g/watch removal and napping behavior. Specifically, Websters rules involve rescoring small wake periods surrounded by sleep periods as sleep and rescoring small sleep periods surrounded by wake periods as wake. An additional method to be used in the study for di fferentiating watch o ff periods from naps involves increasing the sensitivity level to the highest setting (0) and noting which periods are still identified as naps at this setting. If a peri od of inactivity is labeled as a nap at the highest

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33 setting, the nap should be eliminated from the anal ysis. An activity count of contains less activity then would be required fo r human sleep and actually represen ts watch off intervals (M. Reed, Minimitter, personal communication, June 6, 2005). Finally, in order to encompass the range in th e duration of naps of 5 to 45 minutes found in previous research, naps that ranged in durati on from 5 to 180 minutes were included in the analysis. Frequency as measured by actigraphy. Frequency refers to the total number of periods during the day (as measured by actigraphy) that were scored as sleep. The total number of inactive periods during the day was averaged over 12 days to create the nap frequencyo variable. Duration as measured by actigraphy. Duration refers to the total time in minutes that the actigraph was scored as sleep for discrete na p periods throughout the day time. If there were multiple naps of different durations during the day, the mean nap duration for each day was calculated for each participant. An overall mean nap durationo was calculated by averaging the average daily nap durations over 12 days. Time of day. Time of day was determined from the actigraphy data by converting the time each nap occurred into 24-hour clock time. The time of dayo variable was created by summing the time of day of all naps for each par ticipant and dividing by the number of naps for each participant. Subjective measures of the time of day of naps could not be determined from the information gathered by the sleep diary. The above mentioned operationalization of tim e of day of napping involves averaging the time of day of naps for each participant and di viding by the total number of naps. While this calculation may accurately describe the time of da y for nappers who consistently nap at the same

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34 time each day, it may not accurately describe the ti me of day for more variable nappers. If a participant naps both in the morning and the ev ening, for example, averaging the time of day naps would suggest that they typically nap in the afternoon. In addition to the analysis of a continuous measurement of time of day of napping (subaims 1.2a and 1.2b), a categorical measurement was used that iden tified individuals who napped in the daytime versus the evening. Time of day nap categories (used in subaim 1.3) were created by aggregating participants who napped during both the day and evening in to the day and evening nap group and participants who solely napped during the daytime into the daytime nap group. Evening naps have been previously defined as out-of-bed sleep that occurs within the timeframe of within two hours to just before bed (Yoon et al., 2003b). A si milar inclusion criteria was used in this study where a nap was labeled an evening nap if it occured within two hours of the individuals bedtime for the day being considered. Subjective nap variables Two subjective estimates of napping behavior can be derived usi ng the sleep diary: frequencys and durations (the subscript s denotes subjectiv ely measured napping). The nap section of the sleep diary provides a place for th e individual to record the total number of minutes spent napping prior to bedtime for each day. Frequency as measured by sleep diaries. Frequency was determined from sleep diaries by summing the number of naps that were self -reported over 12 days and dividing by 12 to create the nap frequencys variable. Duration as measured by sleep diaries. Duration was derived from the sleep diary data by summing the total nap time reported for each nap on the sleep diary and dividing by the total number of days for which a nap was reporte d in order to create the nap durations variable. Importantly, sleep diary nap durations differs from actigraphy nap durationo in that it refers to the

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35 average total daily nap duration while the actigraphy nap durationo refers to the average nap duration for each nap Although according to many partic ipants the sleep diary nap dur ation typically reflects the duration for a single nap (they re ported engaging in only one nap pe r day) it cannot be discerned whether the duration reported on the sleep diary re fers to the average total daily nap duration or the average duration of individual naps. Although the possibility ex ists that the durationo and durations variables may be referring to different constructs, it is important to retain th ese variables for a couple of reasons. First, nap duration as recorded by sleep diaries is the tr aditional and most commonly employed method of assessing nap duration among the literature. Theref ore, by retaining this va riable in the study it will be possible to compare our results to previo us findings. Additionally, sleep diaries are the method most commonly used by sleep clinicians to assess clients sleeping behavior. Hence, the inclusion of sleep diaries in the present st udy will provide information that may have implications for the provision of treatment by clinicians. S econd, nap duration as recorded by actigraphy provides the most sensitive estimate of nap duration. This method ensures that the nap duration that is recorded capture s the duration of individual naps. Consequently, the information provided by both of these variable s is valuable to the study. Demographics and Health survey This survey consists of 13 items collecting information on demographics, sleep disorder symptoms, physical health, and mental health (L ichstein et al., 2004) (see Appendix B). Health conditions were assessed as the number of condi tions selected from the following list: heart attack, other heart problems, cancer, AIDS, hype rtension, neurological disorder (seizures, Parkinsons), breathing disorder (asthma, em physema, allergies), urinary problems (kidney disease, prostate problems), diabet es, pain (arthritis, back pain, migraines), and gastrointestinal

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36 disorders (stomach, irritable bowel s, ulcers, gastric reflux). Se lf-report sleep questions on the survey contained information on wh ether the participant had a sleep problem and if they or a bed partner noticed heavy snoring, difficulty breathing or gasping for breath, frequent leg jerks, restlessness before sleep onset, sl eep attacks during the day, or para lysis at sleep onset. If they answered yes to any of these problems, they we re asked to describe the problem and indicate how often and for how long the symptoms had occurred. Cognitive Impairment Participants were screened for cognitive impairment using the Cognistat (The Neurobehavioral Cognitive Status Examinati on; Mueller, Kiernan, & Langston, 2001). This measure contains ten subscales measuring the domains of: orientation and attention, language, visual memory and constructiona l ability, verbal memory, calcula tions, reasoning, and judgment. Each domain area is initially assessed using a screen item (e .g., a three stage command, Turn over the paper, hand me the pen, and point to you r nose). If the partic ipant does not correctly answer the screen item a set of follow-up items of increasing difficulty are administered. The test takes approximately 20 minutes to administer. Individuals w ho scored in the impaired range on three or more of the ten subscales were ex cluded from the study. The Cognistat has been found to more sensitively detect cognitive-impairme nt than the Mini-Mental State Exam (Fields, Fulop, Sachs, Strain, & Fillit, 1992) and to effectively differentia te between impairment due to psychiatric illness versus impairment due to organic cognitive impairment (Wiederman & Morgan, 1995). Interrater reliability wa s found to range from 0.997 to 1.00 (Cunic & Denny, 2001).

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37 Daytime Functioning Measures Beck depression inventorysecond edition (BDI-II) Depression was measured using the Beck De pression Inventory-Second Edition (BDI-II; Beck, Steer, & Garbin, 1996). This is a 21-it em measure with a scale ranging from 0-3 measuring the severity of depressive symptoms (3 being the most severe). Scores range from 0 63. Scores within the 0 13 ra nge indicate none or minimal depression, 14 to 19 indicate mild depression, 20 to 28 indicate moderate depressio n, and 29 to 63 indicate severe depression. Participants were asked to res pond to the questions based on the previous two weeks. The BDIII has demonstrated sufficient inte rnal consistency reliability (.90) and concurrent validity (.69 .76) (Storch, Roberti, & Roth, 2004). In th e present study, the boundary scores for mild depression were used as the cutoffs for evid ence of a daytime functi oning complaint (BDI-II > 13). State-trait anxiety invent ory, form Y1 (STAI) Anxiety was measured using the Stait-Trai t Anxiety Inventory Form Y1 (STAI-Y1; Spielberger, Gorsuch, Lushene, Vagg, & Jacobs 1983). This is a 20-item measure with a 4point scale indicating ho w often the statement is true. Sc ores range from 20 80 with higher scores indicating greater maladjustment. The scale assesses how often the individual experienced apprehension, tensi on, nervousness, and worry during the previous two weeks. The STAI-Y1 has a test-retest reliab ility coefficient of .92 and ade quate criterion validity (>.70; Spielberger, 1989). Scores greater than 36 we re used as evidence of a daytime functioning complaint. This cutoff was chos en, because a score of 37 is 1 SD below the mean for psychiatric inpatients with a primary diagnosis of anxiet y (Spielberger, Gorsuch, Lushene, Vagg, & Jacobs, 1983).

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38 Epworth sleepiness scale (ESS) The Epworth Sleepiness Scale (ESS; Johns, 1991) measures trai t daytime sleepiness. For eight common, quiet daytime activities (e.g. watchi ng television) respondents indicate how likely they are to fall asleep. The responses are base d on the previous two weeks. Responses range from 0 ( would never doze ) to 3 ( high chance of dozing ). Total scores range from 0 to 24, with the higher scores indicating great er daytime sleepiness. Altho ugh adequate norms for the ESS are not available, Johns and Hocking (1997) administered the ESS to 331 corporate employees. They reported that normal sleepers scored, M = 4.6, SD = 2.8. Additionally, insomnia complaints were positively correlated with the ESS. Scores greater than 7.3 were used as evidence of a daytime functioning complaint. This cutoff was chosen, because it is 1 SD above the reported mean for normal sleepers. Fatigue severity scale (FSS) The Fatigue Severity Scale (FSS; Kr upp, LaRocca, Muir-Nash, & Steinberg, 1989) consists of 9 items assessing the experience of fatigue in different aspects of living. Responses range from 1 ( strongly disagree ) to 7 ( strongly agree ). Responses are averaged across the nine items, yielding a possible score range of 1 to 7. While normative data on the FSS are limited, Lichstein, Means, Noe, and Aguillard (1997) found individuals with insomnia seeking treatment at a sleep disorders center averaged 6.0 ( SD = 0.5) on the FSS. A complaint of daytime function was supported by scores greater than 5.4. This cutoff was chosen, because it is 1 SD below the reported mean for persons seeking treatment for insomnia. Data Analysis Specific Aim 1 The first specific aim is to investigate th e relationship between napping behaviors and sleep quantity.

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39 Subaim 1.1a To investigate the relationship betwee n subjectively measured napping behaviors (frequencys and durations as measured by sleep diaries) and objective sleep quantity as measured by actigraphy (total sleep timeo, sleep onset latencyo, wake time after sleep onseto, and sleep efficiencyo). Data analysis. A Canonical Correlation Analysis w ill be conducted to examine the interrelationships among the two metric independ ent variables of subjectively measured napping (frequencys and durations as measured by sleep diaries) and the multiple metric dependent variables of sleep quantity as asse ssed by actigraphy (total sleep timeo, sleep onset latencyo, wake time after sleep onseto, and sleep efficiencyo). A canonical correlation analysis was chosen beca use 1) the use of a multivariate analysis such as canonical correlation analysis controls fo r the inflation of experi mentwise error rates and 2) canonical correlation analysis allows for the derivation of an optimal linear combination between a set of multiple independent variables and a set of multiple dependent variables (Afifi and Clark, 1996). Considering that canonical correlation analysis is a la rge-sample method potentially requiring 15 to 20 participants per m easured variable (Barci kowshi & Stevens, 1975), and considering the conceptual distinctions between objectively and subjectively napping and sleep, four separate analyses will be conduc ted for objectively and subjectively measured napping and objectively and subjectively measured sleep. Canonical correlation analysis is pa rticularly suited for analyzing this aim in that it allows for both an overall examination of the magnitude of the relationships that may exist between napping and sleep and the measurement of the relative contribution of each variable to the overall relationship between napping and sleep.

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40 Subaim 1.1b To investigate the relationship betwee n subjectively measured napping behaviors (frequencys and durations as measured by sleep diaries) and subjective sleep quantity as measured by the sleep diaries (total sleep times, sleep onset latencys, wake time after sleep onsets, and sleep efficiencys). Data analysis. A Canonical Correlation Analysis will be conducted to examine the interrelationships among the two metric independ ent variables of subjectively measured napping (frequencys and durations as measured by sleep diaries) and the multiple metric dependent variables of sleep quality as assessed by sleep di aries (total sleep times, sleep onset latencys, wake time after sleep onsets, and sleep efficiencys). Subaim 1.2a To investigate the relationship betwee n objectively measured napping behaviors (frequencyo, durationo, and time of dayo as measured by actigraphy) and objective sleep quantity as measured by actigraphy (total sleep timeo, sleep onset latencyo, wake time after sleep onseto, and sleep efficiencyo). Data analysis. A Canonical Correlation Analysis will be conducted to examine the interrelationships among the multiple metric independent variables of objectively measured napping (frequencyo, durationo, and time of dayo as measured by actigraphy) and the multiple metric dependent variables of sleep quantity as assessed by actigraphy (total sleep timeo, sleep onset latencyo, wake time after sleep onseto, and sleep efficiencyo). Subaim 1.2b To investigate the relationship betwee n objectively measured napping behaviors (frequencyo, durationo, and time of dayo as measured by actigraphy) and subjective sleep quantity

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41 as measured by the sleep diaries (total sleep times, wake time after sleep onsets, total wake times, and sleep efficiencys). Data analysis. A Canonical Correlation Analysis will be conducted to examine the interrelationships among the multiple metric independent variables of objectively measured napping (frequencyo, durationo, and time of dayo as measured by actigraphy) and the multiple metric dependent variables of sleep quantity as assessed by sl eep diaries (total sleep times, sleep onset latencys, wake time after sleep onsets, and sleep efficiencys). Subaim 1.3a To investigate the relationship between time of day of napping categories (day and evening nappers versus daytime nappers) and objective sl eep quantity as measured by actigraphy (total sleep timeo, sleep onset latencyo, wake time after sleep onseto, and sleep efficiencyo). Data analysis. A Multivariate Analysis of Va riance (MANOVA) will be conducted to examine the differences between the two non-metric independent variables (daytime and evening nappers and daytime nappers) in terms of the multiple metric dependent variables of objective sleep quantity as measured by actigraphy (total sleep timeo, sleep onset latencyo, wake time after sleep onseto, and sleep efficiencyo). Subaim 1.3b To investigate the relationship between time of day of napping categories (day and evening nappers versus daytime nappers) and subjective sleep quantity as measured by the sleep diaries (total sleep times, sleep onset latencys, wake time after sleep onsets, and sleep efficiencys). Data analysis. A Multivariate Analysis of Va riance (MANOVA) will be conducted to examine the differences between the two non-metric independent variables (daytime and evening nappers and daytime nappers) in terms of the mu ltiple metric dependent variables of subjective

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42 sleep quantity as measured by the sleep diaries (total sleep times, sleep onset latencys, wake time after sleep onsets, and sleep efficiencys). Specific Aim 2 The second specific aim is to identify the di fferences between the four sleep subtypes (noncomplaining good sleepers, complaining good sleepers, noncomplaining poor sleepers, and complaining poor sleepers) in terms of their napping behavior (frequencyo/s, durationo/s, and time of day of nappingo) as measured by actigraphy and sleep diaries. Subaim 2.1a Investigate the extent to which the four sleep subtypes (noncompl aining good sleepers, complaining good sleepers, noncomplaining poor sleep ers, and complaining poor sleepers) differ in terms of their obj ectively measured napping behavior (frequencyo, durationo, and time of dayo as measured by actigraphy). Data analysis. A Multivariate Analysis of Va riance (MANOVA) will be conducted to examine the differences between the four non metric independent va riables (noncomplaining good sleepers, complaining good sleepers, noncompl aining poor sleepers, and complaining poor sleepers) in terms of the multiple metric depe ndent variables of objectively measured napping behavior (frequencyo, durationo, and time of dayo as measured by actigraphy). Subaim 2.1b Investigate the extent to which the four sleep subtypes (noncompl aining good sleepers, complaining good sleepers, noncomplaining poor sleep ers, and complaining poor sleepers) differ in terms of their subjectively m easured napping behavior (frequencys and durations as measured by sleep diaries). Data analysis. A Multivariate Analysis of Va riance (MANOVA) will be conducted to examine the differences between the four non metric independent va riables (noncomplaining

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43 good sleepers, complaining good sleepers, noncompl aining poor sleepers, and complaining poor sleepers) in terms of the two metric dependent variables of subjectively measured napping behavior (frequencys and durations as measured by sleep diaries).

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44 CHAPTER 5 RESULTS The main objective of the study was to ex amine the relationship between napping and sleeping behavior in older a dults. The main objective was achieved by examining napping behavior in relation to 1) objectively and subjecti vely measured sleep quantity and 2) in relation to the four sleep subtypes. The two main object ives were achieved through specific aims and associated subaims. The results will be disc ussed separately for each subaim. Descriptive results of the characteristics of napping behavior of the sample are presented at the beginning of the results section. Characteristics of Napping Behavior within the Sample Three separate nappi ng variables (frequencyo/s, durationo/s, and time of dayo) were collected during the st udy. Two of the napping variables (frequencyo/s and durationo/s) were collected using both objective (a ctigraphy) and subjective (sleep diary) methods. The third variable, time of dayo of napping, was collected using actigraphy. See Chapter 4 for operational definitions of the variables. Three individuals were excluded from the following analyses because they did not engage in naps during the course of the study. In terms of napping frequencyo, individuals engaged, on aver age, in 12 naps over the 12 day period as measured by actigraphy (see Table 51 for means, ranges, and standard deviations of the nap variables). In contrast, the partic ipants self-reported napping (according to sleep diaries) on average, four out of the 12 days. According to actigraphy, the maximum number of naps recorded was 43 naps, indicating an aver age daily maximum of four naps. For the subjective sleep diary data, the maximum number of naps reported over the 12-day period was ten naps, with one nap per day as the maximum daily nap frequency.

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45 The average nap durationo recorded by actigraphy was 12 minutes and 26 seconds. The average nap durations reported by sleep diary (indicating th e average total daily nap duration) was 18 minutes. The average nap durationo recorded using actigraphy ranged from 0 to 17 minutes. The average nap durations reported by sleep diaries ranged from 0 to 152 minutes. A paired samples t test was conducted to evaluate wh ether the frequency and duration of naps reported by actigraphy and slee p diaries were signif icantly different. The results indicated that the nap frequencyo as measured by actigraphy was si gnificantly higher than the nap frequencys recorded using sleep diaries ( t [99] = -8.11, p < .001, 2 = 0.40). Conversely, the nap durations reported by sleep diaries was signifi cantly longer than the nap durations recorded using actigraphy ( t [97] = -2.58, p < .05, 2 = 0.06). In terms of the time of day of napping, the peak time of day of naps (the mode nap time of day for all naps of all part icipants) recorded by actigraphy occurred between 20:30 and 21:00 p.m. (see Figure 5-1 for the time of day of all naps). The average time of day of naps was between 14:30 and 15:00. Forty-seven percent of all of the naps occurred after 6 p.m. Fiftyeight percent of the sample enga ged in an evening nap (a nap th at occurred within two hours of bedtime) and 85% engaged in a daytime nap. A ll the participants who engaged in an evening nap, on average, also napped during the day. Specific Aim 1 The first specific aim was to investigate the relationship between napping behaviors and sleep quantity. Subjective Napping and Obj ective Sleep (Subaim 1.1a) A canonical correlation analysis was conducted with subjectively measured napping behaviors (frequencys and durations as measured by sleep diary) as the independent variable set and objective sleep quantity as measured by actigraphy (total sleep timeo, sleep onset latencyo,

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46 wake time after sleep onseto, and sleep efficiencyo) as the dependent variable set. Of the two possible pairs of canonical variates, the first cano nical correlation was st atistically significant (Wilks = .78, p < .01). The canonical correlation was .46 and accounted for 21% of the variance in the pair of variates Table 5-1 shows the canonical coefficients and the structure correlations for the napping and sl eep variables. According to a cutoff correlation of .35 for interpretation (Tabachnik & Fidell, 1989), nap durations, frequencys, total sleep timeo, and sleep efficiencyo were the variables that cont ributed the most to the canonical variate. Individuals who engaged in a shorter nap duration and a smaller number of naps as measured by sleep diaries experienced longer total sleep time and a higher sleep efficiency as measured by actigraphy. Subjective Napping and Subject ive Sleep (Subaim 1.1b) As in subaim 1.1a, a canonical correlation anal ysis was conducted to investigate subaim 1.1b. The independent variable set consisted of the subjectively measured napping behaviors (frequencys and durations as measured by sleep diaries) and the dependent variable set consisted of the subjective sleep quantity variables (total sleep times, sleep onset latencys, wake time after sleep onsets, and sleep efficiencys) as measured by the sleep diaries. The first canonical correlation of 0.42 was significant (Wilks = .80, p < .01) and accounted for 18% of the variance in the pair of variates. Nap frequencys, durations, and total sleep times contributed most to the canonical variate (Table 5-2). The greater the number of naps and the longer the duration of naps, the shorter the total sleep times. Objective Napping and Objective Sleep (Subaim 1.2a) A canonical correlation analysis was conduc ted with objectively measured napping behaviors (frequencyo, durationo, and time of dayo as measured by actigraphy) as the independent variable set and objective sleep quantity as measured by actigraphy (total sleep timeo, sleep onset latencyo, wake time after sleep onseto, and sleep efficiencyo) as the dependent variable set.

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47 Objectively measured napping behaviors were not found to be significantly related to objectively measured sleep quantity (Wilks = .88, p > .05). Objective Napping and Subjective Sleep (Subaim 1.2b) A canonical correlation analysis was conducted to examine the relationship between the set of independent variables (objectively measured na pping behaviors frequencyo, durationo, and time of dayo as measured by actigraphy) and the set of dependent variables (total sleep times, sleep onset latencys, wake time after sleep onsets, and sleep efficiencys as measured by sleep diaries). Objectively measured napping behavior s were not found to be significantly related to subjectively measured sleep quantity (Wilks = .92, p > .05). Nap Categories: Day and Evening Nappers versus Daytime Nappers (Subaim 1.3a) Based on a distribution within th e sample of 58% of the par ticipants engaging in both a daytime and evening nap, and 27% of the sample engaging solely in daytime naps, the participants were divided into two groups: 1) day and evening nappers and 2) daytime nappers. A comparison involving participan ts who solely napped during th e evening was not conducted as all of the participants who engaged in an evening nap al so napped during the day. A 2 (time of day of nap group) x 4 (object ively measured sleep quantity) MANOVA was performed to examine differences in objectiv ely measured sleep among the two nap groups. A MANOVA, as opposed to a univariate analysis of variance, was employed in the study since it adequately controls for the experimentwise erro r rate and takes into account the correlations among the dependent variables (Stevens, 1986). Separate MANOVAs were performed for each of the subaims as is recommended when the outcome variables are conceptually clustered (Stevens, 1986). There was a significant main eff ect for the nap groups [Wilks = .81, F (4, 77) = 4.82, p < .01, 2 = 0.19]. For the size of the effect, eta-square is roughly equivalent to the R2 used in

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48 multiple regression (Grimm & Ya rnold, 1995). According to C ohen (1977), for effect sizes measured via R2 or similar indices, an effect size of .09 is considered medium and an effect size of .25 or greater is considered large. Therefore, the eta-squa re of 0.19 suggests a medium maineffect for nap groups. Univariate tests revealed significant differences for sleep onset latencyo [ F (1, 80) = 4.37, p < .05, 2 = 0.05], wake time after sleep onseto [ F (1, 80) = 14.27, p < .001, 2 = 0.15], and sleep efficiencyo [ F (1, 80) = 12.01, p < .01, 2 = 0.13], see Table 5-3 for means and standard deviations. Individuals who na pped in the daytime and the even ing had significantly less sleep onset latency (21 minutes), less wake time afte r sleep onset (7 minutes), and greater sleep efficiency (5%) as measured by actigraphy co mpared to those who only napped during the daytime. The size of the effect for the univa riate tests ranged from small (for sleep onset latency) to medium (for wake time after sleep onset and for sleep efficiency). Nap Categories: Day and Evening Nappers versus Daytime Nappers (Subaim 1.3b) A 2 (time of day of nap group) x 4 (subjec tively measured sleep quantity) MANOVA was performed to examine differences in subjectiv ely measured sleep among the two nap groups. There was not a significant main effect for the nap groups [Wilks = .93, F (12, 222.535) = 0.50, p > .05, 2 = 0.25]. This result indicat es that there was not a si gnificant difference between the two nap groups (evening and daytime and daytim e nappers) in terms of their subjective sleep quantity (see Table 5-4 for mean s and standard deviations). Specific Aim 2 The second specific aim was to identify the di fferences between the four sleep subtypes (noncomplaining good sleepers, complaining good sleepers, noncomplaining poor sleepers, and complaining poor sleepers) in terms of their napping behavior.

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49 Sleep Subtypes and Objective Napping (Subaim 2.1a) A 4 (sleep subtype) x 3 (frequencyo, durationo, and time of dayo ) MANOVA was performed to examine differences in objectiv ely measured napping behavior among the four sleep subtypes. The multivariate main effect was non-significant [Wilks = .93, F (9, 228.92) = .78, p > .05, 2 = 0.02] indicating that the four sleep su btypes do not differ in terms of the frequencyo, durationo, and time of dayo of napping as measured by actigraphy. Sleep Subtypes and Subjective Napping (Subaim 2.1b) A 4 (sleep subtype) x 2 (subjectively measured napping behavior) MANOVA was performed to examine differences in subjectiv ely measured napping behavior among the four sleep subtypes. The multivariate effect was non-significant [Wilks = .97, F (6, 186) = .43, p > .05, 2 = 0.01] indicating that the four sleep subtypes do not signifi cantly differ in terms of the frequencys and durations of their naps as measured by sleep diaries.

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50 Table 5-1. Mean nap frequency, du ration, and time of day as measured by actigraphy and sleep diaries Nap variable M SD Minimum value Maximum value Nap frequencyo a 11.71 9.21 0 43.00 Nap frequencys a 4.26 3.31 0 10.00 Nap durationo b 12.44 1.96 0 17.00 Nap durations b 18.11 21.91 0 152.14 Time of day of napso 0.62 9.87E-02 .33 .95 aFrequency refers to the total numbe r of naps summed over 12 days bDuration refers to the average nap length

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51 Time of Day (24-hour clock)Percent of Total Number of Naps5:30 7:30 17:30 22:30 18:30 19:30 21:30 23:30 20:30 6:30 9:30 8:30 10:30 11:30 12:30 13:30 14:30 15:30 16:30 1:30 4:30 3:30 2:30 0:30Time of Day (24-hour clock)Percent of Total Number of Naps5:30 7:30 17:30 22:30 18:30 19:30 21:30 23:30 20:30 6:30 9:30 8:30 10:30 11:30 12:30 13:30 14:30 15:30 16:30 1:30 4:30 3:30 2:30 0:30 0 1 2 3 4 5 6 7 Figure 5-1. Percentage of total na ps taken by all participants that occurred during each half-hour interval of the 24-hour clock.

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52 Table 5-2. Correlations of sleep diary napping, actigraphy sleep, a nd sleep diary sleep variables with the canonical variate Variable Nappings and sleepo (subaim 1.1a) Nappings and sleeps (subaim 1.1b) Canonical structure coefficient Canonical coefficient Canonical structure coefficient Canonical coefficient Sleep Diary Napping frequencys -.72 -.00 .79 .16 durations -1.00 -1.00 .99 .88 Sleep Diary Sleep total sleep times -.89 -1.33 sleep onset latencys .07 .34 wake time after sleep onsets .15 .33 sleep efficiencys -.23 1.10 Actigraphy Sleep total sleep timeo .98 .72 sleep onset latencyo -.28 .12 wake time after sleep onseto .07 .55 sleep efficiencyo .49 .59 Note. Structure coefficients for aim 1.2a and 1.2b are omitted from this table because the canonical variate wa s not significant. Subscript s denotes subjectively measured va riables and subscript o denotes objectively measured variables.

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53 Table 5-3. Means and standard de viations for the time of day of nap groups for objective sleep Actigraphy sleep variables SOL WASO SE TST (minutes) Group M SD M SD M SD M SD Daytime naps 26.50* 13.01 72.82*** 24.65 76.80** 6.41 382 43.04 Daytime and evening naps 20.00* 12.28 51.43*** 21.99 81.95** 5.80 393 58.71 *p < .05. **p < .01. ***p < .001

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54 Table 5-4. Means and standard de viations for the time of day of nap groups for subjective sleep Sleep Diary sleep variables SOL WASO SE TST (minutes) Group M SD M SD M SD M SD Daytime naps 25.61 16.74 25.19 23.50 86.05 6.65 430 46.89 Daytime and evening naps 23.92 19.73 28.72 26.28 84.97 9.43 408 69.02

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55 CHAPTER 6 DISCUSSION The main focus of the study was to examine the relationship between subjectively and objectively measured napping and sleeping behavior in a sample of community-dwelling older adults. Although a number of prev ious studies have examined th is relationship, the association between napping and sleep remains unspecified. The present study sought to further define the relationship between napping and sleep by addres sing several methodological limitations of the previous research. These limitations were addressed through the in troduction of several innovations including: 1) the us e of both subjective and objectiv e measures of nap and sleep behavior, 2) capturing the inhere nt variability in sleep and na pping behavior with an extended data collection period, 3) examining multiple as pects of napping behavi or (frequency, duration, and time of day), and 4) using a classificati on of sleep subtypes, studying napping behavior simultaneously in both healthy individuals and th ose diagnosed with insomnia. The goal of the study was to further specify the relationship be tween napping and sleep through the use of the abovementioned innovations. A common theme that emerged during the study was the complexity of the relationship between objectively and subjectiv ely measured variables. Bo th objective (actigraphy) and subjective (sleep diary) measures were employe d for the napping and sleep variables. The multiple subaims of the study allowed for various combinations of the subjective and objective variables. Depending on the mode of study (obj ective or subjective), napping had a differential association with noc turnal sleep. The results suggest that the relationship between napping and sleep may be moderated by the mode of measurement. The differential results associated with objec tive and subjective measurement illustrate the differences between perceptions and objective asse ssment of sleep previous ly reported in the

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56 literature. Poor sleepers have both unde rreported (Lichstein and Johnson, 1991) and overestimated (Morin, 1993) their sleep problems in comparison to PSG results. The fact that poor sleepers can inaccura tely estimate thei r sleep problems suggests that the lack of correlation between objective and self-report measures may be due to an information processing issue rather than motivational factors (i.e. overestimating wake time in order to portray a severe sleep problem; Lichstein and Morin, 2000). The dis tinction between the pe rception and objective assessment of sleep is further illustrated by the diagnostic entity of sleep state misperception (American Sleep Disorders, 1997). This diagnosis as represented by the sleep subtype group of complaining good sleepers, involves complaints of insomnia without objec tive evidence of sleep problems. The existence of a condition such as sleep state misperception suggests that the experience of insomnia is affected both by pe rceptions of and the ex istence of objectively measured poor sleep. In fact, it has been suggested that unlike as ymptomatic diseases such as hypertension which require tests for verification, it is the complaint aspect of insomnia that is of interest to researchers and clinicians (Lichstein and Morin, 2000). The results from this study replicate previous results on the differences betw een subjective and objective assessment of sleep and extend the field of research to include diffe rences in the subjective and objective assessment of napping. The final chapter is organized in to four major sections. Firs t the results will be reviewed and interpreted for each of the studys specific aims. Second, the li mitations of the study will be considered. Third, the theoretical and clinical implications of the study will be presented. Finally, future research directions stemming from the findings of the study will be proposed. Review of Study Findings The main objective of the study was to ex amine the relationship between napping and sleep in a sample of community-dwelling older adults. This objectiv e was achieved through the

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57 analysis of objective (actigraphy) and subjective (sleep diary) measures of napping and sleep. The findings are discussed in terms of the two broader aims of the study and the associated subaims. In addition, descriptive analyses of th e characteristic napping behavior of the sample are discussed. Characteristics of Napping Behavior within the Sample In order to interpret further analyses of nappi ng behavior, it is helpful to first describe the characteristics of the naps taken by the sample. These characteristics were collected using both subjective and objective methods. For the objective assessment of napping, the participants, engaged in, on average, one nap per day (nap frequency), with an average nap duration of approximately 12 minutes. While the peak time of day for naps for the sample was between 8:30 and 9:00 p.m., the average time of day of naps was between 2:30 and 3:00 p.m. For the subjective assessment of napping, th e participants self-reported napping on average 4 out of the 12 days of assessment (nap frequency). The av erage self-reported nap duration was 18 minutes. Interestingly, there were significant differences between the subjective and objective measures of nap frequency and duration. A great er average frequency of napping was identified by actigraphy while a greater av erage duration of napping was reported by sleep diaries. The time of day of naps could not be compared acro ss subjective and objective data as only objective data was collected. In terms of nap frequency, the subjectively re ported average nap frequency of 4 naps over a twelve day period is consistent with previous ly reported results (Buys ee et al., 1992). The frequency of naps recorded us ing actigraphy (12 over a 12 day period) is considerably higher than previously reported results. A possible e xplanation for the significan tly higher frequency of naps assessed by actigraphy is that actigraphy ma y be capturing a greater number of evening naps than sleep diary. Yoon and colleague s (2003a) found only 22.6% of evening nappers

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58 reported their evening naps in their sleep diarie s. Additionally, large discrepancies in napping have been found between sleep diaries and PSG recordings (Jean-Louis, 2000). Corroborating these studies are anecdotal evidence from our partic ipants suggesting that they tend not to record brief evening naps as a nap on their sleep diary. Additionally, the lack of elevated nap frequenc ies in previous studies may be due to the fact evening nap frequencies were not reporte d by the researchers (Y oon et al., 2003a; Yoon et al., 2003b; Yoon et al., 2004). If this data had been reported, elev ated frequencies such as those captured in the present study may have been observed. In terms of nap duration, previous studies have reported average nap durations ranging from 23.3 to 45 minutes per day (Jean-Louis et al., 2000; Shirota et al., 2002; Yoon et al., 2003a; Yoon et al., 2004). The average nap durations reported both by object ive and subjective measures in this study are comparatively lower than previously reported results. An explanation for the much lower objectively measured average nap duration (12 minutes) is that the inclusion of evening naps (typically of shorter duration than daytime naps; Ancoli-Israel, 1985; Yoon, 2004;) would decrease the mean duration. While the sleep diary nap duration (18 minutes) is less than previously reported averages, it is st ill comparable to the lower range of average durations reported in the literat ure review (23.5 minutes). It is important to note that the subjective and objective duration va riables were measuring different constructs. While durationo as measured by actigraphy recorded the average duration for individual naps, durations as measured by sleep diaries reported the average daily duration for naps. The final nap variable that was measured was time of day of napping. Both an average time of day of naps (between 2:30 and 3:00 p.m.) and an alternate measure of time of day, the peak time of day of naps, were calculated. The peak time of day of naps (a calculation of the

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59 mode nap time of day for all naps of all participants) occurred between 8:30 and 9:00 p.m. This is consistent with previous studies that have f ound the evening to be the most characteristic time of day of napping for older samples (Ancoli-Isreal et al., 1985; Jean-Lou is et al., 2000; Yoon et al., 2003a, 2004). Therefore, this study replicates previous findings indicating evening naps are prevalent in older adults. Several theoretical explanations for the large number of evening naps within the sample exist. First, napping during the evening may represent an advance in circadian rhythms in older adults. Some older adults experience a phase advance resulting in ear lier bedtimes and earlier waketimes (Van Cauter, Leproult, & Kupfer, 1996; Van Coevorden et al., 1991; Yoon et al., 2003a). Therefore, out-of-bed sleep in the even ing could represent the start of the nocturnal sleep period for some older adults. An alternate explanation is that napping dur ing the evening may represent a weakening of the alerting signal from the suprachiasmatic nuc leus (Yoon et al., 2004). The suprachiasmatic nucleus is involved in generating a 24-hour rhythm for several bod ily functions, including sleep. Action potentials within the s uprachiasmatic nucleus fire in a 24-hour rhythym and reach a maximum firing at mid-day and then fall again at night. It is possible th at evening naps could result from a premature drop in the firing of actio n potentials within the suprachiasmatic nucleus. As a result, evening naps may occur because the altertness of the individual is being insufficiently maintained. Finally, it is possible that increased evening naps within the sample could reflect greater sleep needs or trait sleepiness. Each of these theoretical explanations fo r the prevalence of evening naps among the sample have different implications for nocturnal sleep. If the individual is experiencing a phase advance, napping in the evening could meet some of their nocturnal sl eep need and may be

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60 reflected in an earlier wake time and/or greater wake time after sleep onset. Similarly, if the individual naps during the eveni ng due to a decrease in alertne ss, the sleep may meet some of their nocturnal sleep need and re sult in greater wake time after sleep onset and/or earlier wake times. Alternatively, if evening naps are resultin g from greater sleep needs or trait sleepiness, by napping during the evening the individual could meet some of their sleep need without compromising their nocturnal sleep quality. Each of these explanations, or combinations of the explanations, could be implicated in the asso ciation between napping an d sleep reflecting the complexity of the relationship be tween napping and sleep behavior. Subjective Napping and Obj ective Sleep (Subaim 1.1a) Individuals who engaged in naps of shorter duration and engaged in naps less frequently had greater total sleep time and a higher sleep efficiency. Greater total sleep time and higher sleep efficiency are both indicative of improved nocturnal sleep quantity. This result is consistent w ith the hypothesis that subjec tive napping variables (frequencys and durations) would be most strongly co rrelated with the sleep quantit y variable of total time spent asleep. The hypothesis was non-directiona l because previous findings indicated that napping duration and frequency were both positivel y and negatively associated with nocturnal sleep. The current result supports the portion of pr ior findings that found higher frequencies (Hays et al., 1996; Monk, 2001) and longer durati on (Beh, 1994) of napping are associated with an increased risk of sleep complaint. Within the present sample the negative relationship between napping and sleep was replicated. Decreased napping (frequency and duration) was correlated with increased sleep quantity (total sleep time and sleep efficiency) Interestingly, the objective sleep variable of sleep efficiency was f ound to be significantly related to the napping va riables. Although this relationshi p was not accounted for in the hypothesis, the association makes sense conceptually. Sleep efficiency consists of a ratio of total

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61 time spent asleep to total time spent in bed. Cons idering that an increase in total sleep time was associated with a decrease in napping duration and frequency, it follows that sleep efficiency (which is composed in part from total sleep tim e) would also be implicated in the relationship between napping and sleep Subjective Napping and Subjective Sleep (Subaim 1.1b) As the frequency and duration of naps increase d, the total sleep time decreased. This result suggests that worse nocturnal sleep quantity as measured by sleep diaries is associated with increased napping (frequency and duration) as measured by sleep diaries. This result is consistent with the hypothesis that the napping vari ables (frequencys and durations) would be most strongly correlated with total sleep time. Additionally, the negative association between napping behaviors and nocturnal sleep demonstrated by this aim is consistent with previous research (Beh, 1994; Hays et al., 1996; Monk, 2001). Interestingly, the napping variables were not significantly associated with subjectively measured sleep efficiency, but were associated with objectively measured sleep efficiency. Using the same sample, McCrae and colleagues ( 2005) found that subjective measures of sleep efficiency were not significantly correlated with objective measures of sleep efficiency. The differences in the canonical va riates derived for subjective na pping and objective and subjective sleep may be the result of the differences be tween objectively measured and self-reported sleep Objective Napping and Objective Sleep (Subaim 1.2a) While subjectively measured napping was found to be significantly co rrelated with both objective and subjective sleep quantity, there was no significant rela tionship between the objective napping variables and obje ctive sleep quantity. This result is contrary to our hypothesis. While the direction of the relations hip between napping and sleep was not predicted, it was hypothesized that such a rela tionship would exist. The lack of a relationship is consistent

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62 with previous findings that have shown na p frequency (Bliwise, 1992; Buysee et al., 1992; Morin et al., 1989), duration (Aber & Webb, 1986), and both nap frequency and duration (Johnston, Landis, Lentz, & Shaver, 2001; Morga n, Healey, & Healey, 1989; Morin & Gramling, 1989) failed to differentiate be tween good and poor sleepers. Two likely explanations exist for the lack of relationshi p between objective napping and sleep. First, it is possible that the lack of significant interrelat ionships between these variables reflects a genuine lack of relationship between objectively measured daytime napping variables and objective sleep. As previous research has shown, several st udies have failed to detect a relationship between napping and sl eep. An alternative explanati on is that actigraphy, with the use of a novel application for an alyzing napping, is not a reliable measure of napping behavior. This methodological concern will be discusse d further under the lim itations portion of the discussion. Objective Napping and Subjective Sleep (Subaim 1.2b) Similar to the relationship between object ive napping and objective sleep, objectively measured napping was found to be unrelated to subjectively measured sleep. This result is inconsistent with the hypothesis that object ively measured napping would be significantly associated with subjectively measured total sleep tim e. This result is consistent with a number of studies that have faile d to find a significant relationship between nappi ng and sleep (Bliwise, 1992; Buysee et al., 1992; Mori n et al., 1989; Aber & Webb, 1986; Johnston, Landis, Lentz, & Shaver, 2001; Morgan, Healey, & Healey, 1989; Morin & Gramling, 1989). As suggested objective napping and objective sleep, the lack of findings may reflec t a genuine lack of relationship between objectively measured napping and sleep, or may be due to a methodological limitation associated with the use of actigraphy to assess napping behavior. It is problematic to make the assertion that napping is or is not as sociated with nocturnal sleep. The presence or

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63 absence of a relationship between napping a nd sleep appears to vary depending on the methodology of assessment used. The difference in the relationship between subjective and objective napping and sleep is further reinforced by the fact that while all of the subjective nap variables were significant, none of the objective nap variables were. Nap Categories: Day and Evening Nappers versus Daytime Nappers (Subaim 1.3a) Considering the difficulty in capturing vari able napping behavior with a single average time of day of naps variable, a categorical measur ement was used in addition to the analysis of a continuous measurement of time of day. Individuals were divide d into two groups those who napped during the daytime and those who napped during the daytime and evening. There was a significant difference found betw een those who napped during the day and those who napped both during the day and evening in terms of their objective sleep quantity. Essentially, those who napped during both the da y and evening had significantly less wake time during the night. On average, day and evening nappers fell asleep 21 minutes faster than day nappers and were awake for seven less minutes during the night. Additionally, day and evening nappers had higher average sleep efficiencies (5% higher) compared to day nappers. The reduced wake time during the night for those who napped during the day and evening suggests that these indivi duals had greater consolidation of nocturnal sleep compared to day nappers. This result is consistent w ith the hypothesis that objectiv e napping would be significantly associated with objective sleep. This result differs from those that were obtained for subaims 1.1a and 1.1b in that increases of the napping vari able (naps that occurre d both in the day and evening) was associated with improved sleep wh ereas the earlie r results suggested the opposite. This result also conflicts w ith conventional sleep hygiene re commendations that suggest individuals avoid napping altogeth er or restrict naps to befo re noon (Lichstein & Morin, 2000). The positive association between napping and slee p is consistent with previous literature

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64 (Arakawa et al., 2002; Buysee et al., 1992; Foely et al., 1995; Tanaka et al., 2002). This result is innovative in that for the first time nappers were divided into groups ba sed on the portion of the day (am/pm) that the naps occurred. Furthermore, the results are clinically significant in addition to being statistically significant. A decrease in the average time to fall asleep of 21 minutes and an increase in sleep efficiency of 5% can have clinical significance for elderly sleepers. An average wake time after sleep onset of greater than 31 minutes can result in a diagnosis of insomnia. Therefore, a decrease in sleep onset latency of 21 minutes could have a significant impact on an individuals sleep. Possible interpretations of this finding are 1) older adults who engaged in both daytime and evening naps do experience better objectively m easured nocturnal sleep and 2) the individuals who comprised the day and eveni ng nap group may have greater sleep needs or trait sleepiness. Interestingly, objectively meas ured napping was not significan tly related to objective or subjective sleep when it was analyzed as a cont inuous variable. The cat egorical approach to analyzing time of day of napping used in th is subaim may more accurately capture the differential association between ti me of day of napping and sleep. Nap Categories: Day and Evening Nappers versus Daytime Nappers (Subaim 1.3b) There was no significant difference between the day and evening and the day nap groups in terms of their subjective sleep. This result is not consistent with the hypothesis that napping would be significantly (positively or negatively) associated with sleep. While a lack of relationship between napping and sleep has been reported in previous studies (Bliwise, 1992; Buysee et al., 1992; Morin et al., 1989; Aber & Webb, 1986; Johnston, Landi s, Lentz, & Shaver, 2001; Morgan, Healey, & Heale y, 1989; Morin & Gramling, 1989), this result is surprising considering the significant asso ciation found in subaim 1.3a.

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65 Four Sleep Subtypes (Specific Aim 2) The second specific aim involve d identifying the differences between the four sleep subtypes (noncomplaining good sleepers, comp laining good sleepers, noncomplaining poor sleepers, and complaining poor sleepers) in terms of their napping behavior (frequencyo/s, durationo/s, and time of day of nappingo) as measured by actigraphy and sleep diaries. The four sleep subtypes did not di ffer in terms of the frequencyo/s, durationo/s, and time of day of nappingo. This aim was exploratory in that th e four sleep subtypes had not previously been studied in relation to napping behavior. He nce, an association between the sleep subtypes and the nap variables was not hypothesized. This aim allowed for the examination of a sl eep classification system (McCrae et al., 2005) in relation to napping. The sleep subtypes are unique in that they classify individuals based on both subjective quantitative and qualitative estimates of sleep. The results suggest that regardless of whether poor sleep is based on qualitative estimates of sleep (complaining good sleepers), or quantitative estimates of sleep (noncomplaining good sleepers), th ese different experiences of insomnia are not differentially asso ciated with the frequency, durati on, or time of day of naps. Study Limitations Limitations of the present study include restricted generalizability of re sults, an inability to determine the direction of th e association between napping and sleep, and methodological concerns. The use of a convenience sample re stricted the diversity of the sample. The participants were primarily European Caucasia n, college educated, a nd resided in their own homes. The homogeneity of the sample prevents reliable generalization to a diverse population. Additionally, individuals were ex cluded from the study if they presented with sleep disorders other than insomnia (e.g. sleep apnea, periodic leg movements). Approxima tely one half of the elderly population experience one or both of thes e conditions (Ancoli-Is rael, Kripke, Mason, &

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66 Kaplan, 1985). Previous research has exam ined the relationship between napping and respiration. Carskadon and colleagues (1982) ha ve found an association between nocturnal breathing disturbances and the degree of day time sleepiness. Buys ee and colleagues (1992) found no main effect of napping frequency on an index for sleep apnea (AHI) or for periodic limb movements. Unfortunately, the relationship between breathing disorders or periodic limb movements and napping could not be explored in the current study as individuals with these conditions were excluded from participating in the study. C onsequently, the results of the current study cannot be extended to a significant portion of the population diagnosed with other sleep complaints. Because the observations in the current study ar e derived from cross-sectional data it is impossible to make any causal conclusions about the relationship betw een napping and sleep. Although there are underlying biological mechan isms to explain the relationship between napping and sleep (circadian rhythm and homeost atic drive), these mechanisms may work bidirectionally. Hence, alt hough significant relationships be tween napping and sleep were observed, we cannot determine if this relationshi p is unidirectional (napping impacts sleep, sleep impacts napping) or bi-directional (napping and sleep both impact each other). Finally, noticeable differences in the rela tionship between napping and sleep were observed depending on the methodology used to study napping. While these differences may accurately reflect the relationshi p between napping and sleep, it is also possible that the observed differences may in part be due to methodologic al limitations of the napping measures. Two measures (objective and subjective) were employe d in the study. Strengths and weaknesses were associated with each measure. While actigra phy provides a sensitive measure of the individual napping behavior of each participan t, it is a novel approach that ha s not previously been applied

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67 to the study of napping behavior. Consequently, a limitation of the study is the use of a measure that has limited reliability data. Additionally, while many precautions were taken to prevent the misidentification of watch-off periods as na pping, it is possible that there were modest inaccuracies in the differentiation of wake/sleep periods. There ar e also limitations associated with the use of sleep diaries to assess napping behavior. Altho ugh sleep diaries are traditionally used to measure napping behavior, they have lim ited utility for assessing duration of napping and frequently, do not assess time of day of nappi ng, and result in the underreporting of evening naps. Implications Implications for Theory and Research A major implication for future research on napping and sleep involves the mode of measurement employed. This study was the first to compare multiple variables of napping and sleep using both subjective and objective meas ures. Accordingly, there were significant differences in the relationship between the c onstructs of napping and sleep depending on the mode of measurement (objectiv e and subjective). The findings show that the study of the relationship between napping and sleep is fu rther complicated by the methodology used. It would be helpful for future research to make a point of explicitly describing the methodology used and to recognize the strengths and weakne sses associated with each alternative. Clinical Implications In addition to exploring the theoretical a ssociation between napping and sleep, there are clinical implications for further defining this re lationship. The services provided by health care professionals are beginning to reflect the chan ging U.S. demographics. Currently, 68% of psychologists provide services to older adults (Qualls, Segal, Norman, Niederehe, & GallagherThompson, 2002). The existing number of psychologi sts providing services to older adults will

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68 need to more than double to meet the growing demands of the aging population (Gatz & Finkel, 1995). In order to effectively assess and treat ol der adults, clinicians will need to understand the age-related changes (e.g. difficulty sl eeping) that impact this population. Considering the prevalence of insomnia among ol der adults (15 65%), there is a need to develop and implement treatments that target th is disorder. Cognitive-behavioral treatments (CBT) are often employed to target insomnia in older adults. The restriction or elimination of napping behavior is a common element of the sl eep hygiene component of cognitive-behavioral treatments (CBT) for insomnia (Lichstein & Mori n, 2000). Interestingly, the empirical basis for this treatment recommendation is unclear. The results from the present study suggest that the relationship between napping and sleep va ries and a uniform recommendation to restrict/eliminate napping may not meet the needs of older adults with insomnia. Additionally, there are implications for the selection of m easures to assess napping behavior. The results suggest that differential relations hips between the clients nappi ng behavior and sleep could be revealed depending on the mode of m easurement (subjective or objective). Future Directions The results of the present study provide many po tential directions for future research. First, considering the role that methodology play ed in the study of napping and sleep, future research is needed in order to establish reliab ility data for both objective and subjective measures of napping. Second, future research could furthe r define the relationship between napping and sleep by examining the intraindividu al variability of napping and sleep data. It is possible that there are individual differences in the rela tionship between napping and sleep and these individual differences may explain the lack of consensus in the field re garding the relationship between daytime naps and sleep. Third, it would be helpful to examine the role of cognitions as a possible mediator of the relationship between napping and sleep. There are differing opinions

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69 as to the costs/benefits associated with daytim e napping. Additionally, cultural issues play a role (e.g. the siesta nap is considered a necessity in some cultures). A considerable amount of research has examined the role of cognitions in exacerbating insomnia among older adults. It would be helpful to extend this body of resear ch by examining the role of cognitions about napping and the subsequent impact of these cognitions on nocturnal sleep. Conclusions This study enabled the examination of th e relationship between napping and sleeping behaviors in a sample of community-dwelling olde r adults. Not unlike previous research, the findings from this study were mixed regardi ng the relationship between napping and sleep. Depending on the mode of measurement employed (subjective or objective) napping was found to be associated with impaired nocturnal sleep, improved nocturnal sleep, and found to be unrelated to nocturnal sleep. Additionally, the prevalence of evening naps within samples of older adults was replicated in the current study. A strength of the study was the unobtrusive assessment of the elderly participants within th eir home environment. The use of actigraphy as opposed to PSG preserved the ecologi cal validity of the study by allo wing participants to engage in their typical activities wh ile participating in the study.

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70 APPENDIX A EXAMPLE OF SLEEP DIARY ID# ______________ BASELINE TX___ POST-TX FOLLOW-UP_____ Please answer the fo llowing questionnaire WHEN YOU AWAKE IN THE MORNING Enter yesterday's day and date and provide the information to describe your sleep the night before. Definitions explaining each line of the questionnaire are given below. EXAMPLE yesterday's day yesterday's date TUES 10/14/97 day 1 day 2 day 3 day 4 day 5 day 6 day 7 1. NAP (yesterday) 70 2. BEDTIME (last night) 10:55 3. TIME TO FALL ASLEEP 65 4. # AWAKENINGS 4 5. WAKE TIME (middle of night) 110 6. FINAL WAKE-UP 6:05 7. OUT OF BED 7:10 8. QUALITY RATING* 2 9. BEDTIME MEDICATION (include amount & time) Halcion 0.25 mg 10:40 pm *Pick one number below to indicate your overall QUALITY RATING or satisfaction with your sleep. 1. very poor, 2. poor, 3. fair, 4. good, 5. excellent Figure A-1. Sleep Diary (Lic hstein, Riedel, & Means, 1999) used during the study.

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71 APPENDIX B HEALTH SURVEY

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75 Lichstein, K. L., Durrence, H. H., Riedel, B. W., Taylor, D. J., & Bush, A. J. (2004). Epidemiology of sleep: Age, gender, and ethnicity. Mahwah, NJ: Lawrence Erlbaum Associates, Publishers. Lichstein, K. L., Durrence, H. H., Taylor, D. J., Bush, A. J., & Riedel B. W. (2003). Quantitative criteria for insomnia. Behaviour Research and Therapy, 41 (4), 427-445. Lichstein, K. L. & Johnson, R. S. (1991). Older a dults objective self r ecording of sleep in the home. Behavior Therapy, 22, 531-548. Lichstein, K. L., Means, M. K., Noe, S. L ., & Aguillard, R. N. (1997). Fatigue and sleep disorders. Behavior Research and Therapy, 35 (8), 733-740. Lichstein, K. L., & Morin, C. M. (2000). Treatment of late-life insomnia Thousand Oaks, CA: Sage Publications, Inc. Lichstein, K. L., Riedel, B. W., & Means, M. K. (1999). Psychological treatment of latelife insomnia. In R. Schulz, G.Maddox, & P. Lawton (Eds.). Annual review of gerontology and geriatrics: Vol. 18. Focus on interventions research with older adults (pp. 74-110). New York: Springer Publishing Company. Lichstein, K. L., Wilson, N. M., Noe, S. L., Aguillard, R. N., & Bellue, S. N. (1994). Daytime sleepiness in insomnia: Behavi oral, biological and subjective indices. Sleep, 17, 693-702. McCrae, C. S., Rowe, M. A., Dautovich, N. D., Lichstein, K. L., Durrenc e, H. H., Riedel, B. W., Taylor, D. J., & Bush, A. J. (2005) Sleep hygiene practices in two community dwelling samples of older adults. McCrae, C. M., Rowe, M., Tierney, C., Dautovic h, N. D., Definis, A., & McNamara, J. (2005). Sleep complaints, subjective and objectiv e sleep patterns, he alth, psychological adjustment, and daytime functioning in community-dwelling older adults. The Journal of Gerontology: Psychological Sciences, 60B, 182-189. McCrae, C. S., Wilson, N. M., Lichstein, K. L., Du rrence, H. H., Taylor, D. J., Bush, A. J., & Riedel, B. W. (2003). Young old and old ol d poor sleepers with and without insomnia complaints. Journal of Psychosomatic Research, 54, 11-19. Mini Mitter Co., Inc. (2001). Actiwatch 16/ Actiwatch 64/ Ac tiwatch-L/ Actiwatch-Score instruction manual. Bend, OR: Mini Mitter Co., Inc. Monk, T. H., Buysse, D. J., Carrier, J., Billy, B. D., & Rose, L. R. (2001). Effects of afternoon siesta naps on sleep, alertness, performance, and circ adian rhythms in the elderly. Sleep, 24 680-687.

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79 BIOGRAPHICAL SKETCH Natalie Dautovich obtained her Bachelor of Arts degree with distinction at the University of Alberta in Edmonton, Alberta, Canada. She is currently enrolled in the doctoral program in counseling psychology through the Depa rtment of Psychology at the Un iversity of Florida. She is a member of the Sleep Research Lab.


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