The relationship between pain and disruptive behaviors in nursing home resident with dementia

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Title:
The relationship between pain and disruptive behaviors in nursing home resident with dementia
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Ahn, Hyochol
Horgas, Ann
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BioMed Central (BMC Geriatrics)
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Abstract:
Background: Nursing home residents with dementia gradually lose the ability to process information so that they are less likely to express pain in typical ways. These residents may express pain through disruptive behaviors because they cannot appropriately verbalize their pain experience. The objective of this study was to investigate the effect of pain on disruptive behaviors in nursing home residents with dementia. Methods: This is a secondary analysis of the Minimum Data Set (MDS 2.0) assessment data on long-term care from the state of Florida. The data used in this study were the first comprehensive assessment data from NH residents with dementia aged 65 and older (N = 56,577) in Medicare- or Medicaid-certified nursing homes between January 1, 2009 and December 31, 2009. Variables examined were pain, wandering, aggression, agitation, cognitive impairment, activities of daily living impairments, and demographic characteristics. Ordinal logistic regression was used to evaluate the effect of pain on disruptive behaviors. Results: Residents with more severe pain are less likely to display wandering behaviors (OR = .77, 95% CI for OR = 0.73, 0.81), but more likely to display aggressive and agitated behaviors (OR = 1.04, 95% CI for OR = 1.01, 1.08; OR = 1.17, 95% CI for OR = 1.13, 1.20). Conclusions: The relationship between pain and disruptive behaviors depends on the type of behaviors. Pain is positively correlated with disruptive behaviors that do not involve locomotion (e.g., aggression and agitation), but negatively related to disruptive behaviors that are accompanied by locomotion (e.g., wandering). These findings indicate that effective pain management may help to reduce aggression and agitation, and to promote mobility in persons with dementia. Keywords: Disruptive behaviors, Pain, Dementia, Nursing home
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Publication of this article was funded in part by the University of Florida Open-Access publishing Fund. In addition, requestors receiving funding through the UFOAP project are expected to submit a post-review, final draft of the article to UF's institutitonal repository, IR@UF, (www.uflib.ufl.edu/UFir) at the time of funding. The institutional Repository at the University of Florida community, with research, news, outreach, and educational materials.
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Ahn and Horgas BMC Geriatrics 2013, 13:14 http://www.biomedcentral.com/1471-2318/13/14; Pages 1-7
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doi:10.1186/1471-2318-13-14 Cite this article as: Ahn and Horgas: The relationship between pain and disruptive behaviors in nursing home resident with dementia. BMC Geriatrics 2013 13:14.

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dochead Research article
bibl
title
p The relationship between pain and disruptive behaviors in nursing home resident with dementia
aug
au id A1 ca yes snm Ahnfnm Hyocholinsr iid I1 email hcahn@ufl.edu
A2 HorgasAnnahorgas@ufl.edu
insg
ins Department of Adult and Elderly Nursing, College of Nursing, University of Florida, Gainesville, FL, 32610-0197, USA
source BMC Geriatrics
section Neurology, stroke and cognitionissn 1471-2318
pubdate 2013
volume 13
issue 1
fpage 14
url http://www.biomedcentral.com/1471-2318/13/14
xrefbib pubidlist pubid idtype doi 10.1186/1471-2318-13-14pmpid 23399452
history rec date day 18month 8year 2012acc 522013pub 1122013
cpyrt 2013collab Ahn and Horgas; licensee BioMed Central Ltd.note This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/2.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
kwdg
kwd Disruptive behaviors
Pain
Dementia
Nursing home
abs
sec
st
Abstract
Background
Nursing home residents with dementia gradually lose the ability to process information so that they are less likely to express pain in typical ways. These residents may express pain through disruptive behaviors because they cannot appropriately verbalize their pain experience. The objective of this study was to investigate the effect of pain on disruptive behaviors in nursing home residents with dementia.
Methods
This is a secondary analysis of the Minimum Data Set (MDS 2.0) assessment data on long-term care from the state of Florida. The data used in this study were the first comprehensive assessment data from NH residents with dementia aged 65 and older (N = 56,577) in Medicare- or Medicaid-certified nursing homes between January 1, 2009 and December 31, 2009. Variables examined were pain, wandering, aggression, agitation, cognitive impairment, activities of daily living impairments, and demographic characteristics. Ordinal logistic regression was used to evaluate the effect of pain on disruptive behaviors.
Results
Residents with more severe pain are less likely to display wandering behaviors (OR = .77, 95% CI for OR = [0.73, 0.81]), but more likely to display aggressive and agitated behaviors (OR = 1.04, 95% CI for OR = [1.01, 1.08]; OR = 1.17, 95% CI for OR = [1.13, 1.20]).
Conclusions
The relationship between pain and disruptive behaviors depends on the type of behaviors. Pain is positively correlated with disruptive behaviors that do not involve locomotion (e.g., aggression and agitation), but negatively related to disruptive behaviors that are accompanied by locomotion (e.g., wandering). These findings indicate that effective pain management may help to reduce aggression and agitation, and to promote mobility in persons with dementia.
bdy
Background
Pain assessment in nursing home (NH) residents with dementia is challenging due to cognitive and communicative impairments. Pain self-report, the gold standard assessment in cognitively intact persons, is questionable in cognitively impaired NH residents because dementia impairs their ability to remember, interpret, and respond to pain abbrgrp
abbr bid B1 1
B2 2
. NH residents with dementia gradually lose the ability to process information so that they are less likely to express pain in typical ways, even when there is a probable cause for pain
1
. Therefore, pain is often under-reported in NH residents with dementia. These residents may express pain through disruptive behaviors
B3 3
, because they cannot appropriately verbalize their pain experience.Disruptive behaviors, also known as “problematic behaviors,” “disturbing behaviors,” or “challenging behaviors,” refer to inappropriate, repetitive, or dangerous behaviors that are disruptive to the living and working environment in the NH
B4 4
B5 5
. Among many disruptive behaviors, three behaviors are most prominent in the current literature: wandering behaviors, aggressive behaviors, and agitated behaviors
B6 6
B7 7
. Wandering occurs in approximately 40 to 60% of NH residents with dementia
B8 8
, and aggression and agitation occurs in about 50% to 80% of NH residents with cognitive impairments
B9 9
.Disruptive behaviors are problematic to NH residents and staff. Disruptive behaviors are associated with injuries and hospitalizations among NH residents with dementia, and contribute to stress and burnout among caregivers
B10 10
B11 11
. The cost of care for NH residents with dementia is three times higher than that of other NH residents, and about 30% of these costs are attributed to the management of disruptive behaviors
B12 12
. Psychoactive medications or restraints are often used to manage disruptive behaviors
B13 13
; however, these often lead to falls, impaired functioning, and decreased mobility. The use of restraints is also an affront to personal dignity. The better approach to managing disruptive behaviors is to control their possible causes, such as pain.Thus, the purpose of this study is to explore the relationship between pain and disruptive behaviors in NH residents with dementia. Such information may identify potential new intervention approaches for managing these behaviors.
Theoretical framework
The Need-driven Dementia-compromised Behavior (NDB) model
B14 14
was used to guide this study of the relationship between pain and disruptive behaviors in NH residents with dementia (Figure figr fid F1 1). The NDB model posits two main constructs that are associated with dementia-compromised behaviors: background factors and proximal factors. Background factors represent those characteristics that place older adults at risk for disruptive behaviors. Proximal factors represent the conditions under which disruptive behaviors occur. We conceptualized pain as a proximal factor that would have a direct relationship with disruptive behaviors (e.g., wandering, aggression, and agitation). For this study, the level of cognitive impairment, activities of daily living (ADL) impairment, and demographic characteristics (e.g., age and sex) represent background factors. These variables were selected as covariates because they have established relationships with both pain and disruptive behaviors
B15 15
B16 16
B17 17
B18 18
and may influence the relationship between pain and disruptive behaviors.
fig Figure 1caption Theoretical framework adapted from the Need-driven Dementia-compromised Behavior (NDB) modeltext
b Theoretical framework adapted from the Need-driven Dementia-compromised Behavior (NDB) model.
graphic file 1471-2318-13-14-1
Methods
This is a secondary analysis of the nursing home Minimum Data Set (MDS) from the state of Florida during calendar year 2009. The first comprehensive assessment for each NH resident was used in this study. The archived data files of the most recent version of MDS (MDS 3.0) were not yet available to researchers, but are due for release in early 2013
B19 19
. The MDS data are mandatory in all NHs certified to participate in Medicare and Medicaid. Approval for the study was obtained from the University of Florida Health Science Center Institutional Review Board.The MDS assessment data, standardized data on residents’ status based on routine and continuous observations by nursing staff, provides comprehensive information on all the NH residents. The MDS assessment is completed on admission to the facility, on a quarterly basis thereafter, and upon significant changes in status
B20 20
. The complete federal database consists of over 1.5 million older adults who live in NHs throughout the United States. Although it is used primarily for clinical purposes, the MDS has also been used for research on cognition and behavioral symptoms in this population
B21 21
B22 22
B23 23
. Several MDS subscales have been created and evaluated, and have demonstrated acceptable reliability and validity: MDS-Pain severity scale
B24 24
, MDS-Depression Rating Scale
B25 25
, MDS-Aggression Behavior Scale
B26 26
, MDS-Challenging Behavior Profile
B27 27
, MDS-Discomfort Behavior Scale
B28 28
, MDS-Cognitive Performance Scale
28
B29 29
, MDS-index of social engagement
B30 30
B31 31
, MDS-Activities of Daily Living scale
B32 32
B33 33
, Resident Assessment Instrument-Mental Health
B34 34
, and MDS-Change in Health, End-stage disease and Signs and Symptoms
B35 35
. Details of the reliability and validity coefficients for each of the major study variables are described in the measurement section.
Data used in this study
The data used in this study were collected on residents with dementia in Medicare- or Medicaid-certified NHs who have a MDS comprehensive assessment on file. The data were acquired from the Centers for Medicare & Medicaid Services. Selection criteria were applied to ascertain data from NH residents older than 65 years old with Alzheimer’ disease or other dementia, based on documented medical diagnosis. Data from comatose residents were excluded, because these residents cannot display the disruptive behaviors investigated in this study. This selection process yielded 56,577 unique cases for the analyses.The sample is mostly female (67.7%), and a mean age of 84 (years range = 65–109). The prevalence of disruptive behaviors is as follows: wandering behaviors (9.0%), aggressive behaviors (24.4%), and agitated behaviors (24.1%) (Table tblr tid T1 1).
table
Table 1
Sample characteristics
tgroup align left cols 3
colspec colname c1 colnum 1 colwidth 1*
center c2 2
c3
thead valign top
row rowsep
entry
Characteristic
Number
Total sample
tfoot
it MDS-CPS = MDS-Cognitive Performance Scale.
MDS-ADL = MDS-Activities of Daily Living impairment scale.
MDS-ABS = MDS-Aggression Behavior Scale.
Revised MDS-CBP agitation = revised MDS-Challenging Behavior Profile, agitation subscale.
tbody
Age, mean ± SD
56577
84.37 ± 7.43
Gender, n (%)
56566
  Male
18,265 (32.3)
  Female
38,301 (67.7)
MDS-CPS, mean ± SD
56543
3.17 ± 1.52
MDS-ADL, mean ± SD
56577
18.66 ± 6.41
Pain severity, mean ± SD
56568
0.48 ± 0.70
Wandering behaviors, n (%)
56573
  No wandering (MDS-wandering = 0)
51,463 (91.0)
  1-3 days in 7 days (MDS-wandering = 1)
2,637 (4.7)
  4-6 days in 7 days (MDS-wandering = 2)
994 (1.8)
  Wandering daily (MDS-wandering = 3)
1,479 (2.6)
Aggressive behaviors, n (%)
56572
  None (MDS-ABS = 0)
42,764 (75.6)
  Moderate (MDS-ABS = 1 – 2)
9,667 (17.1)
  Severe (MDS-ABS = 3 – 5)
3,390 (6.0)
  Very severe (MDS-ABS = 6 – 12)
751 (1.3)
Agitated behaviors, n (%)
56571
  None (revised MDS-CBP agitation = 0)
42,941 (75.9)
  Mild (revised MDS-CBP agitation = 1)
6,916 (12.2)
  Moderate (revised MDS-CBP agitation = 2)
5,099 (9.0)
  Severe (revised MDS-CBP agitation = 3)
1,615 (2.9)
Measurement
MDS subscales and items were used to indicate the main study concepts: pain, wandering, aggression, and agitation. These are described below.
Pain
The MDS-pain severity scale
24
, combining both pain frequency (0 = no pain, 1 = pain less than daily, and 2 = pain daily) and pain intensity (1 = mild pain, 2 = moderate pain, and 3 = horrible or excruciating pain), was used to assess pain severity in NH residents with dementia. This scale can range from 0 to 3, with higher scores indicating greater pain severity. NH residents’ self-report is reflected in the MDS pain items if residents can self-report and staff completing the MDS assessments have confidence in residents’ self-report. Otherwise, the staff who complete the MDS assessment document pain symptoms based on proxy reports from facility nursing staff that provides care to the residents. The MDS-pain severity scale has been reported to have an inter-rater reliability coefficient of 0.73, and kappa coefficient of 0.70 with a Visual Analogue Scale in a study involving 95 U.S. nursing home residents at 25 Medicare-certified skilled nursing facilities in Massachusetts
24
.
Disruptive behaviors
The MDS-wandering item was used to measure the frequency of wandering in the last 7 days. Wandering frequency is recorded by staff observation. It is recorded as no wandering, wandering occurred 1 to 3 days, wandering occurred 4 to 6 days, and daily wandering. The wandering item has been reported to have a reliability coefficient of 0.63, and an inter-rater reliability of 0.95
B36 36
B37 37
.The MDS-Aggression Behavior Scale (MDS-ABS) was used to measure the frequency of aggressive behaviors. The MDS-ABS is a sum score of four MDS items: verbally abusive behavioral symptoms, physically abusive behavioral symptoms, socially inappropriate behavioral symptom, and resisting care. The MDS-ABS can range from 0 to 12, with higher scores indicating more frequent aggressive behaviors. The MDS-ABS has been reported to have an internal consistency reliability of 0.79 to 0.95, and a criterion validity coefficient of 0.72 with Cohen-Mansfield Agitation Inventory aggression subscale scores
26
.The revised MDS-Challenging Behavior Profile (MDS-CBP) agitation subscale was used to assess the frequency of agitated behaviors. The revised agitation scores, calculated using two MDS items (e.g., periods of restlessness and repetitive physical movements), can range from 0 to 3, with higher scores indicating more frequent agitated behaviors. This revised agitation scale has Cronbach’s alpha coefficient of .68. The original MDS-CBP agitation subscale, computing from 4 MDS items (e.g., periods of restlessness, repetitive physical movements, wandering, and socially inappropriate behavioral symptom), has been reported to have Cronbach’s alpha coefficient of 0.70, inter-rater reliability of 0.61, and a Spearman’s rank correlation coefficient of 0.50 with Behavior Rating Scale for Psychogeriatric Inpatients
27
.
Background factors
The MDS-cognitive performance scale (MDS-CPS)
B38 38
was used to measure the level of cognitive impairment. The MDS-CPS score is calculated using five MDS items: comatose, short-term memory, cognitive skills or daily decision making, making oneself understood, and self-performance in eating. The MDS-CPS can range from 0 to 6, with higher scores indicating more cognitive impairment. The MDS-CPS has been reported to have a kappa coefficient of 0.45-0.75 with Mini-Mental State Examination, a kappa coefficient of 0.41-0.77 against Global Deterioration Scale, a kappa coefficient of 0.66 against Psychogeriatric Dependency Rating Scale, a kappa coefficient of 0.45 against Mattis Dementia Rating Scale
29
38
B39 39
B40 40
B41 41
.The MDS-Activities of Daily Living-Long Form (MDS ADL-Long Form)
B42 42
was used to measure the level of ADL impairment. The MDS ADL-Long Form scores are calculated using 7 MDS items: self-performance of bed mobility, transfer, locomotion on unit, dressing, eating, toilet use, and personal hygiene. MDS ADL-Long Form can range from 0 to 28, with higher scores indicating more impairment of ADLs. The MDS ADL-Long Form has been reported to have a reliability coefficient of 0.92-0.97, an inter-rater reliability coefficient of 0.61-0.95, and a kappa coefficient of 0.58 – 0.79 against Physical Self-Maintenance Scale
31
B43 43
.Demographics characteristics (e.g., age and gender) were collected from the MDS form. Age was a continuous variable and gender was dichotomous (0 = female; 1 = male). They were included as covariates in the analyses.
Statistical analysis
Analyses were performed using SPSS, version 20 (IBM Inc., Armonk, NY). Multivariate analyses were conducted to explore the relationship between pain and disruptive behaviors in this sample. Aggression was severely positively skewed, and none of the transformations (e.g., logarithmic transformation, square root transformation, inverse transformation, and square transformation) resolved the normal distribution issue. Therefore, aggression was collapsed into four groups (none, moderate, severe, and very severe), based on published algorithms in the literature
26
. Aggression was transformed as none (MDS-ABS = 0), moderate (MDS-ABS = 1–2), severe (MDS-ABS = 3–5), and very severe (MDS-ABS = 6–12). Due to concerns that NH residents who take psychotropic medications (e.g., antipsychotics, antidepressants, etc.) may exhibit less frequent disruptive behaviors
B44 44
, we re-ran the statistical analysis excluding these subjects.Since the level of measurement of the dependent variables was ordinal, logistic regression for ordinal variables was used to evaluate the effect of pain severity on the three disruptive behaviors, after controlling for covariates. Using the same independent variables in analysis with different dependent variables carries the risk of inflating the Type I error. To keep the overall risk of a Type I error to the 5% level, p-value for the each regression analysis is set at .017.
Results
The results of ordinal logistic regression on three disruptive behaviors, after controlling for covariates (e.g., the level of cognitive impairment, the level of ADL impairment, and sociodemographic factors) are described below.
The effect of pain on wandering behaviors
Pain severity is negatively associated with the frequency of wandering behaviors (Table T2 2). NH residents with more severe pain are less likely to display wandering behaviors (Logistic regression coefficient = −0.26, p < .001, Odds Ratio = .77, 95% CI for Odds Ratio = [0.73, 0.81]).
Table 2
Predicting disruptive behaviors from pain severity, after controlling for covariates (N = 56,577)
10
c4 4
c5 5
c6 6
c7 7
c8 8
c9 9
c10
morerows
Variables
nameend namest
Wandering
Aggression
Agitation
B
OR
95% CI for OR
B
OR
95% CI for OR
B
OR
95% CI for OR
Nagelkerke R-square: Wandering = 0.15, Aggression = 0.06, Agitation = 0.08. B = logistic regression coefficient, OR = Odds Ratio = Exp(B). MDS-CPS = MDS-Cognitive Performance Scale. MDS-ADL = MDS-Activities of Daily Living impairment scale. sup *
p < .001.
Independent Variable
  Pain
−0.26*
0.77
[0.73, 0.81]
0.04*
1.04
[1.01, 1.08]
0.15*
1.17
[1.13, 1.20]
Covariates
  MDS-CPS
0.68*
1.97
[1.91, 2.02]
0.36*
1.43
[1.41, 1.46]
0.46*
1.58
[1.55, 1.60]
  MDS-ADL
−0.15*
0.87
[0.86, 0.87]
−0.03*
0.98
[0.97, 0.98]
−0.02*
0.98
[0.97, 0.98]
  Age
−0.01*
0.99
[0.98, 0.99]
−0.01*
0.99
[0.99, 0.99]
−0.01*
0.99
[0.99, 0.99]
  Sex
    Male
0.22*
1.25
[1.17, 1.33]
0.28*
1.33
[1.27, 1.39]
0.24*
1.27
[1.22, 1.33]
    Female
0.00
1.00
0.00
1.00
1.00
The effect of pain on aggressive behaviors
Pain severity is positively associated with the frequency of aggressive behaviors (Table 2). NH residents with more severe pain are more likely to display aggressive behaviors (Logistic regression coefficient = 0.04, p < .001, Odds Ratio = 1.04, 95% CI for Odds Ratio = [1.01, 1.08]).
The effect of pain on agitated behaviors
Pain severity is positively associated with the frequency of agitated behaviors (Table 2). NH residents with more severe pain are more likely to display agitated behaviors (Logistic regression coefficient = 0.15, p < .001, Odds Ratio = 1.17, 95% CI for Odds Ratio = [1.13, 1.20]).
The study results in subsample without psychotropic medications
The results of ordinal logistic regression in the subsample without psychotropic medications (e.g., antipsychotics, antidepressants, etc.) are summarized in Table T3 3. These results of ordinal logistic regression are similar when NH residents who used psychotropic medications in the past 7 days were excluded. Pain severity is negatively associated with the frequency of wandering behaviors, but positively associated with the frequency of aggressive and agitated behaviors.
Table 3
The study results in subsample without psychotropic medications (N = 17,435)
Variables
Wandering
Aggression
Agitation
B
OR
95% CI for OR
B
OR
95% CI for OR
B
OR
95% CI for OR
Nagelkerke R-square: Wandering = 0.13, Aggression = 0.03, Agitation = 0.05. B = logistic regression coefficient, OR = Odds Ratio = Exp(B). MDS-CPS = MDS-Cognitive Performance Scale. MDS-ADL = MDS-Activities of Daily Living impairment scale. *
p < .001. **
p < .05.
Independent Variable
  Pain
−0.33*
0.72
[0.63, 0.83]
0.07**
1.07
[1.01, 1.15]
0.15*
1.16
[1.08, 1.25]
Covariates
  MDS-CPS
0.63*
1.87
[1.76, 2.00]
0.29*
1.34
[1.29, 1.38]
0.42*
1.53
[1.47, 1.58]
  MDS-ADL
−0.15*
0.86
[0.85, 0.87]
−0.04*
0.97
[0.96, 0.97]
−0.04*
0.96
[0.96, 0.97]
  Age
0.00
1.00
[0.99, 1.01]
0.01*
1.01
[1.00, 1.02]
0.00
1.00
[1.00, 1.01]
  Sex
    Male
0.12
1.12
[0.96, 1.31]
0.19*
1.21
[1.10, 1.33]
0.22*
1.24
[1.13, 1.37]
    Female
0.00
1.00
0.00
1.00
1.00
Discussion
It was found that more severe pain is associated with less frequent wandering behaviors, but more frequent aggressive and agitated behaviors, after controlling for covariates. Most of the published literature suggested that there is a positive relationship between pain and disruptive behaviors in general
6
11
B45 45
. However, the results of this study suggest that the relationship between pain and disruptive behaviors depends on the type of behaviors examined. The direction of the relationship between these variables depends on whether the disruptive behaviors are accompanied by locomotion. Pain is positively correlated with disruptive behaviors that do not involve locomotion (e.g., aggression and agitation), but negatively related to disruptive behaviors that are accompanied by locomotion (e.g., wandering). That is, residents who experience more severe pain are more likely to display aggression and agitation, and less likely to move around.The finding that pain and aggressive or agitated behaviors are positively linked in NH residents with dementia is consistent with other published reports. Buffum and colleagues
B46 46
reported that pain was positively related to agitation (r = .50, p = .003) using a bivariate correlation analysis in 33 Veterans Affairs NH residents with dementia. Manfredi and colleagues
B47 47
demonstrated that opioid treatment for pain reduced agitation in 13 NH residents with dementia who were more than 85 years old (mean change in CMAI score: -6.4, 95% CI [−10.96, -1.8]). Both of these studies have a small sample size. Thus, the results of this study using a large sample from all the nursing home residents with dementia in the state of Florida substantiates and extends the positive relationship between pain and non-locomotive disruptive behaviors from these previous findings.In contrast, the finding on the relationship between pain and wandering behavior in this study is opposite to the findings presented in the literature review. Kiely and colleagues
B48 48
used MDS assessment data from 8,982 NH residents, and reported that NH residents who expressed sadness or pain in MDS assessment data were 65% more likely to develop wandering behaviors than their counterparts who did not express sadness or pain (OR = 1.65, p = .02). Our study measured pain more specifically using the MDS-pain severity scale
24
, combining both pain frequency and pain intensity, while Kiely and the colleagues
48
measured pain by a dichotomized expression of sadness or pain. Sadness is not typically considered an indicator of pain, and its inclusion may have confounded pain and depression or mood disorder.Several limitations of this study should be noted. First, this study is inherently limited by secondary analysis of federally mandated MDS assessment data, and the effect of clustering within facility is not controlled in this study. The variables and the procedures cannot be controlled. The MDS assessment data may have some variability due to different styles and skills of MDS coordinators in each facility. Second, the role of pain medications is not considered in this study. The highest level of pain could have been managed by pain medications, but it is not possible to discern this in the MDS assessment data. However, similar to our study, most of the literature reported the relationship between highest level of pain and the frequency of behavioral symptoms during the observation period without controlling for pain medications
11
B49 49
. Third, the amount of variance in disruptive behaviors that is explained by these logistic regression models is small (ranging from 6% to 15%). This suggests that there are other factors that contribute to disruptive behaviors that were not specified in our models. Finally, this study design is descriptive and cross-sectional. As such, this study is not able to examine causal relationships between pain and disruptive behaviors.Findings from this study can be a foundation for future research. Studies using prospective designs are needed to validate these findings. Also, randomized controlled trials can be used to compare comprehensive pain management and usual pain management with regard to the frequency of disruptive behaviors. This type of study can provide evidence for causal relationships between pain management and disruptive behaviors and support changes in clinical practice. Third, future research would include the longitudinal MDS assessment data to examine trends over time. The longitudinal nature of MDS assessment data, collected every three months or more often, provides an opportunity to describe change over time, and facilitates the use of more powerful statistical analysis techniques to describe both within- and between-person changes.
Conclusions
Pain exacerbated disruptive behaviors that are not locomotion-based. In order to reduce these disruptive behaviors, their underlying causes, such as pain, should be investigated and well managed. However, pain assessment in cognitively impaired residents can be challenging. Comprehensive pain assessment should be developed further, and pain should be well controlled to reduce these problematic disruptive behaviors.
Abbreviations
ADL: Activities of daily living; MDS: Minimum data set; MDS-ABS: MDS-Aggression behavior scale; MDS-CBP: MDS-Challenging behavior profile; MDS-CPS: MDS-Cognitive performance scale; NH: Nursing home.
Competing interests
The authors have no financial or any other kind of personal conflicts with this manuscript. This study was supported by Grant award from Sigma Theta Tau Alpha Theta Chapter.
Authors’ contributions
HA conceptualized the study, completed all statistical analyses, and wrote the manuscript. AH provided oversight and consultation during all aspects of the study. Both authors read and approved the final manuscript.
bm
refgrp Pain assessment in persons with dementia: Relationship between self-report and behavioral observationHorgasAElliottAFMarsiskeMJ Am Geriatr Soc2009571126lpage 13210.1111/j.1532-5415.2008.02071.xpmcid 2712941link fulltext 19054191The adequacy of the minimum data set assessment of pain in cognitively impaired nursing home residentsCohen-MansfieldJJ Pain Symptom Manage200427434335110.1016/j.jpainsymman.2004.01.00115050662Behavioral cues to expand a pain model of the cognitively impaired elderly in long-term careBurfieldAHWanTTSoleMLCooperJWClin Interv Aging20127207223339605022807630The serial trial intervention: an innovative approach to meeting needs of individuals with dementiaKovachCRNoonanPESchlidtAMReynoldsSWellsTJ Gerontol Nurs2006324182516615709The implementation of the serial trial intervention for pain and challenging behaviour in advanced dementia patients (STA OP!): a clustered randomized controlled trialPieperMJAchterbergWPFranckeALvan der SteenJTScherderEJKovachCRBMC Geriatr20111111210.1186/1471-2318-11-12307232821435251Awareness and behavioral problems in dementia patients: a prospective studyAaltenPvan ValenEde VugtMELousbergRJollesJVerheyFRInt Psychogeriatr200618131710.1017/S104161020500277216388704Dangerous wandering: elopements of older adults with dementia from long-term care facilitiesAudMAAm J Alzheimers Dis Other Demen200419636136810.1177/15333175040190060215633945Ethnic differences in the prevalence and pattern of dementia-related behaviorsSinkKMCovinskyKENewcomerRYaffeKJ Am Geriatr Soc20045281277128310.1111/j.1532-5415.2004.52356.x15271114Documentation, assessment, and treatment of aggression in patients with newly diagnosed dementiaKunikMEWalgamaJPSnowALDavilaJASchulzPESteeleABMorganROAlzheimer Dis Assoc Disord200721211512110.1097/WAD.0b013e318065c4ba17545736Consequences of aggressive behavior in patients with dementiaKunikMESnowALDavilaJAMcNeeseTSteeleABBalasubramanyamVDoodyRSchulzPEKalavarJSWalderAMorganROJ Neuropsychiatry Clin Neurosci2010221404710.1176/appi.neuropsych.22.1.4020160208Predictors of need-driven behaviors in nursing home residents with dementia and associated certified nursing assistant burdenNortonMJAllenRSSnowALHardinJMBurgioLDAging Ment Health201014330330910.1080/13607860903167879204256492011 Alzheimer’s Disease facts and figures
http://www.alz.org/downloads/Facts_Figures_2011.pdf
Management of the behavioral and psychological symptoms of dementiaHerschECFalzgrafSClin Interv Aging200724611621268633318225462Need-driven dementia-compromised behavior: An alternative view of disruptive behaviorAlgaseDLBeckCKolanowskiAWhallABerentSRichardsKBeattieEAm J Alzheimers Dis Other Demen1996116101910.1177/153331759601100603A longitudinal examination of agitation and resident characteristics in the nursing homeBurgioLDParkNSHardinJMSunFGerontologist200747564264910.1093/geront/47.5.64217989406Verbal and physical non-aggressive agitated behaviors in elderly persons with dementia: Robustness of syndromesCohen-MansfieldJLibinAJ Psychiatr Res200539332533210.1016/j.jpsychires.2004.08.00915725431Disparities in pain management between cognitively intact and cognitively impaired nursing home residentsReynoldsKSHansonLCDeVellisRFHendersonMSteinhauserKEJ Pain Symptom Manage200835438839610.1016/j.jpainsymman.2008.01.00118280101The multidimensional experience of noncancer pain: Does cognitive status matter?ShegaJWErsekMHerrKPaiceJARockwoodKWeinerDKDaleWPain Medicine201011111680168710.1111/j.1526-4637.2010.00987.x21044258Long Term Care Minimum Data Set 3.0
http://www.resdac.org/cms-data/files/mds-3.0
Use of proxy respondents and accuracy of minimum data set assessments of activities of daily livingLumTYLinW-CKaneRLJ Gerontol A Biol Sci Med Sci200560565465910.1093/gerona/60.5.65415972620Long-term effects of analgesics in a population of elderly nursing home residents with persistent nonmalignant painWonALapaneKLVallowSScheinJMorrisJNLipsitzLAJ Gerontol A Biol Sci Med Sci200661216516910.1093/gerona/61.2.165227658516510860Using the minimum data set to determine predictors of terminal restlessness among nursing home residentsLeeFPLeppaCScheppKJ Nurs Res200614428629610.1097/01.JNR.0000387588.12340.d117345758Measuring change in activities of daily living in nursing home residents with moderate to severe cognitive impairmentCarpenterGIHastieCLMorrisJNFriesBEAnkriJBMC Geriatr200661810.1186/1471-2318-6-1137964716403236Pain in U.S. Nursing homes: validating a pain scale for the minimum data setFriesBESimonSEMorrisJNFlodstromCFlodstromCBooksteinFLGerontologist200141217317910.1093/geront/41.2.17311327482Development of an minimum data set-based depression rating scale for use in nursing homesBurrowsABMorrisJNSimonSEHirdesJPPhillipsCAge Ageing20002916517210.1093/ageing/29.2.16510791452The aggressive behavior scale: a new scale to measure aggression based on the minimum data SetPerlmanCMHirdesJPJ Am Geriatr Soc200856122298230310.1111/j.1532-5415.2008.02048.x19093929The MDS challenging behavior profile for long-term careGerritsenDLAchterbergWPSteverinkNPotAMFrijtersDHRibbeMWAging Ment Health200812111612310.1080/1360786070152988218297486The discomfort behavior scale: a measure of discomfort in the cognitively impaired based on the minimum data Set 2.0StevensonKMBrownRLDahlJLWardSEBrownMSRes Nurs Health200629657658710.1002/nur.2016817131282The MDS cognition scale: a valid instrument for identifying and staging nursing home residents with dementia using the minimum data setHartmaierSLSloanePDGuessHAKochGGJ Am Geriatr Soc19944211121212137963211The effect of depression on social engagement in newly admitted Dutch nursing home residentsAchterbergWPotAMKerkstraAOomsMMullerMRibbeMGerontologist200343221321810.1093/geront/43.2.21312677078Efforts to establish the reliability of the resident assessment instrumentSgadariAMorrisJNFriesBELjunggrenGJonssonPVDuPaquierJNSchrollMAge Ageing199726Suppl 2273010.1093/ageing/26.suppl_2.279464551Predicting patient scores between the functional independence measure and the minimum data set: Development and performance of a FIM-MDS “crosswalk”WilliamsBCLiYFriesBEWarrenRLArch Phys Med Rehabil1997781485410.1016/S0003-9993(97)90009-59014957Minimum Data Set Plus (MDS+) scores compared with scores from five rating scalesFrederiksenKTariotPDe JongheEJ Am Geriatr Soc19964433053098600202The resident assessment instrument-mental health (RAI-MH): inter-rater reliability and convergent validityHirdesJPSmithTFRabinowitzTYamauchiKPerezETelegdiNCPrendergastPMorrisJNIkegamiNPhillipsCDFriesBEJ Behav Health Serv Res200229441943210.1007/BF0228734812404936The MDS-CHESS scale: a new measure to predict mortality in institutionalized older peopleHirdesJPFrijtersDHTeareGFJ Am Geriatr Soc20035119610010.1034/j.1601-5215.2002.51017.x12534853Psychometric characteristics of the minimum data set I: confirmatory factor analysisCastenRLawtonMPParmeleePAKlebanMHJ Am Geriatr Soc19984667267359625189Psychometric characteristics of the minimum data Set II: validityLawtonMPCastenRParmeleePAHaitsmaKVCornJKlebanMHJ Am Geriatr Soc19984667367449625190MDS cognitive performance scaleMorrisJNFriesBEMehrDRHawesCPhillipsCMorVLipsitzLAJ Gerontol A Biol Sci Med Sci1994494174182Use of the cognitive performance scale (CPS) to detect cognitive impairment in the acute care setting: Concurrent and predictive validityBulaCJWietlisbachVBrain Res Bull2009804–517317819559765Validation of the minimum data Set cognitive performance scale: agreement with the mini-mental state examinationHartmaierSLSloanePDGuessHAKochGGMitchellCMPhillipsCDJ Gerontol A Biol Sci Med Sci199550A212813310.1093/gerona/50A.2.M128Effects of cognitive performance on change in physical function in long-stay nursing home residentsMcConnellESPieperCFSloaneRJBranchLGJ Gerontol A Biol Sci Med Sci2002571277878410.1093/gerona/57.12.M778Scaling ADLs within the MDSMorrisJNFriesBEMorrisSAJ Gerontol A Biol Sci Med Sci1999541154655310.1093/gerona/54.11.M546Reliability estimates for the Minimum Data Set for nursing home resident assessment and care screening (MDS)HawesCMorrisJNPhillipsCDMorVFriesBENonemakerSGerontologist199535217217810.1093/geront/35.2.1727750773Comparison of citalopram, perphenazine, and placebo for the acute treatment of psychosis and behavioral disturbances in hospitalized, demented patientsPollockBGMulsantBHRosenJSweetRAMazumdarSBharuchaAMarinRJacobNJHuberKAKastangoKBChewMLAm J 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Abstract
Background
Nursing home residents with dementia gradually lose the ability to process information so that they are less likely to express pain in typical ways. These residents may express pain through disruptive behaviors because they cannot appropriately verbalize their pain experience. The objective of this study was to investigate the effect of pain on disruptive behaviors in nursing home residents with dementia.
Methods
This is a secondary analysis of the Minimum Data Set (MDS 2.0) assessment data on long-term care from the state of Florida. The data used in this study were the first comprehensive assessment data from NH residents with dementia aged 65 and older (N = 56,577) in Medicare- or Medicaid-certified nursing homes between January 1, 2009 and December 31, 2009. Variables examined were pain, wandering, aggression, agitation, cognitive impairment, activities of daily living impairments, and demographic characteristics. Ordinal logistic regression was used to evaluate the effect of pain on disruptive behaviors.
Results
Residents with more severe pain are less likely to display wandering behaviors (OR = .77, 95% CI for OR = [0.73, 0.81]), but more likely to display aggressive and agitated behaviors (OR = 1.04, 95% CI for OR = [1.01, 1.08]; OR = 1.17, 95% CI for OR = [1.13, 1.20]).
Conclusions
The relationship between pain and disruptive behaviors depends on the type of behaviors. Pain is positively correlated with disruptive behaviors that do not involve locomotion (e.g., aggression and agitation), but negatively related to disruptive behaviors that are accompanied by locomotion (e.g., wandering). These findings indicate that effective pain management may help to reduce aggression and agitation, and to promote mobility in persons with dementia.
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Ahn, Hyochol
Horgas, Ann
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Hyochol Ahn et al.; licensee BioMed Central Ltd.
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BMC Geriatrics. 2013 Feb 11;13(1):14
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RESEARCHARTICLEOpenAccessTherelationshipbetweenpainanddisruptive behaviorsinnursinghomeresidentwith dementiaHyocholAhn*andAnnHorgasAbstractBackground: Nursinghomeresidentswithdementiagraduallylosetheabilitytoprocessinformationsothatthey arelesslikelytoexpresspainintypicalways.Theseresidentsmayexpresspainthroughdisruptivebehaviors becausetheycannotappropriatelyverbalizetheirpainexperience.Theobjectiveofthisstudywastoinvestigate theeffectofpainondisruptivebehaviorsinnursinghomeresidentswithdementia. Methods: ThisisasecondaryanalysisoftheMinimumDataSet(MDS2.0)assessmentdataonlong-termcarefrom thestateofFlorida.ThedatausedinthisstudywerethefirstcomprehensiveassessmentdatafromNHresidents withdementiaaged65andolder(N=56,577)inMedicare-orMedicaid-certifiednursinghomesbetweenJanuary 1,2009andDecember31,2009.Variablesexaminedwerepain,wandering,aggression,agitation,cognitive impairment,activitiesofdailylivingimpairments,anddemographiccharacteristics.Ordinallogisticregressionwas usedtoevaluatetheeffectofpainondisruptivebehaviors. Results: Residentswithmoreseverepainarelesslikelytodisplaywanderingbehaviors(OR=.77,95%CIfor OR=[0.73,0.81]),butmorelikelytodisplayaggressiveandagitatedbehaviors(OR=1.04,95%CIfor OR=[1.01,1.08];OR=1.17,95%CIforOR=[1.13,1.20]). Conclusions: Therelationshipbetweenpainanddisruptivebehaviorsdependsonthetypeofbehaviors.Painis positivelycorrelatedwithdisruptivebehaviorsthatdonotinvolvelocomotion(e.g.,aggressionandagitation),but negativelyrelatedtodisruptivebehaviorsthatareaccompaniedbylocomotion(e.g.,wandering).Thesefindings indicatethateffectivepainmanagementmayhelptoreduceaggressionandagitation,andtopromotemobilityin personswithdementia. Keywords: Disruptivebehaviors,Pain,Dementia,NursinghomeBackgroundPainassessmentinnursinghome(NH)residentswithdementiaischallengingduetocognitiveandcommunicative impairments.Painself-report,thegoldstandardassessment incognitivelyintactpersons,is questionableincognitively impairedNHresidentsbecausedementiaimpairstheirabilitytoremember,interpret,andrespondtopain[1,2].NH residentswithdementiagraduallylosetheabilitytoprocess informationsothattheyarelesslikelytoexpresspainin typicalways,evenwhenthereisaprobablecauseforpain [1].Therefore,painisoftenunder-reportedinNHresidents withdementia.Theseresidentsmayexpresspainthrough disruptivebehaviors[3],becausetheycannotappropriately verbalizetheirpainexperience. Disruptivebehaviors,alsoknownas “ problematic behaviors, ”“ disturbingbehaviors, ” or “ challengingbehaviors, ” refertoinappropriate,repetitive,ordangerous behaviorsthataredisruptivetothelivingandworking environmentintheNH[4,5].Amongmanydisruptive behaviors,threebehaviorsaremostprominentinthe currentliterature:wanderingbehaviors,aggressivebehaviors,andagitatedbehaviors[6,7].Wanderingoccursin approximately40to60%ofNHresidentswithdementia [8],andaggressionandagitationoccursinabout50%to 80%ofNHresidentswithcognitiveimpairments[9]. *Correspondence: hcahn@ufl.edu DepartmentofAdultandElderlyNursing,CollegeofNursing,Universityof Florida,Gainesville,FL32610-0197,USA 2013AhnandHorgas;licenseeBioMedCentralLtd.ThisisanOpenAccessarticledistributedunderthetermsofthe CreativeCommonsAttributionLicense(http://creativecommons.org/licenses/by/2.0),whichpermitsunrestricteduse, distribution,andreproductioninanymedium,providedtheoriginalworkisproperlycited.AhnandHorgas BMCGeriatrics 2013, 13 :14 http://www.biomedcentral.com/1471-2318/13/14

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DisruptivebehaviorsareproblematictoNHresidents andstaff.Disruptivebehaviorsareassociatedwithinjuries andhospitalizationsamongNHresidentswithdementia, andcontributetostressandburnoutamongcaregivers [10,11].ThecostofcareforN Hresidentswithdementiais threetimeshigherthanthatofotherNHresidents,and about30%ofthesecostsareattributedtothemanagement ofdisruptivebehaviors[12].Psychoactivemedicationsor restraintsareoftenusedtomanagedisruptivebehaviors [13];however,theseoftenleadtofalls,impairedfunctioning,anddecreasedmobility.Theuseofrestraintsisalso anaffronttopersonaldignity.Thebetterapproach tomanagingdisruptivebehaviorsistocontroltheir possiblecauses,suchaspain. Thus,thepurposeofthisstudyistoexploretherelationshipbetweenpainanddisruptivebehaviorsinNH residentswithdementia.Suchinformationmayidentify potentialnewinterventionapproachesformanaging thesebehaviors.TheoreticalframeworkTheNeed-drivenDementia-compromisedBehavior(NDB) model[14]wasusedtoguidethisstudyoftherelationship betweenpainanddisruptivebehaviorsinNHresidentswith dementia(Figure1).TheNDBmodelpositstwo mainconstructsthatareassociatedwithdementiacompromisedbehaviors:backgroundfactorsand proximalfactors.Backgrou ndfactorsrepresentthose characteristicsthatplaceolderadultsatriskfor disruptivebehaviors.Proximalfactorsrepresentthe conditionsunderwhichdisr uptivebehaviorsoccur. Weconceptualizedpainasaproximalfactorthatwould haveadirectrelationshipwithdisruptivebehaviors (e.g.,wandering,aggressi on,andagitation).Forthis study,thelevelofcognitiveimpairment,activitiesof dailyliving(ADL)impairment,anddemographiccharacteristics(e.g.,ageandsex)representbackgroundfactors. Thesevariableswereselectedascovariatesbecausethey haveestablishedrelationshipswithbothpainanddisruptivebehaviors[15-18]andmayinfluencetherelationship betweenpainanddisruptivebehaviors.MethodsThisisasecondaryanalysisofthenursinghomeMinimum DataSet(MDS)fromthestateofFloridaduringcalendar year2009.Thefirstcomprehensiveassessmentforeach NHresidentwasusedinthisstudy.Thearchiveddatafiles ofthemostrecentversionofMDS(MDS3.0)werenotyet availabletoresearchers,butaredueforreleaseinearly 2013[19].TheMDSdataaremandatoryinallNHscertifiedtoparticipateinMedicareandMedicaid.Approvalfor thestudywasobtainedfromtheUniversityofFlorida HealthScienceCenterInstitutionalReviewBoard. TheMDSassessmentdata,standardizeddataonresidents ’ statusbasedonroutineandcontinuousobservations bynursingstaff,providescomprehensiveinformationon alltheNHresidents.TheMDSassessmentiscompleted onadmissiontothefacility,onaquarterlybasisthereafter, anduponsignificantchangesinstatus[20].Thecomplete federaldatabaseconsistsofover1.5millionolder adultswholiveinNHsthroughouttheUnitedStates. Althoughitisusedprimarilyforclinicalpurposes,the MDShasalsobeenusedforresearchoncognitionand behavioralsymptomsinthispopulation[21-23].Several MDSsubscaleshavebeencreatedandevaluated,andhave demonstratedacceptablereliabilityandvalidity:MDS-Pain severityscale[24],MDS-DepressionRatingScale[25], MDS-AggressionBehaviorScale[26],MDS-Challenging BehaviorProfile[27],MDS-DiscomfortBehaviorScale[28], MDS-CognitivePerformanceScale[28,29],MDS-indexof socialengagement[30,31],MDS-ActivitiesofDailyLiving scale[32,33],ResidentAsse ssmentInstrument-Mental Health[34],andMDS-ChangeinHealth,End-stagedisease andSignsandSymptoms[35].Detailsofthereliabilityand validitycoefficientsforeachofthemajorstudyvariablesare describedinthemeasurementsection.DatausedinthisstudyThedatausedinthisstudywerecollectedonresidentswith dementiainMedicare-orMedicaid-certifiedNHswho haveaMDScomprehensiveassessmentonfile.Thedata wereacquiredfromtheCentersforMedicare&Medicaid Services.Selectioncriteriawereappliedtoascertaindata Disruptive Behaviors Wandering Aggression Agitation Factors Proximal factor o Pain Background factors o Cognitive impairment o ADL impairment o Age o Sex Figure1 TheoreticalframeworkadaptedfromtheNeed-drivenDementia-compromisedBehavior(NDB)model. AhnandHorgas BMCGeriatrics 2013, 13 :14 Page2of7 http://www.biomedcentral.com/1471-2318/13/14

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fromNHresidentsolderthan65yearsoldwithAlzheimer ’ diseaseorotherdementia,basedondocumentedmedical diagnosis.Datafromcomatoseresidentswereexcluded, becausetheseresidentscannotdisplaythedisruptive behaviorsinvestigatedinthisstudy.Thisselectionprocess yielded56,577uniquecasesfortheanalyses. Thesampleismostlyfemale(67.7%),andameanage of84(yearsrange=65 – 109).Theprevalenceofdisruptivebehaviorsisasfollows:wanderingbehaviors(9.0%), aggressivebehaviors(24.4%),andagitatedbehaviors (24.1%)(Table1).MeasurementMDSsubscalesanditemswereusedtoindicatethe mainstudyconcepts:pain,wandering,aggression,and agitation.Thesearedescribedbelow.PainTheMDS-painseverityscale[24],combiningbothpain frequency(0=nopain,1=painlessthandaily,and2=pain daily)andpainintensity(1=mildpain,2=moderatepain, and3=horribleorexcruciatingpain),wasusedtoassess painseverityinNHresidentswithdementia.Thisscalecan rangefrom0to3,withhigher scoresindicatinggreater painseverity.NHresidents ’ self-reportisreflectedin theMDSpainitemsifresidentscanself-reportand staffcompletingtheMDSassessmentshaveconfidenceinresidents ’ self-report.Otherwise,thestaff whocompletetheMDSassessmentdocumentpain symptomsbasedonproxyreportsfromfacilitynursing staffthatprovidescaretotheresidents.TheMDS-pain severityscalehasbeenreportedtohaveaninter-raterreliabilitycoefficientof0.73,andk appacoefficientof0.70with aVisualAnalogueScaleinastudyinvolving95U.S. nursinghomeresidentsat25Medicare-certifiedskilled nursingfacilitiesinMassachusetts[24].DisruptivebehaviorsTheMDS-wanderingitemwasusedtomeasurethe frequencyofwanderinginthelast7days.Wandering frequencyisrecordedbystaffobservation.Itisrecorded asnowandering,wanderingoccurred1to3days, wanderingoccurred4to6days,anddailywandering. Thewanderingitemhasbeenreportedtohaveareliabilitycoefficientof0.63,andaninter-raterreliability of0.95[36,37]. TheMDS-AggressionBehaviorScale(MDS-ABS)was usedtomeasurethefrequencyofaggressivebehaviors. TheMDS-ABSisasumscoreoffourMDSitems: verballyabusivebehavioralsymptoms,physicallyabusive behavioralsymptoms,sociallyinappropriatebehavioral symptom,andresistingcare.TheMDS-ABScanrange from0to12,withhigherscoresindicatingmore frequentaggressivebehaviors.TheMDS-ABShasbeen reportedtohaveaninternalconsistencyreliabilityof 0.79to0.95,andacriterionvaliditycoefficientof0.72 withCohen-MansfieldAgitationInventoryaggression subscalescores[26]. TherevisedMDS-ChallengingBehaviorProfile (MDS-CBP)agitationsubscalewasusedtoassessthe frequencyofagitatedbehaviors.Therevisedagitation scores,calculatedusingtwoMDSitems(e.g.,periods ofrestlessnessandrepetitivephysicalmovements), canrangefrom0to3,withhigherscoresindicating morefrequentagitatedbehaviors.ThisrevisedagitationscalehasCronbach ’ salphacoefficientof.68. TheoriginalMDS-CBPagitationsubscale,computing from4MDSitems(e.g.,periodsofrestlessness,repetitive physicalmovements,wandering,andsociallyinappropriate behavioralsymptom),hasbeenreportedtohave Cronbach ’ salphacoefficientof0.70,inter-raterreliabilityof0.61,andaSpearman ’ srankcorrelation coefficientof0.50withBehaviorRatingScalefor PsychogeriatricInpatients[27]. Table1SamplecharacteristicsCharacteristicNumberTotal sample Age,meanSD5657784.377.43 Gender,n(%)56566 Male18,265(32.3) Female38,301(67.7) MDS-CPS,meanSD565433.171.52 MDS-ADL,meanSD5657718.666.41 Painseverity,meanSD565680.480.70 Wanderingbehaviors,n(%)56573 Nowandering(MDS-wandering=0)51,463(91.0) 1-3daysin7days(MDS-wandering=1)2,637(4.7) 4-6daysin7days(MDS-wandering=2)994(1.8) Wanderingdaily(MDS-wandering=3)1,479(2.6) Aggressivebehaviors,n(%)56572 None(MDS-ABS=0)42,764(75.6) Moderate(MDS-ABS=1 – 2)9,667(17.1) Severe(MDS-ABS=3 – 5)3,390(6.0) Verysevere(MDS-ABS=6 – 12)751(1.3) Agitatedbehaviors,n(%)56571 None(revisedMDS-CBPagitation=0)42,941(75.9) Mild(revisedMDS-CBPagitation=1)6,916(12.2) Moderate(revisedMDS-CBPagitation=2)5,099(9.0) Severe(revisedMDS-CBPagitation=3)1,615(2.9)MDS-CPS =MDS-CognitivePerformanceScale. MDS-ADL =MDS-ActivitiesofDailyLivingimpairmentscale. MDS-ABS =MDS-AggressionBehaviorScale. RevisedMDS-CBPagitation =revisedMDS-ChallengingBehaviorProfile, agitationsubscale.AhnandHorgas BMCGeriatrics 2013, 13 :14 Page3of7 http://www.biomedcentral.com/1471-2318/13/14

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BackgroundfactorsTheMDS-cognitiveperformancescale(MDS-CPS)[38] wasusedtomeasurethelevelofcognitiveimpairment. TheMDS-CPSscoreiscalculatedusingfiveMDSitems: comatose,short-termmemory,cognitiveskillsordaily decisionmaking,makingoneselfunderstood,andselfperformanceineating.TheMDS-CPScanrangefrom0 to6,withhigherscoresindicatingmorecognitive impairment.TheMDS-CPShasbeenreportedtohavea kappacoefficientof0.45-0.75withMini-MentalState Examination,akappacoefficientof0.41-0.77against GlobalDeteriorationScale,akappacoefficientof0.66 againstPsychogeriatricDependencyRatingScale,a kappacoefficientof0.45againstMattisDementiaRating Scale[29,38-41]. TheMDS-ActivitiesofDailyLiving-LongForm(MDS ADL-LongForm)[42]wasusedtomeasurethelevelof ADLimpairment.TheMDSADL-LongFormscoresare calculatedusing7MDSitems:self-performanceofbed mobility,transfer,locomotiononunit,dressing,eating, toiletuse,andpersonalhygiene.MDSADL-LongForm canrangefrom0to28,withhigherscoresindicating moreimpairmentofADLs.TheMDSADL-Long Formhasbeenreportedtohaveareliabilitycoefficientof0.92-0.97,aninter-raterreliabilitycoefficient of0.61-0.95,andakappacoefficientof0.58 – 0.79 againstPhysicalSelf-MaintenanceScale[31,43]. Demographicscharacteristics(e.g.,ageandgender)were collectedfromtheMDSform.Agewasacontinuousvariableandgenderwasdichotomous(0=female;1=male). Theywereincludedascovariatesintheanalyses.StatisticalanalysisAnalyseswereperformedusingSPSS,version20(IBMInc., Armonk,NY).Multivariateanalyseswereconductedto exploretherelationshipbetweenpainanddisruptive behaviorsinthissample.Aggressionwasseverelypositively skewed,andnoneofthetransfo rmations(e.g.,logarithmic transformation,squareroottransformation,inversetransformation,andsquaretransformation)resolvedthenormal distributionissue.Therefore, aggressionwascollapsedinto fourgroups(none,moderate,severe,andverysevere), basedonpublishedalgorithmsintheliterature[26]. Aggressionwastransformedasnone(MDS-ABS=0), moderate(MDS-ABS=1 – 2),severe(MDS-ABS=3 – 5), andverysevere(MDS-ABS=6 – 12).Duetoconcerns thatNHresidentswhotakepsychotropicmedications (e.g.,antipsychotics,antide pressants,etc.)mayexhibit lessfrequentdisruptivebehaviors[44],were-ranthe statisticalanalysisexcludingthesesubjects. Sincethelevelofmeasurementofthedependentvariableswasordinal,logisticregressionforordinalvariables wasusedtoevaluatetheeffectofpainseverityonthe threedisruptivebehaviors,aftercontrollingforcovariates. Usingthesameindependentvariablesinanalysis withdifferentdependentvariablescarriestheriskof inflatingtheTypeIerror.Tokeeptheoverallriskof aTypeIerrortothe5%level,p-valuefortheeach regressionanalysisissetat.017.ResultsTheresultsofordinallogisticregressiononthreedisruptivebehaviors,aftercontrollingforcovariates(e.g.,the levelofcognitiveimpairment,thelevelofADLimpairment,andsociodemographicfactors)aredescribedbelow.TheeffectofpainonwanderingbehaviorsPainseverityisnegativelyassociatedwiththefrequencyof wanderingbehaviors(Table2).NHresidentswithmore severepainarelesslikelytodisplaywanderingbehaviors (Logisticregressioncoefficient= 0.26,p<.001,Odds Ratio=.77,95%CIforOddsRatio=[0.73,0.81]). Table2Predictingdisruptivebehaviorsfrompainseverity,aftercontrollingforcovariates(N=56,577)VariablesWanderingAggressionAgitation BOR95%CIforORBOR95%CIforORBOR95%CIforOR IndependentVariable Pain 0.26*0.77[0.73,0.81]0.04*1.04[1.01,1.08]0.15*1.17[1.13,1.20] Covariates MDS-CPS0.68*1.97[1.91,2.02]0.36*1.43[1.41,1.46]0.46*1.58[1.55,1.60] MDS-ADL 0.15*0.87[0.86,0.87] 0.03*0.98[0.97,0.98] 0.02*0.98[0.97,0.98] Age 0.01*0.99[0.98,0.99] 0.01*0.99[0.99,0.99] 0.01*0.99[0.99,0.99] Sex Male 0.22*1.25[1.17,1.33]0.28*1.33[1.27,1.39]0.24*1.27[1.22,1.33] Female 0.001.000.001.001.00NagelkerkeR-square:Wandering=0.15,Aggression=0.06,Agitation=0.08.B=logisticregressioncoefficient,OR=OddsRatio=Exp(B).MDS-CPS=MD S-Cognitive PerformanceScale.MDS-ADL=MDS-ActivitiesofDailyLivingimpairmentscale.*p <.001.AhnandHorgas BMCGeriatrics 2013, 13 :14 Page4of7 http://www.biomedcentral.com/1471-2318/13/14

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TheeffectofpainonaggressivebehaviorsPainseverityispositivelyassociatedwiththefrequency ofaggressivebehaviors(Table2).NHresidentswith moreseverepainaremorelikelytodisplayaggressive behaviors(Logisticregressioncoefficient=0.04,p<.001, OddsRatio=1.04,95%CIforOddsRatio=[1.01,1.08]).TheeffectofpainonagitatedbehaviorsPainseverityispositivelyassociatedwiththefrequency ofagitatedbehaviors(Table2).NHresidentswithmore severepainaremorelikelytodisplayagitatedbehaviors (Logisticregressioncoefficient=0.15,p<.001,Odds Ratio=1.17,95%CIforOddsRatio=[1.13,1.20]).Thestudyresultsinsubsamplewithoutpsychotropic medicationsTheresultsofordinallogisticregressioninthesubsample withoutpsychotropicmedicatio ns(e.g.,antipsychotics,antidepressants,etc.)aresummari zedinTable3.Theseresults ofordinallogisticregressio naresimilarwhenNHresidents whousedpsychotropicmedicationsinthepast7dayswere excluded.Painseverityisnegativelyassociatedwiththe frequencyofwanderingbehaviors,butpositivelyassociated withthefrequencyofaggressi veandagitatedbehaviors.DiscussionItwasfoundthatmoreseverepainisassociatedwith lessfrequentwanderingbehaviors,butmorefrequent aggressiveandagitatedbehaviors,aftercontrollingfor covariates.Mostofthepublishedliteraturesuggested thatthereisapositiverelationshipbetweenpainand disruptivebehaviorsingeneral[6,11,45].However,the resultsofthisstudysuggestthattherelationship betweenpainanddisruptivebehaviorsdependsonthe typeofbehaviorsexamined.Thedirectionoftherelationshipbetweenthesevariablesdependsonwhether thedisruptivebehaviorsareaccompaniedbylocomotion. Painispositivelycorrelatedwithdisruptivebehaviors thatdonotinvolvelocomotion(e.g.,aggressionand agitation),butnegativelyrelatedtodisruptivebehaviors thatareaccompaniedbylocomotion(e.g.,wandering). Thatis,residentswhoexperiencemoreseverepainare morelikelytodisplayaggressionandagitation,andless likelytomovearound. ThefindingthatpainandaggressiveoragitatedbehaviorsarepositivelylinkedinNHresidentswithdementia isconsistentwithotherpublishedreports.Buffumand colleagues[46]reportedthatpainwaspositivelyrelated toagitation( r =.50, p =.003)usingabivariatecorrelationanalysisin33VeteransAffairsNHresidentswith dementia.Manfrediandcolleagues[47]demonstrated thatopioidtreatmentforpainreducedagitationin13 NHresidentswithdementiawhoweremorethan 85yearsold(meanchangeinCMAIscore:-6.4,95%CI [ 10.96,-1.8]).Bothofthesestudieshaveasmallsample size.Thus,theresultsofthisstudyusingalargesample fromallthenursinghomeresidentswithdementiain thestateofFloridasubstantiatesandextendsthe positiverelationshipbetweenpainandnon-locomotive disruptivebehaviorsfromthesepreviousfindings. Incontrast,thefindingontherelationshipbetween painandwanderingbehaviorinthisstudyisoppositeto thefindingspresentedintheliteraturereview.Kielyand colleagues[48]usedMDSassessmentdatafrom8,982 NHresidents,andreportedthatNHresidentswho expressedsadnessorpaininMDSassessmentdata were65%morelikelytodevelopwanderingbehaviors thantheircounterpartswhodidnotexpresssadness orpain(OR=1.65,p=.02).Ourstudymeasuredpain morespecificallyusingtheMDS-painseverityscale [24],combiningbothpainfrequencyandpainintensity,whileKielyandthecolleagues[48]measured painbyadichotomizedexpressionofsadnessorpain. Sadnessisnottypicallyconsideredanindicatorof Table3Thestudyresultsinsubsamplewithoutpsychotropicmedications(N=17,435)VariablesWanderingAggressionAgitation BOR95%CIforORBOR95%CIforORBOR95%CIforOR IndependentVariable Pain 0.33*0.72[0.63,0.83]0.07**1.07[1.01,1.15]0.15*1.16[1.08,1.25] Covariates MDS-CPS0.63*1.87[1.76,2.00]0.29*1.34[1.29,1.38]0.42*1.53[1.47,1.58] MDS-ADL 0.15*0.86[0.85,0.87] 0.04*0.97[0.96,0.97] 0.04*0.96[0.96,0.97] Age0.001.00[0.99,1.01]0.01*1.01[1.00,1.02]0.001.00[1.00,1.01] Sex Male 0.121.12[0.96,1.31]0.19*1.21[1.10,1.33]0.22*1.24[1.13,1.37] Female 0.001.000.001.001.00NagelkerkeR-square:Wandering=0.13,Aggression=0.03,Agitation=0.05.B=logisticregressioncoefficient,OR=OddsRatio=Exp(B).MDS-CPS=MD S-Cognitive PerformanceScale.MDS-ADL=MDS-ActivitiesofDailyLivingimpairmentscale.*p <.001.**p <.05.AhnandHorgas BMCGeriatrics 2013, 13 :14 Page5of7 http://www.biomedcentral.com/1471-2318/13/14

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pain,anditsinclusionmayhaveconfoundedpainand depressionormooddisorder. Severallimitationsofthisstudyshouldbenoted.First, thisstudyisinherentlylimitedbysecondaryanalysisof federallymandatedMDSassessmentdata,andtheeffect ofclusteringwithinfacilityisnotcontrolledinthis study.Thevariablesandt heprocedurescannotbe controlled.TheMDSassessmentdatamayhavesome variabilityduetodifferentstylesandskillsofMDS coordinatorsineachfacility.Second,theroleofpain medicationsisnotconsideredinthisstudy.Thehighest levelofpaincouldhavebeenmanagedbypainmedications,butitisnotpossibletodiscernthisintheMDS assessmentdata.However,similartoourstudy,mostof theliteraturereportedtherelationshipbetweenhighest levelofpainandthefrequencyofbehavioralsymptoms duringtheobservationperiodwithoutcontrollingforpain medications[11,49].Third,theamountofvariancein disruptivebehaviorsthatisexplainedbytheselogistic regressionmodelsissmall(rangingfrom6%to15%).This suggeststhatthereareotherfactorsthatcontribute todisruptivebehaviorsthatwerenotspecifiedinour models.Finally,thisstudydesignisdescriptiveandcrosssectional.Assuch,thisstudyisnotabletoexaminecausal relationshipsbetweenpainanddisruptivebehaviors. Findingsfromthisstudycanbeafoundationfor futureresearch.Studiesusingprospectivedesignsare neededtovalidatethesefindings.Also,randomizedcontrolledtrialscanbeusedtocomparecomprehensive painmanagementandusualpainmanagementwithregard tothefrequencyofdisruptivebehaviors.Thistypeofstudy canprovideevidenceforcausalrelationshipsbetweenpain managementanddisruptivebehaviorsandsupportchanges inclinicalpractice.Third,futureresearchwouldinclude thelongitudinalMDSassessmentdatatoexaminetrends overtime.ThelongitudinalnatureofMDSassessment data,collectedeverythreemonthsormoreoften,provides anopportunitytodescribechangeovertime,andfacilitates theuseofmorepowerfulstatisticalanalysistechniquesto describebothwithin-andbetween-personchanges.ConclusionsPainexacerbateddisruptivebehaviorsthatarenotlocomotion-based.Inordertoreducethesedisruptivebehaviors, theirunderlyingcauses,suchaspain,shouldbeinvestigated andwellmanaged.However,painassessmentincognitively impairedresidentscanbechallenging.Comprehensive painassessmentshouldbedevelopedfurther,andpain shouldbewellcontrolledtoreducetheseproblematic disruptivebehaviors.Abbreviations ADL:Activitiesofdailyliving;MDS:Minimumdataset;MDS-ABS:MDSAggressionbehaviorscale;MDS-CBP:MDS-Challengingbehaviorprofile; MDS-CPS:MDS-Cognitiveperformancescale;NH:Nursinghome. Competinginterests Theauthorshavenofinancialoranyotherkindofpersonalconflictswith thismanuscript.ThisstudywassupportedbyGrantawardfromSigmaTheta TauAlphaThetaChapter. Authors ’ contributions HAconceptualizedthestudy,completedallstatisticalanalyses,andwrote themanuscript.AHprovidedoversightandconsultationduringallaspectsof thestudy.Bothauthorsreadandapprovedthefinalmanuscript. Received:18August2012Accepted:5February2013 Published:11February2013 References1.HorgasA,ElliottAF,MarsiskeM: Painassessmentinpersonswith dementia:Relationshipbetweenself-reportandbehavioralobservation. JAmGeriatrSoc 2009, 57 (1):126 – 132. 2.Cohen-MansfieldJ: Theadequacyoftheminimumdatasetassessment ofpainincognitivelyimpairednursinghomeresidents. JPainSymptom Manage 2004, 27 (4):343 – 351. 3.BurfieldAH,WanTT,SoleML,CooperJW: Behavioralcuestoexpanda painmodelofthecognitivelyimpairedelderlyinlong-termcare. 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Submit your next manuscript to BioMed Central and take full advantage of: € Convenient online submission € Thorough peer review € No space constraints or color “gure charges € Immediate publication on acceptance € Inclusion in PubMed, CAS, Scopus and Google Scholar € Research which is freely available for redistribution Submit your manuscript at www.biomedcentral.com/submit AhnandHorgas BMCGeriatrics 2013, 13 :14 Page7of7 http://www.biomedcentral.com/1471-2318/13/14