1 INVESTIGATION OF THE START BACK SCREENING TOOL IN OUTPATIENT PHYSICAL THERAPY SETTING S By JASON M ICHAEL BENECIUK A DISSERTATION PRESENTED TO THE GRADUATE SCHOOL OF THE UNIVERSITY OF FLORIDA IN PARTIAL FULFILLMENT OF THE REQUIREMENTS FOR THE DEGREE OF DOCTOR OF PHILOSOPHY UNIVERSITY OF FLORIDA 2011
2 2011 Jason M ichael Beneciuk
3 Dedicated to Monika, Aiden, Alexa, Brody & Barren for being my inspiration and putting up with my moodswings over the past five years ; y ou guys have taken this journey with me and for that I thank you
4 ACKNOWLEDGMENTS I would like to thank all of those people who helped make this dissertation possible. Firs t and most important my c ommittee chair Dr. Steven George for his commitment, guidance, and dedication over the past five years. Im not sure he knew what he was getting himself into when my wife came to the application interview and had more questions th an I did; but for whatever reason he still agreed to take me under his wing and for that I am truly grateful. Second, I would like to thank my committee members for their contributions in my overall professional development. Dr. Mark Bishop has always remi nded me to stay focused on the big picture, especially when I had a tendency to get lost in translation Fortunately, Dr. Michael Robinson has managed to sit through my repeated change analysis questions and remained on my committee although he probably just fe lt sorry for me Dr. Nabih Asal has provided me with an epidemiological perspective on this project and served a s my primary public health mentor. Dr. Julie Fritz has provided me with insight related to the classification of low back pain and has offered me the opportunity to be involved with a similar project to this dissertation in the past; therefore I am thankful that she has agreed to be a member of this disser tation committee. Third, I would like to thank Brooks Rehabilitation for funding this project Fourth, I would like to acknowledge the T 32 Neuromuscular Plasticity Training Grant and Dr. Krista Vandenborne for funding my predoctoral education. Fi nally t hank you to Joel Bialosky, Carolina Valencia, Roy Coronado, and Corey Simon for their support and feedback over the years. A special thank you to Anne Nisenz on, Laura Wandner, and Calia Torres is deserved for their roles in this project. Last but definite ly not least, thank you to Jim Viti for being a great mentor and friend.
5 TABLE OF CONTENTS page ACKNOWLEDGMENTS .................................................................................................. 4 LIST OF TABLES ............................................................................................................ 8 LIST OF FIGURES .......................................................................................................... 9 LIST OF ABBREVIATIONS ........................................................................................... 10 ABSTRACT ................................................................................................................... 11 CHAPTER 1 INTRODUCTION .................................................................................................... 13 2 LITERATU RE REVIEW .......................................................................................... 15 Epidemiology of Low Back Pain .............................................................................. 15 Incidence and Prevalence ................................................................................ 15 Societal Impact ................................................................................................. 19 Healthcare Utilization for Low Back Pain: Who is Seeking Care? .................... 21 The Fear Avoidance Model of Musculoskeletal Pain .............................................. 23 Prognosis and Low Back Pain ................................................................................ 25 Methodological Issues ...................................................................................... 25 New Onset of Low Back Pain ........................................................................... 27 Baseline Clinical Characteristics ...................................................................... 28 Future Clinical Outcomes ................................................................................. 29 Measuring the Influence of Psychological Factors with Self Report Questionnaires .................................................................................................... 31 Screening Process ........................................................................................... 31 Studies of Psychological Measures: Single Construct Approaches .................. 34 Studies of Psychological Measures: Multiple Construct Approaches ............... 39 Public Health Significance and Relationship to Rehabilitation Science .................. 41 3 RESEARCH HYPOTHESES .................................................................................. 43 Specific Aim 1 ......................................................................................................... 43 Construct Validity of the STarT Back Tool Classification Scheme at Initial Physical Therapy Evaluation ......................................................................... 43 Discrimination of Psychological Factors amongst STarT Back Tool Classification Status at Initial Physical Therapy Evaluation ........................... 43 Clustering of Psychological Factors at Initial Physical Therapy Evaluation without considering STarT Back Tool Classification Status ........................... 44 Specific Aim 2 ......................................................................................................... 45 Predictive Validity of the STarT Back Tool (4 Week Outcomes) ...................... 45
6 Predictive Validity of the STarT Back Tool (4 Week Outcome Change Scores) .......................................................................................................... 45 Specific Aim 3 ......................................................................................................... 45 Prediction of Sustained STarT High Risk Allocation ......................................... 45 Sustained STarT High Risk Allocation and Outcomes ...................................... 46 Relevance and Novelty of Specific Aims ................................................................. 46 4 METHODS .............................................................................................................. 48 Research Design .................................................................................................... 48 Participants ............................................................................................................. 48 Inclusion Criteria ............................................................................................... 49 Exclusion Criteria ............................................................................................. 49 Procedures ....................................................................................................... 49 Demographic and Clinical Measures ...................................................................... 49 Subgroups for Targeted Treatment (STarT) Back Screening Tool ......................... 50 Fear Avoidance Model Based Psychological Measures ......................................... 51 Fear Avoidance Beliefs Questionnaire ............................................................. 51 Pain Catastrophizing Scale .............................................................................. 52 Tampa Scale of Kinesiophobia ......................................................................... 53 Pati ent Health Questionnaire ............................................................................ 54 State Trait Anxiety Inventory ............................................................................ 54 Outcome Measures ................................................................................................. 55 Pain Intensity .................................................................................................... 55 Revised Oswestry D isability Questionnaire ...................................................... 55 RolandMorris Disability Questionnaire ............................................................ 55 Physical Impairment Index ............................................................................... 56 Sample Size Estimate ............................................................................................. 56 Statistical Analyses ................................................................................................. 57 Specific Aim 1 ................................................................................................... 57 Construct validity of the STarT Back Tool classification scheme at initial physical therapy evaluation ..................................................................... 57 Discrimination of psychological factors amongst STarT Back Tool classification status at initial physical therapy evaluation ........................ 58 Clustering of psychological factors at initial physical therapy evaluation without considering STarT Back Tool classification status ..................... 59 Specific Aim 2 ................................................................................................... 59 Predictive validity of the STarT Back Tool (4week outcomes) .................. 59 Predictive validity of the STarT Back Tool (4week outcome change scores) .................................................................................................... 60 Specific Aim 3 ................................................................................................... 61 Prediction of sustained STarT high risk allocation ..................................... 61 Sustained STarT high risk allocation and outcomes .................................. 61 5 RESULTS ............................................................................................................... 64 Participants ............................................................................................................. 64
7 Specific Aim 1 ......................................................................................................... 65 Construct Validity of the STarT Back Tool Classification Scheme at Initial Physical Therapy Evaluation ......................................................................... 65 Discrimination of Psychological Factors amongst STarT Back Tool Classification Status at Initial Physical Therapy Evaluation ........................... 66 Clustering of Psychological Factors at Initial Physical Therapy Evaluation without considering STarT Back Tool Classification Status ........................... 68 Specific Aim 2 ......................................................................................................... 70 Predictive Validity of the STarT Back Tool (4 Week Outcomes) ...................... 70 4 week pain intensity (NPRS) scores ......................................................... 70 4 week disability (ODQ) scores .................................................................. 71 4 week disability (RMDQ) scores ............................................................... 71 4 week physical impairment (PII) scores .................................................... 72 Predictive Validity of the STarT Back Tool (4 Week Outcome Change Scores) .......................................................................................................... 72 4 week pain intensity (NPRS) raw change scores ..................................... 72 4 week disability (ODQ) raw change scores .............................................. 73 4 week disability (RMDQ) raw change scores ........................................... 73 4 week physical impairment (PII) raw change scores ................................ 73 Specific Aim 3 ......................................................................................................... 74 Prediction of Sustained STarT High Risk Allocation ......................................... 74 Sustained STarT High Risk Allocation and Outcomes ...................................... 74 6 DISCUSSION ......................................................................................................... 90 Statement of Principal Findings .............................................................................. 90 Strengths and Weaknesses of Study ...................................................................... 91 Comparison to Other Studies .................................................................................. 92 Pote ntial Implications .............................................................................................. 94 Unanswered Questions and Future Research ........................................................ 95 7 CONCLUSIONS ..................................................................................................... 97 LIST OF REFERENCES ............................................................................................... 99 BIOGRAPHICAL SKETCH .......................................................................................... 114
8 LIST OF TABLES Table page 5 1 Baseline Patient Characteristics. ........................................................................ 76 5 2 Coefficients of Psyc hological Measure Predictor Variables of the Discriminant Function. ............................................................................................................. 78 5 3 Four Week Pain Intensity Scores (NPRS). ......................................................... 79 5 4 Four Week Disability Scores (ODQ). .................................................................. 80 5 5 Four Week Disability Scores (RMDQ). ............................................................... 81 5 6 Four Week Physical Impairment Scores (PII). .................................................... 82 5 7 Intake to 4week Pain Intensity (NPRS) Change Scores. ................................... 83 5 8 Intake to 4Week Disability (ODQ) Change Scores. ........................................... 84 5 9 Intake to 4Week Disability (RMDQ) Change Scores. ........................................ 85 5 10 Intake to 4Week Physical Impairment (PII) Change Scores. ............................. 86 5 11 Overall Logistic Regression Model Predicting STarT High Risk Subgroup Status at 4 weeks. .............................................................................................. 87
9 LIST OF FIGURES Figure page 4 1 Flow chart of study design. ................................................................................. 62 4 2 Initial STarT subgroup distribution across studies by setting. ............................. 63 5 1 Cluster profiles using initial FAM measure scores. ............................................. 88 5 2 STarT risk distribution amongst cluster profiles. ................................................. 89
10 LIST OF ABBREVIATION S FABQ PA Fear Avoidance Beliefs Questionnaire physical activity scale FABQ W Fear Avoidance Beliefs Questionnaire work scale FAM Fear Avoidance Model of Musculoskeletal Pain LBP Low Back Pain NPRS Numerical Pain Rating Scale ODQ Revised Oswestry Disability Questionnaire PCS Pain Catastrophizing Scal e PII Physical Impairment Index PHQ 9 Patient Health Questionnaire 9 item version RMDQ RolandMorris Disability Questionnaire STAI T State Trait Anxiety Inventory trait portion STarT Subgroups for Targeted Treatment Back Screening Tool TSK11 Tampa Scale for Kinesiophobia 11item version
11 Abstract of Dissertation Presented to the Graduate School of the University of Florida in Partial Fulfillment of the Requirements for the Degree of Doctor of Philosophy INVESTIGATION OF THE START BACK SCREENING TOOL IN OUTPATIENT PHYSICAL THERAPY SETTINGS By Jason M ichael Beneciuk December 2011 Chair: Steven Z. George Major: Rehabilitation Scienc e Low back pain (LBP) is a major public health problem representing a significant portion of patients seen in physical therapy (PT) settings where some develop chronic symptoms influenced by psychological factors. The Fear Avoidance Model of Musculoskeletal Pain consists of individual psychological factors that provide a theoretical explanation as to why chronic pain conditions develop in a minority of those experiencing an acute episode. Currently, there is no standardized psychological screening process to identify these at risk patients suited for clinicians in busy PT settings. One potential screening method involves measuring the influence of individual psychological constructs with several questionnaires, while an alternative method includes screening f or general psychological distress with a single questionnaire. The STarT Back is a 9 item screening tool consisting of functional and psychological items that allocates patients into subgroups (i.e., low, medium, or high risk) describing risk status for fu ture disability and are associated with initial treatment options in primary care settings The STarT Back was developed and intended for use in primary care settings; however has potential for use in physical therapy settings.
12 This study included 146 pat ients seeking PT for LBP that completed a battery of measures at initial evaluation and 4 weeks later. Results indicated that the STarT Back was consistent at d ifferentiating patients based on severity of LBP at initial evaluation but not as consistent for predicting 4week treatment outcomes. Furthermore, an individual Fear Avoidance Model psychological measure (FABQ PA) was useful in predicting which patients maintained STarT Back high risk status following 4weeks of PT treatment for LBP The primary l imitation to this study wa s that PT treatment was not tailored to address LBP associated psychological factors. This study provides preliminary evidence that a brief psychological screening tool maybe useful in distinguishing severity of LBP, but may have limited ability to predict 4 week treatment outcomes.
13 CHAPTER 1 INTRODUCTION From a public health perspective, low back pain (LBP) is the second most common cause of adult disability in the United States .1, 2 Pain has been recognized by the World Health Organization as a problem of epidemic proportion,3 w ith others highlight ing the influence of LBP specifically.4, 5 This has important implications for rehabilitation science considering one of the largest proportions of direct medical costs for LBP have be en attributed to physical therapy services.6 As a result, the need for effective interventions has been emphasized with particular concern for the influence that modifiable factors have on LBP outcomes,7 -9 with psycho logical factors specifically being highlighted as a potential treatment target .5, 10-13 Therefore, o ne goal for rehabilitation scientist s is to determine optimal screening procedures for patients with LBP in order to identify those at increased risk for developing chronic symptoms. In 2009, t he Tenth International Forum for Primary Care Research on Low Back Pain was held in which recent concepts, research methods, and relevant study results were presented.5 Consistent with the gen eral theme of this dissertation, early risk factor screening for poor clinical outcomes was identified as a potential method to improve the efficiency and effectiveness of care and associated clinical outcomes.5 Ultimately, an optimal screening process would provide clinicians with valuable information in the form of prognostic indicators and /or treatment effect modifiers that would assist in clinical decision making. Specific to physical therapy psychologically informed practice ha s recently been presented as a secondary prevention approach for chronic LBP that integrates both biomedical (focused on physical impairments) and cognitivebehavioral (focused on
14 psychological distress) principles .13 The primary goal of a psychologically informed approach is to prevent future LBP associated disability with routine and specific identification of modifiable psycholog ical risk factors being emphasized. Specific to this dissertation, determining the validity and clinical utility of commonly used psychological screening measures has been indicated as a top priority for future research for psychologically informed practic e .13 Therefore, the primary goal s of this dissertation w ere to : 1) determine the validity of the STarT Back Tool (a multi construct psychological screening measure) in outpatient physical therapy settings and 2) test the clinical utility of the STarT Back Tool in comparison to commonly used singleconstruct psychological screening measures. The following literature revi ew will provide relevant information to support the rationale for these goals
15 CHAPTER 2 LITERATURE REVIEW Epidemiology of Low Back Pain Incidence and Prevalence An overlying goal of epidemiological research includes the control of health problems via the study of the distribution and determinants of health related conditions.14 The heterogeneity associated with studying pain in human populations complicates the ability to compare findings across epidemiological studies. This is particularly relevant when studying certain types of musculoskeletal pain, such LBP where psychological factors have an influential role in the pain experience.10 Considering this heterogeneity, it is important to critically evaluate the case definition used to define LBP when interpreting the results of epidemiological studies and the impact LBP has on society prior to implementing results into decision making processes related to rehabilitation. Commonly reported epidemiological occurrence rates include incidence and prevalence. Incidence has traditionally been used to indicate the frequency of a new developed case of a particular healthrelated outcome.14 Prevalence measures the frequency of an existing outcome based on specific time parameters (i.e., point, period, or lifetime prevalence).14 In terms of epidemiological studies involving LBP, prevalence estimates are frequently the reported measure of occurrence based on the episodic or recurrent nature of this c ondition; thereby limiting the ability to report true incidence rates. I t is important to note that incidence can also refer to the occurrence of a new or recent episode of LBP, although it may not be the initial incidence of LBP over the course of ones lifetime. However, variable methods in defining episodes or recurrence
16 have been used in review studies,15 suggesting a need for standardized LBP recurrence terminology.16 For example, in a previous study, 73% of patients with acute LBP had at least one reoccurrence within 12 months,17 however when using standardized methods to define recurrence, estimates have been reported to be much lower (i.e., 24% to 33%).18 Considering these factors, LBP occurrence rates will be reported as prevalence estimates in this dissertation as they are most commonly reported. The prevalence of LBP is extensively documented in the literature; however estimates vary due to differences in research methodology. For example, case definitions used to describe the characteristics and duration of LBP in the general population are inconsistent, thus limiting the ability to c ompare prevalence estimates among studies. A systematic review19 of the literature from 1966 to 1998 consisting of population prevalence studies has provided very broad point prevalence (12% to 33%), 1 year prevalence (22% to 65%), and lifetime prevalence (11% to 84%) estimates of LBP. Although direct comparisons cannot be made, findings from a separate systematic review highlight the influence that case definitions have on prevalence estimates. Loney and Stratford20 provided point prevalence (4% to 33%) and 1 year preval ence (4% to 63%) estimates of LBP from prevalence studies consisting of adult community based samples but excluded studies involving occupational groups (e.g., healthcare works, industrial workers, military). The authors commented that improved methods are required prior to using these estimates with confidence when considering issues related to healthcare policy (e.g., physical therapy), including the standardization of case definitions for adequate comparisons among studies.20
17 The National Health Interview S urvey (NHIS) is a national survey conducted by the National Center for Health Statistics, a branch of the Centers for Disease Control and Prevention. The NHIS provides U.S. national estimates for a broad range of health measures among the civilian, non ins titutionalized adult population. Deyo and colleagues21 p rovided ageadjusted prevalence estimates of LBP using 2002 NHIS data (n = 31,044), in which 26.4% of respondents indicated they experienced LBP lasting at least a whole day in the past 3 months Additional findings indicate that: 1) adults greater than 45 years of age reported LBP at an elevated rate in comparison to younger adults (18 to 44 years), however prevalence decreased slightly among the oldest adults ( to men (24.3%).21 Strine and Hootman22 also utilized 2002 NHIS data (n = 29,828) to provide prevalence estimates of LBP. Based on weighted data to represent national estimates, 17.0% reported LBP, resulting in an estimated 34 million adults in the U.S. population. Potential reasons for differences in prevalence estimates (i.e., 26.4% vs. 17.0% ) utilizing 2002 NHIS data may be a result of different weighting techniques, method of estimate reporting, and / or sample sizes. The National Health and Nutrition Examination Survey (NHANES) is another national survey conducted by the National Center f or Health Statistics, a branch of the Centers for Disease Control and Prevention. NHANES is a program of studies designed to assess the health and nutritional status of noninstitutionalized adults and children in the United States and is unique in that it combines interviews and physical examinations. Hardt and colleagues23 provided estimates of LBP prevalence using 1999 to 2002 NHANES data (n = 10,291), in which 10.1% of respondents indicated they
18 experienced non minor LBP, Freburger and colleagues24 reported on the rising prevalence of chronic and acute LBP following a cross sectional evaluation of North Carolina households conducted in 1992 and repeated in 2006. Chronic LBP was defined as: 1) LBP that limited daily activity everyday for the past 3 months or 2) > 24 episodes of LBP that limited activity 1 day in the past year. Provided estimates indicate an increasing prevalence of chronic, impairing LBP over the 14year interval from 1992 (3.9%) to 2006 (10.2%), resulting in an overall increased prevalence of 162%. Increases were identified in all age strata, in men and women, and in White and Black races. In the Freburger and colleagues study ,24 a cute LBP was defined as: 1) LBP limiting daily activity activity in the past year. Provided estimates indicate an increasing prevalence of acute LBP over the 14 year interval from 1992 (7.3%) to 2006 (10.5%), resulting in an overall increased prevalence of 44%.24 The authors speculated on the increased prevalence of several factors which may have been associated with increased LBP prevalence rates in North Carolina during this interval including obesity, psychosocial and physical work demands, depression, and increased symptom awareness and reporting of LBP. While these results cannot be extrapolated to national estimates, this study is relevant because it is the first populationbased study in the United States which has examined trends in the prevalence of LBP using identical case defi nitions of LBP. Focus on Therapeutic Outcomes (FOTO), Inc (Knoxville, Tennessee) is an international medical rehabilitation database.25 Between 2002 and 2006 data was
19 analyzed from 17,804 patients being treated for neuromusculoskeletal conditions in 121 outpatient rehabilitation clinics in 26 states (in the United States). Of these patients, 31.4% received outpatient physical therapy services for conditions related to musculoskeletal LBP.26 These findings are similar to those found between 2005 and 2008 in Israel outpatient rehabilitation clinics.27 In summary, prevalence estimates for LBP in the U.S. have ranged from 17% to 26% and chronic LBP rates specifically have been estimated at 10%.21-23 North C arolina data indicates that the prevalence of acute and chronic LBP has increased 44% and 162% respectively, when standard definitions were used over a 14year period.24 Specific to outpatient physi cal therapy settings, data has indicated that 31% of patients seeking outpatient physical therapy seek services for LBP.26 So cietal Impact Considering symptoms of pain are a leading reason for medical visits28, 29 and the most common pain complaints are musculoskeletal (of which LBP is the most common),30 it is plausible to assume that healthcare expenditures associated with LBP have an enormous negative impact from a societal perspective. In 2005, the Centers for Disease Control and Prevention indicated that back or spine problems were the second leading cause of disability in the United States.2 In 2002, LBP accounted for approximately 2.3% of all physician visit rates with only routine examinations, hypertension, and diabetes resulting in more visits.21 In 2008, bac k pain was the fourth leading reason for hospital outpatient or office based p rovider visits .31 Results from the 2007 Medical Expenditure Panel Survey indicated that 27 million adults (11.9%) reported LBP of which 70.4% received treatment totaling 30.3 billion dollars amounting in annual mean expenditures of approximately 1,600 dollars per adult.32 In 2005, direct
20 treatment for back and neck pain accounted for approximately 86 billion dollars in healthcare expenditure in the United States however did not distinguish expenditures associated with LBP specifically .33 Additionally, a systematic review of LBP cost of illness studies in the United States and internationally between 1997 and 2007, indicated that the largest proportion of direc t medical costs for LBP can be attributed to physical therapy (17%) and inpatient services (17%), followed by pharmacy (13%) and primary care (13%).6 In that systematic review, the range of direct (12.2 to 90.6 billion dollars ) and indirect (7.4 to 28.2 billion dollars ) costs of LBP in the United States were determined from the results of 3 and 5 studies respectively. Special consideration is warranted when interpreting the upper limit of direct costs, as th at review study was published in 1998 and results may be a reflection of the 1996 approval of the fusion cage surgical implant. The authors commented that the most notable finding in their review of LBP cost of illness was the heterogeneity in methodology used to derive cost of illness among 27 studies examined. While the above study findings demonstrate the burden that LBP has on society in the form of healthcare expenditures, they do not provide information on the entire healthcare experience associated with an episode of LBP. A previous study found that individuals with back pain incurred healthcare expenditures 60% higher than individuals not experiencing back pain, however did not account for individual differences in those with back pain.34 Studies investigating the entire healthcare experience throughout a LBP episode may provide further insight as to how LBP may also be associated with nonLBP costs. Nimgade and colleagues35 found that average monthly healthcare expenditures for non LBP expenditures increased when compared to the previous 1 to 3
21 months following the initiation of a LBP episode. Moreover, patients with increased nonLBP expenditures were more likely to have been prescribed psychiatric medications.35 LBP has been reported to be a common reason for lost work days,36-38 work related disab ility,36 and the fourth most costly physical health condition affecting several large U.S. employers.39 It has been estimated that 149 million days of work are lost because of LBP.40 In a random sample of U.S. working adults 18 to 65 years of age over a two week period, LBP ranked second among painf ul conditions as the reason for lost productive time at work (mean = 5.2 hours per week), costing employers an estimated 19.8 billion dollars per year.38 In the United States, working adults 40 to 65 years of age with LBP cost employers an estimated 7.4 billion dollars per year, with those experiencing an exacerbation of LBP symptoms accounting for 71.6% of this cost.37 These findings may be underestimating ac tual costs based on the results of a systematic review indicating that when total costs are reported, the indirect costs resulting from lost work productivity represent a majority of overall costs associated with LBP.6 In summary, direct costs associated with healthcare services for LBP are enormous and there have been indications that physical therapy services account for a large portion of these costs. Furthermore, indirect costs are frequently associated with greater adverse effects on society with the development and progression to chronic LBP being highlighted. Healthcare Utilization for Low Back Pain: Who is Seeking Care? Results from a 1997 North Carolina survey41 indicated that 12.6% of respondents sought physical therapy services for acute LBP with post high school education,
22 receiving workers compensation, having had prior physical therapy for LBP, having LBP and pain below the knee, and increased disability scores being positively associated with physical therapy utilization. Results from a 2011 North Carolina population based survey42 indicated that 29.7% of respondents sought physical therapy services for chronic LBP with receiving workers compensation, having seen a physician specialist, and higher levels of function being positively associated and having no health insurance being negatively associated with physical therapy utilization. Furthermore, in that study, Freburger and colleagues42 found that some previ ously reported effective physical therapy treatments for chronic LBP were underutilized (e.g., spinal manipulation 10.4%) and ineffective treatments were overutilized (e.g., corset or bracing 24.0%) ; potentially indicating the need to improve processes of matching patients with optimal treatment approaches for LBP A dose repose relationship has also been indicated between the timing of physical therapy initiation for acute LBP and subsequent healthcare utilization. Gellhorn and colleagues43 analyzed data from a nationally representative sample of Centers for Medicare and Medicaid Services physician outpatient billing claims and found that patients (mean age = 76.0 years) who r eceived physical therapy early after an episode of acute LBP were at lower risk for subsequent LBPrelated healthcare utilization over the following year compared to those who received physical therapy at later times. Furtherm ore, only 16.2% of patients received physic al therapy for LBP, potentially suggesting underutilization of physical therapy servic es for patients with acute or subacute LBP by medical generalist specialists.43
23 Collectively, these findings potentially suggest that the majority of individuals experiencing LBP are not necessarily utilizing the bulk healthcare resources especially physical therapy services, which Freburger and colleagues have refer red to as missed opportunities.42 Rather, a small percentage of patients with chronic LBP account for a large fraction of associated costs.44, 45 Furthermore, the timing of physical therapy initiation during early episodes of LBP and improvements in processes that aim to match patient s with optimal treatment approaches are potentially important factor s to consider when attempting to lower subsequent healthcare utilization for LBP The Fear Avoidance Model of Musculoskeletal Pain The Fear Avoidance Model of Musculoskeletal Pain (FAM) provides a theoretical explanation as to why chronic pain conditions develop in a minority of those experiencing an acute episode. Considering the experience of pain is highly variable among individuals, an understanding of what constitutes pain per ception is an important concept to comprehend in order to gain a full appreciation of the FAM. A s proposed by Lethem and colleagues ,46 pain perception involves a sensory component (i.e., pain sensation) and an emotional reaction component (i.e., pain experience, pain behavior, physiological responses to pain stimulation ) Potential coping strategies used by individuals experiencing pain range from the extremes of confrontation to avoidance. The type of coping strategy adopted i s influenced by several psychosocial factors (i.e., stressful life events, personal pain history, personal coping / response strategies, and personality).46 A daptive responders (i.e., confronters) view pain as temporary and have increased motivation to return to full function. These individuals maintain a timely balance (i.e., synchrony) between pain sensation, pain experience, and pain behaviors thereby increasing the likelihood of resuming normal function.
24 Alternatively, non adaptiv e responders (i.e., avoiders) are not able to maintain this timely balance (i.e., desynchr ony) and may exhibit an increased fear of pain, resulting in avoidance of physical and social activit ies. Although the FAM is primarily focused on the emotional react ion component of pain perception, it provides a plausible explanation of how the psychological consequences of avoidance behaviors can ultimately lead to adverse physical and psychological consequences, including physical disability depression, and exaggerated pain perception.46 Since its development in 1983, the FAM has gained popularity in research focusing on musculoskeletal pain and has been expanded upon. For example, Vlaeyen and colleagues47 refined t he FAM in 1995 by incorporating the term pain catastrophizing into the model as a potential precursor to painrelated fear. Pain catastrophizing involves an exaggerated negative interpretation of actual and anticipated pain experience resulting in exaggerated threat value of pain and negative appraisal of ones ability to cope with pain.48-51 Vlaeyen and Linton further refined the FAM in 2000 by speculating on the role that negative affectivity (i.e., subjective distress, negative mood states)52, 53 and threatening illness information have on pain catastrophizing.54 The current FAM55 accounts for several components which were previously discussed (e.g., adopti on of coping strategies ), however also consists of several revisions that provide additional insight to psychological constructs within the FAM. Fear of pain and pain anxiety are distinguished from one another, with the former representing defensive behaviors (e.g., escape) in response to present threats and the latter representing preventative behaviors (e.g., avoidance) in response to anticipated
25 future threats. Although both types of behaviors may be advantageous during acute pain episodes, they may influence the threshold of future pain experiences.55 Although individual psychological constructs within the FAM are separate from one another, it is debatable as to whether they are actually distinct enough from one another to be distinguish ed from a clinical perspective. Nevertheless, the current FAM provides an indepth theoretical perspective as to why some patients that experience an acute episode of musculoskeletal pain eventually develop chronic musculoskeletal pain. Recently, a collaborative narrative review presented potentia l limitations and proposed potential extensions that can potentially be incorporated into the current FAM in order to increase its clinical utility.5 6 For example, evidence for the current FAM is predominantly supported through experimental studies, while observational studies consisting of patients are associated with conflicting results and frequently utilize cross sectional study designs Furthermore, suggestions for future research to improve the clinical utility of the FAM included: 1) the development of more psychometrically sound assessment tools 2) the ability to identify subgroups within the FAM, and 3) the need for more prospective studies.56 Prognosis and Low Back Pain Methodol ogical Issues The ability to generalize findings from previous LBP prognostic studies is associated with limitations based on methodological issues.57 Potential explanations as to why inconsistent findings exi st in the literature include heterogeneity of populations (e.g., general population, clinical population) settings (e.g., primary care, secondary care, occupational) stage of condition (e.g., new episode, acute, subacute, chronic) and potential prognostic indicators (e.g., demographic, clinical, psychological)
26 Furthermore, inconsistent measurement of clinical outcome domains across studies is common; therefore the ability to generalize findings is potentially limited Many review studies consist of individual studies that report on mixed outcome domains (e.g., return to work status, pain intensity, disability) which need to be interpreted with caution when attempting to discern results. Specifically, changes in different LBP outcome domains are not always positively correlated,5, 58 which limit s the ability to draw definitive conclusions based on review study results that incorporate mixed outcome domains The influence of psychological factors on LBP outcomes also varies based on screening methods (e.g., single construct or multiple construct approaches ) and statistical ana lyses. Specific to interpretation of study findings and statistical analyses, it is important to distinguish between prognostic factors and treatment effect modifiers P rognostic factors are characteristics that identify patients who recover at different rates or have different outcomes, which can be used to predict patient outcomes.59, 60 Alternatively treatment effect modifiers are charact eristics that identify subgroups of patients who respond differently to a specific intervention (or intervention approach) that are capable of predicting treatment effects.59, 60 While treatment effect modifiers and prognostic factors may share similar characteristics, they provide different information to both researchers and clinicians, therefore should be interpreted and analyzed separately As a result, i t has been suggested that when attempting to identify either prognostic factors or treatment effect modifiers appropriate study designs and analysis techniques should be implemented.59, 60 For example, if the intent is to identify prognostic factors single arm cohort studies similar to the design used in this study are appropriate. Alternatively, if the intent is to identify treatment effect modifiers, two arm
27 trials that incorporate a comparison group (preferably a control group) should be utilized to investigate factors that may modify treatment effects. In summary methodological inconsistencies across prognostic studies related to LBP is common, therefore establishing definitive findings to outpatient physical therapy settings is difficult. As a result, the subsequent sections can be interpreted as a brief summary of the collective evidence fo r the relationship of psychological factors with: 1) a new onset of LBP; 2) baseline clinical characteristics; and 3) the influence on future clinical outcomes. New O nset of Low Back Pain A complicating factor involving the role of psychological factors on LBP includes the chicken or the egg dilemma.61, 62 Specifically, are psychological characteristics preexisting factors that influence patients prior to an episode of LBP or do they manifest their influence following the initiation of a LBP experience? To succinctly investigate this question, a longitudi nal, prospective cohort study design consisting of people without LBP would be optimal to determine patients psychological status prior to LBP has an influence on a new episode of LBP. For example, in a classic study by Bigos and colleagues ,63 premorbid factors that were predictive of future LBP episodes were investigated in over 3000 aircraft workers. Results indicated that work perceptions and certain psychosocial responses were most predictive of subsequent reports of LBP.63 P ainrelated fear and pain catastrophizing have been implicated as risk factors associated with the development of future LBP in healthy individuals.64-66 Other studies have suggested similar results in the general public or work settings.62, 64, 65, 6770
28 In summary, there is evidence to suggest that elevated levels of premorbid psychological factors are predictive of new LBP episodes, which is consistent with the results of a systematic review on this topic published in 2000.61 Baseline C linical C haracteristics Psychological factors have been found to be associated with baseline clinical characteristics related to LBP in crosssectional studies Measures of pain catastrophizing,71-73 painrelated fear,71, 74 fear avoidance beliefs,74, 75 depression,73 anxiety,76, 77 and negative affect75 have all been associated with baseline clinical characteristics (e.g., pain intensity, disability) For example, elevated levels of fear a voidance beliefs about physical activity have been found to be positively associated with baseline self reported disability in both acute and chronic LBP patients .75 Other studies have indicated similar relationships between fear avoidance beliefs about wor k,73 painrelated fear,71, 74 or pain catastrophizing71, 72 with baseline self reported disability or pain intensity.71-73 Previous studies conducted by our group in outpatient physical therapy settings have reported on the relationship between individual FAM measures and baseline clinical characteristics in patie nts with LBP.78, 79 Testing the criterion validity of several FAM measures (FABQ PA, FABQ W, FPQ 9, TSK 11) indicated that fear avoidance beliefs about physical activity (FABQ PA) scores contributed additional variance to initial pain intensity ratings (23%) and disability scores (23%), while fear avoidance beliefs about work (FABQ W) scores contributed additional variance to initial physical impairment (13%) and disability scores (8%) in patients with chronic LBP .78 P ain catastrophizing (PCS) scores also contributed additional variance (37%) to initial depression scores. Other FAM measures did not contribute to the respective
2 9 regression models. In a separate study with a different sample of patients, testing the criterion validity of similar FAM measures (FABQ PA, FABQ W, TSK11, PCS) indicated that FABQ PA scores contributed additional variance to initial pain intensity ratings (18%) and disability scores (27%) while PCS scores contributed additional variance to initial pain intensity ratings (6%) and di sability scores (3%) in patients with LBP of various durations.79 Other FAM measures did not contribute to the respective regression models. Further analysis i ndicated that PCS scores mediated the relationship of the FABQ PA by weakening its association with pain intensity ratings and disability scores. In summary, there is evidence to support that elevated levels of psychological distress are associated with hi gher pain intensity, disability, and physical impairment at baseline in a variety of healthcare settings, including physical therapy. Future Clinical Outcomes Although previous LBP history and pain intensity may be consistent predictors of future disabili ty,80 psychological factors have also been suggested to be influential in the development of chronic LBP and related disability. Pain catastrophiz ing,67 painrelated fear,67, 81, 82 fear avoidance beliefs,83-87 depression,85, 88, 89 anxiety,77, 90 negative affect,80, 86 and expectations,86 have all been implicated in the development and progression of chronic LBP Other studies contradict these findings and suggest there is no link between psychological factors (e.g., fear avoidance beliefs) and poor prognosis.91 Distinguishing which psychological factors are most important in predicting the development of chronic LBP is not clear.9, 57, 92-95 One of the classic systematic reviews on the influence of psychological factors associated with spinal pain i s provided by Linton (2000).61 A comparison across settings and time points in 37 prospective studies indicated that stress, distress, anxiety and
30 depressed mood were consistently related to future disability across settings (i.e., general population, primary care, secondary car e, workplace) and time points (i.e., onset of pain episode, acute or subacute, chronic) One study in particular was relevant to this dissertation based on clinical setting and reported clinical outcomes.96 The findings of that study indicated that elevated depression w as highly related to future disability in patients with chronic LBP.96 One of the most recent systematic review s involvin g psychological factors as prognostic indicators for persistent pain and disability is provided by Nicholas and colleagues .11 A comparison across 12 prior review studies indicated consistent re lationships between depression, pain catastrophizing, pain intensity and beliefs about pain with future clinical or occupational outcomes in patients with acute or subacute LBP. Furtherm ore, the authors highlighted that many commonly used psychological screening instruments (e.g. FABQ TSK) may be better suited for patients with persistent pain, therefore suggest potential benefits of using single, composite instruments with a small number of items (e.g., STarT Back Tool) for predicting risk of future clinical outcomes in physical therapy settings .11 One of the most recent systematic reviews involving predictors of poor clinical outcomes at 1year is provided by Chou and Shekelle.97 A comparison across 20 prospective studies consisting of patients with LBP of less than 8 weeks in duration (i.e., acute or subacute) indicated that nonorganic s igns elevated maladaptive pain coping behaviors elevated baseline LBP related disability the presence of psychiatric comorbidities and low general health status were the strongest predictors of poor clinical outcomes at 1 year follow up. Alternatively, l ow levels of fear avoidance and low
31 baseline LBP related disability were strongest predictors of recovery at 1 year follow up. Work environment, baseline pain intensity, and presence of radiculopathy were not as useful for predicting poor clinical outcom es while LBP episode history and demographic variables were not at all useful.97 T he authors suggested that because individual risk factors were relatively weak risk prediction screening instruments could be more useful in predicting poor clinical outcomes in comparison to screening instruments focused on a single domain. In summary, previous review studies have provided evidence that elevated measures of several different psychological factors are positively associated with poor future clinical outcomes in a variety of clinical settings, including physical therapy however there is a definite need for improving the methodology of primary and review studies involving the prognosis of LBP.57 Relevant to this dis sertation, potential benefits of incorporating brief, composite risk prediction instruments for future clinical outcomes (e.g., STarT Back Tool) have been suggested .11, 13, 98 Measuring the I nfluence of P sychological F actors with S elf R eport Q uestionnaires Screening P rocess The intent of primary prevention is the protection of health by personal and community wide efforts As a potential component of primary prevention, screening can provide valuable information regarding risk factors for future disease among healthy individuals in the general population ( e.g., demographics or lifestyle) .99 However, screening is more commonly associated with secondary prevention processes where the intent is early identification of individuals with the potential for poor future outcomes (e.g., LBP related disability).98 As previously described, psychologically informed
32 practice has been presented as a secondary prevention approach to physical therapy for chronic LBP that integrates both biomedical (focused on physical impairments) and cognitivebehavioral (focused on psychological distress) intervention principles.13 The flag system has been suggested as a framework to classify patients and assist in clinical decision making processes based on flag colors representing different types of risk factors.11, 13 Red Flags serious pathology (e.g., fracture) Orange Flags ps ychopathology (e.g., clinical depression) Yellow Flags normal psychological reactions to symptoms (e.g., fear avoidance beliefs about physical activity) Blue Flags perceptions about work and health relationships (e.g., belief that increased work will l ead to further injury) Black Flags healthcare system influence on clinical decisions and contextual factors (e.g., insurance restrictions, socioeconomic status) At this point, it is also important to distinguish between modifiable and nonmodifiable ps ychological risk factors from a physical th erapy intervention perspective because both may be strong predictors of poor future outcomes identified through screening. Main and George13 suggest that the ability to distinguish between these two types of risk factors based on the flag system is a critical component to psychologically informed practice because physical therapists are not trained to address all psychological risk factors. For example, if properly trained, physical therapists are equipped to provide interventions tailored to addressing yellow flags (e.g., fear avoidance beliefs); which are considered modifiable psychologica l risk factor s. However, it is not within the scope of physical therapy practice to provide intervention for orange flags (e.g., clinical depression); which are considered non modifiable psychological risk factor s through physical therapy intervention h owever can be treated by other healthcare professionals (e.g., clinical psychologists)
33 Previous suggestions indicate that implementing appropriate treatment (e.g., behavioral interventions ) during early stages of the LBP experience may be advantageous because of the adverse effects that psychological factors may exert over a prolonged period.8, 100, 101 Results of a high quality RCT also suggest that cognitivebehavioral approaches may be detrimental for individual s not deemed appropriate for this treatment approach.102 There is an adequate amount of literature to suggest that psychological risk factors are modifiable with appropriate interventions and more importantly that psychological risk factor modification is associated with improved patient clinical outcomes.102108 Therefore, the rationale for screening of modifiable psychological risk factors is clinically important because of the potential implications these factors may have on establishing a prognosis and in implementing appropriate interventions. Although the processes involved with establishing a prognosis and screening share s imilarities, they should be interpreted as separate entities in the assessment of patients with LBP. Screening procedures can be used in the early identification of factors that may be influential in the development of chronic disability.98 Additionally, the purpose of psychological screening in patients experiencing LBP has been suggested to be useful in matching patients with appropriate interventions prior to the development of chronicity.100, 109 In comparison, the process involved with establishing a prognosis is often more comprehensive in nature and consists of findings from the patients history and diagnostic tests during the physical examination. Therefore, screening tests should not be int erpreted as diagnostic tools,110 however can be considered a rough assessment to narrow down the number of patients who nee d to be assessed in more detail.100
34 The literature involving screening for modifiable psychological risk factors is extensive and includes studies that use self report questi onnaires ranging from those focusing on a singleconstruct that measure the influence of a specific psychological construct to those that utilize a multipleconstruct approach which determine risk based on overall psychological distress. There are strengt hs and weaknesses associated with self report questionnaires that incorporate either single or multiple psychological construct approaches. For example, singleconstruct screening questionnaires do not investigate the potential influence that other psychological constructs may have on the risk of future clinical outcomes unless several questionnaires are used, which is often not feasible in clinical settings. Multiple construct questionnaires may be more feasible to use in clinical settings, however are fr equently used to determine risk based on overall psychological distress and do not provide detailed information on specific psychological constructs that may ultimately be treatment targets This is an important issue because information on specific psychological constructs may be needed to implement psychologically oriented interventions that reduce the likelihood of developing chronic LBP. Therefore, a n optimal clinical scenario may consist of screening with a brief multiple construct risk prediction in strument (e.g., STarT Back Tool) to determine which patients require further detailed measurement via individual questionnaires .11, 13, 98 Studies o f P sychological M easures: S ingle C onstruct A pproach es Single construct measurement approaches can be used to quantify the influence of a single, specific psychological construct of interest via the use of questionnaires containing a single item or multiple items. The following study results are focused on
35 comparing the contributions of specific psychological factors when using a single construct measurement approach. Crombez and colleagues74 reported on the results of 3 independent studies investigating different aims. In these studies, pain related measures were correlated with each other (r = 0.34 to 0.76) and pain catastrophizing (r = 0.53 to 0.61; study 3), which may suggest construct redundancy of total scores. Specifically, painrelated fear measures were better predictors of self reported disability (FABQ PA, FABQ W, TSK (17physical impairment (FABQ 0.27 to 0.28) than pain intensity ratings or negative affect in patients with chronic LBP.74 Results from a separate analysis in the sam e cohort of patients suggested that pain related fear as measured by the TSK was a better predictor of disability and physical impairment in comparison to negative affect or pain catastrophizing.74 McCracken and colleagues76 compared several FAM measures (PASS, STAI trait, FABQ PA, FABQ W, and FPQ) in their ability to predict baseline clinical characteristics in a cohort of chronic pain patients (LBP 62%) referred to a pain clinic. Although this study consisted of a limited sample size (n = 45), results suggested that anxiety as measured by the PASS, accounted for 16% to 54% of the variance in pain severity, perceived disability (with FABQ W), and pain behavior models (with FABQ W).76 Fritz and colleagues84, 111 reported on the importance of fear avoidance beliefs as measured by the FABQ in patients with acute work related LBP. Results suggested that fear avoidance beliefs as measured by the FABQ W was a significant predictor of disability and work status following 4 weeks of physical therapy, while depression as
36 measured by the CES D and anxiety as measured by the Beck Anxiety Index were not.84, 111 Similar results have been reported in other studies involving work related LBP.112 de Souza and colleagues113 reported that TSK (17 item version) and FABQ scores were highly c orrelated with each other (r = 0.86) when Portuguese versions of these measures were administered in a cohort of LBP patients. Both measures were also moderately correlated with pain intensity (r = 0.42 to 0.43). TSK scores were moderately correlated with Global Perceived Effect (GPE) scale scores (r = 0.46), while FABQ scores were not. Moreover, the TSK outperformed FABQ total and subscale scores in identifying change in GPE scores overtime.113 Woby and colleagues114 reported that several psychological measures (FABQ PA, FABQ W, catastrophizing (via CSQ subscale), appraisals of control (via CSQ 2 single items)) were significantly correlate d with each other (r = 0.37 to 0.51), with the exception of FABQ W and appraisals of control over pain (r = 0.10, p > 0.05) in a cohort of chronic LBP patients. Hierarchical regression analyses revealed that only a greater ability to decrease pain (appr 0.24, p < 0.05) contributed a small but statistically significant proportion of the variance (6%) in pain intensity. After adjusting for age, sex, and pain intensity, only FABQ unique contribution to the prediction of disability in a final model that explained 52% of the variance in disability.114 Meyer and coll eagues73 reported that several psychological measure scores (PCS, FABQ PA, FABQ W, Modified Somatic Perception Questionnaire, Modified Zung Depression Scale) were significantly correlated with pain intensity ratings (r = 0.23 t o
37 0.60), disability scores (r = 0.52 to 0.70), and each other (r = 0.28 to 0.61) in a cohort of chronic LBP patients. In the pain model, only FABQ odel that explained 42% of variance in pain intensity ratings. In the disability model, only FABQ contributions in a model that explained 59% of variance in disability scores.73 George and colleagues78 compared several FAM measures (F ABQ PA, FABQ W, FPQ 9, TSK11, PCS) in a physical therapy setting. Similar to previous studies, FAM measures were significantly correlated with each other (r = 0.30 to 0.69), with the exception of FPQ 9 and FABQ W (r = 0.04, p>0.05). Criterion validity of these FAM measures was examined by their ability to predict baseline clinical outcomes. After controlling for age, sex, and employment status in separate multiple regression models: 1) the PCS contributed an additional 37% (p <0.01) variance in depressi on scores; 2) the FABQ PA contributed an additional 23% (p<0.01) variance in pain intensity ratings; 3) the FABQ W contributed an additional 13% (p<0.01) variance in physical impairment scores; and 4) the FABQ PA and FABQ W contributed an additional 23% and 8% variance in disability scores.78 Lundberg and colleagues115 investigated the individual contribution of FAM variables (i.e., pain intensity, kinesiophobia, depressed mood) on baseline disability (i.e., ODQ scores) for patients with specific or nonspecific chronic LBP in an orthopaedic outpatient setting using a crosssectional study design. For patients with specific LBP, after controlling for age and sex, FAM variables explained 67% of the variance in disability scores with each contributin g uniquely (pain intensity ( = 0.48),
38 kinesiophobia ( = 0.18), depressed mood ( = 0.42)) For patients with nonspecific LBP, after controlling for age and sex, FAM variables explained 63% of the variance in disability scores with only pain intensity ( = 0.51) and depressed mood ( =0.40) contributing uniquely.115 Foster and colleagues116 investigated the ability of 20 psychological factors to predict 6 month disability (i.e., RMDQ scores) following primary care consultation using a longitudinal study design. Five previously validated screening instruments were used in this study (i.e., the Revised Illness Perception Questionnaire; the Tampa Scale of Kinesiophobia; the Coping Strategies Questionnaire; the Hospital Anxiety and Depression Scale; the Pain Self Efficacy Questionnaire ) Only 2 of the baseline psych ological factor scores were not significantly associated with baseline disability scores (i.e., illness perceptions about timeline cyclical, coping subscale interpretation). The 20 factors accounted for between 0.04% and 33.3% of the variance in baseli ne disability scores. A univariate analysis resulted in 11 factors that were associated with disability scores at 6 months (i.e., perceptions about consequences, emotional representations, personal control, treatment control, timeline acute/chronic, ill ness identity, immunity attribution, depression, pain self efficacy, fear avoidance, and catastrophizing). However, after controlling for demographic and baseline clinical characteristics, psychological factors only accounted for 0.5 to 4.9% (p < .01) add itional variance in disability scores at 6 months.116 Final multivariate analyses resulted in only = 0.10), timeline 0.11)) that remained statistically significant (p < .01) in a final model explaining 56.6% of LBP related
39 disability. In this model d epression, fear avoidance, and catastrophizing were no longer statistically significant.116 The authors stressed the importance of illness perceptions and self e fficacy as psychological factors which may predictive of future outcome. Based on the results of this study, others have commented that other usual suspects (e.g., depression, fear avoidance, and catastrophizing) are not always guilty.117 In summary many FAM focused psychological factors are positively correlated with each other when comparing scores obtained from single construct screening questionnaires Collectively FAM focused psychologi cal factors are strongly linked to baseline clinical characteristics and future clinical outcomes; however the magnitude of th ese relationships is not always consistent Studies of P sychologi cal M easures: M ultiple C onstruct A pproach es Multiple construc t measurement approaches can be used to quantify general psychological distress via the use of risk prediction instruments by combining responses from several single item questions, each representing a different psychological construct. The following study results are focused on the STarT Back Tool for the purpose of this dissertation; however it is acknowledged that similar risk prediction instruments have been reported in the literature (e.g., t he Vermont Disability Prediction and rebr o Musculoskeletal Pain Screening Questionnaires).118, 119 The STarT Back Screening Tool which is a 9 item screening questionnaire that consists of items relating to referred leg pain, comorbid pain, disability, and psychological factors (i.e., bothersomeness, catastrophizing, fear, anxiety, and depression).120 Based on STarT responses, patients are allocated into 1 of 3 subgroups (i.e., low, medium, and high risk) describing risk status for future disability
40 and are associated with initial treatment options in primary care settings. For example, patients allocated to the medium risk subgroup are deemed suitable for standard physical therapy intervention, whereas those allocated to the high risk subgroup may requ ire a combination of physical and cognitivebehavioral treatment approaches.120 The STarT was developed and validated in the primary care setting and was intended to be utilized for the identification of treatment subgroups in th at setting. Specific to physical therapy settings, a previous prospective study conducted by our group involv ing patients (n = 214) seeking care for LBP in the outpatient physical therapy setting (n = 3) reported on the distribution of STarT subgroups (33% low risk; 48% medium risk; 19% high risk).121 Patients allocated to STarT low risk had lower initial pain and disability scores in comparison to those allocated to STarT medium or high risk (p < .001) and patients allocated to STarT high risk had higher initial pain and disability scores in comparison to patients allocated to STarT medium or low risk (p < .001). In addition, patients allocated to STarT medium risk had higher initial pain and disability scores in comparison to patients allocated to STarT low risk (p < .001). Further analyses using linear mixed modeling techniques were used to investigate patterns of change in predicted clinical outcomes across the episode of care in a subset of patients (n = 177). Relative to STarT low risk, the high ris k subgroup had larger improvements in predicted outcomes and the medium risk subgroup had similar improvements. Variable timing of follow up assessments was a potential limitation to this study.121 Additional studies that have reported on STarT Back Tool psychometric properties are presented in the methods section of this dissertation.
41 Public Health Significance and Relationship to Rehabilitation Science Previous epidemiological literature has indicated that LBP is a major public health problem at both the individual and societal level s with the development and progression to chronic LBP aggravating matters and accounting for a majority of healthcare resources Previous healthcare service literature has indicated that physical therapy services compromise one of the largest proportions of direct medical costs for LBP,6 whi ch is not surprising considering nearly one third of all patients in outpatient physical therapy settings seek care for LBP.26 S pecific to this dissertation, the FAM provides an explanation for why a minority of individuals that experience an acute episode of LBP eventually develop chronic LBP that is primarily influenced by psychological factors. Psychological screening is primari ly focused on modifiable risk factors This is relevant for physical therapists because early identification of modifiable psychological risk factors for poor clinical outcomes may be most appropriate for patients that have not yet developed and progressed to chronic pain states (i.e., secondary prevention) .11, 13 Furthermor e, it is important that clinicians in outpatient physical therapy settings are able to distinguish between yellow flags (e.g., catastrophizing, fear avoidance beliefs) and orange flags (e.g., depression, anger) with the former appropriate for physical therapy intervention and the latter requiring consultation from mental health professionals.11, 13 F ocusing on routine and specific methods to identify the influence of psychological factors on clinical outcomes has been recommended by Main and George as a component of psychologically informed practice for the management of LBP in physical therapy settings.13 Therefore, a viable goal for rehabilitation scientis ts is to improve the screening process for patients with LBP in order to detect those at risk for developing chronic symptoms. Determining optimal screening procedures will provide
42 clinicians with valuable prognostic and/or treatment effect modi fication in formation to assist in clinical decision making algorithms that may lead to better clinical outcomes for patients with elevated psychological distress
43 CHAPTER 3 RESEARCH HYPOTHESES The primary goals of this dissertation were to: 1) determine the validity of the STarT Back Tool (a multi construct psychological screening measure) in outpatient physical therapy settings and 2) test the clinical utility of the STarT Back Tool in comparison to commonly used singleconstruct psychological screening meas ures. These goals were addressed through three specific aims. The following sections provide initial hypotheses and support for each specific aim Specific Aim 1 C onstruct V alidity of the STarT Back Tool Classification S cheme at I nitial P hysical T herapy E valuation We hypothesized that patients allocated to the STarT high risk subgroup would be associated with higher baseline pain intensity, disability, physical impairment, and psychological distress in comparison to patients allocated to STarT medium and l ow risk subgroups. A previous study by our group in an outpatient physical therapy setting supports this hypothesis for baseline pain intensity and disability scores however did not test for relationships between STarT risk allocation and physical impairment or psychological scores.121 A previous study conducted in a chiropractic setting supports this hypothesis for several individual FAM based psychological measures (i.e., fear avoidance beliefs, pain catastrophizing, and depressive symptoms.122 Discrimination of P sychological F actors amongst STarT Back Tool Classification S tatus at I nitial P hysical T herapy E valuation For this exploratory aim, we hypothesized that depressive symptoms (PHQ 9) would demonstrate a strong ability to discriminate initial STarT classification status, while measures focused on painrelated fear (PCS, TSK 11) and fear avoidance beliefs
44 (FABQ W, FABQ PA) would demonstrate moderate abilities. T hese hypotheses were primarily based on collective results from prior studies using similar subgrouping methodologies. Separate studies using a screening instrument similar to the STarT Back Tool indicated that groups defined as painrelated fear and depressed mood and distressed fear avoidant were associated with poor initial clinical characteristics and outcomes in comparison to low psychological distress groups.100, 123 A previous unpublished study by our group (in revision) u sing discriminant function analyses, in dicated that FABQ W, PCS, and FDAQ scores demonstrated strong relationships, while FABQ PA scores were associated with weaker relationships to three cluster solutions based on the FAM (i.e., low risk, high specific fear, and high fear and catastrophizing). Clustering of P sychological F actors at I nitial P hysical T herapy E valuation without considering STarT Bac k Tool Classification S tatus For this exploratory aim, we hypothesized that two to four distinct FAM based psychological profiles would result fr om a cluster analysis. Again, this hypothesis is primarily based on a previous unpublished study by our group (in revision) that used similar subgrouping methodologies to create three distinct cluster profiles (i.e., low risk, high specific fear, and high fear and catastrophizing) amongst four FAM measures (i.e., FABQ PA, FABQ W, FDAQ, and PCS). We further hypothesized that our emerging cluster profiles would be similar to the STarT risk categorization scheme based on psychological distress.
45 Specific Aim 2 P redictive V alidity of the STarT Back Tool ( 4 W eek O utcomes ) We hypothesized that STarT psychosocial scale scores measured on a continuous scale would have similar abilit y to predict 4week clinical outcomes when c ompared to individual FAM based single construct psychological measures in physical therapy settings Support for this hypothesis is primarily based on the ST arT Back Tool development study from a primary care setting where STarT psychosocial scale scores best discriminated (via area under the receiver operating characteristic curve (AUC) estimates) catastrophizing (0.83) fear (0.81) depressive symptom s (0.76) and disability (0.90) reference standards.120 Furthermore, results from a separate study from primary care indicated that STarT psychosocial su bscale scores were highly correlated with fear (r = 0.66) and catastrophizing (r = 0.67) scores.124 P redictive V alidity of the STarT Back Tool (4 W eek O utcome C hange S cores) For this exploratory aim, we hypothesized that results would be similar to those described above for 4 week outcomes however wanted to investigate potential differences based on multivariate regressi on modeling techniques Specifically, we intended to investigate for differences in results if: 1) initial scores were controlled for in our models with 4 week outcomes serving as the dependent variable or 2) 4week outcome change scores served as dependent variables and initial scores were not entered into our models S pecific Aim 3 Prediction of S ustained STarT H igh R isk A llocation For this aim, we hypothesized that FABQ PA, FABQ W, and PCS scores would be best at predicting patients allocated to STarT high risk at initial physical therapy
46 evaluation and remained high risk at 4 weeks. Preliminary s upport for this hypothesis is primarily based on : 1 ) cross sectional studies investigating relationships between individual FAM based psychological measures and clinical characteristics and 2) the STarT Back subgrouping scheme associating high risk patients with poor future outcomes. Previous studies by our group 78, 79 provide preliminary support for this hypothesis by indicating that initial FABQ PA, FABQ W, and PCS scores were predictive of initial pain and disability scores in outpatient physical therapy settings. Sustained STarT H igh R isk A llocation and O utcomes For this aim, we hypothesized that patients allocated to STarT high risk at intake and remained high risk at 4weeks would have poor er outcomes compared to patients allocated to STarT high risk at intake and changed to low or medium risk at 4 week s. Relevance and Novelty of Specific Aims The relevance and novelty of this dissertation can be demonstrated in several ways First the STarT Back Tool was developed and intended for use in primary care settings.120 To date there has only been one published study reporting on data from patients in outpatient physical therapy settings,121 therefore the results of this study have potential to impact physical therapy practice, which is both a relevant and novel asp ect of this dissertation. Second, in the attempt to meet previous research priorities 5, 11, 13, 56 the STarT Back Tool (a multipleconstruct risk prediction instrument) was compared to individual FAM based psychological measures using a longitudinal st udy design. Incorporating these previous research prioritie s into the design of this study is a relevant aspect of this dissertation that has potential to positively impact future physical therapy research and practice when standardized psychological screening procedures are identified for patients with LBP. Third while appealing to clinicians, there may be
47 disadvantages in using dichotomous cutoff scores of psychological measures for predicting risk of poor outcomes,125 therefore analysis of continuously distributed data has been recommended which can be considered an additional relevant aspect of this dissertation.13 F ourth this study design consisted of sta ndardized timing of follow up assessments and measured multiple clinical outcome domains These are important criteria that have been recomm ended for future research126 and are relevant based on difficulties when attempting to compare results of previous studies consisting of heterogeneous methodologies. Finally, modifiable psychological risk factors have been targeted in this dissertation with the next step being able to match patients with appropriate physical therapy interventions to address these factors which is both a relevant and novel aspect of this dissertation Collectively, all of the above mentioned aspects of this dissertation are in line with a recommended shift in physical therapy management for LBP consistent with psychologically informed practice.13
48 CHAPTER 4 METHODS R esearch Design This study was designed to investigate the validity and clinical utility of the STarT Back Screening Tool in comparison to FAM based singleconstruct psychological measures Co nsecutive patients seeking outpatient physical therapy services for LBP were considered for study participation ( Figure 41 ) Patient s meeting study inclusion criteria and who provided informed consent completed self report forms for demographic, clinical and psychological measures and underwent a standard physical examination that was performed by a licensed physical therapist. Then, patients received physical therapy intervention for LBP that was left to the discretion of the physical therapist. At 4weeks following the initial evaluation, patients completed self report forms for clinical and psychological measures and underwent a st andard physical examination. In the event that patients were not able to attend the 4 week follow up session in person, the option to complete self report forms for clinical and psychological measures through mail was offered as an alternative. In these cases, a standard physical examination was not performed at 4weeks. P articipants Consecutive patients seeking outpatient physical therapy services for LBP in s ix outpatient physical therapy clinics located in Gainesville and Jacksonville, Florida were screened for study eligibility by a physical therapist.
49 Inclusion Criteria Potential study participants met both of the following criteri a before being enrolled into this study: 1) adults between the ages of 18 and 65 years seeking physical therapy for LBP and 2) the ability to read and speak the English language. Exclusion Criteria Potential study participants were ineligible to participate in this study if any of the following criteria were met: 1) the presence of systemic involvement rel ated to metastatic or visceral disease; 2) recent fracture; 3) osteoporosis; or 3) pregnancy. Procedures Consecutive patients seeking outpatient physical therapy services for LBP in s ix outpatient physical therapy clinics located in Gainesville and Jacksonville, Florida were screened for study eligibility by a physical therapist at the initial evaluation session. P hysical therapists provided all patients that met study eligibility criteria with a brief explanation of the study and a study advertisem ent with primary investigator contact information. Clinicians emphasized to patients that participating in this study would not dictate the treatment they received for their LBP and if they elected not to participate they would receive the same treatment. If appropriate, informed consent was obtained in compliance with the University of Floridas Internal Review Board. The following demographic, clinical and psychological measures were administered within the first two physical therapy sessions and again 4 weeks later. Demographic and Clinical Measures Study participants w ere asked to complete a standardized self report questionnaire consisting of questions related to age, sex race, ethnicity, education, household income, marital and employment status. A dditionally, information involving
50 LBP clinical characteristics (i.e., prior surgery symptom duration, symptom onset, symptom location, work related LBP) was obtained. Subgroups for Targeted Treatment (STarT) Back Screening Tool The primary measure of int erest for this dissertation is the STarT Back Tool which is a 9 item screening measure used to identify subgroups of patients with LBP in primary care settings based on the presence of potentially modifiable prognostic factors which may be useful in matching patients with targeted interventions.120 The STarT contains items related to physical (items 2, 3, 5, and 6) and psychosocial (items 1, 4, 7, 8, and 9) factors that have been identified as strong independent predictors for persistent disabling LBP. Potential responses for the STarT are dichotomized (agree or disagree), with the exception of an item related to bothersomeness which uses a 5point Likert scale. Overall STarT scores (ranging from 0 to 9) are determined by summing all positive responses. Psychosocial subscale scores (ranging from 0 to 5) are determined by summing items related to bothersomeness, fear, catastrophizing, anxiety, and depression (i.e., items 1, 4, 7, 8, and 9). Based on overall and psychosocial subscale scoring, the STarT categorizes patients as highrisk (psychosocial subscale scores factors are present with or without physical factors present, medium risk (overall score >3; psychosocial subscale score <4) in which physical and psychosocial factors are present, but not a high level of psychosocial factors, or lowrisk (overall score 0 3) in which few prognostic factors are present.127 The STarT overall (0.79, 95% CI: 0.73 0.95) and psychosocial subscale (0.76, 95% CI: 0.52 0.89) scores has been found to have acceptable test retest reliability (weighted kappa values) in patients with stable symptoms.120 Cronbachs alpha
51 estimates for overall ( 0 .79) and psychosocial subscale ( 0 .74) scores suggest the STarT has demonstrates internal consistency.120 The predictive validity of the STarT has been reported in which subgrouping cutoff scores were predictive of poor 6month disability outcomes in low (16.7%), medium (53.2%), and high (78.4%) risk subgroups.120 The discriminant validity of the STarT scores (AUC range: 0.73 0.92) have been reported and suggest that overall scores best discriminate physical reference standards (e.g., disability and referred leg pain), while psychosocial subscale scores best discriminate psychosocial reference standards (e.g., catastrophizing, fear, and depression).120 The STarT has demonstrated concurrent validity in comparison to the rebro Musculoskeletal Pain Screening Questionnaire, in which both instruments displayed similar subgroup characteristics and the ability to discriminate for disability, catastrophizing, fear, comorbid pain and time off work reference standards.124 Danish and Spanish versions of the STarT Back Tool have been validated.128, 129 Results from a crosssectional study in the chiropractic setting (n = 475) reported on the distribution of STarT subgroups (59% low risk; 29% medium risk; 11% high risk) and doseresponse relationship for STarT subgroup status with continuous scores for depressive symptoms (Major Depression Inventory), fear avoidance beliefs (FABQ total scores) and catastrophizing (CSQ catastrophi zing subscale) .122 A summary of STarT subgroup distributions across studies by setting is presented in Figure 42. Fear Avoidance Model Based Psychological Measures Fear Avoidance Beliefs Questionnair e Fear avoidance beliefs specific to LBP w ere assessed with the FABQ.130 The FABQ consists of a 4 item FABQ phy sical activity scale (FABQ PA, potentially ranging from 0 to 24) and a 7item FABQ work scale (FABQ W, potentially ranging from 0 to
52 42), with higher scores indicating higher levels of fear avoidance beliefs for both FABQ scales. Patients rated their agre ement with statements related to either physical activity or work on a 7 point Likert scale (0 = completely disagree, 6 = completely agree).130 The FABQ scales have been found to have acceptable reliability.130133 Test retest reliability has been reported for the FABQ PA (Pearson r = 0.84 to 0.88) and FABQ W (Pearson r = 0.91 to 0.88).130, 133 Cronbachs alpha estimates for the FABQ PA (ranging from 0 .70 to 0 .83) and FABQ W (ranging from 0 .71 to 0 .88) scores suggest both scales demonstrate internal consistency.81, 130, 133135 The FABW has demonstrated predictive validity for disability and work loss in patients with LBP.84, 102, 111, 133 A suggested FABQ W cutoff score of >29 has been suggested as an indicator of return to work status in patients receiving physical therapy for acute occupational LBP111 and a cutoff score of >22 has been suggested in non working populations.136 An FABQ PA cutoff score of >14, based on a median split of the FABQ has been suggested as an indicator of treatment outcomes in LBP patients seeking care from primary care or osteopathic physicians.105 George and colleagues analyzed data from 2 separate physical therapy intervention clinical trials and found that the FABQ W cutoff score (>29) was a better predictor of self reported disability at 6months in comparison to the FABQ PA cutoff score (>14).136 Pain Catastro phizing Scale The PCS w as used to assess the degree of catastrophic cognitions due to LBP.137 Pain catastrophizing has been broadly defined as an exaggerated negative orientation towards actual or anticipated pain experiences.137 The PCS is a 13item questionnaire with a potential range of 0 to 52, with higher scores indicating higher level s of pain catastrophizing. Patients rate d their agreement with statements related to thoughts and
53 feelings when experiencing pain on a 5point Likert scale (0 = not at all, 4 = all the time).137 The PCS assesses 3 independent dimensions of pain catastrophizing: rumination (items 811 ruminating thoughts, worrying, inability to inhibit pain related thoughts); magnification (items 6,7,13 magnification of the unpleasantness of pain situations and expectancies for negative outcomes); and helplessness (items 15, 12 inability to deal with painful situations).137, 138 Test retest reliability has been reported for the PCS at 6 (r = .75) and 10 weeks (r = .70).137 Cronbachs alpha estimates ranging from .85 to .92 suggest the PCS is inter nally consistent.74, 139, 140 and similar findings have been found for items related to rumination (.85), magnification (.75), and helplessness (.86).140 The PCS has been found to demonstrate several different types of validity.74, 137, 139, 140 Tampa Scale of Kinesiophobia The TSK 11 w as used to assess the degree of fear of movement and injury or reinjury in individuals with LBP.141 The TSK 11 is an 11item questionnaire with a potential range of 11 to 44, wi th higher scores indicating greater fear of movement and injury or re injury due to pain. Patients rated their agreement with statements related to fear of movement and injury or re injury when experiencing pain on a 4 point Likert scale (1 = strongly di sagree, 4 = strongly agree). Test retest reliability (ICC = 0.81; 95% CI: 0.7 1 0 .88) and internal consistency (Cronbachs alpha = .79) have bee reported for the TSK 11.141 The concurrent validity of this instrument has been reported in which changes in disability were correlated with TSK11 change scores (r = 0.51).141 The predictive validity of the TSK 11 has also been reported in which reductions on TSK 11 scores explained an additional 12% of variance in disability in patients with chronic LBP.141 There have been no reports of
54 suggested cutoff scores to identify elevated levels of painrelated fear using the TSK 11, however a 4point reduction in TSK 11 scores has been suggested as an indicator in identifying important reductions in fear of movement (sensitivity = 66%, specificity = 67%).141 Patient Health Questionnaire The PHQ 9 w as used to assess the degree to which depressive symptoms have on patients with LBP. The PHQ 9 is a 9 item questionnaire with a potential range of 0 to 2 7, with higher scores indicating elevated depressive symptoms. Patients rated their agreement with statements related to signs and symptoms of depression on a 4point Likert scale (0 = not at all, 3 = nearly every day). The PHQ 9 total score was used for this study The PHQ 9 has been validated in different settings142, 143 and has been used in studies involving patients with LBP.144 In addition to being used as a screening instrument, the PHQ 9 has also been suggested for use as an outcome measure.145 A PHQ 9 cutoff score of (sensitivity = 88%, specificity = 88%; positive LR = 7.1).142 State Trait Anxiety Inventory The trait portion of the STAI (STAI T) w as used to assess the degree that dispositional anxiety has on patients with LBP.146 Trait anxiety has been suggested to be more closely related to disability following episodes of musculoskeletal pain90 and the STAI T has been used in othe r studies involving LBP patients in physical therapy settings.147 The STAI T is a 20 item questionnaire with a potential range of 20 to 80, with higher scores indicating elevated levels of anxiety. Patients rate d their agreement with statements related to signs and symptoms of trait anxiety on a 4point Likert scale (1 = almost never, 4 = almost always). The STAI T has been found to be reliable and
55 valid,148, 149 however the use of cutoff scores have res ulted in less than optimal results in a sample of psychiatric outpatients.149 A potential limitation in using the STAI T is that it has been found to be limited in its ability to differentiate anxiety from depressive disorders.150 Therefore, we used a validated depression screening instrument (i.e., PHQ 9) in this study. Outcome Measures Pain Intensity Pain intensity w as rated using a numerical pain rating scale (NPRS), ranging from 0 (no pain) to 10 (worst pain imaginable).151-153 Participants w ere asked to rate their current pain intensity, as well as their best and worst level of pain intensity over the past 24 hours. Revised Oswestry Disability Questionnaire LBPrelated disability w as assessed with the revised Oswestry Disability Questionnaire (ODQ), which has 10 items that assesses how LBP affects common daily activities.154, 155 The ODQ has a range of 0% no disability due to LBP to 100% completely disabled due to LBP, with higher scores indicating higher disability from LBP. The ODQ has been found to have high levels of test retest reliability, interna l consistency, validity, and responsiveness.155-157 Roland Morris Disability Questionnaire LBPrelated disability w as also assessed with the Roland Morris Disability Questionnaire (RMD Q ), which has 24 items that assesses the functional status over the past 24 hours in patients with LBP.158 The RMD Q has a range of 0 (no disability due to LBP) to 24 (maximum disability due to LBP), with higher scores indicating higher
56 disability from LBP. The RMD Q has been found to have high levels of test retest reliability, internal consistency, validity, and responsiveness.157, 158 Physical Impairment Index Physical impairment w as assessed using the Physical Impairment Index (PI I ) which was used to establish an objective measurement of physical impairment in patients with LBP.159 The PI I consists of seven physical examination tests routinely implemented in a physical therapy physical examination for patients with LBP. The individual tests include d : 1) lumbar flexion range of motion (ROM); 2) lumbar extension ROM; 3) lumbar lateral flexion ROM; 4) passive straight leg raise ROM; 5) bilateral active straight leg raise; 6) active sit up; and 7) assessment of spinal tenderness. Each test was scored positive or negative based on published cut off values.159 The overall PI I score ranges between 0 and 7, with higher scores indicating greater levels of physical impairment. Good or excellent reliability has been reported for individual items of the PI I and convergent validity has been supported via correlations with disability in patients with chronic LBP.159 Similar results have been reported in patients with acute LBP.160 In patients with acute LBP, the overall PI I score is more responsive to change than its individual test components, with a 1point change representing a minimal detectable change over four weeks of physical therapy.160 S ample Size Estimate Since effect sizes for STarT tool from physical therapy settings were not available when this project was planned our sample size estimate (n = 150) was based on suggested guidelines (i.e., 10 cases per predictor variable) for creating multiple regression models that were not overfit .161, 162 In our separate regression models for clinical outcomes ( specific aim 2 ) there was the potential for 14 to 15 variables t o be
57 entered into each model. Therefore a liberal sample si ze estimate (n = 150) allowed us to meet these minimum guidelines for subsequent analyses. S tatistical Analyses All d ata analys es w ere performed using SPSS, Version 18.0. Means and standard devia tion were calculated for all baseline continuous variables and frequency counts with percentages were calculated for categorical variables. These descriptive statistics are presented for the entire study sample and for each STarT subgroup. The distributions of baseline continuous variables were examined by visual inspection of histograms and calculating skewness and kurtosis statistics. Nonparametric estimates were used for variables with significant deviations from a normal distribution based on visual i nspection, skewness and/or kurtosis statistics. Specific Aim 1 Construct validity of the STarT Back Tool classification scheme at initial physical therapy evaluation The construct validity of the STarT w as assessed by investigating how key i nitial demographical, clinical, and psychological variables discriminated amongst STarT subgroup status for patients seeking outpatient physical therapy. Demographic variables consisted of age, sex, race, ethnicity, employment status, education, and household i ncome. Clinical variables consisted of LBP associated: surgical status, symptom duration, symptom onset, symptom location, baseline pain intensity (NPRS average ratings), LBP related disability (ODQ and RMDQ scores), and physical impairment (PII scores). P sychological variables consisted of measures of fear avoidance beliefs (FABQ physical activity and work scales), pain catastrophizing (PCS), pain related fear (TSK 11), depression (PHQ 9), and anxiety (STAI trait).
58 Baseline STarT risk subgroup differences in variables were tested with oneway analysis of variance (ANOVA) and post hoc testing as appropriate for continuous variables and chi square testing for categorical variables Discrimination of psychological factors amongst STarT Back Tool classificat ion status at initial physical therap y evaluation As an exploratory aim, we investigated how psychological factors discriminated amongst initial STarT Back subgroup status with a discriminant function analysis (DFA). DFA is a multivariate statistical pr ocedure used to determine if a set of variables can predict group membership; in this case initial STarT subgroup status This procedure has been used in other studies investigating classification schemes for patients receiving physical therapy for LBP.163 Specifically, w e used discriminant function analysis to determine: 1) which psychological measures at intake differentiated STarT subgroup status at intake and 2) the accuracy in STarT subgroup allocation at intake using psychological measure scores at intake. Psychological variables (FABQ PA, FABQ W, PCS, TSK11, STAI T, PHQ 9) were entered into a DFA based on their contributions to: 1) the Fear Avoidance Model and 2) STarT psychosocial subscale items that are focused on fear, catastrophizing, anxiety, and depression. T his analysis included three groups (i.e., low, medium, and high risk), therefore two discriminant functions were generated from the DFA. Eigenvalues were reported as a measure of variance, indicating how well the discriminant function discriminate d between STarT subgroups with high er eigenvalues indicating greater discrimination. Canonical correlations were reported as a measure of the relationship between initial STarT subgroup status and the discriminant function, with chi square tests used to determine
59 the significance of the rel ationship. Finally, a summary of classification results from the DFA was generated. Clustering of psychological factors at initial physical therapy evaluation without considering STarT Back Tool classification status As an additional exploratory aim, w e investigated how psychological factors clustered at intake (without consideration for STarT subgroup status) with a cluster analysis. Raw scores for each psychological measure (i.e., FABQ PA, FABQ W, PCS, TSK11, PHQ 9, and STAI T) were transformed to z scores to provide standardized scores for subsequent cluster analysis techniques. An exploratory hierarchical agglomerative cluster analysis was performed using Wards clustering method with squared Euclidean distances as the similarity measure to create distinct cluster profiles among FAM measures. Agglomeration coefficients were inspected and plotted to establish the most optimal cluster solution based on the percent change between adjacent cluster solutions164 and plot characterist ics (i.e., elbow criterion).165 To identify potential cluster group differences in demographic variables and baseline clinical measures, oneway ANOVA with Bonferroni post hoc correction was used for continuous v ariables and chi square analysis was used for categorical data. Specific Aim 2 Predictive validity of the STarT Back Tool (4week outcomes) The predictive validity of the STarT Back Tool was compared to commonly used single construct psychological measure s for 4 week clinical outcomes. The ability of the STarT psychosocial subscale score as a prognostic factor was investigated with four separate multivariate hierarchical regression models with 4week clinical outcomes (pain intensity (NPRS), LBP related disability ( ODQ RMDQ ), or physical impairment
60 ( PII ) scores) serving as dependent variables. These hierarchical regression models consisted of separate simultaneous blocks to account for baseline dependent variable scores (block 1 baseline NPRS, ODQ RMDQ or PII scores depending on the model), demographic and clinical variables (block 2 age, sex, household income, surgery for current condition, duration of current symptoms, and number of PT visits at 4 weeks), STarT scores (block 3 baseline STarT psychosocial scores), and other psychological measure scores (block 4 baseline FABQ PA, FABQ W, PCS, TSK11, STAI T, and PHQ 9 scores). Regression diagnostics were performed to assess for multicollinearity between predictor variables in all multivariate regression analyses. Predictive validity of the STarT Back Tool (4week outcome change scores) As an exploratory aim, we tested the predictive validity of the STarT Back Tool in comparison to commonly used singleconstruct psychological screening measures for 4 week clinical outcome raw change scores Our rationale for this separate analysis was that we wanted to investigate for potential differences in results based on different multivariate regression modeling techniques and because assessing change is a debatable issue when using self report measures .125 Four separate multivariate hierarchical regression models were constructed similar to those described for 4 week outcomes, with the following exceptions:1) raw change scores were calculated for each respective clinical outcome and served as the dependent variable by subtracting 4week scores from initial scores, and 2) block1 which consisted of baseline scores, was removed. Therefore, for models for this aim consisted of: block 2 age, sex, household income, surgery for current condition, duration of current symptoms, and number of PT vi sits at 4 weeks; block 3 bas eline STarT psychosocial scores; and block 4 baseline FABQ PA, FABQ W, PCS, T SK11, STAI T, and PHQ 9 scores
61 Specific Aim 3 Prediction of sustained STarT high risk allocation We investigated factors that were best at predicting patients allocated to STarT high risk at in itial physical therapy evaluation and remained high risk at 4weeks. The relationship between STarT subgroup status at 4 weeks and baseline demographic, clinical, and psychological variables was tested with hierarchical logistic regression analyses. STarT subgroup status at 4 weeks served as the dependent variable and was dichotomized as low / medium risk or high risk. We explored univariate relationships between potentially important baseline variables in our sample with STarT subgroup status at 4 weeks with zeroorder correlations. The hierarchical logistic regression models consisted of separate simultaneous blocks to account for demographic and clinical variables (block 1) and baseline psychological measure scores (block 2) based on univariate relationships (p < .15); which is ack nowledged as a liberal model building approach. Sustained STarT high risk allocation and outcomes As an exploratory analysis, we investigated if patients allocated to STarT high risk at in itial evaluation and remained high risk at 4weeks demonstrated poor er outcomes compared to patients allocated to STarT high risk at intake and changed to low or medium risk at 4 weeks. W e tested for group x time statistical interactions for all clinical outcomes using 2x2 repeated measures model analysis of variance (ANO VA) with between factors consisting of STarT status at 4 weeks (i.e., low/medium or high risk) and time factors consisting of intake and 4 week clinical outcome scores. These exploratory analyses only consisted of patients allocated to STarT high risk at intake.
62 Figure 41 Flow chart of study design. Clinician inquires about participation in study Patient provided with study flyer Informed consent obtained from clinician D emographics and clinical characteristics obtained Psychological q uestionnaires completed o STarT Back Tool (9 items) o Fear Avoidance Beliefs Questionnaire (16 items) o Pain Catastrophizing Scale (13 items) o Tampa Scale of Kinesiophobia (11 items) o Patient Health Questionnaire (depression) (9 items) o State Trait Anxiety Inventory (trait portion) (20 items) Self report outcome measures completed o Pain Intensity (Numerical Pain Rating Scale) o Revised Oswestry Disability Questionnaire (10 items) o Roland Morris Disability Questionnaire Physical Impairment Scal e (7 tests) completed Additional physical examination tests completed o Prone instability test o Hip internal rotation o Passive spine mobility testing o Qualitative spine mobility assessment o Centralization / Peripheralization phenomena # of visits determine d / PT status Re assess: Physical Impairment Scale (if in person) The following will be administered in person or through mail (if pa rticipant is not able to attend 4 week follow up in person): Patient satisfaction with the delivery of PT treatment Re administer psychological questionnaires as listed above Re administer self report outcome measures as listed above # of visits determined / PT status Re assess: Physical Impairment Scale (if in person) The following will be administered in person or through mail (if participant is not able to attend 6 month follow up in person): Patient satisfaction with the delivery of PT treatment Patient satisfaction with the pain effect of PT treatment Patient satisfaction with the function effect of PT treatmen t Re administer psychological questionnaires as listed above Re administer self report outcome measures as listed above Within 1 st w eek (or during initial evaluation) 4 week follow up 6 month follow up Initial Evaluation
63 Figure 42 Initial STarT subgroup distribution across studies by setting.
64 CHAPTER 5 RESULTS Participants Between December 2009 and August 2011, 16 physical therapists from six different outpatient clinics recruited consecutive patients seeking physical therapy services for LBP. During this time 275 patients were screened for eligibility criteria. Of these patients, 123 were excluded from study participation with the most common reason being that they were greater than 65 years of age (n = 47). The remaining 152 patients provided informed consent and were enrolled into the study. Of these patients, six were dropped from the study due to personal reasons Therefore, baseline data was obtained from 1 46 patients and 4week follow up data was obtained from 127 patients (87%) either inperson (n = 108) or through mail (n = 19). Independent samples t tests were used to compare patients that completed the 4 week follow up assessment (n = 127) to those that did not (n = 19) on demographic, clinical, and psychological characteristics at initial evaluation. Results indicated that completers were older (mean difference = 7.9 years; SE = 3.2 ) and reported h igher PHQ 9 scores (m ean difference = 3.0; SE = 1.5 ) c om pared to non completers (ps < .05). Furthermore, noncompleters had a higher proportion of African Americans (28.0%) compared to Caucasians (10.0%) or other races (9.1%) (p = .05) Baseline demographic data for entire sample is presented in Table 5 1. T he mean age of study participants was 41.4 (sd = 13.5) years of age, 89 (61.0%) were women, 26 (17.8%) had prior LBP related surgery, and 19 (13.0%) experienced work related LBP. The mean duration of LBP symptoms for t he current episode of LBP was 483.5 (s d = 1157.7) days with 11.6% acute ( 14 days), 38.4% subacute (15 to 90 days), and
65 47.9% chronic ( > 91 days) episodes Approximate normal distribution for initial pain intensity, disability, physical impairment, and individual FAM based psychological measures was suggested based on visual inspection of histograms and normal qq plots The average number of physical therapy visits at 4 weeks was 6.87 (sd = 2.65; range = 1 to 13 ) where 100 (68.5%) participants were still receiving physical therapy, 15 (1 0.3%) completed physical therapy and were discharged, and 10 (6.8%) elected not to continue with physical therapy. There were no differences in initial or Specific Aim 1 4 week pain intensity, disability, physical impairment, psychological measure scores or STarT subgroup status between participants that participated in 4 week follow up assessments in person compared to those that were done through mail (ps > .05) Based on initial STarT subgroup status, there were no differences in number of visits, follow up rates, me thods of follow up, or current physical therapy status at 4 weeks (ps > .05). Construct V alidity of the STarT Back Tool Classification S cheme at I nitial P hysical T herapy E valuation Baseline patient demographic, clinical, and psychological score characteristics are displayed in Table 5 1 As expected, the distribution of symptom duration (in days) demonstrated significant positive skewness and kurtosis therefore were described durati on with nonparametric statistics. The STarT Back Tool categorized 53 (36.3%) patients as low risk, 55 (37.7%) as medium risk, and 38 (26.0%) as high risk. There were no differences in demographic characteristics amongst STarT subgroups (ps > .05). A comparison of baseline clinical characteristics indicated that patients in the low
66 risk category were more likely to have experienced a gradual onset of symptoms and 2 (2) = 25.88, p < .001). Compa risons amongst all STarT risk subgroups at indicated a doseresponse relationship with several psychological and clinical measures Specifically, patients initially allocated to the S TarT low risk subgroup had lower initial FABQ PA, PCS, TSK11, and PHQ 9 scores compared to those categorized as being medium or high risk (ps < .05). This dose response relationship was also consistent when using the STarT medium or high risk group as a reference for comparisons. Similar results were indicated for pain intensity (NPRS) ratings (ps < .001) and LBP related disability ( RMDQ ) scores (ps < .001). Comparisons amongst STarT low and high risk subgroups indicated that patients initially allocated to the STarT low risk subgroup had lower initial FABQ W and STAI T scores compared to those categorized as high risk (ps < .05) Similar results were indicated for LBP related disability ( ODQ ) and physical impairment ( PII ) scores (ps < .01) In addition to the findings above, the only unique finding for patients initia lly allocated to the STarT medium risk subgroup were greater initial LBP related disability ( ODQ ) scores compared to those categorized as being low risk ( p < .001). Discrimination of P sychological F actors amongst STarT Back Tool Classification S tatus at I nitial P hysical T herapy E valuation Discriminant function analysis run with simultaneous entry method with six predictors (FABQ .001; PHQ .001; STAI = .94, p = .011;) suggested that each predictor contributed uniquely to in itial STarT subgroup allocation and resulted in two discriminant functions
67 which is expected with 3 STarT subgroups. The overa ll test of the two functions (i.e., 2 that predictor scores were able to discriminate amongst the three STarT subgroups. The test for function 2 alone was not significa 2 indicating that that after function 1 is removed, significant discrimination did not remain, therefore results will be reported only for function 1. Function 1 accounted for 42% (canonical R = .65) of the tot al relationship between predictors and STarT subgroups. The first discriminant function accounted for 99% of the betweengroup variability of STarT subgroup status. The pooled within groups correlations between discriminating variables and standardized canonical discriminant functions, as well as the standardized canonical discriminant function coefficients (analogous to multiple regression beta weights) are provided in Table 52 When discriminant function analyses result in multiple functions, the first f unction is considered the most important.166 Therefore, based on the standardized coefficients for t he first discriminant function in Table 5 2 depressive symptoms (PHQ 9) demonstrated the strongest positive relationship with the discriminant function, whereas fear avoidance beliefs about physical activity (FABQ PA) and pain catastrophizing (PCS) demons trated moderate positive relationships and kinesiophobia (TSK 11) demonstrated the weakest positive relationship. Fear avoidance beliefs about work (FABQ W) and trait anxiety (STAI T) demonstrated weak negative relationships with the discriminant function. Together, the functions were able to correctly classify 55.6% of the 3 STarT subgroups (75.0% of the Low Risk, 30.8% of the Medium Risk, and 63.2% of the High Risk), which is higher than the expected rate
68 from chance ( estimated at 33% assuming equal probability of STarT risk group assignment). Clustering of P sychological F actors at I nitial P hysical T herapy E valuation without considering STarT Back Tool Classification S tatus Results from our exploratory cluster analysis investigat ing how psychological factors clustered at intake, w ithout consideration for STarT subgroup status indicated that a 3 cluster solution was appropriate ( Figure 51 ) Z score transformations for psychological measure scores were required for cluster analysis procedures; however raw scores are reported for descriptive purposes because they are more clinically interpretable. Inspection of all predictor z scores indicated that absolute values did not exceed 4.0 (range = 2.54 to 3.20 ), suggesting the data did not contain extreme outliers.166, 167 Inspection of agglomeration coefficients from a hierarchical agglomerative cluster analysis of six psychological measures revealed that the percent change was large (46.8%) between the 3 and 2cluster solutions with relatively smaller changes in preceding steps, suggesting a 3 cluster solution is appropriate, which was further confirmed by visual inspection of plotted agglomeration coefficients.164, 165 Cluster 1 was labeled Low Psychological Distress (n = 84, 59%) and was comprised of individuals that were associated with low individual FAM based psychological measure scores. Cluster 2 was labeled High Psychological Distress (n = 38, 27%) and was comprised of individuals that were associated with high individual FAM based psychological measure scores Cluster 3 was labeled High Psychological Distress with Low Fear Avoidance Work Beliefs (n = 20, 14%) and was com prised of individuals that were ass ociated with high individual FAM based psychological measure scores with the exception being FABQ W
69 Differences were detected between clusters for STarT subgroup distributions (Figure 52). Chi square analyses revealed that the Low Psychological Distres s cluster had proportionally more STarT low risk patients (53.6%) compared to High Psychological Distress (10.5%) or High Psychological Distress with Low Fear Avoidance Work Beliefs (15.0%) clusters and less STarT high risk patients (8.3%) compared to High Psychological Distress (47.4%) or High Psychological Distress with Low Fear Avoidance Work Beliefs (65.0%) clusters ( 2 (4) = 45.70, p < .001 ) There were no differences in demographic variables detect ed between clusters (ps > .05), however there was a potential trend for less patients with work related LBP in the High Psychological Distress with Low Fear Avoidance Work Beliefs cluster (p = .06). Differences in initial clinical measures were detected between clusters for pain intensity ratings (NPRS; p < .001), LBP related disability ( ODQ and RMDQ ; ps < .001), and physical impairment ( PII ; p < .05) scores Post hoc comparisons with Bonferonni correction revealed that the Low Psychological Distress clus ter was associated with lower NPRS, ODQ, RMDQ, and PII scores compared to the High Psychological Distress cluster (p s < .001) and lower ODQ and RMDQ scores compared to the High Psychological Distress with Low Fear Avoidance Work Beliefs cluster (p s = .00 1 ) Differences between clusters were also detected for all psychological measure scores (i.e., STarT total, STarT psychosocial, FABQPA, FABQ W, PCS, TSK11, PHQ 9, and STAI T) (ps < .001 ). Post hoc comparisons with Bonferonni correction revealed that the Low Psychological Distress cluster was associated with lower psychological measure scores compared to other cluster s (p s < .001 ) with the exception of FABQ W scores
70 where the High Psychological Distress cluster was associated with higher FABQ W scores compared to other clusters (ps < .001) Specific Aim 2 Pearson correlation coefficients indicated that initial FAM related psychological measures were significantly correlated with each other (r = 0.19 to 0.57, p < .05) and with initial STarT psychosocial subscale scores (r = 0.20 to 0.62, p < .05). Regression diagnostics indicated that multicollinearity was not a concern amongst predictor variables for all models according to published guide lines.168 Variance inflation factors (VIF) were not substantially greater than 1.0 and were all below 10.0 (range: 1.10 to 2.90), and tolerance estimates were greater than 0.2 (range: 0.34 t o 0.91). For all regression models, assumptions of homoscedasticity and linearity of standardized residuals were met, and independence of residuals was confirmed through the Durbin Watson statistic (range: 1.77 to 2.09).168 Predictive V alidity of the STarT Back Tool (4W eek O utcomes) 4 week pain intensity (NPRS) scores The final regression model for 4week pain intensity ratings is reported in Table 5 3 In th e first block, baseline NPRS scores accounted for 33% (F (1,112) = 54.79 p < .001) of the variance i n 4 week pain intensity ratings In the second through fourth blocks, demographic and clinical variables, STarT psychosocial scores, and other psychological measures contributed an add itional 2% to 3 % of variance, however did not reach statistical significance (model change ps > .05). In the final model explaining 42% of the variance in 4 week pain intensity ratings ( F (14,113) = 5.02, p < .001 ) baseline NPRS scores .21, p = .017) contributed unique variance.
71 4 week disability ( ODQ ) scores The final regression model for 4week ODQ scores is reported in Table 5 4 In the fi rst block, baseline ODQ scores accounted for 48% (F (1,112) = 104 .48, p < .001) of the variance in 4 week ODQ disability scores. In the second block, demographic and clinical variables contributed an additional 7% (F (6,106) = 2.64, p = .020) of variance in 4 week ODQ disability scores. In the third and fourth block s, STarT psychosocial scores and psychological measure scores contributed an additional 0 .4% and 3% of variance respectively, however did not reach statistical significance (model change ps > .05). In the final model explaining 58% of the variance in 4 week ODQ scores (F (14,113) = 9.89, p < .001 ) baseline ODQ .22, p = .004) scores contributed unique variance and a potential trend was indicated for FABQ p = .065). 4 week disability ( RMDQ ) scores The final regression model for 4week RMDQ scores is reported in Table 5 5 In the first block, baseline RMDQ scores accounted for 42% (F (1,110) = 81. 12, p < .001) of the variance in 4week RMDQ disab ility s cores. In the second through fourth blocks, demographic and clinical variables, STarT psychosocial scores, and other psychological measures contributed an additional 1% to 4 % of variance, however did not reach statistical significance (model change ps > 05). In the final model explaining 53% of the variance in 4 week RMDQ scores (F (14,111) = 7.84 p < .001 ) baseline RMDQ .18, p = .026), and FABQ
72 4 week physical impairment ( PII ) scores The final regression model for 4week physical impairment scores is reported in Table 5 6 In the first and second blocks, baseline PII scores accounted for 41% (F (1,95) = 66.44, p < .001) and demographic and clini cal variables contributed an additional 8% (F (6,89) = 2.23, p = .047) of variance in 4 week physical impairment scores. In the third b lock, STarT psychosocial scores contributed an additional 0.4% of variance, however did not reach statistical significance (model change p > .05). In the fourth block, other psychological measures contributed an additional 8% (F (6,82) = 2.68, p = .020) of variance in 4 week physical impairment scores. In the final model explaining 58% of the variance in 4 week PII scores (F (14,96) = 7.95, p < .001 ) baseline PII W scores ( .25, p = .006) contributed unique variance. Predictive V alidity of the STarT Back Tool (4W eek O utcome C hange S cores) 4 week pain intensity (NPRS) raw change scores The final regression model for intake to 4 week pain intensity raw change scores is reported in Table 5 7 In the first block, demographic and clinical variables accounted for 5 % of the variance i n change scores however did not reach statistical significance (p = .427) In the second block STarT psychosocial scores contributed an additional 10% (F ( 1,106 ) = 11.92, p < .001 ) of variance i n change scores In the third block, other psychological measures contributed an additional 4 % of variance, however did not reach statistical significance (model change p = .557) In the final model explaining 19% of the variance in intake to 4week pain intensity change scores (F (13,113) = 1.79, p = .055) household income 23, p = .023) and STarT psychosocial scores .32 p = .0 2 7) contributed unique variance
73 4 week disability ( ODQ ) raw change scores The final regression model for intake to 4 week ODQ raw change scores is reported in Table 5 8. In the first block, demographic and clinical variables accounted for 11% of the variance i n change scores however did not reach statistical significance (p = .058). In the second and third blocks, STarT psychosocial scores and psychological measure scores contributed an additional 2% and 4% of variance respectively, however did not reach statistical significance (model change ps > .05). In th e final model explaining 16% of the variance in intake to 4week ODQ change scores (F (13,113) = 1.49, p = .133 ) only 7 p = .0 11 ) contributed unique variance. 4 week disability ( RMDQ ) raw change scores The final regression model for intake to 4 week RMDQ raw change scores is reported in Table 5 9. In the first block, demographic and clinical variables accounted for 6 % of the variance i n change scores, however did not reach statistical significance (p = 354 ). In the second block, STarT psychosocial scores contributed an additional 14% (F (1,104) = 17.67, p < .001) of variance in change scores. In the third block, other psychological measures contributed an additional 4%, however did not reach statistica l significance (model change p = .451). In the final model explaining 24% of the variance in intake to 4week RMDQ change scores (F (13,111) = 2 .40, p = .007 ) .22, p = .031), 0 p = .0 42) = .44, p = .002), contributed unique variance. 4 week physical impairment ( PII ) raw change scores The final regression model for intake to 4 week PII raw change scores is reported in Table 5 10. In the first block, demographic and clinical variables accounted for 8 % of the variance i n change scores, however did not reach statistical significance (p = 280 ).
74 In the second and third blocks, STarT psychosocial scores and psychological measure scores contributed an additional 0% and 10% of variance respectively, however did not reach statistical significance (model change ps > .05). In the final model explaining 18% of the variance in intake to 4week PII change scores (F (13,96) = 1. 38, p = .189 ) only the number of physical therapy visits = 26, p = .0 41), contributed unique variance. Specific Aim 3 Prediction of S ustained STarT H igh R isk A llocation At baseline and 4weeks, STarT subgroup status was available for 82.2% (n = 120) of the total study sample. At intake, 27.5% (n = 33) of these patients were allocated to the STarT high risk subgroup in comparison to 6.7% (n = 8) at 4weeks. Logistic regression analyses indicated that initial FABQ PA scores were significant predictors of sustained STarT subgroup status at 4 weeks (B = .28, p = .032, OR = 1.32), with higher FABQ PA scores associated with higher probability of being allocated to the STarT high risk subgroup (Table 5 11 ). Based on these results and specific to this study sample, each unit increase in FABQ PA scores increases the odds of sustained STarT high risk subgroup status at 4 weeks from 1.00 to 1.32. Sustained STarT H igh R isk A llocation and O utcomes R esults from an exploratory repeated measures ANOVA analys i s run with only patients that were high risk at baseline (n = 33) indicated that there were no significant group (i.e., sustained or non sustained high risk status) x time interactions for NPRS (F ( 1,31) = 0.00, p = .999, partial 2 = .00) or RMDQ (F ( 1,29) = 0.66, p = .422, partial 2 = .02) scores, with a potential trend for PII (F ( 1,25) = 2.96, p = .098, partial 2 = .11) scores. However, there was a significant group x time interaction for ODQ (F ( 1,31 ) =
75 7. 77, p = .0092 = .20 ) scores Patients allocated to STarT high risk at intake and changed to STarT low or medium risk at 4 weeks were associated with decreased ODQ scores (M = 11.3, sd = 13.5) while patients that remained in STarT high risk were associated with increased ODQ scores (M = 5.0, sd = 8.6)
76 Table 5 1. Baseline Patient Characteristics Variable Total Sample (n = 146) STarT Low Risk (n = 53) STarT Medium Risk (n = 55) STarT High Risk (n = 38) p value Age ( Y ears) 41.4 (13.5) 38.8 (14.0) 44.6 (12.8) 40.3 (13.0) .069 Sex (Female) (Male) 89 (61.0%) 57 (39.0%) 28 (52.8%) 25 (47.2%) 37 (67.3%) 18 (32.7%) 24 (63.2%) 14 (36.8%) .291 Race (Caucasian) (African American) (Other) 110 (75.3%) 25 (17.1%) 11 (7.6%) 39 (73.6%) 12 (22.6%) 2 (3.8%) 41 (74.5%) 9 (16.4%) 5 (9.1%) 30 (79.0%) 4 (10.5%) 4 (10.5%) .635 Ethnicity (Hispanic or Latino) (Not Hispanic or Latino) (Missing) 13 (8.9%) 130 (89.0%) 3 (2.1%) 3 (5.7%) 49 (92.4%) 1 (1.9%) 6 (10.9%) 49 (89.1%) 0 (0.0%) 4 (10.5%) 32 (84.2%) 2 (5.3%) .579 Employment status (Employed) (Unemployed) (Retired) (Missing) 94 (64.4%) 39 (26.7%) 10 (6.8%) 3 (2.1%) 35 (66.0%) 15 (28.3%) 2 (3.8%) 1 (1.9%) 39 (70.9%) 9 (16.4%) 6 (10.9%) 1 (1.8%) 20 (52.6%) 15 (39.5%) 2 (5.3%) 1 (2.6%) .219 Education completed (Less than high school) (High school) (College) (Post graduate) (Missing) 7 (4.8%) 85 (58.2%) 43 (29.5%) 10 (6.8%) 1 (0.7%) 3 (5.7%) 30 (56.6%) 12 (22.6%) 7 (13.2%) 1 (1.9%) 0 (0.0%) 31 (56.4%) 21 (38.2%) 3 (5.4%) 0 (0.0%) 4 (10.5%) 24 (63.2%) 10 (26.3%) 0 (0.0%) 0 (0.0%) .111 Income level (< $20,000) ($20,000 to $35,000) ($35, 001 to $50,000) ($50,001 to $70,000) (> $70,000) (Missing) 32 (21.9%) 22 (15.1%) 20 (13.7%) 22 (15.1%) 45 (30.8%) 5 (3.4%) 15 (28.3%) 5 (9.4%) 7 (13.2%) 6 (11.3%) 17 (32.1%) 3 (5.7%) 8 (14.5%) 12 (21.8%) 10 (18.2%) 9 (16.4%) 15 (27.3%) 1 (1.8%) 9 (23.7%) 5 (13.2%) 3 (7.9%) 7 (18.4%) 13 (34.2%) 1 (2.6%) .415 Previous low back surgery (Yes) 26 (17.8%) 8 (15.1%) 11 (20.0%) 7 (18.4%) .773 Symptom duration (Days) 483.6 (1157.7) 538.3 (1208.1) 455.2 (1234.3) 448.2 (991.7) .913 Acute ( Subacute (15 90 days) Chronic ( (Missing) 17 (11.6%) 56 (38.4%) 70 (47.9%) 3 (2.1%) 3 (5.7%) 20 (37.7%) 29 (54.7%) 1 (1.9%) 11 (20.0%) 17 (30.9%) 25 (45.5%) 2 (3.6%) 3 (7.9%) 19 (50.0%) 16 (42.1%) 0 (0.0%) .079
77 Table 5 1. Continued. Variable Total Sample (n = 146) STarT Low Risk (n = 53) STarT Medium Risk (n = 55) STarT High Risk (n = 38) p value Symptom onset (Gradual) (Sudden) (Traumatic) (Missing) 70 (47.9%) 53 (36.3%) 21 (14.4%) 2 (1.4%) 34 (64.2%) 13 (24.5%) 5 (9.4%) 1 (1.9%) 23 (41.8%) 22 (40.0%) 10 (18.2%) 0 (0.0%) 13 (34.2%) 18 (47.4%) 6 (15.8%) 1 (2.6%) .042 Symptom location (Low back only) (Low back & buttock or thigh) (Low back & lower leg) 49 (33.6%) 72 (49.3%) 25 (17.1%) 25 (47.2%) 23 (43.4%) 5 (9.4%) 15 (27.3%) 30 (54.5%) 10 (18.2%) 9 (23.7%) 19 (50.0% ) 10 (26.3%) .059 Work related LBP (Yes) 19 (13.0%) 8 (15.1%) 7 (12.7%) 4 (10.5%) .813 FAM Based Psychological Measures FABQ PA (potential range, 0 24) a FABQ W (potential range, 042)b PCS (potential range, 052)a TSK 11 (potential range, 1144)a PHQ 9 (potential range, 027)a STAI T (potential range, 2080)b 14.6 (5.8) 12.8 (11.1) 16.9 (12.2) 25.2 (6.9) 7.4 (6.1) 36.0 (9.2) 11.8 (5.5) 9.6 (9.6) 10.7 (9.6) 21.9 (6.4) 3.7 (3.8) 33.4 (7.6) 14.6 (5.4) 13.7 (10.7) 17.1 (10.5) 25.2 (5.4) 7.6 (5.5) 36.0 (9.9) 18.4 (4.4) 15.8 (12.6) 25.3 (12.9) 29.7 (6.9) 12.4 (6.0) 39.5 (9.4) <.001 .023 <.001 <.001 <.001 .008 STarT Measures STarT Overall score (potential range, 0 9) a STarT Psych score (potential range, 0 5) a 4.5 (2.5) 2.4 (1.6) 1.8 (1.0) 0.9 (0.8) 5.1 (1.1) 2.3 (0.9) 7.4 (1.1) 4.5 (0.5) <.001 <.001 Clinical Outcome Measures NRS Average (potential range, 0 10) a 5.4 (2.0) 4.4 (1.9) 5.6 (1.9) 6.6 (1.5) <.001 ODQ (potential range, 0 100) b 32.5 (16.7) 20.0 (12.7) 37.0 (14.1) 43.5 (14.2) < .001 RMDQ (potential range, 0 24) a 11.2 (6.0) 6.7 (4.5) 12.1 (5.1) 16.2 (4.2) <.001 PII (potential range, 0 7) b 3.9 (1.8) 3.3 (1.6) 4.0 (2.0) 4.6 (1.6) .006 All values represent means (standard deviations) or frequency counts (percentages). a indicates (low risk < medium risk < high risk) (p < .05); b indicates (low risk < high risk) (p < .05)
78 Table 5 2. Coefficients of Psychological Measure Predictor Variables of the Discriminant Function. Discriminant Function 1 FAM Based Psychological Measure Standardized Coefficient a Correlation Coefficient b FABQ PA 0.449 0.579 FABQ W 0.126 0.256 PCS 0.351 0.621 TSK 11 0.083 0.567 PHQ 9 0.692 0.785 STAI T 0.119 0.300 Key: a indicates standardized canonical discriminant function coefficients; b indicates pooled within groups correlations between discriminating variables and standardized canonical discriminant functions
79 Table 5 3. Four Week Pain Intensity Scores (NPRS) Model R 2 Adj. R 2 R 2 change Model change (p value) 1. Baseline NPRS score .33 .32 .33 <.001 2. Demographic & Clinical .37 .33 .04 .320 3. STarT Psychosocial score .39 .34 .02 .067 4. Psychological measure scores .42 .33 .03 .655 Final Model for 4 Week Pain Intensity (NPRS) Ratings (n = 114) Variable B p value VIF Baseline NPRS score .81 .67 < .001 1.92 Age .01 .07 .419 1.38 Sex .37 .08 .341 1.10 Household income .31 .21 .017 1.27 Surgery .17 .03 .731 1.16 Duration of current symptoms 3.09E 5 .02 .838 1.11 PT visits .003 .003 .975 1.39 STarT Psychosocial score .30 .21 .104 2.76 FABQ PA .05 .12 .213 1.65 FABQ W .01 .07 .439 1.37 PCS .01 .05 .655 2.50 TSK 11 .02 .05 .705 2.51 PHQ 9 .02 .05 .670 2.10 STAI T .004 .01 .878 1.52 Final model accounted for 42% of the variance in NPRS scores [F (14,113) = 5.02, p < .001 ]
80 Table 5 4. Four Week Disability Scores ( ODQ ) Model R 2 Adj. R 2 R 2 change Model change (p value) 1. Baseline ODQ score .48 .48 .48 < .001 2. Demographic & Clinical .55 .52 .07 .020 3. STarT Psychosocial score .55 .52 .004 .365 4. Psychological measure scores .58 .52 .03 .327 Final Model for 4 Week Disability (ODQ) Scores (n = 114 ) Variable B p value VIF Baseline ODQ score .59 .57 < .001 2.01 Age .24 .19 .017 1.43 Sex 3.68 .10 .141 1.12 Household income 2.39 .22 .004 1.27 Surgery 1.13 .03 .720 1.23 Duration of current symptoms .00 .02 .766 1.11 PT visits .68 .10 .186 1.33 STarT Psychosocial score .08 .01 .945 2.58 FABQ PA .48 .16 .065 1.66 FABQ W .08 .06 .474 1.41 PCS .004 .003 .979 2.49 TSK 11 .02 .009 .932 2.51 PHQ 9 .16 .06 .548 2.10 STAI T .13 .07 .404 1.48 Final model accounted for 58% of the variance in ODQ scores [F (14,113) = 9.89, p < .001 ]
81 Table 5 5. Four Week Disability Scores ( RMDQ ) Model R 2 Adj. R 2 R 2 change Model change (p value) 1. Baseline RMDQ score .42 .42 .42 < .001 2. Demographic & Clinical .48 .45 .06 .099 3. STarT Psychosocial score .49 .45 .01 .306 4. Psychological measure scores .53 .46 .04 .159 Final Model for 4 Week Disability (RMDQ) Scores (n = 112 ) Variable B p value VIF Baseline RMDQ score .59 .61 < .001 2.24 Age .11 .26 .003 1.41 Sex .03 .002 .974 1.13 Household income .67 .18 .026 1.29 Surgery .16 .01 .889 1.21 Duration of current symptoms 5.96E 6 .001 .987 1.16 PT visits .22 .10 .240 1.34 STarT Psychosocial score .73 .20 .095 2.90 FABQ PA .21 .20 .027 1.71 FABQ W .02 .03 .685 1.42 PCS .08 .17 .114 2.39 TSK 11 .06 .07 .532 2.61 PHQ 9 .001 .001 .989 2.20 STAI T .04 .06 .489 1.50 Final model accounted for 53% of the variance in RMDQ scores [F (14,111) = 7.84, p < .001 ]
82 Table 5 6. Four Week Physical Impairment Scores ( PII ) Model R 2 Adj. R 2 R 2 change Model change (p value) 1. Baseline PII score .41 .41 .41 < .001 2. Demographic & Clinical .49 .45 .08 .047 3. STarT Psychosocial score .49 .45 .004 .401 4. Psychological measure scores .58 .50 .08 .020 Final Model for 4 Week Physical Impairment (PII) Scores (n = 97 ) Variable B p value VIF Baseline PII score .54 .51 < .001 1.39 Age .03 .22 .015 1.46 Sex .17 .04 .587 1.15 Household income .17 .13 .094 1.24 Surgery .75 .15 .073 1.32 Duration of current symptoms 1.38E 4 .08 .307 1.12 PT visits .11 .14 .121 1.59 STarT Psychosocial score .08 .07 .536 2.38 FABQ PA .03 .08 .362 1.65 FABQ W .04 .25 .006 1.47 PCS .005 .04 .740 2.30 TSK 11 .008 .03 .808 2.53 PHQ 9 .008 .03 .800 2.29 STAI T .01 .07 .480 1.81 Final model accounted for 58% of the variance in PII scores [F (14,96) = 7.95 p < .001 ]
83 Table 5 7 Intake to 4 week Pain Intensity (NPRS) Change Scores Model R 2 Adj. R 2 R 2 change Model change (p value) 1 Demographic & Clinical 05 00 05 427 2 STarT Psychosocial score 15 09 10 .001 3 Psychological measure scores 19 08 .0 4 557 Final Model for Intake to 4Week Pain Intensity (NPRS) Change Scores (n = 114 ) Variable B p value VIF Age .01 .05 .603 1.33 Sex .42 .10 .290 1.10 Household income .29 .23 .023 1.27 Surgery .18 .03 .717 1.17 Duration of current symptoms 1.90E 5 .01 .900 1.11 PT visits .03 .04 .729 1.33 STarT Psychosocial score .39 .32 .027 2.45 FABQ PA .06 .16 .179 1.64 FABQ W .009 .05 .626 1.31 PCS .02 .12 .393 2.33 TSK 11 .03 .09 .530 2.44 PHQ 9 .03 .09 .510 2.05 STAI T 1.04E 4 4.82E 4 .996 1.50 Final model accounted for 19 % of the variance in NRS change scores [F (13,113 ) = 1.79 p = .055 ]
84 Table 5 8 Intake to 4 Week Disability ( ODQ ) Change Scores Model R 2 Adj. R 2 R 2 change Model change (p value) 1 Demographic & Clinical 11 06 11 .0 58 2 STarT Psychosocial score 12 07 .0 2 137 3 Psychological measure scores 16 05 .0 4 604 Final Model for Intake to 4Week Disability (ODQ) Change Scores (n = 114) Variable B p value VIF Age .14 .14 .190 1.35 Sex 5.16 .19 .056 1.10 Household income 2.24 .27 .011 1.27 Surgery 1.73 .05 .605 1.18 Duration of current symptoms 1.13E 4 .01 .913 1.11 PT visits .66 .12 .240 1.33 STarT Psychosocial score 1.06 .13 .363 2.43 FABQ PA .34 .14 .219 1.64 FABQ W .05 .04 .664 1.31 PCS .14 .14 .325 2.35 TSK 11 .22 .11 .436 2.44 PHQ 9 .03 .02 .903 2.04 STAI T .11 .07 .503 1.48 Final model accounted for 16 % of the variance in ODQ change scores [F (13,113 ) = 1.49 p = .133 ]
85 Table 5 9 Intake to 4 Week Disability ( RMDQ ) Change Scores Model R 2 Adj. R 2 R 2 change Model change (p value) 1 Demographic & Clinical .06 .01 .06 .354 2 STarT Psychosocial score .20 .14 .14 < .001 3 Psychological measure scores .24 .14 .04 .451 Final Model for Intake to 4Week Disability (RMDQ) Change Scores (n = 112) Variable B p value VIF Age .08 .22 .031 1.36 Sex .10 .01 .915 1.12 Household income .65 .20 .042 1.29 Surgery 1.01 .08 .418 1.17 Duration of current symptoms 2.02E 4 .05 .602 1.14 PT visits .16 .08 .436 1.33 STarT Psychosocial score 1.37 .44 .002 2.51 FABQ PA .15 .17 .133 1.67 FABQ W .03 .06 .536 1.33 PCS .07 .18 .195 2.38 TSK 11 .02 .03 .846 2.58 PHQ 9 .08 .10 .413 2.09 STAI T .04 .07 .541 1.50 Final model accounted for 24 % of the variance in RMD change scores [F (13,111 ) = 2.40 p = .007 ]
86 Table 5 10 Intake to 4 Week Physical Impairment ( PII ) Change Scores Model R 2 Adj. R 2 R 2 change Model change (p value) 1 Demographic & Clinical 08 02 .08 280 2 STarT Psychosocial score 08 01 .00 955 3 Psychological measure scores 18 05 10 139 Final Model for Intake to 4Week Physical Impairment (PII) Change Scores (n = 97 ) Variable B p value VIF Age .01 .09 .424 1.31 Sex .03 .01 .927 1.14 Household income .18 .17 .119 1.24 Surgery .40 .10 .384 1.29 Duration of current symptoms 8.29E 5 .06 .589 1.11 PT visits .16 .26 .041 1.56 STarT Psychosocial score .18 .19 .226 2.33 FABQ PA .01 .05 .684 1.64 FABQ W .03 .21 .076 1.44 PCS .01 .08 .600 2.29 TSK 11 .04 .16 .313 2.45 PHQ 9 .01 .05 .758 2.29 STAI T .004 .03 .831 1.80 Final model accounted for 1 8% of the variance in PII change scores [F (13 ,96) = 1.38 p = .189 ]
87 Table 5 11 Overall Logistic Regression Model Predicting STarT High Risk Subgroup Status at 4 weeks Predictor B S.E. B 2 (df = 1) p value Exp(B) (95% CI) Age .08 .05 2.28 .131 1.08 (0.98 1.19) Surgery 19.56 7017.66 .00 .998 0.00 ( --) FABQ PA .28 .13 4.59 .032 1.32 (1.02 1.70) PCS .03 .06 .22 .639 1.03 (0.92 1.15) TSK 11 .01 .11 .01 .921 0.99 (0.80 1.22) PHQ 9 .05 .09 .32 .569 1.05 (0.89 1.25) STAI T .08 .05 2.71 .100 1.08 (0.98 1.19) Constant 14.74 4.89 9.08 .002 --2 2 (7) = 22.52, p = .002); Goodness of fit test: Hosmer & 2 (8) = 2.65, p = .955); R2-type indices: Hosmer & Lemeshow R2 = .384 (equation = model 2 / null model -2LL), Cox & Snell R2 = .172, Nagelkerke R2 = .443.
88 Figure 51. C luster profiles using initial FAM measure scores
89 Figure 52. STarT risk distribution amongst cluster profiles
90 CHAPTER 6 DISCUSSION In the profession of physical therapy, Psychologically Informed Practice has recently been presented as a secondary prevention approach for chronic LBP that emphasizes routine and specific identification of potentially modifiable psychological risk factors.13 Validation of measurement instruments in physical therapy settings has been highlighted as a top research priority before recommending their use in clinical practice.13 The STarT Back Tool has been developed and intended for use in primary care settings for subgrouping LBP patients at risk for poor future disability.120 Utilization of the STarT Back Tool in outpatient physical therapy settings is promising,121 however has not been extensiv ely investigated. Therefore, the purpose of this dissertation was to: 1) determine the validity of the STarT Back Tool in outpatient physical therapy settings and 2) test the clinical utility of the STarT Back Tool in comparison to commonly used individual Fear Avoidance Model psychological screening measures We sought to achieve this purpose through three specific and several supporting exploratory aims. Statement of P rincipal F indings The STarT Back Tool classification scheme demonstrated good construct validity based on its ability to discriminate patients on initial clinical and psychological measures during the physical therapy evaluation. Most individual Fear Avoidance Model psychological measures demonstrated moderate to strong abilities in discriminating initial STarT subgroup status and similar psychological profiles were generated when using cluster analysis to develop independent psychological subgroups. B oth STarT psychosocial subscale and individual psychological measures demonstrated poor predictive validity for 4 week clinical outcomes, after controlling for initial scores.
91 However, our findings suggested that STarT psychosocial subscale scores may be important for predicting raw pain intensity and disability change scores. Finally, f ear avoidance beliefs about physical activity were important for predicting continued STarT high risk categorization after 4 weeks of physical therapy This finding has potential clinical implications for the STarT Back Tool as a treatment monitoring measure because patients that remained high risk at 4weeks reported worsening disability (i.e., higher ODQ scores) from intake while patients that changed STarT categorization from high risk to low or medium risk reported improved disability over 4 weeks Fut ure analyses of data from this study will determine if those that sustained STarT high risk status at 4 weeks also had poorer 6 month outcomes. Strengths and W eaknesses of S tudy This study consisted of several strengths. First, this was only the second study121 we are aware of that has incorporated STarT Back Tool data from physical therapy settings. This may have important implications because the STarT Back Tool was developed and intended for use in primary care settings .120, 122, 124, 128, 169 Second, in an attempt to meet previous research priorities ,5, 11, 13, 56, 126 the STarT Back Tool was compared to individual Fear Avoidance Model psychological measures using a study design with standardized timing of follow up assessments and measurement of multip le outcome domains. Finally, this study focused on potentially modifiable psychological risk factors which have important implications because future studies involving matched treatment approaches may consider incorporating the re sults of this study. This study also consisted of several limitations. First, we did not measure the influence that other potentially important psychological factors (e.g., self efficacy, preference, expectation) have on LBP outcomes.116, 170 Second, physical therapy
92 treatment was not standardized in this study. Specifically, clinicians were not required to review psychological measur e scores and treatment was not tailored to address psychological factors which may have influenced our results. Finally, we did not have access to 6 month outcomes during preparation of this dissertation which have potential to further support the findings of this study Comparison to O ther S tudies The findings of this study are similar to previous studies that have used the STarT Back Tool. Hill and colleagues120 indicated that initial STarT Back overall and psychosocial scores best discriminated initial self reported disability and psychosocial re ference standards respectively in primary care settings. Importantly, in that study, reference standards were based on dichotomized cutoff scores which may be associated with clinical limitations13 and other outcome domains (e.g., pain intensity, physical impairment) were not included in validity analyses Fritz and colleagues121 reported similar findings to Hill and colleagues120 for pain intensity and disability when measured on continuous scales in outpatient physical therapy settings however did not include individual psychological measures Therefore, a potential strength of this study in comparison t o previous studies involving the STarT Back Tool includes the use of multiple outcome domains and several individual Fear Avoidance Model measures The results of this st udy are similar to Fritz and colleagues121 based on relationships between initial STarT subgroup status and initial pain and disability however also provides additional information involving initial physical impairment Potentially, this has important clinical implications for physical therapists in outpatient physical therapy settings based on the STarT Back subgrouping scheme and its ability to discriminate among multiple outcome domains.
93 Foster and colleagues found that after controlling for demographic and baseline clinical characteristics, only 11 out of 20 psychological factors investigated accounted for between 0.5% to 4.9% (p < .01) additional variance in LBPrelated disa bility at 6 months in primary care settings .116 Our study findings are similar based on the addition of individual p sychological measures or STar T psychosocial scores account ing for between 0.4% to 4.0% additional variance in pain intensity and disability at 4 weeks however none reached statistical significance (p > .05) Our study findings potentially expand on Foster and colleagues116 based on the addition of individual psychological measures accounting for 8.0% additional variance in physical impairment at 4weeks (p < .05). Our study also provided alternative regression modeling techniques to investigate for differences based on using outcome change scores as dependent variables. These results indicated similar results based on the addition of individual psychological measures accounting for between 4.0% to 10.0% (p > .05) additional variance in all outcomes at 4weeks In contrast, STarT psychosocial scores account ed for 10.0% and 14.0% (p < .001) additional variance in pain intensity and disability (i.e., RMDQ) respectively. With the exception of fear avoidance beliefs about work for predicting physical impairment at 4weeks, f ear avoidance beliefs about physical activity was the only other important individual psychological factor as it predict ed both disability and patients that remained STarT high risk at 4weeks. Similar to the results of this study, the influence of initial fear avoidance beliefs about physical activity on disability following 4weeks of physical therapy has been implicated in p revious studies by our group.78, 79 When attempting to interpret the relationship between fear avoidance beliefs about work and
94 outcomes, one potential imitation to th is study is that only 13.0% of patients reported work related LBP. Previous studies that have reported on the influence of fear avoidance work beliefs have primarily consisted of patients with work related LBP or appropriate numbers to conduct subgroup analyses .84, 111 Furthermore, it has been suggested that fear may be a m ore important predictor of chronic LBP outcomes and may not be as important during earlier stages of LBP .91 Potential Implications A small portion of patients with acute and chronic LBP seek physical therapy services41, 42 and previous findings indicate that a small percentage of patients with chronic LBP are utilizing a majority of healthcare resources associated with treatment for LBP .44, 45 Considering that potentia lly modifiable risk factors have been identified with increased physical therapy utilization for LBP, a standardized screening process may assist in clinical decision making processes. For example, identifying patients at high risk for developing chronic LBP may influence treatment approaches in the form of tailored physical therapy int erventions psychological counseling, or both. Realistically, such a screening process would require a dynamic approach including consistent monitoring of psychological sympt oms and response to treatment over an episode of physical therapy care as opposed to a one size fits all intervention approach based solely on intake measures Specifically, a dynamic screening process may consist of more information than is obtained d uring the initial evaluation as previous suggestions have indicated that some psychological factors (e.g., fear avoidance beliefs) may be more important as prognostic indicators for chronic LBP, while others (e.g., depressive symptoms) may be more important at earlier stages.91
95 Unanswered Q uestions and F uture R esearch The American Pain Society and American College of Physicians have recommended routine assessment of psychological risk factors for patients with LBP.171 However, a previous review study by our group172 has suggested that psychological factors are not adequately assessed during development of clinical decision tools for physical therapy interventions. Future studies that use subgrouping paradigms to match patients with appropriate physical therapy interventions have potential to benefit from incorporating a standardized dynamic psychological screening procedure consisting of both individual F ear Avoidance Model based measures and the STarT Back Screening Tool. A s previously mentioned, f uture analys e s of 6 month data may provide additional information as to the implications of initial psychologica l screening information or if continual monitoring over an episode of care is more appropriate Therefore, a potentially interesting future study may consist of integrating two separate subgrouping paradigms for the management of LBP in the physical therapy setting. For example, the Treatment Based Classification System173 may provide useful information for initial treatment approaches and subsequent decisions to incorporate supplemental behavioral interventions could be based on treatment monitoring via STarT Back Tool risk allocation, but tailored to match responses from individual Fear Avoidance Model meas ures Recently, a clinical trial comparing a stratified management care approach for LBP (based on STarT Back subgroup allocation ) to current best practice was conducted in the primary care setting.174 Results of that study indicated that after adjusting for conf ounding factors, changes in disability were significantly higher for the stratified care group compared to the current best practice group at 4months (effect size = 0.32) and
96 12months (effect size = 0.19) Moreover, stratified care was associated with a mean increase in generic health benefit and cost savings at 12 months.174 While the findings of this study have potential implications in the primary care, they require further testing before being translate d to physical therapy settings Finally, this study investigated th e influence of initial psychological measures on outcomes following 4 weeks of physical therapy F uture studies should investigate if changes in individual psychological measures are indicative of improved outcomes ; and if so which measures Previous studies have indicated that changes in pain catastrophizing,175, 176 fear avoidance beliefs,103 or depressive symptoms177 were predictive of future outcomes potentially suggesting that changes in psychological measures may provide more clinically important information than initial measures alone. Furthermore, future studies could extend the results of this study by investigating which changes in individual psychological measures are indicative of changes in STarT classification. Again, these questions may be answered when 6month outcomes for this study are analyzed in the near future.
97 CHAPTER 7 CONCLUSIONS This study investigated the validity and clinical utility of the STarT Back Screening Tool in c omparison to several Fear Avoidance Model based single construct psychological measures in outpatient physical therapy settings. Results of this study indicated that The STarT Back Tool subgrouping scheme demonstrated good construct validity at initial phy sical therapy evaluation based on concurrent clinical and psychological measures Both STarT psychosocial subscale and individual Fear Avoidance Model measures demonstrated poor predictive validity for 4week clinical outcomes however our findings suggest that STarT psychosocial subscale scores may be important for predicting pain intensity and disability raw change scores. Finally, baseline fear avoidance beliefs about physical activity were important for predicting those remaining as STarT high risk cate gorization at 4 weeks. This finding has potential clinical implications for the STarT Back Tool as a treatment monitoring measure because patients that remained high risk at 4weeks reported wor se disability from intake while patients that changed from high risk to low or medium ris k reported improved disability. Based on the results of this study, immediate future research priorities include determining if initial or continual monitoring of psychological symptoms over an episode of care is more appropriate as a prognostic indicator for poor 6 month outcomes and if changes in individual psychological measures are indicative of changes in STarT classification or clinical outcomes Further research priorities include development of appropriate psychological cl assification methods for the comprehensive management of LBP in physical therapy settings.
98 The primary purpose of this dissertation was to determine optimal screening procedures for psychological distress in patient s seeking physical therapy for LBP. Based on these data, incorporating the STarT Back and F ABQ PA as part of a dynamic psychological screening process is recommended for use in outpatient physical therapy settings based on the following reasons: 1) the STarT Back demonstrated the ability to differentiate patients based on individual psychological and clinical characteristic measures at initial evaluation and 2) the FABQ PA demonstrated the ability to detect which patients sustained STarT high risk status following 4weeks of PT. As previously mentioned, future analysis of 6 month data potentially will either support or refute these recommendations and provide further insight as to the importance of screening for psychological distress at initial evaluation compared to monitoring of treatment responses over the episode of PT care.
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114 BIOGRAPHICAL SKETCH Jason Beneciuk, PT, DPT, MPH, FAAOMPT earned his Master of Public Health (MPH) with an epidemiology concentration from the University of Florida in 2011. H e was recognized as a Fellow of the American Academy of Orthopaedic Manual Physical Therapists (AAOMPT) after completing his advanced manual therapy training at the University of St. Augustine for Health Sciences in 2006. He earned his Doctor of Physical Th erapy (DPT) degree from the University of St. Augustine for Health Sciences in 2002 and his Bachelor of Science (BS) degree in b iology from the Richard Stockton College of New Jersey in 1996. Jason is a member of various professional associations including the American Physical Therapy Association, the Florida Physical Therapy Association, the American Academy of Orthopaedic Manual Physical Therapists, and the American Pain Society.