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UNIFORMED SERVICES UNIVERSITY OF THE HEALTH SCIENCES430' JONES BRIDGE ROAD
IE'l'HESDA. MARYLAND .,41-4.,.
APPR.OVALSHEET
Title ofnesis:
Name orCaadidate:
"Predicdal Outcome in PatieDts with Work-blated Upper ExtremityDisorders: A Prospective Study oCMeclical, Physical, EIJODomic,. adPsychosocial Risk Factors"
GratD.HuqDepllblllllt orMedical ..d CliDical PsychololYMuter ofSci.ce1999
~~--Depllblllllt orMedicalad CIiDica1 'sycholalYnesis Advisor
David KraIRZ, •DepIlbDellt oCMecIical.d CliDical PlychololYCollllllittee Member
~-DepIlbDlDt ofMedical ad CliDical'sycIlolalYCoIIIIIIiaee Member
-~~q-----,-Date
The author hereby certifies that the use of any copyrighted material in the thesismanuscript entitled:
"Predieling Outeo_. in Ptltiellb with Worlc·R.ltIted Upper EztrelftityDiso"",: A 1'rD,peetiN Struly 01Mediclll, P"y,iclll, Erro"e_ie, IlIUIP',,:"o,.'" Ru/c FlICtDn"
beyond briefexcerpts is with the permission of the copyright owner, and will save andhold hannless the Uniformed Services University of the Health Sciences from anydamage which may arise from such copyright violations.
1::!!~Department ofMedical and Clinical PsychologyUniformed Services University of the Health
Sciences
ii
ABSTRACT
Title ofThesis: Predicting Outcome in Patients with Work-Related Upper
Extremity Disorders: A Prospective Study ofMedical, Physical,
Ergonomic, and Psychosocial Risk Factors
Grant D. Huang, Master of Science, 1999
Thesis directed by: Michael Feuerstein, PhD.
Professor
Departments ofMedical &. Clinical Psychology and
Preventive Medft:ine &. Biometrics
Althoup predictors of work-related upper extremity disoiders (WRVEDs) have been
identified, little is known about what predicts clinical outcomes in patients who already
have this problem. The present jnvestiption prospectively examined worken with
WRUEDs CD. =70) over a 3 month period. A baseline questionnaire was used to assess
demographic characteristics, occupational status, medical history, symptoms, physical
function, ergonomic risk exposure, work demands, occupational psychosocial factors
(e.g., job stress), social support (e..g., job support), and individual psychosocial facton
(e.g., general distress, reactivity to pain). Lapstic regression analyses were then
conducted to predict composite outcome status. The composite outcome measure
included symptom severity, functional status, mental health, and lost days from work. At
both 1 and 3 months, cqonomic risk exposure (1 month RR =1.06, 95., CI = 1.01
1.11; 3 month RR =1.08, 95IfJ CI=1.01-1.1S),job support (1 month RR =1.03, CI=1.00 -1.07; 3 month RR = 1.04, CI= 1.01-1.08), andcatastrophizing(1 month RR=
I.S8, CI= 1.12 - 2.23; 3 month RR =1.81, CI= 1.24 - 2.66) predicted poorer outcome.
iii
Number of past upper extremity diagnoses (RR = 1.71, CI = 1.14 .. 2.57), baseline SF-36
Mental Health score eRR =1.24, CI =1.01-1.54), and pain severity (RR. =1.50, CI =1.08 .. 2.07) also predicted outcome status at 1 month, while baseline symptom severity
(RR =6.21, CI =1.28 .. 30.09), past recommendation for surgery (RR =5.53, CI =1.18 ..
25.86), number of prior treatments (RR =2.24, CI =1.26 - 3.96), and job stress (RR =1.21, CI = 1.02 -1.43) were additional significant predicton at 3 months. These findings
indicate the need to address medical, physical, ergonomic, and psychosocial facton in
efforts to improve outcomes. Furthennore, it is suggested that an organizational
environment that encourages a coordinated effort from employees and management
should also help improve recovery from these complex disorders.
iv
PredletlDl Outcome In Patients with
Work-Related Upper Extrellllty Dilorden: A Prospeetlve Study of
Medical, Physical, Eqonoadc, and Psycbolodal RIsk 'acton
by
Grant D. Huang
Thesis submitted to the Faculty of the Department ofMedicallDd Clinical PsychololY
Graduate Prosram of the Uniformed Services Univenity of the Health Sciences
in partial fulfillment of the requirements for the depe of
MasterofScience 1999
y
ACKNOWLEDGEMENTS
I would like to express my sincerest gratitude to certain individuals for their
valuable contributions and significant influences on this thesis.
Fust. I would like to thank my mentor, Dr. Michael Feuerstein, for his guidance
and direction. While this thesis is just one of several milestones that are to hopefully
CODle, its completion is an indication of his continual shaping and development of my
academic pursuits. Additionally, I would like to thank Drs. Jerome Singer, David Krantz,
and Tracy Sbrocco. Their input and suggestions for improving this study and manuscript
have greatly added to the learning experience.
A uemendous amount of usistance and support on this project were provided by
Francesca Belouad, Caroline Ennen, Amy Haufler, Julie Miner, and Julie StOleY. Their
help in conducting this investilation certainly made the process mote mana_Ie.
Robert Bettendorfand the Office Eqonomics Research Committee also deserve
particular recopition for funding this research.
I am especially appreciative of my family as wen as Patrick Cben, Faydeana Lau,
David Tsai. Jenny Wanl, and ADdIu Yeh. Their prayers and encoura~ment served as
strong motivations for putting forth a steady and quality effort. Furthermore, a more
meaningful perspective on this work was provided through their cballenamg and thought
provokinl discussions.
Finally, I thank God who is my sttenatb and the reason for my desiIe to learn and
expand my mind. throup endeavon such as this one.
vi
TABLE OF CONTENTS
Approval Sheet i
Copyrllbt StateDleDt li
Abstraet- ••••••••.•••• •••.•••••••.•• •• iii
Tide ..........•.....................•.................................................................................... v
Acknowled. ts ..................•. vi
Table of Contents ...•.......... ...•... •........ vii
LIlt ofTables ....•.. ......•••. .. xi
IDtrocIuctlOD •...••..•••••••.•....•....•.•.• .•.........••.•.•••. ••••... 1
Work-Related UP'POf Extremity Disorders 1
WRUEDs and Their Relation to Physical and Psychological Health ..... 2
Additional Impact ofWR'UEDs 3
Towards a Multidimensional Approach to Undentandinl WRUEDs .... 4
Physiological / Medical FlII:IOrs 5
Ergonomic Risk Factors 6
Occupational Psychosocial FtJCtors ~............ 7
IndividlltJl PsychosocilJl Factors 8
Study Rationale .•.•..•.••.....•.••••••••••.••..••.•••••••••••...•••••.•...••...•.•••.•••••.••.•.•...•• 9
MetllCIIII .••••••.•.••••.•••••••••••••••••••••••••••••••••••••.••••••••••••••••...•••••••.•••••••••••••••••••••••••.•••• 11
Study Panicipants 11
Baseline Procedure. 12
Follow-Up PJ1:)cedure •••••••••••••••••••••••••••••••••••••••••••••••••••••••••••••••••••••••••••••• 13
Baseline Questionnaire •••..••••.••••••.•••••.•.•• 13
vii
Demographic Characteristics 13
Occupational SttltllS 14
Medical History I Status 14
Symptoms ....•••.......•......•.••••....•••.••.•....•.•.••••.•.•.•.•.....•.•••.•...•.•••••.•.. 14
Physical Function .•...•....••.••••..•...•....•.•••..••••.••...••.••.•.................•.. IS
Ergonomic I BiomeclltJniclll ...••.••••••.... 15
OccupatiO'lllll Psycho,ocilll 16
Work Demands ..•••.••••....••..•••..••••• .••.•• 17
SocioJ Suppon ••••.•••..••••.•.•.••• •••• 17
IlIdividMal P.,eltoaocitll •••••••••••••••••••••.••••••••••••••••.••••.•••••••••••••..••• 18
Meas,ures ofOutcome ••.•••••.•.•...••..••.•.•••.••••.•.•.••.•••••.••.••..•..•.•.•..••...•...•.... 18
Selection. ofPotential Predicton •....•...••.. ....•..•......•....•... .•.•.. 19
Calculation ofComposite Outcome Index 20
Analyses ...•.......•.•.••••..•• 21
a.aItI 22
Demopapbic Cbarac:teristics 22
Test-Retest .•.•••••••..•.•••••..•....•..•...••.••••••••.........•.........••..•••.••.••.•••••......••.•.. 23
Predictors ofComposite Outcome Status at 1Month 23
Derno,raphit: CltartlCteMics 24
~~CJ~~t~ ••••••••••••••••••••••••••••••••••••••••••••••••••• :Z~
Mediclll History I StillllS 2~
S'ympItJmS 24
Physiclll FlIIICtioll :Z~
viii
Ergonomic I BiomechDnictll ••••. 25
OcCllptltiOnal Psychosocial 2S
Work Demands 25
Social Suppo'" ..••••.•••••••.•••••. •.•••..•••••••..••.••••.• .••• 2S
Individlllli Psychosocial 2S
Predictors ofComposite Outcome Status at 3 Months 26
Demogrtlphic ChtJrtJCteristics •••• 26
()~~~.,nal St~s •...•.•••.•••.•.••.•....•.••...•.••.•...•.••••••.•• 2"
Medict:Jl History I StlJlUs .•.••.•.•:..................................................... 27
Symptoms n
Plrysict:Jl Function 2"
Ergonomic I B;o~cllaniClJl 2"
()cCllptllional PsychosociJ:ll ••••.••••••.•.••••••.••••..••.••••••••••••.•..•••..••...• 28
Wor1c Demands •••••••••••••••••••••••...•••••••••...•••••••••••••.•••••.•••••••••••.•••••• 28
SociJ:Il Sllppon 28
Intlividlllll Psychosocitll 28
Predictors of Individual Outcomes at 1 Month 29
Predieton of Individual Outcomes at 3 Months 29
DilellaIOR .•..••••••.•••••••••.•••••..••.•.••••••••.••..•..••••••.••••••••••••••••••••••••••.•••••••••.•...•..•.•...• 30
Risk FlCton for' Poorer Outcome 30
Medict:Jl History I SttItUS 30
S."",tOIfl Severity ""................................................... 31
Erg.ollDmic RiskFllClor E:xpoSllrtIJ 31
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Occupational Psychosocial Factors 31
ww Job Support .•.••..•.••••..• 32
IndividlUll Psychosocial Factors 33
Potential Mechanisms ....••........••....•..•.............. 33
Implications and Suggestions for Intervention 36
Study limitations 39
Conclusion 42
Tabt. 43
Appe~ ~........................................................... 58
Relenac. .....•...•......•..........................•...... .. 99:
x
LIST OF TABLES
Table 1: Correlations Among Medical Status Measures
Table 2: Correlations Among Symptom Measures
Table 3: Correlations Among Physical Function Measures
Table 4: Correlations Among Occupational Psychosocial Measures
Table S: Correlations Among Work Demand Measures
Table 6: Correlations Among Individual Psychosocial Measures
Table 7: Standardized Factor Loadings for Composite Outcome Index
Table 8: Demographic Characteristics
Table 9: Diaposes
Table 10: Treatments Used Prior to Baseline, 1 & 3 Month Follow-Ups
Table 11: Test-Retest Reliability of Independent Variables
Table 12: Predictors of Composite Outcome Status: 1 Month
Table 13: Predictors of Composite Outcome Status: 3 Months
Table 14: Predictors of Individual Outcomes: 1& 3 Months
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INTRODUcnON
Work-related upperextremity disorders (WRUEDs) impact workers md wort
organizations because of the diverse set of medical, psychological, legal, socialmd
financial challenges that they cm present. This impact is funher magnified considering
that a wide array of individuals can be affected anellor involved with the case. In addition
to the worker md manapment, pbysicims, occupational/physical therapists,
ergonomists, psychologists, as well as co-workers and family members may also be
affected by the sequelae of a given WRUED case. Over the past few decades, empirical
investiptions have found that medical, physical, erlonomie, md psychosocial factors are
correlated with anellor predictive ofthese disorders (e.g., Armsttonl et al., 1993; Bongers
et al., 1993; Hales & Bernard, 1996). However, it is less clear how these factors
contribute to clinical outcomes once a worker has developed a disorder.
Work-Related Upper ExtremIty DIIonien
The International Labor Organization Advisory Committee on Salaried md
Professional Workers noted that "repetition strain injuries" were an ~palional problem
related to mechanized work during the 1960s (Chatterjee, 1987). In the 1980s, marked
increases in the incidence ancIIor prevalence of these problems were reponed in AUI1rIlia
(Hocking, 1987), Canada (Ashbury, 1995), and the United States (BaDrahan et al., 1991).
As these "repetition strain injuries" received pealer attention, other names were used
synonymously in the literature, including: cumulative trauma disorders. repetitive trauma
disorders, and overuse syndromes (GeJ:ret a1., 1991). However, these descriptions imply
a causal mechanism (i.e., repetition. ovause) that bas not yet been definitively
1
2
established. One tenn that does not suggest an etiology and, therefore, is more
appropriate is "work-related upper extremity disorders."
More precisely, WRUEDs stem from symptoms and functional limitation
associated with muscles, tendons, andlornerves in the finger, hand, wrist, elbow, arm,
shoulder, and neck regions (Feuerstein, Huang," Pransky, 1999; Rempel et aI., 1992;
Putz-Anderson, 1988). Cases typically present symptoms of pain, tingling, numbness,
swelling, andlor tendemess (Szabo &. Madison, 1995; Amadio, 1995; Downs, 1997).
Additionally, while definitions for what constitutes a WRUED may vary, some of the
more common diagnoses include: carpal tunnel syndrome, tendinitis, tenosynovitis (e.g.,
deQuervain's disease), lateral epicondylitis, and nerve entrapment syndromes (Rempel et
al., 1992; Gerr et aI., 1991).
WRUEDs and TIIeIr a.UoD to Phyllcal and PsycbolOlla1 Health
It has been noted that individuals with work-related upper extremity disorders
continue to work with pain (Feuerstein et al., 1998). However, should symptoms
associated with such disorders persist, functional limitations andlor work disability may
result (Feuerstein, Huang, "Pransky, 1999). In other words, a worker may experience
pain and/or other symptoms to an extent that helshe can no longer tolerate them and
hislher ability to work becomes impaired. Should this impaired ability to work continue,
the worker may eventually become disablecL
In addition to physical health considerations, the psychololical health of WRUED
patients also deserves attention. Anxiety disorders were found to be the most prevalent
DSM-IDR (American Psychiatric Association, 1987) diagnosis in a sample ofcarpal
3
tunnel syndrome patients who sought treatment from an orthopedic hand surgeon (Mathis
et aI., 1994). In a study of sign language interpreters, a fear ofdeveloping pain was
assOciated with the presence of an upper extremity disorder and also had an impact on
function, pain and Perceived muscle tension while at work (Feuerstein et al., 1997).
While causality cannot be established from the designs of these studies, the findings
hilhlight the importance of addressing both physical and psychological health aspects in
patients with WRUEDs.
Addltlonallmpaet of WRUEDs
In addition to the physical and psychological impact on the worker, WRUEDs can
also have significant organizational, financial, social, and legal impacts. Recent data
reponed by the Bureau ofLabor Statistics (1999) indicated that over419,000 upper
extremity injuries/illnesses involved days away from work in 1997. According to the
same data, carpal tunnel syndrome and tendinitis accounted for about 47,000 of these
cases. Repons have also indicated that mean costs for upper extremity disorder cases can
range between $8,000 to $10,000 (Webster & Snook, 1994; Brogmus ~Marco, 1992).
In 1989, it was estimated that all compensable upper extremity disorders in the United
States cost approximately $563 million (Webster& Snook, 1994). From a legal
PerSpective, impairments of the upper extremities (i.e., arm, shoulder, hand, cumulative
ttauma disorders, carpal tunnel sYndrome) were found to be the foUl1h most prevalent
source of litigation associated with the Americans with Disabilities Act overa six-year
Period (Huang & Feuerstein, 1998).These data suuest that WRUEDs consume a Iarp
amount of resources at several levels. TherefOle, it would seem thatprimary and
4
secondary prevention efforts thJlt address WRUEDs could provide substantial benefits to
the worker, work organization, and society.
Towards. MulUdlmeDlioaal Approach to UDderstaDdlnl WRUEDs
Presently, a combination of medical, physical, ergonomic, and psychosocial
factors is theorized to contribute to the development, exacerbation, and maintenance of
work-related upper extremity disorders. Although the exact mechanisms by which these
factors interact remain unclear, several models have been proposed to explain this
multidimensional nature and to provide a conceptual framework for understanding
WRUEDs. Armstrong and colleagues (1993) have sugested a dose-response model that
focuses on mechanical and physiolopcal facton and also notes the role of psychological
factors.. According to this model. internal doses (e..g., tissue loads and metabolic
demands) stem from external exposure to work requirements. These internal doses
subsequently lead to internal "disturbances" (i.e•• mechanical, physiological. or
psycholopcal) "that in tum, produce responses sucb as changes in tiaue sbape, ion
concentrations, and substrate levels.. After repeated. or sustained doses and responses, an
individual's capacity to adapt to the intemal changes may be enhanced or reduced. It is
believed that when this capacity is mduced.. muscle, tendon. ornerve-related disorders
result.
In a model of work disability associlled with occupational musculoskeletal
disorders in general, Feuerstein (1991) has sullestee:l that such disability results from a
complex interaction amana medical status, physical capabilities, work demands, and
psycbolopca1lbebavioral resources.. More specifically, this model sugests that medical
s
status variables associated with the musculoskeletal, neurologic, and cardiovascular
systems influence a person's physical ability to work. These physical capabilities, in
conjunction with work demands (i.e., biomechanical, aerobic, and psychological),
determine a worker's ability to execute a given job task. However, discrepancies
between the physical capabilities and work demands reduce the likelihood of returning to
work from a work-related musculoskeletal disorder. Additionally, the model also
suggests that the amount psychologicallbehavioral resources available to the worker can
also moderate the discrepancy between physical capabilities and work demands. Taken
together, this model proposes that medical, biomechanical, physical, and psychological
facton all contribute to the worker's ability to retum to work after a musculoskeletal
injury or illness.
Physiological I Medical Factors
Physiologically, inadequate blood supply, nou-optimal hydrogen ion
concentrations, and decreased supply ofadenosine triphosphate and calcium ions are
important facton that contribute to muscle fatigue (Rodgen, 1997). A~tional1y, if a
worker is not given an adequate recovery time, symptoms such as aching, swelling,
bumin" and pain may arise from sustained and/or repetitive efforts. One study of
workers who performed a staDdardized machine-paced task found that hiper levels of
static trapezius muscle activity (meuured byelecuomyograpbic (SMG) recordinp) were
sipificandy conelated with complaints of soreness, filip, or pain in the neck and
shoulder regions (Veiersted, Westpard, &. AndeIsen, 1990).
6
Compression of the median nerve at the wrist can also result in symptoms related
to carpal tunnel syndrome (erS) (Dawson, 1993). In cases ofers, the pressure inside
the carpal tunnel can increase from 3 mm Hg to 30 mm Hg (Rempel, Harrison, "
Bamhart, 1992). Clinical assessment methods for ers include Phalen's test, Tinel's
sign, and detennining nerve conduction velocity from the wrist to the thenar muscles
(D~wsoo, 1993). It should be noted, however, that there is not a ugold standard" in
diagnosing these problems (e.g., Baron, Hales, "Hunell, 1996). In an investigation of
asymptomatic workers, median sensory nerve conduction studies were not found to
predict future erS-like symptoms (i.e., pain, numbness, tingling, or buming) in the hands
or fingers (Wemer et al., 1997). Self-repon measures of symptoms such as the Symptom
Severity Scale (Levine et al., 1993) have also been developed to assess pain, weakness,
numbness, and tingling. Studies on this scale have found it to be significantly correlated
with physical measures (e.g., grip strength, pinch strength, and 2-point discrimination) of
ers (Levine et aI., 1993).
E,.,onomic Risk FQ£tors
Eraonomic risk facton such as forceful exertions, repetitive or prolonled
activities, awkward postures, contact stresses, vibration, and temperature extremes have
all been associated with work-related upperextremity symptoms and disorders (e.g.,
Williams" Westmorland, 1993; Gettet aI., 1991). Methods for usessiDg exposure to
qonomic risk facton include direct observation, the use ofchecklists, and self-report
(1'"., Punnett, 1998; Stetson et aI., 1991). A studythat assessed eraonomic exposure by
means of a questionnaire as well as observationf~ an increasinl prevalence of upper
7
extremity disorders was associated with greater exposure to ergonomic risk factors
including non-neutral postures, vibration, manual forces in handling tools and parts, and
mecbanical pressures in tool use (Punnett, 1998). Another study that utilized the 1988
National Health Interview Survey found that self-reported repetitive bendingltwisting of
the bands/wrists as well as use of vibrating hand tools placed a worker at a greater risk
for carpal tunnel SYndrome (Tanaka et a1., 1995). In a review of upper extremity
disorders associated with video display unit work (Punnett &. Bergqvist, 1997), factors
such as high keyboard position, lack of ann support, chair discomfort, non-optimal desk
height, and non-optimal screen height have also been found to place a worker at greater
risk for neclrlshoulder, armIelbow, and band/wrist disorders.
OccupGtional Psychosocial Factors
Seven! models ofoccupational stress have incorporated organizational and
individual characteristics in a.ddIessing occupational health in general as well as work
related musculoskeletal disorders (e.g., Cooper, 1986; Smith &. Carayon, 1996). In these
models, occupational stress has been proposed to stem from factors suc~ as job/task
design, organizational role, career development, interpersonal relationships at work (i.e.,
with colleagues, sUpervisors), work demands, and organizational climate.
Empirical investigations on occupational psychosocial risk facton have also
found several variables to be associated with and/or predictive ofWRUEDs. A review of
these studies by Bonlen and colleagues (1993) found that time pressure, monotonous
work, hip Pereeived work load. poor work content, hip perceived work stress, and low
job satisfaction were positively associated with neck or shoulder pain. Furthermore,
8
previous studies have found that lower levels ofjob support were associated with greater
self-reported Dumbness in the hand and ann regions (Faucett eft Rempel, 1994) and a
greater risk for self-reported ofshoulder and neck pain (Linton eft Kamwendo, 1989).
Additionally, lower job support levels in both blue- and white-coUar workers have
predicted a change in the occurrence of upper extremity symptoms and disorders over a
lo-year period (Leino" Hanninen, 1995).
lrulividutll Psychosocial Factors
Emotional distress, PerCeptions, and interpretation of pain have been noted as
some of the major components of an individual's pain eXperience (Craig, 1994;
Weisenberg, 1994). Furthermore, it has been noted that stress can lead to increases in
pain by trigering peater autonomic, visceral, and skeletal activity (Craig, 1994). In a
study of musicians, a pain stressor task produced SMG elevations in the flexor and
trapezius muscles in the musicians who had a history of upper limb pain (Moulton eft
Spence, 1992).
Patients with a history of upper extremity pain have been found to report higher
levels of anxiety and distress prior to the provision of relaxation training and/orSMG
biofeedback treatments (Spence et aI., 1995). "Catutrophizinl" bas been described as
"neptive self-statements and overly nepUve lhouJbts and idea about the future" and
bas also been implicatecl as a mediator ofpain and function (Weisenberg, 1994). A study
of low back pain patients that utilized the Catastrophizin. subscale of the Coping
Strategy Questionnaire found that a catastrophizing coping style was related to how a
person adjusted to chronic pain (RosenstieI "Keefe, 1983).. Catastrophizing has also
9
been found to distinguish between workers with an upper extremity disorder who were
disabled and those who continued working (Himmelstein et al., 1995).
Study RatIonale
While it is important to continue efforts that are directed at elucidating the
etiology of these disorders, few studies have examined predictors of outcomes. Older
age, non-white ethnicity, repetitive hand or wrist bending, and industry of lut
employment have been indicated as risk factors for work cessation in persons with carpal
tunnel syndrome (Blanc et aI., 1996). A recent study of U.S. Army soldiers found that
age, race (i.e., Caucuian), lower orpDizationai status, and self-reported occupational
stress wu predictive of work c6sability associated with an upperextremity disorder
(Huang et al., 1998). Cole and Hudak (1996) reviewed prognoses related to nonspecific
work-related upper extremity e6sorders and found that a longer duration of symptoms
before medical consultation was soupt and increased workplace demands were
potentially important propostic factors. However, they argue that methodological
limitations and the lack ofempirical evidence sugest a need for more resean:h on the. .
proposis of these e6sorders. Another review of treatment outcomes in carpal tunnel
syndrome patients (Feuerstein et al., 1999) found that compared to open release suqery,
endoscopic release was related to increasedphysical function and fewer days to retum to
work. The same review also indicated that pain n:cluction was associated with steroid
injections. use of vitamin 86, ranle ofmotion exadses, and copitive behavior therapy.
btum to work was also associated with I1I1lpofmotion exercises and multicUsciplinary
rehabililation. Yet, despite tbese fincUnp, the authon also note that there are few well-
10
controlled investigations of such outcomes. Considering this scarcity ofoutcomes
related research. even less is known about determinants ofclinical outcomes in workers
once diagnosed with a WRUED.
The present investigation prospectively examined a sample ofpatients with a
recendy diagnosed WRUED. It was hypothesized that a combination of medical.
physical. ergonomic, occupational psychosocial. and individual psychosocial factors
would predict a composite outcome comprised of symptom severity, functional status,
mental health, and lost days. The purpose of this investigation was to delineate specific
predictors in order to enable a more focused approach for future intervention and
prevention efforts. Such strategies may subsequendy help to improve health outcomes in
affected workers, resulting in increased productivity, efficiency, and job satisfaction, as
weD as improvements in one's overall quality of fife.
METHODS
Study Partldpants
Studypanicipants were recruited from the metropolitan Washington, D.C. region
(including Maryland and Northern Virginia) through advertisements placed in regional
newspapers, health newsletters, clinics, and hospitals. Persons interested in participating
underwent a telephone interview to determine eligibility for the study (see Appendix A).
Eligibility was based on the foUowing criteria:
1) meeting a modified National Institute ofOccupational Safety &. Health (NIOSH) case
definition for an occupational upper extremity disorder; this definition includes:
a) symptoms of pain, achinS, stiffness, burning, tingling, and/or numbness in
the finger, band, wrist, elbowt arm, shoulder, or neck regions
b) symptoms beginninl after employment at the present job
c) symptoms having lasted for more than one week, or at least once per month
since their onset
d) no priornon-occupational accident or acute trauma to the symptom area
within the put year
e) no priordiasnOlis to the specified symptom area
f) baving teeeived a diaposis from a health care provider within the past six
weeks
2) between 20 and 6S years of age
3) presendy working at least 20 hours per week
Based on these criteria, 87 individuals were determined eligible for participation.
11
12
Bueline Procedure
After participants consented to participate and provided documentation of their
diagnosis from their health care provider. a physical examination was given to obtain
measures ofheight, weight. pinch grip strength, and hand grip strength. Both the Pinch
grip strength and hand grip strength measurement procedures were conducted in
accordance with the recommendations of the American Society ofHand Therapists
(Casanova, 1992) as well as the manufacturers of the Iamar dynamometer. Following
this examination, participants were given a 347...item baseline questionnaire.
Approximately 1hour was required to complete the questionnaire and participants were
allowed to take breaks as needed. Additionally, the investigator conducted checks at IS...
20 minute intervals to provide clarification on questionnaire items, ifnecessary..
After completinl the questionnaire, participants were given a packet that included
three copies of a foUow-up questionnaile to be completed at 1, 2, and 3 months post
baseline survey. A note indicatinl the three foDow-up dates was also provided in the
packet. Monetary compensation ($40) was provided to the participants upon the receipt
of the third follow-up questiODlUlire.
At the conclusion of the initial visit, participants were offemcl the opportunity to
participate in a test-letest investigation. This teIt-Ntest investigation was conducted to
determine the reliability ofthe measures used in the present study. It involved returning
to the university within 2 weeks of the baseline viait, completing the 347-item
questionnaire apin. and receiving monetary compensation upon completion. 24
participants (27.6'5 of the total sample) volunteeleCl for the test-retest investiBalian.
13
All data obtained on the baseline and test-retest questionnaires were double-
scored and double.entered into the database by two research assistants.
FoUow-Up Proeedure
In addition to being provided with a reminder, participants were called 3 to Sdays
prior to the follow-up date. Despite the follow-up efforts, 17 (19.5%) subjects were lost
to fonow-up. Reasons for this attrition included: decision to terminate participation after
the initial visit because of a lack of personal time, loss of interest in the investigation, and
failure to return the follow-up questionnaire on time. Of the 17 subjects lost to fonow-
up, one subject participated in the test-retest evaluation. All follow-up data were double-
scored and double.entered into the database by two research assistants.
..line Questlollllllire
The baseline questionnaile was multidimensional in nature and assessed factors
hypothesized to contribute to outcomes associated with upper extremity disorders. These
factors were categorized as: demopaphic characteristics. occupational,status, medical
history/status. symptoms, physical function, ergonomielbiomechanical, occupational
psychosocial, work demands, social support, and individual psychosocial. The entile
questionnaire is provided in Appendix B.
Demo,rtlp#aic Characteristics
Demopaphic information obtained included aF, gender. education level, marital.status, and etbnicity.
14
Occupational Status
Questions on occupational status included the fonowing: type ofjob, duration at
present job, part/full time status, days lost within the put month, and limited duty days.
Medical History / StatllS
Items relating to medical history and status were primarily concemed with the
upPer extremity disorder and included the following: prior workers' compensation
injury, number ofput diagnosed upper extremity disorders, time between onset of
present upper extremity symptoms and seeking medical help, number and types of
therapies obtained. whether or not surgery had been recommended for any upper
extremity disorder.
Additionally, questions regarding medical problems (i.e., diabetes, gout, thyroid
problems, kidney failure, alcoholism, lupus, ruptured disc) and various health behaviors
(i.e., tobacco, alcohol, prescription medication usage) were included in this section.
Symptoms
Self-repon of symptoms was obtained using three different measures. The first
measure was the Symptom Severity Scale (SSS) (Levine et al., 1993) which is an II-item
measure that assesses pain, numbness, tinlling, and weakness. It should be noted that
while the questions specifically address symptoms in the hand and wrist repons, subjects
in the present study were instructed to IDSwerquestions as they mlated to the area of their
upPerextremity disorder. The SF-36 Bodily Pain Subscale (Ware" Sherbourne, 1992)
was also included to assess overall pain. This subscale consists of two questions mlating
IS
to the frequency ofany bodily pain over the past 4 weeks.. The third measure of
symptoms was a single question using a IO-Cm.. visual analog scale of pain severity
during the past week.
Physical FlUlction
Four different measures were used to determine physical function. These
measures were the Functional Status Scale (FSS) (Levine et aI., 1993), the Physical
Function and Role-Physical Subscales of the SF-36 (Ware & Sherboume, 1992), aDd the
Upper Extremity Function Scale (UEFS) (Pransky et al., 1997).
The PSS is an 8-item scale that measures a person's difficulty in conducting
various daily hand-related tasks (e.g., writing, buttoning clothes, chores). The SF-36
Physical Function and Role-Physical subscales are comprised of 14 items (total) that
assess general function/activity levels on daily life activities (e.g., bathing, moving). The
UEFS is an 8-item questionnlire that assesses how problematic certain daily tasks (e.g.,
sleeping, writing, picking up small objects, washing dishes) are for a person as a result of
hislher symptoms.
Ergonomic / BiomeclumictU
Self-reportofexposum to suspected ergonomicJbiomechanical rilk factors were
obtained through two sets ofquestions. The tint set ofquestions contained 10 items and
was based on potential risk factors listed by Stetson and colleapes (1991) 81 well as
those identified in the literature (e.g., Armstmng et al., 1993; Halberg et 11.., 1995)..
These risk facton included frequency of: tepetition, forceful movements. ulnar/radial
· 16
deviation, and rest breaks. Questions on specific work-related tasks such as frequency of
using the computer keyboard, mouse, telephone as well as frequency of writing and other
hand motions were also included. All responses were obtained by using a 1O-cm.. visual
analog scale.
The second set ofquestions was obtained from a questionnaire developed by
Pransky and Hill-Fotouhi (1996). This questionnaiJ:e contains 10 items assessing
frequency of performing work-related tasks that may place a worker at risk for injury or
increased pain. Included in this measure are items regarding forceful movements,
awkward postures, repetition, temperature extremes, and duration ofsitting/standing.
OccllptlliolUll Psychosocial
Occupational psychosocial stressors that were examined were general job
stressors. Items addressing general job stress were obtained from the Life Stressors and
Social Resources Inventory (USRES) (Moos" Moos, 1994) as well as the NIaSH
Checklist of Work-Related Psychosocial Conditions (Tepper" Hurrell, 1995).. The job
stress measure of the USRES contains six items on work-related conflicts, physical
environment, and pezeeptions ofwork pace.. The NIaSH checklist is a26-item measure
that examines a worker's perceptions on the physical work environment, work demands,
work characteristics, and perceived work expectations. A 6-item measure ofcognitive
workstyle (Feuerstein, Huang, "Pransky, 1999) developed for this study was also
included (Appendix Bt Items 335-341). This measure was used to assess an individual's
copilive responses to work. Test-retest te6ability analysis of this measure indicated a
comlalion coefficient of0.85 CIt < 0..01).. An intemal consistency analysis resulted in a
Cronbach's alpha of0..87.
17
Work Demands
Measures of work. demands were based on questions developed by Caplan (1971)
which had also been used in prior NIOSH investigations (e.g., Hales et al., 1994).
Specifically, these questions measure workload, workload variance, and physical and
mental exhaustion. Borg's (1998) CRI0 Scale which measures PerCeived exertion during
a "typical day" was also included to assess perceived levels of work demands.
Social Support
Ttuee separate scales were used to measure social support. The first measure
included an II-item measure of social support at work (i.e., from co-workers and
suPerVisor) that was based on questions developed by Caplan (1971). Prior NIOSH
studies (e.g., Hales et aI., 1994) have also used these questions to assess job support.
However, it should be noted that for the purposes of this investigation, responses to these
items were modified into a visual analog format.
The second measure of social support at work was obtained from the lob
Resources SubscaIe of the USRES (Moos & Moos, 1994). This subscale contains six
items that usess the fiequency ofjob support as wen as Perceptions ofjob characteristics
(e.g., responsibility, challenge pro"ided).
The third measure used five items obtained from the Organizational Self
Assessment (OSA) (Habeck et aI., 1991) to assess the availability and/oroffering of
workplace accommodations. While the OSA contains 30 questions that relate to
organizational climate as well as various manapment practices, only five items were
18
selected for the present study because of their relevance to general health and work
related upper exttemity disorders. Specifically, these items asked about frequencies
concerning: the provision of health-related resources and safety training, sUPervisory
monitoring and encouragement in assisting with return to work, modifications made to
help workers with pain and symptoms, and participation in decision-making and
problem-solving in company operations. An internal consistency analyses of these five
items resulted in a Cronbach's alpha of 0.71.
llldividJull Psychosocial
Items assessing an individual's psychological health and emotional reactivity to
stress and pain were obtained from four sources. The first was the 5-item Mental Health
Subscale of the SF-36 (Wile" Sherbourne, 1992). The second was the State-Trait
Anxiety Inventory (STAI), Form X-2 (Spielberger, Gonuch, "Lushene, 1970), which is
a 2O-item measure of general anxiety. The third measure was the 6-item Catutrophizing
Subscale from the Coping Strategies Questionnaire (Rosenstiel " Keefe, 1983). The
fourth measure wu the Discomfort Intolerance Survey (DIS) (Schmidt, 1995). The DIS
is a 6-item visual analog scale that measures one's ability to tolerate pain/discomfort and
hislher reactivity to such pain/discomfort.
M.....fOutco..
A follow-up questionnaire consisting of 100 self-report items was desillted to
obtain measures on the following outcomes: days lost from work within the past month,
symptom seventy, physical function. and mental health. Additionally, in order to
19
determine the influence of baseline levels of these variables, items used in the fonow-up
questionnaire were identical to those administered at baseline. Specifically, the scales
used for follow-up were: the Symptom Severity Scale (Levine et al., 1993); the
Functional Status Scale (Levine et al., 1993); the Physical Function, Vitality, Role-
Physical, and Social Function Subscales of the SF-36 (Ware & Sherbourne, 1992); CRI0
Scale ofperceived exertion (Borg, 1998); the Mental Health Subscale of the SF-36 (Ware
& Sherbourne, 1992); and, the STAI (Spielberger et aI., 1970). The entire follow-up
questionnaire is provided in Appendix C.
SeledioD ofPoteDtIIIl PndIeton
Several measures within each of the categories (i.e., demographic characteristics,.
medical history/status, symptoms, function, Cfgonomic/biomechanical, occupational
psychosocial, work demands, social support, and individual psychosocial) hypothesized
to contribute to upper extremity-related outcomes were obtained. Therefore, in an effort
to reduce the number of potential predictors that were to be examined as wen as any
redundancies, correlation coefficients among variables within each of these categories
were tint obtained. In the ergonomiclbiomechanical risk factor categoryt a correlation
coefficient of0.26 <It < O.OS) was found for the Pransky-Putouhi (1996) Scale and the
ergonomic stressors scale based on Stetson et al. (1991). Since more than two variables
were included in the othercategories, the conelation matrices for these catelories are
provided. in Tables 1 to 6.
Selection of potential predictors wu partially based on an examination ofthe
conelation coefficients. Measules determined to be representative of the construct in
20
question were chosen based on having a minimum correlation coefficient of0.25 <2 <
O.OS) with other variables assumed to measure the same construct within the category.
When two or more variables were significantly correlated, simplicity of the items (e.g.,
wording, number of items) and hypothesized relevance to upper extremity disorders
(versus general or back-related problems) were factored into the final selection process.
The variables chosen for further analyses were: Demographic Characteristics ..
age, gender; Occupational Status .. work days lost in the past month at baseline; Medical
HistorylStatus .. prior workers' compensation injury, number of past upper extremity
diagnoses, dominant hand grip strength, recommendation of surgery for an upper
extremity disorder, treatment history; Symptoms - SSS at baseline, pain severity; Physical
FUllCtion - PSS at baseline; Occupational Psychosocial .. Moos " Moos (1994) lob Stress
Subscale and the cognitive workstyle scale; Work Demands - Borg's (1998) CRI0 Scale
ofperceived exenion; Sociol Support - Caplan's (1971) job support (i.e., co-workers and
supervi~r) scale and work accommodation (Habeck et al., 1991); Individual
Psychosocial- SF-36 Mental Health Subscale (Ware "Sherbourne, 1992) and
eatastrophizing (RosenS1iel "Keefe, 1983).
Calculation of eo.......OutcoJDeInda
For both the I-month and 3-month foUow-up periods, factor analyses were
conducted on the standardized scores of four outcome measures: days lost fmm work, the
SSS, the PSS, and the Mental Health Subscale of the SF-36 (e.I., Grice" Harris, 1998;
Oonuch, 1983). These measures were chosen because they lepleSeDt outcomes of
interest in several WRUED studies (e.I., Blanc et aI., 1996; Franzblau et aI., 1997; Stock
et al., 1996; Spence, 1991). From the analyses, factor loadings on the four outcomes
21
were used to generate a composite outcome score. Since there were two follow-up
periods of interest (1 and 3 months), a composite score for each follow-up period was
calculated. Table 7 shows the loading factors obtained from the factor analyses for
months 1 and 3. Based on a median split, the composite scores were categorized as
"high" or "low." Scores above the median indicated poorer outcome. That is, high
scorers had more days lost, higher levels of symptoms, poorer function, and lower mental
health scores than low scorers.
Analy.
Logistic repession analyses (using SPSS v. 8.0) were conducted to predict
composite outcome status (high vs. low) at both 1- and 3- month fonow-up periods.
Variables selected as potential predlctors were all simultaneously entered into the logistic
regression model. A simultaneous entering method was chosen so that the predictive
ability of the variables could be determined within the context of the other variables.
From these analyses, risk ratios, 9S,. confidence intervals, Wald test statistics, and
standardized parameter estimates were obtained.
Subsequently, multiple linear regression analyses were conducted to detennine
predictors (at 1- and 3-month follow-up) ofeach ofthe four separate outcomes (i.e.,
symptom severity, functional status, lost days, and mental health) used to calculate the
composite outcome score. Independent variables entered into the linear rearession
analyses were identical to those used. in the logistic regression analyses. These variables
were also simultaneously entered into the model.
RESULTS
Throup t-test andr analyses, a comparison of study participants with <n=70)
and without <n =17) complete 1- and 3-month follow-up data found no significant
differences in age. education level, ethnicity, job category, or gender. The results
described are based upon the 70 subjects for whom all follow-up (i.e., both 1- and 3
month) data were obtained.
DelDOlr8pble Charaderlltlcs
The sample ranged in age from 22 to 64 years with a mean age of40.8 years <m
=10.5). The majority of the sample was Caucasian (74.3'1'), female (77.1"), and had at
least some college education (92.9"). Table 8 provides a more detailed description of
the demopphic characteristics.
Table 9 provides the breakdown of the International Classification ofDiseases,
Ninth Revision (lCD-9) (World Health Organization, Geneva, Switzerland, 1995)
diagnoses of the participants. As shown in the table, carpal tunnel syndrome was the
most common eliaposes in the sample. The second most frequent eliaposis was an
unspecified disorder of the synovium, tendon, anellor buna. In addition, the types of
prior treatments that participants had before the baseline, I-month, and 3-month
assessmeat periods are given in Table 10.
There was a moderately sipificandy difference in age between the l-month
"hip" <ttl= 43.23, .m=10.45) and "low" Q4=38.37,m= 10.0S) SCODna groups (l =
-1.98, 1=0.05). No sipificant differences were found between these IJ'OUPS in
education level. ethnicity, job category, or gender. For the 3-month follow-up period,
22
23
"high" and "low" scorers on the composite outcome measure did not significantly differ
on age, education level, ethnicity, job category, or gender.
Test-Retest
Test-retest correlations (n = 23) on the independent variables of symptoms,
function. ergonomic risk exposure, occupational psychosocial facton, social support, and
individual psychosocial facton were examined. The comlation coefficients are provided
in Table 11. As shown, all measures were found to be significantly correlated <ll <0.05),
with correlation coefficients ranging from 0.42 to 0.90. These results indicate a moderate
to high level of reliability in the self-report of the various assessment measures at
baseline.
Predlcton ofComposite Outcome Stalulat 1 Month
After a preliminary logistic regression analyses was conducted, a more specific
model was determined by selectin, variables that reflected the proposed multivariate
nature ofpredictors and were significant at the R<0.15 level. Variables that were
enteled into the finalloaistic regression model were: number ofpast upper extremity
diagnoses. the Mental Health Subscale of the SF-36 at baseline, pain severity within the
past week, er,onomic risk exposure, job sttess (Moos "Moos. 1994), job support
(Caplan. 1971). and eatastrophizin,.
All variables enteral into the final logistic regression model with the exception of
job stress were found to be significant predictors ofcomposite outcome at 1month.
Table 12 provides a summary ofall significant predieton with their risk ratios (RR). 95'1)
24
confidence intervals (el), Wald statistic, and standardized parameter estimates. All
significant predictors had a continuous response scale, and therefore, the risk ratios are
for each unit increase in a given response.
Demographic Characteristics
No demographic characteristic variables from the preliminary model met the
selection criteria for the final model.
Occupational Status
No occupational status variables were found to meet the selection criteria for the
final model.
Medical History I Status
A history ofupper extremity disorders was found to place a person at a greater
risk for poorer outcome. Specifically, each upper extremity diapolis was associated
with a 1.7I-fold risk (CI=1.14 - 2.57) for a poorer outcome.
Symptoms
Self-reports of greater pain severity within the pIIt week also resulted in a pealer
likelihood for poorer outcome (RR = 1.50; CI=1.08 - 2.07).
Physical FIUIClion
No functional measures were entered into the final logistic repession model
because of failure to meet the selectioncriteria for the final model.
25
Ergonomic / Biomeclumical
Exposure to ergonomic risk factors was found to place a person at a greater
likelihood forpoorerouteome (RR =LOS; CI =1.01- 1.11).
OccupatioruU P8YCMsocial
lob stress was not found to be a significant predictorofcomposite outcome status.
Work DetnlIfIds
Perceived exertion as measun=d by the Borg CRIO Scale did not meet the
selection criteria for the final model.
Social SlIpport
Reportina1eas social support from one's co-workers and/or supervisor was found
to predict poorer outcome. Each unit decrease in reported social support had a risk ratio
of 1.03 (CI =1.00 - 1.07).
lrulivit.lllal Psychosocitll
A person who had a lower SF-36 Mental Health Subscale score (indicating poorer
mental health/pealer disuess) at baseline was more likely to have a poorer outcome (RR
= 1.25; CI = 1.01-1.54). Additionally, individuals who &&eatastmphized" more over their
pain hadan increased likelihood for a pooreroutcome (RR =1.58; CI =1.12 - 2.23).
26
The final logistic regression model correctly classified 78.6'1> of all subjects <i=
24.80, dl= 7,11 < 0.001). Specifical1y, 77.1'1> of the "low" scorers and 80.0% of the
--high" scorers were classified correctly.
Predlcton of Composite Outcome Status at 3 Months
Similar to the I-month analyses, a preliminary logistic regteSSion model was
examined to obtain variables for a more specific model targeted at predicting composite
outcome at 3 months. SSS score at baseline, past recommendation for surgery, number
of prior treatments, ergonomic risk exposure, job stress, perceived exertion during a
typical workday, job support, work accommodation, and catastrophizing were the
variables found to be significant at the I! < O.IS level. Therefore, these variables were
entered into the final model.
Table 13 summarizes the significant predictors identified by the final logistic
repession model. All significant predictors, with the exception of past recommended
surgery, had a continuous response scale. Therefore, for these continuous variables, the
given risk ratios are for each unit increase in the responses.
Demogrtlphic Characteristics
No demographic characteristics met the selection ~teria for the final3-month
model.
27
Occupational Status
No occupational status variables were found to meet the selection criteria for the
final model at 3 months.
Medical History I StaIUS
Recommended surgery as well as the number of prior treatments were found to
significantly predict poorer outcome status. Having had a past recommendation for upper
extremity-related surgery resulted in a risk ntio of 5.53 (el = 1.18 - 25.86). Each
treatment for an upper extremity disorder placed an individual at a 2.24-fold greater risk
(CI=1.26 .. 3.96) for a poorer outcome.
Symptoms
An individual's baseline Symptom Severity Scale score significantly predicted
poorer outcome. Each point increase in baseline SSS score was associated with a risk
ratio of 6.21 (el =1.28 .. 30.09).
Physical Faction
No measures of function were enteted into the final model.
Ergonomic I Biomeclumical
Pooreroutcome status was predicted by self-report ofhigher expoSUle levels to
eraonomic risk facton <Rit=1.08; CI=1.01 -1.15).
28
Occupational Psychosocial
Persons who reported higher levels ofjob stress also had a greater likelihood of
having a poorer outcome (RR =1.21; CI =1.02 - 1.43).
Work Demands
Perceived exertion during a typical workday was not found to be a significant
predictor of outcome.
SocioJ Support
lob support was found to predict poorercomposite outcome status, while work
accommodation was not a significant predictor. Lower levels ofjob support from co-
workers aneUor supervisor was associated with a risk ratio of 1.04 (CI = 1.01- 1.08) for
poorer outcome.
Individual Psychosocial
A greater tendency to ueatastropbize" over pain significantly predicted poorer. .
outcome (RR =1.81; CI =1.24 - 2.66).
The final logistic regression model correctly classified 77.1'11 of all subjects <7! =48.38, sit= 13,11 < 0.001). In this model, 8O.QfII of the "low" (i.e., better outcome)
scorers ancl74.3'11 of the "hip" (i.e., poorerourcome) scorers were cometly classified.
29
PredJcton of Indiviclal OutcollllS at 1 Month
Table 14 summarizes the predictors of the individual outcomes incorporated into
the composite outcome index. Baseline SSS score was found to predict days lost,
symptom severity and functional status at 1 month. Catastrophizing was found to predict
symptom severity, functional status, and mental health. Baseline measures of days lost
and mental health predicted their respective outcomes at 1 month as well.
Pndlcton of IDdIYldal OUtco.... at 3 MORtbs
Table 14 also summarizes the predictors of the individual outcomes that were
incorporated into the composite outcome index at 3 months. Baseline SSS score
predicted days lost in the put month, symptom seventy, and functional status.
Additionally, 3-month symptom severity and functional status were predicted by a greater
tendency to "catastropbize" over pain. An individual's cognitive workstyle was also
found to predict days lost. More precisely, an adverse copitive workstyle in which a
person had more frequent beliefs ofneeding to continue work anellor being unable to take
off from work predicted days lost. Poorer mental health was predicted by a lower
baseline mental health score as well as peteeiveclexertiOll during a typical workday.
DISCUSSION
The present investigation prospectively examined a community sample of
worken with an upper extremity disorder to identify predictors ofa composite measure
ofoutcome. The findings indicated that poorer outcome could be predicted by a
combination of medical, ergonomic, occupational psychosocial, and general distress
factors and, therefore, supported the study's hypothesis. The specific variables found to
distinguish outcome status at both 1- and 3- month follow-up periods were: exposure to
ergonomic risk factors, job support, and catastrophizing. Additional predictive variables
at the I-month fonow-up Period included: history of upper extremity disorders, mental
health (as measured by the SF-36 Subscale), and baseline pain severity within the past
week. At the 3-month follow-up period, baseline symptom seventy, recommended
surgery, number of prior treatments, and job stress were also found to predict outcome
status.
RIsk Faden for Poonr Outcome
Medical Hiaro,., I StatIU
In addressing the future outcome of a worker with an upper extremity disorder,
the present findings sugest that baseline medical history is an imponant preliminary
factor to consider. A worker with past upperextremity diagnoses in multiple anatomical
locations, who has had surlery recommended for a work-related upper extremity
problem, and/or has had a multiple past aeatmeDts is at an increased risk for delayed
recovery. These are potentially more complex cases and perhaps deserve peater
attention especially with reprd. to fonow-up.
30
31
Symptom Severity
It is interesting that even though greater symptom severity predicted poorer
outcome at both 1 and 3 months, different measures were found to be significant
predictors at the two follow-up periods. The implication of these findings is that perhaps
a broader measure of symptoms (e..g.., the SSS) would be more sensitive for assisting with
the determination of future outcome. It is also interesting that none of the other baseline
measures of functional status, lost days, or mental health predicted the outcome status
that incorporated these variables. This finding suggests that a panicular focus should be
placed on the other factors (e.g.., ergonomic and psychosocial) that were found to be
sipificant predicton ofoutcome in workers with a WRUBD.
Ergonomic Risk FactorEqolUre
While studies have found ergonomic and biomechanical risk factors to be
associated with and/or predictive of upper extremity symptoms and disorders (e.g.,
Punnett, 1998; English et al., 1995; Tanaka et aI., 1995; Feuerstein &. Fitzgen1d, 1992),
few investiptions have examined these variables as predieton of both physical and
psychological health outcomes. The present study indicates that within a sample of upper
extremity disorderpatients, self-report ofeqonomic risk facton can be used to predict a
composite o~teome index that incorporates both physical and psychololical health.
OccupatiOlllll Psyclao&ociIJI FGClors
Occupational suess hu been found to be conelateel with andIor predictive of
upperextremity symptoms as weD as mental bealth.. A study ofnewspaperemplo)'eCS
32
found that increased job pressure and working under deadlines are associated with a
greater prevalence ofneck, shoulder, hand, and wrist disorders (Bernard et al., 1994).
Peer cohesion, staff support, control, work pressure, clarity in policies/rules, job
satisfaction, work autonomy, stress, and physical comfort have also been found to
distinguish between repons of "high" or "low" levels of pain in a sample of visual
display unit operators employed at a newspaper publishing organization (Stephens"
Smith, 1996). Occupational stress has also been found to be related to mental health
outcomes as well (e.g., Smith, 1997; Spurgeon et al., 1997). In an empirical investigation
ofelectronic company employees, items relating to trouble at work, greaterjob
responsibility, lower margin for error, and poor relationships with superiors have been
found to be associated with poorer general mental health as determined by the General
Health QuestiODDaire (Shigemi et aI., 1997). The present findings are consistent with
previous studies and indicate that job suess can predict acomposite outcome that
incorporates a worker's physical and mental health. Furthermore, given that the present
study assessedjob sttessors such as time pressure and interpersonal conflicts (i.e., using
the Job Stress Subscale), the present findings relating to job support (discussed in the
following section) take on added importance.
Low Job Support
Social support has been noted to be positively associated with physical and
psychological health (House et aI•• 1988). A number ofstudies bave also observed a
relationship between lower levels ofjob support and upper extremity symptomsldisorders
(Faucett" Rempel, 1994; Linton" Kamwendo, 1989; Leino It Hanninen, 1995). In the
33
present investigation, lower perceived levels of support specific to one's work
environment (i.e., from co-workers, suPerVisor) was found to be a significant predictor of
poorer outcome status. This result suggests that job support continues to playa role in
the outcome of a worker once he/she develops an upper exttemity disorder.
Individual Psychosocial Factors
The findings also indicate that a pealer reactivity to pain from an upper exttemity
disorder and its impact (Le., catastrophizing) is predictive of poorer outcome at 1and 3
months. Catstrophizing in relation to pain has also been found to differentiate work-
disabled and non-disabled patients with a work-related upper exttemity disorder as weD
as those with longer duration of disability (Himmelstein et aI., 1995). The present results.
repreting heightened reactivity are also consistent with past studies indicating the
significance ofconsidering general distress in workers with WRUEDs. In acohort of
Finnish farmers, psychological distress (measured by the Symptoms Distress Checklist)
was found to be a risk factor for disability from neck-shoulder disorders (Manninen et aI.,
1997). Additionally, self-reponed depressive symptoms have been found to predict
changes in necldshoulder and upper limbs symptoms in !'Oth men and women (Leino &.
Magni,I993).
Po....tIal MecIwIiIJDI
In considerinl the identified risk facton of the present study, potential
mechanisms can be suuested for conceptualizing how these variables. may lead to poorer
outcomes.. It is interesting that both eraonomic and occupational stressors were found to
34
predict poorer outcomes. While multidimensional models ofWRUEDs address the role
ofergonomic and occupational psychosocial factors, their roles in outcomes is unclear.
One possibility is that in workers who have already developed a WRUED, occupational
stress can result in a heightened physiological reactivity, which in tum, can lead to a
more detrimental outcome from exposure to ergonomic risk factors. This construct of
"workstyle" (Feuerstein, Huang," Pransky, 1999) bas been proposed as a potential link
between ergonomic and psychosocial factors in WRUEDs. While further empirical
support is needed to validate this construct, it may provide a way to understand the
potential interaction between psychosocial and ergonomic stressors.
Interpersonal relationships on the job also appear to play an important role in
WRUED outcomes. Again, it should be noted that the lob Stress Subscale of the
USRES (Moos &. Moos, 1994) used in the present study included items concerning
relationships with co-workers and supervisors. Also, job suppan was found to be a
significant predictor at both the I-month ancl3-month foUow-up periods. Therefore, not
only can adverse work: relationships be a source ofstress for workers with WRtJEDs, but
they also do not allow the worker to obtain support for which to better cope with pain
and/or other consequences of the disorder. As these sequelae persist over time, they may
contribute to poorer outcomes.
Penonality facton (e.g., stable, enduring interactions with one's environment)
have been usociated with upperextremity disorders. Forexample. performance focus
and efficiency. goal dilectedness, timeliness of task accomplishment, and orpnizatiOD of
physical space taken from the Lifestyle A.pproIches scale (Williams et al•• 1992) have
been found to distinpisb between carpal tunnel syndrome (CfS) and non-CTS patients
35
(Vogelsang, Williams, & Lawler, 1994). An investigation ofDanish salespersons with
self-reported musculoskeletal (i.e., neck, shoulder, low back) symptoms found that an
interaction between low control and high levels of perceived competition from other
salespeople placed a saleSPerson at a greater risk for neck-related symptoms (Skov, Borg,
&. Orhede, 1996). It has also been reported that 21'11 of acute carpal tunnel syndrome
patients who saw an onhopedic hand surgeon met DSM-IIIR diagnostic criteria for at
least one personality disorder (Mathis et aI., 1994). In this sample, obsessive-compulsive
(9%) and paranoid (9%) personality disorders were the most common diagnoses. This
pattern of findings suggests that high levels of task-oriented behavior and heightened
sensitivity to negative consequences in the environment are associated with upper
extremity disorders. Subsequendy, this disposition may place a worker with upper
extremity symptoms at a greater susceptibility for distress which may exacerbate the
problem.
In addition to these personality factors, it is has been suggested that uncertainty
about prognosis may also contribute to greater distress (i.e., catastrophizing) in WRUED
patients (Himmelstein et aI., 1995). Failed attempts at seeking relief may further result in
disuess regarding the WRUED and, therefore, lead to poot'er outcome. These
possibilities may become more problematic when coupled with a work environment that
contains adverse relationships, lilde or no support from co-workers anellor supervisors,
and exposure to ersonomic risk factors. Othermechanisms by which catastrophizing
may be related to pain experiences include a neptive appraisal of and a dccn:ased ability
to cope with the pain (Weisenberg. 1994). Therefore. it is possible that stressful
relationships at work as well as a lack ofsupport may result in a reduced ability to cope
36
with and recover from a WRUED. Subsequently, workers with these risk factors may be
more likely to have poorer outcomes in relation to their WRUED.
While these potential mechanisms are speculative, they highlight future directions
for which research on WRUED outcomes can proceed. By obtaining a greater
understanding of such mechanisms, more focused prevention and intervention efforts can
also be conducted.
ImpUeations ud SUgestiODS lor IDtervention
Few prospective studies have examined the combination of factors that were
employed in the present investiption. Furthermore, while past studies have identified
some predictors of work-related upper extremity disorders, it is less clear what role these
factors play once the problem has developed. As previously discus~ them is also a
need to identify mechanisms by which WRUEDs occur and how various factors
contribute to their exacerbation and/or maintenance. However, the present findings that
ergonomic risk exposure, job stress, job support, and cawtrophizing predicted composite
outcome at 3 months hiatilight the potential importance of an integrative approach to
improving worker health and/or preventing funher dectements in outcome following the
onset of a WRVED. In addition, the present results suuest that such effons should also
address both orpnizational and worker-related factors.
Several organizational interventions have been suaested to address ergonomic
risk factors (e.8., Cohen et al., 1997) and occupational sttessors (e.8., Cooper &
Cartwript, 1997; Murphy. 1996; Ivancevich et aI•• 1990). However, few intervention
stratepes have been proposed that tarBet both erpnomic and psychosocial stIeSSOrS..
37
Attempts at reducing these stressors should utilize a multidisciplinary team that involves
management, the employee, occupational health providers, ergonomists, and
psychologists. This approach has been suggested as a feasible way for generating and
implementing accommodation efforts for disabled workers in lipt of the Americans with
Disabilities Act (Kearney 1994; StoekdeU "Crawford, 1992; Huang" Feuerstein,
1998). Schunnan (1996) bas also proposed the use of an intervention and research
method called "participatory action research (PAR)1t for redesigning work organizations
as well as to improve performance, health, and safety. Components ofPAR include: a
focus on system development, a co-learning process, a participatory and democratic
process, an empowering process, and a balance between research an intervention.
Additionally, PAR should be a joint effort on the parts of labor, management, and
researchers.. A recent publication by the National Research Council (Druckman, Singer,
" Van Colt, 1997) has ~oted that changes in technology, environment, and the population
are major factors that influence orpnizational change.. In response to these changes,
different types oforpnizational forms have been developed. One such form utilizes a
team...basedorpnizalional approach. While these teams can be temporary (called
"adhocracies") or permanent in nature. it hu becm sUllested that they can be appropriate
given a particular type ofsituation.
With a multi-faceted team, a problem-solving Sll'lle1Y (Nezu & Nezu. 1993) may
be utilized to reduce risk factors that may lead to decreased worker health. Specifically,
this strategy involves identifyinl and analyziDl problems, pneratinl potential solutions,
then selectinl, imp1ementinl. andevaluatiDl the solution. It has been indicated that self
appraised "effective" problem-solven tend to report fewer physical symptoms (Elliott &
38
Marmarosh,1994). A positive relationship has also been shown to exist between
problem solving ability and reduced levels of psycholopcal distress (D'ZurilJa &. Sheedy,
1991). Other studies on social problem solving have found it to be a moderator of
depressive symptoms related to stress (Nezu et aI., 1986; Nezu & Ronan, 1988). With a
multidisciplinary team involved in a problem-solving process, it is possible that
considerations and/or barriers can be mote diJ:ecdy and effectively addressed. As a
teSult, mote immediate and efficient solutions for reducing organizational and/or
environmental risk factors can be obtained and implemented.
The use of a multidisciplinary team may also help to inctease levels ofjob
support. It should be noted that one aspect of the job stress measure assessed in the
present study was interpersonal conflicts on the job. Coupled with the findings telating
to job support, it would appear that interpersonal relations on the job playa vital role in
influencing the outcome ofa worker with a WRVED. This suggestion can be better
undentood within the context of "autonomy support." Ryan and Solky (1996) describe
this type of support as:
"...the readiness of a person to assume another's penpective or internal frame of
reference and to facilitate self-iDitiatedexpression md action" (p. 252).
Within a work orpnization, it is possible that the inability of a worker to tab the
penpective ofmanagement and vice vena may help explain bow interpersonal facton
affect upperextremity outcome. AccordinalY, ifemployees and management can lam to
increase their awareness ofthe pressures, concerns, and/or difficulties of the other party,
then a less antagonistic and more supportive environment may be produced.
39
Furthermore, with such a support system available, anxiety and heightened reactivity
(i.e., catastrophizing) associated with the disorder may also be reduced.
Presently, it is not clear how to best design a work environment that encourages
autonomy support and/or a team-based form of organization. However, the
organizational literature has discussed total quality management (TQM) as one technique
for facilitating organizational change that encourages such workplace attributes.
Although the consttuct ofTQM has not been clearly specified and quality can be a
relative concept (Druckman, Singer," Van Cott, 1997), TQMdoes address the strategy,
culture, techniques, activities, and overall functioning of the organization. Therefore, it is
possible that TQM may be a potentialS1l'ate1Y for improving the upPer extremity health
of workers as wen as enhancing an organization's overall performance. However, a lack
ofempirical evidence on the effectiveness ofTQM highlights the preliminary nature of
these sugestions and emphasizes the need for more systematic investigations of these
approaches.
Stud, LlDlitatlolll
While this study has several implications for the improvement ofphysical and
psychological health as wen as for secondary prevention, the limitations of the study
must also be taken into account. In pneralizing the present fiDdinp to a IlIFr
population, one should. note that the majority of the participIDts in the pmsent study were
collele educated., Caucasian women. While genderdifferences in WRUEDs have not
been definitively established., past studies bave found that women are more likely to
report upper extremity symptoms (e.g., Polanyi It al., 1997; BemardIt al., 1994). There
40
is also uncertainty concerning the role ofeducation in WRUEDs. Certain jobs (i.e.,
cleaners, hairdressen, secretaries, assembly line workers, and machine operators) have
been found to be significantly over-represented in women who were diagnosed with an
upper extremity disorder (English et at., 1995). However, job type may not necessarily
be a direct reflection of eclucationallevel. Therefore, to understand how applicable the
present findings are to the population in general, further investigations that delineate
individual predictors ofWRUEDs (e.g., gender, ethnicity, education) and theirouteomes
are needed.
The eligibility criteria of a recent diagnosis presented some difficulty in obtaining
panicipants for the study. SUbsequently, a relatively small sample size was examined.
~owever, even with the limited sample size, a number of variables were found to be.
significant predictors at 3 months. Therefore, it is possible that for the identified risk
factors, a larger sample size would have found a greater likelihood for a poorer outcome.
The methodological approach used in obtaining information telating to upper
extremity diagnoses could have also been improved. Although upper extremity disorder
diagnoses were documented by each panicipant's respective health care provider, the use
ofa standardized method for diagnosis (e.g., using a sinlie physician) would have been
more desirable. Such a method may also have provided. useful objective iDformation
regarding clinical presentation, symptoms. and quantitative fuDctionallimitations.
Nevertheless. given that sipificant findinp were obrained with a diverse setof
diagnostic procedures, this study provides useful information concerninl this
heterogeneous population.
41
The exclusive use of self-report measures in the composite measure ofoutcome
may have also been a limitation because of the potential for subject bias. The Symptom
Severity Scale and the Functional Status Scale were utilized in the present study because
of their correlations with other clinical measures (Levine et al., 1993). Nevertheless,
future investigations should incorporate concurrent measures of symptoms, functional
limitation, and psychosocial factors from sourtes such as health care utilization and/or
medical records, personnel records, and/or supervisor reports. It has been argued that
because expert judgments as well as self reports ofergonomic exposures may provide
only a limited amount of information, future research might also usc direct observations
in the ergonomic assessment (van der Beek et Frings-Dresen, 1998).
It is also possible that differences in the patterns ofpredictors may have been
found for a longer follow-up period. The predictors of composite outcome status may
change when a patient has had time to heal and/or obtain tteatment. Presendy, there is an
on-going effort to determine outcome in these patients after a 12-month period. Once
this follow-up is completed, it would be possible to determine whether any differences
occur in the patterns ofpredictors over time. These subsequent results may also provide
further direction for improving worker health ancUor secondary prevention efforts.
One other potential study limitation may be the definition ofcomposite outcome.
Wbile symptoms, function, lost days, and mental health have n:cendy become more
commonly measured clinical outcomes, perhaps a more empirically validated set of
outcomes should be examined. However, few studies have utilized a composite outcome
measure that incorporates both physical and mental health outcomes. Consequendy. it is
42
difficult to ascertain what a meaningful measure ofcomposite outcome and/or health
should entail.
Condolon
The present investigation indicated that ergonomic and psychosocial sbessors
associated with one's work are predictive of poorer outcome in workers with a WRUED..
There were also indications that medical history, symptom severity, and interpersonal
factors deserve attention as potential moderators of these stressors. Implementation of an
interdisciplinary team that utilizes a problem solving approach was proposed as one
strategy for removing potential barriers that contribute to poorer outcome. An
organization with such a team dedicated to improving worker health may also facilitate
m.ore positive worker perceptions of a supportive work environment. While future
evaluation of such an interVention is needed to determine its efficacy, the present findings
indicate that medical. physical, ergonomic, and psychosocial factors all need to be
addressed in any effons targeted at helping workers recover from work-related upper
extremity disorders. By improving outcomes in these workers, it is hoPed that recurrent
and/or chronic problems associated with these disorders can be prevented. Subsequently,
it is possible that organizational efficiency as well as worker satisfaction, productivity,
and overall quality of life can be incn=asecL
TABLES
43
TABLE 1
CORRELATIONS MIONG MEDICAL STATUS MEASURES
~ DcImInn PrIor • at,.. nm.trom • at,.. Sa......, OIlIer...... GrIp ...... PInch ...... Upper Symptom T.......... Recam- Medical.......... ....... CotnpInIa- ED..., OMeIto ......... Problema
lion""'" .....a••• .......T......-nt
Iodr..... 0.170 0.100 0.150 0.122 0.008 -0.031 0.250· 0.167.......DanIInmt -- 0.862·· 0.208 -0.176 0.369·· -0.313-· 0.030 -0.095...... artp.......DanIInmt -- 0..172 -G.239- 0.258· -0.233 0.033 -0.144HInd PInch-- ...
PrIorW....' .- -G.42 0.040 -0.034 0.148 0.037~tlDnlnJln.at ..... -- -0.112 0.276 -0.086 0.070Upper........,_.,........ -- -0.014 0.088 0.010.,....OMeIto......T.......•ot,.. -- 0.083 -0.152T.............. -- 0.326··H..........D=70
• 1<0.05 •• R <0.01 t
....ClovQI:
8dV
II QICI •-l::"':"' __
45
TABLES
CORRELAnoNS AMONG PHYSICAL FUNCnON MEASURES
SF3I SF3IRoIe- UpperPh,..1 PhyalC8l ExtremityFunction Function
Sell..Functional' -0.842** -0.543** 0.880**_ScaleSF38....,... - 0.395** -0.623**Function
SF38Ro1e- - -0.620**Ph • I
0=70
• R < 0.05 ** 11 < 0.01
8\
TABLE.
CORRELATIONS AMONG OCCUPATIONAL PSYCHOSOCIAL MEASURES
NIOSH CognitiveOccup8llol181 Work8tyIePsyc1lo8oc18'Checldlst
JobStreu 0.644** 0.370**(Moo."Moos, 111M)
NIOSH -- 0.437**Occup8tlon81Paychosocl8lChecldlst
0=70
* R < 0.05 ** R < 0.01
:!j
TABLES
CORAELAnoNS AMONG WORK DEMAND MEASURES
WorIdoIId Phyelcal , Me....1 Borg (1998) CA 10V.rI.nce exhaustion scale of
P.-celved Exertion
WorIdoIId 0.406·* 0.490*· 0.277*
Worldolld - 0.439·* 0.200V."nce
....,..1/ .......1 -- 0.340*·Exhauatton
0=70
• I! <0.05 .* I! < 0.01
~
TABLE'
CORRELAnoNS AMONG INDlYIDUAL PSYCHOSOCIAL MEASURES
.....Tndt C8b1etrophlzlng DlecomtortAnxiety IntolenlnceInventory Scale
SF3IMent8I -0.687** -0.625** -0.321**HeIIIth
Sbde-T..n --- -0.442** 0.206AnxietyInventory
CIdIIsIrophlzing -- 0.206
0=70
* R < 0.05 ** R < 0.01
~
so
TAlLE?
STANDARDIZED FACTOR LOADINGS FOR COMPOSITE OUTCOME INDEX
Comp081te Health Index loading
Factor 1 Month 3 Months
Functional Severity 0.871 0.875
Symptom Severity 0.832 0.804
Days Lost 0.431 0.723
Mental Health 0.755 0.689
51
TABLE.
DEMOGRAPHIC CHARACTERISnCS
AgeMean (years) 40.8SO 10.5
n %Gender
Female 54 n.1Male 16 22.9
EthnlcltyWhite/Caucasian 52 74.3Black/African-American 11 15.7LatinolHispanic 4 5.7AsianlPacific Islander 2 2.9Other 1 1.4
Education LevelHigh School Diploma or GED 5 7.1Some college 17 24.32 Year degree 6 8.6Bachelor's degree 10 14.3Some graduate school 11 . 15.7Master's degree 15 21.4Graduate degree 6 8.6
Job categoryClertcal worker; word processor 23 34.3ProfessionallTechnical 23 '·34.3Management/Administration 12 17.1service 4 5.7Sales 3 4.3Machine Operator 2 2.9Craftsman 1 1.4
n=70
52
TABLES
DIAGNOSES
S --c ICD-I Dlaano."No. of
Subjects *
Nerve Root and Plexu. Disorders (353)Thoracic Outlet Syndrome (353.0) 2
Mononeuritis of Upper Umb (354)Carpal Tunnel Syndrome (354.0) 33Unspecified mononeuritis of upper limb (354.9) 3Cubital Tunnel Syndrome (354.2) 1
Disorders of the cervical Region (723)Cervicalgia (pain in neck) (723..1) 2Unspecified neck symptoms or disorders (723.9) 1
Peripheral EnthHopathle. (728)Lateral epicondylitis (726.32) 5Medial epicondylitis (726.31) 2Unspecnled enthesopathy (726.9) 2
Tendon, Synovlum, and Burea Disorders (727)Unspecrled disorder of synovium, tendon, and bursa 13(727.9)Radial styloid tenosynovitis (deQuervain's) (727.04) 4Trigger finger (acqUired) (727..03) 1Other tenosynovitis of handlwrfst (727..05) 1
Disorders of muscle, ligament, and fMcla (728)Muscle spasm (728.85) 1Unspecified disorder of muscle, ligament, and fascia (728.9) 1
Other DI..... of Softn..... (728)Myalgia, myositis. fibromyositis (729.1) 2
.. Note: Total number of subjects is greater than sample size en :: 70) becau.certain subjects had multiple diagno....
53
TABLE 10
TREATMENTS USED PRIOR TO BASEUNE, 1 1& 3 MONTH FOLLOW-UPS
B••llne 1 Month 3 MonthsTreatment n(%) !!(%) n(%)
Medic••Nonsteroidal anti-inflammatory drugs 59 (84.2) 56 (80.0) 44 (62.9)Local steroid injections 14 (20.0) 17 (24.3) 14 (20.0)Surgery 6 (8.6) 5(7.1) 9 (12.9)Other 2 (2.9) 4 (5.7) 5 (7.1)Oral steroids 2 (2.9) 1 (1.4) 0(0.0)Antidepressants 1 (1.4) 4 (5.7) 3 (4.3)
PhYla. TherapySplinting 36 (51.4) 37 (52.9) 30 (42.9)Ultruound 17 (24.3) 18 (25.7) 16 (22.9)Other 16 (22.9) 17 (24.3) 17 (24.3)Muscle re-education 11 (15.7) 9 (12.9) 9 (12.9)Transcutaneous neNe stimulation 9 (12.9) 11 (15.7) 10 (14.3)Traction 3 (4.3) 3 (4.3) 3 (4.3)Collar 0(0.0) 2 (2.9) 1 (1.4)
PaycholOl"'.Stress management 6 (1.4) 4 (5.7) 5 (7.1)Other 1 (1.4) 1 (1.4) 0(0.0)Pain management 0(0.0) 2 (2.9) 1 (1.4)Psychotherapy 0(0.0) 1 (1.4) 0(0.0)Biofeedback 0(0.0) 0(0.0) 1 (1.4)
TABLE 11
TEST-RETEST REUABILITY OF INDEPENDENT VARIABLES
MenU,. r-Symptom Severity Seale 0.79"
Functional Status Scale 0.90**
SF·36 Mental Health Subseale 0.84**
Ergonomic Stressors Scale 0.86**
Job Stress Subseal. 0.83**
Cognitive Workstyle 0.85"
Job Support 0.84"
Catastrophizing 0.72"
Work Accommodation 0.42*
n=23
* R<0.05 .. 11<0.001
Note: Duration = 2 weeks
54
TA8LE12
PREDICTORS OF COMPOSITE OUTCOME STATUS: 1 MONTH
I5%CIRlskRldlo Low. Upper Wald R
No. of Past Upper extremity 1.71 • 1.14 2.57 6.62 0.22DIagnoses
SF38 Mental Health 1.24 • 1.01 1.54 4.29 0.15
Pain Severity 1.50 • 1.08 2.07 5.90 0.20
Ergonomic Risk Exposure 1.06 • 1.01 1.11 4.78 0.17
JobSUpport 1.03 • 1.00 1.07 4.83 0.17
C8tastrophizing 1.58 •• 1.12 2.23 6.85 0.22
0=70
* 8<0.05 ** 8<0.01
..,...,.
TABLE 13
PREDICTORS OF COMPOSITE OUTCOME STATUS: 3 MONTHS
I5%CI.......V...... Rlak RIItIo Lower Upper W.1et R
Symptom severity Scale 6.21 * 1.28 30.09 5.14 0.18
Recommended Surgery 5.53 * 1.18 25.86 4.71 0.17
No. of Prior Treatments 2.24 ** 1.28 3.96 7.62 0.24
Ergonomic Risk Exposure 1.08 * 1.01 1.15 4.63 0.16
Job Stress (Moos) 1.21 * 1.02 1.43 4.71 0.17
Job Support 1.04 * 1.01 1.08 5.63 0.19
C8tas1rophizlng 1.81 ** 1.24 2.66 9.27 0.27
0=70
* 11<0.05 ** 1l:S 0.01
~
TABLE 14
PREDICTORS OF INDIVIDUAL OUTCOMES: 1 1& 3 MONTHS
57
o.ys Lo. In Pam Month1 Month 3 Montha
Variable Beta AfIZ Variable Beta AR"No. of Past UE Baseline SSSDiagnoses -0.330 ** 0.184 Score 0.301 * 0.210Baseline SSS CognitiveScore 0.267 * - Workstyle 0.444 ** 0.128Baseline DaysLost 0.465 ** 0.294
Symptom~
1 Month 3 Month.Variable Beta AR" V.rlable Beta AFt"
Baseline SSS Baseline SSSScore 0.755 ** 0.635 Score 0.557 ** 0.404PerceivedExertion -0.188 * 0.023 eatastrophizing -0.482 * 0.066
CatastroDhizina -0.281 * 0.022
Functional Statu.1 Month 3 Months
Variable Beta AR" Va"'" .... AFt"Baseline SSS Baseline SSSSCore 0.182 * 0.613 SCore 0.230 * 0.497
Catastroghizina -0.308 * 0.027 C8tastroDhizina -0.472 * 0.083
...nI8.....11h1 Month 3110nths
Variable .... AFt" V...ble Beta AFt"Baseline SF36 Baseline SF36Mental Health Mental HealthScore 0.666 * 0.541 SCore 0.852 ** 0.434
PerceivedCatastrophlzing 0..484** 0.088 Exertion 0.248 * 0.038
n=70
* R < 0..05 ** R < 0.01
APPENDICES
S8
AftIlDU A
WRVED 'RO~E SCREEN INTERVIEW59
Hi, I'm •a researcher at die Uniformed Services University. I'm calli... you back toIlk whether you are interested in pllticipadnl in the reseIIdl study of.ork-n"" .pperem_tty dIsonl'ft. The study involves comiDI in for ONE 1to 1~ hour visit wbae,vu willfill out a questioaaaile and complete several tISks. Yau will also be livea dine coplel of. briel2......te queslioanaile to fill out 1,2,ad 3 ...........yoarYilIt. You'D mail them backin the .If-addressecl, pre-paid envelopes proYided.
None orthe procedures lie barmfb1 or cJanaerous in lIlY way. For instIDce, then lie DO aeedlesor blood draws or takiul ofany cIrup. Foryour padicipatioa. (a total ofabout 2 bo... ofyourtime), you will receive MI•• upon completion oftbe third follow-up questiODDlile.
Do you tbiDk that you mipt be iDterestecl in pII1icipatiDa?
IfNO, say, "11uuIIc: you anyway (or your time. Goodbye.It
IfYES, .y, "Great. Let IDe do two tbiDp DOW ifyou have a few minutes. OK, the nRST thiDl.1'd Ute to do now is to ask you some questions in reference to your medical history. Do you havea few more miDutes DOW to answer these questions?
IfNO, say, "When is a aooct time for me to call you blclt?"
IfYES, continue with be saeeD on the aext pile.
lat'rviewer: _
0..: _
N...: _
'IaOD': R IW _
1) What is your aae? _
2) Are you currently employed? Y N
IfYES, bowDIlDYhours per week? _
IfYES, what kiDd ofwork do you do? ~-
603) Have you been diaposed with 18 UPPER EXTREMITY DISORDER Y N
If,., when? _
If,a, did JOu or the doctor who diaposed it believe that it wasIeIatecI to your work? Y N
Ifyes. was the cUaposis within the fut 30 clays? Y N(..accept ap to lis w....) .
Ifyes. have you ever bid suqay for. Upper EDnadty Dilerd.r? Y N
Ifyes. would you be able to obtain a DOte fiom your doctorstatiDa this or \VOuid bel_ be able to fill out a short form witha couple ofquesdoas about your dilposis? Y N
4) Do you have lDy sipificant medical, physical. or emotional problems.such as diabetes, ulcer, thyroid problems, 1Ithritis, alcoholism, depression,~~ Y N
Ifyes. wbat? _
when 1 _
What kiDcl ofmedieatioas wire you prescribed?
5) Ale you tlkjnllDY mccIicatioas c:uneady?IfYES, wbat _
6) Do you have .yother coacIitioD that miabt be affecdDa your cunent health status?Y N .
Do you have my questioas?
An'ER THE MEDICAL SCRDN:
OK. SECOND, let me briefly explain die main compoaen1S ortbe study. One, at your visit, youwiD be liven a questioDlllire to 811 out that wiD ask you some questions about such1binpasyour work. medical history, lid your paiD. or symptoms. You will have your beiabt IDd weiabt1IItISured, alOlll with what _ CIll. piDcblpip test of,our bad. stnaadL Afterwad. you will be.veIlduee copia ofa briefquestioaaIiIe to like bame IDd mail bIck 1, 2.111d 3IIlOIltbs afteryour visit. That's it. AAy questioas It this point?
What wouIcl be a aaod time for you to come" do the questioDlllire?
APPI1IDIJ: I
UPPER EXTREMITY SCREEN
61
NAME: -------------DATE: ---------------
SOCIAL SECURITY NUMBER: -------------STREET ADDRESS: ---------------
CITY, STATE. ZIP: -------------WDRKADDRESS: _
CITY, STATE. ZIP: -----------------HOME PHONE: ---------------WORK PHONE: _
HEIGHT: _
WEIGHT: _
PINCH: _
GRIP: _
62
DI: _
L DlMDGMfIIICI
tl All: \'4IIII ..,..dIIIof,*,,'(~ _
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..... n.... no ................ Donat ..... 1DO••) ..... inclined to ........... bird•......... an Illy".................'wIIfch
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88
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THANK YOU.., for_p a .
APPIIIDIX C
IDI: _
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_ of...., work iniUIY. r......jaIII.
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_1....... IIid..or br'" til..,.. iniUIY.
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MEDICAL:
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PSYCHOLOGICAL:
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.) eua .....,oI you onWllkor V. ..
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11) Didn1 do WDIkor" V. No
at During..".,....... towlllt ,...php.........or................ i ......wIh your ................... tImiIy. tiIndI or '
QuIll ....
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9711
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_) .......cIIIicuIIIIa aM piling up • tMt •C8IIftOI ..............tMm. , I 3 •, I 3 .. _... ...- OlIn ............. -- GIIIft .......
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o NaIti......0.1 v.r..,..,1 very..,2 &ely3 Mad••IIIy""" ...........5 HInI
•'7 v.,....••10 \I!!y•.,.....
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