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SLEEP AND MUSCULOSKELETAL PAIN IN WORKERS

FOLLOWING A SOFT TISSUE INJURY

Angela Cesta

A thesis submitted in conformity with the requirements for the degree of Masters of Science,

Graduate Department of Community Health, University of Toronto

O Copyright by Angela Cesta, 1998

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SIeep and Musculoskeletal Pain in Woskers Following a Soft Tissue Injury

Masters of Science, 1998 Angela Cesta

Graduate Department of Community Health University of Toronto

ABSTRACT

In a longitudinal prospective study of 1 5 males ( mean age =36.7 yrs, s.d.= 9.3) with low

back pain (LBP), sleq, and symptoms were assessed at 6,10, 15, and 19 weeks following a work-

related injury. They were compared to 9 "pain-fieee, age and gender comparable controls. At

each session, subjects wore an actigraph and completed the Hospital Anxiety Scale, the Beck

Depression Inventory, the University of Toronto Sleep Assessment QuestionnaireQ, the Roland

Scale, and the Chronic Pain Grade.

Compared to controls, workers with LBP showed greater anxiety (Hospital Anxiety Scale

p = 0.02), depression (Beck Depression Inventory p = 0.03 and Somatic subscale of Beck

Depression Inventory p 4 0.01), and self-reported sleep disturbances (Sleep Assessment

Questionnaire p < 0.01 and non-restorative subscale of Sleep Assessment Questionnaire p c

0.01). Compared to controls, LBP subjects expenenced Ionger awakenings @ = 0.02) and slept

38 minutes less once they retumed to work (p = 0.01).

ACKNOWLEDGEMENTS

I would like to thank my supervisor, Dr. John Frank, for his expertise and guidance, and

for his patience and support. I am extremely grateful to Sheilah Hogg-Johnson for her statistical

knowledge and for her availability and willingness to share this knowledge. Special thanks to

Dr. Harvey Moldofsb and Dr. Claire Bombardier for their time and wisdom. 1 appreciate the

dedicated work of Franklin Lue and Valarie Gil whose insight and professionalism allowed the

data collection for this project to run smoothly. 1 would especially like to thank my family for

their endless support and Chris Sammut for his dedication and understanding.

This research was supported by a grant fkom the uistitute for Work and Health.

TABLE OF CONTENTS

INTRODUCTION ............. ..... .........................

.................... .....................---..................................................*.......*. LITERATURE REVIEW ... 11 HUMAN SLEEP ................................................................................................................ 11

............................................................................................................. NORMAL SLEEP -11 .......................................................................................................... SLEEP AND PAIN -13

STUDY ............ .......................*....... OBJECTIVES ..

........................................................................................................................ METHODOLOGY -24 ............................................................................................................................. DESIGN 24

....................................................................................................................... SUBJECTS - 2 5 ................................................................................................ PROCEDURES ............ .... 27 ............................................................................................... MEASUREMENT TOOLS 27

................................................................... SLEEP ASSESSMENT ............. ,.... 27 .............................. Oxford Medilog System ..., ............................... -27

................................................................................... Actigraph .......... ... 29 ........................................................................................ Sleep Symptoms -32

................................................................................................. ROLAND SCALE 33 CHRONIC PAIN G W E ..................................................................................... 33 HOSPITAL ANXIETY SCALE AND BECK DEPRESSION INVENTORY ..... 34 RETURN TO WORK ............................................................................................ 35

ANALYSIS ................................................................................................................................. 36

RESULTS ...................................................................................................................................... 38

DISCUSSION ................................................................................................................................. 70

STRENGTHS AND WEAKNESSES ........................................................................................... 78

RECOMMENDATIONS FOR FUTURE STUDIES ..................................................................... 81

APPENDICES ....................................................... ., ...................................................................... 83

BIBLIOGRAPHY ......................................................................................................................... 1

LIST OF FIGURES

Number and Title Page Number

...... ...............................*........... 1 . Percent of cases aot returned to work at each study session .. 39

. .................................................................. 2 . Box Plots of Roland Score for Cases vs Controls 43

. ........................ .......................... 3 - Box Plots of Pain Intensity Score for Cases vs Controls .. 44

. .............................................*.... 4 - Box Plots of Hospital Anxiety Score for Cases vs Controls 45

5 - Box Plots of Beck Depression Inventory Score for Cases vs . Controls .................................. 47

6 - Box Plots of scores for Somatic Score of Beck Depression Inventory

for Cases vs . Controls ................ ... .................................................................................. 49

7 - Box Plots of Sleep Assessment Questionnaire Score for Cases vs . ControIs ........... .. ........ 51

8 - Box Plots of Non-Restorative Score of the Sleep Assessment Questionnaire

for Cases vs . Controls ........................................................................................................ 53

............................................................ . 9 - Box Plcts of Activity Value for Cases vs Controls -54

. ................................................... 10 - Box Plots of Awakenings per Hour for Cases vs Controls 56

. .....................................................* 11 - Box Plots of Awakening Minutes for Cases vs Controls 58

12 - Box Plots of Sleep Minutes for Cases vs . Controls ............................................................... 60

. ........................................................... 13 - Box Plots of Sleep Efficiency for Cases vs Controls 61

24A - Box Plots of Roland Score for Cases NRTW vs . Cases RTW ............................................. 63

14B - Graph of Roland Score for Cases NRTW (No) vs . Cases RTW (Yes),

..................................................................... with upper and lower 95% confidence limits 64

15A - Box Plots of Pain Intensiw for Cases NRTW vs . Cases RTW ............................................ 66

15B - Graph of Pain Intensity Score for Cases NRTW (No) vs . Cases RTW (Yes), . . ..................................................................... with upper and lower 95% confidence lunits 67

LIST OF TABLES

Number and Title Page Number . .

1 . S w staûstics for Weeks Post-Injury by session ......................................................................................... 39

2 . Siimm;zry statistics for Roland Score for Cases vs . Controls ................................................................................ 42

. .............................................................. 3 - Sirmm;iry statistics for Pain Iutensity Score (PI) for Cases vs Controis 44

4A - Summary statistics for Hospital Anxiety Score for Cases vs . Controls .............................................................. 45

4B - GEE models with Hospital Anxiety Score (HM) as their outcorne measure .........................~........................ 46

5A - Summary statistics for Beck Depression Inventory Score for Cases vs . Controls .............................................. 47

5B - GEE models with Beck Depression Inventory Score @DI) as their outcome measure ...................................... 48

6A - Summary statistics for Somatic Score of Beck Depression Inventory

. .........................................................................................................................**........ for Cases vs Controls 49

6B - GEE models with Somatic Score of Beck Depression Inventory (SBDI)as their

outcome measure ........................................................................................................................................... 50

7A - Summary statistics for Sleep Assessrnent Questionnaire Score (SAQ) for Cases vs . Controls .......................... 51

............................ 7B - GEE models with Sleep Assessment Questionnaire Score (SAQ) as their outcome measure 5 2

8A - Summary statistics for Non-Restorative Score of the Sleep Assessment Questionnaire

for Cases vs . Controls .................................................................................................................................... 52

8B - GEE models with Non-Restorative Score of the Sleep Assessment Questionnaire (NRSAQ)

............................................................................................................................... as their outcome measure 53

............................................................................ 9A - Summary statistics for Activity Value for Cases vs- Controls 54

..................................................................... 9B - GEE models with Activity Value (AV) as their outcome rneasure 55

10A - Summary statistics for Awakenings per Hour for Cases vs . Controls ............................................................... 56

...................................................... 1 OB - GEE rnodels with Awakenings per Hour (AH) as their outcorne measure 3 7

. .................................................................. 1 1A - Summary statistics for Awakening Minutes for Cases vs Controls 57

.......................................................... 1 1B - GEE rnodeIs with Awakening Minutes (AM) as their outcome measure 59

12A - Summaxy statistics for Sleep Minutes for Cases vs . Controis ............................................................................ 60

12B - GEE rnodels with Sleep Minutes (SM) as their outcome measure .............................. ... .................................... 60

13A - Summary statistics for Sleep Efficiency for Cases vs . Controls ........................................................................ 61

13B - GEE models with Sleep Eficiency (SE) as their outcome measure .................................................................. 62

14A - Summary statistics fox Roland Score for Cases NRTW vs . Cases RTW ................... .. .................................... 63

14B - GEE model with Return to Work as the outcome measure for Cases NRTW vs . Cases RTW,

with Roland Score as a covariate ................................................................................................................... 65

15A - Siimmary statistics for Pain Intensity (PI) for Cases NRTW vs . Cases RTW ................. .. .............. ............... 65

15B - GEE model with Retum to Work as the outcome rneasure for Cases NRTW vs . Cases RTW,

with Pain Intensity Score as a covariate ................. ... .................................................................................... 67

LIST OF APPENDICES

Number and Title Page Number

..................................................................................... 1) Demographic Profile Fax Sheet 84

................................................................................. 2) Consent for Participation in Shidy 85

........................................................ 3) University of Toronto Research Ethics Approval -87

........................ ........... 4) Algorithm used for Automatic Sleep Scoring (Actigraph) ... 88

.................................................................................... 5 ) Actigraph Activity Sample Data 89

6) Return to Work Questio~aire ..................................................................................... 90

LIST OF ABBREVIATIONS USED

ACR

AH

AHCPR

AM

AV

BDI

CBI

CCP

CLBP

CPG

EEG

EOG

GEE

HAS

ICC

LBP

Ml

M2

M3

NREM

NRSAQ

NRTW

PI

PSG

RA

Arnerican College of Rheumatology

mean awakenings per hour fiom Actigraph

US. Agency for Health Care Policy and Research

mean awakening minutes from Actigraph

mean activity value fiom Actigraph

Beck Depression Inventory

Canadian Back Institute (Brampton, Ontario)

Community Ch ic Programme (at the CBI)

chronic low back pain

Chronic Pain Grade

electroencephalograph

electro-occulogram

generalized estirnating equation

Hospital Anxiety Scale

intra-class correlation coefficent

Iow back pain

GEE model I

GEE model 2

GEE model 3

non-rapid eye movement

non-restorative sleep factor of the SAQ

not returned to work

Pain Intensity

poly somnography

rheumatoid arthritis

REM

RS

RTW

SI

S2

S3

S4

S AQ

SBDI

SE

SM

rapid eye movement

Roland ScaIe

returned to work

Session l(3-8 weeks post-injury)

Session 2 (4*2 weeks after Session 1)

Session 3 (4*2 weeks after Session 2)

Session 4 (4*2 weeks after Session 3)

University of Toronto Sleep Assessrnent QuestionnaireQ

somatic component of the BDI

mean sleep efficiency

mean sleep minutes fiom Actigraph

INTRODUCTION

The significant disability and impairment, as well as the growing economic costs resulting

fiom musculoskeletal disorders, have directed a vast body of research into the etiology, treatment,

prognosis and risk factors, for chronicity of these disorders.

Low back pain (LBP) is the most common rnusculoskeletal cornplaint in the young adult

population (Gallagher, 1989), and is the second most fkequent reason for consuking a physician

(second to respiratory illnesses) (Deyo, 1992). The lifetime prevaience of low back pain has been

reported to range fiom 60% to 80% (Frymoyer, 1992). The major@ of these cases will resolve

within 15-45 days and are responsible for a smaii pomon of the total costs incurred by this disorder.

Five to ten percent of patients, whose LBP becomes chronic or disabling, i.e. continuhg for months,

account for 70-90% of the total costs (Frymoyer, 1992, Abenhaim, 1987). At present there are no

specific physiological findings that can account for the majority of LBP cases and they are therefore

considered "idiopathic" (Kelsey, 1988).

The U.S. Agency for Health Care Policy and Research (AHCPR) has recently recommended

clinical practice guidelines for the treatment of acute low back problems (of less than three months

duration). They suggest that the patient should initially be assessed for any "red flags7', i.e.

"indicators of potentially senous spinal pathology or other nonspinal pathology". If there is no

evidence of senous pathology, they do not recommend M e r testing nor any intensive treatment

for the first four weeks (U.S. Dept. Of Health and Human Services, 1994). These suggestions are

based on findings that patients who have been treated with increased bed rest, andor medications

and/or physiotherapy do not necessarily have a better prognosis. Indeed, recent evidence suggests

that aggressive early treatment cm lead to worse outcomes (Malmivaara, 1995). In the absence of

Z

2

serious pathology, the patients should be assured that they are expected to recover. In other words,

since the majority of patients with LBP will recover within the first few weeks, regardless of

treatment, there is no need to over-treat the patient following the initial consultation. In fact, the

physician may actually do more harm by over-treating the patient, since "ill-conceived diagnostic

behaviour on the physician's part can lead to abnormal illness behaviour in patients, and this, in turn,

may lead to abnomal treatment behaviour" (Nachemson, 1992). During their first visit to a

physician, an explanation of the natural course of LBP may actually be comforting and beneficial

to most patients and may provide them with a positive outlook that may in turn help them to heal

quicker.

Frank describes three stages of uncompiicated occupational LBP beginning with an "acute"

phase lasting for three to four weeks following the onset of symptoms. During this time prognosis

is generalty "good" regardless of the prescribed treatment. The second or "subacute" phase occurs

between three to four weeks and approximately twelve weeks following symptom onset. During this

time, while the majority of LBP patients have returned to work, those who have not returned to work

become "hi& risk" for long km disability. Phase tbree begins at three months following symptom

onset. At this time LBP patients who have not retumed to work are believed to be experiencing early

"chronic pain syndrome" and as a result are likely to remain on disability for long periods of time

(Frank, 1 996).

If we, as a society, are willing to accept the AHCPR guidelines, it seems likely that we could

significantly reduce the economic burden of acute LBP. As noted earlier, however, it is the 5-10%

of patients who will become disabled for more than three months who account for 70-90% of the

total costs. Perhaps then, we should focus on trying to better understand the development of chronic

3

low back pain (CLBP). The important questions then become, how can we identiQ those patients

with LBP who will go on to become chronic and/or disabled and, once they are identified, can early

treatment prevent chronicity? This type of prevention strategy is referred to as secondary

prevention, Le. atternpting to maximize recovery once LBP has occurred (Frymoyer, 1992).

Cats-Baril and Frymoyer found job characteristics (e.g. job satisfaction, work history, work

status), perception of fault, compensation for injury, past hospitalization, and education level, but

not psychological factors, to be predictive of chronic disability. Chronic disability was dehed as

not having returned to work after six months (Cats-Baril, 1991). Crook considered the effects of

gender, age, and r e m to work attempts, on the duration of work-absence following a

musculoskeletal injury in a cohort of patients already off work for three months. She f o n d that

compared to males, females were less likely to retum to work, compared to younger workers, older

workers were less likely to retum to work, and efforts to return to work early decreased "'overall"

work disability (Crook, 1994). Coste evaluated prognostic factors in an inception cohort of 103

patients with "acute localized non-specific back pain lasting less than 72 hours". The factors they

found to delay recovery were; previous chronic episode of LBP, pain worse on standing or lying,

compensation status, employment status, and disability at entry. The same variables, in addition to

male sex and job satisfaction, were found to be predictive of increased lost work tirne (Coste, 1994).

Other predictive variables that have been found to be important determinants of chronicity include;

the patient's understanding O fhis/her medical condition (Lacroix, 1 WO), anxiety, activity level, local

versus widespread pain (Murphy, 1 984), pain intensity at initial visit (Singer, 1 987), diagnosis (pain

or sprain versus intervertebral disc disorder), the number of post-injury days which have passed

prior to initiating treatment, measured spinal flexion at baseline, neurological symptoms, industry

(emp 10 yment of public versus private), emplo yment history (riifante-Rivard, 1 9 96) and

"psychological and social variables" (Gallagher, 1 989).

Many researchers have attempted to identify predictive models for chronic low back pain

(CLBP) but the findings have been inconsistent. The discrepancies may be partly due to:

1) Study Design: One major methodological problem with these studies is that the

majonty of them have been retrospective in nature. The subjects who are being

examined have been disabled for some time pnor to their study assessment. Hence,

it is possible that many of the charactenstic features of these patients are not the

cause of the chronicity but rather the result of their disability. "At a simplistic level,

it c m be argued that any of us would be depressed, anxious, focused on bodily

symptoms (somatizing), physically unfit, and incapable of rehuning to work if we

had LBP for which no diagnosis could be given, no treatment was effective, and for

which emplo yers were unsympathetic toward allowing return to work." (Frymo yer,

1987). Only through well-designed prospective studies can we determine cause and

effect.

2) Definition of Outcome(s): Some studies consider the relationship of the variables

under investigation with return to work status. As pointed out by Von Korff(1994),

having retumed to work does not necessxily imply that the patient is pain-free.

Many patients may return to work for O ther reasons, such as having no other source

of income. Another outcome mesure which is often considered is pain intensity.

Many scales and questionnaires are available for this purpose. However, not al1 of

these have been validated in LBP patients. Perhaps the best method to evaluate

prognostic factors is to use a combination of outcomes i.e. days off work attributed

to LBP, as well as validated pain and function measures.

3) Subject Recruitrnent: While some studies have examined LBP patients referred

fkom a primary care physician's office, O thers have recruited volunteers fkom tertiary

care back pain clinics. Although it is important to examine LBP patients fiom a

variety of settings, inconsistency in the selection process is Likely responsible for

some of the discrepancies amongst the predictive factors reported by researchers.

Other important considerations when reviewing subject selection are; inclusion and

exclusion criteria (e-g. are patients with previous reports of LBP included?), the

amount of tirne that has passed between the injury and the k s t assessrnent of

variables (e.g. are subjects being evaluated at two weeks or ten weeks post injury?),

and the type of treatment that has been prescribed to the patient (e.g. have the

patients been advised of bed rest or exercise?, are they taking any medications?).

4) Analytic Methods: While al1 the better studies employ muhivariate statistical

methods for the adjustrnent of confounding variable effects, these methods vary

widely and some (e.g. discriminant analysis, logistic regression) are not ideal for

longitudinal data (Haidar, 1 997).

5) Unidentified Factors: It is possible that the inconsistent findings fkom these

prognostic studies result fiom failure to measure and control for some unidentified,

yet important, variable(s) that influence the factors being measured. For example,

sleep rnay play an important role in the healing process, and disturbed sleep may

significantly modiQ other factors (e-g. activity level, pain threshold, depression)

under investigation. Furthemore, individuals rnay have different baseline tendencies

to have their sleep disturbed by the initial expenence of back pain.

A different approach towards a better understanding of CLBP would be to consider other

chronic musculoskeletal disorders and to identiQ common characteristics amongst them. As

suggested by Goldenberg, since most such chronic conditions share many common features but are

poorly understood, it rnay be beneficial to study these disorders in a "similar pathophysiologic

fashion so that valid cornparisons can be made between the various chronic musculoskeIeta1

disorders" (Goldenberg, 1987). A chronic musculoskeletal disorder that has been receiving

increasing research attention is fibromyalgia.

6

Fibromyalgia is a chronic pain disorder characterized by diffuse or widespread

rnusculoskeletal aching and soreness accompanied b y cornplaints of fatigue, morning sti fiess, and

poor sleep (Boissevain, 1991). Important to the diagnosis of fibromyalgia is the presence of very

specific anatomical tender points. Some of the other more common symptoms expenenced by

fibromyalgia patients are; 'kaking tired and unrefieshed", anxiety, irritable bowel syndrome (Wolfe,

1 WO), skin sensitivity, generalized andor persistent pain, moming stifThess, and back pain (de

Girolarno, 1991).

Epidemiological data suggest that fibromyalgia is quite common, with a prevalence ranging

fiom 3.7% to 20% in rheumatology clinics, 5.7% in generai medical practices and 9% in other

primary care settings (Boissevain, 199 1). It is more prevalent in women, with reports of 73% to 83%

of fibrornyalgia patients being female (Boissevain, 199 1). Although the age of symptom onset has

been found to range fkom age 9 to 55 y e m (McCain, 1988), the age of presentation has been

reported to range fiom 34 to 53 years (Boissevain, 1991).

In 1990, The Amencan College of Rheurnatology (ACR) put forth the most recent (1990)

critena for the classification of fibromyalgia, with one of its main objectives being to provide a

consensus definition of the disorder. According to these criteria, a diagnosis of fibromyalgia is made

if the patient has been expenencing widespread pain for at least three months as weIl as tendemess

at 1 1 or more of the 18 specific tender point sites. The combination of these two critena have been

shown to have a sensitivity of 88.4% and a specificity of 81.1%, as measured against the

investigators "usual method of diagnosis". Although sleep disturbances, fatigue and stifniess were

recognized as 'central symptoms' of fibromyalgia, their presence was not made necessary for

diagnosis as these symptoms do not exist in all patients with fibromyalgia (Wolfe, 1990). These

7

diagnostic criteria were also proposed to allow fibromyalgia research to be more standardized and

methodologically sound, which in turn would provide more comparable data and perhaps more

consistent hdings.

As may be noted koom the above criteria, there are presently no laboratory tests that can aid

in diagnosing fibromyalgia. In fact the presence of tender points is the most objective fïnding of this

syndrome. Research into possible pathophysiological mechanisrns that May be involved has

included studies looking for abnormalities in muscle tissue, neuroendocrinology, and the immune

system. Since there are no presently discemible physiological abnomalities in fibromyalgia

patients, many question whether such a disorder achially exists. Bennett responds to this skepticism

by stating, 'There are lessons to be learned fÏom the fibrositis/fibromyalgia saga. Not least is

granting patients credibility when symptoms and signs do not conform to contemporary rnedical

prejudices. Willfùl fabrication of symptoms and outright malingering are distinctly uncornmon, yet

the straightjacket of current medical thought sometimes leads to such considerations" (Bennett,

1987). Complicating the controversy of whether or not fibromyalgia exists, is the belief, by some

researchers, that fibromyalgia is a form of, or is associated to psychopathology. For example,

Hudson suggests that because high rates of psychiatric symptoms and disorders have been reported

in fibromyalgia patients and their families; and because many fibromyalgia patients have been shown

to respond to antidepressant medication, then it is possible that fibromyalgia patients are actually

expressing their psychological distress as somatic cornplaints (Hudson, 1989). More recently, Aaron

has compared psychopathology in fibromyalgia patients, fibromyalgia non-patients (i.e. community

residents with fibromyalgia who have not sought any medical help for pain within the last 10 years)

and healthy controls. Aaron concludes that "psychiatric disorders are not intrinsically related to the

8

fibromyalgia ~yndrome"~, but they likely play an important role in the patients' decision to seek

medical care (Aaron, 1996).

The exact cause of fibromyalgia is m o w n . Approxirnately 60% ofpatients cannot identiQ

any event as the cause of their condition. Some precipitating events that have been reported are

trauma and infection. According to Bengtsson, the omet of fibromyalgia is sudden in about one-

third of patients and "initially may be localized". He found that in 87% of fibromyalgia patients,

symptoms are initially localized, and that 55% of the patients reported back pain prior to the

syrnptoms of fibromyalgia (Bengtsson, 1986). Wolfe found 22% of patients reported the occurrence

of a traumatic event prior to the onset of fibromyalgia and he believes that, "Most often the

syndrome follows an 'event' which may be a fall, back strain, or whiplash-like auto injury. Pain is

noted locally in the neck and shoulder region but is soon noted in the am, with subsequent spread

to the contra-lateral side and then generally throughout the body" (Wolfe, 1990).

Some of the methodological problems apparent in studies of CLBP are also important to

consider in studies of fibromyalgia. Again, because of the lack of objective findings, case definitions

of fibromyalgia may Vary, thereb y resulting in heterogeneous subj ect groups across studies. Also

important to consider is the fact that the majority of patients with fibromyalgia are not diagnosed

until years after onset of the disorder; thus, ail studies to date are retrospective in design.

It should be evident fiom the descriptions of fibromyalgia and LBP that these two chronic

conditions share many common features. Some of the similarities are:

1. The majority of LBP diagnoses are made in the absence of any abnormal

laboratory or imaging findings, as is the case with a diagnosis of fibromyalgia i.e.

there are no measurable pathophysiological grounds for the diagnosis of either of

these disorders, and they are broady considered bbsoft tissue disorders" as a diagnosis

of exclusion.

2. Since few consistent objective findings c m be attrïbuted to LBP and to

fibromyalgia, many believe these disorders to be primarily somatization disorders.

However, shidies lookuig at the psychological stahis of fibromyalgia and LBP

patients have not shown consistent findings.

3. Although the existence of tender points is usefbi in diagnosing fibromyalgia, they

are not specific to this group of patients. For example, tender points can also be

found in patients with myofacial pain. Abnormal X-ray hdings are sometimes used

to diagnose LBP, but these too are not specific to this group of patients, since similar

findings c m be seen in persons without any LBP cornplaints (Frank, 1997).

4. One of the main concerns with respect to both LBP and fibromyalgia is their

socioeconomic impact. Cathey et al. found that fibromyalgia patients made

approximately the same number of doctors' visits as did patients with LBP (Cathey,

1986).

The pain experienced by LBP patients is described as more localized, whereas fibromyalgia

patients cornplain of difise pain. However, this difference in pain perception may reflect different

stages of evolution for soft tissue disorders. As reported by Bengtsson (1986) and Wolfe (1990),

symptoms in many fibromyalgia patients are initially localized. It is therefore likely that some

patients with LBP will go on to develop fibromyalgia. Consequently, it would be interesting to

investigate some of the changes that occur in patients with LBP as they either recover or continue

to experience chronic pain. Such a prospective study would allow insight not only into the

development of chronic LBP, but may also have implications for chronic musculoskeletal disorders

in general.

Whiie the etiology of fibromyalgia is unknown, it has been suggested that disturbed sleep

10

rnay play an important role in its development, and that poor sleep may be responsible for the

decreased pain threshold experienced by these patients. More than 75% of fibromyalgia patients

cornplain of sleep disturbances, fatigue or stiffhess and the most fkequently reported symptom is

"'waking tired and mefieshed", reported by 90% of fibromyalgia patients (Wolfe, 1990). For this

reason many studies have attempted to identify whether any diagnosable sleep disorders or any

specific features of sleep in fibromyalgia patients could account for the increased prevalence of

disturbed sleep amongst them. There is evidence to suggest that sleep complaints are also quite

prevalent in LBP patients but few studies have considered sleep complaints and sleep physiology

in this group of patients. Compared to LBP subjects who had returned to work, LBP subjects who

failed to return to work at 21 months post-injury were reported to show "increase in sleep

complaints, fatigue, pain behaviour, nurnber of painful sites, and emotional distress (Crook, 1994).

The existing research into sleep in patients with chronic musculoskeletal disorders will be discussed

in the literature review that follows.

LITERATURE REVIEW

HUMAN SLEEP

The study of sleep behaviour and physiology has made much progress within the last century,

however the biological purpose of sleep remains a mystery. Although many theories have been

proposed, the rnajority of research in this area considers sleep to be either a period of energy

conservation or a time for body restoration. Webb believes that conserving energy through sleep

penods is an adaptive behaviour whose evolution in the different species is related to their food

supply and to predatory pressures (Webb, 1974). The restorative theory proposes that sleep is

required for growth and tissue restoration (Oswald, 1980). This recovery role of sleep is supported

by studies of protein synthesis and peak rates of ceii division during sleep (Adam and Oswald,

1983).

NORMAL SLEEP

Human sleep stages are assessed by the continuous monitoring of three sorts of electrical

signals fiorn the body: electroencephalographic (EEG), electro-occulogram (EOG), and submental

electromyogram (EMG). Standard electrode placement allows the identification of wakefulness, non

rapid-eye movement (NREM) sleep (sleep stages 1, II, III, and IV), and rapid-eye movement (REM)

sleep. Sleep recordings are typically staged using 30 second epochs or time intervals. The following

summary provides a definition of the various sleep stages based on EEG, EOG and EMG activity

(Rechtschaffen and Kales, 1968).

SLEEP EEG ACTIVITY STAGE

Wakefûhess Low voltage, mixed frequency waves, mostly alpha waves (fiequency of 8-12 cycles per second (cps) 1

Stage 1 Low voltage mixed fiequency activity (mainly in the 2-7 cps range), occasional sharp vertex waves, a decrease in alpha waves.

Stage II The presence of spindle activity (12- 14 cps) and K-complexes (a wave form with a negative component followed by a positive component).

Stage III EEG activity contains 20 to 50% delta waves (waves of 2 cps or slower and amplitudes of 75 mV or greater).

Stage IV EEG activity contains greater than 50% delta waves.

REM Low voltage, mixed fiequency waves and saw tooth waves may appear.

EOG ACTIVITY EMG ACTMTY

Rapid eye Submental muscle tone movements or is at its highest level. blinking movements.

Slow rolling eye EMG Ievels are typically movements. below those seen during

wakefulness

Slow rolling eye EMG levels are sirnilar movements. to those observed during

stage 1.

Slow rolling eye Similar to that seen in movements. stages I and II.

Slow roIling eye Similar to Ievels seen in movements. stages 1, II, and III.

Biphasic rapid eye Low amplitude EMG movements. i.e. submental EMG

recording should be at its lowest level.

13

A normal sleep cycle begins with stage 1 sleep which lasts fkom one to seven minutes. It is

followed by stage II sleep for 10 to 25 minutes and then the first cycle of stage III sleep which is

only a few minutes in duration. Next, stage IV appears for approximately 20 to 40 minutes. There

may be a short episode of stage III sleep followed by a few minutes of stage II sleep before REM

onset. The f is t REM period is shoa lasting approximately one to five minutes. REMDIREM cycles

range fiom 90 to 1 10 minutes throughout the night, with slow wave sleep (consishg of stages III

and IV) occupying more time in the early part of sleep and REM sleep episodes becoming longer

across the night. Normal sleep consists of approximately 5% stage 1, 55% stage II, 5% stage III,

1045% stage IV, and 20-25% REM sleep. The actual amount of total sleep time occupied by each

stage varies with age and gender (Williams, 1974).

Some of the important indices or sleep parameters that are commonly used to evaluate sleep

quantity and quality for both clinical and research purposes are: sleep latency or onset (i.e. the time

fkom the beginning of the sleep study to the first epoch of sleep), total sleep time (i-e. the amount

of time fiom sleep onset to the end of the 1 s t sleep period, excluding al1 intermittent wakefulness),

sleep efficiency (i.e. the proportion of time actually slept during a sleep period, it is calculated by

dividing total sleep time by the arnount of time the person was in bed), number of awakenings (i.e.

the number of times one or more epochs is staged as awake during the sleep period), and number of

arousals (Le. the number of awakenings lasting less than half an epoch).

SLEEP AND PAIN

In 1 975, Moldo fsky reported on the alpha electroencephalographic (EEG) non-rapid eye

movement (NREM) sleep anomaly in a group of fibromyalgia patients. The alpha rhythm cm

14

typically be seen during quiet wakefulness in the EEG recordings of the posterior scalp region.

During sleep, alpha becomes more prominent in EEG recordings of the central and prefiontal regions

of the scalp. Alpha EEG has a fiequency of 8 to 12 Hz. and can be found superimposed on regular

sleep patterns (Le. stages 1, II, III, and IV sleep). Moldofsky found this alpha activity to be more

common in a group of fibromyalgia patients compared to age- and gender- matched controls. They

hypothesized that the deprivation of stage IV sleep in healthy subjects would be associated with

musculoskeletal and mood symptoms similar to those observed in fibromyalgia patients. Volunteers

slept in the laboratory for seven consecutive nights. The first two aights served as acclimatization

to the laboratory and the subjects were allowed to sleep undisturbed. During the following three

nights auditory stimuli were presented whenever a subject's EEG recording showed four delta waves

within a 40 second epoch. The auditory stimulation persisted until a movement arousal or a shifi

to stage I or stage II sleep was apparent fkom the subject's EEG recording. During these three nights

of stage N sleep depnvation, the volunteers were found to show increased tendemess (as measured

by dolorimeter scores) and they reported an increase in musculoskeletal symptoms and mood

disturbances. Volunteers were then allowed to sleep in the laboratory for two more nights without

any disruption to their sleep. Following these two nights of undisturbed delta sleep, the subjects'

dolorimeter scores decreased as did their symptoms. The results of this study suggest that while pain

may cause sleep dishirbances it is very likely that disturbed sleep and "the subsequent fatigue,

irritability, depression, anxiety, and musculoskeletal aching and stiflkess [would] become

incorporated in a vicious, self-perpetuating, nonrestorative sleep cycle. Successful treatment of the

clinical disorder might thus lie in the direction of improved sleep physiology" (Moldofsa 1975).

The relationship between alpha activity, slow wave sleep and pain and mood symptoms has

15

also been investigated through the use of pharmacological agents. In fibromyalgic patients,

chlorpromazine has been associated with decreased alpha-EEG sleep, increased slow wave sleep and

improvements in pain and mood symptoms (Moldo f sb , 1 980).

Fibromyalgics have been found to have, on average, 60% of their NREM sleep occupied by

alpha activity, while the NREM sleep of normal subjects and patients with chronic insomnia or

dysthymia has shown approxirnately 25% alpha activity (Gupta, 1986, and Saskin, 1986). This

alpha-EEG anomaly has been interpreted as "evidence for an arousal disorder within sleep and as

a biological indicator of nonrestorative sleep" (Moldofsky, 1989).

Anch et al. postulated that since fibromyalgia patients are believed to be more sensitive to

both physiological and psychological bodily states, they should then show a higher level of arousal

during sleep, compared to a control group. Fibromyalgia patients should have more disturbances

in their sleep continuity and more alpha-EEG during sleep. Subjects slept in the sleep clinic for three

nights. Polysomnographic recordings of EEG, EOG, EMG, and right and iefi anterior tibialis

(RATLAT) were collected. The subjects had a micro-switch taped to one hand and were asked to

press the button every time they believed they had awakened fiom sleep. Anch found more alpha-

EEG in the sleep of fibromyalgia patients compared to controls, and although there was no

significant difference in the number of button presses between the two groups, the fibrornyalgia

patients had greater recall for these events thus suggesting that these patients may have a 'heightened

self-awareness' during sleep (Anch, 199 1).

More recently, Branco et al. reported similar findings when they examined alpha and delta

activity in fibromyalgics. They studied sleep physiology in ten fibromyalgia patients (nine females,

one male, with a mean age of 48 years) and compared it to the sleep physiology of fourteen controls

16

(ten fernales, four males, with a mean age of 29). They found that in cornparison to controls the

fibromyalgics showed a decreased percentage of slow wave and REM sleep throughout the night,

and increased alpha activity during sleep (Branco, 1994).

Since the initial discovery of the alpha EEG non-REM sleep anomaly in fibromyalgia patients,

many investigators have reported similar hdings. Some researchers have not been able to

demonstrate any relationship between alpha-EEG and fibromyalgia (Nielson, 1994, Leventhal,

1992). However, it should be noted that such discrepancies or inconsistencies in results may be due

to the lack of objective diagnostic criteria available for the classification of fibrornyalgia, and to the

different techniques used by various sleep clinics for recording and quant iwg alpha-EEG. At

present, the alpha EEG sleep anomaly c m be thought of as a sensitive indicator for fibromyalgia,

but because it has also been reported in 36 of 240 healthy subjects (Scheuler, 1983), it is not specific

to patients with this syndrome.

Another group of musculoskeletal distress patients whose sleep has been assessed are those

with rheumatoid arthritis (RA). These patients experience moming stiffhess and pain similar to

those described by fibromyalgia patients. Moldofsky therefore hypothesized that the alpha-EEG

sleep anomaly may play a role in the moming pain, weakness and fatigue reported by RA patients.

Fifieen RA patients underwent oveniight polysomnography for eight nights while sleeping in their

hospital beds. The sleep recording of al1 these patients were shown to contain a prominent alpha-

EEG rhythm during NREM sleep (Moldofsb, 1983).

Since depression is a common symptom in chronic pain patients and, because sleep

disturbances have been found in depressed patients, Nicassio and Wallston attempted to clai@ the

relationship between pain, depression, and sleep in a longitudinal study of 242 RA patients. Patients

17

completed questionnaires on two occasions, twelve months apart. Cross-sectional data indicated that

those patients who reported greater arthntic pain also reported a higher degree of sleep disturbance.

RA patients who reported more sleep problems and greater functional impairment were also found

to be more depressed at the current thne. The longitudinal analysis showed that while depression

decreased over t h e for subjects who initially reported low pain and greater sleep disturbances,

subjects who initially reported both greater pain and more sleep problems at the initial assessrnent

were more depressed at follow up 12 months later (Le. the combination of sleep problems and a high

pain level appeared to worsen depression but sleep problems alone did not have the sarne effect).

The authors believe these hdings demonstrate that the ''level of pain substantially altered the

marner in which sleep problems affected depression over tirne". Howevrr, as they point out, the

evidence is based on observational results and a causal relationship cannot be delineated (Nicassio,

1992).

In a study by Lavie, objective sleep measures were compared in RA patients (13 females),

LBP patients (9 fernales), and controls (12 females). Wnst actigraphs (an instrument which uses a

piezoelectric accelerometer to detect movements, in which the movements or activity registered by

the actigraph are analyzed by software capable of deriving sieep/wake measures) were used to

monitor sleep/wake patterns. From the actigraph recording they were able to assess sleep duration,

sleep efficiency, rnean activity level, and "state transitions" (i.e. the nurnber of times the subject

awakened f?om a sleep period). RA patients were shown to have the poorest quality of sleep and to

differ significantly fiom controls with respect to d l four measures (Le., shorter sleep duration,

decreased sleep efficiency, increased activity level during sleep and more state transitions). The

sleep of LBP patients did not differ significantly fkm that of the RA patients, and showed a

significant difference fiom controls only in the number of state transitions (i-e. LBP patients had a

18

greater number of transitions fiom sleep to wake). With respect to the above-mentioned sleep

measures, LBP patients were therefore found to sleep more poorly than controls, but not quite as

poorly as IW patients (Lavie, 1992). A pain measurement would have been usehl in this study.

The level of pain the subjects were experiencing at the time of the study may possibly explain why

the RA patients showed the poorest sleep, the controls had the best sleep and why the sleep of the

LBP patients fell somewhere in between these two groups.

Although sleep cornplaints are common in chronic pain patients, few studies have attempted

to examuie the nature and evolution of these sleep difnculties over time, their contribution to pain,

or their role in the development of chronic pain. The following table summarizes studies which

have attempted to examine the relationship between sleep and pain.

SUMMARY OF SLEEP AND PAIN LITERATURE REVIEW

Favourable Factors of study design: HS = heterogeneous pain subjects with respect to site of pain HI = heterogeneous pain subjects with respect to number of days experiencing pain at initial assessrnent PI = standardized measure of pain intensity PY = psychological measures considered PS = physiological sleep measures recorded MA = multiple assessments over time

Pilowsky 1. (1985)

Atkinson J.H. (1988)

Cross Sectional

Cohort

1) Cohort

II) Cross Sectional

-26 chronic pain with insornnia (cases) referred fiom pain c h i c -1 2 insomnia and psychiatric disorder (IP) -1 6 subjective insornnia with no objective fmdings (SI) - - -- -- - - - - -

-1 00 patients referred to pain clinic

1) -5 I cluonic pain patients fiom pain clinic

11) -7 of the 5 1 patients above compared to "norms"

-1owcst sleep efficiency in IP followed by cases and SI -cases had difficulty in initiating and maintaining sleep while IP had more wakefiilness after final sleep period (Le, time awake in the early moming) -8 cases showed evidence of alpha EEG anomaly in NREM

- 10% reported good sleep -20% reported fair sleep -70% reported poor sleep -poor sleepers reportcd significantly greater intensity of pain and fewer hours of sleep compared to good sleepers -poor sleepers significantly more depressed and showed greater anxiety compared to good sleepers 1) -pain chronicity and depressed mood were strongest predictors of sleep satisfaction -hi@ pain intensity patients reported fewer sleep Iiours and greater difficulty initiating and maintaining sleep compared to low pain intensity patients ii) -most patients showed evidence of sleep impairment Le. periodic leg movernents, absence of slow wave sleep and reduced REM latency

I Haythorn- thwait J.A.

Moffit P.F. (1991)

Staedt J. (1993)

Crook J. (1994)

Pivik R.T. (1 995)

Cohort

,

Cross Sectional

Case Control

Cohort

Cross Sectional

-46 chronic pain patients attending an inpatient rehabilitation programme

- 1765 individuals randomly selected fiom an electoral register

-23 chronic LBP subjects - 10 healthy subjects

-148 individuals with a work related injury and a Workers Compensation Claim

-5 subjects with chronic pain due to low back pain -5 "normal" controls

-patients slept fewer hours and had more difficulty initiating sleep compared to "normative" data -duration of pain was positively associated with increased difficulty falling asleep and decreased quality of sleep -pain severity was related to trouble initiating sleep but not to waking in the rniddle of tlie night nor to early moming awakenings -amie@ and depression were found to be strongly correlated to sleep behaviour -the nurnber of hours slept was found to correlate with depression and anxiety

-pain, anxiety, somatic healtli and annual household income strongly correlated with sleep problems -anxiety, pain and poor somatic health associated with difficulty maintaining sleep -anxiety and pain strongly correlated with difficulty initiating sleep -poor sornatic health and anxiety strongly associated with early morning awakenings

-significantly higher cluster number (Le. 3 or more microarousals, with each miçroarousal occurring 5-1 50 seconds from each other) and cluster disturbed sleep (i.e. clwster duration over the entire total sleep time) in chronic LBP patients compared to controls -no significant difference in the number of movement arousals per minute

. - - - - --

k b j e c r w h o hadnot rcturned to work ai 21 months post-injury were more likely to show an increase in sleep complaints, fatigue and emotional distress compared to subjects who had returned to work -no differences found in sleep stage psrameters -chronic pain patients showed increased alpha activity compared to controls

Sutton D.A. Cross - 1 1924 persons responding (1996) Sectional to the 1991 Canadian

General Social Survey

Drewes A.M. Experi- - 10 healthy subjects (1997) mental

C

-pain was a significant independent predictor of subjectively reported insornnia and unrefreshing sleep

-during muscle pain stimulus, delta (0.5-3.5 Hz) and sigma (12-14 Hz) activities decreased and alpha 1 (8-10 Hz) and beta (14525 Hz) activities increased -during joint pain, delta, theta (3.5-8 Hz) and alpha 1 activity decreased and alpha 2 (10-12 Hz), sigma and beta activity increased -no EEG change obsewed during cutaneous pain

22

It is apparent fkom the findings of these studies that there exists an important but as yet poorly

characterized relationship between musculoskeletal pain, and respectively the development of chronic pain,

sleep, and depression. Ifwe wish to M e r clam this complex relationship, fûture studies should attempt

to (i) identiQ patients with pain as early as possible in the course of their disease process, (ü) follow patients

prospectively in time, (iii) investigate larger sample sizes, (iv) assess more closely the nature of the sleep

cornplaints and disorders (e.g. through measures of sleep physiology), and (v) control for medications

prescribed for depression or chronic pain that may affect sleep.

STUDY OBJECTIVES

The purpose of this thesis was to examine the sleep behaviours and patterns in a group of

workers following a soft tissue injury to their lower back. Subjects attendïng a LBP treatrnent clinic

were identified at three to eight weeks post-injury and were tested repeatedly over a subsequent four

month penod. The prospective design ailowed for an analysis of the relationships between changes

in sleep over time, and the recovery fiom LBP. The outcome of interest was low back pain as

measured by the Chronic Pain Grade and Health Related Quality of Life (i.e. Roland Scale). This

study attempted to answer the following questions:

1. Are indices of sleep qualiiy and quantity, recorded over a six month post-injury

penod, able to differentiate between workers with LBP and age and gender

comparable controls without pain?

2. Are changes in the various repeated rneasures of sleep quantity and quality,

recorded over a six month post-injury period, different in workers with LBP and age

and gender comparable controls without pain?

3. Are the various repeated measures of sleep quantity and quality açsociated with

return to work statu in workers with LBP?

METHODOLOGY

DESIGN

This study had a prospective hybnd design. Repeat sleep measures, collected at the subjects

own home and while sleeping in their own bed, were assessed in an inception C O ~ O ~ of workers with

LBP and compared to a pain-fkee group of control subjects. Cases (i.e. subjects with newly treated

low back pain) were identified at three to eight weeks post injury and were followed for the

following four months. Each subject was studied for nine nights separated into four sessions.

Session 1 (considered the baseline session) consisted of three consecutive study nights and occurred

within three to eight weeks post-injury for cases, but no t h e restriction was irnplemented for

controls (i.e. session 1 occurred once controis had agreed to participate in the study). Session 2 ,3

and 4, each occurred at 4*2 weeks following the preceding session for both cases and controls, and

consisted of two consecutive study nights. It was believed that the identification of cases at

approximately six weeks post-injury would provide us with a combination of workers who had and

had not retunied to work and that the repeat measures over the following four months would alIow

a small percentage of the workers to be defined as having CLBP (Le. LBP lasting greater than three

months duration) by their session 4 evaluation. The key rational for three study nights at session 1

was the need to acclimatize the subjects to the measurement equipment. By collecting two nights

of data at each session we attempted to provide a more accurate representation of the subjects' sleep

patterns (i.e. provide an assessrnent of the night to night variation of sleep in these subjects) as well

as to reduce the amount of substandard measures at any one session due to artifacts and equipment

failure-

participate in the study while they were attending the Canadian Back Institute (CBI) for treatment

of their LBP. Fourteen cases were recruited fiom the CBI in Brampton and one case was recruited

fiom the CBI in Scarborough. Ail cases were required to be males, English-speaking and -writing,

between the ages of 18 and 50, with a low back injury attributed to work, and a Workers

Compensation Board (WCB) claimant attending the Community C h i c Programme (CCP) at CBI.

The Community C h i c Programme is sponsored by the WCB and was available to injured workers

at any time up to ten weeks following their injury, for a maximum of 30 treatment days. During the

course of the programme, clients are exposed to education regardhg their condition, various pain

control strategies, active stretching and positioning, and, where applicable, treatment with ice and

heat. By the end of the programme clients participate, to a varying degree, in a work

conditioning/simulation of their pre-accident activities of daily living, including work.

During the first year of recruitment the therapists at the Brampton CBI agreed to complete

a Demographic Profile Sheet (Appendix 1) for al1 CCP clients attending the clinic and to fax the

completed foms to the study coordinator. The Demographic Profile Sheet allowed us to be in

contact with the clinic on a regular bais and provided us with some dernographic information on

al1 CCP clients attending the clinic regardless of their wilhngness or eligibility to participate in the

study.

Clients attending the CBI for rehabilitation were informed of the study through their therapist

or read about the study in the posters and pamphlets available at the c h i c . Once a client showed

interest in participating in the study, one of the therapists at the CBI informed the study coordinator

26

who arranged to meet with the potential case. The study coordinator ensured that the client fiilly .

understood the procedures he would be involved in, gave a demonstration of the sleep monitoring

equipment that would be used in the subjects homes during the study, and obtained informed

consent. The consent form (Appendix 2) requested that al1 subjects refiain fiom consuming any

caffèine or alcohol the day of the study and also requested that, subject to their doctors' approval,

they avoid the use of the following medications: sleeping pills, tranquilIizers, muscle relaxants,

antidepressants, and narcotics for one week pnor to the start of the sleep measurements and during

their participation in the study. Only one of the fifieen cases was taking any of the above

medications, (Tylenol#3 and lorazeparn) and it was not possible for him to discontinue their use.

Only ten subjects were chosen as controls since it was expected that this group would show

less variance (compared to cases) in the sleep measures uiider investigation, and also because some

normative data on standard sleep measures was already available. We believed it necessary to

collect some in-home data for controls because most of the normative data had been collected in a

sleep clinic setting. ûrïginally, an attempt was made to recruit controls by asking cases to identify

work mates who performed similar types of work. The recruitment of ''finend" controls would have

made it possible to match cases and controls by age, educational level, and occupation, factors which

are h o w n to be associated with the occurrence of low back pain, and to affect sleep physiology as

well. This strategy for control recruitment proved to be unsuccessful. The ten controls who

completed the study were al1 males, similar to the cases in age (to within five years). They were

recmited by advertising at the Toronto Hospital (Western Division) and by word of mouth. Al1

subjects received an honorariurn for their participation in the study as approved by the University

of Toronto and Toronto Hospital (Department of Psychiatry) Human Subj ects Review process

(Appendix 3).

PROCEDURES

Once subjects had consented to participate in the study they, were scheduled for their fïrst

session consisting of three consecutive study nights. Al1 shidy nights were conducted within the

subjects' own home using portable sleep monitoring equipment. A sleep technician and an assistant

would arrive at the subject's home at approximately $:O0 p.m. and would require approximately one

hour to prepare the subject for the study and to ensure d l equipment was fhctional. The research

team would then leave the home for the evening. The subject was instmcted to complete the

necessary questio~aires for that study night, and to maintain a normal sleep schedule, (i.e. they were

to go to bed at their usual tirne). Subjects were given the research coordinator's pager number

should any concems &se through the night. The following morning a technician arrived at the

subject's home to retrieve the equipment and retum it to the sleep clinic, so that it could be reset and

ready for collecting data again that same evening.

hKEASUREMENT TOOLS

A. SLEEP ASSESSUENT

1) Oxford Medilog S ystem

The physiological recordings of sleep were collected using the Oxford Medilog System,

Model9000 II, an ambulatory system presently capable of recording eight channels of physiological

data. A separate channel records tîme and incorporates information generated fiom a manually

activated event marker. The medilog recorder stores data on a standard audio cassette and is

28

powered by four AA alkaline batteries. Prior to commencing the sleep recording, an external

caiibrator is connected to the recorder and provides a 50 or 100 pv pulse onto the audio cassette tape.

This calibration signal is later used as a standard of amplitude for sleep/wake analysis.

For the purpose of this study EEG, EOG, EMG, Electrocardiogram (ECG) and respiratory

effort were contuiuously monitored through the night, using standard placement of electrodes. The

hvestigators believed respiratory screening was necessary, since sleep apnea (characterized by

repetitive episodes of upper airway obstruction during sleep) has been reported to be prevalent in 4%

of rniddle-aged working men (Young, 1993) and has distinct health implications (Stoohs, 1990).

M e r preparing the subject for their sleep study, the technician would temporarily connect

the Medilog recorder to a portable computer. Using the software "Mentor", the physiological

recordings could be displayed on the computer screen to ensure that al1 channels were fully

functional before the technician lef€ the subject's home. Each night the subject was instructed to

press the Medilog event marker at the t h e he went to bed and the following moming when he got

out of bed for the h a l t h e . When the equipment was retumed to the sleep clinic the next moming

the Medilog tape was scanned, using the Oxford Medilog display system. This process made it

possible to review the previous nights' data to ensure that the sleep recording was of acceptable

quality and allowed us to address any technical problems prior to the next scheduled sleep study.

A total of 214 overnight sleep recordings were collected. Although the Medilog system is ideal for

the collection of ambulatory physiological sleep recordings, it is not ideal for the analysis of this

data. Since the technology for replaying this data into another system (e.g. Sandman), for analysis

purposes, was not available at the time the sleep studies were being recorded, and because it would

require approximately 1 year of full-time work to extract and analyze al1 214 sleep recordings it was

29

decided, by the members of the thesis cornmittee, that this data would not form part of this thesis.

II) Actigraph

Another ambulatory method of assessing sleep disturbances or evaluating rest-activity cycles

is through actigraphy. The actigraphs used in this study were the Ccmini-motionlogger"

manufactured by Ambulatory Inc. The actigraph is about the size of a wrist watch and uses a piezo-

resistive bridge accelerometer to detect motion. It is operated by a coin cell battery. Movements

occuning at the wrist are sampled ten times per second and are accumulated in time bins. Using the

software "ACT" and an actigraph interface unit, the actigraph can be programmed to collect activity

data based on the options defined by the user. A brkf description of the options available and the

programme used in this study follow.

Epoch Time: Epoch tirne refers to the time unit that will be used to store the collected data.

The epoch tirne can range fkom two seconds to ten minutes with smaller times providing more

detailed data. For this study 30-second epochs were used since the medilog data will also be

analyzed using 30 second epochs as is standard in sleep research (Rechtschaffen and Kales, 1968).

Packing Option: The packing option assigns a specific number of bits for each data value

and therefore detemiines the nui time of the actigraph. Packing option A was chosen, allowing the

actigraph to collect data for approximately ten continuous days.

Wake-up Time and Stop Tirne: The actigraph was programmed to begin collecting data at

20:OO hours (on the evening it was activated). For continuous data collection over several days the

stop time was set for the same time as the start time (Le. 20:OO hours).

Zero Crossing Mode: In the zero crossing mode the actigraph uses a reference voltage to

30

detect a change in state (Le. movement or activity at the wrist).

Event Mode: The event mode allows subjects to press an extenial button on the side of the

actigraph in order to mark a specified event. Subjects were asked to press this button each night at

the time they went to bed and in the moming at the t h e of their final awakening.

The actigrap h was placed on the non-dominant wrist on the nrst evening of each session and

the subject was instructed to Wear it continuously until the morning following the last study night

for that session. Although it is common practice to place the actigraph on the non-dominant wrist,

few studies have addressed the issue of placement. Sadeh found significant differences in minute-

by-minute activity levels collected nom the dominant and non-dominant wrist. While activity levels

as recorded fiom the dominant wrist were found to be signincantly higher during sleep and

wakefulness, the differences were found to have no effect on the accuracy of the sleep-wake scoring

(Sadeh, 1994). During this study al1 except one subject wore the actigraph on their non-dominant

wrist. The one exception (a low back pain subject) wore the actigraph on his ankle as he thought

it would interfere with his work if worn on his wrist. One other subject (also a back pain subject)

did not agree to Wear the actigraph during the day; therefore only nightly recordings of activity are

available for this subject. The subjects were informed that since the actigraph was waterproof there

was no need to remove it when showering. Therefore, for the £kt session, the subject wore the

actigraph for approximately 60 continuous hours (i.e. 3 nights and 2 days) and during subsequent

sessions (S2, S3, S4) the actigraph was wom for approximately 36 continuous hours (Le. 2 nights

and 1 day).

Once the actigraph data was collected, it was retrieved using the "ACT" software. The

"ACT" file generated was exported into the "Action 3" software (capable of automatically analyzing

31

the raw activity data). "Action 3" provides summary statistics using the raw data The entire data

or rnanually selected intervals of data could be analyzed. Sleep/wake epochs could also be

automatically scored by choosing an algorithm that kmsfers the activity data to sleep/wake scores.

The software algorithm (Appendix 4) that was used to anaiyze this data is one developed by Sadeh

(Sadeh, 1989) and previously used by Lavie to compare sleep in patients with rheumatoid arthritis,

low back pain and healthy controls (Lavie, 1992).

Al1 previous validity studies of sleep assessrnent through actigraphy have been based on the

concomitant recording of actigraphy and polysomnography (PSG), considered the gold standard.

Therefore in previous studies the subjects' sleep was being monitored in a sleep laboratory and the

data fkom the PSG recording, which is scored using standard criteria (Rechtschaffen and Kales,

l968), was compared to the sleep\wake scores generated fiom actigraph data. Minute-by minute

agreement for sleep\wake scoring have been found to range fkom 78.2% to 96.3%. Correlations

ranging nom 0.63 to 0.95 have been reported for sleep efficiency and correlations for duration of

sleep have been reported to range £kom 0.82 to 0.97 (Sadeh, 1995).

The accuracy of the actigraphy data is dependent on many variables, which include: the

scoring algorith, the subject group being studied, the type of actigraph being used and its selected

mode of operation. Mullaney found that minute-by-minute agreement for sleep\wake was lower for

patient groups compared to nomial subjects, for older subjects (i.e. age 50 or above) compared to

younger subjects, and for short sleepers compared to long sleepers (Mullaney, 1980). Different

scoring algorithms may be required to maxirnize accuracy for different groups of patients (e.g.

insomnia patients versus sleep apnea patients).

Once a file was opened in "Action 3", sleep intervals were created for each night of data.

32

The sleep intervals were created using the single channel adjustable view with a "raw data" t h e

compression. The activity data was manually tagged at the time the subject appeared to have fallen

asleep and at the tirne they appeared to have awakened in the moming (Appendix 5). Automatic

sleep scoring (based on the scoring algorithm) was then applied to the activity data within these

intervals. The following variables were automatically derived for each subject for every study night:

Sleep minutes: SIeep efficiency:

Nurnber of awakenings:

Mean awakening minutes:

Mean activity value:

The number sleep minutes during the sleep interval. The number of sleep minutes divided by the total number of minutes in the sleep interval. The number of times the subject was defined as awake during the sleep interval. The average length of d l the awakenings which occurred during a sleep interval. The number of times, for every 10" of a second, the signal voltage is above the reference voltage (thus representing an activity fkequency measure).

iii) Sleep S ymptoms

Once each session, subjects were asked to complete the University of Toronto Sleep

Assessment QuestionnaireQ (SAQ), which has been shown to be a reliable and valid instrument in

the sleep c h i c setting (Cesta, 1996). The SAQ score can range fkom O to 68, with higher scores

being indicative of greater sleep disturbances. The SAQ was found to discriminate between patients

with sleep pathology and normal heaithy controls. The mean total SAQ for controls was found to

be 10.8 (s.d. 5.7), and the mean total SAQ score for patients was found to be 26.0 (s.d. 8.6). Factor

analysis of the 17 questions of the SAQ identified 5 factors which were referred to as; 1) Non-

restorative sleep, ii) Sleep Schedule Disorder, iii) General Sleep Disturbance, iv) Sleep Apnea and

v) Hypersomnolence (Cesta, 1997). Only the non-restorative sleep factor will be analyzed in this

population since these questions reflect quality of sleep which we believe is most affected in subjects

experiencing pain.

C. ROLAND SC&E

The Roland Scale is a 24-item questionnaire which has been shown to be a reliable and valid

measure of disability in patients suffering fiom LBP (Roland, 1983). This instrument has also

proven to be a sensitive measure of changes in disability over time (Deyo, 1990 and Hogg-Johnson,

1997). The 24 items making up the Roland Scale were taken fiom the Sickness Impact Profile, a

functiond status questionnaire. The Roland c m be easily scored by adding up the number of times

the subject responds "yes" to each of the 24 questions. Total scores on the Roland Scale can

therefore range £kom O to 24, with higher scores indicating greater functional disability. The

questions of the original Roland Scale were reworded so that subjects were asked to rate their

disabiliîy over the past month. Subjects were asked to complete this questionnaire on one night of

each session.

D. CHRONIC PAIN GRADE

The Chronic Pain Grade (CPG) consists of 7 questions used to derive a pain intensity and

disability score, as well as to assign disability points. The subject grades his response to each item

using a O to 10 scale. The pain intensity score can range fiom O to 100, with higher scores signifjmg

greater pain. The published version of the CPG was slightly dtered so that subjects rated their pain

syrnptoms over the past month rather than over the past 6 months. The CPG has been shown to have

a statistically signincant relationship with unemployment, hctional limitations, and depression at

one year of follow-up (Von Koff, 1992). Subjects completed the CPG once per session.

34

E. HOSPITAL ANXETYSCALE AND BECK DEPRESSIONINKENTORY

The Literature on the relationship between anxiety, depression and LBP is inconsistent.

However, until this relationship is clarified, anxiety and depression may prove to be important

psychological factors to consider when assessing recovery fkom LBP. Lanier found that a history

of depression or anxiety was significantly related to greater work loss and longer disability (Lanier,

1 990) and Dionne found psychological variables (Le. measures of somakation and depression) to

be the best predictors ofback-related functional limitations ( D i o ~ e , 1997). Anxiety and depression

are also important to consider when evaluating sleep physiology. For example, patients with

depression have been shown to have a shorter REM latency and to experience a greater number of

early rnoming awakenings when compared to non-depressed patients, and anxiety has been

associated with insomnia. Anxiety and depression were therefore evaluated once at baseline and

once again at each follow-up session.

The Hospital Anxiety Scale ( H A S ) was used as a measure of anxiety. It consists of only 7

questions and is quite easily scored. Scores on the HAS can range from O to 21. Zigmond found

that patients who scored 1 1 or greater on the HAS were considered "anxious" by dinicians who

intewiewed them, while a score ranging nom 8-10 was found in doubtful cases and a score of 7 or

less was found in non-cases (Zigmond, 1983). The 21-item Beck Depression Inventory @DI) was

used as a rneasure of depression. Many studies have shown the BDI to be a reliable and valid

rneasure of depression (Beck, 1988). The number of factors making up the BDI have been reported

to range fkom 2 to 7 factors. The number of factors identified and their composition depends on the

diagnostic group completing the BDI. The BDI can be sub-divided into a cognitive-affective and

a somatic subscale as recommended by some researchers (Beck, 1988 ). Higher scores on the BDI

indicate more depressive symptoms-

F. RETURN TO WORK

In order to assess whether subjects with LBP were working at the t ime of each study, they

were asked to complete a R e m to Work Questionnaire (Appendix 6). The R e t m to Work

Questionnaire is made up of questions which the study investigators believed would allow them to

fully assess each subjects' work status. Its basic purpose was to evaluate how many days each LBP

patient had been absent fiom work due to his injury, to record a brief description of his occupation,

to assess his retum to work status, and to detennine whether he worked shifts.

ANALYSIS

Summary statistics for the questionnaire and actigraph rneasures are displayed in tables

and show the number of subjects 0, the range (Min and Max), mean, and standard deviation

(Std) by session.

Using SAS v6.12, boxplots were created to provide a descriptive analysis of the data.

The bottom and top of each box are draw-n at the 2 5 ~ and 7 9 ' percentiles. The horizontal line in

the centre of each box represents the median and the + sign shows the sample mean. The vertical

lines or "whiskers" extending fkom the top and bottom of each box extend to 1.5 interquarhle

ranges. Extreme values are marked with a O if they are within 3 interquartile ranges of the box

and with an * if even more extreme.

The Hospital Anxiety Scale, the Beck Depression Inventory, the somatic component of

the Beck Depression Inventory, the University of Toronto Sleep Assessment Questionnaire, the

non-restorative factor of the Sleep Assessment Questionnaire, mean activity value, mean

awakenings per hour, mean awakening minutes, mean sleep minutes, and mean sleep efficiency

were examined as outcorne variables using a generalized estimating equation (GEE) rnodel. The

GEE mode: is a method of analyiiing longitudinal data which takes into account the intra-subject

correlations, treating them as nuisance parameters, and also allows for subjects to have a

different number of repeated rneasures (Le. subjects are not omitted fiom the analysis if they are

missing data for one session). Regression coefficients were estimated using a SAS GEE macro

written by K a r h and Zeger. For this particular analysis a identity link was used and an auto

regressive correlation structure was specified since we expect the relationship between

successive observations to be larger, the closer in time they occw .

36

37

The above outcome variables were examined using three GEE rnodels. In GEE model 1,

"Type" (i.e. case = 1, control = 0) and Session were assessed as covariates. This mode1 will be

used to determine whether the above outcome variables discriminate between workers with LBP

and controls and whether the measures are significantly changing fiom session to session. To

investigate whether the measures are changing differently in cases and controls, the interaction

between Type and Session is examined as a covarîate in GEE rnodel 2. Mode1 2 will be used to

detemine whether the rate of change in the outcome variables is different in cases and controls.

In GEE rnodel 3, "Retum to work status" (Le. O = No, 1= Yes) was considered as a covariate.

This model will be used to assess whether return to work stahis, in LBP subjects, can predict any

of the outcome variables being analyzed. If the interaction is significant @<OS) then the

interaction will be maintained in interpretation; othenvise only main eEects will be interpreted.

The results of the GEE analysis for each of the outcome variables are summarized in

tables which show the intercept, regression coefficient parameter estimates, standard errors, and

corresponding p-values for the intercept and each of the above covariates.

The variability of the Pain Intensity and Roland scores within the case group was M e r

explored by c l a s s i ~ g cases as returned to work or not returned to work at each session. Pain

Intensity and Roland scores were considered covariates in a GEE analysis with retum to work

status as the outcome variable. In this GEE analysis, a logit link was specified since the outcome

variable, i.e. retuni to work, is a dichotomous variable. The purpose of this analysis was to

identi@ whether pain or functional disability could predict return to work status in workers

following a low back injury.

RESULTS

In total, 1 0 controls took part in the study and 1 7 cases were recruited fkom The Canadian

B ack Institute (CBI). Two of the 1 7 cases decided to withdraw their participation after the h t study

night and only one of the remaining 15 cases did not complete al l four sessions (i.e. this subject

could not complete session 4 due to other commitrnents). One of the controls was excluded fiom

all analyses because his Pain Intensity score on the Chronic Pain Grade was found to range between

40 and 63. Since our goal was to compare workers with a low back injury to a pain-fiee control

group, we decided that this subject did not meet the eligibility criteria set out for controls.

Between March 1994 and November 1994, physiotherapists at the CBI completed 161

Demographic Profile Sheets for potential study subjects. Sixty percent (96/161) of these clients did

not meet the study's inclusion critena for the following reasons: gender was female (n=43), injury

had occurred more than seven weeks ago (n=34), primary injury was not in the lower back (n=9),

client was not between the ages of 1 8 and 50 years of age (n=2), client had a concurrent diagnosis

of fibromyalgia (n=l), and other reasons (n=7). Of the forty percent (65/161) of clients who were

eligible to participate in the study during these nine months, fie-six clients refused and nine clients

volunteered to participate. Amongst the fifty-six eligible CCP clients who did not agree to

participate, the mean age was found to be 34.3 years (s.d. = 8.1) while the mean age for recruited

cases was 36.7 years (s.d. = 9.3). The difference in age was neither clinically nor statistically

significant (Pr > Itl= 0.32). Between November 1994 and December 1996, an additional six CCP

clients were recruited into the study, giving us a total of 15 cases. No other relevant data collection

on study 'crefbsers" was attempted for ethical reasons.

The mean age for study controls was 33.4 years. The difference in ages between the fifteen

38

39

study cases and nine controls was neither statistically significant (Pr > Itl = 0.36) nor clinically

meaningful, although the power to detect a clinically important dif5erence (eg. 5 years) was limited

due to sample size.

TABLE 1 - Summary s t a t i s t i c s f o r Weeks P o s t - I n j u r y by session

1 No. o f cases n o t returned t o work 1 1 1 1 4 1 3 1 3 1 1 Weeks p o s t - i n j u r y (mean) 1 6 1 1 O 1 15 1 19 I 1 Range o f weeks p o s t - i n j u r y (min,max) 1 (3,8) 1 (7,13) 1 (10,17) 1 ( 1 5 , 2 2 ) 1

The number of days between the cases' date of injury and their initial assessrnent (i.e. study night

1) ranged fiom 3 to 8 weeks, with a mean of 6 weeks (TABLE 1). For purposes of analysis, a case

was considered as having not returned to work (NRTW) if he indicated on his R e m to Work

Questionnaire that he was "not presently vorking" or had "retumed to special arrangements" to help

him get back to work. Two of the cases categorized as NRTW had retumed to special work

arrangements at session 2 and did not return to regular work duties over the course of this study.

FIGURE 1 - Percent of cases not re tu rned t o work a t each study session

3

S e s s i o n

40

Figure 1 shows the percentage of cases who had not retumed to regular duties at each study

session. At the thne of their initial assessment (Le. 3 to 8 weeks post-injury) the majority of cases,

eleven of the fifteen (73%), had not retumed to work. By the time of their final assessment three of

the fifteen (20%) LBP workers were still not able to return to theirregular work duties. The majonty

of cases (7 of the 12 who eventually did return to work) retumed to work at some time between the

first and second study sessions, that is, between six and ten weeks post-injury. Those who had failed

to return to work at approximately 15 weeks post-injury (Le. session 3) continued to be off work at

approximately 19 weeks post-injury (i.e. session 4). The return to work rate in the case group is

similar to that reported by Frank, that is, after 15 weeks post-injury, when approximately 20% of

claimants are still off work the curve begins to level off with very little chance of these subjects

returning to work in the near friture (Frank, 1996).

The results of the questionnaire and actigraph measures are shown in the tables and figures that

follow. The number of subjects 0, minimum value (Min), maximum value (Max), mean value,

and standard deviation (Std) are summarized for each session. Al1 of the questionnaires were

completed once per session. Missing questionnaire scores resulted from incomplete questionnaires

(Le. total scores could not be calculated) and on a few occasions the subject forgot to complete his

nightly questionnaires. The SAQ scores that are missing at session 1 (SI) and session 2 (S2) are

actually a result of the SAQ being revised after the study had begud. Total SAQ scores for those

who completed the old version of the SAQ were not included in the analysis.

Following a separate and just completed study of the SAQ's sensitivity the authors of the SAQ added 3 new questions, divided one of the old questions into 2 separate questions, and changed the format of another question. Siuce this new version showed favourable reliabitity and validity (Cesta, 1995, 1996), and the present study had just begun, the new version was used after the first two cases had completed sessions land 2 and the third case had completed session 1.

41

The activity data was collected at each of the nine study nights, with night 1 serving as a night

for acclimatization to the Medilog equipment. The value of eacb sleep measure at each session

represents a mean value for that session (eg. sleep efficiency at S 1 is the mean sleep efficiency for

nights 2 and 3, the sleep efficiency at S2 is the mean sleep efficiency for nights 4 and S), unless only

one night of activity data was available for a session. It was believed, based on severd years of

experience, that the mean value of the two consecutive nights would more accurately reflect the

subject's sleep patterns. Within each session, the ha-class correlation coefficient @CC) was

calculated for each sleep measure. For example, an ICC was calculated for sleep efficiency at S 1 by

comparing sleep efficiency at night 2 with sleep efficiency at night 3. The ICCYs were found to

range between O and 1.0, with the majority of them falling between 0.5 and 0.8.

A total of 23% of the actigraph data was missing (i.e. data for 22 sessions out of a possible 95

sessions). On one occasion the data was Wely lost because the subject wore the actigraph while

swimming (although the actigraphs are said to be waterproof, they are not to be submerssed under

water for a prolonged penod of t h e ) . The actigraph data was omitted on another occasion because

the event marker appeared to be spontaneously recording al1 night making it difficult to interpret

the activity data. Most of the missing actigraph data cannot be accounted for. Although the

actigraphs were initialized or prepared for data collection in a similar manner at d l times (Le. the

available options, as specified on p. 29, were programmed the same way each tirne), in some

circumstances (20% of data files) any atternpt at retrieving the data files resulted in an "error

reading" message. An engineer at Ambulatory Monitoring Inc. (manufachuers of the actigraph) was

contacted to determine whether any of these files could be retrieved. He believed that the actigraph

may have been shutting itself off before it began collecting data (i.e. technicd malhction occured

within the actigraph), and that regular maintenance might have reduced the number of lost files.

The tables and boxplots below display the session scores and ranges for the Roland Scale and

the Pain Intensity subscale of the Chronic Pain Grade for cases and controls (TABLES and

FIGURES 2 and 3). The heterogeneity within cases is apparent when one considers the range of

baseline scores obtained fiom the Roland Scde and the CPG. At S 1 the mean Roland score (RS)

in cases was fomd to be 1 1.3 (TABLE 2) . At the initial assessment, the LBP subject who reported

the greatest functional disability scored 21 (out of a possible 24) on the RS, while the LBP subject

who appeared to be the least functiondly disabled as a result of his injury rated himself as 1.

Overall, the greatest improvement in fûnctional ability in cases occurred sometime between S 1 and

S2 (Le. during the second month of recovery). The mean RS score for cases decreased fiom 1 1.3

to 8.0 during this time. Functional status improved slightly over the next two sessions.

TABLE 2 - Summary s t a t i s t i c s f o r Roland Score f o r Cases vs. ControLs - - - -

Session

4 3 1

Graup

2

Controls

7

0.0

0.0

0 -0

Group Group

Cases

14

0.0

20.0

7.1

Controls

8

0 .O

2.0

0.3

Roland

0.00 7.03

Controls

9

0.0

0.0

O .O

Group

Cases

14

0.0

21.0

7.8

N

Min

Max

Mean

Cases

15

0.0

22.0

8 .O

7.05

Controls

9

O .O

0.0

0.0

0.71 1

Cases

15

1 .O

21 .O

11.3

0.00 Std 6.77 7.12 0.00

XGURE 2 - Box Plots o f Roland Score f o r Cases vs. Controls

CAOUP Controls CPaes ~ontrola Cas06 Controll Cases Controls Cases SEçSfffl 1 1 2 2 3 3 4 4

The cases' mean pain intensity score (PI) at S 1 was 64.5 (TABLE 3). At S1 the greatest PI score

reported arnongst the cases was 97 (out of a possible LOO) and the lowest was a score of 30. The

greatest drop in PI score also occurred between S 1 and S2, when the mean PI score for cases dropped

£iom 64.5 to 52.7. Cases appeared to be experiencing less pain at session 3 (S3) when their mean

PI score decreased to 46.5, but at session 4 (S4) there was a slight increase in mean PI score to 49.6.

TABLE 3 - Summary statistics f o r P a i n Intensity Score ( P I ) f o r Cases vs. C o n t r o l s

;ion

GrOup Group

controis 1 cases 1 ~ o n t r o l s 1 Cases 1 PK

ses

N

Min

FIGURE 3 - Box P l o t s of P a i n I n t e n s i t y Score f o r C a s e s vs. Controls

Uax

Mean

Std

GROUP Conrrolr Caser Cantrols Caser Contrala Cares Controls Cases SEÇSION 1 1 2 2 3 3 4 4

1

Group

The controi subjects showed no sign of functional disability on the Roland Scale (Le. RS's were

Controls

8

0.0

2

Group

13.0

3.6

5-10

O at al1 four sessions), and were relatively "pain-fiee" (indicated by the PI scores which were found

to range between 2 and 5 throughout the four study sessions).

Figures and Tables 4 through 13 show the distribution of session scores for the Hospital Amiety

Scale (HM), the Beck Depression Inventory @DI), the somatic component of the BDI (SBDI), the

University of Toronto Sleep Assessrnent Questionnaire (SAQ), the non-restorative factor of the SAQ

(NRSAQ), and the actigraph measures of mean activity value (AV), mean awakenings per hour

(AH), mean awakening minutes (AM), mean sleep minutes (SM), and mean sleep efficiency (SE)

Cases

14

30.0

Controls

8

0.0

Cases

15

17.0

97.0

64.5

17.84

27.0

4.6

9.69

83.0

52.7

18.46

10.0

3.9

4.26

97.0

46.5

24.60

10.0

2.4

4.24

100.0

49.6

22.85

in cases versus controls.

GEE tables list the intercept, regression coefficient parameter estimates, their standard errors,

and the corresponding p-values for the covariates chosen as predictors of the following outcome

measures; Hospital Anxiety Scale, the Beck Depression Inventory, the somatic subscale of the Beck

Depression Inventory, the Sleep Assessrnent Questionnaire, the non-restorative subscale of the Sleep

Assessrnent Questionnaire, activity value, awakenings per hour, awakening minutes, sleep minutes,

and sleep efficiency.

TABLE 4A - Summary s t a t i s t i c s f o r Hosp i ta l Anxie ty Score f o r Cases vs. C o n t r o l s

Session

Group Group

C o n t r o l s Cases C o n t r o l s Cases

8 12 9 15

3.0 3.0 0.0 3.0

-

Group Group

-

FIGURE 4 - Box P l o t s o f H o s p i t a l Anxiety Score f o r cases vs. Cont ro ls

46

The cases' mean HAS score at S1 was 7.7 (TABLE 4A). HAS scores for cases were found

to follow the same trend as the PI score over the four study sessions. We would expect anxiety

scores to decrease over tirne, but they remained quite stable f?om S 1 to S2, dropped at S3, (Le.

cases appeared least anxious at S3 with a mean HAS score of 6.1) and at S4 H M scores

increased to baseline levels (Le. KAS score at S4 , similar to HAS score at S 1). On average,

cases showed the largest &op in HAS scores between S2 and S3 (nom 7.5 to 6.1).

TABLE 48 - GE€ models w i t h H o s p i t a l Anx ie ty Score (HAS) as t h e i r outcome measure

Outcorne Measure: HAS Mode1 1

Covan'ates:

INTERCEPT

TYPE ' SESSION 3 l I l 1 -0.571 0.81 1 0.4839

TYPE

SESSION 2

SESSION 3

SESSION 4

TYPE ' SESSION 2

Mode1 3 1

246

-0.81

-1.5

-0.61

TYPE ' SESSION 4

RTW

Compared to the cases, the H M scores in the controls were consistently lower. A

statistically significant difference was found in HAS scores in cases versus controls (TABLE 4B:

Model 1, p = 0.02). There was a significant change in HAS scores at S3 (Model 1, ~ ~ 0 . 0 1 ) but

in model 2 only one of the interaction terms (type*session2) was marginally significant.

Generally this model suggests that change over time did not differ significantly for cases versus

controls. The boxplot and GEE table support this hding. Retum to work status did not

significantly contribute to the prediction of HAS (Model 3, p = 0.54).

1 .O2

0.55

0.4

0.59

123 1.03 02301

TABLE SA - Summary s t a t i s t i c s f o r Beck Depression Inventory Score f o r Cases vs. Contro ls

I Session I

1 Group [ Group 1 Group 1 Group 1 Cases Controls Cases

6 -73

FIGURE 5 - Box P lo t s o f Beck Depression Inventory Score f o r Cases vs. Contro ls

(nOUP Controls Cases Controls Ciass Controls Cires Controls Cires

SESSION 1 1 2 2 3 3 4 4

N 9 14 7 12 O 13 7 13

48

The mean BDI score for cases at the initial assessrnent was 9.5 (TABLE SA). Although the

boxplot shows wide variation, cases' BDI scores tended to decrease over time (FIGURE 5: 7.5 at

S4). On average, cases scored 5 points higher than controls, but only a small percentage of cases

scored over 1 1, a cutoff considered indicative of "minimal depression".

TABLE SB - GEE models w i t h Beck Depression Inventory Score (BDI) as their outcome measure

Statistically significant differences were found between cases and controls (TABLE 5B:

Model 1, p = 0.03), but the two groups did not change differently over time (Model 2). In fact,

mode1 1 suggests there was little change over time in either group (P ranges fiom -0.62 to -1.04).

Return to work status was not significantly predictive of BDI score (Model3, p = 0.72).

TABLE 6A - Summary s t a t i s t i c s f o r Somatic Score of Beck Depression Inventory f o r Cases vs. Controls

I Session

Controls Cases Cantrols Cases Controls Cases Cantrols Cases

FIGURE 6 - Box P l o t s o f scores f o r Somatic Score o f Beck Depression Inventory f o r Cases vs.

- -- -

man

Std

Cont r o l s I

10 +

I 1 1

8 +

I I I

6

I I I

4

I I I

2

I I I

O +

Beck somatic

-------i----+-i-i-------+-------*--*--------------+--*--------+----*-----.+-----------

GRWP Contmls Cases controla Cises contrala Cases Controlr cares SESSION 1 1 2 2 3 3 4 4

N B 14 7 12 9 13 7 13

8

0.0

N - Min

t .O

1-51

As mentioned previously, BDI cm be divided into a somatic and an affective component. Items

15 through 21 of the BDI c m be considered a somatic subscale of the BDI. We would expect SBDI

scores to have decreased over time as the cases recovered. Cases' mean SBDI score did not show

14

0.0

4.4

2.27

7

0.0

1 .O

1.29

12

0 .O

2.8

2.86

9

0.0

0.8

1.30

13

0.0

3.3

2.25

7

0.0

1.3

2.21

13

0.0

3.5

3.26

50

any major changes over the four sessions during which time they ranged between a score of 3 and

4 out of a possible maximum of 21 (see TABLE 6A).

TABLE 6B - GEE models w i t h Somatic Score o f Beck Uepression Inventory (SBDI) as t h e i r outcome measure

-- - -- - - - - - -- - - -

Compared to controls, cases were found to have a statistically significant greater number

I Outcorne Measure: SBDl

Covarîates:

INTERCEPT

TYPE

SESS~ON 2

SESSION 3

SESSION 4

TYFE' SESSION 2

TYPE ' SESSION 3

TYPE ' SESSION 4

RTW

somatic depressive cornplaints (TABLE 6B: Model 1, p 4.01). Model 2 shows that the change in

SBDI score at session 2 was different in cases versus controls (Model 2, Type*Session2, p = 0.01).

However, both groups' scores were relatively stable over S2, S3, and S4. In Model 3, return to work

status was found to be a statistically significant independent predictor of SBDI score @ < 0.01).

Mode11

P 1.42

269

-1.05

-0.69

-0.33

Mode12

se

0.56

0.m

0.36

0.36

0.56

CJ 0.96

3.42

-0.14

-0.16

0.49

-1.44

-0.82

-1 -27

Mode13

P 0.0114

0.0005

0.0033

0.0524

0.5485

P 3

1.9

-0.52

-0.14

023

-1.93

se

0.48

0.76

0.1

0.38

P

0.0466

<0.001

0.1389

0.6745

se

0.79

0.83

0.23

0.34

0.55

0.66

P

0.0001

0.0215

0.0264

0.6672

0.6745

0.0037

0.32

0.52

0.62

0.88

0.1285

0.0056

0.1835

0.1499

TABLE 7A - Summary s t a t i s t i c s for Sleep Assessment Questionnaire Score (SAQ)for Cases vs. Controls

I Session

l I

Group Group Group Group

N

Min

Max

m a n

S t d

FIGURE 7 1

40

1 1 1

30 +

1 1 I

20

1 1 l

10 +

1 1 1

0 +

Cases

11

- Box P l o t s of S leep Assessment Questionnaire Score f o r Cases vs. Controls

GRWP Controls Cases Ccnt ro ls Caaes Ccntmls Cases Conrrola Case.

Controls

8

5.0

24.0

15.4

6 -21

Controls

7

Controls

2

15.0

22.0

18.5

4.95

If sleep in cases was improving in workers as they recovered ficorn their LBP then we would

Cases

9

13.0

32.0

22.8

5.93

expect SAQ scores to have decreased over t h e . Amongst cases, the SAQ scores did not change

very much over the four study sessions (TABLE 7A). SAQ scores were the same at SI and S2,

(mean SAQ score at S1 and S2 = 23), decreased slightly at S3, (mean SAQ score at S3 = 21) and

then increased slightly at S4 (mean SAQ score at S4 = 23). The SAQ scores were generally stable

over time in both groups although overall, the scores tended to be higher for the cases.

Cases

13

Controls

7

Cases

14

TABLE 78 - GEE models w i t h Sleep Assessment Questionnaire Score (SAQ) as t h e i r outcome measure

I Outcorne Measure: SAQ Mode11 l Mode12 l Covartates:

INTERCEPT

TYPE

SESSION 2

SESSION 3

SESSION 4

Workers with LBP appeared to be experiencing a greater number of sleep disturbances as

indicated by GEE Model 1 which shows a statistically significant difference in SAQ scores for cases

versus controls (TABLE 7B: Model 1, p < .01) As demonstrated in Model 2 the changes in SAQ

scores, over tirne, were not significantly different in cases versus controls. There was a marginal

contribution for RTW in Model3, showing those cases who had retumed to work tended to have

Iower SAQ scores @ = 0.10).

TABLE 8A - Sumrnary s t a t i s t i c s f o r Non-Restorative Score o f the Sleep Assessment Questionnaire f o r Cases vs. Controls

TYPE * SESSION 2

TYPE ' SESSION 3

TYPE ' SESSION 4

R M I

P 15.55

8.44

-1.24

-1.43

-1.63

-0.047

-0.55

4.41

se

2-19

2.49

1.34

1.61

2 1 1

SAü (non r e s t )

1.95

2.42

2.87

Session

N

Min

Max

Mean

Std

P <.O001

0.0007

0.3524

0.3735

0.4354

0.8103

0.8181

0.1236

1

Group

P 16.44

7.02

-0.94

-1.07

-4.48

-2.42

Controls

2

6.0

7.0

6.5

0.71

Cases

11

5.0

17.0

11 - 4

3.41

se

1.95

2ô3

1.12

1.42

0.89

4

~ r o u p

2

~ r o u p

3

Group

Cont roh

7

1 .O

11.0

4.4

3.21

Controls

8

2.0

10.0

5 .O

2.67

P <.O001

0.0076

0.4009

0.4533

c.0001

Controls

8

4.0

11.0

5.8

2.38

Cases

14

0.0

15.0

8.2

3.62

Cases

13

3.0

18.0

9.6

3.82

P 17.19

7.64

-0.39

-0.5

-0.69

Cases

15

1 .O

19.0

8.7

4.23

FIGURE 8 - Box P lo ts o f Non-Restorative Score o f the Sleep Assessment Questionnaire f o r :ases vs.

I 20 +

1 1 1

15 +

I I I

10

1 I l

5 +

I 1 I

O +

Controls

- - - - - - - - - - - -+- - - - - - - - - - -+- - - - - - * - * - *+- - - - - - - - - - - * - - - - - - - - - - -+- - - - - - - - - - -+- - - - - - - - - - - * - - - - - - - - - - -+- - - - - - - - - - -

OROUP Cantroli Cases Contmls Cases Contmls Cases Contmls Cires SESSIüN 1 1 2 2 3 3 4 4

The non-restorative subscale of the SAQ is made up of six of the SAQ items which, for the

most part, address one's quality of sleep. Cases reported t leir sleep to be least restorative in

nature at the time of their initial assessrnent (Le. highest NRSAQ score over the four sessions,

TABLE 8A), and showed improvement over tirne.

TABLE 8B - GEE rnodels w i t h Non-Restorative Score o f the Sleep Assessment Questionnaire (NRSAQ) as t h e i r outcome measure

Outcome Measure: NRSAQ

Covariates:

INTERCEPT

TYPE

SESSION 2

TYPE * SESSION 4 1 1

- - - -

A statistically significant difference was found between cases and controls (TABLE 8B:

Mode1 1, p c 0.01) and overall there was some change over t h e with NRSAQ scores tending to

M a l 1 Mode12

0.75

0.84

SESSION 3 1 -1.m

P 6.63

4.38

-1.39

SESSION 4

TYPE * SESSION 2

TYPE ' SESSION 3

s8 P 13 se 0.9 <O001 4.77 0.91

1.14 0.0001 6.54 124

0.76 0.0688 0.55 1.16

-247

decrease. Significant decreases in NRSAQ scores occurred at S2 and S3 (Mode11 , p4.03,

p=0.01), but the rate of change was different for cases versus controls only at S3 (Model 2,

Type*Session3, p = 0.02). Generally, it appears the overall change over time can be attributed to

the cases, although the interaction tems are not significant except for at S3. Retum to work

status did not significantly contribute to the prediction of an NRSAQ score (Model 3, p = 0.22).

TABLE 9A - Summary s t a t i s t i c s f o r Act iv i ty Value f o r Cases vs. Contro ls

Session

1 I 2 3 1 4

Group

Activity

FIGURE 9 - Box P l o t s o f A c t i v i t y Value

Controls

Max

w a n

Std

f o r Cases v s . Controls

Group

Cases

N

Min

Group

Conttdls Cases Controls Cases

9

3.3

9.4

6.9

1.98

Group

9.7

7.6

1.40

17.3

7.3

4.14

Controls

11

2.5

Cases

17.3

9.3

4.68

6

5.7

12

3.1

10.6

9.2

1.32

11.0

7.6

2.30

15.3

8.0

3.72

4

8.0

11.8

7.7

3.28

12

3.3

7

5.6

13

1.5

If cases were experiencing improvement in their sleep over time, one would expect the

mean activity value (AV) during their sleep period to have decreased over time as well. Since

increased activity is a reflection of more restlessness and possibly more wake time during sleep,

a smdler activity value suggests less intemipted sleep. In cases, AV was found to increase at S2

and then decrease at both S3 and S4. The lowest AV for cases was found at S1 (TABLE 9A).

TABLE 90 - GEE models w i t h Activity Value (AV) as their outcome masure

Cases and controls were found to show no statistically significant difference in their mean

activity value (TABLE 9B: Mode1 1, p = 0.83), and the rate of change over time was not

significantly different in cases versus controls (Mode1 2). Retum to work status did not have a

significant prediction effect on activity value (Model3, p = 0.64).

Outcorne Measure: AV

Covan'ates:

INTERCEPT

TYPE

SESSlON 2

SESSION 3

SESSION 4

TYPE ' SESSION 2

TYPE ' SESSION 3

Modeli

P 6.63

0.21

1.76

1.56

1.04

Mode12

se

0.71

1

0.98

0.68

0.73

P 6.72

-0.05

0.58

2.21

1.2

1.2

-0.69

Mode1 3

P

C.0001

0.8337

0.0735

0.0232

0.1527

P 7.2

-0.04

1.93

1.75

1.2

se

0.67

1.39

0.5

0.67

0.67

1.66

4.25

P

C.0001

0.9761

0.2501

0.0010

0.0751

0.2341

0.5823

se

1.59

1.12

0.78

0.58

0.61

P

<.O001

0.9681

0.0131

0.0026

0.0488

TABLE 1OA - Summary s t a t i s t i c s f o r Awakenings per Hour f o r Cases vs. Controls

Session 1 1

Group

l M a ~

1 1-71 2:i 1.6 Uean 0.6 0.8

Std 0.57 0.78 0.63

Awakenings per hour

cases

2

Group

N 9 11 6

Min 0-0 0.0 O. 1

FIGURE 10 - Box P l o t s o f Awakenings per Hour f o r Cases vs. Controls

Ifsleep was improving over t h e , the number of awakenings per hour should have decreased

3

Group

accordingly. The greater the number of awakenings during a sleep penod, the more "unrefieshed"

a person is expected to feel the next rnoming. The number of awakenings in cases was found to

increase at S2 (0.8) and remained slightly higher at S3 (0.8) and S4 (0.7) when compared to a mean

AH of 0.6 at S1 (TABLE 10A) but, in both the graph and the model, these ciifferences are clearly

overwhelmed by noise.

4

Group

TABLE 106 - GEE models w i t h Awakenings per Hour (AH) as t h e i r outcome measure

Outcorne Measure: AH

Covariates:

INTERCEPT

TYPE

SESSION 2

B 0.6

-0.08

0.1 6

SESSION 3

SESSION 4

TYPE ' SESSION 2

TYPE ' SESSION 3

GEE results show that mean awakenings per hour could not statistically distinguish cases

kom controls (TABLE 10B: Model 1, p = 0.76) and that changes in AH over time were not

0.41

0.18

TYPE ' SESSION 4

RTW

significantly different in cases versus controls (Model 2). Retum to work did not contribute to the

0.1 61 0.23

1

prediction of awakenings per hour (Model 3, p = 0.17), but once we have accounted for r e m to

0.16

0.12

0.43 0.1707

0.4ïïï

work statu the d

4-59

.fference in AH between cases and controls approaches significance @ = 0.06) and

0.0102

0.1416

the overall change in AH at S 2 and S3 become statistically significant (Model 3, at S2 p = 0.04, at

TABLE 11A - Summary s t a t i s t i c s f o r Awakening Minutes f o r Cases vs. Controls

0.53

0.08

0.1

4-14

Awakening minutes

0.19

0.15

0.31

0.29

Ses

1 Group 1 Group

1

Ln c o n t r y casesl l;ntr&l casesl2

O .O 0 .O 0.5

Max 3.8 4.8 3.3 7.0

0.0050

O.Si55

0.7414

2

Group 1 Group

0.6171 1

0.58

0.3

Mean

Std

0.16

0.19

0.0004

0.1188

1.9

1.32

2.0

1.93

2.0

0.89

3.5

2.03

2.4

0.53

3.5

2.99

- - -

2.7

1.67

4.0

3.33

FIGURE 11- Box P l o t s o f Awakening Minutes f o r Cases vs. C o n t r o l s

Mean awakening minutes represents the average amount of time a subject stayed awake

during all of their wake periods (that occurred during the sleep interval). The larger the AM, the

more trouble the subject had falling back to sleep once awakened during their sleep. We therefore

would expect AM to decrease over time. Counter-intuitively, AM for cases was found to be lowest

at Sl(2.0) cornpared to al1 other sessions (TABLE 11A: 3.5 at S2,3.5 at S3, and 4.0 at S4).

TABLE 11B - GEE models w i t h Awakening Minutes (AM) as t h e i r outcome measure

The results of GEE Model 1 showed a statistically significant difference in AM by "Type"

( TABLE 1 1B : p = 0.02) with cases expenencing more AM compared to controls. The rate of

change in AM over time appeared to be similar for both cases and controls (Model 2). Awakening

minutes was not significantly affected by r e m to work status (Model 3, p = 0.35).

TABLE 12A - Summary s t a t i s t i c s f o r Sleep Minutes f o r Cases vs. Controls

I Session

- --

Group Group Group GrOUp

Controls Cases Controls Cases Controls Cases Controls Cases

sleep N 9 11 6 12 4 12 7 13 Minutes

Min 352.5 304.5 286-5 282.5 422.0 296.5 291.0 219.0

Mean 443.8 427.8 428-7 394.5 476.5 392.6 418.1 393.3

Std 49.15 57.63 79.52 69.26 62.36 68.84 62.13 74.71

FIGURE 1 2 - Box Plots of Sleep Minutes for Cases vs. Controls

CAWP Controls Cases Contmls Casas ~ 0 n t r o l s Garer Controls Cases SESÇION 1 1 2 2 3 3 4 4

Sleep minutes in cases was found to be greatest at S 1 (TABLE 12A). There sleep minutes

dropped fiom S 1 to S2 and theil remained quite stable over the last two sessions.

TABLE 12B - GEE models w i t h Sleep Minutes (SM) as t h e i r outcome measure

Outcorne Measure: SMI Modell 1

1 I I I

TYPE 1 -29.071 25.151 0.2461 1 -25.48

CovarÏates:

INTERCEPT 13

444.7

SESSION 2

SESSION 3

SESSION 4

TYPE ' SESSION 2

TYPE ' SESSION 3

Sleep minutes did not significantly differ in the two study groups (TABLE 12B: Model 1,

p = 0.25) and over time (Model 2). RTW status was found to have a significant relationship with

SM (Model 3, p = 0.01). Cases who had retumed to work slept 38 minutes less than cases who had

not rehimed to work, on average (Model 3: P for RTW).

se

185'

-13.88

-2026

TYPE ' SESSION 4

RfW

-18.82

0.41

P t O û û l

10.92

16.98

B 443.04

11 -56

0.2041

0.2341

-8.67

-1 -76

0.1031 -19.36

-9.6

-26.71

TABLE 13A - Summary s ta t i s t i c s f o r Sleep Efficiency for Cases v s . Controls

1 Session

Sleep Percent

-- -

Group

~ o n t r o l s l Cases

-

Group Group

~ o n t r o l s l Cases ~ o n t r o l s l Cases

Group

Min 93.2

WX 99.9

h a n 97.1

FIGURE 13 - Box Plots of Sleep Efficiency for Cases vs. Controls

85.0

99.8

96.6

Sleep efficiency was found not to significantly differ between the two groups

(TABLE 13B : Model 1, p = 0.56) and cases and contTols did not show differential changes in SE

over t ime (Model 2). Return to work stahis was not a si@cant predictor of sleep efficiency

(Model3, p = 0.25).

Std 2.151 4.22

93.6

99.5

96.6

86.4 92.9 92.1

99.4 96.3 99.3

94.3 94.5 96.0

2.37 4.17 1.511 2.68

TABLE 138 -GEE models w i t h Sleep Efficiency (SE) as their outcome measure

Sleep efficiency represents the proportion of sleep t h e compared to wake time during a

sleep interval. We would expect efficiency to increase with improved sleep. Cases showed the

highest sleep efficiency at S 1 (TABLE 13A).

As mentioned earlier, cases appeared to v a q greatly with respect to their pain intensity and

fùnctional disability scores at S 1 (Le. baseline study). This early heterogeneity within cases was

more closely examined by dividing the cases into two groups, based on their return to work status

(i.e. RTW or M T W ) at each session. As shown in the summary statistics the number of RTW and

NRTW cases at each session is changing. As cases return to work they switch groups (Le. at each

session the RTW and NRTW cases are not the sarne cases).

Outcome Measure: SE

Covariates:

INTERCEPT

P/PE

SESSION 2

SESSION 3

Mode13 Mode12

B 95.52

0.17

-218

-1.71

Mode11

S 97.05

-0.29

-0.23

-221

se

1-94

0.9

0.96

0.48

P CO001

0.5619

0.1585

0.1835

se

0.75

1.49

0.84

P C.0001

0.8493

0.0226

0.0003

B 97.17

-0.58

-1.57

-1.09

P <O001

0.8493

0.7872

se

0.78

1

1.1 1

0.83 0.951 0.0198

TABLE 14A - Summary s t a t i s t i c s f o r Roland Score fo r Cases NRTW vs. Cases RTW

I session I

Roland

L 1

Returned t a Work

MO / Yes

Plo ts o f Roland Score f o r

2

Returned t o Work

NO 1 es

Max

Mean

Std

RTW 1 4

1 1

* - - - - -+ O--....

I I 1 1 f I 1 1 I I I 1 I I 1 I 1 1 1 + 1 I 1 . - - - - - . 1 1

l I 1 + 1 t I 1 1 I I I l I 1 I l 1 1 I I 1 1 I I 1 1 1 1 1 1 1 I +----.+

1 1 I 1 I

1 + - - + *---..+

1 I 1 1 I 1 1

I * I I I 1 1 1 1 1 1 1 1 1 1 I 1 I I *.....+

- - - -+ - - - - - - - - - - -+ - * - - - - - - - - -+ - . * * * -

NRTW nTW NRTW 2 2 3 4 11 3

3

Returned t o Work

NO 1 es

21 .O

14.0

5.73

Cases

O

--

4

Returned t o Work

NO 1 es

NRTW vs. Cases RTW

7.0

4.0

2.58

1 1 I 1 1 1 I l 1 +----.+ +---.-+

1 I 1 + 1 I I 1 1 O - - - . - .

I I +- - - - -+

I I 1

NRTW RTV 4 4 3 11

20.0

13.8

6.13

22.0

5.9

6.32

19.0

15.3

6.35

21.0

5.7

6.00

19.0

14.7

7.51

20.0

5.0

5.60

FIGURE 14B - Graph o f Roland Score for Cases NRTW (No) vs. Cases RTW (Yes), w i t h upper and lower 95% confidence limits

M ean Roland Score by Session

Session

Retumed to Work No e43-0 Yes

At ali sessions, NRTW cases showed more functional disability when compared to RTW cases

(TABLE 14A) The difference in RS between theses two groups was found to be very similar to the

differences in RS between cases and controls (Le. out of a possible RS of 24, RS in NRTW cases

were 7 to 10 points higher than RS scores in RTW cases, and RS scores in al1 cases were 7 to 11

points higher than RS scores in controls, which is regarded as clinically significant) (Stratford,

1996). As seen in the graph (FIGURE 14B), RS within each of the two groups did not show much

change over the four sessions (Le. in NRTW cases RS ranged fkom 14 to 15, in RTW cases RS

ranged fiom 4 to 6). At al1 sessions NRTW cases rated themselves as expenencing greater pain

compared to RTW cases (TABLE 1 SA). RTW and NRTW cases showed the Ieast difference in PI

scores at session 2 (FIGURE 15B) but Uiterestingiy, while the RTW cases showed m e r

improvement in PI after S2 , the NRTW cases reported continued increases in PI &er S2. The

largest difference in PI scores between RTW and NRTW cases was found at S4 when NRTW cases

65

appeared to be expenencing the greatest pain. However, given there were only 3 cases not rehuned

to work at S3 and S4, this fïnding should be interpreted with caution.

TABLE 148 - GEE mode1 with Return to Work as t h e outcome measure for Cases NRTW vs. R M I , with Roland Score as a covariate

Cases

SESSION 2 1 2.45

Co-variates:

INTERCEPT

ROLAND

SESSION 3 1 2.94 1 1.11

SESSION 4 1 2.53 1 1.38

P 2.43

-0.36

NRTW cases reported clinically and statisticaily greater functional disability compared

cases (TABLE 14b: p = 0.04).

TAEKE 15A - Summary s t a t i s t i c s for Pain In tens i ty ( P I ) f o r Cases NRTW

se

1 .S

O. 18

Cases

P

O- 1052

0.0414

to RTW

RTW

I session I

1 N

Max

Mean

Std

Returned t o Work

NO ye s

101 4

97.0

70.3

15.92

Returned t o Work

63.0

50.0

15.03

No

4

es

11

Returned t o Work

83.0

60.8

23.99

No

3

Returned t o Work

Yes

12

NO

3

80.0

49.8

16.41

~e s

11

97.0

71.3

28.92

- -

83.0

40.3

20.18

100.0

82.3

22.50

63.0

40.6

12.96

o f Pain I n t e n s i t y f o r Cases NRTW vs. Cases RTW

- - - - - - - - - - - -+ - - - * - - - - - - -+ - - - - - - - - - - - * - - - - - - - - - - -+ - - - - - - - - - - - * - - - - - - . - - - -+ - - - - - - - - - - -+ - - - - - - - - - - -+ - - - - - - - - - - -

R E N R N NRTW ATW NRTV RTV NRTW RT* MT* RTW SESSION

N 1 1 2 2 3 3 4 4

11 4 4 11 3 12 3 11

FIGURE 150 - Graph o f P a i n I n t e n s i t y Score f o r Cases NRTW (No) vs. Cases RTW (Yes) , with upper and lower 95% confidence l i m i t s

2 3

Session

Returned to Work No Yes

TABLE 156 - GEE mode1 w i t h Return to Work as t h e outcome measure f o r Cases NRTW vs. Cases RTW, w i t h Pain I n t e n s i t y Score as a covariate

The GEE results did not show a statistically significant relationship between PI scores in RTW

cases versus NRTW cases (FIGURE 15B and TABLE 15B: p = 0.47).

There was obvious interest in investigating whether there were clinically andlor statistically

significant differences in actigraphy data between NRTW and RTW cases. However, due to small

Co-variates: I P se

1.4

0.02

0.7

0.85

0.79-

INTERCEPT

ROLAND

SESSION 2

SESSION 3

SESSION 4

P

0.9760

0.471 5

0.01 08

0.0121

0.0069

-0.04

-0.01

1.79

2.14

2.15

68

sample sizes these sleep measures codd not be M e r investigated (e-g. at S3 sleep data is available

for only 1 NRTW case).

69

SUMRlARY OF FlNDINGS

Compared to age and gender matched controls, workers with low back pain were found to

be significantly more depressed and more anxious, and they reported a statistically significant greater

number of sleep disturbances on the Sleep Assessment Questionnaire and on the non-restorative

subscale of the Sleep Assessment Questionnaire. Actigraphy measures of activity value,

awakenings per hour, sleep minutes, and sleep efficiency did not discriminate LBP workers f?om

"pain-fiee" contro'ols. LBP workers were found to experience statistically significant longer wake

periods d u h g their sleep intervals.

Changes in SAQ scores over time did not differ in cases versus controls. The changes in

cases' non-restorative SAQ score at S3 and their somatic BDI score at S 2 were found to be

significantly different fiom the changes that occurred in the controls during these sessions. The

sleep measures, as recorded with actigraphy, did not change differently over time in cases versus

controls.

Retum to work status was not a significant predictor of self reported sleep disturbances (i.e.

SAQ and non-restorative SAQ scores) in workers with LBP. Sleep minutes was the only actigraphy

measure that was significantly affected by the cases' return to work, with those rehiming to work

sleeping approximately 38 minutes less per sleep intemal, cornpared to cases who did not retum to

work.

While cases who had not retumed to work were found to report significantly greater

disability compared to the cases who had retumed to work, the difference in pain intensity between

these two groups was not statistically significant.

DISCUSSION

Of the four cases who had not returned to work at session 2, three were still off work at

subsequent study sessions, suggesting that rather stable '%hronicity" has set in at approximately three

months post-injury. These fïndings are consistent with the fiterature on return to work in LBP

patients. LBP patients who have not returned to work at three months post-injury are usually

classified as having chronic disability, compatible with chronic pain syndrome (Frank, 1996). Our

final assessment occurred at approximately five months post-injury, and while 20% of the workers

had not returned to their regular duties, two of these three workers had returned to either modified

duties, shorter work days, or a combination of both. Alternative approaches would have been to

consider those who indicated a retum to "special work arrangements" as returned to work cases, or

to categorize them into a completely separate group (Le. "partially disabled" cases). LBP studies

which have considered return to work status have not consistently used one approach over another.

In this study the sample size was too small to consider analyzing the data using either of theses

alternative approaches.

As demonstrated by the Pain Intensity and Roland scores, the cases were definitely different

fiom controls with respect to their experience of pain and functional limitations. At the tirne of the

initial assessrnent the cases had a mean RS of 1 1, out of a maximum possible score of 24, this score

dropped to 8 at S2 and remained f&Iy constant over the next two study periods. These findings are

consistent with previously reported initial Roland scores (i.e. 10.1 and 1 1.4), and similar to observed

changes in Roland scores (i.e. RS dropped fiom 10.1 at the initial assessment to 7.1 at three weeks

follow-up) in LBP patients (Deyo, 1986). In cases, PL scores were also greatest at S 1 cornpared to

al1 other sessions. We would expect pain intensiw to decrease over tirne; however, PI scores

70

remained quite steady &er S2 (PI = 53) and at S 4 (PI = 50) were slightly greater than the PI scores

at S3 (PI = 47). The increase in mean pain intensity at S4 did not result fkom increased pain in only

a few of the cases. Eight of the fifteen cases actually reported greater pain at S4 compared to S3.

The increase in the PI score at S4 does not appear to be large enough to be of clînical significance,

and may indicate that most of the recovery from LBP occurs during the first three months post-

injury, after which point Little change is observed, but some pain persistence or recurrence is

comrnon. The largest changes in both the PI score and the RS are seen between S1 and S2 (i.e.

between three and thirteen weeks post-injury), when the majority of the cases are also retuming to

work, as would be predicted fkom previous studies of the "natural history" of LBP.

A statistically significant difference was found between cases and controls with respect to

their mean scores on the Hospital Anxiety Scale. the Beck Depression Inventory and the somatic

component of the Beck Depression Inventory. Afthough the results of the HAS scores in this study

found cases to be more anxious than controls, the case "group" wodd not be considered overly

anxious according to Zigmond's categorization of HAS scores. He found a HAS score of 7 or less

best predicted ccnon-cases" of clinically diagnosed anxiety (where patient i n t e ~ e w s were used as

the gold standard) (Zigmond, 1983). Cases were also found to be more depressed than controls

(according to their BDI scores) but they would not be classified as clùiically depressed if, as

suggested by Beck we were to use a cutoff score of 10.9 for the classification of "minimal

depression" (Beck, 1 988). HAS and BDI scores in cases and controls did not appear to show much

change over time. The cases' BDI and SBDI scores did drop slightly at S2 compared to S 1, during

which time pain intensity and functional ability also showed the greatest hprovements. Their

anxiety scores did not appear to be affected during this time and dropped only slightly between S 2

72

and S3.

Return to work was not found to be significantly associated with either total BDI or anxiety

scores, but a statistically significant relationship was found between r e m to work status and SBDI

scores. The statistically significant drop in SBDI scores associated with retum to work is not

surpnsing since the items in the somatic component of the Beck Depression Inventory address the

subjects' physical well-being, which we expect would improve before cases attempted to retum to

work. Depression and aaxiety scores did decrease over time as cases retumed to work; however,

these changes were not statistically significant.

The outcome variables discussed thus far appeared more or less stable after S 2 . Yet both

pain intensity scores and anxiety scores did not behave as expected at S4. Considering the rather

small sample size in this study, one might speculate that the unexpected increase in these scores at

S4 may result fiom "missing data bias". It is possible that at S4 the PI score may be missing for one

of the cases who had a very iow PI score at sessions 1,2, and 3 (Le. the exclusion of this case's PI

score at S4 may result in the mean PI score for al1 cases to appear to increase slightly in remaing

cases), or the mean H M score at S4 may not include a case with low anxiety due to missing data.

After reviewing individual case scores this does not appear to be a likely explanation for these

findings. As noted earlier, eight of the cases did report an increase in pain intensity at S4 compared

to 53. Compared to HAS scores at S3, scores at S4 were also greater in nine of the cases. Therefore

these unexpected findings do not result fÏom differential non-inclusion of data by time alone.

Since cases are experiencing maximum recovery during the time between the S 1 and S2

assessments, as indicated by their self-rating of pain intensity and functional ability, ~ e e n we would

also expect that if sleep rneasures paralleled these changes they would show m a x i m m changes

73

during this period.

Cases reported a statistically significant greater number of sleep disturbances when compared

to controls. In fact, the cases mean session SAQ score which ranged fiom 21 to 23 is comparable

to the mean SAQ score of 26 found in patients (n = 289) referred to the Sleep Disorders C h i c (at

the Toronto Hospital, Western Division) for an evaluation of their sleep disturbances and

consequently diagnosed with a sleep disorder (Le. according to the International Classification of

Sleep Disorders) (Thorpy, 1990). Again the SAQ scores did not show much change over the four

sessions but a slight increase was noted fi-om S3 (SAQ = 21) to S4 (SAQ = 23). It is possible that

the cases did not experience any changes in their sleep during the study period or that the SAQ is

no t a sensitive rneasure of the types of changes in sleep that are occming in the LBP cases, at least

when studied at these points in the natura! history of the condition. The SAQ has yet to be evaluated

for its sensitivity in detecting irnprovements in sleep quality. It is also possible that the SAQ scores

did not change over thne because any major changes in sleep expenenced by the cases occurred pnor

to baseline assessrnent (Le. in the first three weeks after onset of LBP). While interviewing cases for

recruiîment purposes many cornmented on the improvernent in their sleep they had expenenced over

the previous few weeks. Whether or not the cases expenenced any improvement in their sleep at any

time during recovery, it is interesting to note that according to their SAQ scores at S4 they continue

to have clinically significant sleep disturbances at approximately four to six months post-injury.

Since we do not have any measures of sleep in the cases pnor to their injury, one couId also

speculate that the SAQ scores did not reveal any signincant changes in sleep during the study penod

because cases were already experiencing sleep disturbances long before their work-relat ed inj ury.

This is defïnitely a possibility when one considers that seven of the fifieen cases reported they

74

worked shifts. Sleep disturbances in shift workers have been related to increased nsk of employee

accidents. Smith found an increased incidence of work-related injuries in &if€ workers compared

to day workers in the food processing industry (Smith, 1982).

The controls' SAQ scores ranged fiom 12 to 19, somewhat higher than the SAQ score

previously reported in a control group fiee of sleep disturbances (Le. SAQ score of 10.8, n = 30).

In the present study, controls were not screened with respect to their sleep patterns or behaviour and

thus it is likely that some of the controls were experiencing various problems with their sleep that

are common in the general population (Kryger, 1989). Controls qualified to take part in the study

if they were "pain-fkee7' regardless of whether or not they reported any difficulties with their sleep.

If some of the controls were having problems sleeping, it is likely that their disturbed sleep

minimized any observed differences in the sleep measures of cases versus controls.

As we would predict, the NRSAQ scores show workers with LBP awaken feeling more

unrefkeshed and unrested compared to controls. Cases showed a small but steady decrease in

NRSAQ scores during recovery. This suggest that the NRSAQ subscale of the SAQ is a more

sensitive measure of the changes in sleep that the cases expenenced.

While cases were experiencing pain and functional disability, and showed a statistically

significant difference £iom controls with respect to their selfreports of anxiety, depression, and sleep

disturbances, the only actigraphy measured sleep parameter these differences appeared to influence

was mean awakening minutes. An improvement in sleep could have been reflected by any of the

following trends during sleep; a decrease in activity value, a d o r number of awakenings per hour,

and/or awakening minutes, an increase in sleep minutes andlor sleep efficiency. The cases showed

no such trends. The changes in these sleep measures over the four sessions are minimal (AV ranged

75

fkom 7 to 9, AH ranged from 6 to 8, AM ranged fkom 2 to 4, SM ranged fiom 393 to 428, and SE

ranged from 94 to 97), and do not appear to be of any clinical signiscance. In fact, the changes over

time in these sleep measures are also not in the hypothesized direction. At S2 activity value, number

of awakenings, and awakening minutes increases slightly and sleep minutes and sleep efficiency

decrease slightly. Overall, cases did show statistically significant longer wake penods compared

to controls. However, at S1 where we would expect the ciÏEerence in awakening minutes between

cases and controls to be the greatest, the number of awakening minutes in the two groups is the

same. These fïndings are consistent with those of Lavie who did not fhd a statistically significant

differences in actigraphy measured sleep efficiency and activity value between chronic LBP subj ects

and controls (lavie, 1992).

Sleep minutes was the only sleep variable affected by return to work status. As the cases

retumed to work they appeared to sleep less. As cases recover fiom their LBP we would expect a

greater portion of their sleep interval to consist of sleep t h e compared to wake time, but Secause

they may have to awaken earlier when they return to work, the number of sleep minutes may actually

decrease.

The differences between cases and controls in activity value (0.2 1), awakeniogs per hour

(-0.08), awakening minutes (1 .O6), and sleep efficiency (-0.58) (Le. P estirnates for Type in Mode1

1 of GEE Tables) are quite minimal and therefore not clinically relevant. The difference in sleep

minutes (-29.07) between cases and controls is also of little clinical reIevance when one considers

that retum to work status is primarily responsible for this difference via a direct effect on workers

daily schedules.

The measures of pain and fimctional ability have indicated that the rate of recovery fkorn

76

LBP, as measured by pain and functional statuç changes in these subjects, is greatest between three

and thiaeen weeks, compared to later changes. Within this period, LBP cases appeared to reach a

plateau in t-s of any improvement in pain and functional ability. When the case group was more

closely examined, the PI scores in NRTW cases showed a substantid increase in PI at S3 and again

at S4. Perhaps these cases have aven up on any rehabilitation programme by this t h e or possibly

the mechanisrn of pain perception in these persons has become arnplified as a step towards the

development of chronic pain syndrome. There were three cases who had not retunied to regular

work duties at the final assessment. Two of these individuals reported near maximum Pain Intensity

and Roland scores at baseline (Le. PI scores of 93 and 97 and RS's of 21 and 19), thus suggesting

that they could possibly have been identified and selected for intensive treatment at approximately

six weeks post-injury on the basis of these scores, presuming that larger-scale studies replicate this

finding .

The lack of significant differences between the sleep variables scores of cases and controls

may be partly the result of the variability in pain intensity and functional disability experienced by

the cases, particularly in the earlier measurement sessions. The difference in Roland scores between

RTW cases versus NRTW cases was found to be statistically significant. The difference in pain

intensity scores between these two groups was not statistically significant but NRTW cases did

report greater pain at al1 sessions and their pain intensity scores increased substantially at S3 and S4,

whereas pain intensity in RTW cases remained quite stable after S2 (Le. PI in RTW at S4 = 41, PI

in NRTW at S4 = 82). Unfortunately, due to the small number ofNRTW cases, it was not possible

to fonnally analyze the sleep measures in RTW cases versus NRTW cases.

As noted in the literature review there appears to be an important but unclear relationship

77

between depression, anxiety, sleep and pain. The rather small sampie size in this study made it

impractical to actually analyze this complex relationship by incorporating al1 of these variables into

one model.

STRENGTHS AND WEAKNI3SSES

While selectùig a homogeneous gmup of study subjects allows us to rninirnize the number of

possible confounding variables, such a strategy also restncts the generalizability of the study results.

An important question to consider is; are the low back injured workers who we recniited from the

CBI representative ofmost workers who develop LBP following a work related injury? With respect

to the self reports of pain and disability, the cases do appear to represent an adequate range of LBP

seventy. The study subjects however, were d l males, expenencing a low back injury for the first

tirne, had al1 filed a claim with the Workers Compensation Board and were involved (for varying

arnounts of tirne) in a rehabilitation programme (which included physical therapy as well as

educational programmes) at the time they were recniited into the study. Compared to the 'iisual

care" (Le. which could include physiotherapy, visits to the family physician, or chiropractie care),

the Community C h i c programme which the cases were attending has not been shown to

significantly affect fimctional status and pain measurements (Sinclair, 1 997) but, as noted earlier,

Coste fomd compensation status and previous chronic episodes of LBP to delay the recovery of

patients with acute localized non-specific back pain (Coste, 1994).

By choosing to recruit cases fiom the CBI, it made it difficult to study cases as soon after

their injury as was initially planned While we had hoped that our initial assessrnent would take

place sometime befween 3-6 weeks post-injury, the range for the baseline study was actually 3-8

weeks, with a mean of 6 weeks post-injury. It appears that most of the cases who agreed to

78

79

participate did not enter the Comunity Clinic programme immediately following theîr injury, or

that they had been involved in the programme for sorne time before they decided to take part in the

study. It is possible that significant changes in sleep may have occurred prior to 6 weeks post-injury.

By recruiting cases fiom a family physicians' office, it may have been possible to identify cases at

an earlier post-injury date. However, if we were to identiQ these cases at a very early stage of their

LBP, we would require much larger sample sizes to ensure that a fair portion of the injured workers

had not returned to work at three rnonths post-injury.

During the course of this study we did not collect adequate information on psychosocial

factors and compensation status. These variables appear necessary for a thorough understanding of

return to work status in workers following a soft tissue injury. Cats-Bad found job characteristics

such as work history, occupation, and job satisfaction to be significantly associated with disability

(Cats-Baril, 199 1).

This study was unique in its atternpt to measure changes in sleep measures associated with

recovery fiom a low back injury. It was therefore difficult to accurately estimate the necessary

sample size requirements. Larger sample sizes are required to compensate for the heterogeneity in

the cases' self reported pain and disability and the night-to-night variability in these sleep measures,

especially since each subject's sleep was evaluated in a relatively uncontrolled setting (i.e. the

subject's own home as opposed to a sleep laboratory). A specific bedtime was not enforced and

subjects were advised to follow as normal a routine as possible. The subject's sleep pattern on any

night could be affected by severai factors (e.g. Visitors to their home, staying up to watch a

television programme, telephone interruptions, the demands of young children in the house, or by

at an a lam clock the next rnoming). Given the sample size of this study and taking into account the

80

repeated measures design, we would have required cases and controls to di& by 3.3 in AV, 0.75

in AH, 1.2 in AM, 2.9 in SE, and 72.8 in SM to show statistically sipnificant differences between

the two study groups (where a4.05, and power 4.90) (Diggle, 1994).

RECOMMENDATIONS FOR FZJTURE STUDIES

The results of this study raise some important issues and implications for future research.

Since recovery is greater between three and thirteen weeks post-injury than later on, any attempts

at identimg LBP cases who will potentially become chronic LPB cases should focus on this early

penod. It appears that pain and functional ability measures during this time may be quite useful for

this purpose and may allow us to select those patients who require more intensive treatrnent.

Larger sample sizes are defhitely required in order to dichotomize cases on the ba i s of

return to work status and to be able to examine more closely the complex relationships between sleep

and anxiety, sleep and depression, and sleep and pain.

It may also be beneficial to perform these shidies in a more controlled enwonment (i.e.

a sleep laboratory) where subjects c m be monitored through the night by a technician and where al1

subjects would be exposed to similar sources of measurement errors (i.e. same mattress, similar

interruptions through the night, and possibly a fixed sleep and wake up time).

Baseline sieep measures should occur as early as possible following the injury. It is apparent

f?om the cases' comments that sleep disturbances are greatest in the first two weeks following their

injury. It is possible that important changes in sleep are occurring during these first weeks.

Measures of sleep physiology should be recorded so that changes in EEG fiequencies can

be examined more closely. It is important to consider that the sleep measures which were evaluated

(i.e. sleep minutes, sleep efficiency, nurnber of awakenings, awakening minutes and activity value)

may not be the sleep measures that are behg affected in LBP cases. The total SAQ scores were

basically stable over t h e while the NRSAQ scores did show a steady decrease over the four study

sessions. The six items of the NRSAQ subscale focus on sleep quality - for example, how

81

82

refieshing one's sleep is and how rested one feels the following moming. An evaluation of these

changes in sleep should considermeasures of slow wave sleep as well as measures of EEG fiequency

(i.e. alpha activity) during sleep, neither of which is meamrable using at an actigraph. In a recent

study where pain stimuli was applied during slow wave sleep, muscle pain stimuli resulted in a

decrease in delta (0.5 to 3.5 Hz) and sigma (12 to 14 Hz) and at an k e a s e in alpha (8 to 10 Hz) and

beta (14.5 to 25 Hz) frequencies. Different types ofpain stimulation (i.e. resulting in joint pain and

cutaneous pain) were found to produce different EEG responses @rewes, 1997). EEG recordings

during sleep were recorded in these subjects (using medilog recorders). The analysis of this data

would not only allow us to examine the EEG fiequencies of subjects experiencing LBP but also

allow us to investigate changes in EEG fiequency during recovery.

Finally, while we attempted to fom a homogeneous group of pain subjects, with respect to

site of pain (i.e. LBP) and number ofdays experiencing pain at the initial assessment (Le. three-eight

weeks post-injury), we did not take into consideration the severity of the worker's pain at baseline.

That is to Say, individuals who have discontinued working due to low back pain do not necessarily

experience the same amount of pain andor fùnctional disability. Perhaps when allning to identiQ

LBP subjects who will become chronically disabled following their injury, one should sub-

categorize different groups of subjects based on pain seventy (e-g. usùlg a self-rated pain scale), as

early as possible.

APPENDIX 1

A Study of Sleep and Musculoskeletal Pain in Wotkers Following a Soft Tissue lnjury 84

Demosra~hic Profi le Fax Sheet

Client's Initiais 7 1 SIX CI Date of Birth first middle last F I M day month year

Area code

Client's Telephone No. ( I I 11 - 1 I I 1 - I I

Today's Date 7 1 Social lnsurance Number

day month year CB I Diagnosis:

Date of lnjury -1 I I I I

day month year

I l I

(A) Did the client receive baseline questionnaires ?

NO [I YEÇ n Date Received -1 ID. NO. -1 day rnonth year

6 Check / reason(s) why the client DID NOT receive questionnaires. b Client Refused to Participate a AbS:mzhSpinal injury I I Injury occurred more than 7 weeks ago n 1 1 Other (please specify):

(C) Did

NO

the client receive follow-up questionnaires 5 weeks afier baseline ?

FI YES FI Date Rewiwd I.D. No. r-1 I I I i

Date Retumed 1 1 1 1 day month year

(D) Is client qualified and willing to participate in the EEG study ? NO a YES 17 If NO, check / applicable reason

17 Client Refused to Participate 1-1 Low Back pain IS NOT pnrnary injury

Client is Fernale [ I lnjury occurred more than 7 week ago

r i Client is NOT a WCB clairnant [-1 .client is NOT btwn. 18 - 50 pars of aga

17 Client has concurrent n

FI Client ha; Neurologie Deficit

University of Toronto Centre for SIeep and Chronobiology

The Toronto Hospital, Western Division 399 Bathurst Street Toronto, On tario Canada iM5T 2S8 Tel: (416) 603-5109 Fax: (416) 603-2388

164 Qneen Street East, BI01 Brampton, Ontario Canada L6V l B 4 T elephone: (905) 450-5990 I

. -

Consent for Participation in a Sleep Study after Low Back Pain

1, , consent to parricipate in a study of sleep patterns after Iow back troubles. This study is to be conducted by Drs. H. Moldofsky, J. Frank G d associares at the Canadian Back Institute in Brampton.

I understand thac in order ro assess the effea of the injury on sleep, I will have my sleep monitored for several nighrs in three night blocks. This will involve monitoring my brain waves wirh elemodes amached by tape or glue, and my musde motion with a device simiiar to a watch. My sleep will be monirored for nine nights in four bloclis, ac. approximateIy 5 weeks, 12 nreeks, 20 weeks and 28 weeks beyond my injury. These sleep monitoring sessions .

will occur in my home. I will also be requested to complete evening and m o r b g questionnaires pertaining to my symptoms throughout a two-week period. I will have an assessrnent of my general hedth, GU OUT some ques~iomaires of my pain and other symptoms, and have a measuremenr of my pain wich a pressure gauge (Dolorimeter). 1 understand that there are no known risks to this equipment, except possibly some skin irritation at the site of elearode attachment

I

In order to evaluace rny sleep, I understand that I will be reQuested not ro take any of the following dnigs, if my doaor agrees: sleeping piIls (such as halcion), tranquillizers (nich as vdium), muscle relaxants ((nich as flexeril), anticlepressants (such as elavil), narcotics (such as codeine or darvon) for one week prior to the sr= of the sleep measurements study and during rny participation in this mdy. I dso understand that medications like aspirin, tylenol, and anti-inflammatories (nich as Voltaren, Motrin etc.) are dlowed during the snidy period. 1 dso understand chat 1 should not use alcohol and caffeine the day before my deep mdy. Should 1 requise any medications for any reason I agree to inform the study interviewer.

If any problems arise while 1 am in the study, 1 will c d Dr. Moldofsky at 603-5109, Dr. John Frank at 927-2027 or the Canadian Back Institure at 450-5990 immediately.

1 understand that my anonymity wi.& be safeguarded ia any ~bsequenr professional presentations or publications of the results of the investigation. 1 undersrand that my pmicipation is voluntary and ~ h a t I may discontinue my '

participation at any rime without prejudice and without it &cring furrher medical are. 1 dso undersrand thar the panicular information 1 give in rhis smdy wiIl noc be shared with the WCB. This midy will in no way a f f e a my WCB daim-

1 understand that I will receive a tord of $50.00 per recording session as an honorarium for my participation in the snidy, to a total of $500.00 to assix me wich any corn iccurred as a result of attendhg the study. I understand that 1 may receive the renilts of rhis study once the study is complete.

University of Toronto Centre for SIeep and Chronobiology

The Toronto Hospital, Western Division 399 Bathurst Street Toronto, On tario Canada MST 2S8 Tel: (416) 603-5109 Far: (416) 603-2388

164 Queen Street East, BlOI Brampton, Ontario Canada L6V 1B4 Telephone: (905) 450-5990

I have read and undemood diis consent form. My quescions have been ansa-ered and 1 freely and volunrarily choose to parricipare.

Patient's Signature

Wicness

Date

Date

Universitg of Toronto 57

. -g OFFICEOF RESEARCHSERVICES

ES2u

A~groval b~ Review Cornmittee on the Use of Human Subiects -

Principal Investigator :

Review Committee .

Documents SubmÏtted to Review Cornmittee

Subjects

Procedures

Method for Obtaining Consent

Remarks

Date of Approvai

Protocol Reference #226/95

Dr. H. Moidofsky, Psychiatry

A Study of Sleep and Muscoloskeletal Pain in Workers Following a Sof t Tissue lnjury (Amendment)

. -

Dr. P. Darby, Psychiaw

A ietter dated March 29, 1995 from A. Cesta, Study Coordinator

As approved February 7, 1994

As approved February 7, 1994, except that subjecti will now be remunerated at a rate of $56.00 per ovemight study.

The consent form will be amended to reflect the new study payment.

- *During the course of the research. any significant deviations from the approved protocol andlor any unanticipated deveIopments within the research shoufd be brought to *e attention of the Office of Research Services..

*A copy of this apptoval form is available to Review Committee members upon request.

S P h g

cc: Ms. K. Drysdale - *

Human Subjects Review Committee . .

S b w e Hall 27 King's Callege C ï I e Toronto û n k i o M5S 1Al Telephone 416/ 978-2163 Fax 41 6/ 971-2010 .

1. Ps:

2, Cs:

3. vs t-4

4, Vs t-3

5. vs t-2

6. VS t-1

7. Vs to

8. Vs t+l

9. vs t+2

APPENDIX 4

ALGORITWM USED FOR AUTOMATIC S E E P SCOIUnG

S c o ~ g is based on the following formula:

+VI41 * actiMty[t]+V[5] *activity[t+ l]+V6 * advity[t+Z]+Cs) where;

D = sleeplwake disposition at epoch t Ps = equation scaling factor Cs = equation intercept constant V[O] = coefficient at minute t-4 ......................... V[6] = coefficient at minute t+2

APPENDIX 5

Actigraph@ Activity data recordings for 3 consecutive days

200; PCDACT 150:

iso 4 LOO 501 .

--- - - - 02/11/95 O0 02 04 06 08 10 12 14 16 18 20 22 2.4

1. Briefly describe your work?

2. Do you work shifts? (Check one) YES NO

3. How many days have you been absent fkom work due to your injury? days

4. Have you returned to work? YES NO

If your a m e r to question 4 is NO, please answer questions 5 and 6. Ifyour answer to question 4 is YES, please aLlSWer questions 7,8, and 9.

Does your injury prevent you f?om retuming to work? YES NO

Have you NOT returned to work for any of the followhg reasons?

No longer able to physicaliy perform old job Your workplace was not accessible to you because of your injury Your injury made it clBicult to travel to your job Your old job was only temporary, and is no longer available

Have your returned to? Old employer New employer Became self employed

1s the job you retunied to? Exactly the same as your old job, including job, tasks, and hours Similar, but not identical A M i r e n t job

Have you retunied to? A flexible work schedule Changes to the layout or equiprnent in your work area special training Some other special arrangements to help you get back to work

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