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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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