SLEEP 2011 Abstract Supplement

B. Clinical Sleep Science III. Sleep Disorders – Insomnia
Scale (PSAS) before bedtime. HRV and EEG spectrum analyses were
conducted for the EKG and EEG data collected during the 5 minutes
prior to sleep onset and the 5 minutes after.
Results: Both cognitive and somatic subscales ratings were higher in
insomnia group. Also, insomnia group showed higher alpha power both
prior and after sleep onset, and higher beta power after fallen asleep
(C3: F=4.78, p=.037). In terms of the correlations between PSAS score
and EEG power, insomnia group showed significant negative correlation
between somatic arousal and delta power (C3: r=-.56, p=.029; C4:r=-
.53, p=.042), positive correlation between somatic arousal and alpha
power (C3: r=.57, p=.027; C4:r=.56, p=.029), negative correlation between
cognitive arousal and beta power (C3: r=-.55, p=.032; C4:r=-.53,
p=.042) before sleep onset. After sleep onset, insomnia group showed
positive correlation between somatic arousal and theta power (C3: r=.62,
p=.015; C4:r=.54, p=.038). As regarding HRV, only correlation between
somatic arousal and normalized high frequency (HF(nu)) in insomnia
group after sleep onset (r=.52, p=.049) was significant. No significant
correlations were obtained in normal sleepers.
Conclusion: The results indicate that subjective somatic arousal is associated
with cortical arousal as measured by EEG and ANS arousal by
HRV in insomnia group, but not in good sleepers. Subjective feelings
of cognitive arousal may be less associated with either ANS or cortical
arousal.
0550
PATIENTS’ ATTRIBUTIONS ABOUT THE CAUSES OF
INSOMNIA
Harvey AG 1 , Morin CM 2 , Bélanger L 2 , Lombrozo T 1 , Rifkin JB 1 ,
Talbot LS 1 , Eidelman P 1 , Beaulieu-Bonneau S 2 , Fortier-Brochu E 2 ,
Soehner A 1
1
University of California, Berkeley, Berkeley, CA, USA, 2 École de
Psychologie, Université Laval, Laval, QC, Canada
Introduction: This study investigated the possibility that the ‘folk theories’
or attributions a patient holds about their disorder may impact their
treatment preference. This is important because treatment preference
may influence engagement and compliance with treatment which, in
turn, will impact outcome. Insomnia is the focus as it is prevalent and
associated with significant impairment of quality of life. Moreover, there
are various treatment options.
Methods: Participants were 69 patients with chronic insomnia. They
completed the ‘Causal Attributions of My Insomnia Questionnaire’
(CAM-I), a questionnaire evaluating potential causal explanations/attributions
about insomnia on Likert-type scales (1 = very likely; 7 = very
unlikely). Several other assessment instruments were administered as
part of a larger treatment study (e.g., Duke Interview for Sleep Disorders,
SCID-I).
Results: Of 12 factors rated, emotions and thinking patterns were most
commonly endorsed as ‘contributing to insomnia’ (60% and 58% of
patients, respectively, endorsed these factors as ‘very likely’). Patients
were reasonably confident that targeting these factors in treatment would
alleviate their insomnia (emotions M = 5.96; SD = 1.38; thinking patterns
M = 6.00; SD = 1.25). Percentage of patients who rated that a psychological
treatment could help varied from 30% for genetic factors to
59% for emotions. Patients who rated that a biological treatment could
help varied from 19% for environmental factors to 40% for biochemical
factors. Those who endorsed thinking patterns (t=6.57, p < .001), environment
(t=4.50, p < .001), scheduling (t=4.29, p < .001) and emotions
(t=5.76, p < .001) as likely contributors were more confident that a psychological
than biological treatment would help. Surprisingly, no contributing
factor assessed (hormones, arousal, genetics) were endorsed as
more likely to be alleviated by a biological treatment.
Conclusion: Patient’s attributions influenced treatment choice. Patients
were more confident in psychological treatments over biological treatments.
Support (If Any): 5R01MH079188-02
0551
SLEEP VARIABLES RELATED TO SLEEP QUALITY RATING
Woosley J 1 , Lichstein KL 1 , Thomas J 1 , Taylor DJ 2 , Riedel BW 3 ,
Bush AJ 4
1
Psychology, University of Alabama, Tuscaloosa, AL, USA,
2
University of North Texas, Denton, TX, USA, 3 University of
Memphis, Memphis, TN, USA, 4 University of Tennessee, Memphis,
Memphis, TN, USA
Introduction: Sleep researchers frequently use the term sleep quality,
which lacks an established definition. The purpose of the present study is
to determine which sleep variables are most closely associated with perceived
sleep quality in people not having insomnia (PNI) and in people
with insomnia (PWI).
Methods: Using random-digit dialing, we recruited 772 participants
ranging in age from 20 to 80+, with approximately 50 men and 50 women
in each decade. Participants completed 2 weeks of sleep diaries which
included a daily sleep quality rating (SQR) on a scale from 1 (poor sleep)
to 5 (excellent sleep). The present sample included PNI (n = 400) and
PWI (n = 137). PNI satisfied ICSD insomnia diagnostic criteria. Excluded
were individuals who were partial qualifiers for PNI and PWI.
Results: Stepwise multiple regression found that for PNI, sleep efficiency
(SE) best predicted SQR, explaining 7.3% of variance in SQR.
Number of awakenings (NWAK) explained an additional 1.8% of variance.
Sleep onset latency (SOL), wake time after sleep onset (WASO),
and total sleep time (TST) were excluded. For PWI, WASO was the best
predictor of SQR, explaining 20.8% of the variance in SQR. Together,
NWAK and TST explained an additional 9.9% of variance. SE and SOL
were excluded.
Conclusion: NWAK was the only sleep variable that predicted a significant
amount of variance for both PNI and PWI. SE was the best predictor
of SQR for PNI, whereas WASO was the best predictor of SQR for
PWI. 91% of variability in SQR among PNI remained unexplained after
accounting for self-reported sleep patterns, and 70% of SQR was unexplained
among PWI. Most of perceived sleep quality may be a function
of sleep stages and factors unrelated to sleep pattern and architecture
sometimes grouped under the umbrella of nonrestorative sleep.
Support (If Any): Research supported by National Institute on Aging
grants AG12136 and AG14738.
0552
THE EFFECTS OF SLEEP DISTURBANCE ON PSYCHIATRIC
AND COGNITIVE FUNCTIONING FOLLOWING
TRAUMATIC BRAIN INJURY
Orff HJ 1,2,3 , Jak A 1,2 , Twamley E 1,2
1
Dept. of Psychiatry, University of California, San Diego, San Diego,
CA, USA, 2 Psychology Service, VA San Diego HCS, San Diego, CA,
USA, 3 Research Service, VA San Diego HCS, San Diego, CA, USA
Introduction: Traumatic brain injury (TBI) is a leading cause of death
and permanent disability in the US each year and is considered the hallmark
injury of the wars in Iraq and Afghanistan. Insomnia following
TBI is one of the most common and yet least studied of the post-TBI
sequelae and may contribute to residual mood and cognitive difficulties
in these patients. We evaluated these factors in a sample of Veterans with
mild to moderate TBI (mTBI).
Methods: Retrospective chart reviews of Veterans’ clinical sleep, psychiatric,
and neuropsychological test data were conducted. Bivariate
correlations were performed to assess the relationship between sleep and
measures of cognitive and emotional functioning.
Results: 316 Veterans (mean age=32 yrs; mean education=13.5 yrs)
were evaluated. 85% of patients reported sleep disturbance as measured
by scores on Item #16 on the Beck Depression Inventory (BDI), with
71% of the total sample reporting getting less sleep. In a subset of patients
(n=94) who were administered the Pittsburgh Sleep Quality Inventory
(PSQI), 98% reported clinically significant sleep disturbance (PSQI
SLEEP, Volume 34, Abstract Supplement, 2011
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