Novel Treatment of Comorbid Insomnia and Sleep Apnea in Older Veterans
Phase: NA
Conditions: Insomnia, Apnea
Sponsor: VA Office of Research and Development

Study Protocol: 7/14/2015 
 
 
 
1 
 
 
 
 
 
 
 
 
 
 
 
STUDY PROTOCOL & STATISTICAL ANALYSIS PLAN 
 
A NOVEL TREATMENT OF COMORBID INSOMNIA AND SLEEP APNEA  
IN OLDER VETERANS 
IIR 12-353 
 
1I01HX001070-01A1 
 
PI: Cathy Alessi, MD 

Study Protocol: 7/14/2015 
 
 
 
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Research Design and Methods 
Both OSA and insomnia increase in prevalence with age, and these conditions commonly coexist in older 
Veterans.  Treatment guidelines for insomnia recommend CBT-I as first-line therapy, but most insomnia 
behavioral treatment trials (including our own ongoing work) have excluded individuals with clear evidence of 
moderate-severe OSA.  PAP is the standard for treatment of OSA, but adherence with PAP is problematic and 
best practice to improve PAP adherence when patients have coexisting insomnia is unknown.  Given the high 
prevalence and serious consequences of these disorders, it is clear that research is needed to identify best 
practices for the management of coexisting OSA and comorbid insomnia in older adults.   
 
 Basic study design  
This 3.5 year project will be a randomized controlled trial testing a combined, integrated behavioral 
approach to management in older Veterans (aged  > 50 years) who are diagnosed with OSA, are prescribed 
PAP therapy, and also meet diagnostic criteria for insomnia.  This novel intervention will combine essential 
elements of a CBT-I intervention (for insomnia) plus a behavioral intervention to improve PAP adherence.  The 
combined, integrated intervention will be provided using allied health personnel compared to an active control 
condition (consisting of a general sleep and PAP education program) among older Veterans (N=120 total 
participants, 60 per group).  Structured outcome assessments will be collected at baseline, post-treatment (i.e., 
after completion of the intervention or control condition), and at 3- and 6-months follow-up.  A brief telephone 
interview will be conducted at 12-month follow-up.  Outcomes assessed will include subjective (i.e., 
questionnaire, sleep diaries) and objective (i.e., wrist actigraphy) measures of sleep, objective measures of 
PAP adherence (downloaded from PAP equipment), mood and other measures of health-related quality of life. 
Data will also be collected at post-treatment, and at 3- and 6-months follow-up to assess beliefs and attitudes 
about sleep and OSA.  Adherence with key aspects of the intervention will be collected in intervention 
participants during the treatment phase, and intervention participants will be invited to participate in focus 
groups after completing their 6-month follow-up to identify factors that act as facilitators or barriers to 
participation and adherence with the intervention. 
 
Setting 
The study will take place in VA GLAHS at the Sepulveda and West Los Angeles campuses, which are 
located 15 miles apart in the Los Angeles area, and serve a diverse population of Veterans.  In fiscal year 2011 
(FY11), the West Los Angeles VA campus served 53,913 unique Veterans, and the Sepulveda VA campus 
served 25,535 Veterans.  There were 2,792 unique patients seen in the VA GLAHS sleep clinics at Sepulveda 
and West Los Angeles in FY11, at least 52% were aged 50 years or older, and the majority (over 80%) 
were referred for evaluation of OSA. There were 1852 sleep studies performed in FY11, and 1037 new PAP 
machines were issued during that time period.   Based on the literature and our preliminary studies, we 
estimate that at least 50% of Veterans diagnosed with OSA and prescribed PAP will also meet diagnostic 
criteria for insomnia.  Based on this data, we conservatively estimate that at least 22 Veterans per month will 
be eligible for the study (i.e., [1037 PAP machines prescribed/12 months] x [.52 aged > 60 years] x [.50 
meeting diagnostic criteria for insomnia] = 22.5 ).  Based on consent rates in our prior VA studies enrolling 
older Veterans for interventional sleep research (e.g., VA HSRD IIR-04-321-3) we expect a 50% consent rate 
among eligible Veterans, which would provide 10 enrolled Veterans per month, with 50% (5 per month) 
proceeding to randomization. 
 
 
Figure 1:  Study design 
 
 
 
 
 
 
 
 
 
 
 

Study Protocol: 7/14/2015 
 
 
 
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Study Population 
• 
Recruitment and consent 
We will use a two-step process to recruit participants for this study.  In the first step of recruitment, we will 
screen for insomnia among Veterans aged 50 years and older who are referred to the VA GLAHS sleep clinics 
to rule out OSA (based on the reason for referral to the sleep clinic indicated on the electronic consultation 
form).  At our institution, the majority of individuals referred to sleep clinics are referred for possible OSA, and 
most referred patients receive an ambulatory (i.e., in-home portable) sleep study (rather than a study in the 
sleep laboratory) to test for OSA.  However, we will enroll participants regardless of the location (in-home or in-
laboratory) of their OSA testing.  Currently, there is a 3-4 week wait for an ambulatory sleep study; the wait for 
an in-laboratory study is > 4 weeks.  We will mail a letter to these Veterans when their referral to sleep clinic is 
received to briefly introduce the research, and to offer them a mechanism to “opt-out” of further contact by our 
research team, using a methodology previously approved by our institutional review board.  For patients who 
do not opt out within 7 days of receiving the letter, our staff will contact them by telephone (or in-person if 
preferred by the Veteran) to complete a brief screening measure for insomnia.  The insomnia screener is a 
brief questionnaire that summarizes key diagnostic criteria for insomnia according to ICSD2Error! Bookmark not 
defined.  (see Appendix 1), which we developed, tested and currently use in our ongoing study of CBT-I to treat 
insomnia in older outpatient Veterans (VA HSRD IIR 08-296, PI Alessi).   Veterans who meet diagnostic criteria 
for insomnia will be invited to participate in the study and an in-person visit will be scheduled to explain study 
procedures, obtain written informed consent, and begin assessment procedures.  After consent, the Veteran 
will be sent home with a wrist actigraph to wear for 7 days and nights as an objective measure of sleep/wake 
patterns.  Additional baseline data (e.g., demographic information, subjective measures of sleep, assessment 
of depressive symptoms, medical comorbidity, health-related quality of life) will be collected using structured, 
validated questionnaires (see below).  In addition, one blood sample will be collected.  All research data will be 
collected by trained research staff.  All study visits will be performed in dedicated office space, separate from 
the sleep clinics.  Separate research staff will perform assessment versus intervention activities, in order to 
maintain blinding of both clinic staff and research assessment staff.   
In the second step of recruitment, consented Veterans who have completed baseline testing, are 
diagnosed with OSA (based on sleep clinic physicians interpretation of sleep study results) and are prescribed 
PAP therapy (by sleep clinic clinicians) will be reminded of study procedures, and invited to participate in the 
randomized controlled trial.  Inclusion criteria will include:  1) age > 50 years, 2) meeting ICSD2 diagnostic 
criteria for insomnia, and 3) diagnosis of OSA with an AHI > 15 and prescription of PAP therapy.  Exclusion 
criteria for randomization will include the following:  1) refusal to schedule an appointment to begin PAP 
therapy, 2) a Mini-mental State Examination (MMSE) score < 24 (used to screen for significant cognitive 
impairment), and 3) a history of mania (which is a contraindication for the sleep restriction component of CBT-
I), major psychopathology (e.g., psychosis) or a psychiatric hospitalization within the prior two years.   
 
• 
Randomization 
Participants will be randomized to the intervention or control group using a randomized block design 
based on results from the OSA testing, to increase the likelihood of comparable severity of OSA in both 
groups. Specifically, individuals will be categorized based on AHI < 30 or AHI > 30.  Consented participants will 
be randomized as a block within each category (similar to block randomization techniques we have used in 
prior research).  Available randomization software (e.g., Random Allocation Software, Paradigm) which allows 
for block randomized sequences for parallel group randomized trials will be used to assign participants to the 
intervention or control group, using random allocation concealment. Participants and research staff (except 
intervention staff) will be blinded to group assignment, and additional techniques (e.g., follow-up assessment in 
some consented, non-randomized participants) will be used to prevent unmasking. It may be difficult to keep 
assessment research staff blinded to group assignment if participants inadvertently describe their assignment, 
but all assessment staff will also be blinded to study research questions. 
 
Dependent and Independent Variables (Measurement Techniques) 
A summary of all measurement techniques is shown in Table 1.   
Baseline Assessment 
Consenting participants will receive a baseline assessment.  Data will be collected at two separate visits 
over a seven day period.  At the first visit, research staff will obtain informed consent, complete the first part of 
the baseline assessment, and provide the Veteran with a wrist actigraph device.  Using a process similar to 
that in our ongoing VA HSRD-funded CBT-I trial, the participant will return after one week with the actigraph 

Study Protocol: 7/14/2015 
 
 
 
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and research staff will complete the second part of baseline assessment.  Veterans will receive $25 for 
completing the baseline assessment.   
Independent assessment research staff not involved in the intervention will perform baseline, post-
treatment, and 3- and 6-month follow-up assessments.  All research staff will undergo two weeks of structured 
training, including review of human subjects protection issues, basic interviewing techniques, cultural sensitivity 
training, and in-depth instruction on data collection instruments and equipment. Procedure manuals have been 
written for all instruments and equipment. Senior research staff will observe data collection at least quarterly, 
and inter-rater reliability will be assessed initially and re-assessed annually, and if new research staff are hired.  
These procedures have resulted in consistent, reliable data collection in our prior work and we have 
experience with all measures listed.   
Data collection methods and instruments were chosen that are appropriate for use in older people.  
Specific instruments were chosen based on primary and secondary outcomes of interest, key covariates 
needed for analyses, efforts to minimize participant burden, our prior experience with these measures and 
published recommendations for standard assessment in sleep research.1   For ethical reasons, the 
participant’s primary provider will be notified (with the participant’s consent) if our assessments identify any 
serious, unrecognized sleep disorder, or other severe condition (e.g., severe pain, severe depression).  Our 
research team will also follow our established protocol when there is evidence of any serious, life-threatening 
situation (e.g., suicidality) identified during interactions with participants (see Human Subjects section). 
 
Medical Chart Review (Data Collected by Research Staff) 
• 
Structured clinical review of comorbidity, illness severity, and medications 
The Cumulative Illness Rating Scale for Geriatrics (CIRS-G)2 will be used to assess baseline illness 
severity and comorbidity. We will use data from the medical record to complete the CIRS-G scale. The CIRS-G 
manual has specific criteria for scoring illness severity. We have extensive prior experience in use of the CIRS-
G in a variety of research settings.  We will use CIRS-G total score as an independent variable of baseline 
comordibity in data analyses. 
Medications received during each data collection period will be identified from the electronic medical record 
and a structured medication interview. Medications will be coded by class using a coding system we developed 
in prior work.  We will focus on sedating medications that may affect sleep.  With a methodology we used in 
prior research,3  sedating medication use will be summarized categorically (i.e., was a certain class of sedating 
medication received, and at what time); then daily dose(s) will be converted to total daily equivalences by class 
according to standardized criteria. Because of the intention to treat analysis, major outcomes will be compared 
between the intervention and control groups regardless of medication status.  However, the medication 
variables (e.g., total daily equivalence of sedating medication at each time point) may be explored as potential 
covariates in outcome analyses, and use/nonuse of sedating medications may be considered in subgroup 
comparisons (e.g., subgroup analysis in only participants who did or did not receive sleeping pills). 
 
Questionnaires (Data Collected from Participants) 
• 
Descriptive information will be collected in all participants, including age, gender, ethnicity, marital status, 
and other demographic characteristics. 
• 
Cognitive status  
The Mini-Mental State Examination (MMSE) will be used to screen consented individuals for inclusion and 
to measure baseline cognitive status.4  This scale assesses orientation, registration, attention/calculation, 
recall, language and construction, and has standard instructions. MMSE scores range from 0 to 30, where 
higher scores indicate better mental status. A score below 24 is consistent with dementia or delirium. MMSE 
total score will be used in determining study eligibility (i.e., MMSE score < 24 is an exclusion criteria) and as an 
independent variable of cognitive status in analyses.  
The Hopkins Verbal Learning Test – Revised (HVLT-R)5 will be used to estimate verbal learning and 
immediate and delayed memory functioning, as both sleep and PAP adherence likely impact memory 
functioning. The HVLT-R consists of a Word List, containing 12 words from three taxonomic categories, which 
is read aloud to the participant at the rate of approximately one word every two seconds. The Immediate Recall 
test includes three learning trials. Delayed Recall is assessed following a delay after completion of the 
Immediate Recall test. Immediately after administration of the Delayed Recall trial, a forced-choice Recognition 
test is administered. The Recognition test includes the 12 target words, plus 12 distractors (six semantically-
related and six semantically-unrelated words). The HVLT-R has been validated in healthy and pathological 
aging samples. 

Study Protocol: 7/14/2015 
 
 
 
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The Digit Symbol Substitution6 will be used to estimate processing speed and attention, as both sleep and 
PAP adherence likely impact these cognitive functions. This task consists of nine digit-symbol pairs (e.g. 1/-
,2/┴ ... 7/Λ,8/X,9/=) followed by a list of digits. Under each digit the subject is instructed to write down the 
corresponding symbol as fast as possible. The number of correct symbols written within the allowed time (e.g. 
90) is the outcome measure. 
The Trails A and B7 tests will be used to estimate processing speed, attention, and executive functioning. 
Trails A will be used to assess processing speed, while Trails B will be used to assess attention and task 
switching (executive functions). Trails A requires individuals to connect circles containing numbers in 
sequential order. Trails B requires individuals to connect circles containing numbers and letters in alternating 
sequential and alphabetic order. The outcome measures are the time to complete the tasks. 
The Forward and Backward Digit Span8 tests will be used to estimate immediate memory and working 
memory. The Forward Digit Span tasks requires immediate recall of number presented aurally. The Backwards 
Digit Span requires mental manipulation and rearrangement of numbers presented aurally. The outcome 
measures are the total number of correct sequences recalled. 
The Letter-Number Sequencing8 test is another measure of working memory. This task requires mental 
manipulation and serial rearrangement of numbers and letters presented aurally. The outcome measure will be 
the total number of correct sequences recalled. 
The Control Oral Word Association (COWA)9 will be used to assess phonemic fluency, which is considered 
an executive function. Participants will be read a letter (“F”, “A”, and “S”) and asked to generate as many non-
proper nouns beginning with that letter as possible within sixty seconds. The outcome measure is the total 
number of correct words produced for each letter. 

Study Protocol: 7/14/2015 
 
 
 
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Table 1: Study Variables and Their Measurement 
Independent variables 
Hypothesis 
Measurement Instrument 
Data* 
Demographics 
 
Questionnaire 
I 
Health status measures: 
 
Illness severity/comorbidity 
 
Comorbidity Index  
I 
 
Use of medications 
 
Medication review  
MR, I 
 
Cognitive status 
 
 
 
 
 
 
 
Mini-Mental State Examination (MMSE)  
Hopkins Verbal Learning Test – Revised 
(HVLT-R) 
Digit Symbol Substitution 
Trails A and B  
Forward and Backward Digit Span 
Letter-Number Sequencing 
Control Oral Word Association (COWA) 
I 
I 
I 
I 
I 
I 
I 
I 
 
PTSD 
 
Primary Care PTSD Screen 
I 
 
Pain 
 
Geriatric Pain Measure (GPM) pain  
intensity subscale 
I 
Dependent variables: Outcomes 
Intervention process measures: 
 
Beliefs and attitudes about 
sleep 
 
Beliefs and attitudes about 
OSA and PAP 
4 
 
4 
Dysfunctional Beliefs and Attitudes about 
Sleep (DBAS-16) scale 
Self-efficacy, Knowledge and Decisional 
Balance Index subscales 
I 
 
I 
Subjective sleep measures 
 
Self-rated sleep quality 
 
Severity of insomnia  
      symptoms 
 
Daytime sleepiness 
1, 3 
1, 3 
 
 
Pittsburgh Sleep Quality Index (PSQI)  
Insomnia Severity Index (ISI)  
 
Epworth Sleepiness Scale (ESS)  
I 
I 
 
I 
 
Sleep onset latency, wake 
after sleep onset 
 
Sleep diary 
SR, I 
Objective sleep measures: 
 
Total sleep time, nighttime &   
daytime sleep percent  
1, 3 
 
Wrist actigraphy 
M 
Quality of life measures: 
 
Health-related quality of life 
2, 3 
MOS 12-item Short-form Health Survey 
(SF-12v2); EuroQol-5D 
I 
 
Depressive symptoms 
2, 3 
Patient Health Questionnaire 
Depression module (PHQ-9)  
I 
 
Anxiety 
 
Patient Health Questionnaire 
Generalized Anxiety module   
I 
PAP adherence 
 
 
 
 
 Hours of PAP use per night 
1, 3 
PAP memory card or modem download 
M 
*Data source: I=interview, MR=medical records, M=monitoring, SR=self report  

Study Protocol: 7/14/2015 
 
 
 
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• 
Comorbidity Index10:  The Comorbidity Index is a validated, self-report measure of physical and mental 
comorbidity. This 36-item self-report questionnaire has a 30-item physical component and a 6-item mental 
component and was developed for a population of Veterans. Comorbidity index score and individual comorbid 
conditions will be used as independent variables. 
 
Post-traumatic stress disorder 
The Primary Care PTSD Screen (PC-PTSD) 11  will be used to estimate the presence or absence of PTSD, 
since this disorder may impact both sleep and PAP adherence.Error! Bookmark not defined. This is a 4-item 
scale, where endorsement of 3 of the 4 yes/no items suggests PTSD. The scale has a sensitivity of .78, and 
specificity of .87 compared to clinical diagnosis of PTSD in Veterans.  The PC-PTSD will be used as an 
independent variable of PTSD status (i.e., presence/absence of PTSD and/or number of PTSD symptoms 
endorsed, 0-4).   
• 
Subjective assessment of pain  
The pain intensity subscale (7 items) of the Geriatric Pain Measure (GPM)12 will be used to assess pain, 
since pain may affect sleep outcomes. The GPM is a 24-item multidimensional pain measure (with 5 
subscales) for use in older adults. The pain intensity subscale will be used to minimize participant burden. 
Total score on the GPM subscale will be used as a covariate in analyses of sleep and quality of life outcomes.  
• 
Subjective sleep quality  
We will measure self-reported sleep quality using the Pittsburgh Sleep Quality Index (PSQI),13 the 
Insomnia Severity Index (ISI),14 the Epworth Sleepiness Scale (ESS)15 and a sleep diary; all of which have 
specifically been identified as recommended/essential measures of sleep and insomnia symptoms for standard 
assessment in sleep research.1  
PSQI: This is an 18-item questionnaire that assesses sleep quality and disturbances over the last month. 
The PSQI is a widely used scale that measures subjective sleep quality, sleep latency, sleep duration, habitual 
sleep efficiency, sleep disturbances, use of sleeping medication, and daytime dysfunction.  
ISI: This is a 7-item scale of self-reported severity of insomnia symptoms, satisfaction with sleep, daytime 
functioning, impairment and concern caused by the sleep problem.   
ESS: This is an 8-item questionnaire that assesses daytime sleepiness. The ESS measures the chances 
that an individual would doze off or fall asleep under 8 different circumstances (e.g., reading, watching 
television, sitting quietly). Total PSQI, ISI, and ESS scores will be used at baseline and at each follow-up 
assessment as dependent subjective measures of sleep.  
Sleep diary: Participants will complete a 7-day sleep diary at baseline and follow-up assessments (timed to 
occur at the same time as wrist actigraphy), which will be used to calculate self-reported sleep onset latency 
(SOL, time to fall asleep) and wake after sleep onset (WASO, the time spent awake from sleep onset to final 
awakening) as dependent subjective measures of sleep (see Appendix 2). 
• 
Health-related quality of life  
The Medical Outcomes Study 12-item Short-form Health Survey v2 (SF-12v2)16 will be used as a measure 
of health-related quality of life. The SF-12v2 Health Survey is a 12-item version of the prior SF-36 (therefore 
with less participant burden) with evidence for improved format and precision.  The SF-12v2 can be scored as 
a global scale, in 8 domains (physical functioning, physical, bodily pain, general health, vitality, social 
functioning, emotional and mental health) or as two summary scores (Physical Component and Mental 
Component Summary Scores).  Most population-based descriptive studies of sleep and quality of life have 
used the longer 36-item version, and very few trials of behavioral interventions for insomnia have included 
quality of life as an outcome measure at all; these factors make the choice among these scales difficult.  In 
addition, the recently published recommendations for standard research assessment in insomnia trials 
described above specifically mention the SF-36 as a recommended/essential measure of health-related quality 
of life.1  However, after careful consideration of the balance in participant burden and precision, and our own 
experience with the SF-12v2 in our current work, we have chosen this scale for the current study.  We will use 
the global score, and the Physical Component Summary score and Mental Component Summary score at 
baseline and follow-up assessments as dependent measures of health-related quality of life.   
The EuroQol-5D (EQ-5D)17 will be used as another measure of health-related quality of life.  This 5-item 
questionnaire was developed by the EuroQol Group in order to provide a simple, generic measure of health for 
clinical and economic appraisal.  The EQ-5D included 5 dimensions: mobility, self-care, usul activies, 
pain/discomfort and anxiety/depression. Total EQ-5D score at baseline and follow-up assessments will be 
used as a dependent measure of health-related quality of life.   

Study Protocol: 7/14/2015 
 
 
 
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The Patient Health Questionnaire-9 (PHQ-9)18 will be used to measure depression as another component 
of health-related quality of life. The PHQ-9 is the depression module of the Patient Health Questionnaire (a 
self-administered diagnostic instrument for common mental disorders). The 9 items consist of the diagnostic 
criteria used by the DSM-IV for depressive disorders. The PHQ-9 also measures depression severity.  Total 
PHQ-9 score at baseline and follow-up assessments will be used as dependent measures of depression. 
The 7-item Generalized Anxiety Scale (GAD-7) will be used to measure anxiety, which has been 
demonstrated as an important quality of life outcome in sleep research19 and may impact PAP adherence.  The 
GAD-7 is a component of the Primary Care Evaluation of Mental Disorders (PRIME-MD) suite of evaluation 
tools.  It was initially developed for evaluation of generalized anxiety disorder, and has also proved useful in 
screening for other DSM-IV Axis I anxiety disorders. The GAD-7 is a 7-item scale (scores range from 0 to 27), 
with a cut off score of ≥10 yielding both sensitivity and specificity above .80 for GAD.  The GAD-7 score at 
baseline and follow-up assessments will be explored as a dependent measure of anxiety, but we have not 
included anxiety as a primary outcome measure in sample size calculations and data analysis (see below).   
Caregiving questions (21 items).  To explore how caregiving impacts an individual’s sleep and quality of 
life, we will include questions from the National Alliance for Caregiving.  Questions pertain to the type and 
amount of caregiving provided.   
• 
Intervention process measures 
The Dysfunctional Beliefs and Attitudes about Sleep (DBAS-16) scale, brief version20 will be used to 
measure participants’ sleep-related cognitions. The DBAS-16 uses a Likert-type scale, and was developed 
from the original 30-item DBAS. Total DBAS-16 scores at baseline and at follow-up assessments will be 
compared between groups to measure effects of the intervention on participants' beliefs and attitudes about 
sleep as a measure of the process of the intervention.   
We will use the Self-efficacy (5-item), Knowledge (12-item) and Decisional Balance Index (5-item) 
subscales from the 54-item scale of behavioral determinants of PAP adherence.21  These subscales provide 
Likert-type (for the Self-efficacy and Decisional Balance Index subscales) or yes/no (for the Knowledge 
subscale) response options.  In prior work, the full scale (measured at 1-week after start of PAP therapy) 
predicted PAP adherence, and the DBI individually accounted for 17% of the variance in PAP adherence in 
adjusted analyses.  The Self-efficacy, Knowledge and Decisional Balance Index subscale scores will be 
compared between groups to measure effects of the intervention on participants’ beliefs and attitudes about 
OSA ad PAP. 
• 
Blood sample  
One blood sample (8mL) will be drawn by a study phlebotomist at one of 4 possible locations (CRC at 
West Los Angeles, Building 200 or Building 25 at Sepulveda, or if requested, at a subjects’ home.  Blood 
samples will be processed and stored in the CRC or in a laboratory at Sepulveda (Building 7/C10) until 
transported to the UCLA Cousins Center for Psychoneuroimmunology for analysis.  The blood samples will be 
assayed for proinflammatory cytokines and corresponding acute-phase proteins (i.e., CRP, TNFα, IL-6, IL-8, 
and IL-10), which are markers of immune system activity. 
 
Sleep Assessment Monitoring (Data Obtained through Monitoring of Participants)  
• 
Objective sleep quality monitoring 
Wrist actigraphy will be used as an outcome measure of the effects of the intervention on sleep. 
Participants will wear an actigraph on the dominant wrist (unless that arm is paralyzed) for 7 consecutive days 
and nights at baseline, post-treatment, and at 3-month and 6-month follow-up assessments.  The actigraph is a 
small watch-sized device useful in longitudinal, naturalistic (i.e., not in a sleep laboratory) assessment of sleep-
wake patterns. The device contains subminiature solid state accelerometers and, in general, wrist activity 
below an established threshold is interpreted as sleep; high wrist activity is interpreted as wakefulness.  
Commercially available software uses validated algorithms that take into account wrist movement immediately 
before and after an epoch of interest in determining the likelihood of sleep versus wakefulness during that 
epoch.  Wrist actigraphy has been validated as a measure of sleep versus wakefulness in older people.22 
Previously reported agreement between wrist actigraphy and EEG scoring of sleep variables (e.g., total sleep 
time) in young and older people is 89-95%.  
Wrist actigraphy has also been used to estimate circadian rhythms of activity; however the most 
appropriate analytic techniques to summarize these data and clinical significance of these variables are not 
clear, so we have not included these circadian variables as main outcomes in the current proposal.  We will 
use analytic software to perform least-squares analyses to fit 24-hour cosine curves to actigraphy data, to 

Study Protocol: 7/14/2015 
 
 
 
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determine the mesor (mean value of the fitted curve), amplitude (height of the curve at its peak) and circadian 
quotient (amplitude/mesor, where a higher quotient suggests a "better" rhythm).   
Careful visual review of raw actigraphy data will be performed to eliminate technical (device failure) and 
situational (e.g., device removed) artifact, prior to scoring variables with validated software. We will analyze 
actigraphy data defining "night" and "day" based on participant self-report of their bedtimes and rising times in 
their sleep diary.  The following dependent variables (averaged over 7 days) will be used in analyses as 
measures of sleep-wake: 1) total sleep, 2) nighttime sleep efficiency (mean total sleep time divided by total 
valid recording time), 3) daytime percent sleep (total sleep time divided by total daytime recording time), and 4) 
mean awakening length at night (mean duration of nighttime wake episodes).   
 
PAP adherence.   In addition,  
• PAP equipment will be provided by the VA GLAHS Sleep clinics to all intervention and control participants per 
usual care established clinical protocols.  The VA GLAHS Sleep clinics nearly exclusively use Respironics™ 
devices (Respironics, Inc., Murrysville, PA). The PAP devices are routinely dispensed with heated humidification 
to minimize upper airway dryness, which may affect adherence. The same clinical staff (i.e., sleep technicians) 
will provide PAP equipment and usual setup instructions for both intervention and control participants; these 
clinical staff will be blinded to group assignment.  All PAP devices have an internal secure device (SD) memory 
card that stores PAP usage data and a modem that transmits daily usage to a web-based application 
(EncoreAnywhere) maintained on a secure server by Philips Respironics, Inc. The data on the server are linked 
only to the serial number of the PAP modem and do not include any personal identifiers.  Authorized research 
staff will retrieve data from the server using an assigned password. Philips Respironics, Inc. will have no access 
to the key that links PAP modem serial number to subject identification code or name. For participants who are 
unable to use the modem because they live outside the modem serve area, research staff will download the SD 
card (easily performed with an inexpensive reader device) at the time of the follow-up assessments.  Data will be 
obtained after the first week of PAP therapy, at the post-treatment assessment, and at 3- and 6- and 12-months  
follow-up.  Our primary dependent measure of PAP adherence will be the percentage of nights that the PAP 
equipment was used for > 4 hours per night.  In addition, we will define “adequate” PAP adherence as PAP 
usage of  > 4 hours per night for 70% of days, and we will also record the mean hours of PAP use per 
night.23  PAP machines have the capability to sense when the mask is on the patient’s face, so we will be 
able to assess the hours per night of use at the effective PAP pressure (i.e., mask on at an effective 
pressure) .  Adherence data is automatically stored continuously in PAP equipment, and available by day.  
We plan to summarize data over the prior 7 days (at all data collection time-points) and/or the prior 30 days 
where appropriate (i.e., at 3-¸ 6-, and 12-months follow-up).   
 
Treatment groups 
Participants will be randomized to one of two groups:  1) intervention group, who will receive an integrated, 
manual-based individual CBT-I plus PAP adherence behavioral self-management program, or 2) control group, 
who will receive an attention control condition (general sleep and OSA education).  All participants will be 
prescribed PAP therapy (through the sleep clinic), and will receive their PAP device through the sleep clinic, as 
described above.  The intervention and control conditions will be provided by research allied health personnel 
(i.e., not psychologists).  The active intervention was designed to have a high enough intensity/potency for 
efficacy, while avoiding as much as possible the risks of excessive participant burden and excessive costs of 
implementation into routine care if successful. In addition, the intervention is structured and manual-based (i.e., 
using a concise intervention manual) in order to be highly translatable to routine care. The intervention and 
control programs will begin after baseline assessment and randomization, and the intervention or control 
conditions will begin approximately 2 weeks prior to initiation of PAP therapy.  If there is a delay in receipt of 
PAP equipment, participants will receive a weekly phone call from intervention/control staff to monitor progress 
and provide reinforcement (of information learned in sessions 1 and 2 in the intervention group, and to 
encourage continued participation in the control group).  If the PAP equipment is received prior to completion 
of sessions 1 and 2, the intervention/control condition will progress as scheduled below over a 6 week period. 
 
Intervention condition 
The intervention provides an integrated behavioral approach to OSA and insomnia, which combines a 
CBT-I treatment for insomnia with an OSA and PAP self-management program.  The aspects of each 
intervention are integrated seamlessly into one intervention program, provided in individual (i.e., one-to-one) 
sessions with master’s level allied health personnel (e.g., health educator) (see Appendix 3 for example of 
session material).  The first two sessions will be timed to occur prior to the patient receiving their PAP 
equipment; sessions 3 – 5 will occur after the participant receives their PAP device, with session 3 timed to 

Study Protocol: 7/14/2015 
 
 
 
10 
 
occur approximately one week after receipt of PAP (i.e., during or immediately after the first week of PAP 
therapy). The intervention is provided in 5 sessions over 6 weeks, to allow for one week (week 5) for the 
participant to become accustomed to independent self-management of their sleep problems, prior to the final 
session (week 6).  The intervention staff will have weekly supervision with a study psychologist by telephone, 
where intervention cases currently in progress are reviewed briefly to monitor participant progress (similar to a 
method used in our ongoing CBT-I trial). Integrity of the intervention will be addressed carefully throughout the 
study, including formal training of the intervention staff initially with ongoing review and oversight throughout 
the study and periodic audio-recording of intervention sessions for review by a study psychologist (Dr. Martin).  
In addition, intervention staff will record specific intervention recommendations made to participants and 
participant adherence with these recommendations (similar to work in our ongoing trial of CBT-I), to help 
document the process of the intervention. 
 
Table 2:  Session schedule for the intervention group 
Week 
Session 
Session length 
Content 
1 
1 
60 minutes 
CBT-I: Sleep education, stimulus control, regularize sleep schedule 
PAP:  Understanding OSA and PAP therapy 
2 
2 
30-45 minutes 
CBT-I: Introduction to sleep restriction 
PAP: Review of PAP equipment and set-up procedures, chronic disease 
management skills, communication skills, patient-provider relationship 
3 
3 
30-45 minutes 
CBT-I: Sleep restriction 
PAP: Review prior week PAP adherence and ongoing problem-solving  
4 
4 
30 minutes 
CBT-I: Sleep hygiene, adjust sleep restriction 
PAP: Review prior week PAP adherence and ongoing problem-solving 
6 
5 
30 minutes 
CBT-I and PAP:  Review, relapse prevention and long-term 
management strategies 
 
 
The CBT-I component of the intervention involves a previously tested, manual-based CBT-I program using 
content developed in our prior work which improved sleep among older Veterans meeting diagnostic criteria for 
insomnia (see Preliminary Studies).  The intervention will involve education and practical training in key 
aspects of stimulus control (i.e., reducing anxiety about falling asleep), sleep restriction (i.e., an individualized, 
structured process of reducing time in bed to decrease nighttime wakefulness and consolidate sleep), sleep 
hygiene (i.e., establishing behavioral routines to promote restorative sleep), and cognitive therapy (i.e., 
addressing maladaptive and inaccurate perceptions and beliefs about sleep).   
 
The PAP self-management component of the intervention involves a previously tested OSA disease-
specific, self-management intervention based on the chronic disease model using the social cognitive theory 
and transtheoretical models of behavior change (see Preliminary Studies).Error! Bookmark not defined.,Error! Bookmark not 
defined.,Error! Bookmark not defined.  This program includes information specific to OSA, in addition to concepts in 
chronic illness self-management.  Issues covered include:  understanding OSA symptoms and consequences, 
problem-solving difficulties with PAP, managing emotional-cognitive symptoms, learning strategies to increase 
physical activity, improving communication skills with providers, and developing a patient-provider relationship.  
The participant’s PAP use in the prior week will be reviewed, and a major focus of the program will involve 
troubleshooting commonly occurring problems with PAP, tailored to the participant’s ongoing experience with 
PAP, in addition to understanding how specific aspects of an individual’s use of PAP relates to the 
management of his/her OSA. 
 
Control condition 
The control condition will be administered by research staff using a manual-based education program 
that focuses on general insomnia and OSA education, and is structured based on the control condition from 
our prior work (IIR 08-295-1, PI: Alessi).  In our prior work, the control program was successful in providing an 
attention control placebo condition which also encouraged ongoing participation in the trial; an important factor 
in encouraging control participants to complete follow-up assessments.   
 
Table 3:  Session schedule for the control condition 
Week 
Session 
Session length 
Content 
1 
1 
30 minutes 
Introduction; general sleep and OSA education 
2 
2 
30 minutes 
Sleep across the lifespan, general health education 
3 
3 
30 minutes 
Sleep and health 

Study Protocol: 7/14/2015 
 
 
 
11 
 
4 
4 
30 minutes 
Daytime relaxation techniques 
6 
5 
30 minutes 
Daytime stress reduction 
 
Post-Treatment and Follow-up Assessments 
Post-treatment and follow-up assessments will be performed by research personnel blinded to group 
assignment. Participants who can no longer travel to VA GLAHS (e.g., moved away, too ill) will be visited at 
their living location (if < 30 miles away) or interviewed by telephone (if > 30 miles away).  Veterans will receive 
$25 for each assessment for a possible total of $100 (i.e., baseline, post-treatment, 3-month and 6-month). 
 
      Table 4: Time Points for Data Collection and Measures Used 
 
Baseline 
Post-tx 
3-mo 
6-mo 
12-mo 
Data Collected by Research Staff 
 
 
 
 
 
Blood sample: assayed for proinflammatory cytokines and 
corresponding acute-phase proteins (i.e., CRP, TNFα, IL-
6, IL-8, and IL-10) 
 
 
 
 
 
Medication review  
 
 
 
 
 
Data Collected from Participants 
 
 
 
 
 
Demographic data                                                       
 
 
 
 
 
Mini-Mental State Examination (MMSE)  
 
 
 
 
 
Hopkins Verbal Learning Test – Revised (HVLT-R) 
 
 
 
 
 
Digit Symbol Substitution 
 
 
 
 
 
Trails A and B  
 
 
 
 
 
Forward and Backward Digit Span 
 
 
 
 
 
Letter-Number Sequencing 
 
 
 
 
 
Control Oral Word Association (COWA) 
 
 
 
 
 
Geriatric Pain Measure (GPM) intensity subscale 
 
 
 
 
 
Restless Leg Syndrome scale (RLS)  
 
 
 
 
 
Pittsburgh Sleep Quality Index (PSQI)                                       
 
 
 
 
 
Insomnia Severity Index (ISI)  
 
 
 
 
 
Epworth Sleepiness Scale (ESS)                
 
 
 
 
 
Patient Health Quest. depression module (PHQ-9)                      
 
 
 
 
 
12-item Short-form Health Survey (SF-12v2)                                 
 
 
 
 
 
EuroQol-5D scale (EQ-5D) 
 
 
 
 
 
PHQ GAD 
 
 
 
 
 
PC-PTSD 
 
 
 
 
 
Caregiving questions 
 
 
 
 
 
Dysfunctional Beliefs & Attitudes about Sleep (DBAS-16)      
 
 
 
 
 
PAP Self-efficacy, Knowledge and Decisional Balance 
Index subscales 
 
 
 
 
 
Data from Participant Monitoring 
 
 
 
 
 
Wrist actigraphy 
 
 
 
 
 
PAP adherence 
 
 
 
 
 
Follow-up Data from Participant/ Record Review 
 
 
 
 
 
Sleep clinic visits 
 
 
 
 
 
 
Post-treatment assessment:  As is traditionally performed in behavioral insomnia interventional studies, 
“post-treatment” assessments will be repeated soon after completion of the treatment (either intervention or 
control conditions).  Wrist actigraphy will be repeated for 7 days, in addition to the sleep quality (PSQI, ISI, 
ESS), cognitive functioning tests (HVLT-R, Digit Symbol Substitution, Trails A and B, Forward and Backward 
Digit Span, Letter-Number Sequencing, COWA), depression (PHQ-9), quality of life (SF-12v2), caregiving 
questions, process measures (DBAS-16 and Self-efficacy, Knowledge and Decisional Balance Index 
subscales), and other questionnaires  (see Table 4).  A blood sample will also be obtained from each 
participant. In addition, PAP adherence data will be collected as described above.  
Three-month follow-up assessment:  The main outcome assessment will be performed at three months 
after baseline assessment, using the same measures included in the post-treatment assessment.   

Study Protocol: 7/14/2015 
 
 
 
12 
 
Six-month follow-up assessment: Follow-up assessment will be performed again at 6 months after 
baseline assessment (to test for maintenance of outcomes), using the same measures included in the post-
treatment and 3-month follow-up assessments.   
Twelve-month follow-up assessment:  Participants will be contacted by telephone after 12-months for a 
brief interview.  Research staff will administer the three sleep questionnaires (ISI, PSQI, and ESS) and PAP 
adherence data will be collected. 
 
Unblinded qualitative assessment among intervention participants: After completion of the six-month 
follow-up assessment, intervention participants will be invited to participate in focus groups (up to 6 focus 
groups, N = up to 40 intervention participants). Focus groups will take place during years 2 and 3 of the study 
in an ongoing manner as intervention participants complete their 6-month follow-up assessments.  The 
structure and format of the focus groups will mirror techniques used in our prior qualitative research. The 90 
minute focus groups will be moderated by Dr. Martin, who has previous training and experience moderating 
focus groups.  Ms. Josephson (project manager) will take notes during the group. We will use a structured 
discussion guide to explore the key topics of interest, including participants’ 1) experiences with the 
intervention (e.g., What aspects of the program were most helpful? What aspects were least helpful?), 2) 
attitudes and adherence with the intervention (e.g., What recommendations were the most difficult to follow? 
What recommendations are you still following? What recommendations are you no longer following?), 3) 
perceptions of the program (e.g., What do you think about the format used? What do you think about the 
materials, such as readability, clarity, and graphics? What other information would have been helpful?), 4) 
barriers to participation (i.e., What makes it difficult to attend this program?), and 5) facilitators to participation 
(i.e., What would make it easier to attend this program?) The focus groups will be audio-taped and transcribed. 
 
Data Management 
At study entry, each participant will be assigned a unique identification number for entry on data 
collection forms and computerized files.  Participant identifying information will be kept separate, stored in a 
locked cabinet, with access limited to the principal investigator and data manager. Electronic databases will be 
stored on the VA GLAHS network server and the local HSR&D Center of Excellence server behind the VA 
firewall. Using project folders that are part of the architecture of the server, the research team will have varying 
levels of access to the data. Dr. Alessi (PI), Dr. Martin (co-investigator), Ms. Josephson (project manager), Ms. 
Jouldjian (data manager) and Dr. Mitchell (statistician) will have complete access to all data files. Other 
members of the research team will only have access to selected de-identified datasets. Original data forms will 
be archived and stored in locked cabinets. All data will be entered into a database (SPSS for Windows 20.0) 
using procedures established in prior work.  Equipment-derived data (e.g., actigraphy, PAP adherence data) 
will be downloaded at the end of each monitoring period, and checked to ensure the equipment functioned 
properly. Down-loaded files will be backed up, cleaned and processed using specialized software to yield data 
variables. Separate data sets will be created for each major data type (e.g., equipment data, questionnaires, 
medical record review).  Unit of analysis will be the participant, and data sets will contain all baseline and 
follow-up measures for each variable.  Data in each set will be cleaned by screening for out-of-range or outlier 
values in frequency distributions, and compared against original data forms for accuracy.  Double entry 
procedures will be used on a 20% random sample of cases in each data set, with additional training and review 
of data if errors are identified. Sleep and related data will be processed immediately following each 
participant’s sleep monitoring session, and data from other instruments and measures will be entered within 
three days of data collection.  Data will be cleaned weekly.  Cleaned data will be merged into the main 
database for statistical analyses. 
 
Sample size estimates   
As described above, participants will be enrolled from the sleep clinics at VA GLAHS Sepulveda and 
West Los Angeles campuses.  Based on FY11 data, at least 1037 patients per year will be diagnosed with 
OSA and prescribed PAP (using PAP equipment provided by VA GLAHS).  We expect at least 52% will be 
aged > 50 years, and at least 50% will also meet diagnostic criteria for insomnia.  Based on this data, we 
conservatively estimate that at least 22 Veterans per month will be eligible for the study (i.e., [1037 PAP 
machines prescribed/12 months] x [.52 aged > 60 years] x [.50 meet criteria for insomnia] =22.5).  Based on 
consent rates in our prior VA studies we expect a 50% consent rate among eligible Veterans, which would 
provide at least 10 enrolled Veterans per month.  We estimate that approximately 50% of enrolled participants 

Study Protocol: 7/14/2015 
 
 
 
13 
 
will meet all inclusion and exclusion criteria and be randomized, resulting in approximately 5 randomized 
participants per month, and our total target enrollment will be 120 randomized participants. 
We have extensive experience in methods to encourage participant retention.  For example, in our 
ongoing CBT-I trial in older Veterans, one of 122 participants who have reached the 6-month time-point has 
died, and only an additional 9 participants have been lost to follow-up due to other reasons, resulting in only 
8.2% (10/122) loss by 6-months.  In the current proposal, we conservatively estimate 15% loss by 6 months, 
which would result in approximately 102 (51 per group) participants completing the 6-month assessment.  
However, as in our prior work, we will monitor enrollment and participant loss throughout the study, to allow 
adjustment of the timeline and/or enrollment and retention procedures if we do not meet targets.   As described 
in the analysis plan below, we will use standard “intention to treat” analysis, and sample size calculations have 
been made based on this analysis.  Sample size calculations for each major outcome measure (described 
below) suggest that the target sample size will be sufficient to test our major hypotheses.  All sample size 
calculations are based on 80% power and two-tailed P-value < .05. 
 
Analysis Plan and Hypotheses   
 
The analysis plan for each specific hypothesis is listed below.  In addition to hypothesis testing to analyze 
effects of the intervention on sleep, PAP adherence, depressive symptoms and quality of life, we will develop 
models showing which covariates predict the values of each of the outcome measures.  Prior to hypothesis 
testing, data will be cleaned, possible outliers identified, and data distributions evaluated for assumptions of 
analysis (e.g. normality, homogeneity of variance).  If necessary, normalized rank transformations as described 
in Bonate24 will be performed and normalized rank scores will be submitted to analysis. 
 
Hypothesis 1:  Compared to control participants, participants randomized to the intervention will have 
improved nighttime sleep (i.e., higher sleep efficiency, better self-reported sleep) and better PAP 
adherence (measured objectively) at 3-months follow-up.  
This hypothesis tests for differences between the intervention and control groups in our primary outcome 
measures of nighttime sleep and PAP adherence, between baseline assessment and 3-months follow-up, 
which is our primary time endpoint.  Subjective measures of sleep outcomes will include sleep diary (sleep 
onset latency, wake after sleep onset [WASO], and sleep efficiency) and sleep quality (PSQI).  The objective 
measure of sleep outcome will be actigraphy (sleep efficiency), and the objective measure of PAP adherence 
will be downloaded from the PAP smart card (percent of nights with PAP use > 4 hours, and mean hours of 
PAP use per night).   All outcomes will be assessed using intention to treat analyses.  A 2 X 2 (time X group; 
where time = baseline or 3-month assessment; and group = intervention or control) analysis of covariance 
analysis will be used with Bonferroni-corrected post-hoc comparisons to investigate differences between the 
groups in terms of treatment effects in the sleep variables (where baseline and 3-month follow-up data will be 
available).  For PAP adherence outcomes, there will be no “baseline” data (i.e., PAP adherence data isn’t 
available until the participant starts PAP therapy), so outcomes between groups will be compared with 
independent samples t-tests and Chi-square test for difference in proportions.   
We expect that the group by time analysis of covariance for the sleep variables will show a difference 
between groups, and post-hoc analyses will show increased nighttime sleep efficiency and improved self-
reported sleep (indicated by lower PSQI scores) in the intervention group compared to the control group. 
Following review of graphical representation of our longitudinal results (on main outcome measures), we will 
use repeated measures ANCOVA models to test both linear and nonlinear (i.e., quadratic) differential changes 
over time.  Post-hoc tests within each time point (using Tukey type 1 error control) will be conducted.  We 
expect there will be no difference between intervention and control groups at baseline, but differences will be 
present at follow-up. Other participant characteristics will be considered as possible covariates to reduce bias 
in our estimate of treatment effects and to increase precision. The major covariates that we expect to consider 
are age, cognition (estimated by MMSE) and comorbidity (estimated by CIRS-G).  Other covariates we will 
consider include specific diagnoses and medications that may interfere with sleep, and measures of the 
intervention process (DBAS-16 scores, Self-efficacy, Knowledge and Decisional Balance Index subscales ). 
Sample size calculations were performed for each of the main outcome variables using reported effect 
sizes and/or calculated effect sizes from reported sample means and standard deviations reported in the 
literature in prior studies of CBT-I for insomnia and behavioral PAP adherence interventions in outpatient 
adults (see Table 5).  Prior literature indicates that CBT-I is an extremely potent intervention for insomnia, and 
the studies typically have large effect sizes and small samples.  Some caution is warranted, however, since 
efficacy studies usually employ tightly controlled ‘ideal’ treatment conditions, which also yield larger effect sizes 

Study Protocol: 7/14/2015 
 
 
 
14 
 
than effectiveness studies with more ‘real world’ conditions.   Regardless of these issues, even the most 
conservative estimates of effect size from the literature suggest we will have an adequate sample size to test 
our sleep outcomes.  A recent meta-analysis of trials of PAP adherence interventions published as a Cochrane 
review was used in estimating sample size for the PAP adherence component of our intervention;Error! Bookmark 
not defined. this analysis suggests we will have an adequate sample size to test our PAP adherence outcomes. 
For the proposed study, we calculated sample size based on the outcome at post-treatment, and either 
the reported effect size (d) or d calculated from the reported means and SDs.  The table below lists sample 
size needs for the entire duration of the study (i.e., 6 months).  Based on an expected 15% loss by six months, 
the 5th column in the table below projects the sample size needed for each of 2 groups at randomization to 
maintain sufficient sample size at 6 months to test the selected outcomes. 
 
Table 5 lists expected effect size, shown as the variable “d” (difference between intervention and control 
groups at follow-up divided by standard deviation).  For many outcomes, we list several expected effect sizes 
from the literature; references for these effect sizes are listed in the second column.  The effect size estimates 
take into account expected change in controls over time, since we expect controls will change, but not as much 
as the intervention group.  The sample size needed at randomization to detect effect size d is shown (column 
4), followed by the number of enrolled participants needed for the 6-month analyses (column 5), taking into 
account expected dropout by this time point.  Based on these calculations, 120 randomized participants (60 
per group) will be adequate for analyses at both 3 and 6 months. In addition to these main analyses, we will 
perform follow-up subgroup analysis to identify two or three variables which identify participants who have the 
greatest positive response to the intervention.  Testing for subgroups with better or worse response results in 
such a small sample that overfitting is a potential problem; this risk is discussed below. 
 
For example, in Table 5 the third row (WASO by sleep diary) shows that to have the needed sample size 
(N=19 per group) completing the study (i.e., with follow-up assessment data) to test for an effect (based on an 
expected 15% participant loss by 6 months), we need to enroll 22 participants per group (column 5) at baseline 
to have 19 participants per group remaining at 6 months follow-up.  For all variables listed, we expect an 
adequate sample size to test our hypotheses.  For all sample size calculations, the dropouts are assumed not 
to change on average. All testing assumes a two-sided .05 significance level with 80% power. 
Table 5:  Sample size calculations 
Outcome 
Reference 
Reported (or 
calculated) effect size d 
Enroll per group 
for d:  post-test 
Enroll per group for 
d at 6 months 
WASO  
Sleep diary 
GermainError! 
Bookmark 
not defined. 
.67 
19 
22 
Sleep efficiency  
Sleep diary 
EspieError! Bookmark not 
defined. 
.68 
13 
15 
GermainError! 
Bookmark 
not defined. 
.64 
16 
19 
Actigraphy 
EdingerError! 
Bookmark 
not defined.  
.60 
27 
32 
Sleep onset  latency  
Sleep diary 
EspieError! Bookmark not 
defined. 
.58 
20 
23 
GermainError! 
Bookmark 
not defined. 
.80 
10 
12 
Sleep quality 
PSQI, similar 
scales 
EdingerError! 
Bookmark 
not defined.  
.58 
20 
23 
GermainError! 
Bookmark 
not defined. 
1.37 
10 
12 
PAP adherence 
 
Cochrane 
ReviewError! Bookmark 
not defined.  
.59 
47 
54 
 
OlsenError! Bookmark not 
.55 
54 
62 

Study Protocol: 7/14/2015 
 
 
 
15 
 
 
Hypothesis 2: Compared to control participants, participants randomized to the intervention will report 
fewer depressive symptoms and better health-related quality of life at 3-months follow-up.  
This hypothesis tests for differences between the intervention and control groups in depressive 
symptoms (using the PHQ-9) and health-related quality of life (using the SF-12v2) between baseline 
assessment and 3-months follow-up.  All outcomes will be assessed using intention to treat analyses in an 
identical manner as described for Hypothesis 2.  For sample size calculations, we used data from studies that 
used the same instrument as planned for the current proposal (if available) or from studies where similar 
measures were used, if results from the identical measure were not available (see Table 5).   
 
Hypothesis 3: Compared to control participants, participants who receive the intervention will maintain 
improvements in sleep, PAP adherence, mood and quality of life at 6-months follow-up.    
This hypothesis tests for differential change in outcomes between the intervention and control groups 
from baseline to follow-up assessment at 6 months, to test for maintenance in differences between intervention 
and control groups in the key sleep, PAP adherence, depressive symptoms and quality of life outcomes at 6 
months follow-up.  The statistical analyses used will be the same as described for Hypotheses 1 and 2.   
 
Hypothesis 4a: Among intervention participants, improvements in beliefs and attitudes about sleep 
and OSA will be associated with improved nighttime sleep and better PAP adherence at 3- and 6-
months follow-up.   
 
Hypothesis 4b: Intervention participants will identify factors that act as facilitators or barriers to their 
participation and adherence with the intervention. 
We will measure (in both the intervention and control groups) participants’ beliefs and attitudes about 
sleep (using the DBAS-16 ) and OSA and PAP therapy (using the Self-efficacy, Knowledge and Decisional 
Balance Index subscales).  We will test for differences between groups in these scales between baseline and 
3-months follow-up using analysis of covariance (as described above under Hypothesis 1).   These scales will 
also be included as covariates in secondary analyses of main study outcomes to address the effect of “dose” of 
intervention received on particular participant outcomes (e.g,. nighttime sleep and PAP adherence). Within the 
intervention group, we will also review specific aspects of the process of the intervention (e.g., sleep diary data 
on bedtime, rise time, in-bed time and daytime napping) to further clarify whether key aspects of the 
intervention were implemented by participants. 
In addition, qualitative information will be collected from intervention participants during focus groups 
conducted after completion of the 6-month follow-up assessment to determine participants’ experiences and 
attitudes about the intervention which may act as potential facilitators or barriers to future implementation into 
clinical practice (from the patient point of view).   We will perform three types of analyses of this data. First, 
during the focus groups, the moderator will assure face validity and accuracy of understanding as the 
discussion progresses, and will summarize key points and invite further comment and clarification from 
participants. The second analysis will be completed immediately following the focus group, where the 
moderator and note taker will debrief each other, using notes and the audio-recording to generate a description 
of issues and themes that arose in response to each question in the interview guide. This grounded approach 
integrates data collection and analysis, so the individuals who are most familiar with narrative responses 
identify core themes (e.g., difficulty with adhering to certain aspects of the intervention) that emerged in 
discussions. These themes will be incorporated in the coding system for the final level of analysis. The third 
analysis will be a note-based25 aggregation of domains and thematic responses across the focus groups.  
Transcriptions and audio recordings will be used as reference documentation. Themes (e.g., beliefs about 
defined. 
 
RichardsError! Bookmark 
not defined. 
1.12 
14 
16 
Depression 
Hamilton 
Depression Scale 
GermainError! 
Bookmark 
not defined. 
.67 
14 
16 
Quality of life 
SF-36 
BuysseError! Bookmark 
not defined. 
.57 
50 
58 

Study Protocol: 7/14/2015 
 
 
 
16 
 
acceptability of treatment) and specific issues (e.g., barriers) will be identified and inform future broad 
implementation of the intervention.  
 
Potential Shortcomings in the Proposed Analysis 
         There are statistical problems we may encounter in analyses, including the statistical handling of 
participant dropout, possible differential treatment effects across randomization blocks, and the risk of 
overfitting the data.  To deal with dropouts, we will use standard "intention to treat" analysis.  The main 
independent variable will be whether a participant is in the intervention or control group, rather than whether 
the participant actually receives the intervention.  If the participant rejects the intervention at some point after 
randomization, but allows us to collect follow-up data, we will use standard “intention to treat” analysis.  If the 
participant stops providing data, we will do analyses using all available data, and then repeat analyses after 
estimating missing data using an EM (expectation-maximization) algorithm, which is less subject to bias than 
other methods such as carrying forward the last available value; results from both analyses will be reported.  It 
is important to address dropouts, since those who complete the study may be more compliant or healthier than 
those who drop out.  To understand how “completers” may differ from “dropouts”, we will compare their 
baseline characteristics.  Dropout rates and characteristics of dropouts will also be compared between groups. 
To address the risk of a differential effect of the intervention between randomization blocks, we will test for 
a block by group interaction.  If one is present (suggesting the treatment is more or less effective for one 
stratification group over another), the results cannot be pooled, which impacts statistical power.  However, we 
anticipate overall treatment effect will overshadow any differential effects across stratification blocks. 
Finally, there is a risk of overfitting the data when we perform follow-up subgroup analyses to identify 
characteristics of participants who have the greatest positive response to the intervention.  We will address this 
issue in two ways.  First, we will use factor analysis with the full sample to group the independent variables into 
a small number of factors, then use clinical judgment and the literature to pick one representative variable from 
each factor.  Second, we will use repeated split-sample methods in fitting the data.  These methods repeatedly 
test the fit developed on part of the data on the remaining data.  We have extensive experience with these 
methods to address potential shortcomings in analysis, and additional local expertise and resources are readily 
available to advise the study team on these issues. 
 
Limitations of the Proposed Research 
There are three major limitations to the proposed research that will be addressed here.  First, although we 
will measure the effects of the intervention on attitudes and beliefs about sleep and PAP therapy, we may not 
be able to determine a causative association between other aspects of the process of the intervention and 
study outcomes.  In addition, our qualitative data collection will focus on the experience of intervention 
participants, and may not address other issues of future implementation (e.g.., barriers and facilitators at the 
provider and healthcare facility level).  However, we will seek advisement from the local HSR&D Center of 
Excellence on these other implementation issues and, if the proposal is successful, we plan to pursue 
additional funding for work aimed at implementation of the intervention into clinical practice.  Second, we will 
not be able to test the role of CBT-I alone or the PAP adherence program alone, as compared to the 
combined, integrated intervention in determining outcomes.  This would require a 4-group study design (i.e., 
CBT-I alone, PAP adherence program alone, integrated CBT-I plus PAP adherence program [our intervention], 
control group), which would at least double the necessary sample size.  In fact, comparison of active treatment 
conditions (e.g., CBT-I alone versus integrated CBT-I plus PAP adherence program) would likely require an 
even higher sample size to achieve adequate power for statistical analyses.  Based on our clinical experience, 
we believe a behavioral approach to managing coexisting OSA and insomnia in older Veterans must address 
both conditions in an integrated manner, as included in the current proposal.  Third, because we have chosen 
an active control condition (rather than a usual care control condition), we will not be able to test for a 
difference between our intervention and usual care.  However, based on our experience in testing behavioral 
interventions and current thought on how to best address the “placebo” effect with behavioral interventions, we 
feel it is essential to provide an active, “social attention” control condition to address a possible placebo effect.  
In addition, we’ve found that an active control condition keeps participants randomized to the control group 
engaged in the research, maintains contact with them to a similar degree as the active treatment group, and 
thereby helps prevent greater dropout among controls.   
 
Dissemination and Implementation Plan 

Study Protocol: 7/14/2015 
 
 
 
17 
 
As in our prior work, we will make extensive efforts for broad dissemination of research findings and 
implementation of the methods tested in this proposal.  Research findings will be disseminated at local, 
regional and national geriatrics/gerontology, health services and sleep meetings and in publications in high 
impact journals. Findings will also be disseminated via educational venues of the VA GLAHS GRECC, our 
local VA HSR&D Center of Excellence, and the UCLA/VA Multicampus Program in Geriatric Medicine and 
Gerontology. The senior researchers involved in this proposal have extensive professional links, both within 
and outside the VA, nationally and internationally, allowing for extensive dissemination.  For example, Dr. 
Alessi is a Member of the Board of Directors and is currently President of the American Geriatrics Society, 
Immediate Past Chair of the Health Sciences Section of the Gerontological Society of America, a member of 
the VA National Geriatrics Task Force, and a prior Chair of the Circadian Rhythms Section of the American 
Academy of Sleep Medicine.  Dr. Martin is a nationally recognized behavioral sleep medicine specialist and is 
one of 3 national trainers in the ongoing VA Evidence Based Practice roll-out of CBT-I for VA mental health 
professionals.  In addition, our GRECC provides extensive training to staff and trainees at VA GLAHS, and 
findings from this study will be incorporated into this training, which can be disseminated regionally and 
nationally. Dr. Zeidler is Associate Director of our Sleep Medicine Fellowship Program here, and will 
disseminate findings through educational venues in our sleep program.  We will also incorporate findings from 
this study into ongoing quality improvement projects at VA GLAHS. 
We also have an extensive implementation plan that focuses on local and national implementation.  
Locally, if the intervention is successful, these methods will immediately be implemented at VA GLAHS through 
our local insomnia treatment programs (which Dr. Martin directs) and OSA treatment in our VA GLAHS sleep 
clinics (staffed by Dr. Zeidler).  Both these programs are housed within the VA GLAHS American Academy of 
Sleep Medicine accredited Sleep Disorders Center (directed by Silverio Santiago, MD, who has provided a 
letter of support for this proposal).  The treatment materials and manuals developed for this intervention will be 
immediately adopted for use within these clinical programs.  This local dissemination will rapidly allow access 
to this intervention at our medical center, and will provide information as to whether the intervention remains 
effective when implemented clinically.  In an ongoing process, we will track whether clinical outcomes from 
initial local implementation of this treatment program are comparable to outcomes obtained in the proposed 
trial.  If needed, revisions will be made to the treatment prior to dissemination beyond VA GLAHS.  As part of 
this local implementation, we will solicit feedback from clinicians and trainees who use the intervention program 
and materials, to modify the intervention materials prior to broader implementation. 
We believe that broader implementation outside VA GLAHS will require additional funding.  If the 
intervention is successful, we will propose a 3-step approach for broader implementation.  The first step will be 
to develop a patient screening algorithm that can be used to identify Veterans who are appropriate for the 
intervention.  We believe that development of a structured algorithm must be included with the intervention 
program materials to help clinicians identify Veterans who are most appropriate for the intervention. This 
algorithm will be based on screening methods implemented in the current proposal, modified based on findings 
of the study.  Second, using results from the intervention focus groups performed in the current proposal, we 
will identify patients’ perspectives on potential facilitators and barriers to implementation of the intervention.   
These results will be used to modify the intervention methods prior to broader implementation testing.  Finally, 
using these results and intervention materials from the larger study, we will develop an implementation 
package for broader implementation, which will provide the actual tools needed to implement this model of 
care into current clinical practice. Toward that aim, we will develop a multi-component intervention 
implementation package that will include screening tools, treatment materials, treatment adherence monitoring 
techniques, key pre- and post-intervention outcome measures, and training materials for providers who 
implement the intervention. This implementation package will be based on our research findings, input from 
Veterans who completed the program, and consultation from experts in behavioral treatment of insomnia and 
in adult education methodologies. We’ll test the revised materials in an iterative process, until ready for 
implementation. 
We believe this type of intervention will be most easily implemented in the context of sleep clinics, which 
house the expertise to oversee the CBT-I and PAP adherence aspects of the intervention.  It is possible the 
intervention can be implemented with oversight at a distance from the site of implementation, which would 
provider for even broader implementation.  Dr. Martin is one of three national trainers for the Evidence-Based 
Psychotherapy Rollout of CBT-I.  In this program to date, over 400 VA mental health providers have completed 
training in CBT-I; this resource provides a tremendous opportunity for implementation of an intervention 
combining CBT-I and the behavioral PAP adherence program.   
 

Study Protocol: 7/14/2015 
 
 
 
18 
 
 
                                                 
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