Efficacy of a Healthy Lifestyle Intervention to Reduce Depression in Older Spousally-bereaved Adults
Phase: NA
Conditions: Depression
Sponsor: University of Pittsburgh

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Brief Title: Depression Prevention in Older Spousally-bereaved Adults 
 
NCT Number: NCT04016896 
 
Unique Protocol ID: STUDY19080039 
 
 
Study Protocol and Statistical Analysis Plan 
 
 
This document contains the following items 
1. Final protocol (p 2 - 7)  
2. Fidelity monitoring plan (p 7 – 8) 
3. Statistical analysis plan (p 8 – 11) 
4. References (p 11 – 12)  
 
 
 
 
 
 
 
 
 
 
 

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1. FINAL PROTOCOL 
Overview  
This study will enroll 150 older spousally-bereaved adults who are high risk for major depressive 
disorder (MDD) due to subthreshold symptoms of depression. These subjects will be randomly 
assigned to digital monitoring of sleep, meals, and physical activity behaviors or enhanced usual 
care. Subjects will be followed for 12 months after the intervention. We selected a 12-week 
intervention because this length of time was (a) sufficient to observe change in the proposed 
mechanism of action (circadian rest activity rhythm); and (b) acceptable to participants in our 
pilot RCT. 
 
Participants and Study Design 
Participants. A total of 150 older adults will be enrolled in the proposed study. We have chosen 
to target spousally-bereaved adults aged 60 years and older for the following clinical and 
methodological reasons: (a) adults aged 60 years and older experience bereavement differently 
than younger age groups because older adults are also experiencing declines in physical, mental, 
and cognitive health that may inhibit adaptive functioning following bereavement; (b) recently 
bereaved elders (≤ 12 months post spousal death) are at heightened risk for depression and other 
mental health problems related to poor self-care; (c) there is an urgency to understand strategies 
to modify the trajectories of depressive symptoms in bereaved elders already at risk for 
developing depression (indicated prevention) given the growing population of older adults who 
become bereaved each year, (d) examining bereaved elders who are at risk for depression is 
necessary to observe changes in response to the intervention over the short period of time that is 

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feasible to conduct a RCT. Targeting older adults who are not at risk for depression would 
increase the likelihood of ceiling effects. 
 
Eligibility Criteria.  Inclusion criteria will be (1) aged 60 years and older; (2) spousally bereaved 
within 12 months post-loss; and (3) at-risk for MDD, based on high-risk markers defined as 
subthreshold symptoms of depression (Hamilton Depression Rating Scale score ≥ 9),1 together 
with absence of current MDD, post-traumatic stress disorder, or persistent complex bereavement 
disorder Exclusion criteria will be (1) current DSM-5 criteria for syndromal mood, psychosis, or 
anxiety disorder within the last 12 months; (2) dementia; Modified Mini-Mental State 
Examination <80;2 (3) acute suicide risk; based on Herbeck et al. protocol for suicide risk 
management3; and (4) patients taking new psychotropic medications after spousal death to 
stabilize depression including antidepressants and benzodiazepines >4 days/week for more than 
two months. Individuals who have been on a stable dose for at least 1 month and agree not to 
change during participation, unless it is medically necessary, will be included.  
 
Recruitment & Screening Strategy. To enroll a total of 150 participants (n=30 in Year 01, n=50 
in Years 02-03, n=20 in Year 04), we will take advantage of our network of community partners 
including: (1) Allegheny Health Network’s Healthcare @ Home Hospice Care, (2) primary and 
specialty medicine at the University of Pittsburgh, (3) faith-based organizations; (4) extensive 
print and on-air advertising via the UPMC Aging Institute (aging.upmc.com); and (5) University-
affiliated research registries (ctsi.pitt.edu). We have successfully recruited participants from each 
of these partners for the pilot study. We recognize that efforts to recruit adults who are not 
seeking treatment may be difficult. Recruitment materials will emphasize healthy aging, thereby 

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encouraging participation by individuals who are interested in health, rather than illness-related 
research. Once interested participants are identified, they will be scheduled for a clinical 
assessment during which they will complete a battery of psychosocial questionnaires. Those 
identified ‘at-risk’ will be enrolled.  
 
Procedures 
Baseline. All participants will receive written education about healthy lifestyle choices including 
pamphlets from the National Sleep Foundation, the US Department of Agriculture’s Choose My 
Plate, the NIA’s Age Page on Aging and Alcohol Abuse, and the NIH’s Getting Fit for Life. We 
will help participants to choose a personal health goal on which to focus during the study; 
examples include: (a) engage in 150 minutes of moderate-intensity activity/week; (b) don’t skip 
breakfast; and (c) get 7-8 hours of sleep per night, among others. 
 
Widowed Elders’ Lifestyle after Loss (WELL) Intervention Protocol. The WELL intervention is 
a multicomponent intervention that uses digital monitoring and motivational health coaching to 
encourage a regular routine of sleep, meals, and physical activity. The combination of self-
monitoring, performance feedback, and motivational health coaching will help to ensure the 
Figure 1. Study Design 

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success of study participants. This multicomponent strategy has proven acceptable, with 93% 
retention in our pilot RCT. Figure 1 shows the study design. 
 
• Digital Monitoring Component. We chose to implement an intervention that we hypothesize 
might reduce depression symptoms via re-entraining a regular routine: behavioral self-
monitoring of sleep, meals, and physical activity. Behavioral self-monitoring interventions 
teach individuals to become mindful of their behaviors and the conditions in which they 
occur. By increasing awareness and understanding of one’s own behavior, improvements in 
physical activity, dietary behavior, weight status, and sleep have been observed across 
diverse populations.4–6 Monitoring is usually performed over several months, with 
individuals recording specific behaviors (e.g., minutes exercising, bedtime/wakeup). 
Participants randomized to WELL will record the timing of sleep, meals, and physical 
activity twice daily via Qualtrics on their tablet, smartphone, or PC, for 12 weeks. Tablets 
will be provided to participants who do not own their own device, to improve the 
sustainability of a technology-based treatment in population subgroups. The digital diaries 
includes questions to re-entrain a regular routine; including items from the Pittsburgh Sleep 

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Diary;7 the (1) Morning Diary asks about the previous night’s sleep including bedtime 
(hh:mm); time to fall asleep (minutes); number of nighttime awakenings; mood at bedtime 
(alert, sleepy, worried, anxious; scale 1-10); quality of sleep (scale 1-10); time of morning 
awakening (hh:mm), time out of bed to start daily activities (hh:mm); and mood at morning 
awakening (scale 1-10; very good – very bad); the (2) Evening Diary asks about physical 
activity, diet, and sleep behaviors throughout the day including time daily activities started 
(hh:mm); time of first contact with another person via phone or in-person (hh:mm); time of 
breakfast, lunch, and dinner (hh:mm); number of servings of whole grains, fruits, vegetables, 
calcium-rich foods, proteins, and alcohol); number of meals at a sit-down/take out restaurant; 
number of naps; time spent in light, moderate, and vigorous activity (min); time spent in 
sitting, walking, muscle strengthening activities (min); and mood throughout the day (scale 
1-10; very bad-very good).  
 
• Performance Feedback Component. The WELL intervention includes performance feedback 
to promote participant engagement and self-knowledge. During the intervention, a web-based 
“Lifestyle Log” illustrates the timing of and regularity of sleep, meals, and physical over the 

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last 7 days. User data from the Qualtrics surveys are fed into the Lifestyle Log, creating 
figures that update in real-time, providing users with up-to-date information about their self- 
behaviors.  
 
• Motivational Health Coaching Component. Improving self-care behavior can be challenging, 
requiring effort and motivation. Therefore, the effects of self-monitoring to optimize 
engagement in routine self-care may be enhanced by using motivational interviewing (MI) – 
a patient-centered approach to strengthen bereaved elders’ motivation and commitment to 
change.8 MI facilitates healthy lifestyle change by helping patients resolve ambivalence 
about change in an empathetic and encouraging climate.9,10 During weekly phone 
conversations, a “lifestyle coach” will use MI techniques (express empathy through reflective 
listening, develop discrepancy between current situation and future goals, avoid argument, 
and support self-efficacy) to help strengthen older adults intrinsic motivation to engage in a 
regular behavioral routine 
 
2. FIDELITY MONITORING PLAN 
Fidelity to digital monitoring was calculated by summing the number of times participants 
completed the digital diaries: 2 diaries per day for 3 months = 168 possible diaries. Using the 
gold-standard for coding fidelity of motivational interviewing – the Motivational Interviewing 
(MI) Treatment Integrity Coding Manual – four components of MI will be coded during each 
health coaching session: open-ended questions, affirmations, reflective listening, and 
summarizing statements.11 All MI sessions were audio recorded and 20% of sessions (from early, 
middle, and late intervention) were randomly selected for fidelity ratings (by a MI expert) to 
ensure maintenance of treatment specificity and integrity. The MI expert suggested therapeutic 

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strategies over the course of contact with participants to ensure fidelity to the desired target – 
regularity of sleep, meals, and physical activity. 
 
Table 1 shows our fidelity plan for monitoring intervention delivery, receipt, and enactment.12 
Using the gold-standard for coding fidelity of motivational interviewing – the Motivational 
Interviewing (MI) Treatment Integrity Coding Manual – four components of MI will be coded 
during each coaching session: open-ended questions, affirmations, reflective listening, and 
summarizing statements.11 All coaching sessions will be audiotaped and 20% will be randomly 
selected for fidelity ratings (by a MI expert, TBH) to ensure maintenance of treatment specificity 
and integrity. 13 The MI expert will suggest therapeutic strategies over the course of contact with 
participants to ensure fidelity to the desired target – regularity of sleep, meals, and activity. 
 
3. STATISTICAL DESIGN AND POWER 
Descriptive Statistics 
Data will be examined descriptively using observed means, standard deviations, and percentiles 
for continuous variables; and frequencies and proportions for categorical variables. We will 
Table 1. Fidelity Monitoring Plan

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examine continuous variables to determine if distributional assumptions, for e.g., normality and 
homoscedasticity, are satisfied. Transformations or nonparametric techniques will be applied as 
needed. Statistical comparisons will be performed to compare the intervention and control arms 
with respect to demographic characteristics and important health characteristics at baseline. 
Standard techniques include t-tests for continuous variables and Fisher’s exact test and/or 
Pearson χ2 procedures for categorical variables. The baseline values of the outcome variables 
will be analyzed in a similar manner to determine whether any systematic differences between 
the treatment arms remained after randomization. The proposed study is a randomized clinical 
trial with repeated measures, with the purpose of (1) assessing change over time for the 
intervention group relative to the enhanced usual care group and (2) comparing the change 
between the intervention and enhanced usual care group with regards to the primary outcome 
(depression symptoms).  
 
Randomization 
Groups will be randomized using a 1:1 randomization scheme to minimize threats to internal 
validity.14 We will use permutated-block randomization where subjects are allocated randomly 
within blocks known only to statisticians. Given the possibility of insomnia as an effect modifier 
we will stratify randomization based on presence of insomnia (Insomnia Severity Index ≥10).15 
We will follow the CONSORT 2010 checklist for randomization. Sequence generation: Dr. 
Krafty will generate the randomization sequence using the R statistical software. Allocation 
concealment: the randomization sequence will remain concealed to research staff.  Research staff 
who are enrolling participants will not know the allocation sequence in advance. Implementation: 
after a participant is determined eligible, research staff will contact Dr. Krafty about treatment 

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allocation. Consideration of sex as a biological variable: groups will be stratified by sex because 
women are more likely to experience the death of their spouse compared to men (75% of 
participants in our pilot RCT were women).  
 
Efficacy Analyses  
We will employ repeated-measures mixed-effects ANCOVA, which extend the standard 
repeated measures ANCOVA to allow for missing values, error structures other than compound 
symmetry, and measurements taken non-equal intervals. The test of efficacy for the intervention 
will be analyzed under an 'intent-to-treat' criteria.16 We will control for important baseline 
variables, including baseline levels of the outcome of interest (HAM-D), and, to extend the 
'intent to treat' mechanism, all participants randomized into the study are included in all analyses 
irrespective of protocol violations arising post randomization. Inclusion of covariates may add 
precision to the estimates and allow us to assess the generalizability of the effects across the 
covariates. The list of covariates, (e.g., age, sex, race, medical co-morbidity) will be developed 
prior to any analysis. Statistical significance will be α=0.05 (two-tailed).  Controlling for 
baseline variables will allow us to assess both group differences (main effect of group) and for 
differential change over time for depression symptoms repeatedly over the course of the study 
(group X time interaction). If the group X time interaction is significant, we will assess in post 
hoc tests, where the two groups differ. If no group X time interaction, will test main effects only. 
In all analyses, the time (in days) since spousal death will be included as a covariate. 
 
Missing Data 

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Missing values are inevitable in clinical research. Participants may drop out from the 
intervention for a variety of reasons, including time constraints, competing interests, and 
personal choice. If, despite our projections, there is substantial missing values, we will 
incorporate the impact of censoring due to lost to follow-up and dropout into the analysis to 
assess if possible bias exists. We will use pattern mixture models to evaluate if the missing 
mechanism has an influence on parameter estimates. We will use standard multiple imputation 
for conducting inference on full data effects. If our data are not missing at random (MAR)17 (i.e., 
pattern of ‘missingness’ is similar between groups), we will assess the impact of missingness on 
our estimates and will use pattern mixture models to check that there are no untoward influences 
of missing values. Pattern mixture models compare the outcomes (trajectories) across the various 
patterns of missing data.18  
 
Sample Size and Power Calculations 
Power calculations for each aim were calculated assuming effect sizes as estimated from the 
preliminary data collected in 55 subjects in the PI’s pilot RCT. Calculations were conducted in R 
using the pwr and powerMediation packages. All tests were conducted at level α=0.05. In the 
preliminary data, a Cohen’s d of 0.616 was observed for the change in depression scores after 
treatment between WELL and EUC. Under this effect size, there is an estimated 96.3% power to 
detect differences in changes in depression among treatment groups in Aim 1.   
 
4. REFERENCSE 
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