Behavioral Health & Resilience Training for Military Leaders
Phase: NA
Conditions: Health Behavior, Well-Being
Sponsor: Oregon Health and Science University

 
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Template Revised: 6.11.2015 
 
 
PROTOCOL FOR: 
 
BEHAVIORAL HEALTH & RESILIENCE TRAINING FOR MILITARY 
LEADERS 
 
DR. LESLIE HAMMER, PI 
 
NCT04152824 
 
UPDATED: OCTOBER 12, 2022 
ORIGINAL VERSION: NOVEMBER 25, 2019 
 
 
 

 
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Template Revised: 6.11.2015 
 
1. Protocol Title 
Behavioral Health & Resilience Training for Military Leaders 
 
2. Objectives 
Current training on resilience in the military focuses on the individual. Thus, leaders are trained 
in how to improve their own resilience but not necessarily how to support resilience within their 
troops. The proposed study adapts the researchers’ existing evidence-based supportive 
leadership training for Veterans and the National Guard to an active duty population. The 
ultimate aim of our intervention is to train supervisors to be more supportive toward their 
subordinate soldiers leading to improved readiness, resilience, health and well-being of 
subordinates. The multi-component intervention uses accelerated-learning techniques, such as 
breaking information into small units and using various modalities of delivery. While being 
piloted with an Army population at Joint Base Lewis-McChord (JBLM) in Washington, the end 
training product will be translated and applicable for all branches and first-responders, 
enhancing resilience in the face of stressful and hazardous workplace situations in a myriad of 
contexts. 
The overarching goals of this proposed study are to: 
 1) customize our existing evidence-based intervention on supportive supervision to 
active duty leaders in the U.S. Army with a focus on resilience and readiness, which 
we are calling the Resilience Supportive Leader Training (RESULT),  
2) evaluate RESULT and its effect on psychological health, unit cohesion, resilience and 
readiness of subordinates,  and  
3) translate RESULT to leaders in all branches of the military, as well as civilian first-
responders.   
Specific Aims of the study (listed in our Statement of Work in our funded grant): 
Specific Aim 1: Customize and adapt current evidence-based leadership support training 
intervention to develop a multi-component training intervention, Readiness Supportive 
Leadership Training (RESULT), using accelerated learning strategies aimed at improving 
Service Member resilience and readiness in the military.  
Specific Aim 2:  To assess the impact of RESULT intervention components using reports 
of leaders’ reactions to the training program in terms of satisfaction, utility, and learning 
outcomes (Hypothesis 1). 
Specific Aim 3: To test the effects of the RESULT training compared to the control group 
on perceptions of increased leadership resilience-supportive behaviors from the 
perspective of the service members, following the training (Hypothesis 2).  
Specific Aim 4: To test the effects of the RESULT training compared to the control group 
on behavioral health measures such as emotion regulation, connectedness, team 
cohesion, psychological health, and physical health following the training (Hypotheses 3 
& 4).  
Specific Aim 5: Translate the tenets of the RESULT to other branches of services, and 
other employee populations who would benefit, such as first responders.   
 
 
Study Hypotheses 

 
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Template Revised: 6.11.2015 
1) Leaders in the intervention group will report positive reactions to the training and will 
demonstrate increased knowledge from pre-test to post-test. 
2) Service Members in the intervention group will report improved perceptions of 
resilience-supportive leadership behaviors compared to those in the control group. 
3) Service Members in the intervention group will report higher levels of resilience-related 
factors such as adaptive emotion regulation strategies, resilience, social connectedness 
and belongingness, and team cohesion, compared to those in the control group. 
4) Service Members in the intervention group will report higher levels of resilience-related 
outcomes such as psychological and physical health and well-being, compared to those 
in the control group. 
 
 
3. Background 
The Department of Defense (DoD) has prioritized programs to optimize readiness by enhancing 
resilience of its service members. Psychological resilience refers to the process of coping with or 
overcoming exposure to adversity or stress (Meredith, et al., 2011). Resilience enables 
individuals to persevere in challenging times, and is comprised of trainable skills as opposed to 
stable traits (Reivich, Seligman, & McBride, 2011).  Despite this focus, a gap exists in the current 
military resilience training that teaches leaders to provide support to subordinate soldiers, 
thereby promoting their psychological health, resilience, and ultimately readiness. Our own 
previous research has demonstrated the effectiveness of supervisor training to provide support 
at improving health and workplace outcomes for subordinates (Dimoff et al., 2016; Hammer et 
al., 2011; Hammer et al., 2016; Odle-Dusseau, Hammer, Crain, & Bodner, 2016), including 
supervisors of veterans reintegrating into the civilian workforce. (Hammer et al., 2018). As in our 
previous work, the ultimate aim of our intervention is to train supervisors to be more 
supportive, leading to improved psychological health and well-being of subordinates.  
Review of Resilience Definitions and Resilience Training Programs in the Military 
The DoD and military services have embraced the idea of fostering resilience to maintain a 
healthy fighting force; however, there are no standard definitions and measures of resilience or 
outcomes used across DoD resiliency programs (Meredith et al., 2011). The Army has referred to 
resilience as the “ability to bounce back” (Reivich et al., 2011), suggesting an individual can 
maintain or return to previous levels of well-being and functioning in response to adversity 
(Bowels & Bates, 2010). A more recent perspective from the Air Force Resilience Training 
program suggests that resilience changes day-to-day; it is in a constant state of fluctuation 
where resilience resources and stressors can come and go (Meadows, Miller, & Robson, 2016). 
Additionally, others (e.g., Carver, 1989) have argued that beyond returning to a status quo, 
adversity can lead some to thrive or be stronger in the face of stress than before.  
The Army Comprehensive Soldier Fitness Program (CSF) was created to prevent adverse mental 
health outcomes associated with trauma exposure by implementing resilience-enhancing 
interventions before deployment (Denning, Meisnere, & Warner, 2014). The CSF includes five 
dimensions of health (physical, social, emotional, spiritual, and family) and is able to conform to 
each individual’s resilience level. Army Regulation 350-53 (i.e., CSF) defines resilience as “the 
mental, physical, emotional, and behavioral ability to face and cope with adversity, adapt to 
change, recover, learn, and grow from setbacks. A resilient and fit individual is better able to 
leverage intellectual and emotional skills and behaviors that promote enhanced performance 
and optimize their long-term health.” (Department of the Army [DA], 2014). The program is 
carried out through multiple avenues and includes resilience assessment tools, Master 

 
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Resilience Training (MRT), and online, self-help modules (Casey, 2011). The MRT curriculum 
consists of three components: Preparation, Sustainment, and Enhancement. The segments 
teach resilience fundamentals based on findings within the field of positive psychology, 
deployment cycle training, and personal skill-sets which enhance individual performance 
(Reivich et al., 2011). The MRT program is delivered through a 10-day, train-the-trainer model 
wherein unit leaders learn how to educate soldiers on respective resilience. These skills include 
improving awareness of individual assumptions and thought patterns in order to improve 
effectiveness and also are geared toward building mental toughness and strengthening 
relationships. 
Another resilience program to note is the Airman Resilience Training Program (ART). ART was 
implemented to help airmen cope with deployment-related stress and improve well-being 
(Gonzalez, Singh, Schell, & Weinick, 2014). Similar to MRT, this training is also administered via 
PowerPoint by trained “briefers” and is a one-size-fits-all approach, as all airmen receive the 
same training. The training includes components named the “four C’s” of coping with stressful 
deployment situations, which include: check, control, connect, and confidence (Gonzalez et al., 
2014). Check refers to self-awareness and checking on others around you. Control is related to 
self-control and the self-awareness of how one tends to respond in stressful situations. The third 
component, connect, is related to social connectedness with one’s friends and family. Finally, 
the last “C” is confidence, which is related to developing trust and leadership skills.  
In their assessment of resilience programs being conducted within military populations, Morgan 
and Bibb (2011) suggested that subsequent resilience programs be founded on evidence-based 
interventions and include measures that capture intervention effectiveness. The authors 
emphasized the need for providing resilience resources that are applicable across military 
branches, occupations, and ranks in order to increase warfighter consistency. In terms of 
improving current programs, it was recommended that the ART program modify its formatting 
and incorporate more specific information on topic areas that were considered important but 
were not initially included, such as sleep, health, and relationship building (Gonzalez et al., 
2014). Although contemporary resilience programs have demonstrated efficacy (Harms et al., 
2013; Lester et al., 2011), and have been perceived by service members to be helpful in their 
military jobs and civilian life (Griffith & West, 2013), they have the potential to be strengthened. 
The MRT and ART programs focus largely on improving leader’s own resilience with little 
attention to providing support to subordinates to improve their resilience. Thus, a gap exists in 
the current training in terms of offering strategies and tools for leaders to use when intervening 
to provide support to subordinate service members and thereby promoting their resilience.  
 
 
4. Study Design 
The study design is a cluster-randomized controlled trial randomized by battalion. There are 11 
battalions in the population we are targeting   at Joint Base Lewis-McChord (JBLM) in Lacey, 
Washington. Soldiers in each battalion will be randomly assigned to the RESULT intervention or 
usual practice control condition, ideally after baseline data collection, if possible. The 
intervention targets mid-level military leadership, namely the Platoon Leadership Team (PLT), 
usually consisting of a platoon leader (i.e., a junior-level officer) and a platoon sergeant.  
Figure 1 depicts the overall study design. To test the effectiveness of the intervention, we will 
collect data pre- and post- intervention from all soldiers, as well as platoon leaders. The control 
group will be usual practice, as we have done in most of our prior clinical trials. There are an 
estimated 5200 soldiers in the Battalions included in the study; we anticipate about 30% will 
participate with a target sample size of n = 1560).  

 
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Template Revised: 6.11.2015 
Figure 1. Study Design  
 
 
The surveys will take approximately 30 minutes to complete and will be completed 
electronically, using REDCap survey software. Survey participation is voluntary and leadership 
training is mandatory per the senior command at JBLM. However, any data collected from the 
leaders during training will be consented or if consent is not given, will not be analyzed.  
Baseline data collection with all Soldiers will be conducted within a 2-3 week period, with a 
follow-up survey 4 months later. The leadership training intervention will begin approximately 3 
weeks after the baseline survey is completed, with scheduling occurring over a 3 week period.  
A research unit at JBLM, the West coast arm of the Walter Reed Army Institute of Research (aka 
WRAIR-W) and with whom we have been working for several years, will provide advice in the 
form of consultation and coordination with unit leaders at JBLM. The WRAIR-W team located at 
JBLM has extensive experience working with operational partners for the development and 
execution of studies assessing novel interventions for optimizing psychological health and 
soldier readiness. Lieutenant Colonel Oscar Cabrera, Director of WRAIR-W, will serve as the 
primary consultant, with additional support from Major Mike Dretsch, Deputy Director. We are 
also currently working with WRAIR-W on our DoD-funded Military Employee Sleep and Health 
(MESH; Study #00016555) study that is taking place in the Oregon National Guard and have 
made numerous trips to JBLM to discuss current and future research. Based on this relationship, 
we have developed a greater sense of the context and culture of the workings at JBLM and our 
proposal has benefitted from the experiences of the WRAIR-W staff conducting studies at that 
installation. We have been discussing issues surrounding study design for over a year now with 
LTC Cabrera. While we are working with the Army specifically, we anticipate this training will be 
easily translatable to other branches, as well as to segments of the public sector, such as first 
responders. We have also developed a successful and supportive working relationship with the 
Division Behavioral Health leader, Major Connie Thomas, who has been critical to the 
RESULT STUDY DESIGN 
Intervention 
group: 
Supervisor In 
Person 
Training  
Survey #1:  
All Service 
Members 
Survey #2: 
All Service 
Members 
 
Intervention 
group: 
Supervisor 
Follow Up 
Activities 
Control Group: Usual practice 
SEP 2020   
OCT 2020 
FEB/MAR 2021   
NOV 2020 – 
JAN 2021 

 
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Template Revised: 6.11.2015 
development of this study, particularly in the COVID-19 era. The majority of the changes to this 
protocol are under her guidance. 
Randomization 
Based on advice received from our partners at JBLM, we determined that it is best to randomize 
at the battalion level because of the likelihood of contamination effects between intervention 
and control groups if randomization was conducted at a lower level (e.g., platoon or company). 
Furthermore, randomizing at the battalion level will provide protection from intervention 
selection effects that occur in traditional non-equivalent control group quasi-experimental 
designs.  Along with the collection and use of baseline, pre-intervention soldier data for the 
targeted study outcomes, our proposed approach can go a long way in reducing concerns 
related to biases that undermine internal validity when it is not feasible to randomize more 
units by balancing potentially confounding covariates across study conditions (Shadish, Cook & 
Campbell, 2002).  
 
Timeline 
Start date: 15 SEP 2019, anticipated end date: 14 SEP 2022 
 
 
 
 
 
 
 
 
 
 
Note: Lighter color cells are for contingency planning 
The first three quarters will focus on hiring personnel, formative information gathering, regulatory review, 
protocol creation, and refining our schedule. Coordination and refining the timeline for participant 
recruitment will occur during the first nine months; however, actual participant recruitment will not happen 
until after we receive HRPO approval. Intervention activities begin about 3-weeks (intervention group only) 
after the baseline survey so they co-occur in the same quarter. The follow up survey is 4-months post-
baseline. Contingency periods are built in for both the intervention and 6-month survey. Data cleaning 
begins shortly after the first surveys are administered. The last year of the grant is reserved for translating 
the intervention to other branches of the military, analysis, writing and dissemination of findings. 
 
 
 
 
 
Activity 
YEAR 1 
YEAR 2 
YEAR 3 
  
1 
2 
3 
4 
1 
2 
3 
4 
1 
2 
3 
4 
IRB and HRPO approval 
  
  
  
  
  
  
  
  
  
  
  
  
Formative Information Gathering 
  
  
  
  
  
  
  
  
  
  
  
  
Survey Development 
  
  
  
  
  
  
  
  
  
  
  
  
Coordination/Timeline 
  
  
  
  
  
  
  
  
  
  
  
  
Customization of Intervention 
  
  
  
  
  
  
  
  
  
  
  
  
Baseline survey 
  
  
  
  
 
 
  
  
  
  
  
  
Implement Intervention  
  
  
  
  
  
  
  
  
  
  
  
  
6-month Survey 
  
  
  
  
  
  
  
  
  
  
  
  
Cleaning & Analyzing Data 
  
  
  
  
  
  
  
  
  
  
  
  
Report Findings 
  
  
  
  
  
  
  
  
  
  
  
  
Write Papers/Translation/Dissemination 
  
  
  
  
  
  
  
  
  
  
  
  

 
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5. Study Population 
 
a. Number of Subjects 
For the intervention, approximately 102 Platoon Leadership Teams (PLTs) from 7-8 battalions 
will be targeted for leadership training and testing of Hypothesis 1. For Service Member 
participation, based on communications with our JBLM partners, we expect about 30% of the 
total population (N=5200) to participate (n=1560) at baseline. In addition, based on both our 
own experience and on those same communications, we expect about 20% attrition at the 
second data collection, owing largely to individual change in duty stations, remote training, 
deployments, etc. Thus, we anticipate 1245 soldiers to participate in the study data collection at 
baseline and at the 6-month follow-up for Hypotheses 2, 3 and 4.   
We will work with command teams to avoid data collection, when possible, that would be timed 
during large deployments or other similar anticipated events. Participation in the training is 
mandatory, though allowing our researchers to use data collected in association with the 
training (e.g., test scores, reaction) will be consented. However, the increased sample size will 
allow our team greater flexibility in dealing with these issues should they arise. 
 
b. Inclusion and Exclusion Criteria 
The inclusion criteria for soldiers is to be currently serving Active Duty in one of the targeted 
battalions, and in positions of platoon leader or below. For the leader training, we will target the 
platoon leaders and platoon sergeants. We will work with senior leadership to identify these 
individuals. 
 
c. Vulnerable Populations 
No individuals who are known to be members of a vulnerable population will be enrolled.  We 
will not identify subjects on whether they are members of a vulnerable population. In other 
words, we will not collect any information about subjects’ status as part of any vulnerable 
populations, including prisoners, pregnant woman, children, neonates, and/or adults lacking 
capacity. 
d. Setting 
 
Survey data collection will occur online using REDCap survey software. Currently, training delivery will all 
take place on site at Join Base Lewis-McChord (JBLM) near Tacoma, WA. For the training, class size will 
be limited to 10 people, including the training, wearing masks. If COVID-19 conditions worsen, training 
will be conducted remotely using Webex or Microsoft Teams. Data collection (i.e., recruitment, 
consenting, data analysis) will be performed primarily by OHSU personnel, with some Portland State 
University (PSU) personnel assisting. PSU personnel will work under the direction of OHSU personnel to 
ensure all procedures are followed. PSU has ceded oversight to the OHSU IRB. We will also inform the 
IRB at JBLM of our study and provide study materials for their review.  
 
e. Recruitment Methods, Consent & Data Collection Procedure 
 
Baseline Survey Data Collections with Service Members 

 
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Data from the surveys, completed by soldiers, will be used to evaluate the Resilience Supportive 
Leader Training (RESULT). Recruitment will occur at the company level; each Brigade is 
comprised of approximately 20-25 companies of about 40-70 soldiers each.  
Several months prior to data collection and based on our timeline, our Study Coordinator will 
work with our staff at JBLM to have an Operations Order issued, directing a company to click or 
copy the provided link to the online survey. These orders are standard operating procedure for 
studies conducted with the military and assures time is set aside for participation during duty 
hours. Our contacts at WRAIR-W have used this procedure in previous studies. We will provide a 
recruitment flyer, included with IRB application. Soldiers will be required to access the survey, 
provide their name, rank and unit and then opt in or out by consenting or not. It will be made 
clear that they do not HAVE to complete the survey, but have to at least go through the opt 
in/out process. Names of the soldiers who have opted in/out will be provided to Battalion POCs, 
but not whether the soldier has completed the survey.   
Soldiers will be consented online and select “I consent to participate” if they would like to 
participate and then immediately be launched into the survey. If they select “I do not consent”, 
we will confirm their declination, and then the survey will end.   
The survey will be open for two weeks and our team will communicate several times with 
Battalion POCs to communicate who has accessed the survey (but not whether or not they 
completed the survey). At the conclusion of the two week period, the project manager will 
download the data from REDCap, deidentify and clean the responses, then store them on a 
restricted folder on Box. 
4-Month Follow-Up Survey 
The 4-month survey will mirror the baseline data collection, where another Operation Order will 
be issued with the survey link and a brief explanation for the study.  
We will duplicate the consent procedure at 4 months to cover those who did not participate at 
baseline (i.e., were not in the unit at that time, not present, or changed their mind about 
participating). The surveys will be identical except we will ask if they participated in the survey 
at baseline in order to facilitate matching of responses. 
Survey Incentives. Financial incentives will not be provided for participation, as service members 
are completing the surveys while on duty and compensation is not allowed while on duty hours 
per DoD regulations.  However, to help increase the response rate we will offer pizza for 
platoons with 50% response rate or higher.  
Platoon Leader Recruitment: Training 
After randomization occurs, our Training Coordinator (i.e., separate from Study Coordinator 
responsible for survey data collection) will work with Brigade command on scheduling for 
specific units, dates and times for the face-to-face training. Command will inform leaders when 
and where to report for training and that participation in the training is being mandated by 
Command (Note – we will consent for use of any training data; see below). Typically, two 
members of each Platoon Leadership Team will participate in the training, the Platoon Leader 
(i.e., officer) and Platoon Sergeant (i.e., enlisted, non-commissioned officer, who is subordinate 
to the officer). An Operations Order will be issued for the leadership team to be at the training 
at a designated date, time, and location. 
Prior to beginning the training, we will inform the leaders of our interest in including data 
associated with the training (e.g., test scores, reactions) as part of our research to evaluate the 
training but emphasize that allowing use of those data is voluntary and declining will not affect 
them in any way. We will clarify the while the training is mandated, the use of any training-

 
Page 9 of 22 
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related data is not. We will provide them an opportunity to complete the informed consent 
confidentially before beginning the training. We will have physical copies of the consent forms 
(included in the IRB submission) for them to sign and provide them a copy as well. In accordance 
with DoD regulation, if any senior-ranking officers are present, particularly if they command the 
platoon leaders, they will be asked to leave the room during the consent portion of the session. 
If they do not sign the consent form to use their training data, any individual data collected as a 
result of the training will not be used in the study. Blanks will be considered as non-consent. 
The leader intervention involves an initial in-person training with the PI of the study, including a 
computer-based training, an evaluation of a case study, group discussions and more related to providing 
resilience support for their subordinates. The content will be based on pervious training developed by 
the PI and consultants on the project, all which were part of previous IRB-approved protocols. The 
content will be adapted to focus on resilience and readiness in the military. Some examples of the types 
of information the training will include based on the Hammer’s (PI) prior validated trainings include: 1) 
the benefits of reducing stress and increasing resilience for one’s soldier; 2) why it is important to focus 
on resilience, making the case that it is important to support soldiers’ resilience so that it will make the 
team more autonomous and efficient in the field; 3) reducing suppression of emotion and increased 
reappraisal of negative situations (adaptive emotion regulation), leading to leaders facilitating stronger 
resilience behaviors in soldiers; 4) how to enact resilience supportive behaviors such as providing 
emotional and instrumental support and modeling effective resilience behaviors. Topics to be covered 
based on the Dimoff mental health awareness training: 1) facts about the prevalence of mental health; 
2) warning signs of deteriorating mental health; and 3) what leaders can do to promote resilience. The 
intervention also includes several ‘micro-learning’ activities over the following two months to reinforce 
learning and assist leaders to enact supportive behaviors they learned in the training. These activities 
include watching videos with testimonials about supportive leadership, podcasts, team activities, and 
quizzes. More detailed information can be provided to the IRB once it becomes available. 
 
Following current base regulations, class size will be limited to 10 individuals including the trainer with 
masks on. If conditions change, the training will change to comply with the current recommendations. 
 
f. Consent Process 
 
The consent process is described in detail above, but summarizing/highlighting salient points: 
• 
Consent will take place online,  just before survey data collection and/or just before training 
implementation.  
• 
Participants will be re-consented at the 4 month follow up survey. 
• 
We will have contact information available if Soldiers have questions. 
 
6. Procedures Involved 
 
Data collection procedures are described in #5 above, but summarizing/highlighting salient 
points: 
• 
Data collection is online using REDCap survey software. The link is available through an 
Operations Order issued by leadership at JBLM. The survey will be repeated 4 months 
later.  We estimate 30 minutes for completion. 
• 
For those leaders in the training condition, we will collect data about their learning, 
participation and reaction to the training. Training participation is mandated by the base 
leadership at Ft. Lewis; participants can chose whether they consent to their data being 
used.  

 
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Template Revised: 6.11.2015 
• 
Participants will be provided contact information for staff if they chose to withdraw from 
the study. 
 
7. Data and Specimens 
a. Handling of Data and Specimens 
 
Once downloaded from REDCap, data will be saved to a secure Box folder with very limited 
access (i.e., only study staff who need to access raw data based on their job description) and 
then imported into SPSS.  
De-identified data will be kept indefinitely on the secure servers at OHSU; data with 
identifiers will be deleted at the conclusion of the study. 
We will act as our own Repository for the survey and training data. We will keep it on the 
OHSU secure servers (X: drive) with access limited to only a few key research staff (i.e., PI, 
project manager, data manager). We will provide information on our study website 
(https://www.resultstudy.org/) at the completion of the study and once results are 
published on the potential availability of the survey data. Potential researchers will be 
provided with a form to complete, similar to what we use for our internal paper 
development purposes. Researchers will need to state the purpose of data use (e.g., specific 
hypotheses), provide a background rationale for those hypotheses, specify which variables 
are requested, and where the data will be published (e.g., the conference and/or journal). 
We will also provide acknowledgement language required in any papers or presentations. 
Once approved by the PI and the co-PIs, this information will be drafted into a formal Data 
Use Agreement signed by all parties. The Project Manager (currently Dr. Krista Brockwood) 
will be the repository guardian. 
 
All study staff dealing with both participants and/or data will have completed sanctioned 
Human Subject Research training. The PI and Project Manager both have experience with 
DoD-regulated research and reviewed these regulations with the DoD Science Officer after 
the grant was awarded. They will both be responsible for training any new study staff with 
regard to these specific DoD regulations. 
b. Survey Measures  
We will collect sociodemographic data and military experience, including military work 
history, combat exposure and deployment history. Our survey outcome measures will map 
on to our hypotheses to ensure we can evaluate between- and within-group effects. We will 
also ask which specific unit to which they are currently assigned so we can nest data within 
units and account for unit-level similarities (see Statistical Analysis below).  Some of the 
hypotheses include data that are not from the surveys, such as training data (pre- and post-
tests) (see Hypothesis 1), but we will track that information as well and merge with survey 
data. Table 1 includes a summary of proposed measures, sources, and when and from 
whom they will be collected. All proposed measures have been used in previous research 
and are psychometrically sound. A list of individual surveys items are included in our 
submission. 
Hypothesis 2 will be evaluated with a measure assessing the leader’s support for resilience 
within their unit. This measure, commensurate with previous work we have done (e.g., 
Family-Supportive Supervisor Behaviors and Sleep Leadership), will be developed based on 
tenets of the intervention. It will be measured from the perspective of the subordinates 
(e.g., “My platoon leadership team supports resilience in our unit”). Before reporting any 

 
Page 11 of 22 
Template Revised: 6.11.2015 
findings on Hypothesis 2, we will examine the psychometric properties of the adapted 
measure to ensure reliability and validity. 
The bulk of the survey will be comprised of measures that assess Hypotheses 3 and 4. 
Hypothesis 3 is specific to perceptions around resilience factors such as social 
connectedness, resilience, and emotional regulation, whereas Hypothesis 4 is specific to 
perceptions around resilience-related outcomes including psychological, physical health, 
and well-being.   
Table 1. Summary of Survey Measures 
Concept 
Measure 
Reference 
# of 
Items 
When 
collected* 
Who* 
Hyp. 
Leader Training 
Data 
Leader reactions to 
training 
Adapted from 
Hammer et al. (2011) 
3 
T 
PLT 
 
1 
Knowledge of resilience 
leadership 
Adapted from 
Hammer et al. (2011) 
3 
T 
PLT 
1 
Resilience-supportive 
Behaviors 
RSLB measure adapted 
from VSSB and FSSB  
(Service Member’s 
Ratings of Leaders) 
Adapted from Perry 
et al. (2018) and 
Hammer et al. (2009, 
2013) 
3-5 
S 
SM 
2 
Perceived Leader 
Effectiveness 
Adapted from Ragins 
1989 by WRAIR  
5 
S 
SM 
2 
General Supervisor 
Support  
Yoon & Lim (1999)  
3 
S 
SM 
2 
Emotion 
Regula-
tion 
Reappraisal and Emotion 
Suppression 
Gross & John (2003) 
10 
S 
SM 
3 
Resilience 
Brief Resilience Scale 
Smith et al. (2008)  
6 
S 
SM 
3 
CD-RISC (Brief Connor-
Davidson Resilience) 
Campbell-Sills & Stein 
(2007) 
10 
S 
SM 
3 
Social 
Connectedness 
Thwarted Belongingness 
Subscale 
Hill et al. (2015).  
5 
S 
SM 
3 
Brief Loneliness Scale 
Hughes, et al. (2004) 
3 
S 
SM 
3 

 
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Template Revised: 6.11.2015 
Psychological Health 
K6 Psychological Distress 
Kessler et al. (2002) 
6 
S 
SM 
4 
Functional Impairment 
(WRAIR) 
Herrell et al. (2014)  
13 
S 
SM 
4 
Perceived Stress Scale 
(PSS) 
Cohen et al. (1983) 
4 
S 
SM 
4 
PTSD (PCL-5) 
Price et al. (2016) 
4 
S 
SM 
4 
Dimensions of Anger 
(DAR-5) 
Forbes et al. (2014) 
5 
S 
SM 
4 
Physical Health 
Sleep Problems 
Jenkins et al. (1988) 
4 
S 
SM 
4 
General Perceived Health 
Hobfoll et al. (2012) 
4 
S 
SM 
4 
Chronic Pain 
Mattacola et al. 
(1997) 
1 
S 
SM 
4 
Alcohol misuse (AUDIT-C) 
Bush et al. (1998) 
3 
S 
SM 
4 
Unit 
Cohe-
sion 
Unit Cohesion 
Williams et al. (2016) 
8 
S 
SM 
4 
Demographics 
Brief Combat Exposure  
WRAIR  
 
T  
S 
PLT, SM 
 
Unit info, age, rank, 
gender, Relationship 
Status, # of Children, 
Years in military, 
deployment history, 
Months in platoon  
 
 
T 
S 
PLT, SM 
 
*NOTE: T = Training; S = Survey; PLT = Platoon Leadership Team; SM = Service Member 
 
c. Sharing of Results with Subjects 
 
We currently do not have plans to share results with participants participating in the survey. Leaders in 
the treatment group will receive the results of their pre- and post-test on the training. Results of the 
study will be shared with the leadership at JBLM, but only at an aggregate level. 
 
8. Data Analysis 
 

 
Page 13 of 22 
Template Revised: 6.11.2015 
a. Statistical Plan and Data Analysis 
The data for this study will be generated from a randomized controlled trial with all participating 
leaders and soldiers (in non-support units) within the participating units randomly assigned (by 
battalion) to either an intervention or usual practice control condition. Standard general linear 
and generalized linear mixed model approaches for clustered designs (i.e., hierarchical linear 
models, multilevel models; Murray, 1998; Murray, Varnell, & Blitstein, 2004) will be used for 
data analysis for Hypotheses 2-4 to account for the clustered nature of the data. As these 
models are now widely used and understood and are available in numerous statistical software 
packages, our discussion here on the specifics of these analyses will be brief. For each 
hypothesis, link functions for these models will be determined by the scaling of each outcome 
variable. As study implementation (i.e., intervention-related and data collection activities) will 
occur at the level of the platoon within brigades, platoon-level random effects will be included 
in these statistical models.  The evaluation of Hypothesis 1 will focus on leaders in the 
intervention condition providing a point estimate and confidence interval for the usefulness of 
the training and the change in training-related knowledge from pre- to post-training. 
Hypotheses 2-4 will focus on differences in the key study outcomes between the intervention 
and usual practice conditions for soldiers. For these latter models, we will use the outcome 
variable at baseline as a predictor in the model to adjust for unexpected imbalance across 
conditions and to increase the statistical power for and precision of parameter estimates (cf. 
Bodner & Bliese, 2018). Finally based on planned preliminary data analyses, the recruitment 
wave (i.e., block), rank, gender, unit type, marital status, and mental health symptoms of 
soldiers may be used as predictors in the statistical models to further increase statistical power 
or eliminate potential intervention effect bias. Of interest in these latter models is the direction, 
magnitude, and statistical significance of the parameter corresponding to the intervention 
condition indicator. As needed, depending on attrition and missing data, this basic generalized 
linear mixed model will be extended in the analysis of the study hypotheses as mentioned below 
(e.g., multiple imputation for missing predictor variable values, FIML estimation for missing 
outcome variable values). 
 
b. Power Analyses 
This section documents the power analyses we conducted for the planned analyses for 
Hypotheses 1-4.   
Key factors for the power analysis are the likely size of the intervention effect and the degree of 
non-independence, quantified as an intra-class correlation, as leaders and soldiers are nested in 
platoons, given the expected number of platoons discussed above.  Prior research with platoon-
level implementation (e.g., Adler, et al., 2009; Adler, et al., 2015a; Adler, et al., 2015b) indicates 
platoon-level random effects are often considered small in size (e.g., ICCs < .04, except when the 
outcome involves a platoon-level construct such as cohesion). Although small, it is important to 
include these effects in the analysis models for the study hypotheses and to incorporate these 
random effects into the power analyses for the study hypotheses.  In the power analyses, we 
assumed an ICC of .04 for the platoon-level random effects. 
Hypothesis 1 assesses the perceived usefulness of the training as rated by the leaders that 
participate in the training.  Our prior research involving similar leadership training (i.e., SERVe) 
indicated that 81% of the 928 trained leaders rated it as good or excellent and 95% rated it as 
useful to extremely useful for their work.  Hypothesis 1 also assesses the increase in leader 
knowledge of the training material.  Prior research indicates that these increases in knowledge 
are large [e.g., d = 3.31 in Anger, et al., unpublished; d = 1.23 in Hammer, et al. (2011)]. Using 

 
Page 14 of 22 
Template Revised: 6.11.2015 
the smaller of these effect size estimates for the power analysis for H1, we estimate power to be 
.99 in the current study.   
Hypothesis 2 assesses the effect of the intervention on the soldiers’ perceptions of their leaders 
on the targeted intervention behaviors. Estimates of the effect of similar leadership 
interventions on subordinate perceptions of targeted leadership behaviors indicate small 
positive effects [e.g., d = .27 in Crain, et al. (2018); d = .39 in Odle-Dusseau, et al. (2016)].  Using 
the smaller of these effect size estimates for the power analysis for H2, we estimate power to be 
.96 in the current study. 
Hypothesis 3 assesses the effect of the intervention on the soldiers’ resilience-related factors 
such as adaptive emotion regulation strategies, resilience, social connectedness and 
belongingness. . Estimates of the effect of similar interventions on adaptive emotion regulation 
vary widely [e.g., d = .26 in Bentley, et al. (2018); d = .30 in Cameron, Carroll & Hamilton (2018); 
and d = .90 in Mahatmya, Thurston, & Lynch (2018)].  Estimates of the effect of similar 
interventions on prosocial connections tend to be small in size [e.g., d = .205 for organizational 
citizenship behaviors in Hammer, et al. (2016)].  Using the smallest of these effect size estimates 
for the power analysis for H3, we estimate power to be .80 in the current study. 
Hypothesis 4 assesses the effect of the intervention on the soldiers’ resilience-related outcomes 
such as psychological and physical health and well-being. Estimates of the effect of similar 
interventions on health outcomes tend to be small in size [e.g., d = .26 for physical health in 
Hammer, et al. (2011); d = -.217 for blood pressure in Hammer, et al. (2015].  Using the smallest 
of these effect size estimates for the power analysis for H4, we estimate power to be .84 in the 
current study. 
In summary, based on the expected sample sizes, participation and attrition rates, and effect 
sizes (i.e., from the research literature) we are adequately powered to test the 4 study 
hypotheses. 
 
c. Missing Data and the Application of Intent-to-Treat  
Missing data intermittently during the study and/or dropouts are inevitable and an issue faced 
by all longitudinal studies, although recent evidence indicates relatively low levels of attrition for 
randomized trials in a military context (Adler, Williams, et al., 2015). There is no consensus, 
however, on the optimal analytical strategy to analyze missing data. Using the standard missing 
data taxonomy (Rubin, 1987), we will follow the recommendations made by Nich and Carroll 
(1997, 2002) and conduct intent-to-treat analyses using three strategies. In the first strategy we 
will extend the multiple imputation method of Little and Yau (1996) to allow for non-monotone 
missing values, which could occur intermittently during the study period. Monotone missing 
patterns require subsequent variables to be missing once a variable is missing. We will impute 
unobserved outcomes based on study condition, observed subject-level covariates at baseline 
and observed follow-ups. Inferences will be made on imputed datasets using Rubin’s method 
(Barnes, Lindborg, & Seaman, 2006; Rubin, 1996). Our second analytical strategy will consider 
selection models and pattern-mixture models (Michiels, Molenberghs, Bijnens, Vangeneugden, 
& Thijs, 2002) based on different factorization of the joint distribution of the response variables 
and the missing patterns. As different strategies require different assumptions for the estimated 
treatment effects to be unbiased and some assumptions are not testable, comparisons of these 
strategies serve mainly as sensitivity analyses of their influence on the estimated key 
parameters of each Aim. A third strategy will consider the use of Full Information Maximum 
Likelihood methods in the analysis of incomplete data as implemented in several software 
programs (e.g., Mplus; Muthen & Muthen, 2007). As mentioned in the prior section, this study is 
adequately powered for an attrition rate of 20%. 

 
Page 15 of 22 
Template Revised: 6.11.2015 
 
 
9. Privacy, Confidentiality, and Data Security 
 
Confidentiality: 
• 
All devices that can link to OHSU or house OHSU data are required to have Symantec Whole Desk 
Encryption software installed. All data will be stored on secure, password protected servers. 
• 
Methods of sharing data will NOT include the use of email or thumb drives, but rather by IRB approved 
methods, such as Box.com, which is sanctioned by OHSU’s IRB.  
• 
Any contact information, including mailing address, email and phone numbers for participants will be 
kept separate from any files containing survey data. We will only have this contact information from 
platoon leaders and unit POCs (not soldiers). Only a few key staff members will have access to these 
files with contact information, generally those who need to interact with participants for incentive 
payments or for reminders to complete a survey or training. 
• 
If there is a reasonable expectation of harm to self or others, staff are expected to break confidentiality 
by reporting this to the proper authorities. This information is included in the Informed Consent.  
• 
We have included a statement in the Informed Consent stating that representatives of USAMRMC 
(DoD) may review our study records to ensure we are compliant with our research protocols. 
Disposition of Data: 
• 
Electronic data will be stored primarily on the secure OHSU servers, which is encrypted and password 
protected. 
• 
Any hard copies of data will be kept in a locked file cabinet in the project office, which is also locked 
when no one is present. 
• 
De-identified data will be kept indefinitely on the secure servers at OHSU.  
• 
Any contact information for participants will be destroyed at the end of the project. 
• 
The project manager will be primarily responsible for ensuring data are secure and protocols are 
followed by all approved and trained staff. 
o We will have a data sharing agreement that details these protocols to ensure the confidentiality 
and integrity of the data. A signed copy stating they will comply with these protocols must be on 
file with the project manager before an individual is granted access to data, as well as a valid 
reason for having access (e.g., a paper proposal).  
o All individuals who will have contact with data and/or participants will have a copy of a record of 
Human Subjects training on file. 
 
10. Provisions to Monitor the Data to Ensure the Safety of Subjects 
 
We will prepare this if the study is deemed to be more than Minimal Risk. 
 
11. Risks and Benefits 
 
a. Risks to Subjects 
Foreseeable risks: 
Efforts will be made to minimize risks associated with this study. Minimal potential risks for 
participation include breaches of confidentiality associated with data collected for research 
purposes. In addition, there is a risk of psychological distress associated with the psychological 
distress survey measures. Additional potential, but not expected, risk is that a supervisor may be 

 
Page 16 of 22 
Template Revised: 6.11.2015 
upset about being contacted to participate in a study or may not like the training. Leaders can 
discuss these issues at any time with research staff.  
 Risk management and emergency response: 
To mitigate potential distress related to the psychological well-being survey items, participants 
will be made aware that participation is completely voluntary and that they are welcome to not 
answer any questions participants find distressing or to withdraw involvement at any moment 
without consequence. On the information sheet, we will provide contact information for 
behavioral health resources at OHSU. 
Confidentiality:  
Several processes are put in place to mitigate against breach of confidentiality for survey and 
training data: 
• 
All devices that can link to OHSU or house OHSU data are required to have Symantec Whole 
Desk Encryption software installed. All data will be stored on secure, password protected 
servers. 
• 
Methods of sharing data will NOT include the use of email or thumb drives, but rather by IRB 
approved methods, such as OneDrive, which is sanctioned by OHSU’s IRB.  
• 
If we collect any contact information, including mailing address, email and phone numbers for 
participants will be kept separate from any files containing survey data. We will only have this 
contact information from department heads. Only a few key staff members will have access to 
these files with contact information. 
• 
If there is a reasonable expectation of child abuse, staff are expected to break confidentiality by 
reporting this to the proper authorities. This information is included in the Informed Consent.  
• 
In the event we have any hard copies of data, they will be kept in a locked file cabinet in the 
project office, which is also locked when no one is present. 
• 
De-identified data will be kept indefinitely on the secure servers at OHSU.  
• 
Any contact information for participants will be destroyed at the end of the project. 
• 
The project manager will be primarily responsible for ensuring data are secure and protocols 
are followed by all approved and trained staff. 
o We will have a data sharing agreement that details these protocols to ensure the 
confidentiality and integrity of the data. A signed copy stating they will comply with 
these protocols must be on file with the project manager before an individual is granted 
access to data, as well as a valid reason for having access (e.g., a paper proposal).  
o All individuals who will have contact with data and/or participants will have a copy of a 
record of Human Subjects training on file. 
 
 The Study PI will also follow the University’s guidelines for reporting any unanticipated events 
in a timely fashion and consult with compliance specialists at the university on appropriate 
responses or additional reporting as needed. 
 
b. Potential Benefits to Subjects 
For employees, there is no immediate, direct benefit. We expect that when we train leaders in 
mental health support, we also may enhance employees’ psychological health and attenuate 

 
Page 17 of 22 
Template Revised: 6.11.2015 
traumatic situations that could lead to negative behavioral health outcomes. We anticipate that 
the training program serves as a primary prevention intervention that will have a positive impact 
on individual health behaviors, including psychological health, risky behaviors, and hazardous 
alcohol consumption. This training intervention will eventually have the opportunity of being 
extended and implemented  more broadly. The study holds great promise for informing the 
implementation of evidence-based leadership training programs across workplace settings.  
 
 
12. Multi-Site Coordination (delete if not applicable) 
 
Portland State University is a co-investigation site on our grant; Dr. Leslie Hammer, PI for OHSU, also has 
a dual appointment at PSU and Dr. Cynthia Mohr is PI for PSU. All research activities will be overseen by 
OHSU staff, including recruitment, data collection, and training delivery. The PSU IRB is ceding oversight 
to OHSU’s IRB. Any PSU research assistants will go through the same training as OHSU RAs. The PSU team 
will be working primarily in providing consultation and writing papers.  
 
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