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. Author manuscript; available in PMC: 2024 Jun 29.
Published in final edited form as: Psychol Serv. 2023 Jun 29;20(Suppl 2):248–259. doi: 10.1037/ser0000764

Supporting Service Members and Veterans During Transition to Civilian Life Using Certified Sponsors: A 3-Arm Randomized Controlled Trial

Joseph C Geraci 1,2,3,4, Ariana Dichiara 1, Ashley Greene 1,4, Molly Gromatsky 1,4, Erin Finley 2,5, Daniel Kilby 1,3, Sheila Frankfurt 2,6, Emily R Edwards 1,7, A Solomon Kurz 2, Yosef Sokol 1,4, Sarah R Sullivan 1, Meaghan Mobbs 1, Richard W Seim 2, Marianne Goodman 1,2,4
PMCID: PMC10755060  NIHMSID: NIHMS1913516  PMID: 37384439

Abstract

Transitioning military servicemembers and veterans (TSMVs) face difficulties throughout their reintegration to civilian life, including challenges with employment, poor social connection, and elevated risk for suicide. To meet the needs of this high-risk population, national initiatives have leveraged community-based interventions. Authors conducted a 3-arm randomized controlled trial (n=200) to evaluate two community-based interventions. The first, Team Red, White & Blue (RWB), connects TSMVs to their community through physical/social activities. The second, Expiration Term of Service Sponsorship Program (ETS-SP) provides one-on-one certified sponsors to TSMVs who provide support during the reintegration process. TSMVs were assessed at baseline, 3-months, 6-months and 12-months. The primary hypothesis was not supported as reintegration difficulties and social support were not significantly different for participants randomly assigned to the two community-based interventions (Arm-2/RWB and Arm-3/RWB+ETS-SP), when the data from the separate arms was collapsed and combined, compared to the waitlist. The results did support the secondary hypothesis as Arm-3/RWB+ETS-SP had less reintegration difficulties over 12 months and initially had more social support compared to Arm-2/RWB, which suggest that augmenting interventions with sponsors outperforms participation in community-based interventions alone. Overall, the results show some limitations of the studied community-based interventions, as implemented and researched within this study. The authors identified factors that may have contributed to the null findings for the primary hypothesis, which can be addressed in future studies, such as addressing the unique needs of TSMVs, enrolling TSMVs into interventions prior to military discharge, measuring and improving participation levels, and providing stepped-care interventions based on risk levels.

Keywords: Reintegration Difficulties, Community Interventions, Sponsors, Transitioning Servicemembers and Veterans

Each year, approximately 200,000 military servicemembers transition out of active-duty military service and rejoin their civilian communities (U.S. Department of Veterans Affairs [VA], 2018a). This military-to-civilian transition has long been considered immensely stressful for transitioning servicemembers and veterans (TSMVs). For example, as early as 7th or 8th century BC, Homer described the extensive difficulties that Odysseus faced during his journey home after his military service (Geraci et al., 2020a; Geraci et al., 2020b). Accordingly, the United States aims to support TSMVs through connection to community-based services, such as medical care, employment opportunities, and education (Carroll et al., 2020; Ainspan & Penk, 2008; White House, 2018; White House, 2019; White House, 2021; Veteran Sponsor Partnership Network [VA, 2022a]) . The current investigation represents one such effort and explores the additive value of incorporating certified sponsors into community-based transition support programs.

Needs of Transitioning Service Members and Veterans

In tandem with the immense stresses of the military-to-civilian transition, many TSMVs face incredible medical and psychosocial difficulties. For example, because of recent, life-saving advancements in medical care, service members are less likely to die in the field, contributing to a greater prevalence of service-related injuries and disabilities among current TSMVs compared to those of previous service eras (Amara & Hendricks, 2016). Recent estimates suggest more than half of TSMVs experience a physical health condition within the first year after discharge (Vogt et al., 2020), and these difficulties predict poor subsequent well-being throughout the reintegration process (Vogt et al., 2020; Vogt et al., 2021). Rates of psychiatric disorders, such as mood disorders, posttraumatic stress, and personality disorders, also tend to exceed those of their civilian peers (Derefinko et al., 2019; Edwards et al., 2022a), and an early diagnosis of depression similarly tends to predict later poor wellbeing, homelessness, and suicide attempts throughout the reintegration process (Koh et al., 2022; Stanley et al., 2022; Vogt et al., 2021). Rates of suicide death are also particularly elevated among TSMVs, especially in the first three years following military discharge (Shen et al., 2016). Reintegration difficulties appear particularly elevated among younger TSMVs and among those with lower ranks in the military (Edwards et al., 2022a; Elbogen et al., In Press; Koh et al., 2022). The psychological difficulties of TSMVs appear to have a bidirectional relationship with reintegration difficulties; reintegration difficulties may exacerbate existing psychological difficulties, which in turn complicate the reintegration process by interfering with relationships, employment, and/or other areas of functioning (Interian et al., 2012; Kline et al., 2011; Sayer et al., 2011; Sokol et al., 2021; Elbogen et al., In Press).

Many TSMVs also experience formidable challenges in their social relationships. For example, upon return to their civilian communities, TSMVs often report feelings of alienation and social disconnection (Ahern et al., 2015; Brenner et al., 2009; Pietrzak et al., 2009). In contrast to the close-knit relationships, supports, and mentorship of military service (Geraci et al., 2020b), many find themselves feeling unable to interpersonally connect with civilians and tend to view civilians as not understanding the TSMVs experience (Demers, 2011). Within the family, TSMVs often struggle with marital conflict, decisions of separation or divorce, and difficulties in parent-child relationships (Interian et al., 2012; Kline et al., 2011; Sayer et al., 2011), and many TSMVs find their partners and children are afraid of and detached from them (Sayers et al., 2009). Correspondingly, recent research suggests low social support in the first three months after military discharge, particularly when coupled with high depression, is predictive of exceptionally low wellbeing over the next six months (Vogt et al., 2021). Conversely, greater social support assessed three years after military discharge is associated with less reported difficulties in readjustment to civilian life (Elbogen et al., In Press).

Reintegration difficulties often also extend into the TSMV’s educational and occupational pursuits. In these settings, TSMVs often struggle to navigate ambiguous civilian career progression procedures (Prudential Financial, 2012), to translate their military skillsets to the civilian workplace (Davis & Minnis, 2017), to succeed without continuous feedback about performance (Naphan & Elliot, 2015), and to evade prejudiced hiring decisions (Stone & Stone, 2015). Such difficulties are particularly pronounced for TSMVs with co-occurring stressors, such as functional disabilities, PTSD symptoms, poor social support, or difficulties in intimate relationships (Elliot et al., 2011). Consequently, TSMVs often cite employment concerns as a top source of reintegration difficulties as many TSMVs change jobs multiple times throughout their transition (Prudential Financial, 2012). Correspondingly, recent research from the Veterans Metric Initiative (TVMI) –a longitudinal investigation using a large, community-based sample of TSMVs (Vogt et al., 2018)– suggest 43% of TSMVs face unemployment in the first three months after military discharge (Vogt et al., 2020), and early employment difficulties are predictive of readjustment difficulties at three years post discharge (Elbogen et al., In Press).

The Promise of Peer Sponsorship Programs

Various efforts have been implemented to support TSMV reintegrate into civilian life more successfully. For example, more than 27,000 non-profit, community-based organizations provide programs, services, and supports to assist TSMVs (U.S. Internal Revenue Service, 2022). However, many TSMVs find navigating these systems and connecting to these organizations difficult (Geraci et al., 2020b). Similarly, only 26% of TSMVs utilize services from the Veterans Health Administration after military service (VA, 2018a; VA, 2018b). To better aid TSMVs, particularly in the domains of social support and reintegration difficulties, some experts have recommended integration of peer and/or mentorship-based programming (e.g., Vogt et al., 2021). Growing research attests to the benefit of peer- or mentor-based interventions. In a meta-analysis of over 100 mentorship-based interventions, mentoring yielded a broad range of favorable behavioral, attitudinal, health-related, relational, motivational, and career outcomes and decreased potentially destructive factors such as withdrawal, deviance, substance use, and psychological stress (Eby et al., 2009). The VA routinely capitalizes on these benefits through the employment of Peer Support Specialists, veteran peers who work as members of interdisciplinary teams in VA acute care, outpatient, and specialized program settings (Chinman et al., 2021).

Current Study

Existing research underscores the importance of bolstering social support and decreasing reintegration difficulties to promote reintegration success among TSMVs, particularly during the first few years after military discharge. In accordance with recent calls for community-based supports for TSMVs and recommendations for peer or mentorship support for veterans (Vogt et al., 2021), the current study represents a preliminary investigation into the additive value of certified sponsors within community-based interventions. This study is part of the VA’s Veteran Sponsorship Initiative (VA, 2022b), which is a public-private partnership between federal and local entities that aims to successfully transition TSMVs to civilian life.

Method

Study Design and Protocol

We conducted a 3-arm, parallel randomized controlled trial. After providing informed consent and completing the baseline assessment (Time 0) using Qualtrics™, eligible TSMVs were randomly assigned (1:1:1) through the random number function in Excel, as described by Kim and colleagues (2014). TSMVs were considered eligible if they were at least 18 years-old, had recent or current military service, and were residing within NYC or planning on moving to the NYC area post-discharge. Servicemembers who were still serving in the military were enrolled pending they were exiting the military and moving to NYC during the enrollment window. Exclusion criterion included prior participation in the assessed interventions. Participants completed assessments via Qualtrics 3-months (Time-1), 6-months (Time-2), and 12-months (Time-3) after assignment. Participants were recruited through flyers approved by the Teachers College, Columbia University Institution Review Board.

Participants

A total of 200 TSMVs were included in the current study. These participants were mostly men and White, with a history of military service in the US Army. See Table 1 for more detailed demographic information. Sample size was determined a-priori using the powerlmm package (Magnusson, 2018) within the R computing environment (R Core Team, 2020). Based on the analysis of earlier pilot data, we expected a standardized mean difference (Cohen’s d; Cohen, 1988) of 0.3. Given a longitudinal design with four time points, random assignment into three equal-sized groups, an expected dropout rate of 20% per time point, and an analytic strategy using hierarchical models, the power analysis indicated n = 60 per condition to detect a standardized mean difference of 0.3 between conditions.

Table 1.

Characteristics at Baseline of 200 Recently Transitioned Servicemembers by Arm

Total N=200 Arm 1: Waitlist n=65 Arm 2: RWB n= 67 Arm 3: RWB+ETS-SP n=68 Combined (Arm 2 & Arm 3) n=135
Characteristic N % N % N % N % P N %
Race-ethnicity ns
 Caucasian/White 91 46 28 43 32 48 31 46 63 47
 African American 32 16 10 15 10 15 12 18 22 16
 Latino/Latina 53 27 15 23 17 25 21 31 38 28
 Asian/Pacific Islander 15 8 8 12 5 7 2 3 7 5
 Other 9 5 4 6 3 4 2 3 5 4
Rank ns
 Enlisted Ranks 1 to 4 91 46 27 42 36 54 28 41 64 47
 NCO 73 37 27 42 23 34 23 34 46 34
 Commissioned Officer 36 18 11 17 8 12 17 25 25 19
Age ns
 20–24 yo 16 8 8 12 6 9 2 3 8 6
 25–29 yo 55 28 15 23 20 30 20 29 40 30
 30–39 yo 99 50 31 48 31 46 37 54 68 50
 40+ yo 30 15 11 17 10 15 9 13 19 14
Gender ns
 Men 168 84 53 82 59 88 56 82 115 85
 Women 32 16 12 18 8 12 12 18 20 15
Branch ns
 Army 123 62 42 62 36 54 45 69 81 61
 Marines 39 20 11 16 15 22 13 20 28 21
 Air Force 16 8 7 10 7 10 2 3 9 7
 Navy 21 11 8 12 8 12 5 8 13 10
 Other 1 1 0 0 1 1 0 0 1 1
Time Since Discharge 2.77+/−4.09 years 2.83+/−4.40 years 2.66+/−3.82 years 2.81+/−4.09 years 2.73 +/− 3.94 years
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Notes. RWB= Team Red, White and Blue Membership Only

RWB+ETS-SP= RWB PLUS Expiration Term of Service-Sponsorship Program

NCO= Non Commissioned Officer

Intervention Arms/Hypotheses

Arm-1/Waitlist:

Participants were placed on a waitlist for twelve months and then offered the same services as in Arm-3, though were not eligible to be enrolled again in the study.

Arm-2/RWB: Team Red, White and Blue (RWB) Membership Only.

Participants joined Team Red, White, and Blue (Team RWB; 2022), a non-profit, community-based organization. RWB connects veterans to their communities through physical and social activity in approximately 200 chapters with over 210,000 members across the nation. After participants were assigned to RWB, they had access to a large, online community, received weekly emails from the NYC chapter about upcoming events, and were able to voluntarily participate in physical/social events. No participation was required in these events.

Arm-3/RWB+ETS-SP.

Participants joined RWB plus received six months of sponsorship from a certified, volunteer Expiration Term of Service Sponsorship Program (ETS-SP) sponsor. ETS-SP (2022) is a nonprofit organization that connects TSMVs with one-on-one sponsors in their post-military hometowns similar to the US Department of Defense’s (DoD) Permanent Change of Station (PCS) sponsorship program. As part of the PCS sponsorship program, the military provides all servicemembers with a PCS sponsor from their destination installation. For example, the U.S. Marine Corps has a thorough and required PCS sponsorship program that intends to reduce “stress and challenges associated with relocating” (US Navy, 2012, p. 2). PCS sponsors orient the servicemembers to their new installation and help them accomplish their transition tasks. The support received from such leaders and sponsors is considered critical for servicemembers to accomplish their designed mission within the military (Geraci et al., 2020b; Geraci et al., 2022a). Though, prior to ETS-SP there was no comparable program for TSMVs as they transitioned to civilian life.

ETS-SP was also established according to recommendations in the DoD’s (2011) Best Practices Identified for Peer Support Programs. ETS-SP is a national organization that is part of a VA network –Veteran Sponsor Peer Network (VA, 2022a)– along with many local organizations across the nation that serve as community integration coordinators (CICs). The CICs execute local sponsorship tasks, such as recruiting and managing sponsors, matching sponsors with TSMVs and directly assisting TSMVs with specific transition needs after identified by a sponsor. The CICs also ensure that all sponsors are certified, which consists of them going through a screening process and attending the three-session, manualized training (7.5 hours; Geraci et al., 2020c). This training ensures sponsors have the necessary competencies to provide TSMVs necessary supports. The local organization for this study was the nonprofit organization ProVetus (2022).

The first session of this training focuses on promoting social support by training sponsors to utilize relational-oriented leadership behaviors (Geraci et al., 2020c). Relational-oriented behaviors consist of establishing supportive environments based on strong interpersonal and trusting relationships through using behaviors such as treating TSMVs as equals, showing concern and respect for TSMVs, and applying active-listening skills (DeRue et al., 2011). The second session focuses on reducing reintegration difficulties by helping TSMVs to develop Specific-Measurable-Achievable-Relevant-Time Bound (SMART) goals specific to reintegration domains, such as employment, education, housing, family, community engagement and medical (Geraci et al., 2020c). The task-oriented leadership behaviors learned in this session are action-oriented and problem-solving focused. The third session focuses on identifying and responding to suicide risk. Sponsors practice the required behaviors within small groups before demonstrating them in a certification role-play evaluation.

Sponsors then integrate their new behaviors during weekly contact with TSMVs via social media/email and monthly video or in-person sessions. During these sessions, sponsors help to identify SMART goals and develop reintegration action plans. Because no single entity can fulfill all TSMV needs, sponsors work closely with their CICs and community-focused digital platforms to connect TSMVs to other services (AmericaServes, 2022; America’s Warriors Partnership, 2022).

Consistent with CONSORT guidelines for 3-arm trials (Juszczak et al., 2019), the primary hypothesis of this study was that TSMVs randomly assigned to the two community interventions (Arm-2/RWB and Arm-3/RWB+ETS-SP), when the data from the separate arms was collapsed and combined, would experience less reintegration difficulties (primary outcome) and more social support (secondary outcome) compared to TSMVs randomly assigned to the Arm-1/Waitlist over a 12-month period. The secondary hypothesis was that TSMVs assigned to Arm-3/ RWB+ETS-SP would experience less reintegration difficulties and more social support compared to TSMVs assigned to Arm-2/RWB over a 12-month period.

Measures

Military-to-Civilian-Questionnaire-M2CQ

(Sayer et al., 2011) is a 16-item measure that assesses reintegration difficulties for TSMVs in domains of productivity (e.g., schooling, employment, domestic life), taking care of one’s health, social relationships, community engagement, perceived meaning in life, and leisure. Items are rated on a 5-point Likert scale [0 (no difficulty) to 4 (extreme difficulty)]. Respondents can indicate “does not apply” for four items that assess relationships and work/school functioning. To ensure consistency across respondents, these four items were not included within analyses. The M2C-Q was initially validated in a sample of Iraq and Afghanistan veterans seeking VA healthcare services (Sayer et al., 2011) and has since shown strong construct validity and internal reliability in TSMVs samples (Castillo et al., 2019; Sayer et al., 2014). Cronbach’s α was .95.

Social-Support-Survey-MOS SSS

(Sherbourne et al., 1991) is a 19-item measure of perceived availability of social support that has demonstrated strong psychometric properties in military (Erbes et al., 2017), veteran (Currier et al., 2013), and civilian samples (Sherbourne & Stewart, 1991). The items are rated on a 5-point Likert scale [0 (none of the time) to 4 (all of the time)]. Cronbach’s α was .98.

Sponsor Evaluation: Leader-Behavior-Description-Questionnaire-LBDQ

(Halpin, 1957) was developed from work with military units and is a 30-item measure that assesses the frequency with which individuals perceive their leaders engage in two types of leadership behaviors: relational-oriented (or consideration; “is friendly and approachable”) and task-oriented (or initiating structure; “emphasizes the meeting of deadlines”). Research shows that improved outcomes and performance occur when individuals/subordinates are exposed to a combination of these leadership behaviors (Hartnell et al., 2016; Liao et al., 2007; Walumbwa et al., 2019). Items are rated on a 5-point Likert scale [1 (never) to 5 (always)]. Cronbach’s α was .98.

Open-Ended Items

were used to collect ETS-SP participant feedback. Participants had the opportunity to respond to two questions related to most and least beneficial aspects of ETS-SP.

Quantitative Analysis

The CONSORT diagram (online supplement) shows that 206 TSMs completed the baseline assessment and 200 were randomized. Exploratory analyses suggested no significant differences in participant demographic or baseline measure scores across study conditions at baseline. Little’s MCAR test failed to indicate that the data was not missing at random. Attrition was 38% by Time-3. Retained and missing participants were equivalent on all baseline characteristics (online supplement).

HLM8 (Raudenbush et al., 2019) was used to create a hierarchical linear model for each outcome (reintegration difficulties and social support). Intent-to-treat analyses were utilized. Time was included as a Level 1 predictor as a linear pattern of change with a static time term for each time point. A static term for a quadratic pattern of change was also created by squaring the linear time variable. Time was centered at Time-3 so that the parameter for the intercept would represent the outcomes at the final assessment (O’Connor et al., 2014). Although no differences were identified at baseline, baseline levels (Table 2) of the outcomes were included as covariates in the respective models at Level 2 to improve the precision of estimates (Shadish et al., 2001). We created the full model by including orthogonal contrasts at Level 2 to test the hypotheses. As described by CONSORT guidelines (Juszczak et al., 2019) and recommended by Feingold and colleagues (2013) for 3-arm trials, the first contrast tested the primary hypothesis of community interventions (Arm-2/RWB=1/3 and Arm-3/RWB+ETS-SP=1/3) vs. waitlist (−2/3) and the second contrast tested the secondary hypothesis of Arm-2/RWB (−.5) vs. Arm-3/RWB+ETS-SP (.5). Effect size was calculated using procedures outlined by Feingold (2013) with results being equivalent to those identified by Cohen (1988).

Table 2.

Means/Standard Deviations for Outcomes by Arm and Timepoint

Baseline n=200 Time-1 (3-Month) n=139 Time-2 (6-Month) n=126 Time-3 (12-Month) n=122
Outcome Variable by Arm M SD M SD M SD M SD
Reintegration Difficulties (M2CQ)
Arm 1: Waitlist 1.61 1.21 1.55 1.26 1.49 1.19 1.59 1.18
Arm 2: RWB 1.18 0.92 1.02 0.91 1.10 0.95 1.00 0.94
Arm 3: RWB+ETS-SP 1.40 1.01 1.36 1.09 1.38 1.07 1.11 0.98
Combined Intervention (RWB+ETS-SP and RWB) 1.29 0.97 1.19 1.02 1.25 1.02 1.06 0.96
Total 1.39 1.06 1.31 1.11 1.33 1.08 1.23 1.06
Social Support
Arm 1: Waitlist 56.17 29.03 54.54 30.87 60.05 29.42 62.38 28.78
Arm 2: RWB 64.36 26.89 68.89 23.87 65.89 27.89 72.06 22.89
Arm 3: RWB+ETS-SP 59.17 28.61 62.24 29.69 67.91 29.77 61.17 32.50
Combined Intervention (RWB+ETS-SP and RWB) 61.74 27.79 65.42 27.12 66.95 28.73 66.48 28.58
Total 59.93 28.25 61.74 28.80 64.54 29.04 65.09 28.60
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Notes. RWB= Team Red, White and Blue Membership Only

RWB+ETS-SP= RWB + Expiration Term of Service Sponsorship Program

Combined Intervention= Combined values for both community interventions/arms

M2CQ= Military to Civilian Questionnaire

As secondary analysis, we examined the impact of covariates upon each of the outcome variables in each of the aforementioned models. Predictor variables, as listed in Table 1, were added at Level 2, including race-ethnicity (Caucasian/White vs. others), rank, age, gender, branch (Army vs. others) and time since discharge. Separately, we conducted analysis with TSMVs in Arm-3/RWB+ETS-SP. The scores for the two types of leadership behaviors (task-and relational-oriented) were used to create contrast variables for each behavior through conducting median splits (low=0/high=1). The variables were individually added to models for each outcome variable at Level 2, in addition to baseline outcomes values. Given the reduced sample size from assessing only TSMVs in Arm-3/RWB+ETS-SP, time was only included as a Level 1 predictor with a linear pattern of change.

Qualitative Analysis

Most Arm-3/RWB+ETS-SP participants (n=57; 84%) responded to the qualitative questions creating 251 responses. Two independent coders separated response text into three broad categories (benefits, challenges, and recommendations), then conducted thematic analysis to identify topics occurring repeatedly (themes). Coders independently reviewed responses, then held meetings to finalize a list of key themes before systematically coding all responses. To limit the potential for bias, coders were otherwise uninvolved in study design, data collection, and analysis.

Results

Reintegration Difficulties

The cross-level interaction effect (Table-3 and Figure-1) testing the primary hypothesis related to reintegration difficulties was not significant for a linear trend. This means that the change in reintegration difficulties was not significantly different for participants randomly assigned to the two community interventions (Arm-2/RWB and Arm-3/RWB+ETS-SP), when the data from the separate arms was collapsed and combined, compared to those assigned to the waitlist. However, results did support the secondary hypothesis identifying a significant cross-level interaction effect when comparing Arm-3/RWB+ETS-SP to Arm-2/RWB (t(569)=−2.04, p<.05). Thus, participants in Arm-3/RWB+ETS-SP had significantly reduced reintegration difficulties compared to participants in Arm-2/RWB from baseline to Time-3. The quadratic trend was positive and approached significance (t(569)=1.94, p=.053) indicating that the effect of Arm-3/RWB+ETS-SP compared to Arm-2/RWB was minimal at Time-1 (d=.24) and Time-2 (d=−.10) but then accelerated and greatly increased by Time-3 (d=−1.11).

Table 3.

Mixed Effect Models (Time Centered at 12-months/Time-3)

Reintegration Difficulties (M2CQ) Social Support
π 0i Coef SE Coef SE
 Intercept, β00 1.27 .06*** 64.15 1.78**
π1i, TIME:Linearti Slope
 Intercept, β10 −.08 .08 .74 2.19
 Combined Intervention (Arm 2 & 3) vs.Waitlist, β11 .07 .16 −8.62 4.53
 RWB (Arm 2) vs RWB+ETS-SP (Arm 3), β12 −.36 .18* −8.97 5.20
 Baseline, β13 .03 .07 .12 .09
π2i, TIME:Quadraticti Slope
 Intercept, β20 .01 .02 .24 .66
 Combined Intervention (Arm 2 & 3) vs.Waitlist, β21 −.04 .05 2.79 1.37*
 RWB (Arm 2) vs RWB+ETS-SP (Arm 3), β22 .10 .05 2.80 1.59
 Baseline, β23 −.04 .02* −.07 .03*
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Notes.

*

p<.05,

**

p<.01,

***

p<.001

RWB= Team Red, White and Blue Membership Only

RWB+ETS-SP= RWB PLUS Expiration Term of Service-Sponsorship Program

Combined Intervention= Combined values for both community interventions/arms

M2CQ= Military to Civilian Questionnaire

Figure 1.

Figure 1.

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Reintegration Difficulties: Combined Interventions (RWB and RWB+ETS-SP) vs. Waitlist

Social Support

The cross-level interaction effect (Table-3 and Figure-2) testing the primary hypothesis for social support was not significant for a linear trend. Thus, the change in social support was not significantly different for TSMVs randomly assigned to the two community interventions (RWB and Arm-3/RWB+ETS-SP), when the data from the separate arms was collapsed and combined, compared to TSMVs assigned to the waitlist. Similarly, the results did not support the secondary hypothesis identifying a significant cross-level interaction effect when comparing Arm-3/RWB+ETS-SP to Arm-2/RWB. Further evaluation revealed that when time was centered at Time-1 there was a significant intervention effect when comparing Arm-3/RWB+ETS-SP to Arm-2/RWB (t(574)=1.98, p<.05, d=.38). The quadratic trend was negative and significant (t(574)=−2.12, p<.05) indicating that the intervention effect was initially significant, but its effect diminished by Time-3.

Figure 2.

Figure 2.

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Social Support: Combined Interventions (RWB and RWB+ETS-SP) vs. Waitlist

Secondary Analysis

Covariates.

Race-ethnicity, rank, gender and time since discharge did not have a significant impact upon reintegration difficulties nor social support. Though, there was significant and positive growth in reintegration difficulties for TSMVs who served in the US Army compared to TSMVs who served in other branches (β=.31, t=2.03, df=551, p<.05), which contributed to TSMVs who served in the US Army having reintegration difficulties that were .29 points higher than TSMVs who served in other branches at Time 3 (β=.30, t=2.34, df=551, p<.05). Additionally, those who served in the US Army had social support scores that were 7.78 points lower than scores for those who served in other branches at Time 3 (β=−7.79, t=−2.21, df=556, p<.05). Analysis of age showed that younger TSMVs (20–24 years old) had social support scores that were 5.21 points lower compared to older TSMVs at Time 3 (β=−5.21, t=−2.20, df=556, p<.05). These results are consistent with other research that has identified that younger TSMVs and those who served in the US Army face elevated challenges after military discharge (Ravindran et al., 2020).

Sponsor Evaluation

TSMVs in Arm-3/RWB+ETS-SP who rated their sponsors as high for task-oriented leadership behaviors had significantly reduced reintegration difficulties (t(147)=−2.37, p<.05) and significantly improved social support (t(148)=2.43, p<.05) from baseline to Time-3 compared to TSMVs who rated their sponsors as low (online supplement). TSMVs who rated their sponsors as high for relational-oriented leadership behaviors also had significantly improved social support relative to TSMVs who rated sponsors as low (t(148)=2.39, p<.05).

Open-Ended Item Responses

Most Arm-3/RWB+ETS-SP participants (84%) described benefits of ETS-SP. Nearly half (44%) reported increased social support, most notably having someone to talk to, which helped them to feel connected, understood, and cared for. Participants also reported appreciating sponsors’ honest advice. TSMVs described frequent communication with their sponsor (33%), social programming (21%), and positive qualities of their sponsors (19%) as other benefits of ETS-SP. TSMVs also appreciated being well-matched with their sponsor and the veteran-centric culture of ETS-SP (25%). Several practical benefits were described (32%), including access to information/resources and career/educational development tools.

There were 47% of respondents who noted challenges. These included barriers to program engagement (25%), including scheduling difficulties, geographic distance from sponsors, and emotional obstacles (e.g., feeling guilty others may be in greater need of ETS-SP). Other challenges involved insufficient interaction with their sponsor or program staff (21%) and a need for greater knowledge about the program (e.g., activity schedules) and their sponsor (16%), such as sponsor availability.

Several ETS-SP respondents (33%) provided recommendations for improvement, including greater interaction with sponsors and/or ETS-SP staff (e.g., more in-person meetings, formalized scheduling; 19%), as well as greater personalization to their needs and interests (e.g., facilitating contact with specialized resources; 12%). Some (12%) proposed specific ideas for improvement, which mainly consisted of recommendations to expand ETS-SP.

Discussion

The current study represents an initial investigation into the effectiveness of community-based interventions for TSMVs and the additive value of certified sponsors. The primary hypothesis was not supported as results showed that changes in reintegration difficulty and social support scores were not significantly different for participants randomly assigned to the two community interventions (Arm-2/RWB and Arm-3/RWB+ETS-SP), when the data from the separate arms was collapsed and combined, compared to those assigned to the waitlist over an evaluation period of 12 months. Consistent with previous research attesting to the chronicity of military-to-civilian challenges (Sayer et al., 2014), TSMVs’ reintegration difficulties remained relatively consistent across the course of data collection. Following guidelines for 3-arm trials, collapsing across conditions for those receiving community-based interventions (Arm-2/RWB and Arm-3/RWB+ETS-SP) showed minor improvements in reintegration difficulties by Time-3. However, these differences were not significant. TSMVs in all arms demonstrated improvements in social support across the course of data collection. This may explain, at least in part, why the collapsed and combined data from the community-based interventions did not outperform the waitlist condition with respect to this outcome. Such findings suggest that many TSMVs may experience improved social support even without intervention. For instance, Vogt and colleagues (2020) identified that many TSMVs in their study reported relatively high social well-being during the first year after military discharge, though the TSMVs did experience challenges in other domains.

The current study’s results did support the secondary hypothesis as TSMVs assigned to Arm-3/RWB+ETS-SP experienced less reintegration difficulties and more social support compared to TSMVs assigned to Arm-2/RWB. Though the strength of the effect upon social support dissipated over time, which is an item that could be further explored in future studies with qualitative interviews. Qualitative results in this study identified themes consistent with task-oriented behaviors, such as sponsors giving TSMVs honest advice, providing TSMVs information related to careers/education opportunities, and connecting TSMVs to resources and specialized services to meet their individualized needs. The qualitative results also identified themes consistent with relational-oriented behaviors, such as sponsors frequently communicating with TSMVs and making TSMVs feel supported, understood and cared for. Overall, the results suggest that augmenting a community-based intervention with a sponsorship program significantly outperforms participation in a community-based intervention alone.

It is not surprising that the results of this study identified the importance of sponsors demonstrating leadership behaviors, similar those employed by military leaders, to support the needs of TSMVs as they transitioned to civilian life. For over 50 years, researchers have studied how effective leaders influence their subordinates through a balance of task-oriented and relational-oriented behaviors (Fielder, 1967). Military leadership is especially complex, as leaders must be able to balance and shift between these leadership behaviors –depending on changes to environmental demands– with a direct impact on mission readiness, unit cohesion, subordinate job satisfaction, and rates of psychological disorders within their units (Geraci et al., 2022b). While they serve within the military, their military leaders are critical guides and influencers for TSMVs during every step of their military experience: recruiters, drill sergeants, small-unit leaders, and PCS sponsors during transitions between military installations (Geraci et al., 2020b). It appears that such guides and influencers can also be beneficial for TSMVs during their transition to civilian life –in the form of a sponsor. This was the case for Odysseus as he relied upon Athena, in the form of his comrade Mentor, to face many challenges returning home from war (Geraci et al., 2020b).

The findings specific to the primary hypothesis show some limitations of the studied community-based interventions, as implemented and researched within this study. The authors identified factors that may have contributed to the null findings for the primary hypothesis, which are already being addressed in current and future studies with TSMVs, such as addressing the unique needs of TSMVs, enrolling TSMVs into interventions prior to military discharge, measuring and attempting to improve participation levels, and providing stepped-care interventions based on risk levels (Geraci et al., 2022b; Geraci et al., 2022c; Geraci et al., 2022d).

Addressing the Unique Needs of Transitioning Servicemembers/Veterans

It is important to note that the use of orthogonal contrasts, as described by CONSORT guidelines (Juszczak et al., 2019) and Feingold and colleagues (2013) for 3-arm trials, did not provide a comparison of the intervention arms separately to the waitlist and resulted in both arms being dependent upon RWB performance. But this community-based intervention does not provide direct reintegration service to TSMVs, which might have attenuated the effect of Arm-3/RWB+ETS-SP. For instance, RWB may not be well suited to address some of the top reintegration needs and difficulties (online supplement) identified by TSMVs during the baseline assessment: confiding or sharing personal thoughts and feelings (#1), getting along with your spouse or partner (#3), and finding or keeping a job (#5).

Interventions Begin Prior to Military Discharge

Despite the focus of the study on early interventions, only 21% of TSMVs were still serving on active duty when they enrolled in the study. This limitation is minimized by the fact that the average time since discharge was 2.80 years and still within the target window of three years post-military discharge (Shen et al., 2016; Elbogen et al., In Press). Though, many researchers have recently recommended that the optimal time for enrollment of TSMVs into such preventive interventions is prior to military discharge (Vogt et al. 2020; Koh et al., 2022; Stanley et al., 2022; Chu et al., 2022; Hoffmire et al., 2022). This recommendation is based on research that identifies the challenges that TSMVs face during the first year after military discharge, especially with suicide risk (VA, 2022d; Shen et al., 2016). For example, in a population-based cohort study with over 1.8 million TSMVs, Ravindran and colleagues (2020) found that the risk of suicide death peaked between 6 and 12 months post-military discharge and then declined modestly over the next 6 years.

Participation-levels

Previous research suggests that TSMVs who are actively involved and participate in RWB activities experience improved authentic relationships with others and life satisfaction as a result (Angel et al., 2016). Though, the level of TSMV participation in RWB activities was not tracked by RWB nor the authors in this study. It therefore remains unclear to what extent the level of participation in RWB activities may have moderated observed primary hypothesis results. The authors did conduct secondary analysis with the ratings that TSMVs in Arm-3/RWB+ETS-SP provided of their sponsors, which identified that TSMVs who rated their sponsors higher for task-oriented and relational-oriented leadership behaviors had improvements in outcome variables. It is likely that comparable analysis with RWB participation levels, if collected, would have identified similar trends.

Stepped-Care Interventions Based on Risk-Levels

The current study did not determine risk levels of TSMVs nor offer a stepped-care intervention approach based on risk level. This probably led to TSMVs participating in aspects of the interventions they might not have needed, thus potentially impacting the observed results. Research from the DoD Study to Assess Risk and Resilience in Servicemembers -Longitudinal Study (STARRS-LS) epidemiological-neurobiological studies (Naifeh et al., 2019) suggest that it is possible to categorize active-duty Servicemembers based on risk level and then to provide a stepped-care intervention approach. For instance, STARRS-LS studies have identified that ensemble machine learning models using information available prior to separation (e.g., age, gender, discharge type, substance use, suicidal ideation and behavior, highly stressful events) can predict homelessness and medically serious suicide attempts made after separation with very good accuracy, as indicated by the 15% of TSMVs with highest predicted risk accounting for over 80% of homelessness and medically serious suicide attempts (Koh et al., 2022; Stanley et al., 2022; Chu et al. 2022). It is likely that attending the required and universal DoD Transition Assistance Program (DoD, 2022) might be sufficient to assist many low-risk TSMVs in their transition to civilian life. However, TSMVs identified as high-risk by the STARRS-LS model would most likely benefit from individualized and intensive interventions that consisted of community programs, a certified sponsor, and streamlined access to VA healthcare, including case management, primary care, and suicide-safety planning group treatment (Geraci et al., 2022b; Goodman et al., 2021).

Results of the current study should be understood within the context of a few methodological limitations. First, although the study’s sample size was considered adequate using a-priori statistical power analyses, the sample was comprised predominantly of White men with prior service in the US Army. Future research should therefore aim to include larger and more heterogenous samples. Second, the study was conducted in a large metropolitan area, which might limit the external validity of the results given that population size and socioeconomic factors impact risk level for TSMVs (Edwards et al., 2022b). Third, analyses may have been limited by an overly narrow consideration of outcome variables. Ample research suggests TSMVs often struggle with a range of difficulties that exist in tandem with reintegration difficulties, including mental health concerns, physical health concerns, and difficulties in employment and educational pursuits (Elbogen et al., In Press; Koh et al., 2022; Sokol et al., 2021; Stanley et al., 2022; Vogt et al., 2021). Future research may therefore employ a larger range of potentially relevant outcome measures to provide a more wholistic understanding of the potential benefits of community-based interventions for TSMVs with special attention towards measures that assess the positive end of well-being and reintegration.

Conclusion

This study is the first randomized controlled trial focused on reducing reintegration difficulties and improving social support for TSMVs through community-based interventions. The results did not support the primary hypothesis and the authors identified important factors that likely contributed to the null findings and that can be addressed in future studies with TSMVs. Results did attest to the potential additive value of mentor-sponsorship programs in supporting this vulnerable population. They also emphasized the importance of task- and relational-oriented leadership behaviors in efforts to reduce reintegration difficulties and improve TSMV social support. Given the dearth of similar studies, it would be beneficial to further expand research that studies preventive, community-based interventions for TSMVs to inform implementation decisions, as required by the Foundations for Evidence-Based Policymaking Act (US PL 115–435) of 2018 that mandates the use of evidence and evaluation to inform federal policies and budget allocations (Hahn et al., 2019). This could help to improve the quality and effectiveness of such interventions (Sokol et al., 2021; VA, 2022c) as federal initiatives and legislation, such as the Commander John Scott Hannon Veterans Mental Health Care Improvement Act, have prioritized and allocated funding to support community-based interventions for TSMVs (VA, 2021).

Supplementary Material

Supplemental Material

Impact statement:

Transitioning military servicemembers and veterans (TSMVs) face a range of difficulties throughout their reintegration to civilian life, including challenges with employment, poor social connection, and elevated risk for suicide. The findings suggest that national initiatives consisting of community-based interventions that assist TSMVs may be significantly enhanced through the addition of certified sponsors.

Acknowledgement:

This manuscript is dedicated to Tim O’Connor. Without his efforts this work would not have been possible. Tim’s life ended way too early but his legacy and motto of “Playing Offense for Veterans” live on.

Funding for the study provided by David and Maureen O’Connor and Teachers College, Columbia University. This research was also supported by the US Department of Veterans Affairs, Office of Academic Affiliations, VA Special MIRECC Fellowship Program in Advanced Psychiatry and Psychology. The views expressed here are the authors’ and do not necessarily represent the views of the US Department of Veterans Affairs and the VA’s Office of Academic Affiliations.

The authors have no disclosures nor conflicts of interest that would need to be listed on the Full Disclosure of Interests form. This includes any interests or activities that might be seen as influencing the research (e.g., financial interests in a test or procedure, funding by pharmaceutical companies for research).

References

  1. Ahern J, Worthen M, Masters J, Lippman SA, Ozer EJ, & Moos R (2015). The challenges of Afghanistan and Iraq veterans’ transition from military to civilian life and approaches to reconnection. PloS one, 10(7), e0128599. 10.1371/journal.pone.0128599 [DOI] [PMC free article] [PubMed] [Google Scholar]
  2. Angel C & Armstrong N (2016). Enriching veterans’ lives through an evidence-based approach: A case illustration of Team Red, White & Blue. Syracuse, NY. [Google Scholar]
  3. Ainspan ND, & Penk WE (Eds.). (2008). Returning wars’ wounded, injured, and ill: A reference handbook. Praeger Security International. [Google Scholar]
  4. Amara J, & Hendricks AM (2016). Demographics and characteristics of the U.S. military. In Ainspan ND, Bryan CJ, & Penk WE (Eds.), Handbook of psychosocial Interventions for veterans and service members (pp. 3–13). New York, NY: Oxford University Press. 10.1093/med:psych/9780199353996.003.0001 [DOI] [Google Scholar]
  5. AmericaServes (2022). AmericaServes Insights. New York, NY: Syracuse University. https://americaserves.org/what-we-do/insights/ [Google Scholar]
  6. America’s Warriors Partnership (2022). https://www.americaswarriorpartnership.org
  7. Brenner LA, Homaifar BY, Adler LE, Wolfman JH, & Kemp J (2009). Suicidality and veterans with a history of traumatic brain injury: Precipitating events, protective factors, and prevention strategies. Rehabilitation Psychology, 54(4), 390. 10.1037/a0017802 [DOI] [PubMed] [Google Scholar]
  8. Carroll D, Kearney L, & Miller M (2020). Addressing Suicide in the Veteran Population: Engaging a Public Health Approach, Frontiers in Psychiatry. 10.3389/fpsyt.2020.569069 [DOI] [PMC free article] [PubMed] [Google Scholar]
  9. Castillo EA, Mason J, D’Addario A, Chow GM, & Tenenbaum G (2019). Resilience and veteran community reintegration: An exploratory study. Military Behavioral Health, 7(4), 391–400. 10.1080/21635781.2018.1534702 [DOI] [Google Scholar]
  10. Chinman M, Goldberg R, Daniels K, Muralidharan A, Smith J, …Li L (2021). Implementation of peer specialist services in VA primary care: a cluster randomized trial on the impact of external facilitation. Implementation Science, 16, 60, 10.1186/s13012-021-01130-2 [DOI] [PMC free article] [PubMed] [Google Scholar]
  11. Chu C, Stanley I, Marx B, King A, Vogt D,…Kessler R (2022). Associations of vulnerability to stressful life events with suicide attempts after active duty among high-risk soldiers: results from the Study to Assess Risk and Resilience in Servicemembers longitudinal study (STARRS-LS). Psychol Med. 27:1–11. doi: 10.1017/S0033291722000915. [DOI] [PMC free article] [PubMed] [Google Scholar]
  12. Cohen J (1988). Statistical power analysis for the behavioral sciences (2nd ed.). Hillsdale, NJ: Lawrence Earlbaum Associates. [Google Scholar]
  13. Currier JM, Holland JM, Drescher K, & Foy D (2015). Initial psychometric evaluation of the Moral Injury Questionnaire—Military version. Clinical Psychology & Psychotherapy, 22(1), 54–63. 10.1002/cpp.1866 [DOI] [PubMed] [Google Scholar]
  14. Davis VE, & Minnis SE (2017). Military veterans’ transferrable skills: An HRD practitioner dilemma. Advances in Developing Human Resources, 19(1), 6–13. 10.1177/1523422316682961 [DOI] [Google Scholar]
  15. Demers A (2011). When veterans return: The role of community in reintegration. Journal of Loss and Trauma, 16(2), 160–179. 10.1080/15325024.2010.519281 [DOI] [Google Scholar]
  16. Derefinko KJ, Hallsell TA, Isaacs MB, Colvin LW, Salgado Garcia FI, Bursac Z (2019). Perceived needs of veterans transitioning from the military to civilian life. J Behav Health Serv Res, 46(3), 384–398. Doi: 10.1007/s11414-018-9633-8. [DOI] [PubMed] [Google Scholar]
  17. DeRue DS, Nahrgang JD, Wellman N, & Humphrey SE (2011). Trait and behavioral theories of leadership and meta-analytic test of their relative validity. Personnel Psychology, 64(1), 7–52. 10.1111/j.1744-6570.2010.01201.x [DOI] [Google Scholar]
  18. Eby L, Allen TD, Hoffman BJ (2013). An interdisciplinary meta-analysis of the potential antecedents, correlates, and consequences of protégé perceptions of mentoring, Psychological Bulletin, 139(2), 441–476. 10.1037/a0029279 [DOI] [PubMed] [Google Scholar]
  19. Edwards ER, Dichiara A, Gromatsky M, Tsai J, Goodman M, & Pietrzak R (2022a). Understanding risk of younger Veterans: Risk and protective factors associated with Suicide attempt, homelessness, and arrest in a nationally representative Veteran sample. Military Psychology, 34(2), 175–186. 10.1080/08995605.2021.1982632. [DOI] [PMC free article] [PubMed] [Google Scholar]
  20. Edwards ER, Gromatsky M, Dichiara A, Goodman M, Tsai J, Geraci A, & Geraci J (2022b). Demographic and socioeconomic correlates of suicide deaths and nonfatal self-Injury related hospital visits: An analysis of counties in New York State. Psychiatry Res. doi: 10.1016/j.psychres.2022.114407. [DOI] [PubMed] [Google Scholar]
  21. Elbogen E, Zeber J, Vogt D, Perkins D, Finley E, Copeland L (In Press). Financial status and well-being in recently separated military veterans. Military Medicine. [DOI] [PubMed] [Google Scholar]
  22. Elliott M, Gonzalez C, & Larsen B (2011). US military veterans transition to college: Combat, PTSD, and alienation on campus. Journal of Student Affairs Research and Practice, 48(3), 279–296. 10.2202/1949-6605.6293 [DOI] [Google Scholar]
  23. Erbes CR, Kramer M, Arbisi PA, DeGarmo D, & Polusny MA (2017). Characterizing spouse/partner depression and alcohol problems over the course of military deployment. Journal of Consulting and Clinical Psychology, 85(4), 297. 10.1037/ccp0000190 [DOI] [PubMed] [Google Scholar]
  24. Expiration Term of Service Sponsorship (2022) www.etssponsorship.com.
  25. Feingold A (2013). A regression framework for effect size assessments in longitudinal modeling of group differences. Rev Gen Psychol, 17(1): 111–121. 10.1037/a0030048 [DOI] [PMC free article] [PubMed] [Google Scholar]
  26. Fiedler FE (1967). A theory of leadership effectiveness. Mcgraw-Hill. [Google Scholar]
  27. Geraci J, Murray C, Kapil-Pair KN (2020a). The modern-day Odysseus: How mental health providers can better reintegrate modern warriors and mitigate suicide risk, J. Clin. Psychol 76, 823–915. 10.1002/jclp.22923 [DOI] [PubMed] [Google Scholar]
  28. Geraci J, Mobbs M, Edwards E, Doerries B, Armstrong N…& Goodman M (2020b). Expanded roles and recommendations for stakeholders to successfully reintegrate modern Warriors and mitigate suicide risk. Frontiers in Psychology, 11, 1907. 10.3389/fpsyg.2020.01907 [DOI] [PMC free article] [PubMed] [Google Scholar]
  29. Geraci J, Kilby D, Arenz J(2020c). Trained, peer sponsorship/mentorship training manual. VISN 2 MIRECC. Veterans Affairs [Google Scholar]
  30. Geraci J, Bulanchuk N, Ryszkiewicz P, Goldsmith M, Thompson J, Baker M (2022a). Leading to Promote Resilience and Mitigate PTSD, in Leading in Dangerous Contexts, eds Sweeney P, Matthews M, and Lester P (Annapolis, MD: Naval Institute Press; ), 2nd edition. [Google Scholar]
  31. Geraci J, Borah E, Paine C, Edwards E, Finley E, Goodman M, Seim R, & Kessler R (2022b). Addressing key US Army priority problem areas through the translation of science to the implementation of evidence-based interventions: III Armored Corps’ People First Center. Submitted for publication. [Google Scholar]
  32. Geraci J, Eickhoff C, Edwards E, Finley E, Seim R, Goodman M (2022c). Mitigating suicide risk during the military-to-Civilian transition: veteran sponsorship initiative. Submitted for publication. [Google Scholar]
  33. Geraci J, Finley E, Edwards E, Frankfurt S,…Goodman M (2022d). Partnered implementation of the veteran sponsorship initiative: Protocol for a randomized hybrid type 2 effectiveness-implementation trial, Implementation Science. 17, 43. 10.1186/s13012-022-01212-9 [DOI] [PMC free article] [PubMed] [Google Scholar]
  34. Goodman M, Sullivan S, Spears A, Dixon L, Sokol Y, Kapil-Pair K, Galfalvy H….& Stanley B (2021). An open trial of a suicide safety planning group treatment: “Project life force.” Archives of Suicide Research, 25(3), 690–703. [DOI] [PMC free article] [PubMed] [Google Scholar]
  35. Halpin A (1957). Manual for the leader behavior description questionnaire, Fisher College of Business, Columbus, OH. [Google Scholar]
  36. Hahn R (2019). Building upon foundations for evidence-based policy. Science, 364(6440), 534–535. 10.1126/science.aaw9446 [DOI] [PubMed] [Google Scholar]
  37. Hartnell C, Kinicki A, Lambert L (2016). Do similarities or differences between CEO leadership and organizational culture have a more positive effect on firm performance? A test of competing predictions. Journal of Applied Psychology, 101(6): 846–861. 10.1037/apl0000083 [DOI] [PubMed] [Google Scholar]
  38. Hoffmire C, Borowski S, Griffin B, Maguen S, & Vogt D (2022). Trajectories of suicidal ideation following separation from military service: Overall trends and group differences. Suicide Life Threat Behavior, 52(3):413–426. doi: 10.1111/sltb.12831. [DOI] [PubMed] [Google Scholar]
  39. Interian A, Kline A, Callahan L, & Losonczy M (2012). Readjustment stressors and early mental health treatment seeking by returning National Guard soldiers with PTSD. Psychiatric services, 63(9), 855–861. 10.1176/appi.ps.201100337 [DOI] [PubMed] [Google Scholar]
  40. Juszczak E, Altman D, Hopewell S (2019). Reporting of multi-arm parallel-group randomized trials; Extension of the CONSORT 2010 Statement. JAMA, 10.1001/jama.2019.3087 [DOI] [PubMed] [Google Scholar]
  41. Kim J & Shin W (2014). How to do random allocation (randomization). Clinics in Orthopedic Surgery, 6, 1, 103–109. 10.4055/cios.2014.6.1.103 [DOI] [PMC free article] [PubMed] [Google Scholar]
  42. Kline A, Ciccone DS, Falca-Dodson M (2011). Suicidal ideation among National Guard troops deployed to Iraq. Nervous & Mental Disease, 199, 914–920. 10.1097/NMD.0b013e3182392917 [DOI] [PubMed] [Google Scholar]
  43. Koh KA, Montgomery AE’ O’Brien RW, Kennedy CJ, Luedtke A, Sampson NA,.. & Kessler RC (2022). Predicting Homelessness Among US Army Soldiers No longer On Active Duty. American Journal of Preventive Medicine. 10.1016/j.amepre.2021.12.028 [DOI] [PMC free article] [PubMed] [Google Scholar]
  44. Liao H & Chuang A (2007). Transforming service employees and climate: A multilevel, multisource examination of transformational leadership in building long-term service relationships. Journal of Applied Psychology, 92(4): 1006–1019. 10.1037/0021-9010.92.4.1006 [DOI] [PubMed] [Google Scholar]
  45. Magnusson K (2018). powerlmm: Power analysis for longitudinal multilevel models. (Version 0.4.0.) [Computer software]. https://github.com/rpsychologist/powerlmm.
  46. Naphan D, & Elliot M (2015). Role Exit from the Military: Student Veterans’ Perceptions of Transitioning from the US Military to Higher Education. Qualitative Report, 20(2). https://nsuworks.nova.edu/tqr/vol20/iss2/4/ [Google Scholar]
  47. Naifeh JA, Mash HBH, Stein MB, Fullerton CS, Kessler RC, & Ursano RJ (2019). The Army study to assess risk and resilience in servicemembers (Army STARRS): Progress toward understanding suicide among soldiers. Molecular Psychiatry, 24(1). 10.1038/s41380-018-0197-z [DOI] [PMC free article] [PubMed] [Google Scholar]
  48. O’Connor E, Cappella E, McCormick M (2014). An examination of the efficacy of INSIGHTS in enhancing the academic and behavioral development of children in early grades. Journal of Educational Psychology, 106, 1156–1169. 10.1037/a0036615 [DOI] [Google Scholar]
  49. Pietrzak RH, Johnson DC, Goldstein MB, Malley JC, & Southwick SM (2009). Perceived stigma and barriers to mental health care utilization among OEF-OIF veterans. Psychiatric services, 60(8), 1118–1122. 10.1176/ps.2009.60.8.1118 [DOI] [PubMed] [Google Scholar]
  50. ProVetus (2022). Retrieved from https://www.provetus.org/.
  51. Prudential Financial (2012). Veterans’ employment challenges perceptions and experiences of transitioning from military to civilian life, https://eoa.oregonstate.edu/sites/eoa.oregonstate.edu/files/veterans_employment_challenges.pdf.
  52. R Core Team R (2020). A language and environment for statistical computing. (Version 4.0.3) [Computer software]. https://www.R-project.org/.
  53. Raudenbush S, Bryk A, Cheong Y (2019). HLM 8. Hierarchical Linear and Nonlinear Modeling, Scientific Software International , Inc. [Google Scholar]
  54. Ravindran C, Morley SW, Stephens BM, Stanley IH, & Reger MA (2020). Association of suicide risk with transition to civilian life among US Military Service Members. JAMA Network Open, 3(9), e2016261. 10.1001/jamanetworkopen.2020.16261 [DOI] [PMC free article] [PubMed] [Google Scholar]
  55. Sayers SL, Farrow VA, Ross J, & Oslin DW (2009). Family problems among recently returned military veterans referred for a mental health evaluation. Journal of Clinical Psychiatry, 70(2), 163. 10.4088/jcp.07m03863 [DOI] [PubMed] [Google Scholar]
  56. Sayer N, Frazier P, Orazem R (2011). Military to civilian questionnaire. J. Traum. Stress, 660–670. 10.1002/jts.20706 [DOI] [PubMed] [Google Scholar]
  57. Sayer N, Orazem R Noorbaloochi S (2014). Iraq and afghanistan war veterans with reintegration problems: Differences by veterans affairs healthcare user status, Adm Policy Ment Health. 10.1007/s10488-014-0564-2 [DOI] [PMC free article] [PubMed] [Google Scholar]
  58. Shadish WR, Cook TD, & Campbell D (2001). Experimental and quasi-experimental designs for generalized causal inference. Boston, MA: Houghton Mifflin. [Google Scholar]
  59. Shen YC, Cunha JM, & Williams TV (2016). Time-varying associations of suicide with deployments, mental health conditions, and stressful life events among current and former US military personnel: a retrospective multivariate analysis. The Lancet Psychiatry, 3(11), 1039–1048. 10.1016/S2215-0366(16)30304-2 [DOI] [PubMed] [Google Scholar]
  60. Sherbourne CD, & Stewart AL (1991). The MOS social support survey. Social Science & Medicine, 32(6), 705–714. 10.1016/0277-9536(91)90150-b [DOI] [PubMed] [Google Scholar]
  61. Sokol Y, Gromatsky M, Edwards E, Greene A, Geraci J, Harris R, Goodman M (2021). The Deadly Gap: Understanding Suicide among Veterans Transitioning Out of the Military. Psychiatry Research. 10.1016/j.psychres.2021.113875 [DOI] [PubMed] [Google Scholar]
  62. Stanley IH, Chu C, Gildea SM, Hwang IH, King AJ, Kennedy CJ, ... & Kessler RC (2022). Predicting suicide attempts among US Army soldiers after leaving active duty Using information available before leaving active duty: results from the Study to Assess Risk and Resilience in Servicemembers-Longitudinal Study (STARRS-LS). Molecular psychiatry, 1–9. 10.1038/s41380-021-01423-4 [DOI] [PMC free article] [PubMed] [Google Scholar]
  63. Stone C, & Stone DL (2015). Factors affecting hiring decisions about veterans. Human Resource Management Review, 25(1), 68–79. 10.1016/j.hrmr.2014.06.003 [DOI] [Google Scholar]
  64. Team Red, White & Blue (2021). Enriching the lives of America’s veterans.https://www.teamrwb.org/..
  65. US Department of Defense (2011). Best Practices Identified for Peer Support Programs, Washington D.C. [Google Scholar]
  66. US Department of Defense (2022). Transition Assistance Program. https://www.dodtap.mil/dodtap/app/home.
  67. US Navy (2012). U.S. Marine Corps Sponsorship Program Virginia: US Navy. [Google Scholar]
  68. US Department of Veterans Affairs (2018a). The Military to Civilian Transition 2018. Washington, DC. Retrieved from https://benefits.va.gov/TRANSITION/docs/mctreport-2018.pdf [Google Scholar]
  69. US Department of Veterans Affairs (2018b). Profile of post-9/11 veterans: 2016. Washington DC: National Center for Veterans Analysis and Statistics. Retrieved from https://www.va.gov/vetdata/docs/SpecialReports/Post_911_Veterans_Profile_2016.pdf [Google Scholar]
  70. US Veterans Affairs (2021). National Veteran Suicide Prevention Annual Report. https://www.mentalhealth.va.gov/docs/data-sheets/2021/2021-National-Veteran-Suicide-Prevention-Annual-Report-FINAL-9-8-21.pdf
  71. US Department of Veterans Affairs (2022a). Veteran sponsor partnership network. https://www.va.gov/HEALTHPARTNERSHIPS/vspn.asp.
  72. US Department of Veterans Affairs (2022b). VA Veteran Sponsorship Initiative. https://www.mirecc.va.gov/visn17/research.asp
  73. US Department of Veterans Affairs (2022c). Health Services Research & Development. https://www.hsrd.research.va.gov/research_topics/
  74. US Veterans Affairs (2022d). National Veteran Suicide Prevention Annual Report. https://www.mentalhealth.va.gov/docs/data-sheets/2022/2022-National-Veteran-Suicide-Prevention-Annual-Report-FINAL-508.pdf
  75. US Internal Revenue Service (2022). Tax Exempt Organization Search. Washington, DC: US Internal Revenue Service. [Google Scholar]
  76. Vogt D, Perkins DF, Copeland LA, Finley EP, Jamieson CS, Booth B, ... & Gilman CL (2018). The Veterans Metrics Initiative study of US veterans’ experiences during Their transition from military service. BMJ open, 8(6), e020734. 10.1136/bmjopen-2017-020734 [DOI] [PMC free article] [PubMed] [Google Scholar]
  77. Vogt D, Tyrell F, Bramande E (2020). U.S. military veterans’ health and well-being in the first year after service. American Journal of Preventive Medicine. 58. 352–360. 10.1016/j.amepre.2019.10.016 [DOI] [PubMed] [Google Scholar]
  78. Vogt D, King MW, Borowski S, Finley EP, Perkins DF, Copeland LA (2021). Identifying factors that contribute to military veterans’ post-military well-being. Appl Psychol Health Well-Being, 13(2), 341–356. doi: 10.1111/aphw.12252. [DOI] [PubMed] [Google Scholar]
  79. Walumbwa F, Hsu I, Wu C, Misati E, Christensen-Salem A (2019). Employee service performance and collective turnover: Examining the influence of initiating structure leadership, service climate and meaningfulness. Human Relations, 72(7), 1131–1153. 10.1177/0018726718790649 [DOI] [Google Scholar]
  80. White House (2018). Executive order 13822—Supporting our veterans during their transition from uniformed service to civilian life. https://www.govinfo.gov/content/pkg/DCPD-201800015/pdf/DCPD-201800015.pdf
  81. White House (2019). Executive Order 13861—National roadmap to empower veterans and end suicide. https://www.govinfo.gov/content/pkg/DCPD-201900126/pdf/DCPD-201900126.pdf
  82. White House (2021). Reducing military and veteran suicide: Advancing a comprehensive cross-sector, evidence-informed public health strategy. https://www.whitehouse.gov/wp-content/uploads/2021/11/Military-and-Veteran-Suicide-Prevention-Strategy.pdf [Google Scholar]

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