Improving Voluntary Engagement for PTSD Treatment Among Active-Duty Service Members Using Motivational Enhancement Therapy

Abstract

Objective:

PTSD prevalence in the military is high and effective treatments are underutilized. Motivational Enhancement Therapy (MET) “check-ups” are brief interventions to elicit treatment uptake for those who are non-treatment seeking. The aim of the current study was to test the efficacy of a novel MET intervention designed to promote treatment engagement among active-duty US military personnel with untreated PTSD.

Method:

One hundred and sixty-one active-duty service members who met criteria for PTSD were randomized to MET or Treatment as Usual (TAU, treatment resource and referral). MET participants (n = 82) received up to three 30–90 minute telephone sessions. TAU participants (n = 79) were mailed PTSD resources and referrals. Follow-up assessments were conducted 6-weeks, 3-, and 6- months post-baseline.

Results:

Mixed effect model results indicated treatment uptake significantly increased over time but there were no significant differences between conditions or interactions. PTSD symptom severity significantly decreased for both conditions. There was also a significant three-way interaction with baseline readiness-to-change confidence. Those low in baseline readiness-to-change saw more favorable effects of MET (relative to TAU) at 6-month follow-up.

Conclusions:

Results suggest both MET and high-quality referral options have promise as means of increasing evidence-based treatment uptake and decreasing PTSD for service members with PTSD. MET may be particularly useful for individuals with low confidence in their ability to address PTSD. Given the individual and societal costs of PTSD, there is need for interventions facilitating treatment uptake.

Members of the military are at increased risk for posttraumatic stress disorder (PTSD; Creamer et al., 2011) with post-deployment prevalence of PTSD ranging from 5–20% (Ramchand et al., 2010). Untreated PTSD may become chronic; findings suggest individuals with PTSD at early time points continue to meet criteria for PTSD 20 or 30 years later (O’Toole et al., 2009; Solomon & Mikulincer, 2006). PTSD is associated with negative consequences including poorer physical health, higher morbidity and mortality, suicidal ideation and death by suicide, and higher rates of homelessness and substance misuse (Ramchand et al., 2015).

There are multiple effective treatments for PTSD (Kitchiner et al., 2019; Lewis et al., 2020). Manualized trauma focused therapies with exposure or cognitive restructuring are considered first line treatments (Bisson et al., 2019; Department of Veterans Affairs & Department of Defense, 2017). Evidence-based trauma-focused psychotherapy have also been found to be effective among military samples with 49–70% of patients experiencing clinically meaningful reductions in PTSD following treatment (Kitchiner et al., 2019). Medications such as SSRIs, and SNRIs are also indicated for PTSD, particularly for those who do not have access to trauma focused psychotherapy (Department of Veterans Affairs & Department of Defense, 2017; Hoskins et al., 2021; Huang et al., 2020).

Unfortunately, individuals experiencing PTSD often do not seek treatment. One national study found that of adults with past-year PTSD, only 30% had accessed a mental health specialist (Nobles et al., 2016). Similarly, fewer than half of service members with PTSD seek treatment and for those who receive a specialty care referral, less than half follow through (Edwards-Stewart et al., 2021; Hoge et al., 2006). Meta-analyses reveal the average PTSD treatment dropout rate was 18% in PTSD clinical trials (Imel et al., 2013) and 24.2% in military and veteran samples (Edwards-Stewart et al., 2021). These findings suggest the need to develop interventions to attract and encourage treatment seeking for those with PTSD and encourage ongoing engagement for those who have started treatment.

Lack of awareness of the need to change, ambivalence about symptoms, or a lack of confidence that change is possible may all hinder treatment (Bosmans et al., 2016). For example, PTSD symptoms such as hypervigilance or mistrust of others may instead be seen as coping strategies to deal with a dangerous world. Avoidance may be seen as functional, rather than as a psychiatric symptom (Murphy et al., 2009). Increased awareness of problems and thus readiness to change may facilitate treatment engagement and has been shown to be a malleable intervention target (Murphy et al., 2009).

Motivational interviewing improves treatment engagement, and outcomes for cognitive-behavioral anxiety interventions (Marker & Norton, 2018; Randall & McNeil, 2017), and has been suggested for similar use in PTSD treatment (Hamblen et al., 2015; Resick et al., 2017). A small number of studies have evaluated MI or motivational enhancement therapy (MET; a form of MI) to address problems common among PTSD populations. A four-session group MET was delivered prior to treatment for PTSD and increased motivation for change, treatment attendance and retention among veterans compared to an education control (Murphy et al., 2009). Veterans with mental health concerns (58% with PTSD) were offered 4 sessions of phone delivered MI (Seal et al., 2012), which increased treatment seeking and engagement compared to usual care.

Current Study

The Check-Up model, is an adaptation of motivational interviewing designed to prompt self-referral to care by non-treatment seekers (Walker et al., 2007). Comprised of a marketing campaign, assessment and motivational enhancement therapy, the Check-Up model has been applied to alcohol misuse with both military (Walker et al., 2017) and civilian samples (Miller et al., 1988), and multiple other problem behaviors (Walker et al., 2007). The objective of the present study was to evaluate the efficacy of StressCheck (MET), to address PTSD among service members who are not in treatment, in increasing treatment uptake and reducing PTSD. The comparison condition of treatment-as-usual (TAU) received a mailed packet of referral information. We hypothesized the following: 1) Individuals receiving MET will report more PTSD treatment uptake at follow-up relative to TAU; 2) Individuals receiving MET will experience fewer PTSD symptoms at follow-up relative to TAU; 3) Intervention effects would be moderated by readiness to change, such that those who were lower in readiness to change at baseline would have more favorable reaction to MET (Murphy et al., 2009).

Method

Design

The StressCheck intervention was compared to treatment-as-usual (TAU) in a parallel randomized controlled trial. Prior to commencement of the trial, oversight approval was obtained from Institutional Review Boards at the parent university and the Department of Defense (DoD). Study design was pre-registered with ClinicalTrials.gov (ID#: NCT03423394).

Sample Size & Power Estimates

Prior to the study, power analyses were calculated using a simulation-based approach (Gelman & Hill, 2007). Using R statistical software, 1,000 datasets were generated based on the linear mixed models described below. Estimates for model parameters for standardized PTSD scores (e.g., baseline intercept, slopes for time, distribution of random effects) were guided by preliminary data from a prior trial (Simpson et al., 2022). We specified missingness of 13% and 19% at 3- and 6-month follow-ups, respectively, according to missing data patterns in similar studies (Walker et al., 2017). With a sample of 200 participants, this study would have >.80 power to detect effect sizes of d = .36 or greater at any given follow-up. During recruitment, it was evident that sample size goals would not be met. Thus, power calculations were revised to estimate potential minimum detectable effect sizes for smaller sample sizes. Based on a revised sample size of 160, we estimated >.80 to detect effect sizes of d = .41 or greater.

Eligibility

Inclusion criteria required that participants (1) met DSM-5 PTSD diagnostic criteria, (2) were currently serving in the US Army, Navy, or Air Force, and (3) were not currently receiving evidence-based therapy for PTSD. Participants who were otherwise eligible, were excluded if they (1) had pending deployment preventing study completion, (2) had possible psychotic disorder, or (3) were non-fluent in English.

Enrollment

Recruitment & Screening

Initial recruitment was conducted at Joint Base Lewis-McChord (JBLM), a large military installation that supports both Army and Air Force personnel. With the permission of garrison commanders, print materials (posters, brochures, etc.) were distributed widely throughout the installation. Recruitment messaging was based on prior check-up interventions with military personnel (Walker et al., 2017; Walton et al., 2013) refined through focus group feedback to attract individuals experiencing symptoms of PTSD who may be ambivalent about change (Kaysen et al., 2022). After one year of a two-year recruitment period, we obtained necessary approvals to expand eligibility to Navy personnel and recruit nationally. We engaged a third-party study recruitment company to manage extension of our campaign online regardless of duty location. Comparison of participants based on mode of recruitment (local vs. online) showed no statistically significant difference (ps > .100) on baseline indicators of primary outcomes or secondary indicators that may affect primary outcomes, such as type of trauma, readiness to change, and other mental health concerns (depression, alcohol use disorder, and suicidality).

Screening entailed a two-stage approach. First, consenting participants completed a brief 5–10 minute “pre-screen” through which eligible participants were identified as (1) not currently engaged in PTSD treatment and (2) probable PTSD diagnosis using the 6-item Primary Care PTSD Screen for DSM-5 (PC-PTSD-5; Prins et al., 2016). Step-2 of screening involved a 75–90 minute interview that included a diagnostic PTSD assessment (described below) and a brief psychosis screening – the psychotic and associated symptoms component of the Structured Clinical Interview for DSM (SCID-PAS; First et al., 2002). Prospective participants meeting DSM-5 criteria for PTSD and showing no evidence of psychosis were informed of their eligibility and invited to enroll in the trial after providing informed consent. Full description of screening is provided in the online supplemental materials.

Randomization

Stratified randomization, with a 1-to-1 allocation ratio, was used to ensure equivalent distribution between conditions of four potentially relevant prognostic factors: gender (male/female), duty station (JBLM/non-JBLM), service branch, and PTSD severity (low/high). Lacking psychometric evaluation of the CAPS-5 at the time the study commenced, high PTSD severity was initially set at a score of 60 or above. However, after eight months of recruitment, no participant had yet to reach this threshold. As such, the cut score was lowered to 37 – one standard deviation above the mean baseline score of the then-enrolled sample (n = 22).

Following enrollment, blocking data was entered into randomization software developed for this project, which used a restricted urn procedure for allocation (Schulz & Grimes, 2002). The project director informed the participant of their intervention assignment and mailed them associated materials. Study assessors were blind to treatment condition.

Assessment

Assessments were conducted at baseline, 6-weeks, 3-months, and 6-months post-baseline. Study assessors, at the master’s level or higher in psychology or social work, administered the baseline, 3-month, and 6-month assessments over the phone with participants. Each of these required 60 to 90 minutes to complete. Participants could choose to complete the shorter (10–15 minute) 6-week assessment over the phone with study staff or via online self-response questionnaire. Participants were compensated up to $200 for completing study assessments – $25 each for baseline and 6-week assessments, $50 each for 3- and 6-month assessments, and a $50 bonus for completing all follow-ups.

Measures

Treatment Uptake.

An assessment of treatment uptake was developed specifically for this trial. Participants were asked to report involvement with various forms of treatment during each relevant referent period – 3 months prior to baseline and the time interval since prior assessment for follow-ups. Items were coded to produce a dichotomous variable indicating receipt of evidence-based treatment in the form of psychotherapy or medication. Evidence based psychotherapy was coded if participants indicated they had met with a therapist (psychologist, counselor, or social worker) at least every other week and PTSD symptoms or the traumatic event itself were discussed in every session. They were also asked whether they were continuing to engage with that treatment. Evidence-based pharmacotherapy was coded if their primary care provider, psychiatrist, or psychiatric nurse practitioner was prescribing a medication recommended as monotherapy for the treatment of PTSD (VA/DoD, 2017) and they were taking that medication as prescribed.

PTSD Diagnosis & Severity.

PTSD symptomatology was assessed at baseline, 3-, and 6-month follow-ups. The Life Events Checklist (LEC; Gray et al., 2004) was administered at baseline to determine exposure to a Criterion A traumatic event (APA, 2013). Study assessors then administered the Clinician-Administered PTSD Scale for DSM-5 (CAPS-5; Weathers et al., 2018), which is the gold standard assessment for PTSD diagnosis and severity (range: 0 to 80). Internal consistency was high across time points in the present sample (αs = .74 - .91; Taber, 2018).

Treatment Stigma & Perceptions of Effectiveness.

Reger et al. (2013) developed the Treatment Reactions Scale (TRS) to compare soldiers’ beliefs about the consequences of receiving different forms of PTSD treatment. We asked participants to think about receiving any form of PTSD treatment, including both talk therapy and/or medications, when responding. The TRS includes 31 items with five-point Likert-type response options and contains five subscales: shame/embarrassment, occupational/career impact, and perceived debasement for receiving PTSD treatment; willingness to recommend PTSD treatment to others; and perceived efficacy of PTSD treatment. Subscale scores are presented as the mean of items (range: 1 to 5) with higher scores indicating greater negative beliefs (i.e., greater perceived shame, less willingness to recommend, and less confidence in treatment). All subscales showed adequate internal consistency across time points (αs = .72 - .86; Taber, 2018).

Readiness to Change.

The Readiness Ruler (RR) is widely used in studies of novel motivational interventions. The two items assessing the importance of making a change and confidence in ability to change have both shown validity in predicting subsequent behaviors (Bertholet et al., 2012; Maisto et al., 2011). It was adapted to ask: “How important is it to you to reduce your PTS symptoms (such as, nightmares, jumpiness, irritability, trouble sleeping, avoidance of thoughts or situations related to the trauma)?” and “How confident are you that you will be able to work on your PTS symptoms?” Responses to both items were registered using a 9-point scale, ranging from “0 – Not at all” to “8 – Extremely.”

Interventions

Motivational Enhancement Therapy

The MET intervention uses a motivational interviewing (MI) counseling style with 1–3 sessions delivered via telephone lasting from 30 to 90 minutes (Miller & Rollnick, 2013). MI skills used throughout the MET intervention include evocation, reflective listening, affirmations and supporting the participant’s autonomy. Based on baseline assessment results, a personalized feedback report (PFR) is created for each participant that is mailed or emailed to the participant and reviewed in session 1. The PFR includes topics on life goals, PTSD symptoms and risk, functioning, stigma towards seeking treatment and data regarding PTSD treatment effectiveness and treatment options. The first session addresses participant reasons for calling the program, experiences that led to concern, and information about how PTSD symptoms have affected their life. This lays the groundwork for self-evaluation of their PTSD experiences and how they may benefit from seeking treatment. Throughout, the counselor evokes from the participant their reactions and fosters motivation to change.

Sessions 2 and 3 occur at 1 and 2 months after completion of the baseline for those participants who want additional support or resources for accessing care. They are centered on identifying and responding to barriers to participant’s active engagement in treatment, facilitating enrollment in therapy, and/or responding to risk factors for dropping out of treatment. PTSD symptoms and treatment seeking since the prior session are reviewed in an MI style that allows the participant to discuss treatment seeking attempts including if program information was obtained, acted upon, and if treatment was initiated, how it is progressing.

Treatment as Usual

TAU was modeled after what might typically occur within the military if a service member screened positive for PTSD, essentially a referral for services. TAU participants were mailed a curated resource and referral information pamphlet for PTSD and concomitant disorders (substance misuse), separated out by types of PTSD treatments.

Counselor Training & Supervision

Counselors were trained by the PIs in both MI and PTSD over the course of a two-month period. Counselors read the StressCheck manual and engaged in regular training activities that included didactic and experiential activities. Each counselor completed a practice case and a pilot participant (with an ineligible caller). Training case sessions were audio recorded, reviewed by the PIs and counselors were provided with detailed feedback. Supervision sessions occurred weekly where approximately 50% of sessions were reviewed by supervisors to prevent drift, address training issues and ensure fidelity.

Statistical Methods

When estimating efficacy of the MET, relative to TAU, we used linear mixed models with unstructured covariance matrices to account for repeated assessment within individuals (‘glmmTMB’ package in R; Bolker, 2016), and because of the considerable within-person variability in the outcomes (intraclass correlation coefficients: CAPS severity score ICC = 0.72; CAPS-based PTSD diagnosis ICC = 0.50; Treatment uptake ICC = 0.22). To enable interpretation of effects at various time points (e.g., 3-month follow-up), main effects for time were entered as indicator variables (i.e., baseline = 0) and as a condition×time interaction. These interaction coefficients represent differences between conditions at a given follow-up, relative to differences between the conditions when time was equal to zero (e.g., at baseline). The main effect of treatment condition represents differences between conditions at baseline. For outcomes that have variability at baseline (e.g., CAPS-5), the referent timepoint is baseline; however, for outcomes that had no variability at baseline due to inclusion criterion (i.e., treatment seeking, PTSD diagnoses), the referent timepoint was the next available measurement time. Specifically, the treatment seeking model used 6-week follow-up as the analytic reference timepoint and the CAPS-based PTSD diagnoses model used 3-month follow-up as the referent timepoint.

Logistic regression models were used for binary outcomes (i.e., treatment seeking, PTSD diagnoses) to estimate adjusted odds ratios. All models controlled for several covariates – including variables that were used in the randomization stratification procedures – which statistically controls for demographics (e.g., age, sex assigned at birth), military-specific descriptive (e.g., service branch, active-duty), and baseline clinical characteristics (e.g., treatment confidence, readiness to change). In line with intention-to-treat principles, all participants were retained in analyses regardless of protocol adherence or attrition at a given follow-up timepoint, which was minimal (i.e., 9.9% at 6-week follow-up and 14.3% at both 3- and 6-month follow-ups). Predictors of attrition were examined at each follow-up. Attrition at 6 weeks was only related to station (i.e., greater attrition at JBLM; p=.002); attrition at 3 months was related to treatment condition (i.e., greater among MET; p=.022); and attrition at 6 months was related to both study condition (i.e., greater among MET; p=.019) and baseline readiness to change confidence (i.e., greater among those with lower confidence; p=.047). Consistent with intention-to-treat analyses (White et al., 2011), missing responses were imputed using multivariate chained equations (MICE) using all covariates and outcome variables (‘mice’ package in R; Buuren & Goothius-Oudshoorn, 2011). Twenty imputed datasets were created and models were run within each of the imputed datasets. Effect estimates were ‘pooled’ across the imputed datasets (Rubin, 1987). Moderation effects of readiness-to-change were estimated in a separate model by adding three-way interaction terms (i.e., Time × Condition × Readiness-to-Change). Significant interaction effects were probed by estimating and plotting simple slopes that enhance interpretability of direction and magnitude of interactions.

Results

Recruitment & Participant Flow

Between January 2018 and February 2021, 1,471 individuals were assessed for eligibility. Of the 167 found to be eligible, 163 chose to enroll in the trial. Eighty-one participants were randomized to the experimental MET condition and 82 to the TAU comparison condition. Two TAU participants were excluded from final analysis because it was determined that they should not have been enrolled due to not meeting eligibility criteria – both should have been classified as actively receiving PTS treatment. With these exclusions, the final intent-to-treat sample includes 161 participants. A CONSORT diagram is provided in supplemental materials.

Of 81 participants assigned to the MET condition, 75 (92.6%) completed the intervention by attending at least the first session. Eight (9.9%) completed only the first intervention session, 16 (19.8%) completed two sessions, and 51 (63.0%) completed three sessions.

Follow-up data collection continued until September 2020. Completion rates were high for the full sample with 90.8% completion at 6-week follow-up and 85.9% completion at both 3- and 6-month timepoints. Four MET participants notified study staff of their intent to withdraw from the study (one due to new time commitments; three provided no explanation). No unintended consequences or harms to participants were observed or reported during the trial.

Descriptive Results

Participant demographics, military descriptors, and baseline clinical characteristics are shown in Table 1. Table 2 provides a descriptive overview of main and secondary outcomes by timepoint and stratified by condition. There were no significant baseline differences between groups on any primary outcome measures.

Table 1.

Baseline demographics, military, and clinical characteristics

	N = 161
Age	M = 29.7 (SD = 7.5)
Female	31.2%
Persons of color	19.3%
Lesbian/gay/bisexual	16.9%
Service branch
Army	80.1%
Air Force	16.1%
Navy	3.7%
Duty station: JBLM	29.8%
Years of Service	M = 8.85 (SD = 6.3)
Paygrade
E1-E4	43.5%
E5-E9	43.5%
O1-O9; W1-W5	13.0%
Status
Active duty	69.6%
Reserve	11.2%
National Guard	19.2%
Combat deployed	56.2%
Index trauma
Combat	39.8%
Military sexual trauma	17.4%
Sexual assault (non-military)	9.3%
Violent death (non-combat)	13.0%
Accident	10.6%
Other	10.0%
Lifetime engagement with PTS treatment or support
Self-help or support group	34.2%
Individual therapy	79.5%
Pastoral care	50.9%
Primary care provider	37.9%
Psychiatrist	48.4%
Mobile phone application	26.7%
Any	89.4%

Table 2.

Descriptive overview of main and secondary outcomes at baseline, 6-week, 3-month, and 6-month follow-ups, stratified by intervention condition.

	Baseline		6-Week Follow-up		3-Month Follow-up		6-Month Follow-up
	MET	TAU	MET	TAU	MET	TAU	MET	TAU
Any Tx Engagement	0% [0, 0]	0% [0, 0]	8.6% [2.0, 15.1]	9.3% [2.7, 15.9]	12.5% [4.4, 20.6]	18.9% [10.0, 27.8]	12.5% [4.4, 20.6]	12.2% [4.7, 19.6]
CAPS-based PTSD Diagnosis	100% [100, 100]	100% [100, 100]	---	---	50.0% [37.8, 62.3]	48.0% [36.7, 59.3]	29.7% [18.5,40.9]	40.5% [29.4, 51.7]
CAPS Total Score	33.4 (8.9)	32.4 (8.9)	---	---	22.7 (12.7)	23.2 (12.8)	18.3 (13.1)	20.8 (14.7)
Concern for Occupational/Career Harm	3.1 (1.1)	3.4 (0.9)	3.4 (1.0)	3.5 (0.9)	3.3 (1.1)	3.4 (1.0)	3.2 (1.1)	3.2 (1.0)
Concern for Debasement	2.2 (0.6)	2.3 (0.7)	2.4 (0.7)	2.5 (0.7)	2.1 (0.7)	2.2 (0.7)	2.2 (0.8)	2.1 (0.7)
Shame/Embarrassment	2.5 (0.7)	2.6 (0.8)	2.8 (0.8)	2.8 (0.8)	2.4 (0.9)	2.5 (0.9)	2.5 (0.9)	2.5 (0.9)
Treatment Efficacy/Confidence	2.3 (0.6)	2.3 (0.7)	2.4 (0.6)	2.3 (0.6)	2.3 (0.7)	2.3 (0.7)	2.2 (0.7)	2.3 (0.7)

Note: Percent values are shown with 95% confidence intervals in brackets. Mean values are shown with standard deviations in parentheses. CAPS was not assessed at the 6-week follow-up.; MET = Motivational Enhancement Therapy (experimental condition); TAU = Treatment as usual (comparison condition)

Intervention Efficacy

Treatment Uptake

In estimating treatment uptake efficacy Time × Condition effects were non-significant, indicating that there were no significant differences between the MET and TAU at either the 3- or 6-month follow-up (Table 3). Those with higher baseline CAPS-5 severity scores were slightly more likely to be treatment engaged at the 6-week follow-up (the referent timepoint for this model). Neither readiness-to-change variable significantly moderated the effect of MET on uptake. Approximately 12% of participants were treatment engaged by 6-month follow-up.

Table 3.

Effect of MET vs. TAU on primary outcomes of PTSD treatment engagement, PTSD severity, and PTSD diagnosis, including interactions with readiness to change (RTC)

	PTSD Treatment Engagement				PTSD Severity						PTSD Diagnosis
	Main Effects		Moderator Model		Main Effects			Moderator Model			Main Effects		Moderator Model
	AOR	95% C.I.	AOR	95% C.I.	b	SE	p	b	SE	p	AOR	95% C.I.	AOR	95% C.I.
Intercept	0.00	[0.00, 0.03]	0.00	[0.00,0.53]	12.31	(7.37)	.096	15.52	(9.30)	.096	0.00	[0.00,0.35]	0.00	[0.00, 0.868]
Age	1.00	[0.93, 1.06]	0.99	[0.93, 1.06]	−0.04	(0.13)	.725	−0.04	(0.13)	.723	1.00	[0.92, 1.09]	1.00	[0.91, 1.10]
Sex	1.49	[0.59, 3.76]	1.50	[0.58, 3.87]	3.95	(1.96)	.045	3.80	(1.97)	.055	3.69	[1.06,12.89]	4.25	[1.01,17.92]
Branch	1.65	[0.59, 4.62]	1.70	[0.59, 4.88]	2.94	(2.05)	.152	2.94	(2.04)	.151	2.72	[0.68, 10.93]	3.11	[0.64, 15.25]
Station	1.51	[0.64, 3.59]	1.56	[0.65, 3.78]	1.59	(1.75)	.365	1.52	(1.75)	.383	1.88	[0.65, 5.45]	1.89	[0.58, 6.13]
Active-Duty	1.29	[0.49, 3.40]	1.28	[0.48, 3.42]	−0.17	(1.77)	.925	−0.26	(1.78)	.883	1.04	[0.34, 3.23]	1.06	[0.30, 3.75]
Military Sexual Trauma	1.29	[0.39, 4.29]	1.33	[0.39,4.58]	3.36	(2.57)	.191	3.60	(2.57)	.163	2.96	[0.58, 15.16]	3.44	[0.53, 22.25]
# Combat Deployments	1.05	[0.32, 3.44]	1.12	[0.33,3.81]	0.61	(0.61)	.319	0.62	(0.61)	.310	1.18	[0.80, 1.74]	1.19	[0.78, 1.84]
BL Treatment Confidence	1.35	[0.70, 2.63]	1.33	[0.67, 2.65]	1.01	(1.39)	.468	1.06	(1.38)	.444	1.63	[0.68, 3.90]	1.78	[0.66, 4.83]
BL RTC Confidence	0.94	[0.74, 1.19]	0.84	[0.49, 1.44]	−0.59	(0.47)	.207	−0.56	(0.77)	.466	0.87	[0.63, 1.19]	0.65	[0.34, 1.26]
BL RTC Importance	1.39	[0.96, 2.01]	1.76	[0.69, 4.47]	2.35	(0.61)	<.001	1.86	(0.96)	.054	1.72	[1.10,2.67]	2.39	[1.02, 5.64]
BL CAPS Score	1.06	[1.01,1.12]	1.06	[1.01,1.12]	---	---	---
Main Effect of Time
BL	---		---		Referent			Referent			---		---
6-Week	Referent		Referent		---			---			---		---
3-Month	2.20	[0.76, 6.35]	1.57	[0, >100]	−8.86	(1.31)	<.001	−14.96	(7.22)	.039	Referent		Referent
6-Month	1.30	[0.45, 3.76]	5.34	[0, >100]	−10.94	(1.33)	<.001	−9.91	(7.16)	.167	0.60	[0.23, 1.55]	0.62	[0, >100]
Condition	0.80	[0.14,4.52]	4.12	[0, >100]	0.80	(1.81)	.657	−1.62	(10.51)	.878	1.21	[0.37, 3.90]	17.46	[0, >100]
Time × Condition
3-Month × Condition	0.69	[0.13, 3.67]	1.36	[0, >100]	−0.93	(1.90)	.623	5.23	(10.49)	.618	---		---
6-Month × Condition	1.07	[0.20, 5.76]	0.26	[0, >100]	−1.68	(2.04)	.410	−10.12	(10.49)	.335	0.62	[0.16,2.37]	0.01	[0, 76.96]
3-Way Interactions w/ RTC
3-Month × Condition × BL RTC-Confidence			1.17	[0.47, 2.87]				−0.15	(1.07)	.892
6-Month × Condition × BL RTC-Confidence			0.75	[0.29, 1.93]				2.46	(1.05)	.019			2.40	[0.91,6.35]
3-Month × Condition × BL RTC-Importance			0.81	[0.16,4.09]				−0.76	(1.35)	.573
6-Month × Condition × BL RTC-Importance			1.50	[0.29, 7.72]				−0.69	(1.35)	.612			0.90	[0.3, 2.68]

Note: Statistically significant effects (i.e., p < .05) are highlighted in bold text; BL=Baseline; RTC=Readiness to change

Codes: Sex (1=Female, 0=Male); Branch (1=Army, 0=Other); Station (1=JBLM, 0=Other); Active-duty (1=Yes, 0=No); MST (1=Yes, 0=No); Condition (1=MET, 0=TAU)

CAPS-5 Severity Score and PTSD Diagnoses.

In examining CAPS-5 severity scores, there were no statistically significant differences between the MET and TAU at either the 3- or 6-month follow-up, as shown by the Time × Condition effects (Table 3). The main effect for time indicated that participants, regardless of condition, had significantly lower CAPS-5 scores at 3- and 6-month follow-ups, relative to baseline. Participants with higher baseline perceived importance of change (i.e., readiness to change) had higher baseline CAPS-5 severity scores, on average, as did female participants relative to males. The moderation model, visualized in Figure 1, revealed a significant interaction effect with baseline readiness-to-change confidence (Table 3). Notably, those relatively low in readiness-to-change confidence at baseline saw a more favorable effect of MET (relative to TAU) at the 6-month follow-up. Simple slopes for this subgroup indicated a small but statistically significant effect of MET (p=.041), suggesting that for participants who entered the trial with relatively low confidence in their ability to address PTSD symptoms, MET significantly reduced CAPS-5 severity scores relative to TAU.

Fig 1.

Simple slopes from the 3-way interaction (Time × Condition × Baseline RTC Confidence) on CAPS Severity Scores. Lines indicate the effect of Condition at each of the three timepoints, and the left panel are participants low in baseline RTC confidence and the right panel are participants high in baseline RTC confidence. Bold indicates significant simple slopes effect. Note that simple slopes effect estimates are from pooled multiply imputed models, but this figure is derived from just one imputed dataset as plotting pooled effects is not possible.

For PTSD diagnosis, the model treats 3-month follow-up as the reference timepoint given that all participants met criteria at baseline. There was no statistically significant difference between the MET and TAU at 6-months, relative to the 3-month follow-up (Table 3). Participants with higher baseline readiness-to-change importance had greater odds of meeting PTSD diagnostic criteria at 3-month follow-up as did female participants relative to males. Neither readiness-to-change confidence or importance moderated the effect of MET.

Treatment Reactions

Across all four subscales of treatment reaction, there were no significant differences between the MET and TAU at follow-ups, as compared with baseline. Main effects of time indicated that participants felt more concern for debasement and more shame/embarrassment at the 6-week follow-up, relative to baseline. However, concern for debasement and shame/embarrassment appear to decline again across the 3- and 6-month follow-ups – indicating only a brief potential increase in these treatment reactions.

Discussion

Study findings demonstrate reductions in both PTSD and increases in treatment uptake from either a brief, telephone-delivered MET intervention or well-curated referrals for active service members with PTSD. However, contrary to our hypotheses, the MET intervention was only more effective than TAU for those with low confidence in their ability to change PTSD. Consistent with the Stages of Change model (Proachaska, Redding, & Evers, 1997), findings suggest MET would benefit and should be offered to individuals in lower Stages of Change but not to those whose motivation is already high. Overall, these results suggest both individual and system-level change may be necessary to overcome barriers in treatment uptake.

The Check-up model is relatively unique in that marketing and outreach is considered an active intervention component and way of engaging a treatment-naïve population by creating motivation for change. This outreach for a low-burden and confidential phone-based service had mixed success in attracting active-duty military personnel with PTSD. Recruitment on post using flyers, advertisements, and outreach efforts led to relatively low levels of engagement as compared to prior studies of Check-Up Models (Walker et al., 2017). This possibly could reflect the higher degree of stigma regarding PTS within the military or perceptions that some symptoms of PTS may be functional or adaptive (Britt et al., 2015; Graziano & Elbogen, 2017).

In contrast, once service members had engaged with study staff, they had very high rates of enrollment and retention with 97.6% of those who were eligible enrolling in the study and a first MET intervention session completion rate of 92.6% suggesting high acceptability of the intervention and high interest in participating in a “check-in” around treatment options. Satisfaction ratings around the intervention were also quite high. These high levels of engagement with the MET intervention suggest that phone-based and confidential interventions may be a viable means to reach out to individuals with PTSD, even those who are reluctant to engage in care. Results suggest both MET and high-quality referral options have promise as means of increasing evidence-based treatment uptake and decreasing PTSD for service members with PTSD, with referral being more cost-effective as a universal approach, and MET being indicated for those low in confidence around behavior change. As PTSD is associated with deleterious health, occupational and psychological effects, there is clear need for interventions to bridge the gap between those who are not treatment seeking and existing services, thereby enhancing reach and impact of existing services.

Contrary to our expectations, many service members were already in an evidence-based treatment program (50.2% of those excluded). Additionally, nearly four in five (79.5%) had previously engaged individual psychotherapy and nearly half (48.4%) had previously seen a psychiatrist to “address concerns related to a traumatic event.” These findings highlight that service members are actively attempting to address distress. This high degree of past treatment seeking may also reflect the access to PTSD treatment within the military and progress in reducing stigma and in creating opportunities for care. However, this also highlights that for a portion of service members, despite past efforts at help seeking, their PTSD symptoms remain in a clinical range. This, in turn, may be demoralizing or decrease motivation to change.

We did find a significant main effect for shame and debasement increasing from baseline to 6 week follow-up, although it decreased after that. This increase in shame and debasement did not appear to be an effect of either treatment arm and may instead reflect a reaction to the process of assessment. Assessments, whether in research or clinical settings, tend to be deficit and symptom focused, highlighting the symptoms of PTSD in particular. This may inadvertently highlight feelings of weakness or may build embarrassment regarding symptom severity. One direction for future research is to examine whether this is true in standard clinical settings and may help us understand dropouts from intake to treatment initiation. If so, intake assessments could be modified to incorporate more strengths based approaches.

Attracting a sample with high past treatment experience diverges from prior Check-Up studies focused on other target behaviors (Mbilinyi et al., 2022; Walker et al., 2017) and may have contributed to our lack of overall findings between interventions. Past treatment experience can be indicative of high readiness to change. For service members motivated to change their PTSD, either a MET or treatment referral list appear to increase treatment seeking and decrease PTSD symptoms. In contrast, the MET intervention may be particularly potent for those with lower confidence in their ability to change their PTSD. Future research should explore the role of motivation and confidence in changing and their role in pre-PTSD treatment MET interventions.

Addressing PTSD in a Check-Up intervention may require a different approach than with other health behaviors. Congressionally mandated screenings for mental health concerns have been implemented within the DoD with a goal of decreasing stigma and increasing access to treatment for service members with PTSD, but stigma regarding PTSD remains a barrier to treatment seeking (Lee et al., 2014). A peer-to-peer Check-Up model could serve to break down stigma and to increase engagement. Another option might be to offer a Check-Up intervention in opportunistic settings where individuals are screened for potential PTSD. This in particular, may be more effective in reaching individuals with lower readiness to change.

The study had several limitations. First, this study was not able to meet the original proposed sample size. We elected to end recruitment early due to the recruitment difficulties and because the study was adequately powered to detect a clinically meaningful effect. Due to difficulties with recruiting, this study also turned to a social media recruitment service to help with outreach. As mentioned, typically a Check-up intervention includes a marketing campaign as part of the intervention. Use of the social media service enhanced our ability to recruit and to reach a national audience, but it is unknown to what extent losing control of the marketing messages may have influenced who was attracted to the intervention. Our treatment as usual condition may have differed from TAU in other settings as TAU can include Behavioral Health proactively reaching out to an individual who is identified as “at risk” to schedule an appointment versus in this study where the ownness was on the individual to take the step of connecting with care. Our measure of receipt of an evidence-based psychotherapy deemphasized treatment name and more emphasized therapist behaviors (regular receipt of sessions, time spent focused on working directly on the trauma) as therapists are not always accurate in describing what therapy they have offered and may omit key treatment components (Hogue et al., 2015; Wilk et al., 2013).

In sum, both a brief telephone-based conversation regarding PTS symptoms or a detailed referral list with information about types of treatment options were associated with reductions in PTSD and increases in treatment seeking among active-duty service members. Both MET and high-quality referrals may be viable options in starting conversations with service members regarding treatment options. Moreover, the potential role of client self-efficacy and stage of change in treatment seeking and in PTSD treatment should be further explored as a potential indicator for MET interventions. Lastly, both MET and referral should be explored as ways to help facilitate treatment uptake in settings where service members may present for indicated treatment or prevention programs such as in primary care settings or following routine screenings. Given the high societal and individual cost associated with PTSD, the distress that symptoms cause those afflicted, and the difficulties with a leaky pipeline into effective care, it is critical that the field identify low burden, low-cost ways of helping facilitate treatment.

Clinical Impact Statement.

Study findings suggest that a motivational enhancement therapy (MET) “check-up” may benefit military personnel who have less confidence in their ability to change their PTSD. For those confident in their ability and ready to change, a curated referral resource was as effective as the intervention in both increasing treatment uptake and reducing PTSD. Both MET and referral are viable options to help facilitate treatment uptake for service members with untreated or inadequately treated PTSD. Readiness to change may be an important patient indicator of whether referral will be sufficient or whether a light touch clinician-guided intervention will be more helpful.