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Abstract

Objective:

This study tested whether computerized cognitive-behavioral therapy for depression supported by a peer specialist with lived experience of depression (PS-cCBT) improves mental health–related outcomes for primary care patients.

Methods:

In the U.S. Department of Veterans Affairs, primary care patients with a new diagnosis of depression (N=330) were randomly assigned to 3 months of PS-cCBT or a usual-care control condition. Linear mixed-effects models were used to assess differences in depression symptoms, general mental health status, quality of life, and mental health recovery measured at baseline and 3 and 6 months.

Results:

In adjusted analyses, participants who received PS-cCBT experienced 1.4 points’ (95% confidence interval [CI]=0.3–2.5, p=0.01) greater improvement in depression symptoms on the Quick Inventory of Depression Symptomatology–Self Report at 3 months, compared with the control group, but no significant difference was noted at 6 months. PS-cCBT recipients also had 2.6 points’ (95% CI=0.5–4.8, p=0.02) greater improvement in quality of life at 3 months on the Quality of Life Enjoyment and Satisfaction Questionnaire Short Form and greater improvement in recovery on the Recovery Assessment Scale at 3 months (3.6 points; 95% CI=0.9–6.2, p=0.01) and 6 months (4.5 points; 95% CI=1.2–7.7, p=0.01).

Conclusions:

PS-cCBT is an effective option for improving short-term depression symptoms and longer-term recovery among primary care patients newly diagnosed as having depression.

HIGHLIGHTS

This study tested the effectiveness of computer-based cognitive-behavioral therapy supported by peer specialists with lived experience of depression (PS-cCBT).
The intervention was tested as an augmentation to usual primary care treatment of depression within the U.S. Department of Veterans Affairs health system.
At 3-month follow-up, PS-cCBT was modestly effective for improving depression symptoms, quality of life, and mental health recovery, compared with usual care.
PS-cCBT should be considered for implementation and evaluation in primary care, and adaptations to the computer CBT and peer support components should be considered to further improve effectiveness.
Depression affects nearly 7% of adults annually, and its prevalence is increasing in the United States (1). Depression treatment rates are low, and psychotherapy is underutilized relative to patients’ stated preferences for treatment (2, 3). Psychotherapist availability, costs, transportation difficulties, and discomfort discussing difficult issues may limit psychotherapy use (4, 5).
Computer-based psychotherapy has the potential to address many of the barriers to in-person treatment, given its relatively low marginal costs, accessibility, and privacy (6). Meta-analyses of data from randomized trials have demonstrated the effectiveness of computer-based cognitive-behavioral therapy (cCBT) for depression (79). Studies have also found that providing human support to individuals referred for cCBT results in greater engagement and increased effectiveness, compared with cCBT without human support (7, 10).
Mental health clinicians, technical support personnel, and volunteers have provided support for cCBT (9). Support of cCBT by peer specialists—individuals with mental health challenges who have been trained and employed to support others in their recovery—has not previously been studied. However, peer specialists may improve engagement in cCBT and complement its effectiveness by decreasing social isolation and sharing successful self-management strategies (11). In meta-analyses, peer support improved depression symptoms, compared with usual care (12, 13).
We conducted a randomized controlled trial to determine whether cCBT combined with peer support (PS-cCBT) improves outcomes relative to enhanced usual care (EUC) for primary care patients with depression in the Veterans Health Administration (VHA). In the VHA, primary care clinics have integrated mental health care providers who provide brief psychological, psychiatric, or care management services but do not typically offer cCBT or peer support for depression (14). We focused on primary care patients because they may have more limited access to full courses of evidence-based psychotherapy and peer support for depression, compared with specialty care patients. We hypothesized that PS-cCBT would result in greater reductions in depression symptoms and greater improvements in overall mental health status, quality of life, and mental health recovery.

Methods

Sites, Participant Selection, and Treatment Allocation

We conducted our study from 2015 to 2018 at three midwestern U.S. Department of Veterans Affairs (VA) medical centers and two of their associated outpatient clinics. The study received VA institutional review board approval from all three centers. We identified participants with a new diagnosis of depression and current depression symptoms by querying the electronic medical records database each week to return all patients diagnosed as having depression at a primary care encounter who had not received a depression diagnosis (in any VA setting) or specialty mental health treatment in the prior 4 months and did not have any diagnosis of bipolar disorder, primary psychotic disorder, or dementia in the prior 12 months. From this sample, we manually confirmed primary care documentation of active depression symptoms and excluded those with referrals to specialty mental health care and those who were receiving substance use disorder treatment. Individuals in the resulting sample were then screened by phone, and those eligible for the study had a score of ≥10 on the Patient Health Questionnaire–9 (PHQ-9), had basic skills for Internet and computer use (e.g., e-mail and online banking or shopping), and had no specialty mental health treatment outside the VA in the prior 4 months (15). Receipt of integrated primary care mental health treatment was not exclusionary.
Participants were randomly assigned by using a minimization algorithm designed to balance the two study arms with respect to number of participants, study site, participant gender, age ≥55, use of antidepressant medication, and initial PHQ-9 score of ≥15 (16).

Interventions

PS-cCBT participants continued to receive their usual primary or integrated care, which could include antidepressant medications or in-person psychotherapy. In addition, PS-cCBT participants received access to the online cCBT program Beating the Blues (BtB) for 3 months. BtB consists of eight CBT modules for depression and anxiety and includes video vignettes of program users, interactive assignments, and symptom self-monitoring with the PHQ-9.
Participants in the PS-cCBT arm also completed an initial in-person meeting (or a phone meeting if in person was not possible) with a peer support specialist. After this meeting, peers were expected to conduct approximately weekly phone calls and occasional in-person visits with participants to discuss progress and barriers to completing cCBT modules and to provide general peer support for managing depression. The peer specialists training consisted of a week-long certification training through the State of Michigan; the BtB program; and a 1-day study-specific training that addressed sharing one’s story related to depression, principles of motivational interviewing, and protocols for managing suicide risk. Peer specialists received weekly supervision by a clinical psychologist with prior experience supervising peers and had a peer-led monthly group consultation call (17).
Participants randomly assigned to EUC received The Depression Helpbook, a self-help depression workbook, in addition to their usual care (18). Participants randomly assigned to PS-cCBT also received this workbook.

Measures

Our primary study outcomes included depression symptoms, general mental health status, quality of life, and mental health recovery. Participants completed measures at baseline and at 3 months and 6 months postrandomization. Measures were collected by using Web-based surveys that participants self-administered via a tablet or through an e-mail link to the survey. In rare cases, the measures were administered verbally over the phone or by mailing hard copies. Study staff were not blinded to study arm. For each of the primary and secondary measures described below, higher scores indicate greater levels of the measured construct.
We measured depression symptoms with the Quick Inventory of Depression Symptomatology–Self Report (QIDS-SR) (possible scores range from 0 to 27) (19, 20) and general mental health status with the mental health component subscale (MCS) of the Veterans RAND 12-item Health Survey (VR-12) (21, 22) (scores are standardized to a mean of 50). We measured quality of life by using the Quality of Life Enjoyment and Satisfaction Questionnaire Short Form (Q-LES-Q-SF) (possible scores range from 14 to 70) (23) and recovery by using the Recovery Assessment Scale Short Form (RAS-SF) (possible scores range from 20 to 100) (24).
Secondary outcomes included CBT skills, which were measured by the 16-item Cognitive-Behavioral Therapy Skills Questionnaire (CBTSQ) (25) (possible scores range from 16 to 80). Anxiety was measured with the Generalized Anxiety Disorder seven-item scale (GAD-7) (26) (possible scores range from 0 to 21). Hope was measured with the six-item State Hope Scale (SHS) (27) (possible scores range from 6 to 48).
We measured usual care treatment from baseline to 6 months by using electronic medical records, examining any antidepressant medication prescription. Among antidepressant users, we measured antidepressant medication possession ratios (MPRs), which were defined as the number of days of antidepressant medication on hand divided by the 6-month observation period. We also measured receipt of any psychotherapy and number of psychotherapy sessions completed among psychotherapy recipients.
Patient characteristics measured at baseline via survey items included age, gender, race-ethnicity, marital status, income, education, employment, number of lifetime depressive episodes, age at first onset of depression, social support (via the Interpersonal Support Evaluation List [28]), and physical health (via the physical component subscale of the RAND VR-12) (21).
Participation in BtB was measured by the number of modules completed from the administrative dashboard of the computer program. The number of peer sessions completed was measured by peer documentation in participants’ medical records.

Analyses

To assess balance between treatment arms, we evaluated participants’ baseline characteristics, including the primary outcomes, by arm. We used an intent-to-treat approach and included all participants in their randomly assigned group, regardless of patient adherence to the intervention components. We conducted unadjusted comparisons between treatment arms for the primary and secondary outcomes at 3 and 6 months. We also dichotomized depression symptom improvement as both response, defined as a 50% reduction in QIDS-SR score from baseline to follow-up, and remission, defined as a QIDS-SR score of ≤5 at follow-up. We then compared response and remission rates by arm at 3 and 6 months by using chi-square tests and calculated the number needed to treat (NNT) for significant differences (29).
Our analytic goal was to estimate intervention effects at 3 and 6 months. For the primary outcomes, main analyses consisted of longitudinal linear mixed-effects models with the outcomes data at baseline, 3 months, and 6 months as response variables and with participants as random intercepts. For each outcome model, primary predictors were treatment arm, treatment site, and categorical indicators for 3 and 6 months. We used interaction terms of study arm × 3-month time and study arm × 6-month time to estimate the between-group mean differences at 3 and at 6 months, respectively. The following baseline characteristics found to be associated with follow-up completion or depression at 3 months were also included as covariates: gender, race-ethnicity, education, social support, physical health, lifetime number of depressive episodes, and age at first onset of depression.
For participants assigned to the intervention arm, we used simple regression models to assess whether number of peer specialist encounters or number of BtB modules completed predicted improvement in the primary outcomes at 3 and 6 months. We similarly evaluated the association between peer encounters and cCBT modules completed and the association between cCBT modules completed and CBT skills at 3 and 6 months. We also compared primary outcomes among those who completed five or more cCBT modules (our threshold for adequate treatment) versus those who completed fewer than five. Analyses used SAS software, version 9.4, and SAS Enterprise Guide, version 7.15.

Results

Participants

Of the 11,337 patients with a new depression diagnosis at participating sites, 2,614 were eligible for phone screening, and 163 were randomly assigned to EUC and 167 to PS-cCBT (see online supplement to this article for a CONSORT diagram). Table 1 presents the sample characteristics for the 330 participants. The mean age was 52 years, 80% were male, 71% were white, 21% were black, and 9% were of another race or were missing race data. Compared with EUC participants, a greater proportion of PS-cCBT participants had completed some college (49% versus 40%) and a smaller proportion had an education of high school or less (13% versus 23%).
TABLE 1. Baseline characteristics of veterans with a new diagnosis of depression randomly assigned to enhanced usual care (EUC) or peer-supported computer-based cognitive-behavioral therapy (PS-cCBT)
 EUC (N=163)PS-cCBT (N=167) Total (N=330)
CharacteristicN%N%paN%
Sociodemographic       
 Age (M±SD)51.7±15.5 51.6±14.4 .9051.6±14.9 
 Male1348213178.3926580
 Race    .70  
  White1197311569 23471
  Black31193722 6821
  Other or missing data138159 289
 Hispanic3264.5093
 Education    .04  
  High school or less37232113 5818
  Some college64408249 14645
  College graduate61386338 12438
 Married or lives with significant other92579356.8918556
 Working full- or part-time73457344.8414645
 Income <$25,00058366740.4712538
 Lives alone33203521.876821
Depression history       
 Age at first depressive episode (M±SD)30.9±16.8 30.0±15.9 .7530.4±16.4 
 Lifetime depressive episodes (M±SD)5.8±10.0 6.5±11.8 .846.1±10.9 
Study measures (scores)       
 QIDS-SR (M±SD)b13.4±3.6 14.0±3.9 .1813.7±3.8 
 MCS (M±SD)c32.1±9.9 31.4±9.7 .4531.7±9.8 
 Q-LES-Q (M±SD)d38.8±8.7 37.7±8.3 .2538.2±8.5 
 RAS (M±SD)e69.3±9.7 67.1±11.1 .0968.2±10.5 
a
Chi-square tests for categorical variables; Wilcoxon rank-sum tests for continuous variables.
b
Quick Inventory of Depressive Symptomatology–Self Report. Possible scores range from 0 to 27, with higher scores indicating greater depression symptom severity.
c
Mental health component subscale of Veterans Rand 12-item Health Survey. A score of 50 represents the general population mean, with higher scores indicating better mental health.
d
Quality of Life Enjoyment and Satisfaction Questionnaire–Short Form. Possible scores range from 14 to 70, with higher scores indicating greater quality of life.
e
Recovery Assessment Scale. Possible scores range from 20 to 100, with higher scores indicating greater recovery.

Participation in Study Activities

Among the 330 patients randomly assigned, follow-up assessment completion rates were 72% (N=236) at 3 months and 66% (N=219) at 6 months. The following groups were more likely to complete the 6-month assessments: EUC participants; female participants; and those with lower incomes (specifically $15,000–$25,000 versus $25,000–$50,000 annual income), more lifetime depressive episodes, and later onset of their first depressive episode.
Participants assigned to PS-cCBT completed a mean±SD of 3.2±2.8 contacts with a peer support specialist, including 83% by phone, 14% in-person at a VA clinic site, and 3% in the community or an undetermined location. They completed a mean of 3.8±3.0 and a median of three of the eight computerized CBT modules, and 40% (N=67) completed five or more modules.

Primary Outcomes

In primary longitudinal adjusted analyses of depression symptoms (QIDS-SR), the intervention group × time interaction was statistically significant at 3 months, indicating that PS-cCBT patients had 1.4 points (95% confidence interval [CI]=0.3–2.5, p=0.01) greater improvement in depression symptoms, compared with EUC patients. No between-arm difference in depression symptoms was found at 6 months. Similarly, PS-cCBT patients had a 2.6-point (95% CI=0.5–4.8, p=0.02) greater increase in quality of life (Q-LES-Q-SF) at 3 months, compared with EUC patients, but the difference was not significant at 6 months. No significant differences between groups were found for general mental health status (VR-12 MCS) at 3 months (2.2 points) or 6 months (3.3 points). We found greater improvements in mental health recovery (RAS) in the PS-cCBT group at 3 months (3.6 points; 95% CI=0.9–6.2, p=0.01) and at 6 months (4.5 points; 95% CI=1.2–7.7, p=0.01), compared with the EUC group.
In unadjusted analyses, we found no statistically significant differences in scale scores between treatment arms at 3 or 6 months for any of the primary outcomes (Table 2). However, we found response rates (a 50% reduction in depression symptoms from baseline) at 3 months to be 20.0% in the PS-cCBT group, compared with 6.4% for EUC (p=0.002, NNT=7.3); at 6 months, response rates were 25.3% and 16.4% (p=0.11), respectively (Figure 1). At 3 months, we found remission rates (QIDS-SR score ≤5) of 14.0% for PS-cCBT participants and 6.3% for EUC participants (p=0.046, NNT=13.0); at 6 months, remission rates were 21.8% and 11.0% (p=0.03, NNT=9.3), respectively.
TABLE 2. Outcome measures for veterans with a new diagnosis of depression randomly assigned to enhanced usual care (EUC) or peer-supported computer-based cognitive-behavioral therapy (PS-cCBT)
 Baseline3 months6 months
 EUC (N=163)PS-cCBT (N=167)EUC (N=128)PS-cCBT (N=108)EUC (N=118)PS-cCBT (N=101)
Outcome measureMSDMSDpMSDMSDpMSDMSDp
Primary               
 QIDS-SRa13.43.614.03.9.1811.74.111.14.7.3611.24.410.65.1.43
 MCSb32.19.931.49.7.4536.210.337.311.5.4437.111.040.112.2.08
 Q-LES-Qc38.88.737.78.3.2540.59.941.69.9.4841.010.442.510.7.40
 RASd69.39.767.111.1.0971.710.572.613.7.4071.111.774.114.6.06
Secondary               
 CBT-SQe42.410.240.411.0.1845.110.746.112.6.4045.910.848.014.3.27
 GAD-7f11.34.711.04.3.679.54.88.85.1.279.35.18.15.2.08
 SHSg26.77.924.98.3.0427.98.728.09.7.8528.59.428.29.8.94
 N%N%pN%N%pN%N%p
Other treatment use               
 Any antidepressant medicationh70437646.6488549255.8497609758.79
 Any in-person psychotherapyh,i     56346237.6064396740.87
a
Quick Inventory of Depressive Symptomatology–Self Report. Possible scores range from 0 to 27, with higher scores indicating greater depression symptom severity.
b
Mental health component subscale of Veterans Rand 12-item Health Survey. A score of 50 represents the general population mean, with higher scores indicating greater mental health.
c
Quality of Life Enjoyment and Satisfaction Questionnaire–Short Form. Possible scores range from 14 to 70, with higher scores indicating greater quality of life.
d
Recovery Assessment Scale. Possible scores range from 20 to 100, with higher scores indicating greater recovery.
e
Cognitive-Behavioral Therapy Skills Questionnaire. Possible scores range from 16 to 80, with higher scores indicating greater skills.
f
Generalized Anxiety Disorder seven-item scale. Possible scores range from 0 to 21, with higher scores indicating more severe anxiety symptoms.
g
State Hope Scale. Possible scores range from 6 to 48, with higher scores indicating greater hope.
h
Percentages reflect total Ns at baseline (data obtained from medical records).
i
Not measured at baseline.
FIGURE 1. Depression symptom response and remission rates among veterans enrolled in enhanced usual care (EUC) and peer-supported computer-based cognitive-behavioral therapy (PS-cCBT)

Secondary Outcomes

We found no difference between study arms with respect to anxiety, hope, or CBT skills at 3 or 6 months (Table 2). At 6 months, no differences were noted in any antidepressant use or MPRs (MPR=0.81 for EUC versus 0.80 for PS-cCBT), in receipt of any psychotherapy, or mean number of sessions among psychotherapy recipients (1.7 for EUC versus 1.6 for PS-cCBT).

Intervention Subgroup Analyses

Among participants assigned to the PS-cCBT arm, no association was found between the number of peer encounters completed and any of the primary outcomes at 3 or 6 months. Peer encounters were positively associated with the number of cCBT modules completed (b=0.46, p<0.001). The number of cCBT modules completed was not associated with improvement in any of the primary outcomes or CBT skills at 3 months but was associated with improvement in MCS (b=1.1, p=0.03) and RAS (b=1.3, p<0.01) scores at 6 months. Compared with those who completed fewer than five cCBT modules, those who completed five or more experienced less severe depression symptoms (QIDS-SR score, 10.1 versus 12.4; p=0.01) and greater quality of life (Q-LES-Q score, 43.3 versus 39.1; p=0.03) at 3 months. At 6 months, those who completed five or more modules reported fewer depression symptoms (QIDS-SR score, 9.6 versus 12.1; p=0.01), greater quality of life (Q-LES-Q score, 44.5 versus 39.8; p=0.03), greater general mental health status (MCS score, 42.8 versus 36.4; p<0.01), and greater recovery (RAS score, 77.4 versus 69.7; p<0.01), compared with those who completed fewer modules. We did not find a statistically significant difference in CBT skills between those who did and those who did not complete at least five cCBT modules at either 3 or 6 months.

Discussion

We found that PS-cCBT as an enhancement to usual primary care treatment for depression was associated with greater improvements in depression symptoms, quality of life, and mental health recovery at 3 months, compared with usual care alone. Improvements in mental health recovery, although not the other outcomes, were sustained up to 6 months. Although statistically significant, the clinical significance of these effects is modest. The intervention was associated with an estimated 1.4-point greater improvement on the 27-point QIDS-SR scale at 3 months, compared with usual depression care; a 4-point change is a conservative threshold for clinically significant changes in functioning (30).
Traditional measures of response and remission showed similar statistically significant but modest effects. For depression symptom response at 3 months, the intervention was superior to usual depression care, with an NNT for response of 7.3, and the NNT for depression remission was 13.0. The NNTs for depression response for widely adopted practices, such as antidepressant medications (compared with placebo) or traditional CBT combined with medication (compared with monotherapy), are estimated to be between 3 and 5 (29). The more modest benefits we found with PS-cCBT should be considered in the context that over 50% of participants also received antidepressant medication with high levels of adherence and over 30% received some in-person psychotherapy. In contrast to our adjusted analyses, in unadjusted comparisons we found no significant difference across any of the primary outcomes, suggesting that it was necessary to account for other sources of variance (e.g., baseline scores, gender, race-ethnicity, and education) in order to detect differences by treatment arm.
Our findings are consistent with meta-analyses showing that patients in primary care treatment benefit less from cCBT than do broader participant samples (e.g., those recruited from the Internet) (9). It has been speculated that greater depression severity or comorbid conditions among primary care populations may contribute to this finding (9).
Although our study did not test the effect of peer support on cCBT engagement, participation in both components were correlated. PS-cCBT participants also completed a median of three cCBT modules, compared with two in a United Kingdom trial of BtB, which provided technical support rather than peer support (31). These differences could be the result of differences in the study populations, their usual care, or research protocols; however, our findings suggest that peers may be modestly effective at improving patient engagement in cCBT, compared with technical support or, presumably, no support.
Generalizability of our findings is limited by high rates of ineligibility and refusal among patients diagnosed as having depression. The participants who completed follow-up assessments may also not be representative of all participants who enrolled, and differential follow-up rates between the arms could have biased the findings toward an intervention effect. Reduced statistical power from lower follow-up rates may also have biased some findings toward the null. The high rate of refusals and lower follow-up rate in the intervention arm versus control group also suggest limited acceptability of the intervention as an augmentation to patients’ current depression treatment. The study population of primarily male veterans and the treatment setting, which includes integrated mental health care and access to specialty mental health care, may also limit generalizability to populations outside the VA. The study population also had substantial impairment in mental health–related quality of life, according the VR-12 MCS scores. Although these scores are consistent with those found in prior studies of VA patients receiving specialty mental health services, they may represent greater impairment than experienced by other populations of primary care patients with depression (32, 33).

Conclusions

PS-cCBT should be considered as an initial treatment enhancement to improve effectiveness of primary care treatment of depression. Although PS-cCBT appears to improve several depression-related outcomes, implementation in the VA will require local, regional, or national VA leaders to license (or build) a cCBT program for clinical use and extend the VA’s existing peer specialist workforce to include supporting cCBT in primary care. Implementation outside the VA is likely to face additional challenges, particularly in insured populations where cCBT or peer support are not covered services. In addition to addressing implementation barriers, future work should prioritize improving engagement and effectiveness of PS-cCBT, such as by tailoring the cCBT program to individual patients, incorporating mobile device features, involving primary care providers, intentionally matching patients to peers, and conducting more rigorous monitoring (e.g., audio-recorded sessions) and provision of feedback to the peer specialists.

Supplementary Material

File (appi.ps.201900283.ds001.pdf)

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Pages: 256 - 262
PubMed: 31931686

History

Received: 3 June 2019
Revision received: 7 August 2019
Accepted: 6 September 2019
Published online: 14 January 2020
Published in print: March 01, 2020

Keywords

  1. Depression
  2. Cognitive therapy

Authors

Details

Paul N. Pfeiffer, M.D. [email protected]
U.S. Department of Veterans Affairs (VA) Ann Arbor Healthcare System, Ann Arbor, Michigan (Pfeiffer, Zivin, Ganoczy, Kim, Walters, Emerson, Nelson, Abraham, Valenstein); Department of Psychiatry, University of Michigan Medical School, Ann Arbor (Pfeiffer, Zivin, Walters, Emerson, Nelson, Valenstein); Battle Creek VA Medical Center, Battle Creek, Michigan (Pope, Houck); John D. Dingell VA Medical Center, Detroit (Benn-Burton); Consulting for Statistics, Computing and Analytics Research, University of Michigan, Ann Arbor (Kim); Department of Psychology, University of Detroit Mercy, Detroit (Abraham).
Brooke Pope, Ph.D.
U.S. Department of Veterans Affairs (VA) Ann Arbor Healthcare System, Ann Arbor, Michigan (Pfeiffer, Zivin, Ganoczy, Kim, Walters, Emerson, Nelson, Abraham, Valenstein); Department of Psychiatry, University of Michigan Medical School, Ann Arbor (Pfeiffer, Zivin, Walters, Emerson, Nelson, Valenstein); Battle Creek VA Medical Center, Battle Creek, Michigan (Pope, Houck); John D. Dingell VA Medical Center, Detroit (Benn-Burton); Consulting for Statistics, Computing and Analytics Research, University of Michigan, Ann Arbor (Kim); Department of Psychology, University of Detroit Mercy, Detroit (Abraham).
Marc Houck, Psy.D.
U.S. Department of Veterans Affairs (VA) Ann Arbor Healthcare System, Ann Arbor, Michigan (Pfeiffer, Zivin, Ganoczy, Kim, Walters, Emerson, Nelson, Abraham, Valenstein); Department of Psychiatry, University of Michigan Medical School, Ann Arbor (Pfeiffer, Zivin, Walters, Emerson, Nelson, Valenstein); Battle Creek VA Medical Center, Battle Creek, Michigan (Pope, Houck); John D. Dingell VA Medical Center, Detroit (Benn-Burton); Consulting for Statistics, Computing and Analytics Research, University of Michigan, Ann Arbor (Kim); Department of Psychology, University of Detroit Mercy, Detroit (Abraham).
Wendy Benn-Burton, Ph.D.
U.S. Department of Veterans Affairs (VA) Ann Arbor Healthcare System, Ann Arbor, Michigan (Pfeiffer, Zivin, Ganoczy, Kim, Walters, Emerson, Nelson, Abraham, Valenstein); Department of Psychiatry, University of Michigan Medical School, Ann Arbor (Pfeiffer, Zivin, Walters, Emerson, Nelson, Valenstein); Battle Creek VA Medical Center, Battle Creek, Michigan (Pope, Houck); John D. Dingell VA Medical Center, Detroit (Benn-Burton); Consulting for Statistics, Computing and Analytics Research, University of Michigan, Ann Arbor (Kim); Department of Psychology, University of Detroit Mercy, Detroit (Abraham).
Kara Zivin, Ph.D.
U.S. Department of Veterans Affairs (VA) Ann Arbor Healthcare System, Ann Arbor, Michigan (Pfeiffer, Zivin, Ganoczy, Kim, Walters, Emerson, Nelson, Abraham, Valenstein); Department of Psychiatry, University of Michigan Medical School, Ann Arbor (Pfeiffer, Zivin, Walters, Emerson, Nelson, Valenstein); Battle Creek VA Medical Center, Battle Creek, Michigan (Pope, Houck); John D. Dingell VA Medical Center, Detroit (Benn-Burton); Consulting for Statistics, Computing and Analytics Research, University of Michigan, Ann Arbor (Kim); Department of Psychology, University of Detroit Mercy, Detroit (Abraham).
Dara Ganoczy, M.P.H.
U.S. Department of Veterans Affairs (VA) Ann Arbor Healthcare System, Ann Arbor, Michigan (Pfeiffer, Zivin, Ganoczy, Kim, Walters, Emerson, Nelson, Abraham, Valenstein); Department of Psychiatry, University of Michigan Medical School, Ann Arbor (Pfeiffer, Zivin, Walters, Emerson, Nelson, Valenstein); Battle Creek VA Medical Center, Battle Creek, Michigan (Pope, Houck); John D. Dingell VA Medical Center, Detroit (Benn-Burton); Consulting for Statistics, Computing and Analytics Research, University of Michigan, Ann Arbor (Kim); Department of Psychology, University of Detroit Mercy, Detroit (Abraham).
H. Myra Kim, Sc.D.
U.S. Department of Veterans Affairs (VA) Ann Arbor Healthcare System, Ann Arbor, Michigan (Pfeiffer, Zivin, Ganoczy, Kim, Walters, Emerson, Nelson, Abraham, Valenstein); Department of Psychiatry, University of Michigan Medical School, Ann Arbor (Pfeiffer, Zivin, Walters, Emerson, Nelson, Valenstein); Battle Creek VA Medical Center, Battle Creek, Michigan (Pope, Houck); John D. Dingell VA Medical Center, Detroit (Benn-Burton); Consulting for Statistics, Computing and Analytics Research, University of Michigan, Ann Arbor (Kim); Department of Psychology, University of Detroit Mercy, Detroit (Abraham).
Heather Walters, M.A.
U.S. Department of Veterans Affairs (VA) Ann Arbor Healthcare System, Ann Arbor, Michigan (Pfeiffer, Zivin, Ganoczy, Kim, Walters, Emerson, Nelson, Abraham, Valenstein); Department of Psychiatry, University of Michigan Medical School, Ann Arbor (Pfeiffer, Zivin, Walters, Emerson, Nelson, Valenstein); Battle Creek VA Medical Center, Battle Creek, Michigan (Pope, Houck); John D. Dingell VA Medical Center, Detroit (Benn-Burton); Consulting for Statistics, Computing and Analytics Research, University of Michigan, Ann Arbor (Kim); Department of Psychology, University of Detroit Mercy, Detroit (Abraham).
Lauren Emerson, M.A.
U.S. Department of Veterans Affairs (VA) Ann Arbor Healthcare System, Ann Arbor, Michigan (Pfeiffer, Zivin, Ganoczy, Kim, Walters, Emerson, Nelson, Abraham, Valenstein); Department of Psychiatry, University of Michigan Medical School, Ann Arbor (Pfeiffer, Zivin, Walters, Emerson, Nelson, Valenstein); Battle Creek VA Medical Center, Battle Creek, Michigan (Pope, Houck); John D. Dingell VA Medical Center, Detroit (Benn-Burton); Consulting for Statistics, Computing and Analytics Research, University of Michigan, Ann Arbor (Kim); Department of Psychology, University of Detroit Mercy, Detroit (Abraham).
C. Beau Nelson, Ph.D.
U.S. Department of Veterans Affairs (VA) Ann Arbor Healthcare System, Ann Arbor, Michigan (Pfeiffer, Zivin, Ganoczy, Kim, Walters, Emerson, Nelson, Abraham, Valenstein); Department of Psychiatry, University of Michigan Medical School, Ann Arbor (Pfeiffer, Zivin, Walters, Emerson, Nelson, Valenstein); Battle Creek VA Medical Center, Battle Creek, Michigan (Pope, Houck); John D. Dingell VA Medical Center, Detroit (Benn-Burton); Consulting for Statistics, Computing and Analytics Research, University of Michigan, Ann Arbor (Kim); Department of Psychology, University of Detroit Mercy, Detroit (Abraham).
Kristen M. Abraham, Ph.D.
U.S. Department of Veterans Affairs (VA) Ann Arbor Healthcare System, Ann Arbor, Michigan (Pfeiffer, Zivin, Ganoczy, Kim, Walters, Emerson, Nelson, Abraham, Valenstein); Department of Psychiatry, University of Michigan Medical School, Ann Arbor (Pfeiffer, Zivin, Walters, Emerson, Nelson, Valenstein); Battle Creek VA Medical Center, Battle Creek, Michigan (Pope, Houck); John D. Dingell VA Medical Center, Detroit (Benn-Burton); Consulting for Statistics, Computing and Analytics Research, University of Michigan, Ann Arbor (Kim); Department of Psychology, University of Detroit Mercy, Detroit (Abraham).
Marcia Valenstein, M.D.
U.S. Department of Veterans Affairs (VA) Ann Arbor Healthcare System, Ann Arbor, Michigan (Pfeiffer, Zivin, Ganoczy, Kim, Walters, Emerson, Nelson, Abraham, Valenstein); Department of Psychiatry, University of Michigan Medical School, Ann Arbor (Pfeiffer, Zivin, Walters, Emerson, Nelson, Valenstein); Battle Creek VA Medical Center, Battle Creek, Michigan (Pope, Houck); John D. Dingell VA Medical Center, Detroit (Benn-Burton); Consulting for Statistics, Computing and Analytics Research, University of Michigan, Ann Arbor (Kim); Department of Psychology, University of Detroit Mercy, Detroit (Abraham).

Notes

Send correspondence to Dr. Pfeiffer ([email protected]).

Competing Interests

The authors report no financial relationships with commercial interests.

Funding Information

This work was supported by VA Health Services Research and Development grant IIR-13-310. The study is registered at clinicaltrials.gov (NCT02057042).

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