Proactive, Recovery-Oriented Treatment Navigation to Engage Racially Diverse Veterans in Mental Healthcare (PARTNER-MH), a Peer-Led Patient Navigation Intervention for Racially and Ethnically Minoritized Veterans in Veterans Health Administration Mental Health Services: Protocol for a Mixed Methods Randomized Controlled Feasibility Study
Bibliographic record
Abstract
BACKGROUND: Mental health care disparities are persistent and have increased in recent years. Compared with their White counterparts, members of racially and ethnically minoritized groups have less access to mental health care. Minoritized groups also have lower engagement in mental health treatment and are more likely to experience ineffective patient-provider communication, which contribute to negative mental health care experiences and poor mental health outcomes. Interventions that embrace recovery-oriented practices to support patient engagement and empower patients to participate in their mental health care and treatment decisions may help reduce mental health care disparities. Designed to achieve this goal, the Proactive, Recovery-Oriented Treatment Navigation to Engage Racially Diverse Veterans in Mental Healthcare (PARTNER-MH) is a peer-led patient navigation intervention that aims to engage minoritized patients in mental health treatment, support them to play a greater role in their care, and facilitate their participation in shared treatment decision-making. OBJECTIVE: The primary aim of this study is to assess the feasibility and acceptability of PARTNER-MH delivered to patients over 6 months. The second aim is to evaluate the preliminary effects of PARTNER-MH on patient activation, patient engagement, and shared decision-making. The third aim is to examine patient-perceived barriers to and facilitators of engagement in PARTNER-MH as well as contextual factors that may inhibit or promote the integration, sustainability, and scalability of PARTNER-MH using the Consolidated Framework for Implementation Research. METHODS: This pilot study evaluates the feasibility and acceptability of PARTNER-MH in a Veterans Health Administration (VHA) mental health setting using a mixed methods, randomized controlled trial study design. PARTNER-MH is tested under real-world conditions using certified VHA peer specialists (peers) selected through usual VHA hiring practices and assigned to the mental health service line. Peers provide PARTNER-MH and usual peer support services. The study compares the impact of PARTNER-MH versus a wait-list control group on patient activation, patient engagement, and shared decision-making as well as other patient-level outcomes. PARTNER-MH also examines organizational factors that could impact its future implementation in VHA settings. RESULTS: Participants (N=50) were Veterans who were mostly male (n=31, 62%) and self-identified as non-Hispanic (n=44, 88%) and Black (n=35, 70%) with a median age of 45 to 54 years. Most had at least some college education, and 32% (16/50) had completed ≥4 years of college. Randomization produced comparable groups in terms of characteristics and outcome measures at baseline, except for sex. CONCLUSIONS: Rather than simply documenting health disparities among vulnerable populations, PARTNER-MH offers opportunities to evaluate a tailored, culturally sensitive, system-based intervention to improve patient engagement and patient-provider communication in mental health care for racially and ethnically minoritized individuals. TRIAL REGISTRATION: ClinicalTrials.gov NCT04515771; https://clinicaltrials.gov/ct2/show/NCT04515771. INTERNATIONAL REGISTERED REPORT IDENTIFIER (IRRID): DERR1-10.2196/37712.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.014 | 0.014 |
| Meta-epidemiology (narrow) | 0.003 | 0.002 |
| Meta-epidemiology (broad) | 0.004 | 0.004 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.003 | 0.002 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.003 | 0.002 |
| Research integrity | 0.003 | 0.005 |
| Insufficient payload (model declined to judge) | 0.039 | 0.004 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".