The Transitions Clinic Network: Post Incarceration Addiction Treatment, Healthcare, and Social Support (TCN-PATHS): A hybrid type-1 effectiveness trial of enhanced primary care to improve opioid use disorder treatment outcomes following release from jail
Bibliographic record
Abstract
BACKGROUND: In 2016, at least 20% of people with opioid use disorder (OUD) were involved in the criminal justice system, with the majority of individuals cycling through jails. Opioid overdose is the leading cause of death and a common cause of morbidity after release from incarceration. Medications for OUD (MOUD) are effective at reducing overdoses, but few interventions have successfully engaged and retained individuals after release from incarceration in treatment. OBJECTIVE: To assess whether follow-up care in the Transitions Clinic Network (TCN), which provides OUD treatment and enhanced primary care for people released from incarceration, improves key measures in the opioid treatment cascade after release from jail. In TCN programs, primary care teams include a community health worker with a history of incarceration, and they attend to social needs, such as housing, food insecurity, and criminal legal system contact, along with patients' medical needs. METHODS AND ANALYSIS: We will bring together six correctional systems and community health centers with TCN programs to conduct a hybrid type-1 effectiveness/implementation study among individuals who were released from jail on MOUD. We will randomize 800 individuals on MOUD released from seven local jails (Bridgeport, CT; Niantic, CT; Bronx, NY; Caguas, PR; Durham, NC; Minneapolis, MN; Ontario County, NY) to compare the effectiveness of a TCN intervention versus referral to standard primary care to improve measures within the opioid treatment cascade. We will also determine what social determinants of health are mediating any observed associations between assignment to the TCN program and opioid treatment cascade measures. Last, we will study the cost effectiveness of the approach, as well as individual, organizational, and policy-level barriers and facilitators to successfully transitioning individuals on MOUD from jail to the TCN. ETHICS AND DISSEMINATION: Investigation Review Board the University of North Carolina (IRB Study # 19-1713), the Office of Human Research Protections, and the NIDA JCOIN Data Safety Monitoring Board approved the study. We will disseminate study findings through peer-reviewed publications and academic and community presentations. We will disseminate study data through a web-based platform designed to share data with TCN PATHS participants and other TCN stakeholders. Clinical trials.gov registration: NCT04309565.
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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 | 0.003 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.002 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.002 | 0.004 |
| Insufficient payload (model declined to judge) | 0.009 | 0.001 |
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".