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Record W3128518631 · doi:10.1016/j.jsat.2021.108315

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

2021· article· en· W3128518631 on OpenAlexaboutno aff
Benjamin A. Howell, Lisa B. Puglisi, Katie Clark, Carmen E. Albizu‐García, Evan Ashkin, Tyler Booth, Lauren Brinkley‐Rubinstein, David A. Fiellin, Aaron D. Fox, Kathleen Maurer, Hsiu‐Ju Lin, Kathryn E. McCollister, Sean M. Murphy, Diane S. Morse, Shira Shavit, Karen Wang, Tyler N. A. Winkelman, Emily A. Wang

Bibliographic record

VenueJournal of Substance Abuse Treatment · 2021
Typearticle
Languageen
FieldMedicine
TopicOpioid Use Disorder Treatment
Canadian institutionsnot available
FundersNational Center for Advancing Translational SciencesNational Institute on Drug AbuseNational Institutes of Health
KeywordsOpioid use disorderPsychiatryMedicinePsychological interventionAddictionOpiate Substitution TreatmentCriminal justiceOpioidOpioid overdoseBuprenorphinePsychologyCriminologyInternal medicine

Abstract

fetched live from OpenAlex

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.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.416
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0000.000
Science and technology studies0.0010.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.018
GPT teacher head0.300
Teacher spread0.282 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

Study designObservational
Domainnot available
GenreEmpirical

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".

Quick stats

Citations53
Published2021
Admission routes1
Has abstractyes

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