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Record W4295682060 · doi:10.1080/09687637.2022.2114879

Developing a realist theory of community-based residential substance use treatment

2022· article· en· W4295682060 on OpenAlexaffabout
Christina Mutschler, Heather Haines, Kelly McShane, Michael Lochran, Laura Bhoi

Bibliographic record

VenueDrugs Education Prevention and Policy · 2022
Typearticle
Languageen
FieldHealth Professions
TopicHealth Policy Implementation Science
Canadian institutionsToronto Metropolitan University
Fundersnot available
KeywordsThematic analysisContext (archaeology)Agency (philosophy)Qualitative researchSubstance usePsychologyDiversity (politics)Medical educationSociologyMedicineClinical psychology

Abstract

fetched live from OpenAlex

Community-based residential treatments for substance use disorders (SUDs) have mixed effectiveness, which has been hypothesized to be due to the variability of program offerings across treatments. Therefore, the purpose of the present study was to develop a realist program theory of a community-based residential treatment centre to understand which components of treatment are most effective, who benefits from treatment, and why. The study was completed in collaboration with a community-based residential treatment program located in Canada. A realist evaluation was conducted using qualitative interviews (N = 27) with program stakeholders. Transcripts were analyzed using thematic analysis to identify Context-Mechanism-Outcome (CMO) configurations that create the program theory. The analysis identified an overarching organizational context and 11 CMO configurations that comprise the program theory. The CMOs were grouped into three themes (i.e. relational, psychological, and diversity), underscoring the multiple pathways in which recovery is achieved for individuals with SUDs. Across the themes, the importance of building peer recovery relationships, creating structure, and inter-agency collaborations were highlighted. The results of the present study offer a contribution to the literature in understanding how, why, and for whom community-based residential treatment for SUDs is effective while offering specific recommendations to best tailor treatments to individuals.

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)0.003
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesScience and technology studies
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.670
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0030.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0020.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.495
GPT teacher head0.628
Teacher spread0.132 · 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 designTheoretical or conceptual
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

Citations2
Published2022
Admission routes2
Has abstractyes

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