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The Need to Move from Describing to Evaluating the Effectiveness of Indigenous Drug and Alcohol Residential Rehabilitation Services: A Systematic Review

2018· review· en· W2795863736 on OpenAlexaboutno aff
Doug James, Anthony Shakeshaft, Alice Munro, Ryan J. Courtney

Bibliographic record

VenueCurrent Drug Abuse Reviews · 2018
Typereview
Languageen
FieldSocial Sciences
TopicIndigenous Health, Education, and Rights
Canadian institutionsnot available
Fundersnot available
KeywordsIndigenousRehabilitationAlcoholMedicinePsychologyPhysical therapy

Abstract

fetched live from OpenAlex

BACKGROUND AND OBJECTIVES: Despite the importance of Indigenous drug and alcohol residential rehabilitation, the knowledge supporting these services is limited. This paper aims to: (i) identify the research output related to Indigenous drug and alcohol residential rehabilitation services; (ii) classify identified studies according to their methodology; and (iii) describe key characteristics of clients and services, and critique the research methods. METHODS: A PRISMA compliant search of 10 electronic databases for studies of Indigenous drug and alcohol residential rehabilitation services from Australia, United States, Canada and New Zealand, published between 1 January 2000 and 28 March 2016, was conducted. RESULTS: Of the 38 relevant studies, 20 were service descriptions, one was a thesis, 16 described treatment or client characteristics and one was a pre/post evaluation. No systematic reviews or the development or evaluation of measures was identified, with reviewed studies found to be of relatively low methodological quality. CONCLUSION: There are few published studies on Indigenous drug and alcohol residential rehabilitation services, an average of one paper per annum internationally, and only one treatment outcome evaluation. Three key features of the reviewed papers included (i) studied services were mostly located in regional areas; (ii) services provided multi-component programs, with little alignment between the models of care of other services; and (iii) the majority used qualitative, rather than quantitative methods. Client outcomes will likely improve if future research can establish best-practice, culturally acceptable models of care and increase the application of evidence-based, culturally validated quantitative evaluation measures to complement existing qualitative research.

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 machine prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.182
metaresearch head score (Gemma)0.451
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Systematic review · Consensus signal: Systematic review
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.182
Threshold uncertainty score0.962

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.1820.451
Meta-epidemiology (narrow)0.0020.003
Meta-epidemiology (broad)0.0170.011
Bibliometrics0.0200.018
Science and technology studies0.0020.005
Scholarly communication0.0140.021
Open science0.0060.005
Research integrity0.0070.008
Insufficient payload (model declined to judge)0.0070.001

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.

Opus teacher head0.080
GPT teacher head0.422
Teacher spread0.342 · 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 source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designSystematic review
Domainnot available
GenreReview

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

Citations19
Published2018
Admission routes1
Has abstractyes

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