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Record W2784601547 · doi:10.5014/ajot.2018.022863

Interventions for Women With Substance Abuse Issues: A Scoping Review

2018· review· en· W2784601547 on OpenAlexaff
Alison Leppard, Margaret Ramsay, Andrea Duncan, Cindy Malachowski, Jane A. Davis

Bibliographic record

VenueAmerican Journal of Occupational Therapy · 2018
Typereview
Languageen
FieldMedicine
TopicSubstance Abuse Treatment and Outcomes
Canadian institutionsOntario Tech University3M (Canada)University of WaterlooUniversity of Toronto
Fundersnot available
KeywordsPsychological interventionInclusion (mineral)Substance abuseHarmCategorical variableHarm reductionIntervention (counseling)PsychologyDescriptive statisticsSubstance useClinical psychologyMedicinePsychiatrySocial psychologyNursingPublic health

Abstract

fetched live from OpenAlex

OBJECTIVE: The aim of this scoping review was to describe the characteristics and features of substance abuse interventions for women in North America and discuss the findings from an occupational perspective. METHOD: A scoping review was conducted to examine North American peer-reviewed literature published between 2001 and 2014. Four databases were searched using terms related to intervention, substance abuse, and women only. Descriptive statistics of categorical groupings were used to describe the data sources and characteristics and features of the interventions. RESULTS: Forty-two articles met the inclusion criteria, with the majority citing a harm-reduction approach and using multifaceted interventions with various targets for change. CONCLUSION: Substance abuse interventions for women are typically multifaceted and follow a harm-reduction philosophy. Further research into the efficacy of interventions that more specifically target occupation beyond substance use is needed.

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)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Other design · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.937
Threshold uncertainty score0.893

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0030.001
Bibliometrics0.0000.001
Science and technology studies0.0000.000
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 head0.197
GPT teacher head0.490
Teacher spread0.293 · 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.

The models applied no category: nothing in the taxonomy fit this work.
Study designOther design
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

Citations17
Published2018
Admission routes1
Has abstractyes

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