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Record W2593018030 · doi:10.1080/1536710x.2017.1299662

Assessment and Treatment for Persons with Coexisting Ability and Substance Use Issues: A Review and Analysis of the Literature

2017· review· en· W2593018030 on OpenAlexafffund
Gabriela Novotná, Randy Johner, Michelle McCarron, Nuelle Novik, Bonnie Jeffery, Meagan Taylor, Michelle Jones

Bibliographic record

VenueJournal of Social Work in Disability & Rehabilitation · 2017
Typereview
Languageen
FieldMedicine
TopicSubstance Abuse Treatment and Outcomes
Canadian institutionsRegina Qu'Appelle Health RegionUniversity of Regina
FundersSaskatchewan Health Research Foundation
KeywordsPopulationMedical prescriptionSubstance useMedicinePsychiatryPsychologyClinical psychologyNursingEnvironmental health

Abstract

fetched live from OpenAlex

Persons with ability issues are at considerably higher risk to develop substance use problems when compared to the general population. Yet, little is known about the current status of substance use treatment for this population. A comprehensive search of the literature revealed a need for (a) population-specific instruments for screening and assessment of the use of alcohol and drugs, including the misuse of prescription medication; (b) tailored treatment methods and individualized treatment plans that meet diverse literacy or cognitive needs; (c) treatment programs located in facilities that are readily accessible for all abilities; and (d) population-specific service provider training.

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)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.231
Threshold uncertainty score0.711

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0030.001
Bibliometrics0.0000.001
Science and technology studies0.0000.001
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 head0.093
GPT teacher head0.436
Teacher spread0.343 · 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 designObservational
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

Citations8
Published2017
Admission routes2
Has abstractyes

Explore more

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