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Record W2548957187 · doi:10.1007/s40429-016-0127-6

Personality-Targeted Interventions for Substance Use and Misuse

2016· review· en· W2548957187 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.
fundA Canadian funder is recorded on the work.

Bibliographic record

VenueCurrent Addiction Reports · 2016
Typereview
Languageen
FieldPsychology
TopicPersonality Disorders and Psychopathology
Canadian institutionsUniversité de Montréal
FundersCanadian Institutes of Health ResearchKing's College London
KeywordsPsychological interventionPersonalityClinical psychologyPsychologySubstance usePersonality disordersIntervention (counseling)PsychiatrySubstance abuseBig Five personality traitsPsychotherapistSocial psychology

Abstract

fetched live from OpenAlex

PURPOSE OF REVIEW: Personality factors have been implicated in risk for substance use disorders through longitudinal and neurobiologic studies for over four decades. Only recently, however, have targeted interventions been developed to assist individuals with personality risk factors for substance use disorders manage their risk. This article reviews current practices in personality-targeted interventions and the eight randomised trials examining the efficacy of such approaches with respect to reducing and preventing substance use and misuse. RECENT FINDINGS: Results indicate a moderate mean effect size for personality-targeted approaches across several different substance use outcomes and intervention settings and formats. CONCLUSIONS: Personality-targeted interventions offer several advantages over traditional substance use interventions, particularly when attempting to prevent development of problems in high-risk individuals or when addressing concurrent mental health problems in brief interventions.

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.

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 categoriesMeta-epidemiology (narrow), Insufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.913
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

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

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 head0.198
GPT teacher head0.450
Teacher spread0.252 · 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