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Motivational Interviewing With Dually Diagnosed Adolescents in Juvenile Justice Settings

2006· article· en· W2090576506 on OpenAlexaff
Sarah W. Feldstein, Joel. I. D. Ginsburg

Bibliographic record

VenueBrief Treatment and Crisis Intervention · 2006
Typearticle
Languageen
FieldPsychology
TopicChild and Adolescent Psychosocial and Emotional Development
Canadian institutionsMinistry of Community Safety and Correctional Services
Fundersnot available
KeywordsJuvenilePsychologyEconomic JusticeInterviewMotivational interviewingClinical psychologyMedical emergencySocial psychologyApplied psychologyCriminologyDevelopmental psychologyMedicinePsychiatryPolitical scienceIntervention (counseling)Law

Abstract

fetched live from OpenAlex

Recent empirical investigations have gathered data regarding the rates of psychiatric comorbidity within juvenile justice populations. Data from these studies detail the prevalence of risk-taking behavior, substance abuse and dependence, posttraumatic stress disorder, and sexual risk taking. In addition to reviewing these findings, this paper explores the use of motivational interviewing (MI) with adult offenders and adolescent substance users. The efficacy of MI in these areas indicates the potential fit of MI with juvenile justice populations. Although the application of MI with this population is theoretically indicated, research is needed to garner empirical support for this application of MI. [Brief Treatment and Crisis Intervention 6:218–233 (2006)]

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)0.000
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: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.115
Threshold uncertainty score0.631

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
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)0.0000.000

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 head0.016
GPT teacher head0.280
Teacher spread0.264 · 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
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

Citations49
Published2006
Admission routes1
Has abstractyes

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