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Record W1750391704 · doi:10.1111/ijsw.12096

Do depressive symptoms in justice‐involved girls reduce the effects of a cognitive‐behavioral program on their disruptive and delinquent behaviors?

2014· article· en· W1750391704 on OpenAlexaff
Nadine Lanctôt, Stéphane Hauth‐Charlier, Annie Lemieux

Bibliographic record

VenueInternational Journal of Social Welfare · 2014
Typearticle
Languageen
FieldPsychology
TopicChild and Adolescent Psychosocial and Emotional Development
Canadian institutionsUniversité de Sherbrooke
Fundersnot available
KeywordsSeriousnessPsychologyClinical psychologyCognitionDepressive symptomsJuvenile delinquencyDevelopmental psychologyPsychiatry

Abstract

fetched live from OpenAlex

The present study evaluated the effects of a cognitive‐behavioral program on disruptive and delinquent behaviors among a sample of adolescent girls placed in a residential center in Q uebec ( C anada). This study also investigated the moderating impact of depressive symptoms on program effectiveness. The study used a quasi‐experimental design to allow comparisons between 104 girls in the treatment group and 78 girls in the comparison group over 18 months. Findings showed that the program contributed significantly, albeit modestly, to a decline in some forms of disruptive/delinquent behaviors. Results also indicated that girls with a higher level of depressive symptoms at admission also reported higher involvement in a myriad of disruptive/delinquent behaviors and that for some types of problem behaviors, this higher involvement persisted over time. In general, however, the seriousness of the depressive symptoms that the girls reported at admission did not interfere with the effectiveness of the cognitive‐behavioral program.

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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.877
Threshold uncertainty score0.432

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 head0.021
GPT teacher head0.358
Teacher spread0.338 · 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

Citations2
Published2014
Admission routes1
Has abstractyes

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