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Record W2493725579 · doi:10.5539/ijps.v8n3p123

The Effect of a Cognitive Behavioral Treatment Program for Male Young Delinquents in Guangzhou: A Pilot Study

2016· article· en· W2493725579 on OpenAlexvenueno aff
Jinwu Zhang, Yan Zhang

Bibliographic record

VenueInternational Journal of Psychological Studies · 2016
Typearticle
Languageen
FieldPsychology
TopicPersonality Disorders and Psychopathology
Canadian institutionsnot available
Fundersnot available
KeywordsPsychologySocial skillsInefficiencyPsychological interventionCognitionClinical psychologyChinaDevelopmental psychologyPsychiatry

Abstract

fetched live from OpenAlex

Pro-criminal attitudes and inefficiency in social skills or problem-solving skills are associated with criminal conducts. Targeting on these factors, Cognitive-Behavior Treatment (CBT) programs are effective interventions for adult and young offenders. However, the effectiveness of CBT programs in Chinese correctional facilities is unknown. The present study, as a pilot one, evaluates a CBT program consisting of six sessions to treat young delinquents in South China. In Guangzhou, 60 male delinquents were divided into experimental and comparison group. Problem-solving skills, social skills and pro-criminal attitudes were measured and compared before and after the program for both groups. Measured by Social Maladjustment Scale (SOC) and General Self-efficacy Scale (GSES), the experimental group showed significant improvements in social skills and problem solving skills, while those of the comparison group remained constant. The results of the pilot study were encouraging and demonstrating the potential of CBT programs to be effective treatment for young delinquents in South China. Implications for future research and cross-cultural generability of CBT are discussed.

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: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.267
Threshold uncertainty score0.344

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
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 head0.172
GPT teacher head0.526
Teacher spread0.354 · 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
Published2016
Admission routes1
Has abstractyes

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