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Record W4415382921 · doi:10.1080/09687637.2025.2569526

Evaluation of the outcomes and influencing factors of non-custodial educational programmes for people who use drugs in South Korea

2025· article· en· W4415382921 on OpenAlexaff
Kyung-ae Nam, In‐Sun Oh, Sun‐Kyeong Park

Bibliographic record

VenueDrugs Education Prevention and Policy · 2025
Typearticle
Languageen
FieldMedicine
TopicHIV, Drug Use, Sexual Risk
Canadian institutionsJewish General Hospital
Fundersnot available
KeywordsQualitative researchData collectionMEDLINE

Abstract

fetched live from OpenAlex

Background This study evaluated the effectiveness of deferred prosecution (DP) and probation, defined as non-custodial educational programmes (NCEPs), for drug users in South Korea.Methods We analyzed questionnaire responses from participants in a DP group (N = 203) and a probation group (N = 254) over a 2-year period (January 2022–December 2023). We used the Wilcoxon signed-rank test to compare the pre- and post-programme scores for drug-related knowledge and the Hanil Drug Insight Scale (HDIS). Multivariate logistic regression identified factors associated with programme effectiveness, including prior treatment experience, Meaning of Life Questionnaire (MLQ) scores, and mental health status.Results Both groups showed significant improvements in drug-related knowledge and HDIS scores (p < 0.001). Factors significantly associated with improved outcomes included prior treatment experience (odds ratio [OR]: 3.73, 95% confidence interval [CI]: 1.3–10.71), poor mental health (OR: 2.45, 95% CI: 1.01–5.95), and higher MLQ scores (OR: 2.9, 95% CI: 1.50–5.63). Personal well-being and health-related education appear more influential than marital or employment status.Conclusion This study provides preliminary empirical evidence of the positive impact of NCEPs in South Korea and identifies key psychological and experiential factors that contribute to their effectiveness.

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: Empirical · Consensus signal: Empirical
Teacher disagreement score0.199
Threshold uncertainty score0.500

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
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 head0.039
GPT teacher head0.412
Teacher spread0.374 · 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

Citations1
Published2025
Admission routes1
Has abstractyes

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