The Effect of Leisure Intervention on Occupational Performance and Occupational Balance in Individuals with Substance Use Disorder: A Pilot Study
Bibliographic record
Abstract
Background and Purpose. Leisure, as an occupation, played a crucial role in promoting individuals’ health and well‐being. However, the specific impact of leisure as an intervention for individuals with substance use disorder remains unclear. This pilot study was aimed at investigating the effect of a leisure intervention on occupational performance and occupational balance in individuals with substance use disorder. Methods. The sample for this quasiexperimental pretest–posttest with a two‐month follow‐up design comprised nine individuals aged between 18 and 55 years, selected using a convenience sampling method. The intervention consisted of a 2‐month group leisure participation program, conducted twice a week, followed by a 2‐month follow‐up period. Primary outcome measures included occupational performance and occupational balance, and secondary outcome measures were leisure participation, quality of life, and drug craving. Outcome measures were assessed three times: preintervention, postintervention, and after the follow‐up period. The outcome measures included the Canadian Occupational Performance Measure (COPM), Occupational Balance Questionnaire‐11 (OBQ11), Nottingham Leisure Questionnaire (NLQ), 36‐Item Short‐Form Health Survey (SF‐36), and Desire to Drug Questionnaire (DDQ). Data analysis was performed using the Friedman test and Wilcoxon signed‐rank test as a post hoc procedure, with a significance level set at 5%. Results. The findings showed significant improvements in participants’ occupational performance in postintervention and follow‐up assessments (p < 0.01, r = 0.59) and better occupational balance from pre‐ to postintervention (p < 0.01, r = 0.59) and after the follow‐up period (p < 0.01, r = 0.60). Furthermore, significant enhancements were observed in leisure participation, quality of life, and a reduction in drug craving. Conclusion. The findings indicate that leisure intervention positively impacted both occupational performance and occupational balance, suggesting its potential as a beneficial therapeutic approach for individuals with substance use disorder. Additional research is warranted to delve deeper into and validate the effectiveness of leisure intervention within this specific population.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".