Measuring the Effectiveness of Interpersonal Psychotherapy Training for Kerman Prison Staff: With Emphasis on Prisoners' Rights
Bibliographic record
Abstract
This study aimed at improving the rights of prisoners by measuring the effectiveness of providing interpersonal psychotherapy training to social workers and psychologists in Kerman Central Prison. This experimental study uses focus groups, the Standard Interpersonal Problems Questionnaire (IIP) and Beck Depression Inventory and Alexithymia Toronto Scale (TAS), to assess the knowledge and skills of prison staff regarding how to deal with prisoners. Interpersonal psychotherapy training program (IPT) was performed using pre-test and post-test methods for 39 social workers and psychologists working in Kerman Prisons Organization who participated in interpersonal psychotherapy training workshops. All participants were included in this study and the data were analyzed using SPSS 22 software. The findings showed that the effectiveness of interpersonal psychotherapy training in the post-test phase is a function of participants' scores of depression, mood disorders and problems. Less interpersonal problems, mood swings, and depression among prison staff meant greater effectiveness of the prisoner training program. The research findings also showed that the higher level of education and work experience of paramedics increased the effectiveness of the training program. Therefore, it is suggested that the Prisons Organization, with the help of human rights experts and social psychologists, improve the ability of its personnel regarding their interpersonal communication and reduce depression, which makes it possible for this group to decrease the communicative problems of the prisoners.
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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 | 0.003 | 0.011 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".