Psychodrama Group Therapy for Social Issues: A Systematic Review of Controlled Clinical Trials
Bibliographic record
Abstract
The aim of this study was to carry out a systematic review of controlled clinical trials in order to identify both specific populations and social issues which may benefit from the effective use of psychodrama psychotherapy. A search was conducted in the WoS, SCOPUS, PsychINFO, Medline, Academic Search Ultimate, ProQuest, and PubPsych databases, complemented by a manual search on relevant websites and in the reference lists of the selected studies. Randomized controlled trials (RCTs) and quasi-RCTs of group-based psychodrama psychotherapy were included. The Effective Public Health Practice Project (EPHPP) tool was adopted to assess the methodological quality of the included studies. The search identified 14 RCTs and one quasi-RCT evaluating the effects of group-based psychodrama psychotherapy. The total number of participants in the studies was 642 people. Seven studies were conducted in Turkey, two in the USA, two in Finland, one in Canada, one in Brazil, one in Italy, and one in Iran. The heterogeneity of the issues analyzed indicates that psychodrama improves the symptoms associated with a wide range of problems. Despite psychodrama's long history, most clinical trials in this field have been published this century, which suggests not only that this psychotherapeutic practice remains relevant today but also that it continues to attract substantial interest among the scientific community. Nevertheless, further research efforts are required to understand its potential benefits for psychosocial well-being.
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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 | 0.048 | 0.122 |
| Meta-epidemiology (narrow) | 0.002 | 0.002 |
| Meta-epidemiology (broad) | 0.018 | 0.011 |
| Bibliometrics | 0.019 | 0.017 |
| Science and technology studies | 0.002 | 0.002 |
| Scholarly communication | 0.004 | 0.005 |
| Open science | 0.003 | 0.003 |
| Research integrity | 0.004 | 0.002 |
| Insufficient payload (model declined to judge) | 0.005 | 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".