Effectiveness of Group Schema Therapy in Reducing the Symptoms of Major Depression in a Sample of Women
Bibliographic record
Abstract
Treatment of the symptoms of major depression is one of the important issues in the treatment of psychological disorders. This study aims to investigate effectiveness of group schema therapy in reducing the symptoms of major depression in a sample of women in the Ahvaz City. This is a quasi-experimental with two control and treatment groups. To this end, 30 married women in Ahvaz were selected using the convenience sampling method and were included in two treatment and control groups of 15 persons. After pre-test for both groups, the experimental group received schema therapy in 10 sessions for one month; however, the control group received no training. Beck Depression Inventory that has an acceptable reliability and validity was used to assess depression. Finally, test scores were analyzed by analysis of covariance. The results showed that group schema therapy training was effective at the level of error P<0.0001 on reducing the symptoms of depression in the treatment group. Accordingly, it can be concluded that the group schema therapy training affects the mental health promotion. Therefore, the intervention can be effective in preventing mental injuries.
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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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".