omparative Effects of Acceptance and Commitment Therapy (ACT) and Intensive Short-Term Dynamic Psychotherapy (ISTDP) on Depression, Alexithymia, Quality of Life, and Mental Health in Women with Breast Cancer
Bibliographic record
Abstract
Objective: This study examines the comparative effectiveness of Acceptance and Commitment Therapy (ACT) and Intensive Short-Term Dynamic Psychotherapy (ISTDP) on depression, alexithymia, quality of life and mental health in women with breast cancer. Methods and Materials: A randomized controlled trial with a pre-test-post-test design was conducted, involving 36 participants assigned to ACT, ISTDP, and control groups. The participants completed the Toronto Alexithymia Scale (1994), Beck Depression Inventory (1996), WHOQOL-BREF Questionnaire, and Witt and Weir Mental Health Scale (1983) before and after the interventions. The experimental groups received the respective ACT and ISTDP interventions. Data were analyzed using MANCOVA and Bonferroni post-hoc tests. Findings: Both ACT and ISTDP interventions significantly improved depression, alexithymia, quality of life, and mental health scores (p<0.05), with no significant differences between the therapies in effectiveness. Conclusion: These findings indicate that both ACT and ISTDP may effectively enhance mental health and quality of life in women with breast cancer, supporting their use as valuable components of comprehensive cancer care.
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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 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| 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 | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".