Comparison of the Effectiveness and Stability of Integrated Transdiagnostic Treatment and Dialectical Behavior Therapy on Psychological Well-Being and Pain Perception in Patients with Cancer in Isfahan, Iran
Bibliographic record
Abstract
Background: The process of cancer and its treatment has effects on patients, so that the physical and mental function of the patient is reduced. In this regard, the use of therapeutic approaches to improve mental health problems caused by the disease has been identified and presented. Considering the repetition of other therapeutic strategies and the variety of psychological problems of patients with cancer, lack of use of two strategies of integrated transdiagnostic treatment and dialectical behavior therapy (DBT) in the group of patients with cancer, and the impact of a person's cognitive skill on maintaining mental health, the purpose of the present study was to compare the effectiveness of integrated transdiagnostic treatment and DBT in psychological well-being and pain perception of patients with cancer. Methods: The design of this quasi-experimental study was pre-test, post-test, and follow-up with a control group. The statistical population of the study consisted of all patients with cancer in Isfahan, Iran, in 2021. The study sample consisted of 63 patients with cancer who were selected by the available sampling method and randomly assigned to three experimental and control groups. Research data were collected using McGill Pain Questionnaire (MPQ) and Ryff's Psychological Well-Being Scale and analyzed using repeated-measures analysis of variance (ANOVA) in SPSS software. Findings: Integrated transdiagnostic and DBT education was effective in improving pain perception and psychological well-being of patients with cancer in the experimental group compared to the control group. Moreover, there was a significant difference between the two educational strategies (integrated transdiagnostic and DBT) in the post-test for variable of pain perception (0.58 and 0.42, respectively) and for the psychological well-being variable (0.27 and 0.17, respectively). In the follow-up phase, it was obtained as 0.58 and 0.43 for the pain perception variable and 0.30 and 0.17 for the psychological well-being variable (P < 0.01). Integrated transdiagnostic treatment has been more effective in the psychological well-being and pain perception of patients with cancer. Conclusion: Integrated transdiagnostic treatment and DBT lead to increased psychological well-being and improved pain perception in patients, and health professionals can use this treatment method to improve the psychological performance of patients.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.003 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| 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) | 0.001 | 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 teacher head, 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".