Effectiveness of an Integrative Educational Package Based on Motivational Interviewing, Acceptance and Commitment Therapy, and Compassion-Focused Therapy on Alexithymia and Quality of Life in Women with Multiple Sclerosis
Bibliographic record
Abstract
Objective: The present study aimed to design an educational package based on Motivational Interviewing, Acceptance and Commitment Therapy, and Compassion-Focused Therapy and evaluate its effectiveness on alexithymia and quality of life in patients with Multiple Sclerosis (MS) in Tehran. Method: This study employed a quasi-experimental design with a control group and pre-test, post-test, and follow-up assessments. Forty women with MS, who visited the MS Association in Tehran Province from October to February 2021, were selected based on research criteria through purposive sampling and were randomly assigned to two groups (using a random number table). After random assignment, one of the groups was randomly designated as the experimental group, receiving the researcher-developed integrative treatment package, and the other as the control group (n=20). The data collection tools included a demographic information questionnaire, the Toronto Alexithymia Scale (Bagby, Taylor, & Parker, 1994), and the Multiple Sclerosis Quality of Life-54 Instrument (Ware et al., 1988). Data were collected at three stages: baseline, post-intervention, and three-month follow-up. The research hypotheses were analyzed using repeated measures ANOVA and Bonferroni post hoc tests. Findings: The results of this study indicated that the educational package based on Motivational Interviewing, Acceptance and Commitment Therapy, and Compassion-Focused Therapy significantly improved alexithymia (F=24.31, P<0.001) and quality of life (F=22.67, P<0.001) in women with MS. Conclusion: It can be concluded that the educational package based on Motivational Interviewing, Acceptance and Commitment Therapy, and Compassion-Focused Therapy is effective in improving alexithymia and quality of life in women with MS.
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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) | 0.001 | 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 | 0.001 |
| 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".