The Effectiveness of Positive Psychotherapy on Optimism and Alexithymia in Retired Female Teachers with Anxiety
Bibliographic record
Abstract
Abstract The purpose of this study was to investigate the effect of positive psychotherapy on optimism and alexithymia in retired women's teachers with anxiety. The study was applied based on the target. The method was semi-experimental with pre-test, post-test, and follow up design with experimental and control groups. Thirty retired women's teachers with anxiety were selected as the sample using the purposeful method. Fifteen subjects were randomly assigned to the experimental group and fifteen people in the control group. The instruments for collecting data were Questionnaires of Scheier & Carver Optimism, Toronto Alexithymia & Beck Anxiety Questionnaire. Positive psychology protocol for eight sessions every week in 90 minutes was accomplished in the experimental group, while the control group didn't receive any intervention. The covariance analysis was used for data analysis. The research results indicated positive psychotherapy had a positive effect on optimism and alexithymia. It led to increasing emotional recognition, reducing the difficulty of describing emotions, and increasing the objective thinking of anxious retired women's teachers. Positive psychotherapy had a decreased effect on alexithymia in the experimental group in the post-test and follow-up phases. Simultaneously, there was an increase in optimism in the experimental group in the post-test and follow-up stages. Moreover, the effects of the interventions remained stable until the follow-up in the experimental group
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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 | 0.000 | 0.001 |
| 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".