Effectiveness of acceptance and commitment therapy on forgiveness, mood deficiency and feelings of loneliness in betrayed women
Bibliographic record
Abstract
Background: The aim purpose of this study was to determine the effectiveness of treatment on acceptance and acceptance on forgiveness, mood deficiency and loneliness in betrayed women. Materials and methods:The research method was a quasi-experimental using pre-test, post-test and experimental and control group.The statistical population of this study consisted of all women affected by infidelity who referred to counseling centers in Qom (Fardai Roshan and Shamim Counseling Center).The sampling method was voluntarily and with random replacement; In this way, 30 women were selected among the women affected by infidelity who referred to the mentioned centers, and then randomly and based on the list of names, they were randomly assigned to two experimental and control group.Loneliness Questionnaire (Russell, 1996), the Toronto Alexithymia Questionnaire (Taylor, 1986) and the Forgiveness Questionnaire (Pollard et al., 1998) were used.Results: The data were analyzed by multivariate covariance test and mixed analysis of variance with repeated measurement design and the squared value of eta indicates the effectiveness of acceptance and commitment therapy on the variables of forgiveness, alexithymia and lonely feeling.Conclusion: As a result, the findings of this research confirmed the role and efficacy of education based on acceptance and commitment in reducing unforgiveness and emotional inadequacy and feelings of loneliness of betrayed spouses.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.001 |
| 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".