Narrative Therapy as an Intervention for Post-Divorce Adjustment and Grief: Examining Psychological Outcomes
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Bibliographic record
Abstract
Objective: This study aimed to evaluate the effectiveness of narrative therapy in improving post-divorce adjustment and reducing grief symptoms among individuals experiencing marital dissolution. Methods and Materials: A quasi-experimental design was used with a treatment group (n = 36) receiving ten structured narrative therapy sessions and a control group (n = 36) receiving no intervention. Participants were assessed at three time points: pre-test, post-test, and follow-up. Standardized measures, including the Post-Divorce Adjustment Scale (PDAS) and the Grief Experience Questionnaire (GEQ), were administered to evaluate changes over time. Data were analyzed using repeated measures ANOVA and Bonferroni post-hoc tests to determine within-group and between-group differences in post-divorce adjustment and grief levels. Findings: Results showed a significant improvement in post-divorce adjustment in the treatment group compared to the control group (F = 57.90, p = 0.0001). Grief levels significantly decreased in the treatment group over time (F = 71.92, p = 0.00001), with Bonferroni post-hoc comparisons indicating that post-divorce adjustment increased significantly from pre-test to post-test (p = 0.001) and was maintained at follow-up (p = 0.0003), while grief decreased significantly from pre-test to post-test (p = 0.0001) and continued to decline at follow-up (p = 0.00001). Conclusion: The findings suggest that narrative therapy is an effective intervention for enhancing post-divorce adjustment and reducing grief. By enabling individuals to reconstruct their divorce narratives, the therapy promotes emotional healing, resilience, and future-oriented self-perceptions. Narrative therapy should be considered a valuable therapeutic approach for individuals struggling with the emotional consequences of divorce.
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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 | 0.007 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.003 |
| Insufficient payload (model declined to judge) | 0.000 | 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 it