The Effectiveness of Mindfulness-Based Cognitive Group Therapy on Marital Satisfaction and General Health in Woman With Infertility
Bibliographic record
Abstract
Infertility affects around 80 million people around the world and it has been estimated that psychological problems in infertile couples is within the range of 25-60%. The purpose of this study was to determine the effectiveness of Mindfulness-based cognitive group therapy on consciousness regarding marital satisfaction and general health in woman with infertility. Recent work is a clinical trial with a pre/posttest plan for control group. Covering 60 women who were selected by in access method and arranged randomly in interference (30) and control (30) groups. Before and after implementation of independent variable, all subjects were measured in both groups using Enrich questionnaire and marital satisfaction questionnaire. Results of covariance analysis of posttest, after controlling the scores of pretest illustrated the meaningful difference of marital satisfaction and mental health scores in interference and control groups after treatment and the fact that MBCT treatment in infertile women revealed that this method has an appropriate contribution to improvement of marital satisfaction and mental health. Necessary trainings for infertile people through consultation services can improve their mental health and marital satisfaction and significantly help reducing infertile couples' problems.
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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".