Effectiveness of Group Education of Marital Enrichment Program (Olson Style) on Improvement of Married Women’s Satisfaction
Bibliographic record
Abstract
This semi-experimental study with control group and pre test-post test was conducted to evaluate the effectiveness of Olson's marriage enrichment group training on marital satisfaction of women whose husbands don't participate in the program. To this purpose using a non- randomly sampling method (accessible sampling) 40 volunteers from women who referred to one of Tehran's municipal health centers were selected and none randomly assigned to two experimental and control groups. As pre test, dependent variable in both groups measured by short form of ENRICH or 40 items form (Bahmani, Asgari, 1385). Members of experimental group participate in 10 training sessions of 90 minutes meeting which were held twice a week while control group members (waiting list) did not participate in any official intervention. Finally both groups measured as post-test. Data were processed by SPSS-16 to calculate statistical and inferential statistics. Analysis of covariance showed that global satisfaction score of experiential group was significantly (P‹ %1) higher than control group. Therefore it can be concluded that Olson's marriage enrichment program as an intervention that originally designed in such a way that both partners must be present simultaneously in training sessions, can increase women's marital satisfaction even when their husbands don't participate in the program
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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) | 0.003 | 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".