Comparison the Effects of Communication and Conflict Resolution Skills Training on Marital Satisfaction
Bibliographic record
Abstract
The purpose of the study was to examine the effects of communication and conflict resolution skills training on marital satisfaction among Iranian couples based on PREPARE-ENRICH program. In this study, marital satisfaction was measured by ENRICH Marital Satisfaction. The methodology of this study was experimental method; with pre-test, post-test, and control group design. Purposive sampling was conducted to select the sample that was included 54 couples who were consisted of all couples referred to the researcher by counselling centres. The referrals were done for about two months in 2009. These couples were randomly assigned to an experimental and a control group as well. The dependent variables were marital satisfaction, and the independent variables were communication and conflict resolution skills training. Consequently, the results indicated that communication and conflict resolution skills training improved marital satisfaction (p<.05). Moreover, the results showed that communication and conflict resolution training was effective in martial satisfaction in post-test (p<.05). In conclusion the findings of this study indicated that the on PREPARE-ENRICH program can be effective in improving marital satisfaction among Iranian couples.
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 | 0.002 |
| 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".