The Moderating Effect of the Economic Situation on Relationship between Problem-Solving Skills and Mental Health in Working Women and Housewives
Bibliographic record
Abstract
Women as an important stratum of society play a fundamental role in the creation, establishment and strengthening of families. So, paying attention to their mental health as the family guides has direct effects on the mental health of children, families and consequently the whole of society. Thus, the present study was performed to investigate the moderating effect of the economic situation on the relationship between problem solving skills and mental health in two groups of working women and housewives referring to Welfare Centers in the city of Karaj. Based on Morgan’s sampling table, 199 working women and 192 housewives (totally 391) were selected by simple random sampling method. Then, Cassidy and Long (1996) Problem-Solving Style Questionnaire and Goldberg (1989) General Health Questionnaire were administered on the sample group, and data were analyzed using SPSS software (ver. 17). The results showed that the economy had an independent contribution in predicting the mental health of working women, but it was not capable to act as a moderating variable in relationship between problem-solving skill and mental health of working women. In addition, according to the results obtained from the housewife population, not only the economy does not have an independent contribution in the prediction of their mental health, but also it cannot act as a moderating variable in this relationship. But the problem-solving skill alone explains 23.8% of the variance of mental health in the sample population. In other words, problem-solving ability was effective in increasing the level of mental health. But the impact of economy as a moderating variable in the relationship between problem-solving skill and mental health of housewives and working women was not significant.
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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 | 0.001 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| 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".