Saudi female university employee self-determination in their own health-related issues
Bibliographic record
Abstract
Introduction: To date, there have been no studies located investigating Saudi women's self-determination in their own health-related issues. This study aims to investigate how women in Saudi Arabia see their ability and willingness to decision making in this matter.Methodology: The study design is ethnonursing and Leininger’s Sunrise model was utilized as background theory; qualitative data analysis method was used. 12 Saudi women worked at a large University in Saudi Arabia were interviewed in-depth.Results and discussion: Seven universal Saudi Arabian cultural themes were identified: customs and traditions, women’s decision-making denied, shared decision-making, informed women and empowerment rise, financial status matters, emerging changes in the society, and impact from the Western world.Conclusions: One of the major findings in the interviews was that all research participants observed themselves as more independent and empowered than in the accounts reflecting other women they knew. They saw other women, whom they met at the hospital or who were their friends or relatives, were without equal rights for independent decision making. Mainly, men are interested in reproductive health and are willing to dominate women’s independent decision making in healthcare. The main conclusion, according to this study, the Saudi women research participants who are educated, are more independent in their health-related decision making than the previous literature suggested. The result may be different in villages and among less educated women and their husbands.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.008 | 0.001 |
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".