Examining The Potential For Vitamin D Deficiency In Young Saudi Women Living In Canada: A Qualitative Study
Bibliographic record
Abstract
More than a billion people worldwide suffer from vitamin D deficiency or insufficiency. Canada, which has a long winter and high latitude, has a high rate of vitamin D deficiency. The Middle East also, in particular Saudi Arabia, has one of the highest rates of vitamin D deficiency in the world. The purpose of this research was determining the knowledge, attitudes, and practices (KAP) concerning vitamin D of young Saudi women living in Canada. Health professionals with experience in both Canada and Saudi Arabia acted as key informants. This research assessed topics related to knowledge of vitamin D sources (supplementation, fortification, and exposure to the sun), attitudes regarding the importance of vitamin D, and practices indicating whether knowledge and attitudes were being implemented or not. The study was conducted in Canada. Eight Saudi women between the ages of 18- 45 y and 10 health professionals including physicians, nutritionists and nurses were recruited. Results showed that Saudi women had limited awareness of vitamin D deficiency and lacked motivation to use supplements. They also had limited sun exposure due to environmental and cultural reasons. The health professionals recommended that Saudi women increase their awareness of the risk of vitamin D deficiency and the importance of using vitamin D supplements. Recommendations for more research about Saudi women living in northern locations such as Canada are presented.
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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 | 0.003 | 0.007 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.017 | 0.004 |
| Scholarly communication | 0.004 | 0.001 |
| Open science | 0.002 | 0.003 |
| Research integrity | 0.001 | 0.003 |
| 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".