Dietary lifestyle modifications for vitiligo patients
Bibliographic record
Abstract
Background and objective: Changing the patient lifestyle as regarding diet well helped in vitiligo patient cure. Aim: to examine the effect of applying dietary instructions on dietary lifestyle modifications of vitiligo patients.Methods: Research design: Quasi experimental research design with one group (Pre/Post-test) was utilized in this study. Setting: the study was conducted in the ultraviolet unit at the Dermatology Department of Asyut University Hospitals. Study tool: Structured patient interview questionnaire sheet. It included two parts: Part 1: Assessment of patient’s sociodemographic variables. Part 2: Dietary pattern assessment: derived from Patient Life Style Pattern Assessment Sheet (PLSPAS) for Vitiligo.Results: The mean age of the studied sample was (mean ± SD 34.62 ± 12.35), 51.6% were female, 70% were living in rural areas, a highly statistically significant difference in the total mean knowledge scores between pre and post application of the dietary instructions (p value = .002).Conclusions: The present study concluded that there was a great improvement in the dietary lifestyle pattern of the studied sample after application of dietary instructions. Recommendations: Replication of the study on a larger probability sample from different geographical locations for generalization of the results. Printing copies of the dietary instructions for dissemination among all vitiligo patients attending the dermatology ward for treatment or follow-ups.
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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".