Evaluation of the Effects of an Educational Intervention Based on the Ottawa Nutritional Guideline on Health-Related Quality of Life in Pregnant Women with Nausea and Vomiting
Bibliographic record
Abstract
Background & aim: Nausea and vomiting during pregnancy (NVP) is among the most common problems in pregnant women. As explained in guidelines, combination of non-drug treatments, including nutritional modifications, lifestyle changes, and use of alternative medicine for the treatment of NVP has been less highlighted. The present study was performed with the aim of determining the effect of an educational intervention (based on the Ottawa nutritional guideline) on health-related quality of life in pregnant women with NVP. Methods: This single-blind clinical trial was performed on 60 pregnant women, referred to Daneshamouz and Ahmadi health centers in Mashhad, Iran in 2015. The intervention group received two 60-min training sessions based on the Ottawa nutritional guideline, while the control group received routine care. The data collection tools included the subject selection form, demographic and midwifery information form, health-related quality of life for nausea and vomiting during pregnancy (NVPQOL) questionnaire, and the Ottawa guideline checklist. For data analysis, Chi-square, Fisher’s exact test, Mann-Whitney test, independent t-test, paired t-test, and ANOVA were performed, using SPSS version 16. P-value less than 0.05 was considered statistically significant. Results: The demographic characteristics of the subjects such as education, occupational status, age, gestational age, and body mass index were homogenous in the two groups. The mean NVPQOL score was significantly different between the intervention and control groups after the study (P
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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 | 0.002 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".