Discordance between physical symptoms versus perception of severity by women with nausea and vomiting in pregnancy (NVP)
Bibliographic record
Abstract
BACKGROUND: Nausea and vomiting in pregnancy (NVP) is a multifaceted condition that affects more than half of pregnant women and can range in severity from mild nausea to severe dehydration. Presently physicians evaluate mostly physical symptoms of NVP in trying to assess the severity of the condition. The objective of this study was to investigate how factors, other than the physical morbidity of nausea and vomiting, influence self-perception of NVP by affected women. METHODS: Five hundred women with NVP calling a 1-800 NVP Healthline were asked to rate their NVP severity and report their nausea duration and number of vomiting/retching episodes. RESULTS: Nausea and vomiting/retching correlated significantly but very poorly with self-assessment of NVP severity. There was also a correlation between nausea duration and vomiting/retching frequency however the correlations were weak and overall physical symptoms could only explain 14% of the variability of women's feelings and perceptions through multivariate analysis. CONCLUSIONS: Physical symptoms weakly correlate with self-assessment of NVP severity. Other aspects of this condition, most probably psychosocial, influence women's perception of NVP severity.
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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 | 0.015 |
| 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 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| 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".