Nutrition services by health providers during antenatal consultations in Senegal: a comparison of observed versus self-reported practices
Bibliographic record
Abstract
Background Malnutrition is of concern among pregnant women in Senegal. This paper aimed to compare health providers’ self-reported practices to their actual provision of nutrition services during antenatal care (ANC) consultations. Methods A comparative study was conducted in a random sample of 27 health providers in the Kolda region. Two ANC consultations were monitored for each provider, and later compared to the data that were collected through a face-to-face interview. This provided us with the opportunity to assess the agreement between self-reported and observed actions namely clinical actions, verbal assessments and counseling. Results In general, the ANC providers reported similar extent of clinical actions that they performed. However, in verbal assessments, health providers over-reported inquiring about iron and folic acid intake (44% observed vs 89% reported) and its potential side effects (0% vs 33%), signs of vitamin A deficiency (0% vs 11%) and intake of parasite prophylaxis (18% vs 63%). They also over-reported the provision of counseling on the importance of avoiding tea/coffee (41% observed vs 74% reported), gaining appropriate weight (14% vs 44%), and eating specific foods (7% vs 52%). Conclusions Nutrition services during ANC should be improved, especially in the domains of verbal assessment and nutrition counseling. The possible causes of these discrepancies might be the time constraint for ANC, limited skills, or a low demand of pregnant women for nutritional guidance. Nutrition training and/or supportive supervision of health providers deserve more attention in order to improve the nutrition services and the overall quality of ANC.
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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 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".