Preference and acceptability of alternative delivery vehicles for prenatal calcium supplementation among pregnant women in urban Bangladesh (256.2)
Bibliographic record
Abstract
Prenatal calcium supplementation is recommended by the WHO to decrease the risk of preeclampsia when dietary calcium intake is low; yet, this recommendation has not been successfully implemented to date. We aimed to evaluate preference and acceptability of alternate delivery vehicles for prenatal calcium supplementation (conventional tablets, chewable tablets, unflavored powder, and flavored powder) among pregnant women in urban Bangladesh. In a modified discrete‐choice experiment, pregnant women (n = 132) completed a 4‐day ‘run‐in period’ in which each option was sampled once, followed by a 21‐day ‘selection period’ during which participants freely selected a single option per day. Preference was objectively based on the probability of selection of each option; acceptability was assessed using questionnaires. Conventional tablets demonstrated the highest probability of selection (62%); the probability of selection of chewable tablets (19%), flavored powder (12%), and unflavored powder (5%) were all significantly lower than for conventional tablets (P < 0.001). Conventional tablets were also more acceptable based on subjective reports. Observation of actual use and expressed perceptions showed that a conventional tablet is likely to be the most successful prenatal calcium supplement for scale‐up of the WHO recommendation in Bangladesh. Grant Funding Source : Supported by the Hospital for Sick Children and Sprinkles Global Health Initiative
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.001 | 0.003 |
| 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 | 0.001 | 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".