A tool to assess underlying factors to water provision among Guinean children
Bibliographic record
Abstract
In many countries, water is provided to children under 6 months of age (CU6M) in addition to breast milk (BM), hence increasing the risk of child mortality and morbidity. Factors related to this practice have not been thoroughly investigated either a tool to assess them. Based on the extended theory of planned behaviour (eTPB), we aim to develop and validate a questionnaire to assess psychosocial and environmental factors that may contribute/limit the water provision in addition to BM by mothers of CU6M in the Republic of Guinea. A three-step process was used. Ten focus group discussions (FGDs) were held to identify salient beliefs related to each of the four constructs of the eTPB. Data from FGDs were used to develop a questionnaire composed of 88 items administered to 428 mothers. Exploratory factor analyses were conducted to identify latent factors for each construct. A shorter version of the questionnaire was administered to another sample of 300 mothers. Confirmatory factor analyses (CFAs) were performed. Hancock and Mueller's H reliability indices were computed on final models to assess the tool's validity and reliability. The final questionnaire included 57 items. For all four final models, most criteria for fit indices of CFA were generally met. Reliability coefficients were all equal to or above 0.90 for each construct. This research offers a tool that could be used to investigate determinants of water provision besides BM among mothers of CU6M. Further validation in other contexts is warranted.
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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 | 0.004 | 0.010 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| 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".