The Development and Validation of a Tool to Evaluate the Determinants of Iron-Rich Food Intake among Adolescent Girls of Senegal
Bibliographic record
Abstract
To reduce anemia among adolescent girls, factors that influence the consumption of iron-rich foods/IRF have not been investigated, and neither has a tool been developed to assess its determinants. Using the extended version of the theory of planned behaviour/eTPB, this study aims to develop and validate a questionnaire assessing individual and environmental factors that could influence IRF intake among Senegalese adolescent girls aged 10–19 years old. First, eight focus group discussions (FGDs) were held in different regions to identify salient beliefs related to each of the four constructs of the eTPB. Information from FGDs was used to develop a questionnaire that was administered to the first group (n = 200) of girls. Principal component and exploratory factorial analyses were then performed to identify latent factors for each construct. A modified version of the tool was administered to the second sample of girls (n = 400), and confirmatory factorial analyses were conducted. Hancock and Muller’s H reliability index was computed on the final model. Most metrics for fit indices were respected, and the H value was satisfactory. This study proposes a tool that could be used to explore determinants of the consumption of IRF among adolescent girls.
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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 | 0.009 | 0.012 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| 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".