Factors associated with low short-term memory development among pupils in public primary schools: evidence from Benin republic
Bibliographic record
Abstract
BACKGROUND: Short-term memory, the ability to temporarily hold and manipulate information, plays a critical role in learning and academic performance. This study aims to assess factors associated with low short-term memory in 524 children aged 8-14 years who attended public government schools in the Benin. METHODOLOGY: Sixteen randomly selected schools located in peri-urban areas in northern and southern Benin participated in this cross-sectional study. Short-term memory was assessed via the WISC digit span tool. Food insecurity was evaluated with the Household Food Insecurity Access Scale (HFIAS). Socioeconomic and health data were collected through a digitalized questionnaire. Nutritional status was determined through anthropometric measurements and a hemoglobin test. RESULTS: The prevalence of below average short-term memory was 53.47% in the Northern and 28.81% in the southern Benin. In the northern region, 5.56%, 8.68%, and 13.19% of the pupils were, mildly, moderately, and severely food-insecure, respectively. In the southern region, 22.46%, 6.36%, and 3.38% of the pupils fell into the same categories, respectively. Multivariate logistic regression revealed that severe food insecurity (OR = 3.461, p < 0.05), moderate and severe thinness (OR = 1.680, p < 0.005), poverty (OR = 2.916, p < 0.001), caregivers' illiteracy (OR = 1.89, p < 0.05), pupils' age (OR = 0.864, p < 0.05) and being from the northern regions (OR = 2.263, p < 0.05) were significant predictors of low short-term memory ability. CONCLUSION: Even with access to a school canteen program, pupils from northern regions, malnourished, food-insecure and from socioeconomically disadvantaged households are more likely to exhibit low short-term memory skills. Policymakers should prioritize the implementation of evidence-based interventions and policies aimed at alleviating food insecurity, malnutrition, and poverty, alongside initiatives to enhance infrastructure and essential services, including access to electricity in underserved and remote areas.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".