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 distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.002 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".