Canadian Children from Food Insecure Households Experience Low Self-Esteem and Self-Efficacy for Healthy Lifestyle Choices
Bibliographic record
Abstract
The objectives of this cross-sectional study were to: (i) determine whether there are differences in self-esteem and self-efficacy for healthy lifestyle choices between children living in food secure and food insecure households; and (ii) determine whether the association between household food insecurity (HFI), self-esteem and self-efficacy differs by gender. Survey responses of 5281 fifth-grade students (10 and 11 years of age) participating in the Canadian Children's Lifestyle and School Performance Study II were analyzed using logistic and linear regression. HFI status was determined by the six-item short-form Household Food Security Survey Module (HFSSM). Students from food insecure households had significantly higher odds of low self-esteem, and significantly lower scores for global self-efficacy to make healthy choices, compared to students from food secure households. These associations were stronger for girls than for boys and appeared independent of parental educational attainment. Household income appeared to be the essential underlying determinant of the associations of food insecurity with self-esteem and self-efficacy. Upstream social policies such as improving the household income of low-income residents will reduce food insecurity and potentially improve self-esteem and self-efficacy for healthy choices among children. This may improve health and learning, and in the long term, job opportunities and household earnings.
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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 | 0.002 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| 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".