Food insecurity, diet quality, and mental health in culturally diverse adolescents
Bibliographic record
Abstract
Purpose – The purpose of this paper is to increase the understanding of adolescents’ perceptions of food insecurity and diet quality, and the impact that these factors have on mental health. Design/methodology/approach – This study used a community-based research approach. It gathered qualitative data from 11 in-depth interviews conducted with adolescents aged 13-19. Participants were recruited through various programmes they attended at a community organization in Toronto. Findings – Overall, results indicate that respondents clearly identified a linkage between food insecurity and mental health. They also identified several effects of poor diet quality on mental health. Respondents understood food insecurity and poor diet quality to exist on a continuum. However, they also identified other reasons for making poor dietary choices such as peer pressure. Mental health effects of food insecurity and poor diet quality included sadness, stress, worry, anger, shame, impaired concentration, and fatigue. Practical implications – This research will help to inform future research design in the field of social determinants of mental health. As well, the findings will help guide the development of interventions targeted towards this vulnerable age group. Originality/value – This is the first qualitative study to explore food insecurity and poor diet quality, as existing on a continuum, from the perspective of adolescents. The authors are also the first to explore the impact of these factors on the mental health of adolescents, based on their own understanding. What is more, the authors focused on a culturally diverse population living in an underprivileged neighbourhood in Toronto. The authors chose this population because they are at higher risk of both food insecurity and poor diet quality.
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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 | 0.002 |
| 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 | 0.001 |
| 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".