Correlations between weight perception and overt risk-taking among Canadian adolescents
Bibliographic record
Abstract
OBJECTIVE: Perceptions of body weight represent an important health issue for Canadian adolescents. While associations between weight perception and mental health concerns like eating disorder symptomatology are well established, there is need for more Canadian evidence about how weight perception is associated with overt risk-taking among adolescents, and further how such associations differ by biological sex. METHODS: We conducted a national analysis of grade 9-10 students participating in the 2017-2018 cycle of the Health Behaviour in School-aged Children (HBSC) study in Canada. This analysis described contemporary patterns of alternate weight perception and then examined the strength and statistical significance of such associations by biological sex, with tobacco, alcohol, and cannabis use, binge drinking, fighting, and illicit drug use as outcomes. Behaviours were considered both individually and in combination. Analyses were descriptive and analytical, with regression models accounting for the nested and clustered nature of the sampling approach. RESULTS: Responses from 2135 males and 2519 females were available for a complete case series analysis. A total of 26% and 35% of males and females, respectively, perceived themselves as "too fat" while 20% and 9% identified as "too thin". Females perceiving themselves as "too fat" reported higher likelihoods of engaging in individual and scaled indicators of overt risk-taking. Conversely, among males, alternate weight perception was associated with lower levels of such behaviours. CONCLUSION: As males and females perceive and react to weight perception differently, clinical and health promotion strategies should be developed and uniquely targeted to groups of adolescents in regards to weight perception and risk-taking.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.003 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".