Peer victimization as a predictor of depression and body mass index in obese and non‐obese adolescents
Bibliographic record
Abstract
BACKGROUND: The current study examined the pathway from peer victimization to depressive symptoms and body mass index (BMI) as mediated by self-concept for physical appearance in both obese and non-obese adolescents. It was thought that this pathway would be particularly important for obese adolescents because, compared to non-obese adolescents, they are at risk for being victimized and because the victimization would be more likely to lead to lower self-concept. METHOD: Utilizing data from the National Longitudinal Survey of Children and Youth, the current study examined self-reports of peer victimization, self-concept for physical appearance, depressive symptoms, height, and weight in 1,287 adolescents at three time periods over four years starting when the participants were between the ages of 12 and 13. RESULTS: For non-obese adolescents, victimization did not predict changes in depressive symptoms and body mass index (BMI) four years later. For obese females, the mediated pathway was found from victimization to self-concept to both depressive symptoms and increases in BMI. For obese males, the findings were more complicated. In this group, the mediated pathway was found from victimization to self-concept to decreases in BMI, but a mediated pathway was not found for depressive symptoms. CONCLUSIONS: The current study suggests that a risk-factor for being victimized, such as obesity, may play an important role in the long-term effects of victimization by making it more likely that the adolescent will be victimized over the long term but also that victimization can reinforce the negative self-perceptions that the adolescent already has. It is important to go beyond using obesity as a predictor of long-term adjustment and examine the processes and experiences of obese individuals that might more directly cause depression or changes in health.
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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 | 0.000 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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".