93 “I don’t want them to think that what they said matters”: How Adolescents with Severe Obesity Cope with Bullying
Bibliographic record
Abstract
Abstract Background Adolescents with severe obesity are subject to a high prevalence of weight-based victimization that may contribute to mental health symptoms. The ability to better cope with this victimization could potentially modulate the psychological sequelae. This is the first qualitative study to address the paucity of literature focusing on how adolescents with severe obesity cope with victimization. Objectives To explore how adolescents with severe obesity cope with weight-related victimization and how it subsequently affects their psychological well-being. Design/Methods This was a qualitative research study using an interpretive phenomenological analytic approach. One-on-one semi structured interviews were completed with 19 adolescents (73% female) aged 16 – 19 years, enrolled in a tertiary hospital weight management program. A diverse array of patient experiences of weight-based victimization were sought to explore their coping mechanisms and how the experiences affected them. The interviews were transcribed and sequentially independently analyzed by the research team until thematic saturation was achieved. Results The majority of participants (89.5%) described being a victim of weight-based victimization and highlighted its significant emotional impact. Two key themes were identified that captured the various coping strategies used by participants. The minority (52.9%) described approach coping strategies where they acted on the source to invoke change by standing up for themselves, helping others in similar situations or becoming a bully themselves. Whilst the majority (94.1%) used avoidant coping strategies such as feigning a strong exterior façade, denial, isolation and self-harm. Nearly half (47.1%) used both strategies. It is possible that the study participants did not feel they had control over the weight related bullying, and therefore, were more likely to choose avoidant coping styles. Conclusion Adolescents with severe obesity commonly use avoidant coping strategies to passively regulate emotions, including problem avoidance, wishful thinking, self-criticism and social withdrawal to cope with weight-based victimization. As part of a comprehensive approach to the management of adolescents with severe obesity, counseling should be offered on how to use alternative coping mechanisms in the face of weight-based victimization.
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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 | 0.005 | 0.010 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.004 | 0.005 |
| Scholarly communication | 0.004 | 0.003 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.002 | 0.004 |
| 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".