Examining how sociocultural appearance pressures relate to positive and negative facets of body image and eating behaviors in adolescents: An exploratory person-centered approach
Bibliographic record
Abstract
The present study explored how patterns of sociocultural appearance pressures were linked to positive and negative facets of body image and eating behaviors in an adolescent sample (N = 438). Latent profile analyses indicated three distinct subgroups of perceived sociocultural appearance-related pressures: a Generalized-Pressure profile (28.8%) (moderate pressure from mother, father, and peers, and relatively high pressure from the media), a High-Media-Pressure profile (38.8%) (low pressure from mother, father, peers, and relatively high pressure from the media), and a Low-Pressure profile (32.4%) (low pressure from all sources). Overall, adolescents in the Generalized-Pressure profile reported a less positive relationship with food and their bodies (i.e., higher internalization of the thin ideal, body dissatisfaction, and bulimia symptoms, and lower body esteem and intuitive eating) than adolescents in the High-Media-Pressure profile, who exhibited poorer outcomes than those in the Low-Pressure profile. These findings highlight the importance of exploring how sociocultural appearance pressures from various sources combine in distinct ways, and how these configurations relate to different aspects of body image and eating behaviors in adolescents.
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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 | 0.002 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| 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".