Body surveillance, but not body-related emotions, impact cognitive and motor performance among adolescents
Bibliographic record
Abstract
The salience of social status and appearance during adolescence can lead some to chronically monitor their appearance (i.e., body surveillance) and experience negative body-related emotions, such as shame and guilt. These body image processes impact physical activity outcomes, and theoretical tenets suggest by hindering underlying cognitive and motor skills. This study focused on how individuals with relatively lower or higher levels of body surveillance and negative body-related emotions perform on a mental rotation task. Adolescents (n=73; 12-18 years old; 41 females) completed surveys on body surveillance and body-related emotions before completing a hand laterality judgement task (HLJT). In the HLJT, participants were presented with the palmar or dorsal surface of a left or right hand in an upright or upside-down orientation and had to determine if the image was a left or right hand. Consistent with previous literature, RTs were shortest for upright hands (M = 1294, SD = 327 ms) and were longest for upside-down hands (M = 1925, SD = 536 ms). Participants higher in body surveillance had longer overall RTs (M = 1727, 95% CI [1595, 1860] ms) and were more detrimentally affected by the orientation of the hand than participants lower in body surveillance (M = 1517, 95% CI [1385, 1649] ms). Levels of shame and guilt did not affect performance. These data indicate that adolescents who more frequently monitor their appearance are less efficient at performing cognitive tasks that involve the body. These results have implications for adolescents' physical activity experiences.
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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 | 0.001 |
| 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 | 0.000 |
| 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".