There are no short-term longitudinal associations among interoceptive accuracy, external body orientation, and body image dissatisfaction
Bibliographic record
Abstract
Background: Objectification theory assumes that individuals with low level of interoceptive accuracy may develop an external orientation for information concerning their body. Past research has found associations between interoceptive accuracy and body image concerns. We aimed to explore temporal relationships between the tendency to monitor one's body from a third-party perspective, body image dissatisfaction, and interoceptive accuracy. Method: In a short longitudinal research, 38 Hungarian and 59 Norwegian university students completed the Schandry heartbeat tracking task and filled out baseline and follow-up questionnaires assessing private body consciousness, body surveillance, and body image dissatisfaction 8 weeks apart. Results: Interoceptive accuracy and indicators of external body orientation did not predict body image dissatisfaction after controlling for gender, nationality, and body image dissatisfaction at baseline. Similarly, body surveillance was not predicted by baseline levels of interoceptive accuracy and body image dissatisfaction. Conclusion: Contrary to the tenets of objectification theory, body image dissatisfaction and body surveillance are not predicted by interoceptive accuracy over a short period of time among young individuals.
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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 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".