Personality‐obesity associations are driven by narrow traits: A meta‐analysis
Bibliographic record
Abstract
Obesity has inconsistent associations with broad personality domains, possibly because the links pertain to only some facets of these domains. Collating published and unpublished studies (N = 14 848), we meta-analysed the associations between body mass index (BMI) and Five-Factor Model personality domains as well as 30 Five-Factor Model personality facets. At the domain level, BMI had a positive association with Neuroticism and a negative association with Conscientiousness domains. At the facet level, we found associations between BMI and 15 facets from all five personality domains, with only some Neuroticism and Conscientiousness facets among them. Certain personality-BMI associations were moderated by sample properties, such as proportions of women or participants with obesity; these moderation effects were replicated in the individual-level analysis. Finally, facet-based personality "risk" scores accounted for 2.3% of variance in BMI in a separate sample of individuals (N = 3569), 409% more than domain-based scores. Taken together, personality-BMI associations are facet specific, and delineating them may help to explain obesity-related behaviours and inform intervention designs. Preprint and data are available at https://psyarxiv.com/z35vn/.
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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 | 0.010 | 0.021 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.008 | 0.017 |
| Bibliometrics | 0.002 | 0.004 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| 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".