Examining the effects of implicit and internalized weight bias on physical activity cognitions for women in larger bodies
Bibliographic record
Abstract
Internalized weight bias occurs when negative perceptions about people in larger bodies are attributed to the self. Women in larger bodies frequently experience and internalize weight bias, which can negatively impact physical activity outcomes. Dual process models suggest that information, like experiences of weight stigma, are processed at two levels: associative and propositional. The purpose of this study was to examine whether internalized weight bias measured at the associative and propositional levels was significantly associated with the tendency to avoid physical activity, the expectation of experiencing weight stigma, and self-regulatory efficacy. Participants (n = 154) were over 18, had a BMI over 25, and self-identified as a woman living in a larger body. Implicit weight bias was measured using a single-category implicit association task, while other variables were measured using validated survey measures. Hierarchical multiple regressions were conducted (step 1: covariates; step 2: implicit weight bias [associative]; step 3: internalized weight bias [propositional]). Both implicit (b = -.285, CI: .13,.44) and internalized weight bias (b = -.205, CI: -.37,-.05) were negatively associated with self-regulatory efficacy in step 3. Contrarily, implicit weight bias was significantly associated with the expectation of experiencing weight stigma (b = .203, CI: -.17,.05) and the tendency to avoid physical activity (b = .148, CI: -.18, 07) in step 2, but became non-significant when internalized weight bias was added in step 3 (b = .737, CI: .62,.85; b = .453, CI: .33,.58). Implicit and internalized weight bias were both associated with physical activity related cognitions. Findings provide insight into factors at the associative and propositional level that may dissuade physical activity participation for women in larger bodies.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.011 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| 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".