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Record W6981715143

Examining the effects of implicit and internalized weight bias on physical activity participation for women in larger bodies

2024· other· en· W6981715143 on OpenAlexaff

Bibliographic record

VenueBrock University Digital Repository (Brock University) · 2024
Typeother
Languageen
FieldAgricultural and Biological Sciences
TopicPlant Taxonomy and Phylogenetics
Canadian institutionsBrock University
Fundersnot available
KeywordsWeight stigmaPerceptionImplicit attitudeStigma (botany)Implicit-association testMultilevel modelAssociation (psychology)Implicit biasPhysical activity
DOInot available

Abstract

fetched live from OpenAlex

Weight stigma represents discrimination associated with the social beliefs that people in larger bodies have low willpower, are unmotivated, and are personally responsible for their elevated weight. Internalized weight stigma is the extent to which social perceptions of weight stigma are attributed to the self by people in larger bodies. Dual process models may be uniquely situated to help us understand how weight stigma becomes internalized and whether this impacts (physical activity) PA participation. Within dual process models two systems regulate how we think; the associative system reflects automatic associations and feelings, whereas the propositional system represents deliberate and controlled reasoning. Past research has examined social perceptions of explicit weight stigma alongside implicit measures, rather than examining the internalized form of weight bias. The purpose of this study was to examine whether implicit weight bias (an associative process) and internalized weight bias (a propositional process) are significantly associated with the expectation of experiencing weight stigma, self-regulatory efficacy, the tendency to avoid PA, PA intention, and PA. All eligible participants (n = 154) were over 18, self identified as a woman, had a BMI over 25 and self-identified as a person living in a larger body. Implicit weight bias was measured using a single category Implicit Association Test, while the other study variables were measured using validated survey measures. We conducted a series of hierarchical multiple regression analysis, entering covariates in step 1, implicit weight bias in step 2, and internalized weight bias in step 3. In step 3, both implicit and internalized weight bias were significantly associated with self-regulatory efficacy (p <.001, r2 = .183) and light past PA (p < .05, r2 = .065). Contrarily, the expectation of experiencing weight stigma (p <.05, r2 =.120) and the tendency to avoid PA (p <.001, r2 = .297) were both significantly associated with implicit weight bias in step 2. However, once internalised weight bias was added into the equation in step 3, the implicit association became not significant. No relationship was observed between PA intention, implicit weight bias and internalized weight bias. Similarly, there was no relationship observed between moderate to vigorous physical activity, implicit weight bias and internalized weight bias (p > .05). Implicit weight bias and explicitly measured internalized weight bias were associated with psychological cognitions that may deter PA. They seemed to be more strongly related to cognitions than behaviours, which might suggest that they have indirect relationships with PA. Examining both implicit and internalized weight bias together, through a dual process lens provided insight into the nuanced relationship that people in larger bodies have with PA participation. Future health promotion strategies should consider these findings and must work to shift away from their weight centric approach that may exacerbate internalized weight bias and instead, adopt a more weight-neutral approach towards PA participation.

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 imitation

Not 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.

metaresearch head score (Codex)0.003
metaresearch head score (Gemma)0.011
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.008
Threshold uncertainty score0.016

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0030.011
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0000.000
Science and technology studies0.0010.001
Scholarly communication0.0010.001
Open science0.0000.001
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0040.000

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.

Opus teacher head0.022
GPT teacher head0.199
Teacher spread0.177 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

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".

Quick stats

Citations0
Published2024
Admission routes1
Has abstractyes

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