Building and strengthening physical activity identity: a theory-informed user-guide
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Physical activity identity, or viewing oneself as a physically active person, reliably predicts physical activity. Yet, little is known about how physical activity identity can be developed or strengthened. In this critical narrative review, we conducted a comprehensive literature search to identify models of physical activity identity, health psychology, behaviour change, identity or self-related constructs in search of explanations, constructs, or insights important for physical activity identity building and strengthening. Identified models included: the physical activity self-definition model, maintain IT, M-PAC, PRIME, possible selves, and self-determination theory. Using content analysis, we identified themes around candidate antecedents of physical activity identity. Nine common physical activity identity inputs were identified that we categorised as behavioural (physical activity; self-regulation; investment), cognitive (perceived ability; imaginal experiences, rules/standards; alignment with goals or values) or social (attachment ties; social appraisals). For each candidate input, we identify which models include the input, consider relevant research, discuss how and why the input may be related to physical activity identity, and offer practical strategies for building or strengthening physical activity identity. We offer a list of theory-informed physical activity identity inputs, a working figure which represents these identity inputs, and suggestions about how they may relate to physical activity identity (directly; indirectly). We aim to support future researchers in advancing the physical activity identity literature, and help practitioners support physical activity behaviour change.
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.
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.003 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.005 | 0.001 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.001 | 0.001 |
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 it