Built Environment and Physical Activity Evidence Gaps: A Content Analysis of Published Systematic Reviews
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
Abstract There has been a rapid proliferation of systematic reviews exploring associations between the built environment (BE) and physical activity (PA). The objective of this study was to conduct a content analysis to synthesize the most commonly reported evidence gaps and limitations. Using text excerpts from systematic reviews, an inductive qualitative content analysis was conducted to identify and synthesize research gaps. Analysis involved three phases: 1) preparation (open coding using a hierarchical structure – grandparent, parent and child codes), 2) organization (codes applied to excerpts), and 3) interpretation (codes synthesized). From the 176 systematic reviews, 713 text excerpts describing gaps and limitations were extracted. A total of 157 codes were produced. Grandparent codes included BE features ( n = 123 reviews), measurement ( n = 101), PA types or domains ( n = 53), populations and countries ( n = 98), social environment ( n = 49), and study design considerations ( n = 155). The most common BE features gaps included BE measures (e.g., barriers, accessibility, quality), walkability, BE features (e.g., size, safety, aesthetics), green/natural spaces, rural, and active transportation infrastructure. BE features and study designs (experimental/longitudinal) was the most common intersection of evidence gaps. Findings identified a need for research using experimental and longitudinal designs. Most frequently cited gaps pertained to BE measures, walkability, green and natural spaces, rural, and active transportation infrastructure. This study serves to identify important gaps and limitations in previous research to help advance our understanding of what BE features promote PA and for whom.
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 | 0.005 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 it