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Record W2800961273 · doi:10.3390/ijerph15050897

Neighbourhood Built Environment Influences on Physical Activity among Adults: A Systematized Review of Qualitative Evidence

2018· review· en· W2800961273 on OpenAlex
Grazia Salvo, Bonnie Lashewicz, Patricia K. Doyle–Baker, Gavin R. McCormack

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.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.
fundA Canadian funder is recorded on the work.

Bibliographic record

VenueInternational Journal of Environmental Research and Public Health · 2018
Typereview
Languageen
FieldSocial Sciences
TopicUrban Transport and Accessibility
Canadian institutionsUniversity of Calgary
FundersCanadian Institutes of Health Research
KeywordsNeighbourhood (mathematics)Built environmentRecreationSocioeconomic statusQualitative researchWalkabilityEthnic groupUrban designLevel designPedestrianUrban planningPsychologyEnvironmental healthSociologyMedicineEngineeringTransport engineeringPolitical sciencePopulationCivil engineeringSocial scienceComputer science

Abstract

fetched live from OpenAlex

Qualitative studies can provide important information about how and why the built environment impacts physical activity decision-making—information that is important for informing local urban policies. We undertook a systematized literature review to synthesize findings from qualitative studies exploring how the built environment influences physical activity in adults. Our review included 36 peer-reviewed qualitative studies published from 1998 onwards. Our findings complemented existing quantitative evidence and provided additional insight into how functional, aesthetic, destination, and safety built characteristics influence physical activity decision-making. Sociodemographic characteristics (age, sex, ethnicity, and socioeconomic status) also impacted the BE’s influence on physical activity. Our review findings reinforce the need for synergy between transportation planning, urban design, landscape architecture, road engineering, parks and recreation, bylaw enforcement, and public health to be involved in creating neighbourhood environments that support physical activity. Our findings support a need for local neighbourhood citizens and associations with representation from individuals and groups with different sociodemographic backgrounds to have input into neighbourhood environment planning process.

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 imitation

Not 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.

metaresearch head score (Codex)0.013
metaresearch head score (Gemma)0.002
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Other design · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.924
Threshold uncertainty score0.734

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0130.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.002
Scholarly communication0.0000.001
Open science0.0010.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0000.000

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 head0.311
GPT teacher head0.553
Teacher spread0.242 · 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