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Record W7054530625

ACCEPTABILITY OF BUILT ENVIRONMENT INTERVENTIONS AIMED AT PROMOTING A HEALTHY DIET AND PHYSICAL ACTIVITY IN URBAN NEIGHBOURHOODS OF SASKATCHEWAN, CANADA

2022· dissertation· en· W7054530625 on OpenAlexaboutno aff

Bibliographic record

VenueUniversity Library (University of Saskatchewan) · 2022
Typedissertation
Languageen
FieldEngineering
TopicLaser Design and Applications
Canadian institutionsnot available
Fundersnot available
KeywordsPsychological interventionBuilt environmentIntrusivenessPhysical activityPublic healthPhysical activity levelSample (material)Level designNeighbourhood (mathematics)
DOInot available

Abstract

fetched live from OpenAlex

Background: Physical activity and diet play a critical role in the primary and secondary prevention of several chronic diseases. In Saskatchewan, 35% of adults are reported to be obese, which is partly attributable to physical inactivity and an unhealthy diet. In addition, individuals living in urban areas are faced with an increased risk of an unhealthy lifestyle due to the structure of the built environment (BE). Regardless, attempts to transform BE have met with mixed results. An essential contributor to the heterogeneity found in the success of the BE interventions is ‘public acceptability’. However, current knowledge about the acceptability of diverse BE interventions is limited. Additionally, information on how individual and neighbourhood-level factors influence acceptability is lacking. Purpose: The purpose of this study was to estimate the current level of public acceptability of diverse built environment interventions varying in intrusiveness that support healthy eating and physical activity in Saskatoon and Regina and to identify individual and neighbourhood-level factors associated with the level of acceptability of diverse interventions. Method: This study used a subset of data from “THEPA” - Targeting Healthy Eating & Physical Activity: Citizens' perspectives, with linkage to respondents’ neighbourhood-level factors using data from the Canadian Urban Environmental Health Research Consortium (CANUE). A sample of 2133 respondents was analysed using multi-level logistic regression. Missing observations were treated by multiple imputation procedure. Outcome variables were ‘agreement’ to implement 12 and 26 BE interventions related to food and physical activity. Independent variables were individual and neighbourhood-level factors. Interventions were ordered according to the level of intrusiveness as per Nuffield’s intervention ladder. iii Results: Overall, individuals were more agreeable to implementing the least intrusive interventions in both the food and physical activity domain; even so, the public support differed by the type of intervention. In addition, the likelihood of support across different levels of the intervention varied by gender, immigration status, Indigenous status, employment, education, and neighbourhood ethnic concentration. Notably, women showed a higher likelihood of support for all levels of interventions. However, no strong relationship between neighbourhood-level attributes and acceptability was detected. Conclusion: Individual factors strongly influence public acceptability, and the degree of support varies for different levels of intrusion. This study provides previously lacking evidence on the acceptability of diverse BE interventions, the influence of intervention intrusion, and individual and neighbourhood attributes on acceptability. Further investigation, including the individuals’ lived experiences, is needed for better understanding of the variations observed.

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)0.009
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 score0.032
Threshold uncertainty score0.230

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0030.009
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0010.001
Science and technology studies0.0030.001
Scholarly communication0.0020.000
Open science0.0010.002
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0020.000

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 head0.008
GPT teacher head0.187
Teacher spread0.180 · 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
Published2022
Admission routes1
Has abstractyes

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