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Record W4285728787 · doi:10.1017/s0714980822000241

Indoor Built Environment and Older Adults’ Activity: A Systematic Review

2022· review· en· W4285728787 on OpenAlexafffund
Farah Tabassum Azim, Patrocinio Ariza‐Vega, Paul A. Gardiner, Maureen C. Ashe

Bibliographic record

VenueCanadian Journal on Aging / La Revue canadienne du vieillissement · 2022
Typereview
Languageen
FieldSocial Sciences
TopicUrban Transport and Accessibility
Canadian institutionsUniversity of British Columbia
FundersCanada Research Chairs
KeywordsBuilt environmentPhysical activityLevel designSituatedInclusion (mineral)GerontologyPsychologyApplied psychologyEnvironmental healthMedicineComputer scienceEngineeringMultimediaPhysical medicine and rehabilitationSocial psychology

Abstract

fetched live from OpenAlex

Although the physical environment can influence people's activity, there are few knowledge syntheses for indoor environments and older adults' daily life routines. Therefore, we conducted a systematic review of peer-reviewed evidence to inform future research and practice. Inclusion criteria were studies with any research designs, across all years and languages focused on older adults 60 years of age or more, on physical activity/sedentary behaviour and the indoor environment. After searching five databases, two authors completed title/abstract and full-text screening. The last search was on December 19, 2020. We screened 1,367 citations, and included 23 studies situated in private or collective dwellings (e.g., assisted living). We identified physical activity-supportive indoor features across three domains: campus (e.g., amenities, pathways), building (e.g., area, floor level), and fixtures (e.g., elevators, hallways). Knowledge of indoor environmental factors for older adults' engagement in daily activities can guide future research and policy on housing design.

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)0.006
metaresearch head score (Gemma)0.029
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Systematic review · Consensus signal: Systematic review
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.016
Threshold uncertainty score0.032

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0060.029
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0060.005
Bibliometrics0.0100.013
Science and technology studies0.0010.001
Scholarly communication0.0030.002
Open science0.0010.002
Research integrity0.0020.001
Insufficient payload (model declined to judge)0.0050.000

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 head0.024
GPT teacher head0.265
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

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 designSystematic review
Domainnot available
GenreReview

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

Citations11
Published2022
Admission routes2
Has abstractyes

Explore more

Same venueCanadian Journal on Aging / La Revue canadienne du vieillissementSame topicUrban Transport and AccessibilityFrench-language works237,207