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Record W4415648568 · doi:10.2196/76777

Urban Environment and Outdoor Walking Mobility Among Older Adults With and Without Cognitive Impairment in Singapore: Formative Study

2025· article· en· W4415648568 on OpenAlexvenueno aff
Chek Hooi Wong, Noam Shoval, Moon‐Ho Ringo Ho, Yin Leng Theng

Bibliographic record

VenueJMIR Formative Research · 2025
Typearticle
Languageen
FieldHealth Professions
TopicOlder Adults Driving Studies
Canadian institutionsnot available
FundersNational Research Foundation SingaporeNemzeti Fejlesztési MinisztériumNational Research Foundation
KeywordsSocioeconomic statusFormative assessmentCognitionExploratory researchUrban environmentUrbanizationCognitive impairmentComorbidity

Abstract

fetched live from OpenAlex

Background: There is increasing recognition of the environment's role in shaping cognitive functioning among older adults. Objective: This study aimed to examine the relationship between the outdoor mobility of older adults with and without cognitive impairment and the built environment in 3 urban neighborhoods in Singapore, specifically 3 urban, high-density subzones selected a priori. Methods: Outdoor walking mobility in daily life gait speed (DGS) was collected continuously for 1 week using a previously validated hybrid mobility tracker. Mini-Mental State Examination cut-offs by educational levels were used to differentiate cognitive impairment (CI) and without cognitive impairment (nonCI). The environmental characteristics examined were gross plot ratio and land use. Statistical correlations were used to examine the associations between older adults' outdoor mobility and built environment for all CI and nonCI groups. Two case examples were also used to provide a location-based heatmap on DGS for 3 consecutive days. Results: The overall mean DGS was 0.75m/s (SD 0.12) for the nonCI group and 0.73m/s (SD 0.08) for the CI group. The between-group difference (0.02m/s) was below commonly cited thresholds. Exploratory land-use and zone-specific summaries suggested context-dependent variation, such as residential areas (CI: 0.80m/s and nonCI: 0.62m/s). Higher GPR was associated with faster DGS in the nonCI group (β=0.04, 95% CI 0.01-0.07, P=.04) and slower DGS in the CI group (β=-.13, 95% CI -0.20 to -0.04, P=.01). CI participants spent more time in commercial and business zones than nonCI participants, while both groups spent the majority of walking time in residential areas. However, estimates were based on small subsamples and multiple unadjusted comparisons and should be interpreted as hypothesis-generating. Conclusions: This formative, exploratory study suggests that environmental typologies, particularly GPR and land use, may be associated with differences in mobility patterns between older adults with and without cognitive impairment; subgroup patterns were exploratory and not powered for clinical interpretation. Policy implications include integrating fine-grained environmental metrics into age-friendly urban planning. Clinically, mobility assessments should account for environmental context. Future research should use larger, more diverse, and longitudinal samples to confirm these associations and guide the design of supportive urban environments for cognitively diverse aging populations, noting that findings are context-specific to high-density urban environments. However, given data limitations, unmeasured factors such as comorbidity burden, habitual physical activity, socioeconomic context, and caregiver accompaniment may also contribute to the observed patterns, and findings should be interpreted accordingly.

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 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)0.003
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesScience and technology studies
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.028
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0030.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.001
Science and technology studies0.0020.001
Scholarly communication0.0000.001
Open science0.0000.001
Research integrity0.0000.002
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 head0.037
GPT teacher head0.436
Teacher spread0.399 · 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 teacher head, not a consensus.

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

Citations1
Published2025
Admission routes1
Has abstractyes

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