Examining mobility patterns and social health of older Canadians living at home to inform decision aids about housing
Bibliographic record
Abstract
Context: Older adults’ mobility patterns and social health have not been adequately considered as pivotal considerations in decisions about housing. Objective: Examine mobility patterns and social health of older Canadians living at home to inform decisions about housing options. Methods: Using a mixed-methods study, we recruited a convenience sample of 20 older adults in Quebec and Alberta. Eligibility criteria were: a) aged 65 years or older, b) living autonomously at home or in a senior residence, and c) with outdoor mobility. Data gathered included: i) a sociodemographic, health and quality-of-life survey, ii) GPS tracking, iii) a walking interview, iv) a daily journal, and v) an in-depth interview. We triangulated data to add qualitative dimensions to our quantitative results. Finally, we selected four contrasting participants, 2 in Quebec and 2 in Alberta, to create activity space maps based on GPS data and interpreted them using the other data sources. Results: Out of 25 people approached, 20 participants agreed to participate in the study. Of these, 14 (8 from Alberta and 6 from Quebec) agreed to use GPS trackers and completed the survey, interviews and journals. Maps generated from GPS showed people mostly left home to drive to stores and go for walks. In 14 days, the mean number of trips per person was 10.4 (±5.8). The average distance travelled per person was 186.9 km (±130.4), and average per day was 16.8 km (±29.8). GPS shows the means of transportation was mostly car (n=9) and walking (n=5), while 2 participants used the bus. Daily journals showed that participants typically travelled alone. The interviews showed that their mobility gave them access to important physical assets, among which the 2 most frequently reported were libraries and supermarkets (n=10), and to important social assets, notably family support when desired (n=13) and familiarity with the neighborhood (n=14), contributing to their social health. Winter weather was the most frequently mentioned factor affecting how much or whether participants went out (n=13). Conclusions: In a Canadian cohort of older adults, mobility patterns and existing social and physical assets, such as contact with the neighborhood, made important contributions to their social health and are important to inform decisions about housing options.
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 imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.004 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".