Activity Engagement and Everyday Technology Use Among Older Adults in an Urban Area
Bibliographic record
Abstract
OBJECTIVE: We investigated associations among activity engagement (AE), number of available and relevant everyday technologies, ability to use everyday technologies, and cognitive status among older adults in an urban area. METHOD: This cross-sectional study included 110 participants and used three assessments: the Frenchay Activities Index to measure AE, the Everyday Technology Use Questionnaire to measure the number of and ability to use available and relevant everyday technologies, and the Montreal Cognitive Assessment to measure cognitive status. Data analyses used a one-way analysis of variance and a multiple linear regression model. RESULTS: The number of available and relevant everyday technologies was significantly different (p < .001) among groups that varied in level of AE. Ability to use everyday technologies did not significantly differ among groups. Cognitive status did not explain level of AE when the number of available and relevant everyday technologies was considered. CONCLUSION: Increasing the accessibility of available and relevant everyday technologies among older adults in an urban area may increase AE.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".