Internet Use and Higher-Level Functional Capacity Decline Suppression in Japanese Older Adults With Low Education: JAGES 2016-2019 Longitudinal Study
Bibliographic record
Abstract
BACKGROUND: Higher-level functional capacity (HLFC) is crucial for the independent living of older adults. While internet use positively impacts the health of older adults, its effect on HLFC and how this effect varies with educational attainment remains uncertain. OBJECTIVE: This longitudinal study aimed to investigate whether internet use could mitigate the risk of HLFC decline and if this benefit extends to older adults with lower levels of education. METHODS: The data were sourced from the Japan Gerontological Evaluation Study (JAGES), encompassing 8050 community-dwelling adults aged 65 years and older from 2016 to 2019. The study focused on those who remained self-sufficient from 2016 to 2019, identifying participants with independent HLFC in 2016. The Tokyo Metropolitan Institute of Gerontology Index of Competence defined HLFC operationally, consisting of 3 subscales, namely instrumental activities of daily living, intellectual activity, and social role. The primary variable was the frequency of internet use in 2016; participants who reported using the internet were classified as internet users, while those who answered "No" were identified as nonusers. The study compared the effects of internet use on HLFC decline across educational levels of ≤9 years, 10-12 years, and ≥13 years using Poisson regression analysis adjusted for robust SE to calculate the risk ratio (RR) and 95% CI for HLFC decline in 2019. RESULTS: After adjusting for demographic and health condition risk factors, internet use was significantly linked to a decreased risk of HLFC decline in older adults over 3 years, including those with lower educational levels. Internet users with ≤9 years of educational attainment experienced a suppressed decline in the total score (RR 0.57, 95% CI 0.43-0.76; P<.001); instrumental activities of daily living (RR 0.58, 95% CI 0.38-0.91; P=.02), intellectual activity (RR 0.60, 95% CI 0.41-0.89; P=.01), and social role (RR 0.74, 95% CI 0.56-0.97; P=.03) compared with nonusers. Participants with 10-12 years of education showed suppression rates of 0.78 (95% CI 0.63-0.98; P=.03), 0.59 (95% CI 0.39-0.90; P=.01), 0.91 (95% CI 0.63-1.31; P=.61), and 0.82 (95% CI 0.68-1.00; P=.05), respectively, and those with ≥13 years displayed suppression rates of 0.65 (95% CI 0.51-0.85; P=.001), 0.55 (95% CI 0.36-0.83; P=.01), 0.64 (95% CI 0.37-1.10; P=.11), and 0.83 (95% CI 0.64-1.08; P=.17), respectively. CONCLUSIONS: These findings indicate that internet use supports the maintenance of HLFC independence in older adults with higher education and those with lower educational levels. Encouraging internet use among older adults with lower levels of education through future policies could help narrow functional health disparities associated with educational attainment.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".