Joint associations of smartphone use and gender on multidimensional cognitive health among community-dwelling older adults: a cross-sectional study
Bibliographic record
Abstract
BACKGROUND: Smartphone use has become an increasingly pervasive part of our daily lives, and as a portable media device, smartphones provide good support for cognitive training during aging. However, little is known about the joint association of smartphone use and gender on the cognitive health of older adults, particularly with regard to multi-domain cognition. METHODS: A face-to-face survey of 3230 older adults aged 60+ years was conducted in Xiamen, China, in 2016. The Montreal Cognitive Assessment (MoCA) score was used to measure both general and multi-domain cognition. Smartphone use was self-reported and the number of the smartphone functions used (NSFU) was classified as 0, 1, and 2+. General and subdomain cognitive functions were modelled on NSFU only, gender only, and NSFU and gender combined by using a series of proportional-odds cumulative logit models. Furthermore, joint associations of gender and NSFU on both general and multi-domain cognition were estimated, and a four-category quantile classification was used to evaluate the total MoCA score. RESULTS: Among all 3230 respondents, 2600 remained after exclusion of respondents with very low MoCA scores (below the education-adjusted cut-offs for dementia). Only 29.96% of older adults used smartphones, 473 (60.72%) of which were men. Respondents who had a higher NSFU maintained a better general and sub-domain cognition except for memory and orientation. Although women had lower values compared to men in visuospatial ability (OR (95% CI): 0.46 (0.37-0.57)), they outperformed their male counterparts in memory (OR (95% CI): 1.38 (1.10-1.73)). The results of the joint association showed that women's inferiority in visuospatial ability diminished when they had a NSFU of 2+. However, a significantly better improvement in memory for male was achieved when they had a NSFU of 1 rather than 2 + . CONCLUSIONS: A higher NSFU was positively associated with increased general and partial subdomain cognitive functions. However, gender differences were found in visuospatial ability and memory, which could be alleviated by smartphone use.
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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 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| 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".