Internet-Based Social Activities and Cognitive Functioning 2 Years Later Among Middle-Aged and Older Adults: Prospective Cohort Study
Bibliographic record
Abstract
Background: A number of studies document the benefits of face-to-face social interactions for cognitive functioning among middle-aged and older adults. Social activities in virtual worlds may confer similar if not enhanced cognitive benefits as face-to-face social activities, given that virtual interactions require the additional cognitive tasks of learning and navigating communicative tools and technology platforms. Yet, few studies have examined whether social activities in internet-based settings may have synergistic effects on cognitive functioning beyond those of face-to-face interactions. Objective: This study examined whether internet-based social activity participation is associated with concurrent and later cognitive functioning, after adjusting for face-to-face social activity participation and sociodemographic covariates. Methods: For cross-sectional analyses, we included 3650 adults aged 50 years and older who completed questions in the 2020 Health and Retirement Study about social activity participation, including specific internet-based social activities such as emailing or accessing social networks. Cognitive functioning was measured using the standardized cognitive tasks assessing working memory, episodic memory, and attention and processing speed. The longitudinal analyses included the 2034 participants who also completed follow-up cognitive assessments in 2022. Results: Our results revealed that those with higher levels of internet-based social activity participation had higher levels of concurrent cognitive functioning than those with low levels of internet-based social activity participation, after adjusting for demographic and health-related factors and face-to-face social activity participation (b=0.44, SE 0.07; P<.001). More internet-based social activity participation also predicted better cognitive functioning 2 years later, even when adjusting for baseline cognitive functioning and other covariates (b=0.35, SE 0.09; P<.001). Conclusions: Our findings suggest that greater engagement in internet-based social activities is associated with higher levels of concurrent cognitive functioning and slower cognitive decline in middle-aged and older adults.
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 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 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| 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".