Background: Little is known about the long-term cognitive impact of internet usage among older adults. This research characterized the association between various measures of internet usage and dementia.
Methods: We followed dementia-free adults aged 50-64.9 for a maximum of 17.1 (median = 7.9) years using the Health and Retirement Study. The association between time-to-dementia and baseline internet usage was examined using cause-specific Cox models, adjusting for delayed entry and covariates. We also examined the interaction between internet usage and education, race-ethnicity, sex, and generation. Furthermore, we examined whether the risk of dementia varies by the cumulative period of regular internet usage to see if starting or continuing usage in old age modulates subsequent risk. Finally, we examined the association between the risk of dementia and daily hours of usage. Analyses were conducted from September 2021 to November 2022.
Results: In 18,154 adults, regular internet usage was associated with approximately half the risk of dementia compared to non-regular usage, CHR (cause-specific hazard ratio) = 0.57, 95% CI = 0.46-0.71. The association was maintained after adjustments for self-selection into baseline usage (CHR = 0.54, 95% CI = 0.41-0.72) and signs of cognitive decline at the baseline (CHR = 0.62, 95% CI = 0.46-0.85). The difference in risk between regular and non-regular users did not vary by educational attainment, race-ethnicity, sex, and generation. In addition, additional periods of regular usage were associated with significantly reduced dementia risk, CHR = 0.80, 95% CI = 0.68-0.95. However, estimates for daily hours of usage suggested a U-shaped relationship with dementia incidence. The lowest risk was observed among adults with 0.1-2 h of usage, though estimates were non-significant due to small sample sizes.
Conclusions: Regular internet users experienced approximately half the risk of dementia than non-regular users. Being a regular internet user for longer periods in late adulthood was associated with delayed cognitive impairment, although further evidence is needed on potential adverse effects of excessive usage.
Download full-text PDF |
Source |
---|---|
http://dx.doi.org/10.1111/jgs.18394 | DOI Listing |
J Med Internet Res
January 2025
Department of Neurosurgery, Xijing Hospital, Fourth Military Medical University, Xi'an, China.
Background: Delayed cerebral ischemia (DCI) is a primary contributor to death after subarachnoid hemorrhage (SAH), with significant incidence. Therefore, early determination of the risk of DCI is an urgent need. Machine learning (ML) has received much attention in clinical practice.
View Article and Find Full Text PDFJ Med Internet Res
January 2025
Hills Joint Research Laboratory for Future Preventive Medicine and Wellness, Keio University School of Medicine, Tokyo, Japan.
J Med Internet Res
January 2025
Medical Information Department, Civil Hospices of Lyon, Lyon, France.
J Med Internet Res
January 2025
Division of Nephrology and Endocrinology, The University of Tokyo, Tokyo, Japan.
J Med Internet Res
January 2025
Department of Basic and Community Nursing, School of Nursing, Nanjing Medical University, NanJing, China.
Background: Telehealth interventions can effectively support caregivers of people with dementia by providing care and improving their health outcomes. However, to successfully translate research into clinical practice, the content and details of the interventions must be sufficiently reported in published papers.
Objective: This study aims to evaluate the completeness of a telehealth intervention reporting in randomized controlled trials (RCTs) conducted for caregivers of people with dementia.
Enter search terms and have AI summaries delivered each week - change queries or unsubscribe any time!