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Predictors of Older Adults' Technology Use and Its Relationship to Depressive Symptoms and Well-being

186

Citations

49

References

2013

Year

TLDR

The study aims to extend evidence on predictors of older adults’ ICT use and to investigate its link to depressive symptoms and well‑being. Using a cross‑sectional sample of 6,443 community‑dwelling older adults from the National Health and Aging Trends Study, the authors applied structural equation modeling to assess how predictors influence ICT use and how ICT use affects depressive symptoms and well‑being, including moderation by demographics and use level. Socioeconomic status, age, and cognitive function explained about 60 % of ICT‑use variance, with SES more predictive for Blacks/African Americans and cognition for Whites; ICT use itself was not directly related to depressive symptoms or well‑being but moderated the impact of ADL limitations and ill‑health on depression, suggesting no direct mental‑health benefit but potential protective effects for those with health conditions beyond ADL impairments.

Abstract

To extend the empirical evidence regarding the predictors of older adults' use of information and communications technology (ICT) and to further examine its relationship to depressive symptoms and well-being. This cross-sectional study utilized a sample of community-dwelling older adults from the National Health and Aging Trends Study (N = 6,443). Structural equation modeling was used to estimate the effects of predictor variables on ICT use and the effects of use on depressive symptoms and well-being. Tests of moderation by demographic characteristics and level of ICT use were also performed. Socioeconomic status (SES), age, and cognitive function accounted for approximately 60% of the variance in ICT use. SES was a stronger predictor for Blacks/African Americans, whereas cognitive function was a stronger predictor for Whites. ICT use was unrelated to depressive symptoms or well-being. However, it acted as a moderator, such that limitations in activities of daily living (ADLs) was a stronger predictor of depressive symptoms for high ICT users, whereas ill-health was a stronger predictor for non/limited users. Findings do not support the claim that ICT use directly enhances mental health or well-being among older adults although it may protect against depressive symptoms for individuals coping with health conditions other than ADL impairments.

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