Disability Risk and Everyday Technology Use Among Older Adults in an Urban Area

PURPOSE: Health professionals, including occupational therapy practitioners, assess disability risk among older adults with screens such as the Brief Risk Identification for Geriatric Health Tool (BRIGHT). While less disability risk has been associated with factors such as higher perceived health, higher cognitive status, higher activity engagement, and younger age, little is known about associations between everyday technology use and disability risk. Use of everyday technologies, e.g., smartphones, computers, health monitors, is increasingly necessary to participate in activities within the home and community. In addition to addressing perceived health, cognitive status, and activity engagement to minimize disability risk, practitioners offer expertise in addressing the use of everyday technologies. Higher ability to use everyday technologies may facilitate the ability of all individuals, including older adults, to participate in activites that promote well-being and minimize disability risk. Therefore, this study aimed to investigate which factors, including everyday technology use, predict disability risk among older adults in an urban area.

DESIGN: This was a cross-sectional study based on a volunteer sample of 112 older adults in an urban area.

METHOD: We applied a Poisson regression model to predict disability risk (BRIGHT) based on each participant's ability to use everyday technologies and number of everyday technologies used with the Everyday Technology Use Questionnaire (ETUQ), perceived physical health and perceived mental health with the Patient-Reported Outcome Measurement Information System (PROMIS) Global Health form, cognitive status with the Montreal Cognitive Assessment (MoCA), activity engagement with the Frenchay Activities Index (FAI), and age. To further evaluate the strength of associations between disability risk and predictor variables, we analyzed Spearman correlation coefficients.

RESULTS: For every additional point in ability to use everyday technologies, disability risk decreased by a factor of .95, 95% confidence interval (CI) [.92, .98], p < .001. For every additional point in perceived mental health reported, disability risk decreased by a factor of .97, 95% CI [.94, 1.00], p < .01. For every additional point in activity engagement, disability risk decreased by a factor of .94, 95% CI [.90, .99], p < .01. For every additional point in perceived physical health reported, disability risk decreased by a factor of .97, 95% CI [.94, 1.00], p < .05. Cognitive status, number of everyday technologies used, age, and number of self-reported functional limitations were not significant predictors of disability risk. Analyses of Spearman correlation coefficients indicated that ability to use everyday technologies (r _s = -.38, p < .001), perceived mental health (r _s = -.36, p < .001), and perceived physical health (r _s = -.28, p < .01) were the most strongly associated with less disability risk.

CONCLUSION: Ability to use everyday technologies was both the most significant predictor of and most strongly associated with disability risk among our sample of older adults in an urban area. Because everyday technology use is increasingly required to participate in the activities of the home and community, older adults with higher ability to use everyday technologies may enjoy greater well-being and reduced disability risk. Therefore, practitioners may consider assessment of everyday technology use to complement assessments of other factors that predict disability risk in the community.

IMPACT STATEMENT: This finding adds to a growing body of evidence that suggests practitioners may consider addressing everyday technology use among older adults to facilitate participation and complement other screens for disability risk.

References

Damant, J., Knapp, M., Freddolino, P., & Lombard, D. (2017). Effects of digital engagement on the quality of life of older people. Health & Social Care in the Community, 25(6), 1679–1703. https://doi.org/10.1111/hsc.12335

Park, S., Han, Y., Kim, B., & Dunkle, R. E. (2017). Aging in place of vulnerable older adults: Person–environment fit perspective. Journal of Applied Gerontology, 36(11), 1327–1350. https://doi.org/10.1177/0733464815617286

Satariano, W. A., Scharlach, A. E., & Lindeman, D. (2014). Aging, place, and technology: Toward improving access and wellness in older populations. Journal of Aging and Health, 26(8), 1373–1389. https://doi.org/10.1177/0898264314543470

Walsh, R., Drasga, R., Lee, J., Leggett, C., Shapnick, H., & Kottorp, A. (2018). Activity engagement and everyday technology use among older adults in an urban area. American Journal of Occupational Therapy, 72(4), 7204195040p1-7. https://doi.org/10.5014/ajot.2018.031443