Research on older adults
I recently found two articles about older adults that I found intriguing. First, Fenton, Smail, Lin, Striley & Kaufmann (2024) published “Associations between Driving Cessation and Mental Health among Rural and Urban Older Adults” in Journal of Rural Mental Health. Here are the edited abstract and impact statements:
Driving cessation is robustly associated with poor mental health outcomes among older adults; however, the magnitude of this relationship may differ by rurality. This study examined cross-sectional and longitudinal associations between driving cessation and life satisfaction and depressive symptoms and assessed whether these relationships were moderated by rurality. Data is from participants in the 2014 and 2016 Health and Retirement Study (Mage = 73; 58% female) with information on either depressive symptoms (n = 5,650) or life satisfaction (n = 1,931). Multivariate linear regression models were built to test whether rurality moderated the relationship between driving status and two mental health outcomes (life satisfaction and depressive symptoms). Models tested (1) unadjusted associations and (2) associations adjusted for age, gender, race/ethnicity, years of education, partnership status, current employment, and number of chronic conditions. We found that limited driving and inability to drive were significantly associated (p < .05) with worse cross-sectional life satisfaction; however, there were no significant longitudinal associations for this relationship. Driving status was significantly associated (p < .05) with heightened cross-sectional and longitudinal depressive symptoms. No moderation by rurality was observed in both unadjusted and adjusted models (p > .05). Findings support the importance of policy and programming to support the mental health of older adults across the rural–urban continuum as they experience limitations in their driving ability.
This study suggests that when older adults limit or cease driving, their mental health suffers, especially in the short term. This relationship is similar for both rural and urban older adults, suggesting that more counseling and intervention are needed across the United States to prevent mental health concerns following driving cessation.
This is a huge data sample and helpful research. I like the fact that they didn’t confirm the expectation that rural adults would suffer more. Since the data were collected before the COVID pandemic, it can’t explain the findings. I wonder if loneliness and isolation has become more common in urban settings since the longitudinal data finds impacts on depression. The next study also attempts to make a prediction. Lin & Allen (2024) published “Greater Baseline Intra-individual Variation in Telephone-based Cognitive Screening Predicts Cognitive and Diagnostic Outcomes at 2-year Follow-up” in Neuropsychology. The edited abstract and impact statements:
Intra-Individual Cognitive Variability (IICV) is an emerging clinical tool that has shown promise in predicting cognitive decline and dementia incidence. The present study aims to assess the predictive validity of IICV in remote cognitive screening tests, using nationally representative data. Two waves of cognitive and diagnostic data from the Health and Retirement Study (collected in 2010 and 2012) were utilized to investigate whether baseline IICV can predict cognitive decline and dementia pathology. Middle-aged and older adults who were cognitively intact and completed all cognitive tests at both baseline and follow-up were recruited in the study, resulting in a sample of 6,050 participants. With the coefficient of variation method, the IICV–dispersion was calculated based on cognitive screeners to predict follow-up mean cognitive performance, global cognition, suspected cognitive impairment, and self-reported dementia diagnosis. After accounting for demographics, depressive symptoms, and baseline cognitive performance, the results provide support for the predictive validity of IICV. Specifically, the study demonstrated that IICV–dispersion significantly predicted cognitive and diagnostic outcomes in a concave pattern where the prediction was more sensitive toward the higher end of IICV. IICV explained about 0.2%–2.3% of the variance of outcomes variables. IICV retrieved from cognitive screening tests in telemedicine settings offers insight into future cognitive functioning and neurocognitive diagnostic status, which can be cost-effective and reduce the burden on both patients and health care providers, especially benefitting individuals with low socioeconomic status and rural residents.
Does Intra-Individual Cognitive Variability (IICV) based on virtual cognitive screening tests predict follow-up cognitive decline, dementia diagnosis, and suspected mild cognitive impairment? Baseline IICV–dispersion significantly predicted cognitive and diagnostic outcomes 2 years later within the context of baseline cognitive performance, demographics, and depressive symptoms. Importance: The present study lends support to the use of IICV in clinical settings and provides initial evidence for the application of IICV within teleneuropsychology. Future directions include establishing normative comparison data, exploring the potential moderating effect of demographic factors in more diverse samples, examining the impact of intersectional identities and multiple cognitive risk factors, and investigating longitudinal cognitive decline across multiple time points.
This time, I like the finding that a telemedicine approach measuring cognitive variability predicts later decline and impairment. It’s a huge sample and uses wise controls. Both studies emphasize the value of interventions with older adults.