Risky Driving Behaviors for Older Adults: Differences by Veteran's Status

Driver Rehabilitation Utilization and Need Among Community-Dwelling Older Adults

IMPORTANCE

Driving is one of the most important instrumental activities of daily living. As adults age, many face challenges with maintaining independent driving, leading to risk for decreased occupational engagement and quality of life. The extent to which occupational therapy services meet the driver rehabilitation needs of older adults is unknown.

OBJECTIVE

To characterize driver rehabilitation service utilization among a nationally representative sample of community-dwelling older adults.

DESIGN

Exploratory, descriptive cross-sectional study using the National Health and Aging Trends Study 2016 wave.

PARTICIPANTS

Community-dwelling adults age 65 and older who received rehabilitation services in the past year (N = 1,173).

OUTCOMES AND MEASURES

Sociodemographic information, comorbidities, rehabilitation use, community mobility, and participation restrictions were collected using self-report and performance-based measures.

RESULTS

Of this sample of older adults, 63.0% reported driving as their primary mode of transportation, 25.8% reported limitations in community participation related to transportation, and 9.2% reported having received rehabilitation focused on driving or other transportation goals in the past year. Findings from this study suggest a discrepancy between utilization of driver rehabilitation and self-reported need.

CONCLUSIONS AND RELEVANCE

Many older adults reported limitations in community participation for transportation-related reasons, yet driver rehabilitation represented only a small proportion of services used. As experts in driver rehabilitation, occupational therapy practitioners should lead the way in advocating for increased utilization of driver rehabilitation and development of innovative, accessible transportation options to promote community mobility and participation among older adults.

WHAT THIS ARTICLE ADDS

The results of this study illustrate an important discrepancy between self-reported need for and utilization of driver rehabilitation services. Occupational therapy practitioners can play an important role in meeting older adults' driving and transportation needs to enable them to fully participate in their community and daily routines.

Driving Behaviors 2-3 Years After Traumatic Brain Injury Rehabilitation: A Multicenter Case-Control Study

Introduction: Driving an automobile is an important activity for the social participation of individuals with traumatic brain injury (TBI). Return to safe driving is usually addressed during rehabilitation, but we know little about driving behaviors in the years following TBI rehabilitation.

Objective: To explore self-reported and objective (official driving records) post-rehabilitation driving behaviors and offenses in individuals with TBI: (a) having passed a driving evaluation, (b) who did not undergo a driving evaluation, and (c) non-injured controls.

Methods: Cross-sectional design with 162 adults: (a) 48 participants with mild, moderate, or severe TBI whose drivers' license was suspended and reinstated following a driving evaluation during rehabilitation (TBI-DE; M = 42.2 years of age, SD = 11.5); (b) 24 participants with TBI who maintained their driving privileges without undergoing a driving evaluation (TBI-NE; M = 36.5 years of age, SD = 9.9); (c) 90 non-injured controls (M = 43.8 years of age, SD = 11.4). Participants with TBI were recruited from seven rehabilitation centers, 2–3 years after the end of rehabilitation in the province of Quebec, Canada. During a telephone interview, data were obtained regarding self-reported driving: (a) habits; (b) self-efficacy; (c) anger expression; (d) sensation-seeking; (e) violations/errors; (f) accidents, driving offenses, and demerit points for the two-year interval predating the study. Objective data for driving offenses, accidents, and demerit points were obtained from the automobile regulatory body for the same period and for the two-year interval before the injury for the TBI groups.

Results: Compared to non-injured controls, the TBI-DE group reported significantly lower scores for self-reported verbal aggressive expression of anger and driving violations/errors. Conversely, their official driving records showed significantly more demerit points for the last 2 years, and a significantly higher frequency of serious post-rehabilitation accidents (10), compared to the TBI-NE group (one) and the control group (none). Compared to pre-injury levels, individuals with TBI had significantly more demerit points post-rehabilitation.

Conclusions: Individuals with TBI may underestimate risky driving behaviors even if they have been deemed fit to drive. Reduced self-awareness, memory, and dysexecutive problems following TBI could influence self-report of driving behaviors and explain discrepancies between self-reported and objective driving-related behaviors. Recommendations for research and practice are provided.

Electronic Health Record-Based Screening for Substance Abuse

Existing methods of screening for substance abuse (standardized questionnaires or clinician's simply asking) have proven difficult to initiate and maintain in primary care settings. This article reports on how predictive modeling can be used to screen for substance abuse using extant data in electronic health records (EHRs). We relied on data available through Veterans Affairs Informatics and Computing Infrastructure (VINCI) for the years 2006 through 2016. We focused on 4,681,809 veterans who had at least two primary care visits; 829,827 of whom had a hospitalization. Data included 699 million outpatient and 17 million inpatient records. The dependent variable was substance abuse as identified from 89 diagnostic codes using the Agency for Healthcare Quality and Research classification of diseases. In addition, we included the diagnostic codes used for identification of prescription abuse. The independent variables were 10,292 inpatient and 13,512 outpatient diagnoses, plus 71 dummy variables measuring age at different years between 20 and 90 years. A modified naive Bayes model was used to aggregate the risk across predictors. The accuracy of the predictions was examined using area under the receiver operating characteristic (AROC) curve in 20% of data, randomly set aside for the evaluation. Many physical/mental illnesses were associated with substance abuse. These associations supported findings reported in the literature regarding the impact of substance abuse on various diseases and vice versa. In randomly set-aside validation data, the model accurately predicted substance abuse for inpatient (AROC = 0.884), outpatient (AROC = 0.825), and combined inpatient and outpatient (AROC = 0.840) data. If one excludes information available after substance abuse is known, the cross-validated AROC remained high, 0.822 for inpatient and 0.817 for outpatient data. Data within EHRs can be used to detect existing or predict potential future substance abuse.