Traffic violations versus driving errors of older adults: informing clinical practice.

Certain driving errors are predictive of crashes, but whether the type of errors evaluated during on-road assessment is similar to traffic violations that are associated with crashes is unknown. Using the crash data of 5,345 older drivers and expert reviewers, we constructed a violation-to-error classification based on rater agreement. We examined the effects of predictor variables on crash-related injuries by risk probability using logistic regression. Drivers' mean age was 76.08 (standard deviation = 7.10); 45.7% were women. Of drivers, 44.6% sustained crash-related injuries, and female drivers had a higher injury probability (44%) than male drivers (29%). Lane maintenance, yielding, and gap acceptance errors predicted crash-related injuries with almost 50% probability; speed regulation (34%), vehicle positioning (25%), and adjustment-to-stimuli (21%) errors predicted crash-related injuries to a lesser degree. We suggest injury prevention strategies for clinicians and researchers to consider for older drivers, especially older women.

Validity and critical driving errors of on-road assessment for older drivers.

OBJECTIVES: We examined the validity of our on-road driving assessment to quantify its outcomes. METHOD: Older drivers (N = 127) completed a driving assessment on a standardized road course. Measurements included demographics, driving errors, and driving test outcomes; a categorical global rating score (pass-fail); and the sum of maneuvers (SMS) score (0-273). RESULTS: There were significant differences in the SMS (F = 29.9, df = 1, p < or = .001) between drivers who passed the driving test and those who failed. The SMS cutoff value of 230 points was established as the criterion because it yielded the most optimal combination of sensitivity (0.91) and specificity (0.87). The strongest predictors of failure were adjustment to stimuli and lane maintenance errors. CONCLUSION: The SMS differentiated between passing and failing drivers and can be used to inform clinical decision making.

Person-vehicle-environment interactions predicting crash-related injury among older drivers.

OBJECTIVE: The object of this research was to identify interactions among person, vehicle, and environment factors associated with crashes and injuries among older drivers. METHOD: We quantified risk factors and interactions for 5,744 drivers. RESULTS: Women had a high crash risk during mornings (8:00 a.m.-1:00 p.m.; odds ratio [OR] = 1.73, confidence interval [CI] = 1.40-2.14) or afternoons (2:00 p.m.-8:00 p.m.; OR = 1.74, CI = 1.41-2.15); alcohol-related crashes were the least likely to occur during mornings (OR = 0.19, CI = 0.12-0.31). The greatest crash risk with another vehicle occurred during afternoons (OR = 3.89, CI = 2.41-5.05). Injury had interactions with fixed-object crashes (OR = 427, CI = 182.9-998.24), no seatbelt (OR = 5.69, CI = 3.90-8.29), female gender (OR = 1.54, CI = 1.67-1.92), and mornings (OR = 1.40, CI = 1.01-1.94). CONCLUSION: An opportunity for crash and injury prevention research and shaping longer-range evaluation policies emerged.

Psychometric testing of SPIDER: data capture tool for systematic literature reviews.

OBJECTIVE: Systematic literature reviews contribute to evidence-based occupational therapy, yet no data capture tool currently exists to validly and reliably appraise the characteristics and quality of primary studies. METHOD: We determined the psychometrics of Systematic Process for Investigating and Describing Evidence-Based Research (SPIDER) and piloted it with 201 studies included in a systematic literature review. RESULTS: Content validity showed item relevance with 73% agreement between two experts. For the quality construct, seven of nine quality indicators were positively (p < .05) correlated with the overall quality score. The quality scores were positively correlated (p < .05) with two objective measures, inferring criterion validity. Intrarater reliability was moderate to perfect (kappa = 0.4-1.0). Cross-tab analyses showed less variation in experienced reviewers' interrater reliability. CONCLUSION: SPIDER provides plausible opportunities for occupational therapy researchers and graduate students to appraise the characteristics and quality of primary studies but requires testing across other settings.

Predictors of injury among younger and older adults in fatal motor vehicle crashes.

With 2003 Fatality Analysis Reporting System data, we examined relationships among predictors of motor vehicle injury/fatality outcomes for younger (35-54 years) and older (65 years and older) drivers. Using the Precede-Proceed Model of Health Promotion as an organizing framework, we classified variables into person, vehicle and environment domains and conducted a multinomial logistic regression. Significant risk factors for older driver injuries were impact crashes at 1-3 o'clock (OR=1.65; CI: 1.05-2.59), 7-9 o'clock angles (OR=2.59; CI=1.45-4.63), and driving with one passenger (OR=2.25; CI: 1.58-3.20). Previous other motor vehicle convictions were significantly associated with reduced risk of injury (OR=0.55; CI=0.34-0.90). The 7-9 o'clock angle (OR=3.06; CI: 1.83-5.12), and driving in daylight hours were risk factors for fatality among older drivers. Many risk factors (e.g., female gender, non-seatbelt use, rollover crashes, and vehicle body type), and protective factors (e.g., number of lanes and non-airbag deployment) were relevant for younger and older drivers. Findings showed relevant factors for drivers from both age groups, with some pointing to older adults, and set the stage for further research to develop injury and fatality prevention programs.

Population-based health promotion perspective for older driver safety: conceptual framework to intervention plan.

The topic of motor vehicle crashes among the elderly is dynamic and multi-faceted requiring a comprehensive and synergistic approach to intervention planning. This approach must be based on the values of a given population as well as health statistics and asserted through community, organizational and policy strategies. An integrated summary of the predictors (quantitative research), and views (qualitative research) of the older drivers and their stakeholders, does not currently exist. This study provided an explicit socio-ecological view explaining the interrelation of possible causative factors, an integrated summary of these causative factors, and empirical guidelines for developing public health interventions to promote older driver safety. Using a mixed methods approach, we were able to compare and integrate main findings from a national crash dataset with perspectives of stakeholders. We identified: 11 multi-causal factors for safe elderly driving; the importance of the environmental factors--previously underrated in the literature--interacting with behavioral and health factors; and the interrelatedness among many socio-ecological factors. For the first time, to our knowledge, we conceptualized the fundamental elements of a multi-causal health promotion plan, with measurable intermediate and long-term outcomes. After completing the detailed plan we will test the effectiveness of this intervention on multiple levels.