The Concurrent Criterion Validity of the 32-Item Fitness-to-Drive Screening Measure.

Background: The Fitness-to-Drive Screening Measure© (FTDS) is a free online screening tool that identifies at-risk older drivers. This tool screens for at-risk drivers using proxy rater responses (family, friends, and caregivers) to 54 driving-related items. Consumer usage analysis of the FTDS determined that reducing the time commitment to complete the 54-item FTDS might increase usability and uptake of the tool. To address this need, we used classical test theory and exploratory factor analysis to construct a 32-item version of the FTDS. This study aims to establish the concurrent criterion validity of the 32-item FTDS. Method: Two hundred older driver on-road assessments and Two hundred caregiver FTDS responses were used to generate a receiver operating characteristic (ROC) curve, in which we plotted the rate of true positives against the rate of false positives, calculated the area under the curve (AUC), and used Youden's index to identify the optimal cut-point for the 32-item FTDS. In this study, the true positive rate was the 32-item FTDS' ability to predict a fail when the older driver actually failed the on-road assessment, and the false positive rate was the the 32-item FTDS' ability to predict a pass when the older driver actually passed the on-road assessment. We computed the sensitivity, specificity, positive predictive value, negative predictive value and total number of misclassifications for the optimal cut-point. Results: The ROC curve results indicated an acceptable AUC, with a magnitude of 0.75, p < 0.05. At the optimal cut-point of 4.87, the 32-item FTDS had a sensitivity of 0.74, specificity of 0.69, positive predictive value of 0.30, negative predictive value of 0.93 and 61 (of 200) misclassifications. Conclusion: Although the 32-item FTDS met the criterion (AUC 0.75, p < 0.05.) for good concurrent criterion validity in predicting older driver on-road outcomes, it also misclassified 30% of the drivers and as such may be overly sensitive.

Clinical Utility of the DriveFocus™ Intervention on Young Drivers With and Without Experience.

Introduction: The DriveFocus™ intervention addresses the ability of young drivers to detect and respond to critical roadway information. DriveFocus is an interactive video-based tablet application that teaches users how to detect and prioritize critical roadway items. However, young drivers with and without experience may respond differently to the intervention. Objectives: We compared the simulated driving performance of two 17 year-old licensed drivers with (novice) and without (learner) driving experience, after three (post-test 1) and six (post-test 2) intervention sessions. Methods: We collected clinical, driving performance (number of visual scanning, adjustment to stimuli, and total driving errors) and acceptability data. Results: The learner driver made more visual scanning, adjustment to stimuli and total errors when compared to the novice. Both participants exhibited a decrease in both types and number of driving errors from baseline to post-test 2 and the learner also made less driving errors at post-test 1. Both participants rated the perceived ease of use of the intervention favorably. Conclusions: This study lays the foundation to examine the impact of the DriveFocus™ intervention among novice and more experienced young drivers.

Corrigendum: Construction and Validation of the 21 Item Fitness-to-Drive Screening Measure Short-Form.

[This corrects the article DOI: 10.3389/fpubh.2018.00339.].

An Integrative Review on Teen Distracted Driving for Model Program Development.

Distracted driving, especially driver inattention, is associated with high levels of crash-related fatalities and injury. Teen novice drivers are one of the groups most likely to drive distracted and to suffer its consequences. Teens have a higher risk of engaging in texting or secondary tasks, e.g., eating while driving. Distracted driving interventions to date aim to improve teen and societal safety, but few have achieved effectiveness. A need exists for effective evidence-based distracted driving interventions. We used an integrative review to identify rigorous evidence, and inform the development of a teen distracted driving educational intervention. This five-step review included: identifying the research problem; collecting literature; evaluating literature; synthesizing data; and presenting results. We searched 6 databases, identifying 185 articles. Following three rounds of inclusion screening (title, abstract, and full-text), captured according to a PRISMA flow chart, 17 studies met inclusion. We categorized these studies, conducted in the U.S., as five intervention types that used approaches including presentations, videos or instructional programs, education or training programs, driving simulator training, in-vehicle monitoring or feedback, and integrated programs. Study designs included randomized controlled trials pre-post, quasi-experimental, and experimental designs with prospective longitudinal cohorts. The studies were heterogeneous in design, intervention and outcome. However, three core themes emerged across studies: i.e., hazard awareness, hazard mitigation and attention maintenance are primary critically necessary skills to prevent distracted driving; engaging a parent or adult as a partner in the intervention process from classroom to car contributed to the effectiveness of the intervention; and leveraging technology in training enhanced the effectiveness of the intervention. Study limitations pertained to a focus on short-term effects; sampling distributions that did not account for gender, age, race, and/or ethnicity; types of interventions; and bias. The limitations affect the generalizability of included study findings and, potentially, the review findings, as they may not apply to populations or contexts outside those synopsized. Strengths included our team's expertise in conducting evidence-based reviews, support of a health science librarian, and use of international review guidelines. As an outcome, we are applying findings of the integrated review to develop a computer-based training addressing teen distracted driving.

Constructing the 32-item Fitness-to-Drive Screening Measure.

The Fitness-to-Drive Screening Measure© (FTDS) enables proxies to identify at-risk older drivers via 54 driving-related items, but may be too lengthy for widespread uptake. We reduced the number of items in the FTDS and validated the shorter measure, using 200 caregiver responses. Exploratory factor analysis and classical test theory techniques were used to determine the most interpretable factor model and the minimum number of items to be used for predicting fitness to drive. The extent to which the shorter FTDS predicted the results of the 54-item FTDS was evaluated through correlational analysis. A three-factor model best represented the empirical data. Classical test theory techniques lead to the development of the 32-item FTDS. The 32-item FTDS was highly correlated ( r = .99, p = .05) with the FTDS. The 32-item FTDS may provide raters with a faster and more efficient way to identify at-risk older drivers.

Construction and Validation of the 21 Item Fitness-to-Drive Screening Measure Short-Form.

Introduction: The Fitness-to-Drive Screening Measure is a free online screening tool that detects at-risk older drivers, however, it's 20 min administration time may render the 54-item tool less than optimal for clinical use. Thus, this study constructed and validated a 21-item FTDS Short-Form (FTDS-SF). Method: This mixed methods study used 200 proxy rater responses and older driver on-road assessments. We conducted a Rasch analysis to examine information at the level of the item and used content validity index scores to select items. Using a receiver operator characteristics curve we determined the concurrent validity of the FTDS-SF to on-road outcomes. Results: Twenty-one items were selected for the FTDS-SF. The area under the curve = 0.72, indicated the FTDS-SF predicted on-road outcomes with acceptable accuracy. Still, 68 drivers were misclassified. Conclusion: The FTDS-SF may reduce administration time, while still yielding acceptable psychometric properties. Yet, caution needs to be executed in clinical decision making as the measure is overly specific.

Pilot Efficacy of a DriveFocus™ Intervention on the Driving Performance of Young Drivers.

Road traffic injuries are the leading cause of death for youth between the ages of 15 and 29 around the world. A need remains for evidence-based interventions that can improve the underlying skills of young drivers, including hazard perception and anticipation. This pilot study investigated the preliminary impact of a six session DriveFocus™ intervention on the ability of young novice drivers (mean age = 18.6, SD = 2.12) to detect (visual scanning), and respond (adjustment to stimuli) to critical roadway information. Using a CDS-200 DriveSafety™ simulator, drives were recorded and sent to a blinded evaluator (occupational therapist), who scored the recorded drives for number and type (visual scanning and adjustment to stimuli) of errors. We observed a statistically significant decline in the number of visual scanning [t(34) = 2.853, p = 0.007], adjustment to stimuli [t(34) = 3.481, p = 0.001], and total driving errors [t(34) = 3.481, p = 0.002], among baseline and post-test 2.

Feasibility of DriveFocus™ and Driving Simulation Interventions in Young Drivers.

Motor vehicle collisions are the leading cause of death among North American youth, with a high prevalence of distraction-related fatalities. Youth-focused interventions must address detecting (visual scanning) and responding (adjustment to stimuli) to critical roadway information. In this repeated measures study, we investigated the feasibility (i.e., recruitment and sample characteristics; data collection procedures; acceptability of the intervention; resources; and preliminary effects) of a DriveFocus™ app intervention on youth's driving performance. Thirty-four youth participated in a 9-week protocol (retention rate = 89.7%; adherence rate = 100%). No participants experienced simulator sickness. A preliminary nonparametric evaluation of the results ( n = 34) indicated a statistically significant decrease in the number of visual scanning, F(2, 68) = 3.769, p = .028, and adjustment to stimuli, F(2, 68) = 6.759, p = .002, errors between baseline, midpoint, and posttest. This study lays the foundation to support a targeted intervention trial to improve youth's attention to critical road information, building on their mobile technology preferences.