Hand-held Phone Research Articles

The Impact of Digital Otoscopy on Medical Student and Resident Education

Purpose: Otoscopy is a difficult, but requisite skill for Pediatric Residents and Medical Students to master. Locating the tympanic membrane, identifying normal anatomy and characterizing pathology are all skills that have historically been taught with verbal descriptions and/or static images due to the inability of the teacher and learner to perform the physical exam concurrently. Digital Otoscopy using a hand-held smart phone and performed by an Attending/Resident team may facilitate increased learner comfort with …

The role of beliefs in the use of hands-free and handheld mobile phones while driving

Abstract Objective This study investigated the frequency of mobile phones use while driving by mode (handheld vs. hands-free users) and its relationship with three types of beliefs (behavioural, normative and control). Methods Three hundred and fourteen British drivers (M = 29.4 years; 64% female) completed a questionnaire (White et al., 2010) which measured frequency of mobile phone use while driving (in general, and for four specific phone-related behaviours) and the three types of beliefs. Results The proportion of participants who reported each behaviour on at least a daily basis were: 29% answering calls, 29% initiating calls, 30% reading texts and 22% sending texts. Significant multivariate differences were identified in the behavioural and control beliefs between daily and less frequent handheld mobile phone users. Differences were also found for several specific behavioural beliefs (effectively using time for both modes and receiving important information for handheld users), normative beliefs (handheld - partner, hands-free - friends, family and work colleagues) and control beliefs (hands-free - risk of fines, handheld - all control beliefs). In all cases daily users reported more positive outcomes of phone use, a higher likelihood of being approved by others, and a lower likelihood of control beliefs preventing them from using a phone. However, using composite measures of each belief type, logistic regression found that only control beliefs were significantly related to being a daily user among handheld mobile phone users. Conclusions Differences in beliefs (particularly behavioural and control beliefs) were found between daily and less frequent users of handheld mobile phones, meaning that they may underlie the decision to engage in this risky behaviour. Likewise, several specific beliefs differed between daily and less frequent users of handheld and hands-free mobile phones (using their time effectively). These results may provide useful information for developing countermeasures aimed at curbing mobile phone use while driving.

The Effect of Hands-Free Cell Phone Conversation on Psychomotor Performance Required for Safe Driving: A Quasi-Experimental Study

Background: Hands-free cell phone conversation (HFCC) while driving is a common practice among drivers. Several studies have revealed that HFCC, while driving, is no safer than hand-held cell phone conversations (HHCC). This study was conducted to explore the influence of HFCC on the psychomotor performance of drivers. Methods: In this quasi-experimental study, the participants were randomly allocated into 2 groups. Participants in group1 passed the traffic psychological battery of the Vienna test system (VTS) once without being engaged in any phone conversation and again while making a HFCC. The order of testing in the 2nd group was reversed. All participants shifted their group and passed the tests in a reverse order after 7 to 10 days. The tests included peripheral perception, perceptual speed, general intelligence, visuomotor coordination, and time anticipation. The mixed model analysis was used to assess the association of HFCC with every test. Results: A total of 24 students, with a mean age of 27.1 ± 5.3 years, were included in the study. HFCC had a significant negative influence on the overall mean duration (P value = 0.015), overall percent error duration (P value < 0.001) in visuomotor coordination median deviation time (P value = 0.007) in time anticipation, divided attention in peripheral perception test (P value = 0.053), and general intelligence (P value = 0.005). However, perceptual speed and field of vision did not reveal any significant association. Conclusions: These findings provided further evidence of the adverse effects of HFCC during driving. Even though drivers can perceive an obstacle while talking on a hands-free cell phone, they are highly likely to react incorrectly due to impairment of visuomotor coordination, time anticipation, divided attention, and fluid intelligence.

New evidence shows self-esteem moderates the relationship between narcissism and selfies

Recent statistics show that millions of ‘selfies’ (defined as a self-portrait taken with a hand-held smart phone or camera) are posted on social media every day, and research has shown trait narcissism as a stable positive predictor of this behaviour. However, results regarding subtypes of narcissism and self-esteem as predictors are limited and inconsistent. As such, the current study sought to extend this research by exploring the utility of subtypes of narcissism, individual self-esteem, and interactions between narcissism and self-esteem in predicting posting selfies. Two hundred and fifty-seven participants (22% men and 78% women) completed an online questionnaire including the 40-item Narcissistic Personality Inventory (NPI-40), the Rosenberg Self-Esteem Scale, and a measure of selfie posting frequency. Results showed that higher levels of grandiose-exhibitionism narcissism and lower levels of self-esteem were associated with posting more selfies. Importantly, self-esteem was found to moderate the relationship between grandiose-exhibitionism narcissism and posting selfies. Specifically, the relationship between grandiose narcissism and posting selfies on social media was only significant when self-esteem was low or average. Results of the current study significantly contribute towards understanding the association between selfies and narcissism, showing that self-esteem may play a more fundamental role than previously thought.

The impact of driver distraction in tractor-trailers and motorcoach buses

Driver distraction has become an increasing concern over the last decade as portable technology has emerged and its presence while driving has become more common. Driver distraction occurs when inattention leads to a delay in recognition of information necessary to accomplish the driving task. Two recent studies were conducted using a naturalistic data collection method and analysis of driver distraction. The Commercial Motor Vehicle Driver Distraction study (Olson et al., 2009) was conducted using heavy truck data, and the Distraction and Drowsiness in Motorcoach Drivers study (Hammond et al., 2016) was conducted using motorcoach data. Data were collected continuously every time the instrumented vehicle was turned on and in motion. Data were reduced to identify safety-critical events such as crashes, near-crashes, crash-relevant conflicts, and unintentional lane deviations. Results show that 40% of truck crashes and 56% of motorcoach crashes had some kind of distracting behavior. Odds ratios were calculated on individual secondary tasks and analyses of variance (ANOVAs) were calculated on eye-glance data to determine the effects of eyes off the forward roadway. Fewer distractions were identified in the motorcoach data, most notably the use of handheld cell phones. This suggests that the 2010 ban on handheld phones has had a positive effect on decreasing cell phone use while driving.

Cellphone Legislation and Self-Reported Behaviors Among Subgroups of Adolescent U.S. Drivers

PurposeThe relationship between cellphone use while driving legislation and self-reported adolescent driver behavior is poorly understood, especially across demographic subgroups. This study investigated the relationship between statewide cellphone legislation and cellphone use behaviors across adolescent driver subgroups, including age (16/17 vs. 18), sex, race/ethnicity (white non-Hispanic and others), and rurality (urban or rural). MethodsData from the 2011–2014 Traffic Safety Culture Index Surveys were combined with state legislation. The outcomes were self-reported texting and handheld cellphone conversations. The exposure was the presence of a texting or handheld cellphone ban applicable to all drivers (i.e., universal) in the drivers' state of residence. A multilevel, modified Poisson regression model was used to estimate the risk of engaging in these behaviors. ResultsApproximately 34% of respondents reported to have driven while conversing, and 37% texted and drove in the 30 days before the survey. Universal handheld calling bans were associated with lower occurrences of cellphone conversations across all groups except rural drivers. Overall, handheld cellphone bans were associated with 55% lower (adjusted risk ratio .45, 95% confidence interval .32–.63) occurrences of cellphone conversations. However, universal texting bans were not associated with fewer texting behaviors in any subgroup. ConclusionsUniversal handheld calling bans may discourage adolescents from engaging in handheld phone conversations, whereas universal texting bans may not fully discourage texting behaviors. More interventional or educational work is necessary, particularly addressing texting while driving.

Does Talking on a Cell Phone, With a Passenger, or Dialing Affect Driving Performance? An Updated Systematic Review and Meta-Analysis of Experimental Studies.

Objective An up-to-date meta-analysis of experimental research on talking and driving is needed to provide a comprehensive, empirical, and credible basis for policy, legislation, countermeasures, and future research. Background The effects of cell, mobile, and smart phone use on driving safety continues to be a contentious societal issue. Method All available studies that measured the effects of cell phone use on driving were identified through a variety of search methods and databases. A total of 93 studies containing 106 experiments met the inclusion criteria. Coded independent variables included conversation target (handheld, hands-free, and passenger), setting (laboratory, simulation, or on road), and conversation type (natural, cognitive task, and dialing). Coded dependent variables included reaction time, stimulus detection, lane positioning, speed, headway, eye movements, and collisions. Results The overall sample had 4,382 participants, with driver ages ranging from 14 to 84 years ( M = 25.5, SD = 5.2). Conversation on a handheld or hands-free phone resulted in performance costs when compared with baseline driving for reaction time, stimulus detection, and collisions. Passenger conversation had a similar pattern of effect sizes. Dialing while driving had large performance costs for many variables. Conclusion This meta-analysis found that cell phone and passenger conversation produced moderate performance costs. Drivers minimally compensated while conversing on a cell phone by increasing headway or reducing speed. A number of additional meta-analytic questions are discussed. Application The results can be used to guide legislation, policy, countermeasures, and future research.

Mobile phone use while driving and the risk of collision: A study among preparatory year students at King Saud University, Riyadh, Saudi Arabia.

OBJECTIVES:The objectives of this study were to determine the rate of mobile phones use while driving by the students of King Saud University, Riyadh, Saudi Arabia, their perception of the risks, and contribution to collisions.MATERIALS AND METHODS:A cross-sectional study was conducted in May 2014 targeting 986 male students of King Saud University, Riyadh, Saudi Arabia. A questionnaire was used to obtain data on possessing a driving license, years of driving experience, driving hours, and collision or near misses in the 6 months preceding the study. Eight statements were used to assess the behavior and perceptions related to the use of mobile phones while driving. Data were analyzed using the Chi-square statistic, odds ratio, and the 95% confidence interval.RESULTS:Almost half of the participants (45.3%) had driving experience of 4–6 years and 18.3% of them did not possess a driving license. Collision in the preceding 6 months was reported by 44.6% of participants, and 37.9% of them attributed these collisions to mobile phones. Variable proportions reported that they always texted (53.3%) or talked on a handheld (66.2%) or hands-free (26.1%) phones while driving. A higher proportion conceded that there were hazards in texting (77.0%) and speaking on handheld mobile phones (83.9%) rather than hands-free (35.9%) while driving. The risk increased significantly from 2.052 among participants who reported that they drove daily for 1–2 h to 3.165 of those who reported that they drove for more than 6 h. No significant risk was observed in relation to participants' perceptions, age, driving experience, and possession of a driving license.CONCLUSIONS:There was a risk of collision with the use of handheld and hands-free mobile phones. As hands-free mobile phones are no safer, national legislation should consider restricting their use by drivers and implementing legislations to reinforce safety on the roads. An objective assessment of the contribution of mobile phones to road traffic injuries is recommended.

Falling asleep at the wheel and distracted driving. The High-Risk Professional Drivers study.

Background:Sleepiness at the wheel and driving while engaged in other activities are well known risk factors for traffic accidents. This article estimates the prevalence of these factors among Italian Professional Drivers (PDs) and their impact on reported driving mistakes.Methods:A cross-sectional study was conducted using anonymous questionnaires. PDs (n=497) were divided into two groups: high-risk PDs (HiRis_PDs) (those who self-reported more than one incident during the last 3 years and/or more than one mistake during the past year) and non-HiRis_PDs (subjects who did not meet the above-mentioned inclusion criteria). Logistic regression analyses were performed to assess the association of self-reported sleepiness and/or risky driving behaviour with the condition of being a high-risk driver.Results:161 (32.4%) subjects were defined as HiRis_PDs. Forty-one percent of the interviewees experienced at least one episode per month of sudden-onset sleep at the wheel. Twenty-eight point two percent reported a regular use of a hand-held cell phone. Predictive factors for being HiRis_PDs were: at least one self-reported episode per month of falling asleep at the wheel [odds ratio (OR) 5, 95% confidence interval (CI) 3.21-7.80, P<0.001], driving while regularly engaged in other activities (mainly hand-held cell phone use) (OR 6.11, 95% CI 2.90-12.84, P<0.001), and young age (OR 0.96, OR 1 year of age increase, 95% CI 0.94-0.98, P=0.001).Conclusions:Focusing prevention efforts on recognizing sleepiness at the wheel and on avoiding other distracting activities while driving can reduce the possibility of driving errors on the road by about 5-6 times.

Epidemiology of Handheld Cell Phone Use While Driving: A Study from a South Indian City.

Background:Using cell phones while driving contribute to distractions which can potentially cause minor or major road traffic injuries and also stress among other drivers. With this background, the study was done to ascertain the proportion of handheld cell phone use while driving among road users in Mysore city and also patterns of the use by the day of week, type of road, and type of vehicle.Methods:The study was conducted in Mysore, Karnataka, India. Four stretches of roads were observed thrice daily for 1 week. The total number of vehicles passing through the stretch and the number and characteristics of drivers using hand-held cell was noted. Pearson's Chi-square test was used to ascertain the significance of the difference in proportions.Results:The overall proportion of cell phone users was calculated as 1.41/100 vehicles. The observed use of handheld cell phones was 1.78 times higher on nonbusy roads than busy roads (Χ2 = 25.79, P < 0.0001). More than 50% of the handheld phone users were driving a two wheeler, the proportion being 50.5% in busy roads, and 67% in nonbusy roads. There was no difference in the proportion of cell phone use by time of the day or across different days of the week.Conclusions:The proportion of drivers who use cell phones is found to be relatively lower, and use of cell phones was higher on nonbusy roads.

Autonomous lights detecting and reporting robots from e-scrap (Scrapines)

Abstract Electronic Scrap (E-scrap) encompasses a broad and growing range of electronic devices ranging from large household appliances such as refrigerators, air conditioners, hand-held cellular phones, personal stereos, and consumer electronics to computers. The reuse of E-scrap is mainly limited in the separation of valuable materials, but there is another opportunity in using the E-scrap, to build robots, which are cost effective and building them can be can be very functional for different universal needs such as in a University. Autonomous lights detecting and reporting robot from e-scrap (Scrapines) is able to move through certain university spaces/classes using motion motors, to identify obstacles ultrasonic sensors are used, to detect lights in certain university spaces/classes light sensors and LDR sensors are used, robotic arm are used to turn off lights, and going back to reception to give a report which classes have been visited and in which classes lights are turn off. Autonomous detecting lights and reporting robots from e-scrap will provide a very good learning experience and also serve as a gateway to get into building robotics from e-scrap.

Self-sustainable robot from e-scrap using renewable energy (Scrapino)

Abstract In a sustainable model’s energy and material resources are restricted. Therefore, electronic scrap (E-scrap) encompasses a broad and growing range of electronic devices ranging from large household appliances such as refrigerators, air conditioners, hand-held cellular phones, personal stereos, and consumer electronics to computers. The reuse of E-scrap is mainly limited in the separation of valuable materials, but there is another opportunity in using the e-scrap robots by combining them with renewable energy sources, and this way to build self-sustainable robots, which are cost effective and building them can be very functional for different universal needs. Self-sustainable robot (SSR) from e-scrap using renewable energy, has a solar panel to power it and to make him self-sustainable, it enables the robot to move through campus grounds and search for best angle to sunbathe and this way to collect energy. It can be used in different ways form greeting, giving out flyers, as an information robot to give information on ongoing conferences agenda, workshops etc. SSR, will provide a very good learning experience and show that robotics and renewable energy can go hand in hand and serve as a gateway to start getting SSR from e-scrap.

Response of major road drivers to aggressive maneuvering of the minor road drivers at unsignalized intersections: A driving simulator study

Drivers’ inattention, human error and aggressive behavior are often linked with vehicle crashes. This research studies how major road drivers respond to the aggressive maneuvering of the minor road drivers at unsignalized intersections. The study was also designed to investigate the effect of distracted driving (engaged on handheld phone) on driving performance. In our experiments, 51 drivers were tested for four different events using a driving simulator. The test track comprised of a stretch of 10.4 km having nine unsignalized intersections. A possible conflicting event was designed at each intersection for approaching major road drivers. The major road driver behavior was evaluated with reference to three variables: response time before possible conflict (RTPC), average speed while approaching intersection and at the intersection, and deceleration rate. The analysis results showed that the RTPC values against the right turning vehicles were very low indicating high risk against right turning vehicles (considering left side driving practice). For the same event with handheld phone conversation, the RTPC values were found to be negative indicating that the drivers are more likely to miss the visual reaction time stimuli when engaged in a phone conversation. The 10th and 90th percentile RTPC values were found to vary from 6.3 to 9.4 s and 0.1 to 1.8 s respectively for different events. The driving speed of the drivers was not found to be significantly impacted by the cell phone usage. The approach speed for all drivers at the intersection was found to be lower by 35–40% compared to speeds before responding to the conflicting vehicle. The average decelerating rate for all the drivers was found to be 3.73 m/s2 and 4.23 m/s2 when the participants were driving without phone and with phone respectively. The insights from this study can be used to understand pre-crash driver actions which are necessary for the implementation of appropriate countermeasures and to assess the level of safety at unsignalized intersections.

Talking on a Wireless Cellular Device While Driving: Improving the Validity of Crash Odds Ratio Estimates in the SHRP 2 Naturalistic Driving Study

Dingus and colleagues (Proc. Nat. Acad. Sci. U.S.A. 2016, 113, 2636–2641) reported a crash odds ratio (OR) estimate of 2.2 with a 95% confidence interval (CI) from 1.6 to 3.1 for hand-held cell phone conversation (hereafter, “Talk”) in the SHRP 2 naturalistic driving database. This estimate is substantially higher than the effect sizes near one in prior real-world and naturalistic driving studies of conversation on wireless cellular devices (whether hand-held, hands-free portable, or hands-free integrated). Two upward biases were discovered in the Dingus study. First, it selected many Talk-exposed drivers who simultaneously performed additional secondary tasks besides Talk but selected Talk-unexposed drivers with no secondary tasks. This “selection bias” was removed by: (1) filtering out records with additional tasks from the Talk-exposed group; or (2) adding records with other tasks to the Talk-unexposed group. Second, it included records with driver behavior errors, a confounding bias that was also removed by filtering out such records. After removing both biases, the Talk OR point estimates declined to below 1, now consistent with prior studies. Pooling the adjusted SHRP 2 Talk OR estimates with prior study effect size estimates to improve precision, the population effect size for wireless cellular conversation while driving is estimated as 0.72 (CI 0.60–0.88).

Casual 3D photography

We present an algorithm that enables casual 3D photography. Given a set of input photos captured with a hand-held cell phone or DSLR camera, our algorithm reconstructs a 3D photo , a central panoramic, textured, normal mapped, multi-layered geometric mesh representation. 3D photos can be stored compactly and are optimized for being rendered from viewpoints that are near the capture viewpoints. They can be rendered using a standard rasterization pipeline to produce perspective views with motion parallax. When viewed in VR, 3D photos provide geometrically consistent views for both eyes. Our geometric representation also allows interacting with the scene using 3D geometry-aware effects, such as adding new objects to the scene and artistic lighting effects. Our 3D photo reconstruction algorithm starts with a standard structure from motion and multi-view stereo reconstruction of the scene. The dense stereo reconstruction is made robust to the imperfect capture conditions using a novel near envelope cost volume prior that discards erroneous near depth hypotheses. We propose a novel parallax-tolerant stitching algorithm that warps the depth maps into the central panorama and stitches two color-and-depth panoramas for the front and back scene surfaces. The two panoramas are fused into a single non-redundant, well-connected geometric mesh. We provide videos demonstrating users interactively viewing and manipulating our 3D photos.

Driver behavior formulation in intersection dilemma zones with phone use distraction via a logit-Bayesian network hybrid approach

ABSTRACTUse of cellular phone while driving is one of the top contributing factors that induce traffic crashes, resulting in significant loss of life and property. A dilemma zone is a circumstance near signalized intersections where drivers hesitate when making decisions related to their driving behaviors. Therefore, the dilemma zone has been identified as an area with high crash potential. This article utilizes a logit-based Bayesian network (BN) hybrid approach to investigate drivers' decision patterns in a dilemma zone with phone use, based on experimental data from driving simulations from the National Advanced Driving Simulator (NADS). Using a logit regression model, five variables were found to be significant in predicting drivers' decisions in a dilemma zone with distractive phone tasks: older drivers (50–60 years old), yellow signal length, time to stop line, handheld phone tasks, and driver gender. The identified significant variables were then used to train a BN model to predict drivers' decisions at a dilemma zone and examine probabilistic impacts of these variables on drivers' decisions. The analysis results indicate that the trained BN model was effective in driver decision prediction and variable influence extraction. It was found that older drivers, a short yellow signal, a short time to stop line, nonhandheld phone tasks, and female drivers are factors that tend to result in drivers proceeding through intersections in a dilemma zone with phone use distraction. These research findings provide insight in understanding driver behavior patterns in a dilemma zone with distractive phone tasks.

Hand-held cell phone use while driving legislation and observed driver behavior among population sub-groups in the United States

BackgroundCell phone use behaviors are known to vary across demographic sub-groups and geographic locations. This study examined whether universal hand-held calling while driving bans were associated with lower road-side observed hand-held cell phone conversations across drivers of different ages (16–24, 25–59, ≥60 years), sexes, races (White, African American, or other), ruralities (suburban, rural, or urban), and regions (Northeast, Midwest, South, and West).MethodsData from the 2008–2013 National Occupant Protection Use Survey were merged with states’ cell phone use while driving legislation. The exposure was presence of a universal hand-held cell phone ban at time of observation. Logistic regression was used to assess the odds of drivers having a hand-held cell phone conversation. Sub-groups differences were assessed using models with interaction terms.ResultsWhen universal hand-held cell phone bans were effective, hand-held cell phone conversations were lower across all driver demographic sub-groups and regions. Sub-group differences existed among the sexes (p-value, <0.0001) and regions (p-value, 0.0003). Compared to states without universal hand-held cell phone bans, the adjusted odds ratio (aOR) of a driver hand-held phone conversation was 0.34 [95% confidence interval (CI): 0.28, 0.41] for females versus 0.47 (CI 0.40, 0.55) for males and 0.31 (CI 0.25, 0.38) for drivers in Western states compared to 0.47 (CI 0.30, 0.72) in the Northeast and 0.50 (CI 0.38, 0.66) in the South.ConclusionsThe presence of universal hand-held cell phone bans were associated lower hand-held cell phone conversations across all driver sub-groups and regions. Hand-held phone conversations were particularly lower among female drivers and those from Western states when these bans were in effect. Public health interventions concerning hand-held cell phone use while driving could reasonably target all drivers.

Mild Cognitive Impairment and driving: Does in-vehicle distraction affect driving performance?

ObjectivesIn-vehicle distraction is considered to be an important cause of road accidents. Drivers with Mild Cognitive Impairment (MCI), because of their attenuated cognitive resources, may be vulnerable to the effects of distraction; however, previous relevant research is lacking. The main objective of the current study was to explore the effect of in-vehicle distraction on the driving performance of MCI patients, by assessing their reaction time at unexpected incidents and accident probability. MethodsThirteen patients with MCI (age: 64.5±7.2) and 12 cognitively intact individuals (age: 60.0±7.7), all active drivers were introduced in the study. The driving simulator experiment included three distraction conditions: (a) undistracted driving, (b) conversing with passenger and (c) conversing through a hand-held mobile phone. ResultsThe mixed ANOVA models revealed a greater effect of distraction on MCI patients. Specifically, the use of mobile phone induced a more pronounced impact on reaction time and accident probability in the group of patients, as compared to healthy controls. On the other hand, in the driving condition “conversing with passenger” the interaction effects regarding reaction time and accident probability were not significant. Notably, the aforementioned findings concerning the MCI patients in the case of the mobile phone were observed despite the effort of the drivers to apply a compensatory strategy by reducing significantly their speed in this driving condition. ConclusionOverall, the current findings indicate, for the first time, that a common driving practice, such as the use of mobile phone, may have a detrimental impact on the driving performance of individuals with MCI.

Investigating driver reaction time and speed during mobile phone conversations with a lead vehicle in front: A driving simulator comprehensive study

ABSTRACTThis study analyzed driving performance while using different mobile devices in different road configurations and geometries during a critical driving situation. Three different road environments were implemented in a driving simulator: an urban road, a two-lane rural road, and a highway. Thirty drivers with an average age of 26.8 years were asked to answer a phone call while driving, using different mobile devices: hand-held, hands-free, and hands-free voice-activated cellular phone. The effects of using the mobile phones were also compared to the BC (no phone conversation). Driving performance, under car-following conditions, were collected and statistically analyzed when a sudden braking of the leading vehicle occurred. The main results demonstrated that the driver's speed generally reduced during the phone call whereas the reaction time generally increased, especially under certain driving conditions (urban road, along tangent, using hand-held mobile device). This study analyzed the effects of using a mobile phone while driving, highlighted the worst combinations of the variables investigated, and demonstrated that some reductions in driving performance were revealed, especially in the urban environment, even when using mobile equipment permitted by the regulations of several countries.

Self-regulation of driving speed among distracted drivers: An application of driver behavioral adaptation theory

ABSTRACTObjective: The adaptive behavior of mobile phone–distracted drivers has been a topic of much discussion in the recent literature. Both simulator and naturalistic studies suggest that distracted drivers generally select lower driving speeds; however, speed adaptation is not observed among all drivers, and the mechanisms of speed selection are not well understood. The aim of this research was to apply a driver behavioral adaptation model to investigate the speed adaptation of mobile phone–distracted drivers.Methods: The speed selection behavior of drivers was observed in 3 phone conditions including baseline (no conversation) and hands-free and handheld phone conversations in a high-fidelity driving simulator. Speed adaptation in each phone condition was modeled as a function of secondary task demand and self-reported personal/psychological characteristics with a system of seemingly unrelated equations (SURE) accounting for potential correlations due to repeated measures experiment design.Results: Speed adaptation is similar between hands-free and handheld phone conditions, but the predictors of speed adaptation vary across the phone conditions. Though perceived workload of secondary task demand, self-efficacy, attitude toward safety, and driver demographics were significant predictors of speed adaptation in the handheld condition, drivers' familiarity with the hands-free interface, attitude toward safety, and sensation seeking were significant predictors in the hands-free condition. Drivers who reported more positive safety attitudes selected lower driving speeds while using phones.Conclusion: This research confirmed that behavioral adaptation models are suitable for explaining speed adaptation of mobile phone distracted drivers, and future research could be focused on further theoretical refinement.