Visual attention and self-regulation of driving among older adults

2008 ◽  
Vol 20 (1) ◽  
pp. 162-173 ◽  
Author(s):  
Ozioma C. Okonkwo ◽  
Michael Crowe ◽  
Virginia G. Wadley ◽  
Karlene Ball
Keyword(s):  
Older Adults ◽  
Visual Attention ◽  
Social Engagement ◽  
Public Safety ◽  
Self Regulation ◽  
Significant Proportion ◽  
Objective Measure ◽  
Older Drivers ◽  
Self Report ◽  
Crash Risk

ABSTRACTBackground: With the number of older drivers increasing, self-regulation of driving has been proposed as a viable means of balancing the autonomy of older adults against the sometimes competing demand of public safety. In this study, we investigate self-regulation of driving among a group of older adults with varying functional abilities.Method: Participants in the study comprised 1,543 drivers aged 75 years or older. They completed an objective measure of visual attention from which crash risk was estimated, and self-report measures of driving avoidance, driving exposure, physical functioning, general health status, and vision. Crash records were obtained from the State Department of Public Safety.Results: Overall, participants were most likely to avoid driving in bad weather followed by driving at night, driving on high traffic roads, driving in unfamiliar areas, and making left-hand turns across oncoming traffic. With the exception of driving at night, drivers at higher risk of crashes generally reported greater avoidance of these driving situations than lower risk drivers. However, across all driving situations a significant proportion of higher risk drivers did not restrict their driving. In general, self-regulation of driving did not result in reduced social engagement.Conclusion: Some older drivers with visual attention impairments do not restrict their driving in difficult situations. There is a need for physicians and family members to discuss driving behaviors with older adults routinely to ensure their safety. The association between visual attention and driving restriction also has implications for interventions aimed at preserving mobility in the elderly.

scholarly journals Effects of age, experience and training on hazard perception

2021 ◽  
Author(s):  
Dana Greenbaum
Keyword(s):  
Older Adults ◽  
Visual Attention ◽  
Automatic Transmission ◽  
Older Drivers ◽  
Crash Risk ◽  
Age Group ◽  
Single Session ◽  
Hazard Perception ◽  
Middle Aged Adults ◽  
And Training

Hazard perception (ability to identify dangerous road situations that require evasive action) declines with age and is linked to changes in visual attention and crash risk. Evidence shows that training can improve this ability in older adults. Yet, no study has considered the type of experience (manual versus automatic transmission) these older drivers have. The current study aims to fill this gap by examining the effects of age, experience and training on hazard perception ability. Twenty-four older and 23 middle aged adults (equal number of manual/automatic drivers per age group) were trained in a 20-minute single-session on hazard perception. Results indicate hazard performance declines with age and this is exacerbated with older automatic drivers. Further, the results show that generally training improves for most hazard variable. However, training does does assist older automatic drivers on identifying hazards.

scholarly journals Effects of age, experience and training on hazard perception

2021 ◽  
Author(s):  
Dana Greenbaum
Keyword(s):  
Older Adults ◽  
Visual Attention ◽  
Automatic Transmission ◽  
Older Drivers ◽  
Crash Risk ◽  
Age Group ◽  
Single Session ◽  
Hazard Perception ◽  
Middle Aged Adults ◽  
And Training

Hazard perception (ability to identify dangerous road situations that require evasive action) declines with age and is linked to changes in visual attention and crash risk. Evidence shows that training can improve this ability in older adults. Yet, no study has considered the type of experience (manual versus automatic transmission) these older drivers have. The current study aims to fill this gap by examining the effects of age, experience and training on hazard perception ability. Twenty-four older and 23 middle aged adults (equal number of manual/automatic drivers per age group) were trained in a 20-minute single-session on hazard perception. Results indicate hazard performance declines with age and this is exacerbated with older automatic drivers. Further, the results show that generally training improves for most hazard variable. However, training does does assist older automatic drivers on identifying hazards.

scholarly journals Acceptance of Transportation Technologies by Aging Adults

2020 ◽  
Vol 4 (Supplement_1) ◽  
pp. 555-555
Author(s):  
Neil Charness ◽  
Dustin Souders ◽  
Ryan Best ◽  
Nelson Roque ◽  
JongSung Yoon ◽  
...  
Keyword(s):  
Older Adults ◽  
Older Adult ◽  
Detection System ◽  
Blind Spot ◽  
Driving Performance ◽  
Older Drivers ◽  
Crash Risk ◽  
Warning Systems ◽  
Risk Of Death ◽  
Spot Detection

Abstract Older adults are at greater risk of death and serious injury in transportation crashes which have been increasing in older adult cohorts relative to younger cohorts. Can technology provide a safer road environment? Even if technology can mitigate crash risk, is it acceptable to older road users? We outline the results from several studies that tested 1) whether advanced driver assistance systems (ADAS) can improve older adult driving performance, 2) older adults’ acceptance of ADAS and Autonomous Vehicle (AV) systems, and 3) perceptions of value for ADAS systems, particularly for blind-spot detection systems. We found that collision avoidance warning systems improved older adult simulator driving performance, but not lane departure warning systems. In a young to middle-aged sample the factor “concern with AV” showed age effects with older drivers less favorable. Older drivers, however, valued an active blind spot detection system more than younger drivers.

scholarly journals Association of Photopic and Mesopic Contrast Sensitivity in older drivers with risk of motor vehicle collision using naturalistic driving data

2020 ◽  
Vol 20 (1) ◽  
Author(s):  
Cynthia Owsley ◽  
Thomas Swain ◽  
Rong Liu ◽  
Gerald McGwin ◽  
Mi Young Kwon
Keyword(s):  
Older Adults ◽  
Contrast Sensitivity ◽  
Motor Vehicle ◽  
Age Groups ◽  
Time Of Day ◽  
Motor Vehicle Crash ◽  
Older Drivers ◽  
Crash Risk ◽  
Sensitivity Testing ◽  
Naturalistic Driving

Abstract Background Older drivers have a crash rate nearly equal to that of young drivers whose crash rate is the highest among all age groups. Contrast sensitivity impairment is common in older adults. The purpose of this study is to examine whether parameters from the photopic and mesopic contrast sensitivity functions (CSF) are associated with incident motor vehicle crash involvement by older drivers. Methods This study utilized data from older drivers (ages ≥60 years) who participated in the Strategic Highway Research Program Naturalistic Driving Study, a prospective, population-based study. At baseline participants underwent photopic and mesopic contrast sensitivity testing for targets from 1.5–18 cycles per degree. Model fitting generated area under the log CSF (AULCSF) and peak log sensitivity. Participant vehicles were instrumented with sensors that captured continuous driving data when the vehicle was operating (accelerometers, global positioning system, forward radar, 4-channel video). They participated for 1–2 years. Crashes were coded from the video and other data streams by trained analysts. Results The photopic analysis was based on 844 drivers, and the mesopic on 854 drivers. Photopic AULCSF and peak log contrast sensitivity were not associated with crash rate, whether defined as all crashes or at-fault crashes only (all p > 0.05). Mesopic AULCSF and peak log sensitivity were associated with an increased crash rate when considered for all crashes (rate ratio (RR): 1.36, 95% CI: 1.06–1.72; RR: 1.28, 95% CI: 1.01–1.63, respectively) and at-fault crashes only (RR: 1.50, 95% CI: 1.16–1.93; RR: 1.38, 95% CI: 1.07–1.78, respectively). Conclusions Results suggest that photopic contrast sensitivity testing may not help us understand future crash risk at the older-driver population level. Results highlight a previously unappreciated association between older adults’ mesopic contrast sensitivity deficits and crash involvement regardless of the time of day. Given the wide variability of light levels encountered in both day and night driving, mesopic vision tests, with their reliance on both cone and rod vision, may be a more comprehensive assessment of the visual system’s ability to process the roadway environment.

scholarly journals An automatic estimation of the rest-interval for MotionWatch8© using uniaxial movement and lux data

2020 ◽  
Vol 4 (1) ◽  
Author(s):  
Daniel Backhouse ◽  
Ryan Stanley Falck ◽  
Teresa Liu-Ambrose
Keyword(s):  
Older Adults ◽  
Sleep Duration ◽  
Light Exposure ◽  
Objective Measure ◽  
Self Report ◽  
Time Interval ◽  
Poor Sleep ◽  
Rest Interval ◽  
Scoring Method ◽  
Field Methods

Abstract Background Poor sleep is linked with chronic conditions common in older adults, including diabetes, heart disease, and dementia. Valid and reliable field methods to objectively measure sleep are thus greatly needed to examine how poor sleep impacts older adults. Wrist-worn actigraphy (WWA) is a common objective measure of sleep that uses motion and illuminance data to estimate sleep. The rest-interval marks the time interval between when an individual attempts to sleep and the time they get out of bed to start their day. Traditionally, the rest-interval is scored manually by trained technicians, however algorithms currently exist which automatically score WWA data, saving time and providing consistency from user-to-user. However, these algorithms ignore illuminance data and only considered motion in their estimation of the rest-interval. This study therefore examines a novel algorithm that uses illuminance data to supplement the approximation of the rest-interval from motion data. Methods We examined a total of 1086 days of data of 129 participants who wore the MotionWatch8© WWA for ≥14 nights of observation. Resultant sleep measures from three different parameter settings were compared to sleep measures derived following a standard scoring protocol and self-report times. Results The algorithm showed the strongest correlation to the standard protocol (r = 0.92 for sleep duration). There were no significant differences in sleep duration, sleep efficiency and fragmentation index estimates compared to the standard scoring protocol. Conclusion These results suggest that an automated rest-interval scoring method using both light exposure and acceleration data provides comparable accuracy to the standard scoring method.

scholarly journals Evaluation of the Usability and Acceptability of the InnoWell Platform as Rated by Older Adults: Survey Study

JMIR Aging ◽  
10.2196/25928 ◽  
2021 ◽  
Vol 4 (2) ◽  
pp. e25928
Author(s):  
Haley M LaMonica ◽  
Anna E Roberts ◽  
Tracey A Davenport ◽  
Ian B Hickie
Keyword(s):  
Older Adults ◽  
Social Engagement ◽  
Later Life ◽  
Well Being ◽  
Assessment Tools ◽  
Self Report ◽  
Digital Tool ◽  
System Usability Scale ◽  
Mental Well Being ◽  
Health And Well Being

Background As the global population ages, there is increased interest in developing strategies to promote health and well-being in later life, thus enabling continued productivity, social engagement, and independence. As older adults use technologies with greater frequency, proficiency, and confidence, health information technologies (HITs) now hold considerable potential as a means to enable broader access to tools and services for the purposes of screening, treatment, monitoring, and ongoing maintenance of health for this group. The InnoWell Platform is a digital tool co-designed with lived experience to facilitate better outcomes by enabling access to a comprehensive multidimensional assessment, the results of which are provided in real time to enable consumers to make informed decisions about clinical and nonclinical care options independently or in collaboration with a health professional. Objective This study aims to evaluate the usability and acceptability of a prototype of the InnoWell Platform, co-designed and configured with and for older adults, using self-report surveys. Methods Participants were adults 50 years and older who were invited to engage with the InnoWell Platform naturalistically (ie, at their own discretion) for a period of 90 days. In addition, they completed short web-based surveys at baseline regarding their background, health, and mental well-being. After 90 days, participants were asked to complete the System Usability Scale to evaluate the usability and acceptability of the prototyped InnoWell Platform, with the aim of informing the iterative redesign and development of this digital tool before implementation within a health service setting. Results A total of 19 participants consented to participate in the study; however, only the data from the 16 participants (mean age 62.8 years, SD 7.5; range 50-72) who completed at least part of the survey at 90 days were included in the analyses. Participants generally reported low levels of psychological distress and good mental well-being. In relation to the InnoWell Platform, the usability scores were suboptimal. Although the InnoWell Platform was noted to be easy to use, participants had difficulty identifying the relevance of the tool for their personal circumstances. Ease of use, the comprehensive nature of the assessment tools, and the ability to track progress over time were favored features of the InnoWell Platform, whereas the need for greater personalization and improved mobile functionality were cited as areas for improvement. Conclusions HITs such as the InnoWell Platform have tremendous potential to improve access to cost-effective and low-intensity interventions at scale to improve and maintain mental health and well-being in later life. However, to promote adoption of and continued engagement with such tools, it is essential that these HITs are personalized and relevant for older adult end users, accounting for differences in background, clinical profiles, and levels of need.

scholarly journals The Predictors of Driving Cessation among Older Drivers in Korea

2020 ◽  
Vol 17 (19) ◽  
pp. 7206
Author(s):  
SeolHwa Moon ◽  
Kyongok Park
Keyword(s):  
Older Adults ◽  
Public Transportation ◽  
Public Safety ◽  
Traffic Accidents ◽  
Strong Predictor ◽  
The Elderly ◽  
Older Drivers ◽  
Driving Cessation ◽  
Cross Sectional ◽  
Metro System

Background: As the elderly population and the number of older drivers grow, public safety concerns about traffic accidents involving older drivers are increasing. Approaches to reduce traffic accidents involving older drivers without limiting their mobility are needed. This study aimed to investigate the driving cessation (DC) rate among older Korean adults and predictors of DC based on the comprehensive mobility framework. Method: In this cross-sectional study, data from 2970 to 10,062 older adults over 65 years old from the 2017 National Survey of Elderly People were analyzed in April 2020. Multivariate logistic regression analyses were conducted to identify the predictors of DC. Results: Residential area, an environmental factor, was a strong predictor of DC (Odds Ratio (OR) 2.21, 95% Confidential Interval (CI) 1.86–2.62). Older drivers living in an area with a metro system were 2.21 more likely to stop driving than those living in an area without a metro system. Other demographic, financial, psychosocial, physical, and cognitive variables also predicted DC. Conclusion: Environmental factors were strong predictors of older adults’ DC. Therefore, political and environmental support, such as the provision of accessible public transportation, is essential to increase the DC rate among older adults to increase public safety without decreasing their mobility.

scholarly journals An Automatic Estimation of the Rest-Interval for MotionWatch8© Using Uniaxial Movement and Lux Data

2020 ◽  
Author(s):  
Daniel Backhouse ◽  
Ryan Stanley Falck ◽  
Teresa Liu-Ambrose
Keyword(s):  
Older Adults ◽  
Sleep Duration ◽  
Light Exposure ◽  
Objective Measure ◽  
Self Report ◽  
Time Interval ◽  
Poor Sleep ◽  
Rest Interval ◽  
Scoring Method ◽  
Field Methods

Abstract Poor sleep is linked with chronic conditions common in older adults, including diabetes, heart disease, and dementia. Valid and reliable field methods to objectively measure sleep are thus greatly needed to examine how poor sleep impacts older adults. Wrist-worn actigraphy (WWA) is a common objective measure of sleep that uses motion and illuminance data to estimate sleep. The rest-interval marks the time interval between when an individual attempts to sleep and the time they get out of bed to start their day. Traditionally, the rest-interval is scored manually by trained technicians, however algorithms currently exist which automatically score WWA data, saving time and providing consistency from user-to-user. However, these algorithms ignore illuminance data and only considered motion in their estimation of the rest-interval. This study therefore examines a novel algorithm that uses illuminance data to supplement the approximation of the rest-interval from motion data. We examined a total of 1086 days of data of 129 participants who wore the MotionWatch8© WWA for ≥14 nights of observation. Resultant sleep measures from three different parameter settings were compared to sleep measures derived following a standard scoring protocol and self-report times. The algorithm showed the strongest correlation to the standard protocol (r= 0.92 for sleep duration). There were no significant differences in sleep duration, sleep efficiency and fragmentation index estimates compared to the standard scoring protocol. These results suggest that an automated rest-interval scoring method using both light exposure and acceleration data provides comparable accuracy to the standard scoring method.

scholarly journals An Automatic Estimation of the Rest-Interval for MotionWatch8© Using Uniaxial Movement and Lux Data

2020 ◽  
Author(s):  
Daniel Backhouse ◽  
Ryan Stanley Falck ◽  
Teresa Liu-Ambrose
Keyword(s):  
Older Adults ◽  
Sleep Duration ◽  
Light Exposure ◽  
Objective Measure ◽  
Self Report ◽  
Time Interval ◽  
Poor Sleep ◽  
Rest Interval ◽  
Scoring Method ◽  
Field Methods

Abstract Background: Poor sleep is linked with chronic conditions common in older adults, including diabetes, heart disease, and dementia. Valid and reliable field methods to objectively measure sleep are thus greatly needed to examine how poor sleep impacts older adults. Wrist-worn actigraphy (WWA) is a common objective measure of sleep that uses motion and illuminance data to estimate sleep. The rest-interval marks the time interval between when an individual attempts to sleep and the time they get out of bed to start their day. Traditionally, the rest-interval is scored manually by trained technicians, however algorithms currently exist which automatically score WWA data, saving time and providing consistency from user-to-user. However, these algorithms ignore illuminance data and only considered motion in their estimation of the rest-interval. This study therefore examines a novel algorithm that uses illuminance data to supplement the approximation of the rest-interval from motion data. Methods: We examined a total of 1086 days of data of 129 participants who wore the MotionWatch8© WWA for ≥14 nights of observation. Resultant sleep measures from three different parameter settings were compared to sleep measures derived following a standard scoring protocol and self-report times. Results: The algorithm showed the strongest correlation to the standard protocol (r= 0.92 for sleep duration). There were no significant differences in sleep duration, sleep efficiency and fragmentation index estimates compared to the standard scoring protocol. Conclusion: These results suggest that an automated rest-interval scoring method using both light exposure and acceleration data provides comparable accuracy to the standard scoring method.

An Optimal Self-Report Physical Activity Measure for Older Adults: Does Physical Function Matter?

2020 ◽  
pp. 1-7
Author(s):  
Nancy W. Glynn ◽  
Alexa J. Meinhardt ◽  
Kelsea R. LaSorda ◽  
Jessica L. Graves ◽  
Theresa Gmelin ◽  
...  
Keyword(s):  
Physical Activity ◽  
Older Adults ◽  
Physical Function ◽  
Objective Measure ◽  
The Elderly ◽  
Community Dwelling ◽  
Self Report ◽  
Sensewear Armband ◽  
Physical Activity Measure ◽  
Community Dwelling Older Adults

The authors compared two self-report measures of physical activity, the Physical Activity Scale for the Elderly (PASE) and the Community Healthy Activities Model Program for Seniors (CHAMPS), against the device-derived SenseWear Armband (SWA), to identify a recommended self-report tool to measure physical activity in older adults across physical function levels. A total of 65 community-dwelling older adults completed the PASE, CHAMPS, and seven full days of SWA wear. The authors measured physical function using the modified short physical performance battery (SPPB) and a usual-paced 6-m walk. Age- and sex-adjusted Spearman correlations showed that CHAMPS and SWA were correlated in higher functioning participants (SPPB: ρ = .33, p = .03; gait speed: ρ = .40, p = .006) and also correlated in lower functioning participants for SPPB (ρ = .70, p = .003) only. PASE and SWA were not significantly correlated across physical function. When an objective measure of physical activity is not practical, the CHAMPS questionnaire appears to capture physical activity for older adults across physical function levels.

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