Evidence map›Paper›PMID 39286449›Full record

ArticleTechnology and disability2022

Feasibility of automated in-vehicle technologies on volunteers' driving performance.

Sherrilene Classen, Sandra Winter, Jiajun Wei, Mary Jeghers, Jason Rogers, Wayne Giang

Abstract read
PubMed Full text at PMC Publisher
In one paragraph

Article in Technology and disability, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

0 citing papers in PubMed.

No citing paper in PubMed yet.

4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

6 authors.

Sherrilene ClassenDepartment of Occupational Therapy, College of Public Health and Health Professions, University of Florida, Gainesville, FL, USA.
Sandra WinterDepartment of Occupational Therapy, College of Public Health and Health Professions, University of Florida, Gainesville, FL, USA.
Jiajun WeiDepartment of Occupational Therapy, College of Public Health and Health Professions, University of Florida, Gainesville, FL, USA.
Mary JeghersDepartment of Occupational Therapy, College of Public Health and Health Professions, University of Florida, Gainesville, FL, USA.
Jason RogersDepartment of Occupational Therapy, College of Public Health and Health Professions, University of Florida, Gainesville, FL, USA.
Wayne GiangDepartment of Industrial and Systems Engineering, Herbert Wertheim College of Engineering, University of Florida, Gainesville, FL, USA.

Funding

ACL HHS 90IFRE0035
6 · The paper itself

Abstract

backgroundAutomated in-vehicle technologies, specifically in-vehicle information systems (IVIS) and advanced driver assistance systems (ADAS), are increasingly common in today's cars. Previous studies illustrate benefits of using IVIS and ADAS to improve safety, convenience, and comfort in healthy older drivers. However, research is sparse on the feasibility of such technologies for medically at-risk drivers, such as those with Parkinson's disease (PD).

objectiveThis study enrolled healthy volunteer drivers to examine the feasibility of the procedures and measures for evaluating the effects of IVIS and ADAS on their driving performance.

methodsDuring this feasibility study researchers compared drives completed with and without support of IVIS and ADAS, as participants drove a 2019 Toyota Camry XLE. The test vehicle was equipped with IVIS, ADAS, cameras, a telematics system, and sensors. Participants drove the road course supervised by a Driver Rehabilitation Specialist (DRS).

resultsOverall study procedures and vehicle equipment were feasible and provided sufficient data collection for measuring the impact of IVIS and ADAS on driving performance. Data observation by the DRS combined with data captured from cameras and telematics, facilitated comparisons to increase data reliability and validity.

conclusionsFeasibility study findings informed a randomized clinical trial, examining the use of IVIS and ADAS technologies as an intervention to support drivers with Parkinson's disease.

Indexed as

advanced driver assistance systemsdriver rehabilitation specialistFeasibility studyin-vehicle information systemsvolunteer drivers

Identifiers

PMID39286449
PMCPMC11404526

What OpenQuestion holds

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Registered trials

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.