Evidence map›Paper›PMID 39963526›Full record

ArticleInnovation in aging2025

Evaluation and Modification of the Multifactorial Model of Driving Safety Among Older Adults.

Junyan Tian, Jacqueline Mogle, Kaarin J Anstey, Lesley A Ross

Abstract read
In one paragraph

Article in Innovation in aging, 2025. 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

4 authors.

Junyan TianDepartment of Human Development and Family Studies, The Pennsylvania State University, University Park, Pennsylvania, USA.ORCID https://orcid.org/0000-0001-8119-4799
Jacqueline MogleDepartment of Psychology and Institute for Engaged Aging, Clemson University, Clemson, South Carolina, USA.ORCID https://orcid.org/0000-0002-6082-228X
Kaarin J AnsteyNeuroscience Research Australia, University of New South Wales, Randwick, New South Wales, Australia.ORCID https://orcid.org/0000-0002-9706-9316
Lesley A RossDepartment of Psychology and Institute for Engaged Aging, Clemson University, Clemson, South Carolina, USA.ORCID https://orcid.org/0000-0002-3794-158X

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Background and Objectives: Cognitive, visual, and physical performance are associated with driving safety. However, there are few comprehensive models that empirically evaluate how such factors together affect driving safety in older adults. The present study used structural equation modeling (SEM) to evaluate Anstey's original Multifactorial Model of Driving Safety (MMDS) (2005) as well as a modified MMDS that incorporates recent research. Research Design and Methods: We used the baseline data from the Advanced Cognitive Training for Independent and Vital Elderly study. Participants ( Results: Using SEM, Anstey's original MMDS did not achieve adequate fit (CFI = 0.850, TLI = 0.777, RMSEA = 0.074). However, the modified MMDS had a good fit (CFI = 0.961, TLI = 0.934, RMSEA = 0.040). We found that better physical function was correlated with less driving avoidance (β = 0.28, Discussion and Implications: This study highlights the importance of cognition and physical function in older adults safe driving. Implications for future directions and public policy considerations are discussed. Future research should examine possible dynamic changes between these predictors and driving in a longitudinal model.

Indexed as

CognitionDriving safety modelOlder driversPhysical functionVision

Identifiers

PMID39963526
PMCPMC11831225

What OpenQuestion holds

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LicenceCC BY-NC-ND
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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.