Evidence map›Paper›PMID 39869778›Full record

ArticleAssistive technology : the official journal of RESNA2025

Ultralight wheelchair part failures are associated with sensor-monitored road shocks: A pilot study.

Anand Mhatre, Carmen DiGiovine, Alyssa Boccardi, Fangzheng Wu, Bryan Hess

Abstract read
In one paragraph

Article in Assistive technology : the official journal of RESNA, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing 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

2 citing papers in PubMed.

  1. Reliability assessment of power wheelchairs.The journal of spinal cord medicine · 2026
    Article
  2. Wheelchair Servicing for Older Adults: Cross-Sectional Study.JMIR rehabilitation and assistive technologies · 2025
    Article
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

5 authors.

Anand MhatreSchool of Health and Rehabilitation Sciences, College of Medicine, Ohio State University, Columbus, Ohio, USA.ORCID 0000-0001-6179-3727
Carmen DiGiovineSchool of Health and Rehabilitation Sciences, College of Medicine, Ohio State University, Columbus, Ohio, USA.ORCID 0000-0003-4126-5016
Alyssa BoccardiDepartment of Rehabilitation Science and Technology, University of Pittsburgh, Pittsburgh, Pennsylvania, USA.ORCID 0000-0003-2799-4749
Fangzheng WuDepartment of Rehabilitation Science and Technology, University of Pittsburgh, Pittsburgh, Pennsylvania, USA.ORCID 0000-0002-5353-4589
Bryan HessDepartment of Rehabilitation Science and Technology, University of Pittsburgh, Pittsburgh, Pennsylvania, USA.ORCID 0009-0006-4806-4806

Funding

University of Pittsburgh Clinical and Translational Science InstituteUL1TR001857 · NCATS · UNIVERSITY OF PITTSBURGH AT PITTSBURGH · PI REIS, STEVEN E · 2016 to 2025
$129.3M
Development of a Wheelchair Maintenance Alert Application for Elderly Wheelchair UsersR03AG069836 · NIA · UNIVERSITY OF PITTSBURGH AT PITTSBURGH · PI MHATRE, ANAND · 2020 to 2020
$76k
NCATS NIH HHS UL1 TR001857NIA NIH HHS R03 AG069836
6 · The paper itself

Abstract

Wheelchair part failures and repairs have significantly increased over the last decade, leading to severe consequences for wheelchair users. Servicing these devices by wheelchair repair technicians has reduced part failures. However, no tools or technologies have been developed to support servicing in practice. To inform servicing events, risk factors affecting wheelchair quality and reliability need to be identified. This pilot study tracks wheelchair usage for a week in the community for eight ultralight manual wheelchair users and assesses the relationship between usage variables and user-reported part failures over 20 months. The participants' preferences for using smart technology for wheelchair servicing were evaluated. At least 73 wheelchair part failures and two adverse consequences were reported. Data analysis indicated associations between part failure frequency, usage variable of road shocks, wheelchair maintenance frequency, and the user's demographic characteristics of training status and transportation. Six participants favored using smart technology for wheelchair servicing. This study's findings encourage the development of usage monitoring technology and failure prediction models to support technician-led servicing and prevent wheelchair failures and user consequences.

Indexed as

Equipment FailureWheelchairsAdultAgedEquipment DesignFemaleHumansMaleMiddle AgedPilot Projectsbreakdownfailuremaintenancerepairservicingtelemonitoringwheelchairs

Identifiers

PMID39869778
PMCPMC11864886

What OpenQuestion holds

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Registered trials

None linked

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.