Evidence map›Paper›PMID 37369034›Full record

ArticlePhysical therapy2024

Coproduction and Usability of a Smartphone App for Falls Reporting in Parkinson Disease.

Jill Wales, Jason Moore, Jenni Naisby, Natasha Ratcliffe, Gill Barry, Annee Amjad, Alan Godfrey, Gerry Standerline, Elaine Webster, Rosie Morris

Open access · hybridAbstract read
In one paragraph

Article in Physical therapy, 2024. 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
3.9field-weighted citation impact, top 7% of its field
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, 5 citations in OpenAlex.

  1. Article
  2. 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

10 authors at 3 institutions in 1 country.

Jill WalesDepartment of Sport, Exercise and Rehabilitation, Northumbria University, Newcastle-upon-Tyne, UK.
Jason MooreDepartment of Computer and Information Sciences, Northumbria University, Newcastle-upon-Tyne, UK.
Jenni NaisbyDepartment of Sport, Exercise and Rehabilitation, Northumbria University, Newcastle-upon-Tyne, UK.
Natasha RatcliffeParkinson's UK, London, UK.
Gill BarryDepartment of Sport, Exercise and Rehabilitation, Northumbria University, Newcastle-upon-Tyne, UK.
Annee AmjadParkinson's UK, London, UK.
Alan GodfreyDepartment of Computer and Information Sciences, Northumbria University, Newcastle-upon-Tyne, UK.ORCID 0000-0003-4049-9291
Gerry StanderlinePerson with Parkinson disease, Co-Researcher, UK.
Elaine WebsterPerson with Parkinson disease, Co-Researcher, UK.
Rosie MorrisDepartment of Sport, Exercise and Rehabilitation, Northumbria University, Newcastle-upon-Tyne, UK.ORCID 0000-0002-0290-6688
English Institute of Sport · GBParkinson's UK · GBNorthumbria University · GB

Funding

Northumbria University Participatory Research FundingPrivate Physiotherapy Educational Foundation
6 · The paper itself

Abstract

objectiveThe purpose of this study was to coproduce a smart-phone application for digital falls reporting in people with Parkinson disease (PD) and to determine usability using an explanatory mixed-methods approach.

methodsThis study was undertaken in 3 phases. Phase 1 was the development phase, in which people with PD were recruited as co-researchers to the project. The researchers, alongside a project advisory group, coproduced the app over 6 months. Phase 2 was the implementation phase, in which 15 people with PD were invited to test the usability of the app. Phase 3 was the evaluation phase, in which usability was assessed using the systems usability scale by 2 focus groups with 10 people with PD from phase 2.

resultsA prototype was successfully developed by researchers and the project advisory group. The usability of the app was determined as good (75.8%) by people with PD when rating using the systems usability scale. Two focus groups (n = 5 per group) identified themes of 1) usability, 2) enhancing and understanding management of falls, and 3) recommendations and future developments.

conclusionsA successful prototype of the iFall app was developed and deemed easy to use by people with PD. The iFall app has potential use as a self-management tool for people with PD alongside integration into clinical care and research studies. IMPACT: This is the first digital outcome tool to offer reporting of falls and near-miss fall events. The app may benefit people with PD by supporting self-management, aiding clinical decisions in practice, and providing an accurate and reliable outcome measure for future research. LAY SUMMARY: A smartphone application designed in collaboration with people who have PD to record their falls was acceptable and easy to use by people with PD.

Indexed as

Mobile ApplicationsParkinson DiseaseSelf-ManagementFocus GroupsHumansSmartphoneAccidental FallsAppCo-ProductionDigital Measurement ToolParkinson DiseaseUsability

Identifiers

PMID37369034
PMCPMC10851851
OpenAlexW4382198813

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

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.