Evidence map›Paper›PMID 42774205›Full record

ArticleFrontiers in digital health2026

User-centered design and formative evaluation of a gait dashboard for multidimensional walking assessment in multiple sclerosis.

Brita Sedlmayr, Katrin Trentzsch, Maria Zerlik, Sophia Grummt, Heidi Stölzer-Hutsch, Maximilian Rechenberg, Maximilian Hartmann, Caroline Glathe, Katharina Schuler, Tjalf Ziemssen

Abstract read
PubMed Full text at PMC Publisher
In one paragraph

Article in Frontiers in digital health, 2026. 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

10 authors.

Brita SedlmayrInstitute for Medical Informatics and Biometry, Faculty of Medicine, University Hospital Carl Gustav Carus, TUD Dresden University of Technology, Dresden, Germany.
Katrin TrentzschCenter of Clinical Neuroscience, Department of Neurology, Faculty of Medicine and University Hospital Carl Gustav Carus Dresden, TUD Dresden University of Technology, Dresden, Germany.
Maria ZerlikInstitute for Medical Informatics and Biometry, Faculty of Medicine, University Hospital Carl Gustav Carus, TUD Dresden University of Technology, Dresden, Germany.
Sophia GrummtInstitute for Medical Informatics and Biometry, Faculty of Medicine, University Hospital Carl Gustav Carus, TUD Dresden University of Technology, Dresden, Germany.
Heidi Stölzer-HutschCenter of Clinical Neuroscience, Department of Neurology, Faculty of Medicine and University Hospital Carl Gustav Carus Dresden, TUD Dresden University of Technology, Dresden, Germany.
Maximilian RechenbergCenter of Clinical Neuroscience, Department of Neurology, Faculty of Medicine and University Hospital Carl Gustav Carus Dresden, TUD Dresden University of Technology, Dresden, Germany.
Maximilian HartmannCenter of Clinical Neuroscience, Department of Neurology, Faculty of Medicine and University Hospital Carl Gustav Carus Dresden, TUD Dresden University of Technology, Dresden, Germany.
Caroline GlatheInstitute for Medical Informatics and Biometry, Faculty of Medicine, University Hospital Carl Gustav Carus, TUD Dresden University of Technology, Dresden, Germany.
Katharina SchulerInstitute for Medical Informatics and Biometry, Faculty of Medicine, University Hospital Carl Gustav Carus, TUD Dresden University of Technology, Dresden, Germany.
Tjalf ZiemssenCenter of Clinical Neuroscience, Department of Neurology, Faculty of Medicine and University Hospital Carl Gustav Carus Dresden, TUD Dresden University of Technology, Dresden, Germany.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Digital gait analysis using wearable sensors and instrumented walkways is increasingly implemented in routine care for people with multiple sclerosis. However, multidimensional walking assessments generate longitudinal and heterogeneous outputs that are often presented in fragmented, hard-to-interpret reports, limiting their usefulness for clinical communication and shared decision-making. This study aimed to develop a patient-centered dashboard that integrates multidimensional gait data into a coherent and intuitive overview, to apply a human-centered design process aligned with routine clinical workflows, and to conduct a formative concept evaluation of the dashboard regarding comprehensibility, perceived usability, and perceived usefulness from the perspectives of medical professionals and patients. User requirements were identified through contextual interviews, workflow analysis, persona development, a stakeholder workshop, and a patient survey. Two mid-fidelity dashboard prototypes were iteratively developed and evaluated. The first prototype was assessed by medical professionals (

Indexed as

dashboarddata visualizationdigital healthgait analysismultiple sclerosisuser-centered design

Identifiers

PMID42774205
PMCPMC13593768

What OpenQuestion holds

Textmetadata
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.