Evidence map›Paper›PMID 37872471›Full record

ArticleBMC neurology2023

Acceptability of a digital health application to empower persons with multiple sclerosis with moderate to severe disability: single-arm prospective pilot study.

Max Kutzinski, Nicole Krause, Karin Riemann-Lorenz, Björn Meyer, Christoph Heesen

Abstract read
In one paragraph

Article in BMC neurology, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.

0numbers the graph read from it
0cells of the map it votes in
3citing 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

3 citing papers in PubMed.

  1. Trial
  2. Trial
  3. Effectiveness of a digital health application (Multiple sclerosis journal - experimental, translational and clinical
    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.

Max Kutzinski *Institute of Neuroimmunology and Multiple Sclerosis (INIMS), University Medical Center Hamburg-Eppendorf, Martinistraße 52, 20246, Hamburg, Germany. kutzinskim@gmail.com.ORCID http://orcid.org/0009-0008-8751-603X
Nicole Krause *Institute of Neuroimmunology and Multiple Sclerosis (INIMS), University Medical Center Hamburg-Eppendorf, Martinistraße 52, 20246, Hamburg, Germany. n.krause@uke.de.ORCID http://orcid.org/0000-0001-6681-7054
Karin Riemann-LorenzInstitute of Neuroimmunology and Multiple Sclerosis (INIMS), University Medical Center Hamburg-Eppendorf, Martinistraße 52, 20246, Hamburg, Germany.ORCID http://orcid.org/0000-0002-0779-2640
Björn MeyerResearch and Development Department, GAIA Group, Hamburg, Germany.ORCID http://orcid.org/0000-0003-1100-0260
Christoph HeesenInstitute of Neuroimmunology and Multiple Sclerosis (INIMS), University Medical Center Hamburg-Eppendorf, Martinistraße 52, 20246, Hamburg, Germany.ORCID http://orcid.org/0000-0001-8131-9467

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundMany persons with multiple sclerosis (pwMS) desire to learn how health behaviour changes (e.g., dietary adjustments, physical activity, improvements in stress management) might help them manage their disease. Previous research has shown that certain health behaviour changes can improve quality of life (QoL), fatigue and other MS outcomes. Digital health applications may be well suited to deliver relevant health behavioural interventions because of their accessibility and flexibility. The digital health application "levidex" was designed to facilitate health behaviour change by offering evidence-based patient information and cognitive-behavioural therapy techniques to pwMS. By doing so, levidex aims to improve QoL and MS symptoms such as fatigue and mental health.

objectivesA previous study reported on the development of levidex; this non-randomised pilot study examined the feasibility (practicability and acceptability) of levidex in pwMS with moderate to severe disability. Furthermore, the intervention's impact on empowerment, stress management, and relevant health behaviours (e.g., dietary behaviour, physical activity) was explored.

methodslevidex was originally developed for newly diagnosed pwMS in the first year after diagnosis and eventually modified to offer access to pwMS with moderate to severe disability. Participants (n = 43) with an Expanded Disability Status Scale between 3.5 and 7.5 and a disease duration of more than one year were eligible to participate. The intervention was used over a period of six months with measurement time points at baseline, month 3 and month 6.

resultsOut of 38 participants who completed the six-month intervention period, 18 (47.4%) completed all 16 modules and 9 (23.7%) reached modules 13-16, the long-term maintenance part of levidex. Participants rated levidex positively in terms of practicability and acceptability and had only few points of criticism such as to include more physical exercise routine suggestions suitable for participants with severe impairment. Data on secondary endpoints showed no significant changes.

conclusionThis pilot study provided evidence for the practicability and acceptability of levidex, a digital health application designed to facilitate health behaviour change in pwMS with moderate to severe disability. Adequately powered randomised controlled studies with longer follow-up periods are needed to clarify the benefit of levidex in pwMS with moderate to severe disability.

trial registrationGerman Clinical Trials Register (DRKS) DRKS00032667 (14/09/2023); Retrospectively registered.

Indexed as

Multiple SclerosisFatigueHumansPilot ProjectsProspective StudiesQuality of LifeAdvanced multiple sclerosisDigital health applicationeHealthEvidence-based medicineFeasibility testingHealth behaviour changeLifestyle interventionModerate to severe disabilityPiloting

Identifiers

PMID37872471
PMCPMC10591383

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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.