Evidence map›Paper›PMID 35138262›Full record

SynthesisJournal of medical Internet research2022

Attrition Within Digital Health Interventions for People With Multiple Sclerosis: Systematic Review and Meta-analysis.

William Bevens, Tracey Weiland, Kathleen Gray, George Jelinek, Sandra Neate, Steve Simpson-Yap

Open access · goldAbstract readMeta-AnalysisSystematic Review
PubMed Full text at PMC Publisher
In one paragraph

Synthesis in Journal of medical Internet research, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 22 papers, 4 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
22citing papers in PubMed, 4 pooled it
3.8field-weighted citation impact, top 6% 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

22 citing papers in PubMed, 4 syntheses or guidelines pooled it, 33 citations in OpenAlex.

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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

6 authors at 1 institution in 1 country.

William Bevens *Centre for Epidemiology and Biostatistics, The University of Melbourne, Carlton, Australia.ORCID 0000-0001-6944-6500
Tracey WeilandCentre for Epidemiology and Biostatistics, The University of Melbourne, Carlton, Australia.ORCID 0000-0002-4053-5507
Kathleen GrayCentre for Digital Transformation of Health, The University of Melbourne, Carlton, Australia.ORCID 0000-0003-1616-2170
George JelinekCentre for Epidemiology and Biostatistics, The University of Melbourne, Carlton, Australia.ORCID 0000-0001-6157-0910
Sandra NeateCentre for Epidemiology and Biostatistics, The University of Melbourne, Carlton, Australia.ORCID 0000-0002-0761-9848
Steve Simpson-YapCentre for Epidemiology and Biostatistics, The University of Melbourne, Carlton, Australia.ORCID 0000-0001-6521-3056
The University of Melbourne · AU

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundDigital health interventions have revolutionized multiple sclerosis (MS) care by supporting people with MS to better self-manage their disease. It is now understood that the technological elements that comprise this category of digital health interventions can influence participant engagement in self-management programs, and people with MS can experience significant barriers, influenced by these elements, to remaining engaged during a period of learning. It is essential to explore the influence of technological elements in mitigating attrition.

objectiveThis study aimed to examine the study design and technological elements of documented digital health interventions targeted at people with MS-digital health interventions that were intended to support a program of engagement over a defined period-and to explore how these correlated with attrition among participants of randomized controlled trials (RCTs).

methodsWe conducted a systematic review and meta-analysis of RCTs (n=32) describing digital health self-management interventions for people with MS. We analyzed attrition in included studies, using a random-effects model and meta-regression to measure the association between potential moderators.

resultsThere were no measured differences in attrition between the intervention and control arms; however, some of the heterogeneity observed was explained by the composite technological element score. The pooled attrition rates for the intervention and control arms were 14.7% and 15.6%, respectively.

conclusionsThis paper provides insight into the technological composition of digital health interventions designed for people with MS and describes the degree of attrition in both study arms. This paper will aid in the design of future studies in this area, particularly for digital health interventions of this type.

Indexed as

Multiple SclerosisSelf-ManagementHumansRandomized Controlled Trials as TopicattritionDHIdigital healthdigital health interventionseHealthmeta-analysisMSmultiple sclerosisrandomized controlled trialsself-management

Identifiers

PMID35138262
PMCPMC8867299
OpenAlexW3205594150

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.