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Attrition Within Digital Health Interventions for People With Multiple Sclerosis: Systematic Review and Meta-analysis.
Bevens, William; Weiland, Tracey; Gray, Kathleen; Jelinek, George; Neate, Sandra; Simpson-Yap, Steve.
Afiliação
  • Bevens W; Centre for Epidemiology and Biostatistics, The University of Melbourne, Carlton, Australia.
  • Weiland T; Centre for Epidemiology and Biostatistics, The University of Melbourne, Carlton, Australia.
  • Gray K; Centre for Digital Transformation of Health, The University of Melbourne, Carlton, Australia.
  • Jelinek G; Centre for Epidemiology and Biostatistics, The University of Melbourne, Carlton, Australia.
  • Neate S; Centre for Epidemiology and Biostatistics, The University of Melbourne, Carlton, Australia.
  • Simpson-Yap S; Centre for Epidemiology and Biostatistics, The University of Melbourne, Carlton, Australia.
J Med Internet Res ; 24(2): e27735, 2022 02 09.
Article em En | MEDLINE | ID: mdl-35138262
ABSTRACT

BACKGROUND:

Digital 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.

OBJECTIVE:

This 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).

METHODS:

We 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.

RESULTS:

There 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.

CONCLUSIONS:

This 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.
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Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Assunto principal: Autogestão / Esclerose Múltipla Tipo de estudo: Clinical_trials / Prognostic_studies / Systematic_reviews Limite: Humans Idioma: En Revista: J Med Internet Res Assunto da revista: INFORMATICA MEDICA Ano de publicação: 2022 Tipo de documento: Article País de afiliação: Austrália

Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Assunto principal: Autogestão / Esclerose Múltipla Tipo de estudo: Clinical_trials / Prognostic_studies / Systematic_reviews Limite: Humans Idioma: En Revista: J Med Internet Res Assunto da revista: INFORMATICA MEDICA Ano de publicação: 2022 Tipo de documento: Article País de afiliação: Austrália