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mHealth Apps for the Self-Management of Low Back Pain: Systematic Search in App Stores and Content Analysis.
Zhou, Tianyu; Salman, David; McGregor, Alison.
Afiliação
  • Zhou T; Department of Surgery and Cancer, Imperial College London, London, United Kingdom.
  • Salman D; Department of Primary Care and Public Health, Imperial College London, London, United Kingdom.
  • McGregor A; Department of Surgery and Cancer, Imperial College London, London, United Kingdom.
JMIR Mhealth Uhealth ; 12: e53262, 2024 Feb 01.
Article em En | MEDLINE | ID: mdl-38300700
ABSTRACT

BACKGROUND:

With the rapid development of mobile health (mHealth) technology, many health apps have been introduced to the commercial market for people with back pain conditions. However, little is known about their content, quality, approaches to care for low back pain (LBP), and associated risks of use.

OBJECTIVE:

The aims of this research were to (1) identify apps for the self-management of LBP currently on the market and (2) assess their quality, intervention content, theoretical approaches, and risk-related approaches.

METHODS:

The UK iTunes and Google Play stores were initially searched for apps related to the self-management of LBP in May 2022. A repeat search in June 2023 was conducted to ensure that any relevant new apps developed in the last year were incorporated into the review. A total of 3 keywords recommended by the Cochrane Back and Neck Group were used to search apps "low back pain," "back pain," and "lumbago." The quality of the apps was assessed by using the 5-point Mobile App Rating Scale (MARS).

RESULTS:

A total of 69 apps (25 iOS and 44 Android) met the inclusion criteria. These LBP self-management apps mainly provide recommendations on muscle stretching (n=51, 73.9%), muscle strengthening (n=42, 60.9%), core stability exercises (n=32, 46.4%), yoga (n=19, 27.5%), and information about LBP mechanisms (n=17, 24.6%). Most interventions (n=14, 78%) are consistent with the recommendations in the National Institute for Health and Care Excellence (NICE) guidelines. The mean (SD) MARS overall score of included apps was 2.4 (0.44) out of a possible 5 points. The functionality dimension was associated with the highest score (3.0), whereas the engagement and information dimension resulted in the lowest score (2.1). Regarding theoretical and risk-related approaches, 18 (26.1%) of the 69 apps reported the rate of intervention progression, 11 (15.9%) reported safety checks, only 1 (1.4%) reported personalization of care, and none reported the theoretical care model or the age group targeted.

CONCLUSIONS:

mHealth apps are potentially promising alternatives to help people manage their LBP; however, most of the LBP self-management apps were of poor quality and did not report the theoretical approaches to care and their associated risks. Although nearly all apps reviewed included a component of care listed in the NICE guidelines, the model of care delivery or embracement of care principles such as the application of a biopsychosocial model was unclear.
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Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Assunto principal: Telemedicina / Dor Lombar / Aplicativos Móveis / Autogestão Tipo de estudo: Prognostic_studies Limite: Humans Idioma: En Revista: JMIR Mhealth Uhealth Ano de publicação: 2024 Tipo de documento: Article

Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Assunto principal: Telemedicina / Dor Lombar / Aplicativos Móveis / Autogestão Tipo de estudo: Prognostic_studies Limite: Humans Idioma: En Revista: JMIR Mhealth Uhealth Ano de publicação: 2024 Tipo de documento: Article