Contribution of mobile health applications to self-management by consumers: review of published evidence
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Notice bibliographique
Résumé
Objective The aim of the present study was to review the contribution of mobile health applications ('apps') to consumers' self-management of chronic health conditions, and the potential for this practice to inform health policy, procedures and guidelines. Methods A search was performed on the MEDLINE, Cochrane Library, ProQuest and Global Health (Ovid) databases using the search terms 'mobile app*', 'self-care', 'self-monitoring', 'trial', 'intervention*' and various medical conditions. The search was supplemented with manual location of emerging literature and government reports. Mapping review methods identified relevant titles and abstracts, followed by review of content to determine extant research, reports addressing the key questions, and gaps suggesting areas for future research. Available studies were organised by disease state, and presented in a narrative analysis. Results Four studies describing the results of clinical trials were identified from Canada, England, Taiwan and Australia; all but the Australian study used custom-made apps. The available studies examined the effect of apps in health monitoring, reporting positive but not robust findings. Australian public policy and government reports acknowledge and support self-management, but do not address the potential contribution of mobile interventions. Conclusions There are limited controlled trials testing the contribution of health apps to consumers' self-management. Further evidence in this field is required to inform health policy and practice relating to self-management. What is known about the topic? Australian health policy encourages self-care by health consumers to reduce expenditure in health services. A fundamental component of self-care in chronic health conditions is self-monitoring, which can be used to assess progress towards treatment goals, as well as signs and symptoms of disease exacerbation. An abundance of mobile health apps is available for self-monitoring. What does this study add? A limited number of randomised control trials have assessed the clinical impact of health apps for self-monitoring. The body of evidence relating to current and long-term clinical impact is developing. Despite endorsing self-care, Australian health policy does not address the use and potential contribution of mobile health apps to health care. What are the implications? Widespread and sustained use of validated mobile health apps for chronic health conditions should have potential to improve consumer independence, confidence and burden on health services in the longer term. However, a significant body of scientific evidence has not yet been established; this is mirrored in the lack of acknowledgement of health apps in Australian health policy referring to consumers' self-management.
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Prédiction distillée sur la base complète
Imitation des enseignantsNi prévalence calibrée, ni vérité terrain. Validation humaine à venir. Apprise à partir de 10 348 étiquettes directes de Codex et de 10 348 étiquettes directes de Gemma. Le mode candidate est l'union des têtes enseignantes seuillées; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont ni des étiquettes humaines ni des étiquettes directes de modèles de pointe.
Scores Codex et Gemma par catégorie
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,019 | 0,001 |
| Méta-épidémiologie (sens strict) | 0,001 | 0,001 |
| Méta-épidémiologie (sens large) | 0,011 | 0,001 |
| Bibliométrie | 0,001 | 0,004 |
| Études des sciences et des technologies | 0,001 | 0,000 |
| Communication savante | 0,000 | 0,000 |
| Science ouverte | 0,002 | 0,000 |
| Intégrité de la recherche | 0,001 | 0,002 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,001 | 0,001 |
Scores machine (provisoires)
Les deux têtes enseignantes du modèle étudiant, lues sur ce travail. Un score ordonne la base pour la relecture; il n'affirme jamais une catégorie, et le statut de validation accompagne chaque rangée tel quel.
Scores de référence d'un modèle non mature (critères de maturité non atteints, 7 itérations). Un score ordonne; il n'affirme jamais une catégorie.
score_only:v0-immature-baseline · tel quel depuis la passe de notation : score_only signifie que le nombre peut ordonner les travaux, et qu'aucune étiquette de catégorie n'en découle