Going digital: a narrative overview of the effects, quality and utility of mobile apps in chronic disease self-management
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Notice bibliographique
Résumé
Objective Smartphone health applications (apps) are being increasingly used to assist patients in chronic disease self-management. The effects of such apps on patient outcomes are uncertain, as are design features that maximise usability and efficacy, and the best methods for evaluating app quality and utility. Methods In assessing efficacy, PubMed, Cochrane Library and EMBASE were searched for systematic reviews (and single studies if no systematic review was available) published between January 2007 and January 2018 using search terms (and synonyms) of 'smartphone' and 'mobile applications', and terms for each of 11 chronic diseases: asthma, chronic obstructive lung disease (COPD), diabetes, chronic pain, serious mental health disorders, alcohol and substance addiction, heart failure, ischaemic heart disease, cancer, cognitive impairment, chronic kidney disease (CKD). With regard to design features and evaluation methods, additional reviews were sought using search terms 'design', 'quality,' 'usability', 'functionality,' 'adherence', 'evaluation' and related synonyms. Results Of 13 reviews and six single studies assessing efficacy, consistent evidence of benefit was seen only with apps for diabetes, as measured by decreased glycosylated haemoglobin levels (HbA1c). Some, but not all, studies showed benefit in asthma, low back pain, alcohol addiction, heart failure, ischaemic heart disease and cancer. There was no evidence of benefit in COPD, cognitive impairment or CKD. In all studies, benefits were clinically marginal and none related to morbid events or hospitalisation. Twelve design features were identified as enhancing usability. An evaluation framework comprising 32 items was formulated. Conclusion Evidence of clinical benefit of most available apps is very limited. Design features that enhance usability and maximise efficacy were identified. A provisional 'first-pass' evaluation framework is proposed that can help decide which apps should be endorsed by government agencies following more detailed technical assessments and which could then be recommended with confidence by clinicians to their patients. What is known about the topic? Smartphone health apps have attracted considerable interest from patients and health managers as a means of promoting more effective self-management of chronic diseases, which leads to better health outcomes. However, most commercially available apps have never been evaluated for benefits or harms in clinical trials, and there are currently no agreed quality criteria, standards or regulations to ensure health apps are user-friendly, accurate in content, evidence based or efficacious. What does this paper add? This paper presents a comprehensive review of evidence relating to the efficacy, usability and evaluation of apps for 11 common diseases aimed at assisting patients in self-management. Consistent evidence of benefit was only seen for diabetes apps; there was absent or conflicting evidence of benefit for apps for the remaining 10 diseases. Benefits that were detected were of marginal clinical importance, with no reporting of hard clinical end-points, such as mortality or hospitalisations. Only a minority of studies explicitly reported using behaviour change theories to underpin the app intervention. Many apps lacked design features that the literature identified as enhancing usability and potential to confer benefit. Despite a plethora of published evaluation tools, there is no universal framework that covers all relevant clinical and technical attributes. An inclusive list of evaluation criteria is proposed that may overcome this shortcoming. What are the implications for practitioners? The number of smartphone apps will continue to grow, as will the appetite for patients and clinicians to use them in chronic disease self-management. However, the evidence to date of clinical benefit of most apps already available is very limited. Design features that enhance usability and clinical efficacy need to be considered. In making decisions about which apps should be endorsed by government agencies and recommended with confidence by clinicians to their patients, a comprehensive but workable evaluation framework needs to be used by bodies assuming the roles of setting and applying standards.
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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 | 0,005 | 0,001 |
| Méta-épidémiologie (sens strict) | 0,001 | 0,000 |
| Méta-épidémiologie (sens large) | 0,005 | 0,001 |
| Bibliométrie | 0,000 | 0,002 |
| Études des sciences et des technologies | 0,001 | 0,000 |
| Communication savante | 0,000 | 0,000 |
| Science ouverte | 0,001 | 0,000 |
| Intégrité de la recherche | 0,000 | 0,001 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,000 | 0,000 |
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