Digital Asthma Self-Management Interventions: A Systematic Review
Notice bibliographique
Résumé
BACKGROUND: Many people with asthma tolerate symptoms and lifestyle limitations unnecessarily by not utilizing proven therapies. Better support for self-management is known to improve asthma control, and increasingly the Internet and other digital media are being used to deliver that support. OBJECTIVE: Our goal was to summarize current knowledge, evidenced through existing systematic reviews, of the effectiveness and implementation of digital self-management support for adults and children with asthma and to examine what features help or hinder the use of these programs. METHODS: A comprehensive search strategy combined 3 facets of search terms: (1) online technology, (2) asthma, and (3) self-management/behavior change/patient experience. We undertook searches of 14 databases, and reference and citation searching. We included qualitative and quantitative systematic reviews about online or computerized interventions facilitating self-management. Title, abstract, full paper screening, and quality appraisal were performed by two researchers independently. Data extraction was undertaken using standardized forms. RESULTS: A total of 3810 unique papers were identified. Twenty-nine systematic reviews met inclusion criteria: the majority were from the United States (n=12), the rest from United Kingdom (n=6), Canada (n=3), Portugal (n=2), and Australia, France, Spain, Norway, Taiwan, and Greece (1 each). Only 10 systematic reviews fulfilled pre-determined quality standards, describing 19 clinical trials. Interventions were heterogeneous: duration of interventions ranging from single use, to 24-hour access for 12 months, and incorporating varying degrees of health professional involvement. Dropout rates ranged from 5-23%. Four RCTs were aimed at adults (overall range 3-65 years). Participants were inadequately described: socioeconomic status 0/19, ethnicity 6/19, and gender 15/19. No qualitative systematic reviews were included. Meta-analysis was not attempted due to heterogeneity and inadequate information provision within reviews. There was no evidence of harm from digital interventions. All RCTs that examined knowledge (n=2) and activity limitation (n=2) showed improvement in the intervention group. Digital interventions improved markers of self care (5/6), quality of life (4/7), and medication use (2/3). Effects on symptoms (6/12) and school absences (2/4) were equivocal, with no evidence of overall benefits on lung function (2/6), or health service use (2/15). No specific data on economic analyses were provided. Intervention descriptions were generally brief making it impossible to identify which specific "ingredients" of interventions contribute most to improving outcomes. CONCLUSIONS: Digital self-management interventions show promise, with evidence of beneficial effects on some outcomes. There is no evidence about utility in those over 65 years and no information about socioeconomic status of participants, making understanding the "reach" of such interventions difficult. Digital interventions are poorly described within reviews, with insufficient information about barriers and facilitators to their uptake and utilization. To address these gaps, a detailed quantitative systematic review of digital asthma interventions and an examination of the primary qualitative literature are warranted, as well as greater emphasis on economic analysis within trials.
Récupéré en direct depuis OpenAlex et désinversé. Les résumés ne sont pas conservés dans cette base de données : les index inversés représentent 8,6 Go des 9,3 Go de texte de la base, et le serveur dispose de 13 Go libres.
Comment cette classification a été obtenuedéplier
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 | 0,011 | 0,007 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,005 | 0,003 |
| Bibliométrie | 0,001 | 0,001 |
| Études des sciences et des technologies | 0,000 | 0,000 |
| Communication savante | 0,000 | 0,000 |
| Science ouverte | 0,002 | 0,001 |
| Intégrité de la recherche | 0,000 | 0,003 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,002 | 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 découleClassification
machine, non validéePrédiction automatique; les deux têtes enseignantes s’accordent sur ce qui est montré ici.
Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».