Associations between digital health intervention engagement and dietary intake: A Systematic Review (Preprint)
Notice bibliographique
Résumé
<sec> <title>BACKGROUND</title> There has been a proliferation of digital health interventions (DHIs) targeting dietary intake. Despite their potential, the effectiveness of such interventions are thought to be dependent, in part, on user engagement. However, the relationship between engagement and the effectiveness of dietary DHIs is not well understood. </sec> <sec> <title>OBJECTIVE</title> As such, the aim of this systematic review is to describe the association between DHI engagement (both usage and subjective experience) and dietary intake. </sec> <sec> <title>METHODS</title> A comprehensive search for peer-reviewed literature was undertaken in four electronic databases (EMBASE, MEDLINE, PsychINFO, Scopus) from inception to December 2019. A hand search of targeted journals, grey literature searches and a search of relevant references of similar reviews was also conducted. Studies were eligible if they examined a quantitative association between objective measures of engagement with a DHI (subjective experience or usage) and measures of dietary intake in adults (aged ≥18 years). Authors single screened studies, with a pair of review authors assessing quality of studies and extracting relevant data. Narrative syntheses using vote counting was undertaken to explore to relationship between measures of engagement and dietary intake. </sec> <sec> <title>RESULTS</title> The search resulted in 10,653 citations, of which seven studies (from nine articles) were included in the review. The majority of studies (n=5) included usage measures of engagement rather than subjective experience (n=2). Logins were the most commonly reported usage measure (n=5 studies), and fruit and vegetable intake was the most common measure of dietary intake (n=4 studies). The heterogeneity of engagement and dietary intake measures limited the use of meta-analytic techniques, however narrative review (vote counting) found mixed evidence of an association with usage measures (5 of 12 associations indicating a positive relationship, 7 were inconclusive). No evidence regarding an association with subjective experience was found (0 of 2 associations were inconclusive). The majority of included studies (n=5) were rated poor quality according to the Newcastle Ottawa Scale. </sec> <sec> <title>CONCLUSIONS</title> The findings provide some evidence supporting an association between measures of usage and fruit and vegetable intake, however this was inconsistent. No evidence was found regarding an association with subjective experience. Given the limited number of studies included in the review and poor quality of available evidence further research examining the association between DHI engagement and dietary intake using consistent measures, with an additional focus on subjective experience is warranted. </sec> <sec> <title>CLINICALTRIAL</title> CRD42018112189 </sec>
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 | 0,002 | 0,001 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,003 | 0,001 |
| Bibliométrie | 0,000 | 0,000 |
| Études des sciences et des technologies | 0,001 | 0,000 |
| Communication savante | 0,000 | 0,000 |
| Science ouverte | 0,000 | 0,000 |
| Intégrité de la recherche | 0,000 | 0,000 |
| 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 découleClassification
machine, non validéePrédiction automatique; un appel candidat d’une seule tête enseignante, pas un consensus.
Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».