An Interactive Mobile Phone App (SMART 5-A-DAY) for Increasing Knowledge of and Adherence to Fruit and Vegetable Recommendations: Development and Pilot Randomized Controlled Trial
Notice bibliographique
Résumé
BACKGROUND: Fruit and vegetable consumption is important for health, but many individuals fail to consume adequate amounts for health benefits. Although many individuals are aware of current fruit and vegetable consumption recommendations, research suggests that adherence to these is hampered by low knowledge of the details of these recommendations. OBJECTIVE: This paper reports the development and details of a pilot randomized controlled test of a novel interactive mobile phone app for addressing low knowledge of the UK 5-a-day fruit and vegetable recommendations. METHODS: Requirements for the app were first defined by researchers and potential end users and prioritized using the MoSCoW (Must have, Should have, Could have, Won't have) method. Second, a prototype mobile phone app was developed using an agile approach. Third, the prototype app was tested in a randomized controlled pilot trial for impacts on knowledge and intake of fruit and vegetables. Volunteers were randomized to either receive (n=50) or not receive the app (n=44) for 2 or 4 weeks, and fruit and vegetable knowledge, intake, and behavior were assessed at the beginning of the study and after 1 and 2 weeks or after 2 and 4 weeks, respectively. App usage and qualitative feedback were also investigated. All findings then informed the development of a final app. RESULTS: Low knowledge of consumption recommendations centered around portion sizes and the need for variety, and an interactive mobile phone app was considered a suitable tool for improving this knowledge in a practical manner that would be available both at time of consumption and outside of these times. The pilot test revealed improved behavior after 2 weeks compared with baseline in volunteers who received the app, but improvements in knowledge on fruit and vegetable recommendations were found in both groups, and no improvements in fruit and vegetable intakes were found in formal measures. Patterns of app usage and qualitative feedback also suggested a number of modifications. The resultant final app incorporates several behavior change techniques (goal-setting, self-monitoring, and personalized feedback) as well as aiming to improve knowledge. CONCLUSIONS: A novel interactive mobile phone app was successfully developed based on requirements, and when tested in a pilot randomized controlled trial, this app was found to have some impacts on fruit and vegetable outcomes. Although benefits from the app were small, impacts will likely increase as a result of recent modifications. The final SMART 5-A-DAY app is available in the Google Play Store and now needs testing in the target population. TRIAL REGISTRATION: ClinicalTrials.gov NCT02779491; https://www.clinicaltrials.gov/ct2/show/NCT02779491.
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Comment cette classification a été obtenuedéplier
Prédiction machine sur la base complète
Imitation des enseignantsNi prévalence calibrée, ni vérité terrain. Validation humaine à venir. Le volet Gemma est une étiquette directe du modèle pour chaque travail de la base, lue sur la notice réduite au titre. Le volet Codex est un classifieur appris des 10 348 étiquettes directes de Codex et calibré sur les taux pondérés de l'échantillon; les champs sans appui suffisant ne portent aucun appel Codex. Le mode candidate est l'union des deux volets; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont pas des étiquettes humaines.
Scores du classifieur distillé par catégorie (deux têtes)
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,009 | 0,013 |
| Méta-épidémiologie (sens strict) | 0,002 | 0,001 |
| Méta-épidémiologie (sens large) | 0,003 | 0,003 |
| Bibliométrie | 0,001 | 0,001 |
| Études des sciences et des technologies | 0,001 | 0,002 |
| Communication savante | 0,002 | 0,002 |
| Science ouverte | 0,002 | 0,001 |
| Intégrité de la recherche | 0,003 | 0,002 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,013 | 0,002 |
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 source (Gemma direct ou Codex distillé), 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 ».