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Can a Single Variable Predict Early Dropout From Digital Health Interventions? Comparison of Predictive Models From Two Large Randomized Trials
BACKGROUND: A single generalizable metric that accurately predicts early dropout from digital health interventions has the potential to readily inform intervention targets and treatment augmentations that could boost retention and intervention outcomes. We recently identified a type of early dropout...
Autores principales: | Bricker, Jonathan, Miao, Zhen, Mull, Kristin, Santiago-Torres, Margarita, Vock, David M |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
JMIR Publications
2023
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9898835/ https://www.ncbi.nlm.nih.gov/pubmed/36662550 http://dx.doi.org/10.2196/43629 |
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