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Selecting and describing control conditions in mobile health randomized controlled trials: a proposed typology
Hundreds of randomized controlled trials (RCTs) have tested the efficacy of mobile health (mHealth) tools for a wide range of mental and behavioral health outcomes. These RCTs have used a variety of control condition types which dramatically influence the scientific inferences that can be drawn from...
Autores principales: | , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Nature Publishing Group UK
2023
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10541862/ https://www.ncbi.nlm.nih.gov/pubmed/37775522 http://dx.doi.org/10.1038/s41746-023-00923-7 |
Sumario: | Hundreds of randomized controlled trials (RCTs) have tested the efficacy of mobile health (mHealth) tools for a wide range of mental and behavioral health outcomes. These RCTs have used a variety of control condition types which dramatically influence the scientific inferences that can be drawn from a given study. Unfortunately, nomenclature across mHealth RCTs is inconsistent and meta-analyses commonly combine control conditions that differ in potentially important ways. We propose a typology of control condition types in mHealth RCTs. We define 11 control condition types, discuss key dimensions on which they differ, provide a decision tree for selecting and identifying types, and describe the scientific inferences each comparison allows. We propose a five-tier comparison strength gradation along with four simplified categorization schemes. Lastly, we discuss unresolved definitional, ethical, and meta-analytic issues related to the categorization of control conditions in mHealth RCTs. |
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