Stephanie Carreiro1, Mark Newcomb2, Rebecca Leach2, Simon Ostrowski2, Edwin D Boudreaux2, Daniel Amante3. 1. Department of Emergency Medicine, University of Massachusetts Medical School, 55 Lake Avenue North, Worcester, MA, 01655, USA. Electronic address: stephanie.carreiro@umassmed.edu. 2. Department of Emergency Medicine, University of Massachusetts Medical School, 55 Lake Avenue North, Worcester, MA, 01655, USA. 3. Department of Population and Quantitative Health Sciences, University of Massachusetts Medical School, 368 Plantation Street, Worcester, MA, 01605, USA.
Abstract
BACKGROUND: Connected interventions use data collected through mobile/wearable devices to trigger real-time interventions and have great potential to improve treatment for substance use disorder (SUD). This review aims to describe the current landscape, effectiveness and usability of connected interventions for SUD. METHODS: A systematic review was conducted to identify articles evaluating connected health interventions for SUD in accordance with the Preferred Reporting Items for Systematic Reviews and Meta-Analyses guidelines. Three databases (PubMed, IEEE, and Scopus) were searched over a five-year period. Included articles described a connected health intervention targeting SUD and provided outcomes data. Data were extracted using a standardized reporting tool. RESULTS: A total of 1676 unique articles were identified during the initial search, with 32 articles included in the final analysis. Seven articles of the 32 were derived from two large studies. The most commonly studied SUD was alcohol use disorder. Sixteen articles reported at least one statistically significant result with respect to reduced craving and/or substance use. The majority of articles used ecological momentary assessment to trigger interventions, while four used biologic/physiologic data. Two articles used a wearable device. Common intervention types included craving management, coping assistance, and tailored feedback. Twenty-three articles measured usability factors, and acceptability was generally reported as high. CONCLUSION: Identified themes included a focus on AUD, use of smart phones, use of EMA for intervention delivery, positive effects on SUD related outcomes, and overall high acceptability. Wearables that directly monitor biologic data and predictive analytics using integrated data streams represent understudied opportunities for new research.
BACKGROUND: Connected interventions use data collected through mobile/wearable devices to trigger real-time interventions and have great potential to improve treatment for substance use disorder (SUD). This review aims to describe the current landscape, effectiveness and usability of connected interventions for SUD. METHODS: A systematic review was conducted to identify articles evaluating connected health interventions for SUD in accordance with the Preferred Reporting Items for Systematic Reviews and Meta-Analyses guidelines. Three databases (PubMed, IEEE, and Scopus) were searched over a five-year period. Included articles described a connected health intervention targeting SUD and provided outcomes data. Data were extracted using a standardized reporting tool. RESULTS: A total of 1676 unique articles were identified during the initial search, with 32 articles included in the final analysis. Seven articles of the 32 were derived from two large studies. The most commonly studied SUD was alcohol use disorder. Sixteen articles reported at least one statistically significant result with respect to reduced craving and/or substance use. The majority of articles used ecological momentary assessment to trigger interventions, while four used biologic/physiologic data. Two articles used a wearable device. Common intervention types included craving management, coping assistance, and tailored feedback. Twenty-three articles measured usability factors, and acceptability was generally reported as high. CONCLUSION: Identified themes included a focus on AUD, use of smart phones, use of EMA for intervention delivery, positive effects on SUD related outcomes, and overall high acceptability. Wearables that directly monitor biologic data and predictive analytics using integrated data streams represent understudied opportunities for new research.
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