Evidence map›Paper›PMID 32777691›Full record

SynthesisDrug and alcohol dependence2020

Current reporting of usability and impact of mHealth interventions for substance use disorder: A systematic review.

Stephanie Carreiro, Mark Newcomb, Rebecca Leach, Simon Ostrowski, Edwin D Boudreaux, Daniel Amante

Abstract readSystematic Review
PubMed Full text at PMC Publisher
In one paragraph

Synthesis in Drug and alcohol dependence, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 67 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
67citing papers in PubMed, 1 pooled it
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

67 citing papers in PubMed, 1 synthesis or guideline pooled it.

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7 more citing papers are in PubMed but not listed here.

4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

6 authors.

Stephanie CarreiroDepartment of Emergency Medicine, University of Massachusetts Medical School, 55 Lake Avenue North, Worcester, MA, 01655, USA. Electronic address: stephanie.carreiro@umassmed.edu.
Mark NewcombDepartment of Emergency Medicine, University of Massachusetts Medical School, 55 Lake Avenue North, Worcester, MA, 01655, USA.
Rebecca LeachDepartment of Emergency Medicine, University of Massachusetts Medical School, 55 Lake Avenue North, Worcester, MA, 01655, USA.
Simon OstrowskiDepartment of Emergency Medicine, University of Massachusetts Medical School, 55 Lake Avenue North, Worcester, MA, 01655, USA.
Edwin D BoudreauxDepartment of Emergency Medicine, University of Massachusetts Medical School, 55 Lake Avenue North, Worcester, MA, 01655, USA.
Daniel AmanteDepartment of Population and Quantitative Health Sciences, University of Massachusetts Medical School, 368 Plantation Street, Worcester, MA, 01605, USA.

Funding

University of Massachusetts Center for Clinical and Translational ScienceKL2TR001455 · NCATS · UNIV OF MASSACHUSETTS MED SCH WORCESTER · PI KIEFE, CATARINA I. · 2015 to 2024
$5.0M
iTransform: Wearable Biosensors to Detect the Evolution of Opioid Tolerance in Opioid Naïve IndividualsK23DA045242 · NIDA · UNIV OF MASSACHUSETTS MED SCH WORCESTER · PI CARREIRO, STEPHANIE P · 2019 to 2021
$566k
NCATS NIH HHS KL2 TR001455NIDA NIH HHS K23 DA045242NIDA NIH HHS L30 DA038357
6 · The paper itself

Abstract

backgroundConnected 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.

methodsA 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.

resultsA 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.

conclusionIdentified 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.

Indexed as

AlcoholismCravingHumansSmartphoneSubstance-Related DisordersTelemedicineConnected healthInterventionmHealthSensorsSubstance use disorder

Identifiers

PMID32777691
PMCPMC7502517

What OpenQuestion holds

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Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.