Technology‐mediated just‐in‐time adaptive interventions (JITAIs) to reduce harmful substance use: a systematic review.
Background and Aims: Lapse risk when trying to stop or reduce harmful substance use is idiosyncratic, dynamic and multi‐factorial. Just‐in‐time adaptive interventions (JITAIs) aim to deliver tailored support at moments of need or opportunity. We aimed to synthesize evidence on decision points, tailo...
| Publicado en: | Addiction Vol. 117; no. 5; pp. 1220 - 1242 |
|---|---|
| Autores principales: | , , , , , |
| Formato: | research systematic review tables/charts Journal Article |
| Publicado: |
Wiley-Blackwell
May2022
|
| Acceso en línea: | Ver este registro en EBSCOhost |
| fields | @attributes: recordID: 1 pdfLink: plink: https://search.ebscohost.com/login.aspx?direct=true&db=ccm&AN=156112682&site=ehost-live header: @attributes: shortDbName: ccm uiTerm: 156112682 longDbName: CINAHL Complete uiTag: AN controlInfo: bkinfo: dissinfo: jinfo: jid: 09652140 AIO jtl: Addiction issn: 09652140 maglogo: Y pubinfo: dt: May2022 vid: 117 iid: 5 pid: 480 pub: Wiley-Blackwell place: Malden, Massachusetts artinfo: ui: 156112682 152910496 156112682 156112682 10.1111/add.15687 156112682 ppf: 1220 ppct: 22 formats: fmt: – @attributes: type: T – @attributes: type: C – @attributes: type: P tig: atl: Technology‐mediated just‐in‐time adaptive interventions (JITAIs) to reduce harmful substance use: a systematic review. aug: au: Perski, Olga Hébert, Emily T. Naughton, Felix Hekler, Eric B. Brown, Jamie Businelle, Michael S. affil: Department of Behavioural Science and Health, University College London, London, UK sug: subj: Telehealth Utilization Substance Use Disorders Prevention and Control Health Promotion Affect Technology, Medical Utilization Human Systematic Review Medline Embase Psycinfo Decision Making Behavioral Changes Funding Source ab: Background and Aims: Lapse risk when trying to stop or reduce harmful substance use is idiosyncratic, dynamic and multi‐factorial. Just‐in‐time adaptive interventions (JITAIs) aim to deliver tailored support at moments of need or opportunity. We aimed to synthesize evidence on decision points, tailoring variables, intervention options, decision rules, study designs, user engagement and effectiveness of technology‐mediated JITAIs for reducing harmful substance use. Methods: Systematic review of empirical studies of any design with a narrative synthesis. We searched Ovid MEDLINE, Embase, PsycINFO, Web of Science, the ACM Digital Library, the IEEE Digital Library, ClinicalTrials.gov, the ISRCTN register and dblp using terms related to substance use/mHealth/JITAIs. Outcomes were user engagement and intervention effectiveness. Study quality was assessed with the mHealth Evidence Reporting and Assessment checklist. Findings We included 17 reports of 14 unique studies, including two randomized controlled trials. JITAIs targeted alcohol (S = 7, n = 120 520), tobacco (S = 4, n = 187), cannabis (S = 2, n = 97) and a combination of alcohol and illicit substance use (S = 1, n = 63), and primarily relied on active measurement and static (i.e. time‐invariant) decision rules to deliver support tailored to micro‐scale changes in mood or urges. Two studies used data from prior participants and four drew upon theory to devise decision rules. Engagement with available JITAIs was moderate‐to‐high and evidence of effectiveness was mixed. Due to substantial heterogeneity in study designs and outcome variables assessed, no meta‐analysis was performed. Many studies reported insufficient detail on JITAI infrastructure, content, development costs and data security. Conclusions: Current implementations of just‐in‐time adaptive interventions (JITAIs) for reducing harmful substance use rely on active measurement and static decision rules to deliver support tailored to micro‐scale changes in mood or urges. Studies on JITAI effectiveness are lacking. pubtype: Academic Journal doctype: research systematic review tables/charts Journal Article ougenre: Article language: English refInfo: holdings: @attributes: islocal: N |
|---|