ArticleJournal of psychiatry and brain science2020
Mobile Peer-Support for Opioid Use Disorders: Refinement of an Innovative Machine Learning Tool.
Article in Journal of psychiatry and brain science, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. It is linked to trial NCT05405712 (Increasing Peer Support for OUD Recovery During COVID-19 Through Digital Health), which is not on this map. Cited by 3 papers.
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.
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.
Increasing Peer Support for OUD Recovery During COVID-19 Through Digital Health: A National Randomized Controlled Trial
Who cites it
3 citing papers in PubMed, 7 citations in OpenAlex.
- Digital mental health tools for use by individuals in opioid use recovery: An academic scoping and commercial review.PLOS digital health · 2026Article
- Self-Reported Advantages and Disadvantages of Online Networking About Opioid Misuse Among Those Who Have or Are Currently Misusing Opioids.Substance use & misuse · 2025Article
- A pilot study of a mixed-method approach to design an ED-based peer mHealth referral tool for HIV/HCV and opioid overdose prevention services.Drug and alcohol dependence · 2022Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
9 authors at 3 institutions in 1 country.
Funding
Abstract
backgroundThe majority of individuals with Opioid Use Disorder (OUD) do not receive any formal substance use treatment. Due to limited engagement and access to traditional treatment, there is increasing evidence that patients with OUDs turn to online social platforms to access peer support and obtain health-related information about addiction and recovery. Interacting with peers before and during recovery is a key component of many evidence-based addiction recovery programs, and may improve self-efficacy and treatment engagement as well as reduce relapse. Commonly-used online social platforms are limited in utility and scalability as an adjunct to addiction treatment; lack effective content moderation (e.g., misinformed advice, maliciousness or "trolling"); and lack common security and ethical safeguards inherent to clinical care.
methodsThis present study will develop a novel, artificial-intelligence (AI) enabled, mobile treatment delivery method that fulfills the need for a robust, secure, technology-based peer support platform to support patients with OUD. Forty adults receiving outpatient buprenorphine treatment for OUD will be asked to pilot a smartphone-based mobile peer support application, the "Marigold App", for a duration of six weeks. The program will use (1) a prospective cohort study to obtain text message content and feasibility metrics, and (2) qualitative interviews to evaluate usability and acceptability of the mobile platform. ANTICIPATED FINDINGS AND FUTURE DIRECTIONS: The Marigold mobile platform will allow patients to access a tailored chat support group 24/7 as a complement to different forms of clinical OUD treatment. Marigold can keep groups safe and constructive by augmenting chats with AI tools capable of understanding the emotional sentiment in messages, automatically "flagging" critical or clinically relevant content. This project will demonstrate the robustness of these AI tools by adapting them to catch OUD-specific "flags" in peer messages while also examining the adoptability of the platform itself within OUD patients.
Indexed as
Identifiers
What OpenQuestion holds
Registered trials
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.