Evidence map›Paper›PMID 39159806›Full record

ArticleContemporary clinical trials2024

A mobile health intervention for emerging adults with regular cannabis use: A micro-randomized pilot trial design protocol.

Lara N Coughlin, Maya Campbell, Tiffany Wheeler, Chavez Rodriguez, Autumn Rae Florimbio, Susobhan Ghosh, Yongyi Guo, Pei-Yao Hung, Mark W Newman, Huijie Pan and 6 more

Abstract readClinical Trial Protocol
In one paragraph

Article in Contemporary clinical trials, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 9 papers.

0numbers the graph read from it
0cells of the map it votes in
9citing papers in PubMed
–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

9 citing papers in PubMed.

  1. Trial
  2. Article
  3. Article
  4. Review
  5. "It felt more real": Investigating the User Experience of the MiWaves Personalizing JITAI Pilot Study.International Conference on Pervasive Computing Technologies for Healthcare : [proceedings]. International Conference on Pervasive Computing Technologies for Healthcare · 2026
    Article
  6. Article
  7. Article
  8. SigmaScheduling: Uncertainty-Informed Scheduling of Decision Points for Intelligent Mobile Health Interventions.... International Conference on Wearable and Implantable Body Sensor Networks. International Conference on Wearable and Implantable Body Sensor Networks · 2025
    Article
  9. Article
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

16 authors.

Lara N CoughlinAddiction Center, Department of Psychiatry, University of Michigan, Ann Arbor, MI, USA; Michigan Innovations in Addiction Care through Research and Education, University of Michigan, Ann Arbor, MI, USA. Electronic address: laraco@med.umich.edu.
Maya CampbellAddiction Center, Department of Psychiatry, University of Michigan, Ann Arbor, MI, USA.
Tiffany WheelerAddiction Center, Department of Psychiatry, University of Michigan, Ann Arbor, MI, USA.
Chavez RodriguezAddiction Center, Department of Psychiatry, University of Michigan, Ann Arbor, MI, USA.
Autumn Rae FlorimbioAddiction Center, Department of Psychiatry, University of Michigan, Ann Arbor, MI, USA.
Susobhan GhoshDepartment of Computer Science, Harvard University, Cambridge, MA, USA.
Yongyi GuoDepartment of Statistics, Harvard University, Cambridge, MA, USA.
Pei-Yao HungInstitute for Social Research, University of Michigan, Ann Arbor, MI, USA.
Mark W NewmanSchool of Information, EECS Department, University of Michigan, Ann Arbor, MI, USA.
Huijie PanInstitute for Social Research, University of Michigan, Ann Arbor, MI, USA.
Kelly W ZhangDepartment of Computer Science, Harvard University, Cambridge, MA, USA.
Lauren ZimmermannInstitute for Social Research, University of Michigan, Ann Arbor, MI, USA.
Erin E BonarMichigan Innovations in Addiction Care through Research and Education, University of Michigan, Ann Arbor, MI, USA.
Maureen WaltonAddiction Center, Department of Psychiatry, University of Michigan, Ann Arbor, MI, USA; Michigan Innovations in Addiction Care through Research and Education, University of Michigan, Ann Arbor, MI, USA.
Susan MurphyDepartment of Computer Science, Harvard University, Cambridge, MA, USA; Department of Statistics, Harvard University, Cambridge, MA, USA.
Inbal Nahum-ShaniInstitute for Social Research, University of Michigan, Ann Arbor, MI, USA.

Funding

Pilot and Mentoring CoreP50DA054039 · NIDA · UNIVERSITY OF MICHIGAN AT ANN ARBOR · PI LINDA M COLLINS, SUSAN A MURPHY · 2021 to 2026
$18.2M
TR&D3 - Rapid Translation of AI-powered Temporally Precise mHealth Interventions via Efficient and Embeddable Trustworthy Biomarker ImplementationsP41EB028242 · NIBIB · UNIVERSITY OF MEMPHIS · PI VIVEK SHETTY · 2020 to 2026
$9.5M
MULTIDISCIPLINARY ALCOHOLISM RESEARCH TRAINING PROGRAMT32AA007477 · NIAAA · UNIVERSITY OF MICHIGAN AT ANN ARBOR · PI Maureen A. Walton · 1990 to 2026
$7.4M
Optimizing mobile behavioral economic interventions for rural risky drinkersK23AA028232 · NIAAA · UNIVERSITY OF MICHIGAN AT ANN ARBOR · PI COUGHLIN, LARA NICOLE · 2020 to 2024
$983k
Optimizing an App-based Intervention for Sexual Minoritized Emerging Adults to Reduce Cannabis and Alcohol Co-useK23DA059484 · NIDA · UNIVERSITY OF MICHIGAN AT ANN ARBOR · PI Autumn Rae H Florimbio · 2024 to 2026
$589k
NIAAA NIH HHS K23 AA028232NIAAA NIH HHS T32 AA007477NIBIB NIH HHS P41 EB028242NIDA NIH HHS K23 DA059484NIDA NIH HHS P50 DA054039
6 · The paper itself

Abstract

backgroundEmerging adult (EA) cannabis use is associated with increased risk for health consequences. Just-in-time adaptive interventions (JITAIs) provide potential for preventing the escalation and consequences of cannabis use. Powered by mobile devices, JITAIs use decision rules that take the person's state and context as input, and output a recommended intervention (e.g., alternative activities, coping strategies). The mHealth literature on JITAIs is nascent, with additional research needed to identify what intervention content to deliver when and to whom.

methodsHerein we describe the protocol for a pilot study testing the feasibility and acceptability of a micro-randomized trial for optimizing MiWaves mobile intervention app for EAs (ages 18-25; target N = 120) with regular cannabis use (≥3 times per week). Micro-randomizations will be determined by a reinforcement learning algorithm that continually learns and improves the decision rules as participants experience the intervention. MiWaves will prompt participants to complete an in-app twice-daily survey over 30 days and participants will be micro-randomized twice daily to either: no message or a message [1 of 6 types varying in length (short, long) and interaction type (acknowledge message, acknowledge message + click additional resources, acknowledge message + fill in the blank/select an option)]. Participants recruited via social media will download the MiWaves app, and complete screening, baseline, weekly, post-intervention, and 2-month follow-up assessments. Primary outcomes include feasibility and acceptability, with additional exploratory behavioral outcomes.

conclusionThis study represents a critical first step in developing an effective mHealth intervention for reducing cannabis use and associated harms in EAs.

Indexed as

Mobile ApplicationsTelemedicineAdaptation, PsychologicalAdolescentAdultFeasibility StudiesFemaleHumansMaleMarijuana UsePilot ProjectsRandomized Controlled Trials as TopicResearch DesignYoung AdultCannabis useEngagementMicro-randomized trial (MRT)Mobile health (mHealth)Self-regulatory strategies

Identifiers

PMID39159806
PMCPMC11616772

What OpenQuestion holds

Textmetadata
LicenceTDM
Read underepoch 390

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.