Evidence map›Paper›PMID 39440306›Full record

ArticleMental health science2024

Using Passive and Active Data to Predict Post-Traumatic Stress Disorder Symptoms and Cannabis Use in Recently Discharged UK Veterans: A Protocol for the MAVERICK Feasibility Study.

Grace Williamson, Nora Trompeter, Dominic Murphy, Shaddy Saba, Eric R Pedersen, Jordan P Davis, Daniel Leightley

Abstract read
In one paragraph

Article in Mental health science, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing 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

1 citing paper in PubMed.

  1. 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

7 authors.

Grace WilliamsonKing's Centre for Military Health Research, Institute of Psychiatry, Psychology & Neuroscience, King's College London, United Kingdom.ORCID 0000-0002-4618-5819
Nora TrompeterKing's Centre for Military Health Research, Institute of Psychiatry, Psychology & Neuroscience, King's College London, United Kingdom.ORCID 0000-0001-5800-8679
Dominic MurphyKing's Centre for Military Health Research, Institute of Psychiatry, Psychology & Neuroscience, King's College London, United Kingdom, and, Combat Stress, Leatherhead, United Kingdom.ORCID 0000-0002-9530-2743
Shaddy SabaUniversity of Southern California, Los Angeles, CA, United States.
Eric R PedersenUniversity of Southern California Keck School of Medicine, Department of Psychiatry and Behavioral Sciences, United States.
Jordan P DavisUniversity of Southern California, Los Angeles, CA, United States.ORCID 0000-0002-6108-4936
Daniel LeightleyKing's Centre for Military Health Research, Institute of Psychiatry, Psychology & Neuroscience, King's College London, United Kingdom.ORCID 0000-0001-9512-752X

Funding

Using Machine Learning to predict daily PTSD and cannabis use disorder symptoms among non-treatment seeking veteransR21DA051802 · NIDA · UNIVERSITY OF SOUTHERN CALIFORNIA · PI PEDERSEN, ERIC R. · 2021 to 2022
$459k
NIDA NIH HHS R21 DA051802
6 · The paper itself

Abstract

Introduction: Post-traumatic stress disorder (PTSD) and comorbid cannabis use disorder (CUD) is a growing concern amongst UK veterans. Co-occurrence of problematic cannabis use, and PTSD is associated with greater PTSD symptom severity, decreased likelihood of cannabis use cessation, worse clinical outcomes, and increased societal burden. Despite increased screening efforts among veterans, there are no effective strategies for predicting risk for PTSD and problematic drug use escalation before these conditions develop, worsen, or become chronic. Methods: This feasibility study employs a 4-week (28 day) longitudinal design (daily data collection), multiple passive data collection features via a bespoke study smartphone app called MAVERICK, and active data collection via wearable technology to predict clinically meaningful escalations in cannabis use and PTSD symptoms in UK veterans. Questionnaire data will be collected between 06:00 and 10:00 each day. Passive data will be collected continuously in the background. Results: The study will begin recruitment in June 2023 and will require 18 months to complete. Study results are expected to be published in January 2024. Discussion: This trial will provide information on the feasibility and utility of a smartphone app (MAVERICK) to collect both active and passive data to predict PTSD symptoms and cannabis use in a UK veteran population. If the smartphone app is deemed feasible and acceptable to users, it has the potential to provide an effective measurement tool to mitigate risk of PTSD and problematic cannabis use among veterans.

Indexed as

cannabis usedrug usePost-traumatic stress disordersmartphoneveterans

Identifiers

PMID39440306
PMCPMC11493327

What Socratic 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 Socratic graph.