Evidence map›Paper›PMID 39374076›Full record

ArticleJMIR formative research2024

Inclusion of Individuals With Lived Experiences in the Development of a Digital Intervention for Co-Occurring Depression and Cannabis Use: Mixed Methods Investigation.

Amanda C Collins, Sukanya Bhattacharya, Jenny Y Oh, Abigail Salzhauer, Charles T Taylor, Kate Wolitzky-Taylor, Robin L Aupperle, Alan J Budney, Nicholas C Jacobson

Registry-linked trialAbstract read
In one paragraph

Article in JMIR formative research, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. It is linked to trial NCT06920238 (A Phase I Single-Arm Trial to Test the Use of a Generative AI), which is not on this map. Not yet cited in PubMed.

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

NCT06920238 phase1completednot on this mapstarted 2025, after this paper: background citation

A Phase I Single-Arm Trial to Test the Use of a Generative AI (Gen-AI) Chatbot for Anxiety and Depression Among Persons With Cannabis Use Disorder (CUD)

TypeinterventionalSponsorTrustees of Dartmouth CollegeRan2025 to 2026Enrolled15ConditionsCannabis Use Disorder, Anxiety, Depression, Anxiety, Depression - Major Depressive DisorderArmsTherabot-CALM
3 · Its place in the literature

Who cites it

0 citing papers in PubMed.

No citing paper in PubMed yet.

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

9 authors.

Amanda C CollinsCenter for Technology and Behavioral Health, Geisel School of Medicine, Dartmouth College, Lebanon, NH, United States.ORCID 0000-0002-8258-2272
Sukanya BhattacharyaCenter for Technology and Behavioral Health, Geisel School of Medicine, Dartmouth College, Lebanon, NH, United States.ORCID 0000-0002-7814-7278
Jenny Y OhCenter for Technology and Behavioral Health, Geisel School of Medicine, Dartmouth College, Lebanon, NH, United States.ORCID 0000-0002-2504-4398
Abigail SalzhauerCenter for Technology and Behavioral Health, Geisel School of Medicine, Dartmouth College, Lebanon, NH, United States.ORCID 0009-0009-3210-6807
Charles T TaylorDepartment of Psychiatry, University of California, San Diego School of Medicine, San Diego, CA, United States.ORCID 0000-0002-2337-0392
Kate Wolitzky-TaylorDepartment of Psychiatry and Biobehavioral Sciences, University of California - Los Angeles, Los Angeles, CA, United States.ORCID 0000-0001-6199-4350
Robin L AupperleLaureate Institute for Brain Research, Tulsa, OK, United States.ORCID 0000-0003-2173-6140
Alan J BudneyCenter for Technology and Behavioral Health, Geisel School of Medicine, Dartmouth College, Lebanon, NH, United States.ORCID 0000-0001-6308-6823
Nicholas C JacobsonCenter for Technology and Behavioral Health, Geisel School of Medicine, Dartmouth College, Lebanon, NH, United States.ORCID 0000-0002-8832-4741

Funding

Treatment Development & Evaluation CoreP30DA029926 · NIDA · DARTMOUTH COLLEGE · PI Lisa A. Marsch · 2011 to 2026
$21.5M
Training in the Science of Co-Occurring DisordersT32DA037202 · NIDA · DARTMOUTH COLLEGE · PI Lisa A. Marsch · 2014 to 2026
$4.7M
NIDA NIH HHS P30 DA029926NIDA NIH HHS T32 DA037202
6 · The paper itself

Abstract

backgroundExisting interventions for co-occurring depression and cannabis use often do not treat both disorders simultaneously and can result in higher rates of symptom relapse. Traditional in-person interventions are often difficult to obtain due to financial and time limitations, which may further prevent individuals with co-occurring depression and cannabis use from receiving adequate treatment. Digital interventions can increase the scalability and accessibility for these individuals, but few digital interventions exist to treat both disorders simultaneously. Targeting transdiagnostic processes of these disorders with a digital intervention-specifically positive valence system dysfunction-may yield improved access and outcomes.

objectiveRecent research has highlighted a need for the inclusion of individuals with lived experiences to assist in the co-design of interventions to enhance scalability and relevance of an intervention. Thus, the purpose of this study is to describe the process of eliciting feedback from individuals with elevated depressed symptoms and cannabis use and co-designing a digital intervention, Amplification of Positivity-Cannabis Use Disorder (AMP-C), focused on improving positive valence system dysfunction in these disorders.

methodsTen individuals who endorsed moderate to severe depressive symptoms and regular cannabis use (2-3×/week) were recruited online via Meta ads. Using a mixed methods approach, participants completed a 1-hour mixed methods interview over Zoom (Zoom Technologies Inc) where they gave their feedback and suggestions for the development of a mental health app, based on an existing treatment targeting positive valence system dysfunction, for depressive symptoms and cannabis use. The qualitative approach allowed for a broader investigation of participants' wants and needs regarding the engagement and scalability of AMP-C, and the quantitative approach allowed for specific ratings of intervention components to be potentially included.

resultsParticipants perceived the 13 different components of AMP-C as overall helpful (mean 3.9-4.4, SD 0.5-1.1) and interesting (mean 4.0-4.9, SD 0.3-1.1) on a scale from 1 (not at all) to 5 (extremely). They gave qualitative feedback for increasing engagement in the app, including adding a social component, using notifications, and being able to track their symptoms and progress over time.

conclusionsThis study highlights the importance of including individuals with lived experiences in the development of interventions, including digital interventions. This inclusion resulted in valuable feedback and suggestions for improving the proposed digital intervention targeting the positive valence system, AMP-C, to better match the wants and needs of individuals with depressive symptoms and cannabis use.

Indexed as

DepressionAdultFemaleHumansMaleMarijuana AbuseMiddle AgedQualitative ResearchYoung Adultapp developmentcannabis usedepressiondigital interventionformative researchpositive affect

Identifiers

PMID39374076
PMCPMC11514326

What Socratic holds

Textmetadata
LicenceCC BY
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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 Socratic graph.