Evidence map›Paper›PMID 41610890›Full record

Trial reportJournal of affective disorders2026

Sociodemographic and clinical predictors of digital mental health intervention engagement among treatment-seeking psychiatric outpatients.

Adam G Horwitz, Elizabeth D Mills, Rohan Nanwani, Amy S B Bohnert, Srijan Sen

Abstract readRandomized Controlled Trial
In one paragraph

Trial report in Journal of affective disorders, 2026. 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

5 authors.

Adam G HorwitzUniversity of Michigan Medical School, Department of Psychiatry, 4250 Plymouth Rd., Ann Arbor, MI, 48105, United States of America. Electronic address: ahor@umich.edu.
Elizabeth D MillsUniversity of Michigan Medical School, Department of Anesthesiology, 1500 E Medical Center Dr., Ann Arbor, MI, 48109, United States of America.
Rohan NanwaniUniversity of Michigan Medical School, Department of Anesthesiology, 1500 E Medical Center Dr., Ann Arbor, MI, 48109, United States of America.
Amy S B BohnertUniversity of Michigan Medical School, Department of Psychiatry, 4250 Plymouth Rd., Ann Arbor, MI, 48105, United States of America; University of Michigan Medical School, Department of Anesthesiology, 1500 E Medical Center Dr., Ann Arbor, MI, 48109, United States of America.
Srijan SenUniversity of Michigan Medical School, Department of Psychiatry, 4250 Plymouth Rd., Ann Arbor, MI, 48105, United States of America.

Funding

COMPASS: A comprehensive mobile precision approach for scalable solutions in mental health treatmentU01MH136025 · NIMH · UNIVERSITY OF MICHIGAN AT ANN ARBOR · PI Amy S B Bohnert, Lars Fritsche · 2024 to 2026
$17.9M
Low-burden Adaptive Mobile Interventions for Mood and Suicide RiskK23MH131761 · NIMH · UNIVERSITY OF MICHIGAN AT ANN ARBOR · PI HORWITZ, ADAM GABRIEL · 2022 to 2025
$690k
NIMH NIH HHS K23 MH131761NIMH NIH HHS U01 MH136025
6 · The paper itself

Abstract

backgroundDigital mental health interventions (DMHIs) have shown promise improving depression, anxiety, and psychiatric distress, yet real-world engagement remains low. Increasing engagement has great potential to improve the impact of DMHIs, but little is known about the drivers of engagement in naturalistic settings. To better understand predictors of engagement, we examined sociodemographic and clinical characteristics associated with DMHI usage among a large clinical sample of adults.

method1223 adults (74% White, 68% women, Mage = 36.8 years) with scheduled intake appointments for outpatient psychiatric services were randomized to either a mindfulness-based app (Headspace) or a CBT-based app (SilverCloud). Usage data were automatically collected, and participants were neither required nor compensated to use the apps.

resultsParticipants engaged with their assigned DMHIs a median of 8 days, with 88.2% of participants using their assigned DMHI at least once. Participants engaged with Headspace for more than twice as many days [IRR (95% CI) = 2.4 (2.1, 2.7)] as SilverCloud. Female sex, white race, a college degree, and older age up to 60 predicted greater engagement. Further, depression severity was associated with engagement in a non-linear manner for those assigned to Headspace, with less engagement at minimal/mild and severe symptoms compared to moderate and moderately-severe symptoms.

conclusionsThese findings indicate meaningful differences in engagement between DMHIs based on sociodemographic and clinical characteristics. There may be opportunities to improve engagement by tailoring DMHI offerings, with a particular emphasis on meeting the needs of less-engaged populations.

Indexed as

Mental DisordersMental Health ServicesMobile ApplicationsOutpatientsPatient Acceptance of Health CareAdultCognitive Behavioral TherapyDigital HealthDigital MediaFemaleHumansMaleMental Health TeletherapyMiddle AgedSociodemographic FactorsDigital mental health interventionsEngagementOutpatient psychiatryUsageWaitlist

Identifiers

PMID41610890
PMCPMC12934057

What OpenQuestion 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 OpenQuestion graph.