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Accepted for/Published in: JMIR Mental Health

Date Submitted: Sep 7, 2025
Date Accepted: Jan 30, 2026

The final, peer-reviewed published version of this preprint can be found here:

Popular Online Content as a Treatment-as-Usual Control in Digital Mental Health Intervention Trials: Secondary Analysis of Two Online Randomized Controlled Trials With Repeated Measures

Kaveladze BT, Schueller SM, Mohr DC

Popular Online Content as a Treatment-as-Usual Control in Digital Mental Health Intervention Trials: Secondary Analysis of Two Online Randomized Controlled Trials With Repeated Measures

JMIR Ment Health 2026;13:e83707

DOI: 10.2196/83707

PMID: 42008585

Popular Online Content as a Treatment-as-Usual Control in Digital Mental Health Intervention Trials: Two Online Randomized Controlled Trials with Repeated Measures

  • Benjamin T Kaveladze; 
  • Stephen M Schueller; 
  • David C Mohr

ABSTRACT

Background:

Treatment-as-usual (TAU) conditions are meant to reflect the support people typically receive in a treatment setting. For digital mental health interventions (DMHIs) implemented online, TAU should therefore reflect online help-seeking as usual. Mental health-related popular online content (e.g., advice TikToks, lived experience vlogs, and self-care infographics) may offer an ecologically valid basis for online TAU.

Objective:

Examine if popular online content is feasible as a TAU control in DMHI trials.

Methods:

In each study, participants were randomized to one of three 10-20-minute interventions. In Study 1 (n = 916), (1) a researcher-created single-session intervention (SSI) for depression and anxiety; (2) unguided web-searching for resources; or (3) a curated library of 120 pieces of annotated popular online content. In Study 2 (n = 431), (1) a single-session SSI for loneliness; (2) a curated library of popular online content related to loneliness; or (3) an attention-matched control. Participants reported treatments’ credibility and expected benefit, as well as their distress (Study 1) and loneliness (Study 2).

Results:

In Study 1, dropout during the treatment was 9.6% for the curated library, 25.9% for unguided help-seeking, and 4.8% for the SSI. Credibility and expected benefit for the curated library did not differ from the SSI’s (d = 0.08, P = .88) and were higher than unguided help-seeking’s (d = 0.23, P = .01). In Study 2, dropout was 4.8% for the curated library and 0.0% for both other conditions. Credibility and expected benefit ratings for the curated library were comparable to the attention-matched control’s (d = 0.00, P > .99) but lower than the SSI’s (d = 0.32, P = .02). Change in distress and loneliness over eight weeks did not differ across conditions (ds < 0.15).

Conclusions:

Curated libraries of popular online content provide a valuable and fairly realistic TAU benchmark for effectiveness trials of online DMHIs. Clinical Trial: study 1: https://osf.io/3dyma and study 2: https://osf.io/nvd79


 Citation

Please cite as:

Kaveladze BT, Schueller SM, Mohr DC

Popular Online Content as a Treatment-as-Usual Control in Digital Mental Health Intervention Trials: Secondary Analysis of Two Online Randomized Controlled Trials With Repeated Measures

JMIR Ment Health 2026;13:e83707

DOI: 10.2196/83707

PMID: 42008585

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