Evidence map›Paper›PMID 41540194›Full record

ArticleCommunications medicine2026

Increasing engagement with cognitive-behavioral therapy (CBT) using generative AI: a randomized controlled trial (RCT).

Jessica McFadyen, Johanna Habicht, Larisa-Maria Dina, Ross Harper, Tobias U Hauser, Max Rollwage

Registry-linked trialAbstract read
In one paragraph

Article in Communications medicine, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. It is linked to trial NCT06459128 (Comparison of Delivery Format of Cognitive Behavioral Therapy Materials on Engagement and Symptom Reduction), which is not on this map. Cited by 5 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
5citing papers in PubMed, 1 pooled it
–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.

NCT06459128 nacompletednot on this map

Comparison of Delivery Format of Cognitive Behavioral Therapy Materials on Engagement and Symptom Reduction: AI-Enabled App vs PDF Workbook

TypeinterventionalSponsorLimbic LimitedRan2024 to 2024Enrolled540ConditionsMental Health IssueArmsLimbic Care, Digital Workbook
3 · Its place in the literature

Who cites it

5 citing papers in PubMed, 1 synthesis or guideline pooled it.

  1. Pooled it
  2. Article
  3. Review
  4. Article
  5. 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

6 authors.

Jessica McFadyenLimbic Limited, London, UK. drjessicajean@gmail.com.ORCID http://orcid.org/0000-0003-1415-2286
Johanna HabichtLimbic Limited, London, UK.ORCID http://orcid.org/0000-0001-5043-7129
Larisa-Maria DinaLimbic Limited, London, UK.
Ross HarperLimbic Limited, London, UK.ORCID http://orcid.org/0000-0002-2403-2088
Tobias U HauserLimbic Limited, London, UK.
Max RollwageLimbic Limited, London, UK.ORCID http://orcid.org/0000-0003-4181-3983

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundShortages in mental healthcare lead to long periods of inadequate support for many patients. While digital interventions offer a scalable solution to this unmet clinical need, patient engagement remains a key challenge. Generative artificial intelligence (genAI) presents an opportunity to deliver highly engaging, personalized mental health treatment at scale.

methodsIn a pre-registered (ClinicalTrials.gov: NCT06459128, 10 June 2024), parallel, 2-arm, unblinded, randomized controlled trial (N = 540), we evaluate whether a genAI-enabled cognitive behavioral therapy (CBT) app enhances engagement or symptom reduction compared with digital CBT workbooks. Eligible participants are adults residing in the United States with elevated self-reported symptoms of anxiety (GAD-7 ≥ 7) or depression (PHQ-9 ≥ 9), recruited online. After an online baseline assessment, participants are automatically randomly allocated (3:2) to receive either the genAI-enabled app or a digital workbook, both self-guided over six weeks. Primary outcomes are: 1) engagement frequency and duration, and 2) change in anxiety (GAD-7) and depression (PHQ-9) symptom severity. Secondary outcomes include adverse events and functional impairment. The study is unblinded to participants and researchers due to the nature of the digital interventions.

resultsA total of 540 participants are recruited and randomized to each group (intervention: n = 322, active control: n = 218). Nine participants from the control group are excluded from analysis due to protocol deviations. Over six weeks, the genAI solution (n = 322) increases engagement frequency (2.4×) and duration (3.8×) compared to digital workbooks (n = 209), with moderate to large effect sizes. We observe comparable outcomes for anxiety (GAD-7) and depression (PHQ-9) with no differences in adverse events. Moreover, exploratory analyses suggest that participants who choose to engage with clinical personalization features powered by genAI experience stronger anxiety symptom reduction and improved overall wellbeing.

conclusionsOur findings suggest that, in self-directed usage, tailored genAI-enabled therapy safely enhances user engagement above and beyond static materials, without showing an overall enhancement in anxiety or depression symptom reduction.

Identifiers

PMID41540194
PMCPMC12953620

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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 OpenQuestion graph.