Evidence map›Paper›PMID 40705826›Full record

ArticlePLOS digital health2025

Behavioral engagement patterns and psychosocial outcomes in web-based interpretation bias training for anxiety.

Ángel Francisco Vela de la Garza Evia, Jeremy William Eberle, Sonia Baee, Emma Catherine Wolfe, Mehdi Boukhechba, Daniel Harold Funk, Bethany Ann Teachman, Laura Elizabeth Barnes

Abstract read
In one paragraph

Article in PLOS digital health, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing 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

2 citing papers in PubMed.

  1. Article
  2. 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

8 authors.

Ángel Francisco Vela de la Garza Evia
Jeremy William EberleDepartment of Psychology, University of Virginia, Charlottesville, Virginia, United States of America.ORCID https://orcid.org/0000-0003-0119-2879
Sonia BaeeDepartment of Systems and Information Engineering, University of Virginia, Charlottesville, Virginia, United States of America.
Emma Catherine WolfeDepartment of Psychology, University of Virginia, Charlottesville, Virginia, United States of America.
Mehdi BoukhechbaDepartment of Systems and Information Engineering, University of Virginia, Charlottesville, Virginia, United States of America.
Daniel Harold FunkSartography, Staunton, Virginia, United States of America.
Bethany Ann TeachmanDepartment of Psychology, University of Virginia, Charlottesville, Virginia, United States of America.ORCID https://orcid.org/0000-0002-9031-9343
Laura Elizabeth BarnesDepartment of Systems and Information Engineering, University of Virginia, Charlottesville, Virginia, United States of America.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Digital mental health interventions (DMHIs) have the potential to expand treatment access for anxiety but often have low user engagement. The present study analyzed differences in psychosocial outcomes for different behavioral engagement patterns in a free web-based cognitive bias modification for interpretation (CBM-I) program. CBM-I is designed to shift interpretation biases common in anxiety by providing practice thinking about emotionally ambiguous situations in less threatening ways. Using data from 697 anxious community adults undergoing five weekly sessions of CBM-I in a clinical trial, we extracted program use markers based on task completion rate and time spent on training and assessment tasks. After using an exploratory cluster analysis of these markers to create two engagement groups (whose patterns ended up reflecting generally more vs. less time spent across tasks), we used multilevel models to test for group differences in interpretation bias and anxiety outcomes. Unexpectedly, engagement group did not significantly predict differential change in positive interpretation bias or anxiety. Further, participants who generally spent less time on the program (including both training and assessment tasks) improved in negative interpretation bias (on one of two measures) significantly more during the training phase than those who spent more time (and post hoc tests found were significantly older and slightly less educated). However, participants who generally spent less time had a significant loss in training gains for negative bias (on both measures) by 2-month follow-up. Findings highlight the challenge of interpreting time spent as a marker of engagement and the need to consider cognitive and affective markers of engagement in addition to behavioral markers. Further understanding engagement patterns holds promise for improving DMHIs for anxiety.

Identifiers

PMID40705826
PMCPMC12289040

What Socratic holds

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LicenceCC BY
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Registered trials

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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.