Evidence map›Paper›PMID 41348953›Full record

ArticleJMIR mental health2025

AI-Facilitated Cognitive Reappraisal via Socrates 2.0: Mixed Methods Feasibility Study.

Philip Held, Sarah A Pridgen, Daniel R Szoke, Yaozhong Chen, Zuhaib Akhtar, Darpan Amin

Abstract read
In one paragraph

Article in JMIR mental health, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.

0numbers the graph read from it
0cells of the map it votes in
3citing 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

3 citing papers in PubMed.

  1. Review
  2. Article
  3. Review
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.

Philip HeldDepartment of Psychiatry and Behavioral Sciences, Rush University Medical Center, 1645 West Jackson Boulevard, Suite 602, Chicago, IL, 60612, United States.ORCID 0000-0003-3974-1802
Sarah A PridgenDepartment of Psychiatry and Behavioral Sciences, Rush University Medical Center, 1645 West Jackson Boulevard, Suite 602, Chicago, IL, 60612, United States.ORCID 0000-0002-2640-8050
Daniel R SzokeDepartment of Psychiatry and Behavioral Sciences, Rush University Medical Center, 1645 West Jackson Boulevard, Suite 602, Chicago, IL, 60612, United States.ORCID 0000-0002-6777-3636
Yaozhong ChenDepartment of Psychiatry and Behavioral Sciences, Rush University Medical Center, 1645 West Jackson Boulevard, Suite 602, Chicago, IL, 60612, United States.ORCID 0009-0003-8357-4623
Zuhaib AkhtarDepartment of Psychiatry and Behavioral Sciences, Rush University Medical Center, 1645 West Jackson Boulevard, Suite 602, Chicago, IL, 60612, United States.ORCID 0000-0002-0338-6549
Darpan AminDepartment of Psychiatry and Behavioral Sciences, Rush University Medical Center, 1645 West Jackson Boulevard, Suite 602, Chicago, IL, 60612, United States.ORCID 0009-0002-7925-6190

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Background: Innovative, scalable mental health tools are needed to address systemic provider shortages and accessibility barriers. Large language model-based tools can provide real-time, tailored feedback to help users engage in cognitive reappraisal outside traditional therapy sessions. Socrates 2.0 (Rush University Medical Center) is a multiagent artificial intelligence tool that guides users through Socratic dialogue. Objective: The study aimed to examine the feasibility, acceptability, and potential for symptom reduction of Socrates 2.0. Methods: A total of 61 adult participants enrolled in a 4-week mixed methods preclinical feasibility study. The participants used Socrates 2.0 as desired and completed the self-report measures of depression, social anxiety, posttraumatic stress, and obsessive-compulsive symptoms at baseline and 1-month follow-up. Feasibility, acceptability, and appropriateness, along with usability and working alliance, were assessed via validated measures. The semistructured interviews explored user experiences and perceptions. Results: Participants engaged with Socrates 2.0 an average of 6.70 (SD 4.57) times over 4 weeks. Feasibility (mean 4.26, SD 0.67), acceptability (mean 4.16, SD 0.84), and usability ratings were high. Participants reported small-to-moderate reductions in depression (effect size d=0.30), social anxiety (d=0.25), obsessive-compulsive (d=0.33), and posttraumatic stress (d=0.28) symptoms. Working alliance scores suggested a moderately strong perceived bond with the artificial intelligence tool. Qualitative feedback indicated that the nonjudgmental, on-demand nature of Socrates 2.0 encouraged self-reflection and exploration. Some users critiqued the repeated questioning style and limited conversation depth. Conclusions: Socrates 2.0 was perceived as feasible, acceptable, and moderately helpful for self-guided cognitive reappraisal, demonstrating potential as an adjunct to traditional therapy. Further research, including randomized trials, is needed to determine effectiveness across different populations, optimize personalization, and address the repetitive conversational nature.

Indexed as

Artificial IntelligenceCognitive Behavioral TherapyAdultDepressionFeasibility StudiesFemaleHumansMaleMiddle AgedStress Disorders, Post-TraumaticYoung Adultcognitive behavior therapycognitive reappraisaldigital mental healthgenerative artificial intelligencelarge language models

Identifiers

PMID41348953
PMCPMC12680128

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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 OpenQuestion graph.