AI-Facilitated Cognitive Reappraisal via Socrates 2.0: Mixed Methods Feasibility Study
Bibliographic record
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.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.024 | 0.019 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 0.001 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".