PainTrain-AI Implementation Trial in Primary Care (Competency Gaps and Gender Bias) (PT-AI-IMP)

March 28, 2026 updated by: Francesc Valenzuela Pascual

Implementation of the Digital Intervention PainTrain-AI in Primary Care: Competency Gaps and Gender Bias in the Management of Chronic Musculoskeletal Pain

Cluster trial to assess the effect of a digital clinical simulation (PainTrain AI) on clinical adequacy (0-100 rubric) across T0-T1-T2 in Primary Care. Secondary endpoints: SUS, adherence, low value practice indicators, and latency/friction. The intervention is educational/behavioral; the platform is non diagnostic and RAG fenced to validated content. Analysis per protocol: DiD and LMM/GLMM.

Study Overview

Detailed Description

This study is a pragmatic, cluster-assigned implementation trial designed to evaluate the impact of the digital educational intervention PainTrain-AI on clinical decision-making in Primary Care. The intervention trains health professionals through standardized virtual patient simulations and brief interactive micromodules, using a retrieval-augmented generation (RAG) safety architecture that restricts all outputs to validated clinical content. PainTrain-AI does not generate new clinical information and is used exclusively for educational purposes.

The trial corresponds to Phase 3 of a broader research program described in the project protocol. In this phase, entire Primary Care centers are allocated to either the intervention arm (PainTrain-AI training) or the control arm (usual training/standard practice). A natural comparative setting in specialized care is included for analytical purposes, without access to master datasets and without receiving any financial support. The primary outcome is clinical adequacy, assessed through a validated 0-100 rubric applied to standardized clinical cases at three time points: baseline (T0), immediate post-training (T1), and follow-up (T2). Double-blind scoring and a third-reviewer arbitration process are used to ensure reliability (target kappa ≥0.70).

Secondary outcomes include changes in validated psychometric measures (NPQ-12, PABS-PT, HC-PAIRS, FABQ), adherence to PainTrain-AI micromodules, system usability (SUS), latency/friction metrics derived from platform logs, and indicators of low-value clinical practices. The trial incorporates a sex/gender randomization of clinical vignettes to identify and analyze potential gender bias in clinical decisions. All data collected refer to professionals, not patients. No identifiable clinical data are used; all datasets are pseudonymized according to the approved Data Management Plan (FAIR).

Assignment by clusters prevents contamination between arms, and all centers follow standardized operating procedures (PNT) for recruitment, training, and evaluation. The platform maintains audit logs, human-in-the-loop oversight, and ENS/RGPD-compliant security measures. Analyses will use mixed-effects models and Difference-in-Differences approaches to account for clustering, repeated measures, and baseline differences. Results will inform the feasibility, acceptability, and preliminary effectiveness of a digital simulation-based educational intervention intended to reduce the competency gap, decrease low-value practices, and mitigate gender bias in the management of chronic musculoskeletal pain in Primary Care.

Study Type

Interventional

Enrollment (Estimated)

185

Phase

  • Not Applicable

Contacts and Locations

This section provides the contact details for those conducting the study, and information on where this study is being conducted.

Study Contact

Study Locations

    • Lleida
      • Lleida, Lleida, Spain
        • Institut Català de la Salut (ICS) - Primary Care Network
        • Contact:
      • Lleida, Lleida, Spain
        • Specialized Care Comparative Setting
        • Contact:

Participation Criteria

Researchers look for people who fit a certain description, called eligibility criteria. Some examples of these criteria are a person's general health condition or prior treatments.

Eligibility Criteria

Ages Eligible for Study

  • Adult
  • Older Adult

Accepts Healthy Volunteers

Yes

Description

Inclusion Criteria:

  • Health professionals (medicine, nursing, physiotherapy, psychology, nutrition) working at participating Primary Care centers.
  • Active clinical practice during the study period.
  • Ability to access and use the digital platform (PainTrain-AI) and complete online assessments (T0, T1, T2).
  • Provides informed consent.

Exclusion Criteria:

  • Prior exposure to the PainTrain-AI platform within the previous 12 months (risk of contamination).
  • Planned absence or temporary leave during the evaluation windows (T0, T1, T2).
  • Inability to use the digital platform for technical reasons not solvable by support.
  • Declines participation.

Study Plan

This section provides details of the study plan, including how the study is designed and what the study is measuring.

How is the study designed?

Design Details

  • Primary Purpose: Health Services Research
  • Allocation: Non-Randomized
  • Interventional Model: Parallel Assignment
  • Masking: None (Open Label)

Arms and Interventions

Participant Group / Arm
Intervention / Treatment
Experimental: PainTrain-AI Educational Training (Cluster Implementation Arm)
Participants in Primary Care centers allocated to the intervention cluster receive the PainTrain-AI behavioral educational training. The intervention consists of simulated clinical encounters with virtual standardized patients and interactive micromodules, using a RAG-fenced architecture restricted to validated clinical content. All participants in this arm complete T0, T1, and T2 assessments.
PainTrain-AI is a behavioral educational intervention delivered through a digital clinical simulation platform. The system uses a retrieval-augmented generation (RAG) safety architecture that restricts all outputs to validated clinical content; the platform is non-diagnostic and does not generate new clinical information. Participants complete simulated consultations with virtual standardized patients and a series of brief micromodules designed to train biopsychosocial clinical reasoning for chronic musculoskeletal pain. The intervention is used exclusively for professional training and does not involve patient data. All participants in the intervention arm complete assessments at T0, T1, and T2.
Active Comparator: Usual Training / Standard Practice (Control Arm)
Participants in Primary Care centers allocated to the control cluster follow usual training and standard practice available at their institution. No exposure to the PainTrain-AI platform occurs during the study period. Centers continue their routine continuing medical education activities. All participants complete T0-T1-T2 assessments with the same standardized clinical cases and rubric. This arm serves as the active comparator for evaluating changes in clinical adequacy, low-value practice indicators, and gender-related decision patterns.

Participants continue with usual training and standard practice available at their institution.

No exposure to PainTrain-AI occurs. This arm serves as the active comparator.

What is the study measuring?

Primary Outcome Measures

Outcome Measure
Measure Description
Time Frame
Clinical adequacy score (0-100 rubric)
Time Frame: Baseline (T0), immediate post-training (T1), and 3-month follow-up (T2)
Clinical adequacy will be assessed using a validated 0-100 rubric applied to standardized clinical cases. Scores range from 0 (lowest adequacy) to 100 (highest adequacy), and higher scores indicate a better clinical outcome. The rubric evaluates three domains: (1) evaluation/triage (appropriate tests and red-flag assessment), (2) therapeutic recommendation (prioritizing active strategies and evidence-based pain education), and (3) clinical communication (avoiding iatrogenic messages and establishing functional goals). Scores are generated by double-blinded assessors with adjudication by a third reviewer in case of disagreement (target kappa ≥0.70). Change will be analyzed from T0 to T1 and T2.
Baseline (T0), immediate post-training (T1), and 3-month follow-up (T2)

Secondary Outcome Measures

Outcome Measure
Measure Description
Time Frame
System Usability Scale (SUS, 0-100)
Time Frame: Immediately after training
Usability of the PainTrain-AI intervention will be assessed with the System Usability Scale (SUS), a validated 10-item questionnaire that produces a score from 0 (lowest usability) to 100 (highest usability). Higher scores indicate better usability. The feasibility threshold is SUS ≥70, with an optimal target ≥80.
Immediately after training
Adherence to PainTrain-AI micromodules (% completed)
Time Frame: During the training period (up to 4 weeks)
Adherence will be measured as the percentage of scheduled micromodules or simulation sessions completed by each participant within the defined training period. Scores range from 0% (no modules completed) to 100% (all assigned modules completed). Higher percentages indicate greater engagement with the behavioral intervention.
During the training period (up to 4 weeks)
Low-value clinical practice indicators (count per case)
Time Frame: Baseline, immediately after training, and 3 months after training
Low-value practice indicators will be measured using standardized clinical cases scored with the 0-100 adequacy rubric. For this outcome, low-value practices are counted as discrete events, with possible values ranging from 0 (no low-value decisions in a case) to a higher count indicating more inappropriate decisions. Indicators include inappropriate diagnostic imaging, unnecessary pharmacologic escalation, or early referral to specialized care when not clinically indicated. The measure reflects the number of low-value decisions per case at each time point.
Baseline, immediately after training, and 3 months after training
System latency (seconds)
Time Frame: During the training period (up to 4 weeks)
Latency will be measured as the average system response time (in seconds) between user input and platform output during PainTrain-AI interactions. Scores range from 0 seconds (best possible performance) upward, with higher values indicating greater technological friction and lower technical performance. Latency is automatically recorded through system logs.
During the training period (up to 4 weeks)

Collaborators and Investigators

This is where you will find people and organizations involved with this study.

Investigators

  • Study Director: Fran Valenzuela-Pascual, PhD, IRBLleida / Universitat de Lleida
  • Study Director: Ester García Martínez, PhD, Universitat de Lleida / IDIAP Jordi Gol

Study record dates

These dates track the progress of study record and summary results submissions to ClinicalTrials.gov. Study records and reported results are reviewed by the National Library of Medicine (NLM) to make sure they meet specific quality control standards before being posted on the public website.

Study Major Dates

Study Start (Estimated)

March 1, 2029

Primary Completion (Estimated)

March 1, 2030

Study Completion (Estimated)

December 1, 2030

Study Registration Dates

First Submitted

March 24, 2026

First Submitted That Met QC Criteria

March 28, 2026

First Posted (Actual)

April 2, 2026

Study Record Updates

Last Update Posted (Actual)

April 2, 2026

Last Update Submitted That Met QC Criteria

March 28, 2026

Last Verified

March 1, 2026

More Information

Terms related to this study

Plan for Individual participant data (IPD)

Plan to Share Individual Participant Data (IPD)?

NO

IPD Plan Description

No individual participant data (IPD) will be shared because the study does not involve patient data or clinical individual-level information. All datasets refer to health professionals and are pseudoanonymized. Only aggregated results and anonymized usage datasets (logs, codebooks, processed data) may be shared after study completion following FAIR principles, as described in the Data Management Plan.

Drug and device information, study documents

Studies a U.S. FDA-regulated drug product

No

Studies a U.S. FDA-regulated device product

No

This information was retrieved directly from the website clinicaltrials.gov without any changes. If you have any requests to change, remove or update your study details, please contact register@clinicaltrials.gov. As soon as a change is implemented on clinicaltrials.gov, this will be updated automatically on our website as well.

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