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

ConditionEducational Intervention for Primary Care Professionals on Chronic Musculoskeletal Pain
Trial statusNot yet recruiting
Trial phaseNot applicable
Trial typeInterventional
Biological sexAll
Age18+
SponsorFrancesc Valenzuela Pascual

About this trial

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.

Eligibility criteria

This trial accepts healthy volunteers

Qualifiers

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.

Disqualifiers

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.

Trial design

Design model

Parallel

Treatments tested in this trial

  • PainTrain-AI Educational Training

    Behavioral

    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.

  • Usual Training / Standard Practice

    Behavioral

    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.

Treatment groups

185 Participants
are divided into 2 treatment groups
Group A: PainTrain-AI Educational Training (Cluster Implementation Arm)Experimental treatment 1 intervention
Group B: Usual Training / Standard Practice (Control Arm)Active comparator 1 intervention

Trial outcomes

Primary outcomes

1

Clinical adequacy score (0-100 rubric)

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.

Time frame
Baseline (T0), immediate post-training (T1), and 3-month follow-up (T2)

Secondary outcomes

1

System Usability Scale (SUS, 0-100)

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.

Time frame
Immediately after training
2

Adherence to PainTrain-AI micromodules (% completed)

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.

Time frame
During the training period (up to 4 weeks)
3

Low-value clinical practice indicators (count per case)

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.

Time frame
Baseline, immediately after training, and 3 months after training
4

System latency (seconds)

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.

Time frame
During the training period (up to 4 weeks)

Other outcomes

Sponsors and contacts

Click on the lead sponsor to view all of their trials.

Francesc Valenzuela Pascual

Lead sponsor

Universitat de Lleida

Sponsor institution

Source ClinicalTrials.gov

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