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Using Data Science To Center Patient Perspectives in Mechanism Discovery

Study acronym: CPP
StatusActive, Not Recruiting
PhaseNot specified
Started
View on ClinicalTrials.gov ↗

Record History

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  1. Study completion date: Dec 5, 2026 to Dec 31, 2026
    • Publications: details revised at 4 of 4 entries
  2. Primary completion date changed from estimate of Jun 5, 2025 to May 5, 2025
    • Study completion date: Sep 5, 2025 to Dec 5, 2026
    v5
  3. Trial status: Recruiting to Active, Not Recruiting
    • Enrollment target: estimated 30 to confirmed 33
    • Primary completion date: May 5, 2025 to Jun 5, 2025
    • Site details revised
    v4
  4. Trial status: Not Yet Recruiting to Recruiting
    • Start date changed from estimate of Feb 29, 2024 to Mar 19, 2024
    • Site details revised
    v3
  5. Study description expanded, about 3 wordsv2
  6. Study First Submitted
  • Stopped: an ongoing trial was terminated, suspended or withdrawn.
  • Notable: the trial’s plan changed such as a big move in its timeline or size, a new primary endpoint, sponsor or phase, or recruiting opened or resumed.
  • Minor: routine progress and housekeeping, such as sites added or enrollment closed.
Cambridge Health Alliance
15 trials monitored
See 1 trial at risk
PTSD
889 trials monitored
See 54 trials at risk
Including patient perspectives when developing new therapy interventions is crucial because it can help to understand response heterogeneity and promote engagement. Yet, analyzing patient interview data is difficult and time-consuming. This study aims to explore the potential for natural language processing and deep learning to analyze patient interviews and identify potential ways in which therapy leads to psychological change. This study will recruit participants from an existing clinical service that offers a 16-week online group therapy model (and adjunct individual therapy sessions) called Program for Alleviating and Resolving Trauma and Stress (PARTS) based on a therapy called Internal Family Systems (IFS). The investigators will use a mixed methods approach, applying natural language processing and deep learning to develop models that identify potential mechanisms of change. These models will be based on patient perspectives of psychological change, as expressed in interviews, and be compared to models based on clinical measures.
Trial Details
NCT Number NCT06233968
Lead Sponsor Cambridge Health Alliance
Collaborators: Foundation for Self Leadership
Conditions
(from sponsor)		 Posttraumatic Stress Disorder, Complex Post-Traumatic Stress Disorder
Related terms Stress Disorders, Post-Traumatic
Enrollment 33 participants
Start Date
Primary Completion (estimated)
Study Completion (estimated)
Updated on ClinicalTrials.gov