Advancing PTSD-Substance Use Comorbidity Treatment Research Through Applying FAIR and FACT Data Science Frameworks in <i>Project Harmony</i>

Objective: Posttraumatic stress (PTSD) and substance use disorder (SUD) treatment research has been hampered by heterogeneous measures, inconsistent reporting, and sensitive data governance constraints that limit data synthesis and clinical translation. This manuscript describes how integrating FAIR (Findable, Accessible, Interoperable, Reusable) principles and FACT (Fairness, Accuracy, Confidentiality, Transparency) concepts can strengthen PTSD–SUD data science, with Project Harmony as an applied example. Method: We identify key barriers to evidence accumulation in PTSD–SUD clinical trials and map FAIR+FACT-aligned practices across the research lifecycle (data acquisition, harmonization, analysis, sharing, and dissemination). We then illustrate implementation strategies using procedures from Project Harmony’s (PH) individual participant data meta-analysis (IPD-MA), including common data element (CDE) labeling, interoperable harmonization pipelines, documentation of analytic decisions, and governance-informed access controls. Results: We identify priority points where FAIR+FACT alignment improves reproducibility and validity while reducing participant risk, particularly for populations vulnerable to confidentiality harms and stigma. The PH case example demonstrates feasibility of rigorous harmonization and measurement-equivalence approaches at scale and shows how transparent, provenance-preserving workflows can support comparative effectiveness analyses across diverse trials. Conclusions: FAIR+FACT integration offers a practical framework for advancing trustworthy PTSD–SUD treatment evidence. We provide specific recommendations for investigators, clinical trial networks, and funders/policymakers to institutionalize FAIR+FACT requirements and resource the personnel and infrastructure needed for ethical, reusable PTSD–SUD datasets. Routine adoption of interoperable metadata standards, rigorous documentation and code sharing, and trauma-informed governance can accelerate guideline development, strengthen policy relevance, and improve clinical decision-making for individuals with comorbid PTSD and SUD.

Authors

Institutions

Publication Details

Journal
Journal of Studies on Alcohol and Drugs
Published
2026-07-27
DOI
https://doi.org/10.15288/jsad.26-00098
Primary Topic
Ethics in Clinical Research
Type
article
Field-Weighted Citation Impact
0.00
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Advancing PTSD-Substance Use Comorbidity Treatment Research Through Applying FAIR and FACT Data Science Frameworks in Project Harmony

A. DE HAAN, J. Hamblen, N. Kassam-Adams, M. O’Neil et al.
Journal of Studies on Alcohol and Drugs
Ethics in Clinical Research
article

Advancing PTSD-Substance Use Comorbidity Treatment Research Through Applying FAIR and FACT Data Science Frameworks in Project Harmony

A. DE HAAN, J. Hamblen, N. Kassam-Adams, M. O’Neil, A. A Morgan-Lopez, D.A. Hien
article en

Abstract

Objective: Posttraumatic stress (PTSD) and substance use disorder (SUD) treatment research has been hampered by heterogeneous measures, inconsistent reporting, and sensitive data governance constraints that limit data synthesis and clinical translation. This manuscript describes how integrating FAIR (Findable, Accessible, Interoperable, Reusable) principles and FACT (Fairness, Accuracy, Confidentiality, Transparency) concepts can strengthen PTSD–SUD data science, with Project Harmony as an applied example. Method: We identify key barriers to evidence accumulation in PTSD–SUD clinical trials and map FAIR+FACT-aligned practices across the research lifecycle (data acquisition, harmonization, analysis, sharing, and dissemination). We then illustrate implementation strategies using procedures from Project Harmony’s (PH) individual participant data meta-analysis (IPD-MA), including common data element (CDE) labeling, interoperable harmonization pipelines, documentation of analytic decisions, and governance-informed access controls. Results: We identify priority points where FAIR+FACT alignment improves reproducibility and validity while reducing participant risk, particularly for populations vulnerable to confidentiality harms and stigma. The PH case example demonstrates feasibility of rigorous harmonization and measurement-equivalence approaches at scale and shows how transparent, provenance-preserving workflows can support comparative effectiveness analyses across diverse trials. Conclusions: FAIR+FACT integration offers a practical framework for advancing trustworthy PTSD–SUD treatment evidence. We provide specific recommendations for investigators, clinical trial networks, and funders/policymakers to institutionalize FAIR+FACT requirements and resource the personnel and infrastructure needed for ethical, reusable PTSD–SUD datasets. Routine adoption of interoperable metadata standards, rigorous documentation and code sharing, and trauma-informed governance can accelerate guideline development, strengthen policy relevance, and improve clinical decision-making for individuals with comorbid PTSD and SUD.

Journal of Studies on Alcohol and Drugs
Rutgers, The State University of New Jersey (US), Dartmouth College (US), Children's Hospital of Philadelphia (US), Oregon Health & Science University (US), RTI International (US), Research Institute of Emergency Childrens Surgery and Traumatology (RU), Translational Research Informatics Center (Japan) (JP), VA Portland Health Care System (US), National Center for Post Traumatic Stress Disorder (US), Ruhr University Bochum (DE)
Openalex Percentile: Top 7%
Ethics in Clinical Research
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.