Jodie Trafton Data-verified

Affiliation confirmed via AI analysis of OpenAlex, ORCID, and web sources.

High Impact

Researcher

University of Arkansas

Last publication 2025 Last refreshed 2026-04-01

faculty

46 h-index 199 pubs 9,797 cited

Research Areas

OverviewAI-generated summary

Jodie Trafton's research focuses on understanding and addressing critical health issues within the veteran population, with a significant emphasis on suicide risk and opioid use disorder. Trafton has published work investigating the cost-effectiveness of treatments for opioid use disorder and evaluating predictive modeling programs aimed at identifying and intervening with veterans at high risk for suicide. This includes studies on the REACH VET program within the Veterans Health Administration.

Further research by Trafton explores the genetic underpinnings of suicide attempts and suicidal behaviors. This work includes genome-wide association studies and meta-analyses, identifying genetic loci associated with suicide risk and examining the interplay between genetic factors and specific health conditions in large cohorts, such as the Million Veterans Program. Trafton also investigates the impact of mental health treatment, including the role of tele-mental health, particularly during the COVID-19 pandemic, and the effect of predictive analytics programs on patients prescribed opioids.

Trafton's scholarship metrics include an h-index of 46, with 199 total publications and over 9,700 citations, identifying them as a highly cited researcher. Key collaborators include Matthew Tyler Boden from the University of Arkansas at Fayetteville, and Sara J. Landes, Karen L. Drummond, and Rajinder Sonia Singh from the University of Arkansas for Medical Sciences.

Metrics

h-index: 46
Publications: 199
Citations: 9,797

Selected Publications

Describing county-level clustering patterns of suicide among Veterans Health Administration patients and all American adults, 2018–2019, using exploratory spatial data analysis (2025)

1 citation DOI OpenAlex
Identifying spatiotemporal patterns in opioid vulnerability: investigating the links between disability, prescription opioids and opioid-related mortality (2025)

3 citations DOI OpenAlex
Combining Machine Learning and Comparative Effectiveness Methodology to Study Primary Care Pharmacotherapy Pathways for Veterans With Depression (2025)

DOI OpenAlex
A multilevel investigation of potential inequities in the volume of mental health care received by Black Veterans Health Administration patients. (2025)

DOI OpenAlex
State-level suicide mortality insights: a comparative study of VHA veterans and the whole US population (2025)

2 citations DOI OpenAlex
What do primary care clinicians and patients think about internet-based computerized cognitive behavioral therapy for depression? A qualitative study from the Veterans Health Administration. (2025)

DOI OpenAlex
Decoding substance use disorder severity from clinical notes using a large language model (2025)

10 citations DOI OpenAlex
VA EDH Data Curation Documentation FY25-Q1 (2024)

DOI OpenAlex
Geographical Insights into Suicide Mortality Through Spatial Machine Learning (2024)

2 citations DOI OpenAlex
Investigating the importance of social vulnerability in opioid-related mortality across the United States (2024)

DOI OpenAlex
Describing County-Level Clustering Patterns of Suicide Among Veterans Health Administration Patients and All American Adults, 2018-2019 (2024)

DOI OpenAlex
VA EDH Data Curation Documentation FY24-Q4 (2024)

DOI OpenAlex
Providers’ use of pharmacogenetic testing to inform opioid prescribing among veterans (2024)

DOI OpenAlex
Association of short-term exposure to ambient air pollution and weather conditions with deaths of despair among U.S. Veterans (2024)

DOI OpenAlex
VA EDH Data Curation Documentation (FY24-Q3) (2024)

DOI OpenAlex