Analysis of a national response to a White House directive for ending veteran suicide

Andrea F. Kalvesmaki, Alec B. Chapman, Kelly S. Peterson, Mary Jo Pugh, Makoto Jones, Theresa C. Gleason

Research output: Contribution to journalArticlepeer-review


Objective: Analyze responses to a national request for information (RFI) to uncover gaps in policy, practice, and understanding of veteran suicide to inform federal research strategy. Data source: An RFI with 21 open-ended questions generated from Presidential Executive Order #1386, administered nationally from July 3 to August 5, 2019. Study design: Semi-structured, open-ended responses analyzed using a collaborative qualitative and text-mining data process. Data extraction methods: We aligned traditional qualitative methods with natural language processing (NLP) text-mining techniques to analyze 9040 open-ended question responses from 722 respondents to provide results within 3 months. Narrative inquiry and the medical explanatory model guided the data extraction and analytic process. Results: Five major themes were identified: risk factors, risk assessment, prevention and intervention, barriers to care, and data/research. Individuals and organizations mentioned different concepts within the same themes. In responses about risk factors, individuals frequently mentioned generic terms like “illness” while organizations mentioned specific terms like “traumatic brain injury.” Organizations and individuals described unique barriers to care and emphasized ways to integrate data and research to improve points of care. Organizations often identified lack of funding as barriers while individuals often identified key moments for prevention such as military transitions and ensuring care providers have military cultural understanding. Conclusions: This study provides an example of a rapid, adaptive analysis of a large body of qualitative, public response data about veteran suicide to support a federal strategy for an important public health topic. Combining qualitative and text-mining methods allowed a representation of voices and perspectives including the lived experiences of individuals who described stories of military transition, treatments that worked or did not, and the perspective of organizations treating veterans for suicide. The results supported the development of a national strategy to reduce suicide risks for veterans as well as civilians.

Original languageEnglish (US)
Pages (from-to)32-41
Number of pages10
JournalHealth Services Research
Issue numberS1
StatePublished - Jun 2022
Externally publishedYes


  • health policy/politics/law/regulation
  • mental health
  • natural language processing
  • qualitative research
  • veterans

ASJC Scopus subject areas

  • Health Policy


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