{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,5,27]],"date-time":"2026-05-27T19:57:18Z","timestamp":1779911838042,"version":"3.53.1"},"reference-count":40,"publisher":"Oxford University Press (OUP)","issue":"1-2","license":[{"start":{"date-parts":[[2025,8,9]],"date-time":"2025-08-09T00:00:00Z","timestamp":1754697600000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/academic.oup.com\/pages\/standard-publication-reuse-rights"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2026,1,1]]},"abstract":"<jats:title>Abstract<\/jats:title>\n                  <jats:sec>\n                    <jats:title>Introduction<\/jats:title>\n                    <jats:p>Post-9\/11 wounded, ill, and injured (WII) veterans face significant and multifaceted challenges as they reintegrate into civilian life. These challenges span physical and mental health, economic well-being, and social integration. The Wounded Warrior Project (WWP) Annual Warrior Survey (AWS) serves as a key source of longitudinal data on this population. Although numerous studies have focused on single-year snapshots, this study provides a comprehensive longitudinal synthesis of AWS data from 2014 to 2022, supplemented by Wave 3 data from 2025 to bridge a 2023-2024 reporting gap. The aim is to identify evolving patterns in well-being indicators and inform strategic planning by veteran support organizations (VSOs).<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Materials and Methods<\/jats:title>\n                    <jats:p>This study uses publicly available, aggregated AWS data to examine trends across multiple well-being indicators: post-traumatic stress disorder (PTSD) prevalence, depression symptoms, anxiety, unemployment, food insecurity, sleep difficulties, and Quality of Life metrics (VR-12 PCS\/MCS). Generalized linear modeling (GLM) was employed to analyze trends over time, while ecological time-series regression was used to examine correlations between key variables at the group level. Limitations of this approach include reliance on aggregate data and restricted insight into WWP\u2019s internal weighting and validity methodologies.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Results<\/jats:title>\n                    <jats:p>Post-traumatic stress disorder prevalence remained persistently high across the study period (\u223c75-83%), with depression similarly elevated (\u223c67-77%). Obesity (\u223c50-52%) and chronic pain (\u223c70-75%) remained stable and widespread. The COVID-19 pandemic marked a sharp rise in unemployment (\u223c20-23% in 2020), and although rates declined by 2025 (\u223c12%), they did not return to pre-pandemic levels (\u223c8-11%). Quality of Life scores (VR-12) consistently lagged behind general population norms. Ecological regression indicated moderate positive correlations between PTSD prevalence and both unemployment and food insecurity. Additionally, sleep problems showed negative correlations with VR-12 mental component scores, suggesting a potential aggregate-level linkage between poor sleep and reduced mental health. These associations should be interpreted cautiously because of the potential for ecological fallacy. The absence of AWS data in 2023-2024 creates a discontinuity in year-over-year trend interpretation but does not undermine the overall long-term pattern stability.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Conclusions<\/jats:title>\n                    <jats:p>Findings reveal a deeply entrenched and interconnected set of challenges facing WII veterans, with mental health conditions, chronic pain, and unemployment representing sustained areas of concern. The results highlight the importance of integrated, data-driven approaches by VSOs to address these complex and enduring needs. Interventions focused on long-term mental health care, employment readiness, and sleep health are especially warranted. Despite limitations inherent in the use of aggregated data, this study underscores the utility of AWS as a longitudinal surveillance tool and a resource for targeted service planning. Future research should incorporate individual-level AWS data to explore causal relationships and identify subgroup-specific intervention pathways.<\/jats:p>\n                  <\/jats:sec>","DOI":"10.1093\/milmed\/usaf396","type":"journal-article","created":{"date-parts":[[2025,7,25]],"date-time":"2025-07-25T11:43:00Z","timestamp":1753443780000},"page":"e330-e337","source":"Crossref","is-referenced-by-count":1,"title":["Analyzing a Decade of Warrior Well-Being: Longitudinal Trends and Implications for U.S. Veteran Support From the Wounded Warrior Project Annual Survey (2014-2025)"],"prefix":"10.1093","volume":"191","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-0233-5029","authenticated-orcid":false,"given":"Thomas L","family":"Wiese","sequence":"first","affiliation":[{"name":"College of Business, SUNY Empire State University , 4 Park Ave , New York, NY, 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