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Effects of Military Occupational Exposures on Home-Based Assessment of Veterans’ Self-reported Health, Sleep and Cognitive Performance Measures

Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), ISSN: 1611-3349, Vol: 13310 LNAI, Page: 91-102
2022
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Conference Paper Description

Military occupational exposures are varied and the health effects from these exposures may accumulate over time, causing health concerns in Veterans. However, there are currently no comprehensive exposure assessment tools to assess these military exposures. In this report, we present findings from an ongoing study conducted remotely using telehealth technologies to assess the associations between military exposures and health measures. Veterans were recruited for the study and following enrollment, study participants completed remote data collection by (1) completing web surveys, (2) undergoing remote cognitive performance assessment and (3) wearing a wrist actigraphy device for seven days to examine sleep measures. Past military exposures were assessed using the Veteran-Military Occupational Assessment Tool (V-MOAT) which is a detailed survey that assesses military occupational exposures across well-defined occupational and environmental medicine domains of chemical, physical, biological, ergonomic/injury, and psychosocial hazards. Preliminary findings reveal that while longer military service duration and exposure duration were associated with better self-reported health measures and cognitive performance, military exposure frequency was more associated with poor self-reported health measures. Additionally, the exposure duration and service duration were negatively associated with the sleep efficiency and total sleep time respectively. These findings suggest that longer periods of military occupational exposures may not be as detrimental to health as higher exposure frequency.

Bibliographic Details

Immanuel Samuel; Kamila U. Pollin; Charity B. Breneman; Timothy Chun; Mary M. Valmas; Ryan C. Brewster; Michelle Prisco; John Barrett; Matthew J. Reinhard; Michelle E. Costanzo

Springer Science and Business Media LLC

Mathematics; Computer Science

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