ArticleFrontiers in digital health2025
Real-time monitoring of military health and readiness: a perspective on future research.
Article in Frontiers in digital health, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers, 1 of them a synthesis that pooled it.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
3 citing papers in PubMed, 1 synthesis or guideline pooled it.
- Heart rate variability as a dual-use digital biomarker: integrating clinical, AI, and operational perspectives on human performance and resilience.BMC cardiovascular disorders · 2026Pooled it
- Monitoring military pilots with textile sensors: physiological responses and signal quality under extreme conditions.Frontiers in physiology · 2026Article
- Development of a military mental health training program aiming to promote mental health and operational readiness in the Danish armed forces: an intervention mapping approach.Frontiers in public health · 2025Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
5 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Military personnel face significant physical and mental demands, making continuous physiological monitoring essential for understanding health status, managing long-term health risks, and predicting a soldier's readiness to perform in military operations. Recent advancements in wearable technology enable the tracking of biomarkers and psychophysiological indicators, yet current approaches remain fragmented, often focusing on isolated health outcomes rather than comprehensive, actionable insights. This perspective article reviews overarching theoretical health models and examines statistical modeling approaches to better capture the multidimensional nature of health and readiness. Building on these insights, a vision is presented for developing a military health and readiness monitoring system that integrates wearable technology with tailored health indicators and outcomes, aligned with the specific demands of military tasks. The role of advanced tools, such as Large Language Models (LLMs) and Knowledge Graphs in contextualizing health data with operational demands is highlighted, offering a pathway to more accurate and actionable assessments of readiness. This vision outlines key considerations for future development, aiming to empower service members and military leadership with effective tools for health and readiness management.
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What Socratic holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the Socratic graph.