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For infantry units of the Dutch Ministry of Defence, high attrition rates (varying from 42 to 68%) during initial training are a persisting problem. The reasons for this attrition are diverse. Having better insight into the causes of attrition is a prerequisite for implementing preventive measures. To achieve this, a monitoring assessment system was developed that integrated the effects of physical, mental, and organizational determinants on operational readiness. The aim of this study was to implement the monitoring tools and to establish the set of determinants that best predicted attrition during infantry training of new recruits. Eighty-five recruits were monitored over a 24-week infantry training course. Before the training, recruits were screened for medical, psychological, and physical wellness. During the monitoring phase, mental, physiological, and organizational indicants were obtained using an array of tools such as questionnaires, chest belt monitors (for heart rate, acceleration, and skin temperature measurements), and computerized tests (e.g., vigilance, long-term memory). Survival analyses were used to tease out the determinants of individual and grouped predictors of attrition. Nearly half the recruits (47%) failed the training. Attrition was predicted by both physiological and mental determinants. However, the organizational determinant "trainers' judgment" on the "recruits' military quality" dominated the physiological and mental determinants. It was concluded that the monitoring system was successfully implemented during infantry training, and that the survival analysis method emphasized on single effects and interactions between the different determinants. Based on the current findings, we recommend several steps to successfully implement a monitoring method in settings with high demands.

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We investigated electrodermal activity (EDA) in 130 participants undergoing a shortened version of a novel easy, effective and controlled method to induce stress (the Sing-a-Song Stress Test). We compared skin conductance level (SCL), amplitude and number of skin conductance response peaks with respect to their sensitivity to the known stressor, for different scenarios of interests. EDA increased after stressor-onset for almost all participants. At a group level, the three variables were about equally sensitive. When examining the increase following the stressor with respect to preceding EDA within one individual, peak amplitude was most sensitive. Peak measures were clearly most sensitive in a simulated between-subject scenario (i.e., testing the difference in EDA between stress and non-stress intervals as if data originated from different, stressed and non-stressed groups of individuals). Peaks can be extracted by continuous decomposition (CDA) or through-to-peak analysis (TTP). In all analyses performed, CDA outperformed TTP. We thus recommend CDA peak amplitude for monitoring physiological stress effects in e.g. symbiotic systems.

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