Examining the Relationship Between Mental, Physical, and Organizational Factors Associated With Attrition During Maritime Forces Training

ABSTRACTBinsch, O, Banko, KM, Veenstra, BJ, and Valk, PJL. Examining the relationship between mental, physical, and organizational factors associated with attrition during maritime forces training. J Strength Cond Res 29(11S)S187–S191, 2015—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 “trainersʼ judgment” on the “recruitsʼ 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.