A meta-analytic predictive approach to fitness-related dropout rates of special operations forces candidates

This is the authors' abstract. We don't add key points for this paper.

INTRODUCTION: High dropout rates during the selection of Special Operations Forces (SOF) are well-documented and often linked to inadequate physical preparedness and subsequent injuries. Training recommendations in a preparatory selection phase may offer a strategy to reduce dropout. OBJECTIVE: To assess whether fitness-related dropout was reduced in a study population of SOF candidates receiving training recommendations after fitness assessment, compared to historical attrition rates. METHODS: Using a prospective observational design, male candidates across Swiss Armed Forces and police SOF units received individualized training recommendations in the preparation phase of the main selection period. Dropout due to inadequate physical preparedness for the demands of SOF selection and basic training was tracked through all selection stages. A Bayesian analysis compared observed fitness-related dropout rates with a historical control group using a Meta-Analytic Predictive approach. RESULTS: Fitness-related dropout occurred in 29% of participants (40 of 137), compared to a historical average of 42%, corresponding to a relative reduction of over 30%. The posterior probability of a reduced dropout rate (odds ratio <1) was 91.6%. CONCLUSION: Targeted training guidance as part of human performance management may help to reduce fitness-related dropout rates among SOF candidates.