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

Title: A meta-analytic predictive approach to fitness-related dropout rates of special operations forces candidates
Authors: Dössegger, Alain; Gsponer, Thomas; Protte, Christian; Wyss, Thomas; Gilgen-Ammann, Rahel; Bron, Denis; Veil, Marina; Flück, Martin; Gerber, Markus; Stanga, Zeno
Contributors: Swiss Armed Forces Innovation Board
Source: Military Medicine ; ISSN 0026-4075 1930-613X
Publisher Information: Oxford University Press (OUP)
Publication Year: 2026
Description: 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
Document Type: article in journal/newspaper
Language: English
DOI: 10.1093/milmed/usaf619
DOI: 10.1093/milmed/usaf619/66290694/usaf619.pdf
Availability: https://doi.org/10.1093/milmed/usaf619; https://academic.oup.com/milmed/advance-article-pdf/doi/10.1093/milmed/usaf619/66290694/usaf619.pdf
Rights: https://creativecommons.org/licenses/by-nc/4.0/
Accession Number: edsbas.6608A47D
Database: BASE