A meta-analytic predictive approach to fitness-related dropout rates of special operations forces candidates.
- DOI
- 10.1093/milmed/usaf619
- Published
- 2026 Jul 1
- Container
- Military medicine
- Publisher
- Not recorded
- Open access
- yes
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Cite this work
BibTeX
@article{allodium:10.1093/milmed/usaf619,
title = {A meta-analytic predictive approach to fitness-related dropout rates of special operations forces candidates.},
author = {Dössegger A and Gsponer T and Protte C and Wyss T and Gilgen-Ammann R and Bron D and Veil M and Flück M and Gerber M and Stanga Z},
year = {2026},
journal = {Military medicine},
doi = {10.1093/milmed/usaf619},
url = {https://doi.org/10.1093/milmed/usaf619}
}RIS
TY - JOUR TI - A meta-analytic predictive approach to fitness-related dropout rates of special operations forces candidates. AU - Dössegger A AU - Gsponer T AU - Protte C AU - Wyss T AU - Gilgen-Ammann R AU - Bron D AU - Veil M AU - Flück M AU - Gerber M AU - Stanga Z PY - 2026 JO - Military medicine DO - 10.1093/milmed/usaf619 UR - https://doi.org/10.1093/milmed/usaf619 ER -
APA
A, D., T, G., C, P., T, W., R, G., D, B., M, V., M, F., M, G., & Z, S. (2026). A meta-analytic predictive approach to fitness-related dropout rates of special operations forces candidates.. Military medicine. https://doi.org/10.1093/milmed/usaf619
Source records
- pubmed · retrieved 2026-09-26T22:37:54.355Z