Development of physical selection procedures for the British Army. Phase 2: Relationship between physical performance tests and criterion tasks

This paper is the second in a series of three to describe the development of physical selection standards for the British Army. The first paper defined criterion tasks (single lift, carry, repetitive lift and carry, and loaded march tasks) and set standards on the criterion tasks for all British Army trades. The principal objective was to determine which combination of physical performance tests could be best used to predict criterion task performance. Secondary objectives included developing so-called ‘gender-free’ and ‘gender-unbiased’ models. The objectives were met by analysing performance data on the criterion tasks and a large battery of physical performance tests collected from 379 trained soldiers (mean age 23.5 (SD 4.45) years, stature 1734 (SD 79.5) mm, body mass 71.4 (SD 10.58) kg). Objective 1 was met: the most predictive physical performance tests were identified for all criterion tasks. Both single lift tasks were successfully modelled using muscle strength and fat free mass scores. The carry model incorporated muscle endurance and body size data, but the errors of prediction were large. The repetitive lift models included measures of muscle strength and endurance, and body size, but errors of prediction were also large. The loaded march tasks were successfully modelled incorporating indices of aerobic fitness, supplemented by measures of strength, endurance or body size and composition. The secondary objectives were partially fulfilled, though limitations in the data hampered the process. Although only one model (a loaded march) was gender-free, three models were gender-related (i.e. contained ‘gender’ explicitly in the model). The remaining six were gender-specific (i.e. were appropriate for men or for women). Owing to both a lower accuracy of prediction in women's scores and a greater tendency for the women's scores to be distributed around the pass standards, a greater percentage of women than men were misclassified as passing or failing, resulting in indirect discrimination. A validation of the models in a separate sample of the user population of recruits is reported in the third paper in this series.