Review of instruments measuring decision making performance in military tactical level battle situation context

ABSTRACT

Decision-making skills are important for every small-unit military commander while leading troops in battle situations. Many constructs have been defined and scientifically measured in the context of military decision-making, but none of them have been used to assess decision-making during actual battlefield performances. This study focuses on finding an instrument that will be able to assess military tactical decision-making skills, cost-efficiently and reliably. A systematic literature review was undertaken using EBSCOhost Web database, in order to ascertain how decision-making in critical situations has been defined and how it has been measured. All studies were evaluated according to selected criteria, in order to determine which of the instruments were optimal for measuring military decision-making skills and what other measures have been used for descriptive or predictive purposes in these studies. Results indicate that decision-making instruments can be broadly divided into three performance types: live, simulated and tested. Tested performance instruments were found to be optimal for assessing military decision-making skills in tactical-level battle-like situations. However, since none of the existing instruments assessed decision-making in military battle leading situations, we concluded that such a test should be constructed.

KEYWORDS:

• Military decision making
• testing
• battle situations
• instrument
• measures

Disclosure statement

No potential conflict of interest was reported by the authors.

Notes

1. Reported quality categories are as follows: MI – the quality of main instrument (for example internal reliability, content validity, expert consensus, factor structure etc.), AI – the quality of additional instruments (for example incremental validity, correlations between measures, factor structure etc.) and R – the quality of results (for example group comparisons, pre-test post-test comparisons, effect sizes etc.)