Year: 2026
Type: article
Abstract: INTRODUCTION: Mental workload (MWL) is a key factor in fighter pilot training, yet the widely used NASA Task Load Index (NASA-TLX) may contain dimensions that are less relevant when pilot training is conducted in a simulator. This study examined whether the number of dimensions required to assess MWL could be reduced without compromising the validity of the NASA-TLX. METHODS: NASA-TLX data were collected from 716 high-fidelity F/A-18 simulator missions flown by 20 combat-ready pilots across several different exercises. Pilots provided weights for workload dimensions prior to missions and completed postmission ratings of the dimensions. Analyses included descriptive statistics of weights and scores, principal component analysis, and rank-based correlations between overall workload estimates computed from reduced-dimension composites and those based on all six workload dimensions. RESULTS: Mental demand received the highest weight, while physical demand was consistently lowest. Principal component analysis revealed two components: a cognitive-emotional factor (mental, temporal, frustration) and a performance-effort factor (own performance, effort). Physical demand showed low communality and negligible loadings. Correlation analyses demonstrated that a three-dimensional composite (mental, temporal, frustration) closely reproduced the overall workload determined using six dimensions, while adding own performance and effort further improved correspondence. DISCUSSION: The findings indicate that the NASA-TLX can be streamlined for simulated fighter missions by omitting the physical demand dimension and, when brevity is essential, by using three dimensions (mental, temporal, frustration) without substantial loss of validity. This approach reduces pilot burden and simplifies administration, supporting efficient MWL assessment in training contexts. Mansikka H, Virtanen K. Streamlining NASA task load index for simulated fighter missions. Aerosp Med Hum Perform. 2026; 97(4):279-283.
Authors: Heikki Mansikka, Kai Virtanen
Language: English
Subfield: Social Psychology
Field: Psychology
Domain: Social Sciences
Open Access status: green
OpenAlex ID: W7141588985
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