An intelligible mathematical framework for quantifying neuro-behavioural fatigue and adaptive risk evaluation in educational settings

University students often experience multiple sources of stress, including academic, digital, and lifestyle-related factors. Traditional fatigue assessment tools are largely based on psychometric questionnaires capturing subjective evaluations of fatigue. However, such tools rarely account for multiple interrelated factors in a cohesive framework. This paper introduces the interpretable computational framework known as the Neuro-Behavioural Fatigue Assessment Model (NFAM) for identifying neuro-behavioural fatigue based on commonly reported questionnaire data. The framework employs a composite fatigue index characterized by three underlying components. The first component is the Cognitive Fatigue Index (CFI), which represents fatigue-related factors associated with attention and recovery. The second component is the Digital Overload Multiplier (DOM), which accounts for interaction effects between digital activity and academic engagement. The third component is the Sleep Efficiency Model (SEM), which estimates the sleep-related contribution to overall fatigue using lifestyle factors. The components were combined to form the composite score (i.e., the NFAM composite). The framework was evaluated using the data from 1000 university students. Preliminary assessment of the questionnaire variables suggested that the NFAM is better conceptualised as a formative computational framework rather than a reflective psychometric instrument. The sensitivity analysis of the weightings indicated that the framework remained stable under alternative weighting configurations. The statistical analysis indicated significant differences between the defined fatigue-risk categories, consistent framework performance across the evaluated participants, and the ability to explain individual responses using the composite index. Overall, the current study provides an interpretable framework for assessing neuro-behavioural fatigue in a university student population. Future research will include external validation of the NFAM using independent datasets and established psychometric fatigue measures.