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Objective: There is growing interest in the concepts of listening effort and fatigue associated with hearing loss. However, the theoretical underpinnings and clinical meaning of these concepts are unclear. This lack of clarity reflects both the relative immaturity of the field and the fact that research studies investigating listening effort and fatigue have used a variety of methodologies including self-report, behavioural, and physiological measures., Design: This discussion paper provides working definitions for listening effort and listening-related fatigue. Using these definitions as a framework, methodologies to assess these constructs are reviewed., Results: Although each technique attempts to characterize the same construct (i.e. the clinical presentation of listening effort and fatigue), different assumptions are often made about the nature of these phenomena and their behavioural and physiological manifestations., Conclusion: We suggest that researchers consider these assumptions when interpreting their data and, where possible, make predictions based on current theoretical knowledge to add to our understanding of the underlying mechanisms of listening effort and listening-related fatigue., Foreword: Following recent interest in the cognitive involvement in hearing, the British Society of Audiology (BSA) established a Special Interest Group on Cognition in Hearing in May 2013. In an exploratory group meeting, the ambiguity surrounding listening effort and fatigue was discussed. To address this problem, the group decided to develop a 'white paper' on listening effort and fatigue. This is a discussion document followed by an international set of commentaries from leading researchers in the field. An approach was made to the editor of the International Journal of Audiology who agreed to this suggestion. This paper, and the associated commentaries that follow, are the result.

A system using electroencephalography (EEG) signals could enhance the detection of mental fatigue while driving a vehicle. This paper examines the classification between fatigue and alert states using an autoregressive (AR) model-based power spectral density (PSD) as the features extraction method and fuzzy particle swarm optimization with cross mutated of artificial neural network (FPSOCM-ANN) as the classification method. Using 32-EEG channels, results indicated an improved overall specificity from 76.99% to 82.02%, an improved sensitivity from 74.92 to 78.99% and an improved accuracy from 75.95% to 80.51% when compared to previous studies. The classification using fewer EEG channels, with eleven frontal sites resulted in 77.52% for specificity, 73.78% for sensitivity and 75.65% accuracy being achieved. For ergonomic reasons, the configuration with fewer EEG channels will enhance capacity to monitor fatigue as there is less set-up time required.

Fatigue can be defined as a subjective state of an imbalance in the availability of inner resources needed to perform physical or mental activities. The level of fatigue is determined not only by the availability of inner resources but also by the demands of the activities performed. Most conventional fatigue scales require subjects to rate their level of fatigue without specifying the situation. In the present study, we constructed a subjective rating scale, the Situational Fatigue Scale (SFS), with which subjects estimated their level of fatigue in specific activities of daily life. We administered the SFS, along with the Fatigue Assessment Instrument (FAI) to 96 outpatients in a family-medicine clinic and to 62 college students to assess the psychometric properties of the SFS. Principle component analysis revealed two underlying factors: physical fatigue and mental fatigue. SFS scores were significantly correlated with several FAI scores and differentiated patients complaining of fatigue from those who did not. The SFS also showed good internal consistency and test-retest reliability. These results suggest that the SFS could be a useful tool to measure a different dimension of the broad concept of fatigue.

The aim of the present study was to test the structural stability and reliability of the Swedish occupational fatigue inventory (SOFI) for use in a group of Chinese visual display terminal (VDT) workers. A qualified translator was recruited to translate the Chinese version of the SOFI (SOFI-C). The content validity was established with 12 bilingual practitioners and seven professional experts. The translated SOFI was administered to 104 sedentary workers on two occasions with an interval of 60 min. Most of them were female (80.8%) and they had a mean age of 34.5 years. Fifty-one percent of them reported using a VDT for 4h or more at work. Exploratory factor analysis revealed a five-factor solution, which was comparable to the original latent factors. Cronbach's alpha for the five-factor scales was between 0.88 and 0.95. The test-retest reliability was satisfactory with intra-class correlations ranging from 0.69 to 0.83. The workers who used a VDT for 4h or more had significantly higher SOFI scores than those who used one for less than 4 h (p = 0.007 - 0.046). The results indicated that the SOFI-C was valid and reliable for measuring fatigue among Chinese sedentary workers. The satisfactory structural stability suggested that cultural influences on the construct of fatigue were not strong. Its characteristics of discrimination of the sedentary workers who had high VDT exposure suggested that the SOFI-C would be a useful instrument for prevention and intervention programs designed for work-related injuries in the workplace.