Theoretical and Applied Ergonomics

Work-related musculoskeletal disorders (WRMSDs) remain a major occupational health challenge, and automotive service work is a high-risk context involving awkward postures, repetitive tasks, and sustained static loading. Conventional ergonomic tools capture static posture snapshots and do not reflect how musculoskeletal stress accumulates over time. This study developed the Manual Integrated Ergonomics Risk Assessment Tool (MIERAT), a low-cost, observation-based framework for resource-constrained automotive settings, and conducted an initial field validation. MIERAT combines REBA-based posture severity (PS), exposure duration (D), and a calibrated Time Modifier (TM; 1.0–2.5) into a Cumulative Risk Index (CRI = PS × D × TM), grounded in biomechanical loading theory and aligned with ISO 11226, ISO 11228-1, and ISO 45001. Expert panel review yielded an S-CVI/Ave of 0.95, indicating strong content validity. Duration–CRI associations were very strong for under-vehicle servicing (ρ = 0.910), tyre fitment (ρ = 0.961), and brake/suspension repair (ρ = 0.945), all p < 0.001. Because duration enters the CRI equation directly and also determines the TM, these correlations are mathematically expected; they show that the index behaves as designed but are not independent evidence of construct validity. Inter-rater reliability across three observers was excellent (ICC = 0.975–0.997), with moderate-to-perfect categorical agreement (weighted κ = 0.557–1.000). Task-level profiling identified tyre demounting, wheel alignment, and drain plug loosening as dominant ergonomic hotspots. These findings provide preliminary support for MIERAT as a content-valid and reliable tool for profiling cumulative postural exposure and planning ergonomic interventions in South African automotive workshops. Validation against independent outcomes, such as musculoskeletal symptoms, fatigue, biomechanical loading, or injury data, is needed to establish its construct and predictive validity.

This study considers the cognitive factors influencing the adoption of artificial intelligence (AI) coding agents among software engineers in Agile development environments. In this context, Transparency refers to the degree to which an AI system’s decision processes are clear or understandable to its users, while Trust denotes the confidence developers place in the reliability and correctness of AI-generated code. Specifically, it analyzes the roles of Transparency and Trust as predictors of developers’ Behavioral Intention to deploy AI-generated code. Using a quantitative, cross-sectional survey design administered to 19 Agile software professionals, this study uses descriptive statistics, Pearson correlation analysis, and simple and multiple linear regression to test a mediation model based on the Technology Acceptance Model (TAM). In this exploratory pilot sample, Trust emerged as the strongest predictor of Behavioral Intention (β = 0.64, p = 0.007), though findings should be interpreted cautiously given the limited sample size. Trust demonstrated the strongest association with Behavioral Intention, while Transparency showed a non-significant positive association with Trust. The observed pattern is consistent with a possible indirect relationship, although mediation was not confirmed in this sample. This evidence suggests that organizations seeking to improve AI adoption in development teams should prioritize the reliability and accuracy of AI tools, conditions that encourage trust, over transparency features alone. This study adds to the cognitive engineering literature on human–AI interaction in high-cognitive-demand work environments.

Psychosocial stress has been shown to affect EMG activity in the upper body; however, no known studies have attempted similar research on the lower body. Accordingly, this study aimed to analyze the effects of psychosocial stress on surface EMG amplitude and frequency in the lower leg. The tibialis anterior (TA) and gastrocnemius medialis (GM) were tested on 13 healthy subjects. Two sets of isometric fatigue trials were performed by each muscle, separated by the Trier Social Stress Test. Wilcoxon signed-rank tests were performed (confidence interval (CI) of 95%), and no significant difference was found in mean amplitude (p ≈ 0.30), mean frequency (p ≈ 0.20), or rate of change before and after psychosocial stress. All pre- to post-stress comparisons were determined to be statistically equivalent using the two one-sided t-tests method at 5% significance using a 90% CI. The results imply that the effects of psychosocial stress observed in upper-body muscles may not generalize directly to the lower leg for the conditions of this study and should be evaluated in a muscle-specific and task-specific manner. While limited by a small cohort, these exploratory findings challenge the generalizability of upper-body stress models and establish critical baseline parameters for larger, muscle-specific lower-limb neuromusculoskeletal investigations.