This study examined the prevalence and human factors correlates of startle and surprise events in commercial aviation using a large-scale analysis of NASA Aviation Safety Reporting System (ASRS) narratives. While startle and surprise effects have been identified as contributors to loss-of-control events and other critical incidents, prior empirical research has relied primarily on small-sample surveys, laboratory studies, or case analyses of individual accidents. The present study extends this work by analyzing the co-occurrence of pre-coded human factors with startle-related language across a decade of confidential incident reports. A keyword-matching algorithm was applied to 38,655 ASRS reports (2012–2022) to identify 2,642 reports (6.8%) containing startle/surprise-related language. Chi-square tests, odds ratio analyses with 95% confidence intervals, and logistic regression were used to compare human factors, flight phase distributions, anomaly types, and outcomes between startle-flagged and non-startle reports. All major human factors—including Fatigue (OR = 1.86, p < .001), Physiological factors (OR = 2.11, p < .001), Workload (OR = 1.60, p < .001), and Confusion (OR = 1.38, p < .001)—were significantly over-represented in startle reports. Logistic regression confirmed Physiological factors (β = 0.75) and Fatigue (β = 0.48) as the strongest independent predictors. Loss of aircraft control was 2.4 times more prevalent in startle reports. These findings provide large-scale empirical evidence that fatigue, physiological vulnerability, and high workload significantly amplify the risk and severity of startle reactions in operational aviation, supporting the development of targeted Crew Resource Management interventions and evidence-based training protocols.
Human factors remain one of the leading contributors to aviation accidents despite continuous advancements in aircraft technology and safety regulations. This study examined the critical role of human factors in aviation accident prevention, focusing on Crew Resource Management (CRM), Training and Competency Development, and Safety Culture among Aircraft Maintenance Technology (AMT) students, licensed aircraft mechanics, and on-the-job training (OJT) trainees at Indiana Aerospace University during the Academic Year 2025–2026. An explanatory sequential mixed-method research design was employed, integrating quantitative survey data with qualitative interview responses to provide a comprehensive understanding of maintenance-related human factors. A total of 90 respondents participated in the quantitative phase, while 10 participants were purposively selected for the qualitative inquiry. Descriptive statistics, including frequency, percentage, weighted mean, and ranking, were utilized to analyze quantitative data, whereas thematic analysis was applied to qualitative responses. The findings revealed that respondents strongly agreed on the critical importance of CRM, Training and Competency Development, and Safety Culture in preventing aviation accidents. Teamwork, communication, situational awareness, competency-based training, and organizational commitment to safety were consistently identified as essential elements for minimizing maintenance-related errors. However, the study also identified persistent challenges, including communication breakdowns, insufficient emphasis on human factors education, limited practical exposure, inadequate maintenance resources, ineffective shift turnovers, and unclear task allocation. These issues indicate the need for stronger integration of technical and non-technical competencies within aviation education and maintenance organizations. Based on the findings, an action plan emphasizing continuous human factors training, standardized communication protocols, simulation-based learning, and the promotion of a proactive safety culture was developed. The study contributes empirical evidence that supports curriculum enhancement, organizational safety initiatives, and evidence-based strategies for reducing maintenance-related human errors and strengthening aviation safety.
Brian Robinson, Lance Frederic Arcosa, Khazim Joseph Cagigas et al.· Journal of Advanced Studies...· 0 citations
This work presents an AI-assisted approach that generates candidate hazard scenarios from NASA's Aviation Safety Reporting System (ASRS), and proposes a hybrid variant, conditioning narrative generation on a structured hypothesis produced via evolutionary abduction, improving correctness and reducing variability.
Cristian Mascia, R. Pietrantuono, Daniel Rodríguez et al.· 0 citations
Aviation safety depends heavily on precise interaction between pilots and Air Traffic Control (ATC), yet failures within that interaction remain a recurring contributing factor in civil aviation accidents and incidents. This study aims to identify and analyze patterns of ATC-related failure across a set of historically significant aviation accidents and incidents, and to derive implications for global aviation safety improvement. A qualitative literature review design was employed, drawing on official investigation reports, safety databases, and peer-reviewed journal articles concerning five representative events—Tenerife (1977), Zagreb (1976), Uberlingen (2002), Linate (2001), and Jakarta Halim (2016)—synthesized through directed content analysis guided by the Human Factors Analysis and Classification System (HFACS) and Reason's Swiss Cheese Model. The findings reveal that communication breakdowns, non-standard phraseology, controller work overload, limitations in surveillance technology, and weak inter-unit coordination constitute recurring causal patterns behind ATC-related accidents/incidents. The study concludes that enhancing aviation safety requires stricter phraseology standardization, strengthened Crew/Team Resource Management training for controllers, and sustained investment in surface radar and conflict-alert technologies.
Hendro Eko Saputro, Elfi Amir, Rany Adiliawijaya et al.· International Journal of Hea...· 0 citations
Dynamic positioning (DP) operations are safety-critical maritime activities in which technical system performance, environmental conditions and human decision-making interact continuously. Previous research presented a prediction model based on binary logistic regression that estimates the likelihood of human-error-related DP incidents, identifying the percentage of thrusters online as the significant predictor, using IMCA-reported data from 2007–2015. This study evaluates whether the previously developed prediction model remains valid when applied to a more recent IMCA dataset, with DP incidents from 2016 to 2025. A retrospective documentary analysis was conducted, and 77 incidents met the inclusion criteria for statistical analysis. Human-related factors were identified as a main or secondary cause in 35 cases, representing 45.5% of the analysed sample. The original thruster-based relationship was not reproduced in the updated drilling subset, where the percentage of thrusters online did not distinguish between human-related and non-human-related incidents. Applying the previous model resulted in poor discriminatory performance (AUC = 0.541), indicating that the original relationship between thruster availability and human-related incidents was no longer observed. Additional regression analyses found no statistically significant association between the selected operational, technical or environmental variables and human-related causation. These findings suggest that historical prediction models should be re-evaluated before being applied to contemporary DP operations. They also indicate that the variables available in IMCA reports alone are insufficient to explain human-related incident causation, highlighting the need for future studies to investigate additional human and organisational factors.
Željana Lekšić, Z. Sánchez-Varela· Applied Sciences· 0 citations
This study analyzes the contribution of legal aspects and human factors to civil aviation accidents and incidents associated with Air Traffic Control (ATC) services. Utilizing a qualitative descriptive literature review methodology, this research conducts a comparative evaluation of the Halim Perdanakusuma runway collision accident (2016) and the Austin-Bergstrom near-miss incident (2023). The juridical framework is anchored in Indonesian Aviation Law No. 1 of 2009 and International Civil Aviation Organization (ICAO) standards, while systemic analysis applies the SHELL model and HFACS taxonomy. The results indicate that expectation bias and operational deviations from standardized radio-telephony phraseology are the primary drivers of cognitive and procedural failures. Weak supervisory monitoring and the absence of integrated surface surveillance technology further compromised the systemic defenses in both cases. In conclusion, runway accidents and incidents do not result from isolated operator errors but stem from interactive mismatches within the sociotechnical system. Enforcing legal compliance with standard safety procedures and accelerating the deployment of surface detection radar are critical mitigation strategies to prevent future occurrences.
Freshal Fitran, Elfi Amir, Rany Adiliawijaya et al.· International Journal of Hea...· 0 citations
The ongoing advancement of cockpit automation and the increasing shortage of qualified pilots have intensified discussions on Reduced Crew Operations (RCO) in commercial aviation. RCO comprises two main concepts: Extended Minimum Crew Operations (eMCO), which temporarily reduce cockpit crew during cruise, and Single Pilot Operations (SiPO), which envisage a single pilot on board throughout the entire flight. While technological progress suggests growing feasibility, pilot acceptance remains a critical human factors challenge.This paper investigates pilot acceptance of RCO from a human factors perspective, with a particular focus on trust in automation, perceived safety, and job-related concerns. An empirical mixed-methods study was conducted using an online survey among active, former, and prospective commercial pilots. Quantitative data were analyzed using descriptive and inferential statistical methods, while qualitative responses were examined through structured content analysis. The results indicate an overall low level of acceptance toward RCO, with particularly strong rejection of SiPO. Safety concerns, increased workload, and the perceived irreplaceability of a second pilot were identified as dominant barriers. Acceptance of eMCO was moderately higher but strongly conditional on reliable automation, transparent system behavior, and robust organizational safeguards. Statistical analyses reveal a significant positive relationship between trust in automation and acceptance of RCO, as well as a significant negative relationship between age and acceptance. Other factors, including flight experience, professional position, aviation sector, and perceived job insecurity, showed no significant effects. The findings highlight pilot acceptance as a decisive prerequisite for the implementation of RCO concepts and emphasize the importance of human-centered automation design, trust calibration, and transparent safety strategies in future cockpit systems.
Melanie Kranich, Sumona Sen, Patrick Poetters· AHFE International· 0 citations
