The wrong Wright stuff : mapping human error in aviation

The Aviation Safety Reporting System (ASRS) was instituted to aid the Federal Aviation Administration in tracking trends in aviation incidents so that, ultimately, safety measures and training could be implemented to decrease the occurrence of accidents and incidents within the industry. The current system relies on hand coding of reports to recognize current trends and alert the proper parties. Although the filing party may enter some codified data describing the surrounding scenario (e.g., time of day, weather), there is no opportunity to specify a category if the problem is human error. Considering the prevalence of human error within these incidents (around 55% based on a report by Boeing, 2006), a greater understanding of the driving factors is needed. The current study was an investigation of the human error components of airline incident reports. Text analysis tools were applied to ASRS incident narrative reports to determine a classification based on human performance for commercial and general aviation. The results from the current study demonstrate that an empirically based approach can be used to uncover latent categories within the Flight Crew Human Performance\u27 classified reports. The combined approach of latent semantic analysis, k-means clustering, and keyword analysis were used successfully in developing a nine element classification of commercial aviation reports and twelve element classification of general aviation reports. The taxonomies suggested by the current study for both commercial and general aviation reveal categories beyond just human error elements. The classification scheme suggested for the commercial aviation reports most closely resembled the ACCERS taxonomy developed by Krokos and Baker (2005; see also Baker & Krokos, 2007), which was constructed to help in categorizing all incident reports. The classification suggested for general aviation reports did not closely resemble any existing classification scheme. Although the suggested taxonomy shared categories such as situational awareness and communication with classifications such as crew resource management (CRM) or single pilot resource management (SRM), the current classification also holds non-human elements such as weather and context. The taxonomies for both commercial and general aviation revealed a category for context, and the difficulty of flying into certain airports was apparent. These findings can be implemented to improve training programs by assisting in the creation of contextually based training scenarios. Furthermore, based on findings for general aviation in particular, pilots could benefit from increased training in situational awareness and monitoring of notices and airspace

Exploring the lived experience of Graves’ Disease and its impact on health-related quality of life

The current thesis aimed to explore the impact of Graves’ Disease using a mixed methods approach. First, the impact of GD on an individual’s Health-related quality of life (HRQoL) was assessed through a meta-analysis comparing HRQoL in individuals with Graves’ Disease to healthy subjects. These findings were supplemented by exploring the subjective lived experience of GD through further qualitative scrutiny. Literature review and meta-analysis A systematic literature review and meta-analysis was carried out to assess the impact of Graves’ Disease on HRQoL, as assessed by the Short Form-36 (SF-36), a prominent tool used within clinical and health research. Eight studies were included in a random-effects model of meta-analysis where scores for Graves’ Disease groups were compared to that of healthy subjects, revealing significantly lower scores in the Graves’ Disease group. This indicated a significant impact of Graves’ Disease on the Physical and Mental Components of Health-related quality of life. Empirical research report A qualitative approach using semi-structured interviews was utilised to permit a nuanced and open exploration of the experience of Graves’ Disease prior to, and following diagnosis. Seven women recruited through online Graves’ Disease support platforms took part in interviews, which were analysed using an Interpretative Phenomenological Approach. Two superordinate themes, emerged. The first theme: The oddity of experience, highlighted Graves’ Disease symptoms as a divergence from the ‘norm’ where disparate, unrelated symptoms and conflicting diagnostic narratives disrupted women’s attempts to make sense of what was happening. The second theme: collateral damage captured women’s sense of powerlessness and dread as they grew to understand Graves’ Disease as a chronic, incurable condition, affecting their physical appearance, management of self-image and personal relationships.</p

Bridging Human Reliability Analysis and Psychology, Part 2: A Cognitive Framework to Support HRA

This is the second of two papers that discuss the literature review conducted as part of the U.S. Nuclear Regulatory Commission (NRC) effort to develop a hybrid human reliability analysis (HRA) method in response to Staff Requirements Memorandum (SRM) SRM-M061020. This review was conducted with the goal of strengthening the technical basis within psychology, cognitive science and human factors for the hybrid HRA method being proposed. An overview of the literature review approach and high-level structure is provided in the first paper, whereas this paper presents the results of the review. The psychological literature review encompassed research spanning the entirety of human cognition and performance, and consequently produced an extensive list of psychological processes, mechanisms, and factors that contribute to human performance. To make sense of this large amount of information, the results of the literature review were organized into a cognitive framework that identifies causes of failure of macrocognition in humans, and connects those proximate causes to psychological mechanisms and performance influencing factors (PIFs) that can lead to the failure. This cognitive framework can serve as a tool to inform HRA. Beyond this, however, the cognitive framework has the potential to also support addressing human performance issues identified in Human Factors applications

SANDIA REPORT Issues in Benchmarking Human Reliability Analysis Methods: A Literature Review Issues in Benchmarking Human Reliability Analysis Methods: A Literature Review

ABSTRACT There is a diversity of human reliability analysis (HRA) methods available for use in assessing human performance within probabilistic risk assessment (PRA). Due to the significant differences in the methods, including the scope, approach, and underlying models, there is a need for an empirical comparison investigating the validity and reliability of the methods. To accomplish this empirical comparison, a benchmarking study is currently underway that compares HRA methods with each other and against operator performance in simulator studies. In order to account for as many effects as possible in the construction of this benchmarking study, a literature review was conducted, reviewing past benchmarking studies in the areas of psychology and risk assessment. A number of lessons learned through these studies are presented in order to aid in the design of future HRA benchmarking endeavors.

Development of a statistically based access delay timeline methodology.

The charter for adversarial delay is to hinder access to critical resources through the use of physical systems increasing an adversary's task time. The traditional method for characterizing access delay has been a simple model focused on accumulating times required to complete each task with little regard to uncertainty, complexity, or decreased efficiency associated with multiple sequential tasks or stress. The delay associated with any given barrier or path is further discounted to worst-case, and often unrealistic, times based on a high-level adversary, resulting in a highly conservative calculation of total delay. This leads to delay systems that require significant funding and personnel resources in order to defend against the assumed threat, which for many sites and applications becomes cost prohibitive. A new methodology has been developed that considers the uncertainties inherent in the problem to develop a realistic timeline distribution for a given adversary path. This new methodology incorporates advanced Bayesian statistical theory and methodologies, taking into account small sample size, expert judgment, human factors and threat uncertainty. The result is an algorithm that can calculate a probability distribution function of delay times directly related to system risk. Through further analysis, the access delay analyst or end user can use the results in making informed decisions while weighing benefits against risks, ultimately resulting in greater system effectiveness with lower cost