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Objective: To better understand how human error contributes to U.S. Navy diving accidents.Background: An analysis of 263 U.S. Navy diving accident and mishap reports revealed that the human factors classifications were not informative for further analysis, and 70% of mishaps were attributed to unknown causes; only 23% were attributed to human factors.Method: Five diving fatality reports were examined using the consensual qualitative research (CQR) method to develop a taxonomy of six categories and 21 subcategories for classifying human errors in diving. In addition, 15 critical incident technique (CIT) interviews were conducted with U.S. Navy divers who had been involved in a diving accident or near miss and analyzed using the dive team error taxonomy.Results: Overall, failures in situation awareness and leadership were the most common human errors made by the dive team.Conclusion: The dive team human error taxonomy could aid in accident investigation and in the training and evaluation of U.S. Navy divers.Application: The development of the dive team human error taxonomy has generated a number of considerations that researchers should take into account when developing, or adapting, an error taxonomy from one industry to another. [ABSTRACT FROM AUTHOR]

Introduction: There are a variety of qualitative and quantitative tools for measuring safety climate. However, questionnaires are by far the most commonly used methodology., Method: This paper reports the descriptive analysis of a large sample of safety climate survey data (n=110,014) collected over 10 years from U.S. Naval aircrew using the Command Safety Assessment Survey (CSAS)., Results: The analysis demonstrated that there was substantial non-random response bias associated with the data (the reverse worded items had a unique pattern of responses, there was a increasing tendency over time to only provide a modal response, the responses to the same item towards the beginning and end of the questionnaire did not correlate as highly as might be expected, and the faster the questionnaire was completed the higher the frequency of modal responses). It is suggested that the non-random responses bias was due to the negative effect on participant motivation of a number of factors (questionnaire design, lack of a belief in the importance of the response, participant fatigue, and questionnaire administration)., Conclusions: Researchers must consider the factors that increase the likelihood of non-random measurement error in safety climate survey data and cease to rely on data that are solely collected using a long and complex questionnaire., Impact on Industry: In the absence of valid and reliable data it will not be possible for organizations to take the measures required to improve safety climate., (Copyright © 2011 Elsevier B.V. All rights reserved.)