Unsafe acts and unsafe outcomes in aircraft maintenance

Road safety studies using the Driver Behaviour Questionnaire (DBQ) have provided support for a three-way distinction between violations, skill-based errors and mistakes, and have indicated that a tendency to commit driving violations is associated with an increased risk of accident involvement. The aims of this study were to examine whether the three-way distinction of unsafe acts is applicable in the context of aircraft maintenance, and whether involvement in maintenance safety occurrences can be predicted on the basis of self-reported unsafe acts. A Maintenance Behaviour Questionnaire (MBQ) was developed to explore patterns of unsafe acts committed by aircraft maintenance mechanics. The MBQ was completed anonymously by over 1300 Australian aviation mechanics, who also provided information on their involvement in workplace accidents and incidents. Four factors were identified: routine violations, skill-based errors, mistakes and exceptional violations. Violations and mistakes were related significantly to the occurrence of incidents that jeopardized the quality of aircraft maintenance, but were not related to workplace injuries. Skill-based errors, while not related to work quality incidents, were related to workplace injuries. The results are consistent with the three-way typology of unsafe acts described by Reason et al. (1990) and with the DBQ research indicating an association between self-reported violations and accidents. The current findings suggest that interventions addressed at maintenance quality incidents should take into account the role of violations and mistakes, and the factors that promote them. In contrast, interventions directed at reducing workplace injury are likely to require a focus on skill-based errors.     

A quarter of a century of the DBQ: some supplementary notes on its validity with regard to accidents

This article synthesises the latest information on the relationship between the Driver Behaviour Questionnaire (DBQ) and accidents. We show by means of computer simulation that correlations with accidents are necessarily small because accidents are rare events. An updated meta-analysis on the zero-order correlations between the DBQ and self-reported accidents yielded an overall r of .13 (fixed-effect and random-effects models) for violations (57,480 participants; 67 samples) and .09 (fixed-effect and random-effects models) for errors (66,028 participants; 56 samples). An analysis of a previously published DBQ dataset (975 participants) showed that by aggregating across four measurement occasions, the correlation coefficient with self-reported accidents increased from .14 to .24 for violations and from .11 to .19 for errors. Our meta-analysis also showed that DBQ violations (r = .24; 6353 participants; 20 samples) but not DBQ errors (r = ? .08; 1086 participants; 16 samples) correlated with recorded vehicle speed.

Practitioner Summary: The DBQ is probably the most widely used self-report questionnaire in driver behaviour research. This study shows that DBQ violations and errors correlate moderately with self-reported traffic accidents.     

Using Neural Networks to predict HFACS unsafe acts from the pre-conditions of unsafe acts

Abstract

Human Factors Analysis and Classification System (HFACS) is based upon Reason’s organizational model of human error which suggests that there is a ‘one to many’ mapping of condition tokens (HFACS level 2 psychological precursors) to unsafe act tokens (HFACS level 1 error and violations). Using accident data derived from 523 military aircraft accidents, the relationship between HFACS level 2 preconditions and level 1 unsafe acts was modelled using an artificial neural network (NN). This allowed an empirical model to be developed congruent with the underlying theory of HFACS. The NN solution produced an average overall classification rate of ca. 74% for all unsafe acts from information derived from their level 2 preconditions. However, the correct classification rate was superior for decision- and skill-based errors, than for perceptual errors and violations.

Practitioner Summary: A model to predict unsafe acts (HFACS level 1) from their preconditions (HFACS level 2) was developed from the analysis of 523 military aircraft accidents using an artificial NN. The results could correctly predict approximately 74% of errors.     

Interpersonal violations,speeding violations and their relation to accident involvement in Finland

The aim of the present study was to replicate the distinction between errors, lapses and violations, and to identify aggressive violations from normal or highway code violations. Furthermore, the relationship of these behaviours with road traffic accidents was examined. A total number of 1126 Finnish drivers completed a questionnaire containing the Driver Behaviour Questionnaire (DBQ) with extended violations scale, and questions regarding background information, such as age, gender and mileage. Also, questions about previous accidents and fines were asked. Factor analysis showed that a four-factor structure seemed more appropriate than the earlier established three-factor structure. The four factors were errors, lapses, speeding violations and interpersonal violations. The two types of violations result from different motives, and seem to be associated with different kinds of affect. Both interpersonal and speeding violations were reported most by young males, which was consistent with earlier findings. Logistic regression analyses indicated that errors predicted active accident involvement after partialling out the effects of demographic variables, whereas interpersonal violations were positively related to involvement in passive accidents. This was presumably due to different reporting tendencies of respondents. Speeding tickets were predicted by speeding and interpersonal violations and lapses and penalties for speeding by both kinds of violations and errors. Penalties for speeding, parking and other offences were predicted by interpersonal violations. The implications of these results are discussed.     

Interpersonal violations,speeding violations and their relation to accident involvement in Finland

The aim of the present study was to replicate the distinction between errors, lapses and violations, and to identify aggressive violations from normal or highway code violations. Furthermore, the relationship of these behaviours with road traffic accidents was examined. A total number of 1126 Finnish drivers completed a questionnaire containing the Driver Behaviour Questionnaire (DBQ) with extended violations scale, and questions regarding background information, such as age, gender and mileage. Also, questions about previous accidents and fines were asked. Factor analysis showed that a four-factor structure seemed more appropriate than the earlier established three-factor structure. The four factors were errors, lapses, speeding violations and interpersonal violations. The two types of violations result from different motives, and seem to be associated with different kinds of affect. Both interpersonal and speeding violations were reported most by young males, which was consistent with earlier findings. Logistic regression analyses indicated that errors predicted active accident involvement after partialling out the effects of demographic variables, whereas interpersonal violations were positively related to involvement in passive accidents. This was presumably due to different reporting tendencies of respondents. Speeding tickets were predicted by speeding and interpersonal violations and lapses and penalties for speeding by both kinds of violations and errors. Penalties for speeding, parking and other offences were predicted by interpersonal violations. The implications of these results are discussed.     

Errors and violations on the roads: a real distinction?

In considering the human contribution to accidents, it seems necessary to make a distinction between errors and violations; two forms of aberration which may have different psychological origins and demand different modes of remediation. The present study investigated whether this distinction was justified for self-reported driver behaviour. Five hundred and twenty drivers completed a driver behaviour questionnaire (DBQ) which asked them to judge the frequency with which they committed various types of errors and violations when driving. Three fairly robust factors were identified: violations, dangerous errors, and relatively harmless lapses, respectively. Violations declined with age, errors did not. Men of all ages reported more violations than women. Women, however, were significantly more prone to harmless lapses (or more honest) than men. These findings were consistent with the view that errors and violations are indeed mediated by different psychological mechanisms. Violations require explanation in terms of social and motivational factors, whereas errors (slips, lapses, and mistakes) may be accounted for by reference to the information-processing characteristics of the individual.     

Associations between errors and contributing factors in aircraft maintenance

In recent years cognitive error models have provided insights into the unsafe acts that lead to many accidents in safety-critical environments. Most models of accident causation are based on the notion that human errors occur in the context of contributing factors. However, there is a lack of published information on possible links between specific errors and contributing factors. A total of 619 safety occurrences involving aircraft maintenance were reported using a self-completed questionnaire. Of these occurrences, 96% were related to the actions of maintenance personnel. The types of errors that were involved, and the contributing factors associated with those actions, were determined. Each type of error was associated with a particular set of contributing factors and with specific occurrence outcomes. Among the associations were links between memory lapses and fatigue and between rule violations and time pressure. Potential applications of this research include assisting with the design of accident prevention strategies, the estimation of human error probabilities, and the monitoring of organizational safety performance.     

Skills,rules and knowledge in aircraft maintenance: errors in context

Automatic or skill-based behaviour is generally considered to be less prone to error than behaviour directed by conscious control. However, researchers who have applied Rasmussen's skill-rule-knowledge human error framework to accidents and incidents have sometimes found that skill-based errors appear in significant numbers. It is proposed that this is largely a reflection of the opportunities for error which workplaces present and does not indicate that skill-based behaviour is intrinsically unreliable. In the current study, 99 errors reported by 72 aircraft mechanics were examined in the light of a task analysis based on observations of the work of 25 aircraft mechanics. The task analysis identified the opportunities for error presented at various stages of maintenance work packages and by the job as a whole. Once the frequency of each error type was normalized in terms of the opportunities for error, it became apparent that skill-based performance is more reliable than rule-based performance, which is in turn more reliable than knowledge-based performance. The results reinforce the belief that industrial safety interventions designed to reduce errors would best be directed at those aspects of jobs that involve rule- and knowledge-based performance.     

Skills,rules and knowledge in aircraft maintenance: errors in context

Automatic or skill-based behaviour is generally considered to be less prone to error than behaviour directed by conscious control. However, researchers who have applied Rasmussen's skill-rule-knowledge human error framework to accidents and incidents have sometimes found that skill-based errors appear in significant numbers. It is proposed that this is largely a reflection of the opportunities for error which workplaces present and does not indicate that skill-based behaviour is intrinsically unreliable. In the current study, 99 errors reported by 72 aircraft mechanics were examined in the light of a task analysis based on observations of the work of 25 aircraft mechanics. The task analysis identified the opportunities for error presented at various stages of maintenance work packages and by the job as a whole. Once the frequency of each error type was normalized in terms of the opportunities for error, it became apparent that skill-based performance is more reliable than rule-based performance, which is in turn more reliable than knowledge-based performance. The results reinforce the belief that industrial safety interventions designed to reduce errors would best be directed at those aspects of jobs that involve rule- and knowledge-based performance.     

Aberrant driving behaviour: errors and violations

The present study was a replication of the research of Reason et al. (1990). Its aim was to confirm the distinction between driving errors and violations in a Western Australian driving population. Sixty-one male drivers and 74 female drivers completed a questionnaire containing items on driver demographics, driving penalties incurred, driving convictions and accident history and driver behavioural aberrations drawn from the Driver Behaviour Questionnaire (DBQ). In agreement with Reason et al. factor analysis revealed three factors; in the present study these were general errors, dangerous errors, and dangerous violations. Young drivers committed more dangerous errors and dangerous violations than older drivers. Females reported more dangerous errors than males. Males reported more dangerous violations than females. Drivers who reported a high level of road exposure and those who reported having been convicted for speeding reported more dangerous violations. Differences in the results of the two studies can largely by accounted for by differences in the representation of age and gender in the two populations studied.     

Evaluating the mechanical injury problem in the wood-bamboo furniture manufacturing industry

This paper introduces the method and procedure of evaluating mechanical injury problems in the wood-bamboo furniture manufacturing industry in Taiwan. Epidemiological surveillance and scenario analyses were performed on 1695 workplace-related accidents to identify the general problem areas. Subsequently, on site investigations were conducted in 15 factories to determine the specific contributing factors of the two major hazard patterns in that industry: caught in/between as well as cut and laceration accidents. For the primary cause of the accidents, approximately 60% of the incidents were due to unsafe conditions, and approximately 40% of the incidents were attributed to unsafe acts. Two intervention measures are proposed to reduce the potential hazards resulting from unsafe conditions and unsafe acts.     

Application of HFACS and grounded theory for identifying risk factors of air traffic controllers’ unsafe acts

Unsafe acts of air traffic controllers (ATCers) are caused by various factors. Based on interview data and case reports, human factors analysis and classification system (HFACS) and the grounded theory were adopted to identify the risk factors of ATCers’ unsafe acts comprehensively. The interview data and the case data issued by the authority were first collected. Then, the above data were encoded to obtain the relevant concepts and categories based on the grounded theory, and the HFACS model is used to classify the concepts and categories. Finally, the relationship between the core category and the secondary category was sorted out in the way of storyline. The results show that the risk factors include environmental factors, organizational influences, unsafe supervision and controllers’ states, and the unsafe acts manifest as errors and violations. Among them, the controllers’ states are intermediate variable, and other factors indirectly affect the controllers’ unsafe acts. The first three risk factors with high frequency in unsafe incidents are technical environment, mental states and business ability. The three most common unsafe acts are giving the wrong order, insufficient situational awareness, and poor work order on-site. Through combining HFACS framework and grounded theory to analyze data, a more clear and comprehensive conceptual model of risk factors of ATCers’ unsafe acts can be obtained.     

Patient safety during medication administration: the influence of organizational and individual variables on unsafe work practices and medication errors

Medication errors are a leading cause of unintended harm to patients, both in Australia and internationally, and there is now a concerted attempt to identify and correct individual and workplace factors that encourage medication errors. The current study used structural equation modelling to measure organizational climate and to test a model with hypothesized links between climate and unsafe medication administration behaviours. The study also examined the possible mediating role of stress and morale. Data were collected from 176 nurses working in rural areas in Australia. The model provided a reasonable fit to the data with organizational climate accounting for 39% of the variance in individual distress, which in turn explained 7% of the variance in self-reported violations. The only variable that made a direct contribution to errors was violations, which accounted for 24% of the variance in medication errors. These findings highlight the importance of monitoring the state of the whole health system. Deficiencies at the organizational level affect the psychological well-being of hospital employees, and distressed employees are more likely to engage in substandard work practices that ultimately endanger the patients under their care.     

Predicting unsafe behaviors at nuclear power plants: An integration of Theory of Planned Behavior and Technology Acceptance Model

Unsafe behaviors, including both errors and violations, have been identified as key contributors to accidents at nuclear power plants. However, the mechanisms behind such unsafe behaviors are not fully understood. This study aimed to investigate how workers' attitude and perception factors would predict errors and violations at nuclear power plants by proposing and validating an unsafe behavior model. The proposed model applied the Theory of Planned Behavior as the ground theoretical model and added factors from Technology Acceptance Model to capture workers’ perception of work regulations. To examine the validity of the proposed model, a total of 178 questionnaires were distributed at two nuclear power plants in China and 171 valid questionnaires were returned. The Structured Equation Modeling (SEM) analysis indicated that the proposed model fitted the data well. The results showed that perceived ease of use and perceived usefulness in following work regulations contributed to a positive attitude, which helped reduce the occurrence of both errors and violations. Moreover, errors were further affected by subjective norm while violations were not. Perceived behavior control was not a significant factor of either errors or violations.These findings suggest that to reduce errors and violations, policymakers should focus on methods to improve the perceived usefulness and perceived ease of use of work regulations, and promote a positive attitude towards safety.     

Psychological and physiological fatigue variation and fatigue factors in aircraft line maintenance crews

Aircraft maintenance is an integral component of an aviation system. 21% of all reported incidents in the Aviation Safety Reporting System (ASRS) are fatigue-related, and 18% of all accidents have maintenance factors involved. Guidelines for Maintenance Resource Management (MRM) are hence developed to combine human factors knowledge with interpersonal skills and personal maintenance skills in order to improve communication effectiveness and safety in aircraft maintenance operations. One of the identified human factors that lead to maintenance errors is fatigue. This paper examined the psychological and physiological fatigue variation in shift workers and the subjective factors affecting the fatigue of line maintenance crews. Questionnaires collected from two major airlines in Taiwan are used to investigate the underlying fatigue factors.     

The role of psychological factors in workplace safety

Workplace safety researchers and practitioners generally agree that it is necessary to understand the psychological factors that influence people's workplace safety behaviour. Yet, the search for reliable individual differences regarding psychological factors associated with workplace safety has lead to sparse results and inconclusive findings. The aim of this study was to investigate whether there are differences between the psychological factors, cognitive ability, personality and work-wellness of employees involved in workplace incidents and accidents and/or driver vehicle accidents and those who are not. The study population (N = 279) consisted of employees employed at an electricity supply organisation in South Africa. Mann–Whitney U-test and one-way ANOVA were conducted to determine the differences in the respective psychological factors between the groups. These results showed that cognitive ability did not seem to play a role in workplace incident/accident involvement, including driver vehicle accidents, while the wellness factors burnout and sense of coherence, as well as certain personality traits, namely conscientiousness, pragmatic and gregariousness play a statistically significant role in individuals' involvement in workplace incidents/accidents/driver vehicle accidents. Safety practitioners, managers and human resource specialists should take cognisance of the role of specifically work-wellness in workplace safety behaviour, as management can influence these negative states that are often caused by continuously stressful situations, and subsequently enhance work place safety.     

Workplace and organizational accident causation factors in the manufacturing industry

Labor inspectors investigate accidents to identify possible accident causes, initiate prosecution, and plan future accident prevention. The Method of Investigation for Labor Inspectors (MILI) was designed to help them to identify workplace and organizational factors in addition to immediate factors and legal breaches. The present study analyzes the impact of workplace (work design and provision of unsafe equipment) and organizational factors (training and employee involvement) on accident causation and validates MILI on real accident cases. Accident data from the manufacturing sector are analyzed with LISREL structural equation modeling. Results confirm the relationship between work design and training as well as between provision of unsafe equipment and employee involvement. The present study provides evidence that MILI is a structured accident investigation method allowing multiple accident causation factors to be revealed and that it could help all interested parts (not only labor inspectors, but companies as well) to thoroughly investigate occupational accidents. © 2009 Wiley Periodicals, Inc.     

A method for investigating human factor aspects of aircraft accidents and incidents

Approximately 70% of aircraft accidents and incidents have in the past been attributed to human error, and the importance of human error as a major contributory factor is now universally recognized. A satisfactory technique for the investigation of human error type accidents and incidents has not yet been standardized. This paper describes a comprehensive procedure which has been designed to assess human behaviour in instances of aircraft accidents and incidents. The aim of such a human factors investigation is to understand why the accident or incident occurred and so lead to a better understanding of human error, and as a result enhance flight safety.

The use of questionnaires and interviews to assess the subjective data available is discussed, and it is recommended that the most appropriate technique for the assessment of behavioural data is the use of an interview together with a check list. The importance of an early interview with all personnel associated with an accident or an incident by a human factors specialist trained in interviewing techniques is emphasized.

The check list described has been developed after reviewing the relevant literature and has been modified by personal experience derived from the investigation of Army aircraft accidents and incidents in which human factors have played an important part. The check list is based on a systems approach to understanding human error and includes such headings as ‘stress’ (including life events), ‘fatigue’, ‘arousal’ and ‘personality’. It is hoped that further improvements will be made to the check list to enable it to be used not only within the specific area of aircraft accidents and incidents, but also within the broader context of any accidents which may be attributed to human errors and as a result reduce the number of accidents and identify areas where further research may be useful.     

Helicopter maintenance error analysis: Beyond the third order of the HFACS-ME

In this paper a statistical analysis of a sample of 58 helicopter maintenance-induced safety occurrences is conducted to study helicopter accidents and incidents’ survivability and the severity distribution of such occurrences. Analysis is also carried out to identify helicopter main and sub-systems mostly exposed to maintenance errors and to determine various types of such errors. Expected inherent relations between rotorcraft components affected and types of associated maintenance errors are investigated. Human factors-based triggers of these accidents and severe incidents are explored. The concept of Specific Failures (SFs) that immediately precede each of such occurrences is introduced for more detailed representation of the last breached individual and organizational safety barriers. Root causes of these safety occurrences were then sought utilizing the Human Factors Analysis and Classification System-Maintenance Extension (HFACS-ME) taxonomy with a refined focus on its third order categories’ list. The rotorcraft characteristics influencing individuals and organizational behaviours within Maintenance, Repair and Overhaul organizations (MROs) are discussed in the light of the root cause investigation results.

Relevance to industry

The study of human reliability within helicopter maintenance industry is waited to emphasise the understanding of causes and propagation mechanisms of maintainers' errors and their consequences on the overall aviation safety. Previous works often investigated maintenance errors and their roles in promoting aviation accidents of fixed-wing aircraft; this research is investigating the case of rotorcraft.     

Driving errors,driving violations and accident involvement

Abstract

A survey of over 1600 drivers is reported, the results of which are consistent with those reported in an earlier study (Reason et al. 1990), which identified a three-fold typology of aberrant driving behaviours. The first type, lapses, are absent-minded behaviours with consequences mainly for the perpetrator, posing no threat to other road users. The second type, errors, are typically misjudgements and failures of observation that may be hazardous to others. The third type, violations, involve deliberate contraventions of safe driving practice. In the present study the survey instrument used, the Driver Behaviour Questionnaire, was also shown to be reliable over time. Each type of behaviour was found to have different demographic correlates. Most importantly, accident liability was predicted by self-reported tendency to commit violations, but not by tendency to make errors or to have lapses. The implications for road safety are discussed.