The Driver Behaviour Questionnaire as accident predictor: A methodological re-meta-analysis

Problem The Manchester Driver Behaviour Questionnaire (DBQ) is the most commonly used self-report tool in traffic safety research and applied settings. It has been claimed that the violation factor of this instrument predicts accident involvement, which was supported by a previous meta-analysis. However, that analysis did not test for methodological effects, or include contacting researchers to obtain unpublished results. Method The present study re-analysed studies on prediction of accident involvement from DBQ factors, including lapses, and many unpublished effects. Tests of various types of dissemination bias and common method variance were undertaken. Results Outlier analysis showed that some effects were probably not reliable data, but excluding them did not change the results. For correlations between violations and crashes, tendencies for published effects to be larger than unpublished ones and for effects to decrease over time were observed, but were not significant. Also, analysis using the proxy of the mean of accidents in studies indicated that studies where effects for violations are unknown have smaller effect sizes. These differences indicate dissemination bias. Studies using self-reported accidents as dependent variables had much larger effects than those using recorded accident data. Also, zero-order correlations were larger than partial correlations that controlled for exposure. Similarly, violations/accidents effects were strong only when there was also a strong correlation between accidents and exposure. Overall, the true effect is probably very close to zero (r<.07) for violations versus traffic accident involvement, depending upon which systematic tendencies in the data are controlled for. Conclusions: Methodological factors and dissemination bias have inflated the mean effect size of the DBQ in the published literature. Strong evidence of various artefactual effects is apparent. Practical Applications A greater level of care should be taken if the DBQ continues to be used in traffic safety research. Also, validation of self-reports should be more comprehensive in the future, taking into account the possibility of common method variance.

The Victorian 260 cc Legislation. Evaluation Report Using Accident Data to December, 1982.

Learner and first year probationary motorcyclists are over-represented in traffic accidents, being involved about four times as often as full motorcycle licence holders in relation to their numbers. In an attempt to reduce this over-involvement, the Victorian Government amended the law in 1979 to restrict learner and first year probationary motorcyclists to motorcycles with engine capacities of less than 260 cc. This paper reports an evaluation which showed that casualty rates for learner and first year probationers began to decrease from mid 1979 and continued to do so until the end of 1980. A further analysis indicated that compared to full licence holder casualties, learner permit casualties were about 40% less than expected while first year probationary casualties were about 39% lower.

The Nature, Origins, and Consequences of Finnish Shame-Proneness: A Grounded Theory Study

Although shame is a universal human emotion and is one of the most difficult emotions to overcome, its origins and nature as well as its effects on psychosocial functioning are not well understood or defined. While psychological and spiritual counselors are aware of the effects and consequences of shame for an individual s internal well-being and social life, shame is often still considered a taboo topic and is not given adequate attention. This study aims to explain the developmental process and effects of shame and shame-proneness for individuals and provide tools for practitioners to work more effectively with their clients who struggle with shame. This study presents the empirical foundation for a grounded theory that describes and explains the nature, origins, and consequences of shame-proneness. The study focused on Finnish participants childhood, adolescence and adulthood experiences and why they developed shame-proneness, what it meant for them as children and adolescents and what it meant for them as adults. The data collection phase of this study began in 2000. The participants were recruited through advertisements in local and country-wide newspapers and magazines. Altogether 325 people responded to the advertisements by sending an essay concerning their shame and guilt experiences. For the present study, 135 essays were selected and from those who sent an essay 19 were selected for in-depth interviews. In addition to essays and interviews, participants personal notebooks and childhood hospital and medical reports as well as their scores on the Internalized Shame Scale were analyzed. The development of shame-proneness and significant experiences and events during childhood and adolescence (e.g., health, parenting and parents behavior, humiliation, bullying, neglect, maltreatment and abuse) are discussed and the connections of shame-proneness to psychological concepts such as self-esteem, attachment, perfectionism, narcissism, submissiveness, pleasing others, heightened interpersonal subjectivity, and codependence are explained. Relationships and effects of shame-proneness on guilt, spirituality, temperament, coping strategies, defenses, personality formation and psychological health are also explicated. In addition, shame expressions and the development of shame triggers as well as internalized and externalized shame are clarified. These connections and developments are represented by the core category lack of gaining love, validation and protection as the authentic self. The conclusions drawn from the study include a categorization of shame-prone Finnish people according to their childhood and adolescent experiences and the characteristics of their shame-proneness and personality. Implications for psychological and spiritual counseling are also discussed. Key words: shame, internalized shame, external shame, shame development, shame triggers, guilt, self-esteem, attachment, narcissism, perfectionism, submissiveness, codependence, childhood neglect, childhood abuse, childhood maltreatment, emotional abuse, sexual abuse, spiritual abuse, psychological well-being

安全驾驶性向测验研究

The research is concerned with three aspects: (1) The influence of the drivers' personal conditions on the drivers' accident rates. (2) The influence of the drivers' abilities and personalities on the drivers' accident rates. (3) The difference between the accident drivers and the no-accident drivers. Through the investigation, we get the following conclusion: (1) The proneness of drivers exists exactly. (2) There is significant difference between the accident-group and the no-accident group in their abilities and personalities. The results proves that the reliability and validity of the whole test is good.

The airEXODUS evacuation model and its application to evacuation certification, crew training and accident investigation.

Computer based mathematical models describing the aircraft evacuation process have a vital role to play in the design and development of safer aircraft, in the implementation of safer and more rigorous certification criteria, cabin crew training and in post mortuum accident investigation. As the risk of personal injury and costs involved in performing large-scale evacuation experiments for the next generation 'Ultra High Capacity Aircraft' (UHCA) are expected to be high, the development and use of these evacuation modelling tools may become essential if these aircraft are to prove a viable reality. In this paper the capabilities and limitations of the airEXODUS evacuation model are described. Its successful application to the prediction of a recent certification trial, prior to the actual trial taking place, is described. Also described is a newly defined parameter known as OPS which can be used as a measure of evacuation trial optimality. In addition, sample evacuation simulations in the presence of fire atmospheres are described. Finally, the data requiremnets of the airEXODUS evacuation model is discussed along with several projects currently underway at the the Univesity of Greenwich designed to obtain this data. Included in this discussion is a description of the AASK - Aircraft Accident Statistics and Knowledge - data base which contains detailed information from aircraft accident survivors.

AASK - Aircraft accident statistics and knowledge: A database of human experience in evacuation, derived from aviation accident reports

Computer based mathematical models describing the aircraft evacuation process have a vital role to play in aviation safety. However such models have a heavy dependency on real evacuation data in order to (a) identify the key processes and factors associated with evacuation, (b) quantify variables and parameters associated with the identified factors/processes and finally (c) validate the models. The Fire Safety Engineering Group of the University of Greenwich is undertaking a large data extraction exercise from three major data sources in order to address these issues. This paper describes the extraction and application of data from one of these sources - aviation accident reports. To aid in the storage and analysis of the raw data, a computer database known as AASK (aircraft accident statistics and knowledge) is under development. AASK is being developed to store human observational and anecdotal data contained in accident reports and interview transcripts. AASK comprises four component sub-databases. These consist of the ACCIDENT (crash details), FLIGHT ATTENDANT (observations and actions of the flight attendants), FATALS (details concerning passenger fatalities) and PAX (observations and accounts from individual passengers) databases. AASK currently contains information from 25 survivable aviation accidents covering the period 4 April 1977 to 6 August 1995, involving some 2415 passengers, 2210 survivors, 205 fatalities and accounts from 669 people. In addition to aiding the development of aircraft evacuation models, AASK is also being used to challenge some of the myths which proliferate in the aviation safety industry such as, passenger exit selection during evacuation, nature and frequency of seat jumping, speed of passenger response and group dynamics. AASK can also be used to aid in the development of a more comprehensive approach to conducting post accident interviews, and will eventually be used to store the data directly.

An aircraft accident database of human experience in evacuation derived from aviation accident reports

Computer based mathematical models describing the aircraft evacuation process have a vital role to play in aviation safety. However, such models have a heavy dependency on real evacuation data. The Fire Safety Engineering Group of the University of Greenwich is undertaking a large data extraction exercise in order to address this issue. This paper describes the extraction and application of data from aviation accident reports. To aid in the storage and analysis of the raw data, a computer database known as AASK (Aircraft Accident Statistics and Knowledge) is under development. AASK is being developed to store human observational and anecdotal data contained in accident reports and interview transcripts. AASK currently contains information from 25 survivable aviation accidents covering the period 04/04/77 to 06/08/95, involving some 2415 passengers, 2210 survivors, 205 fatalities and accounts from 669 people. Copyright © 1999 John Wiley & Sons, Ltd.

The AASK database V4.0: aircraft accident statistics and knowledge. A database to record human experience of evacuation in aviation accidents

This paper describes the AASK database. The AASK database is unique as it is a record of human behaviour during survivable aviation accidents. The AASK database is compiled from interview data compiled by agencies such as the NTSB and the AAIB. The database can be found on the website http://fseg.gre.ac.uk

Aircraft accident statistics and knowledge database: analyzing passenger behavior in aviation accidents

The Aircraft Accident Statistics and Knowledge (AASK) database is a repository of passenger accounts from survivable aviation accidents/incidents compiled from interview data collected by agencies such as the US NTSB. Its main purpose is to store observational and anecdotal data from the actual interviews of the occupants involved in aircraft accidents. The database has wide application to aviation safety analysis, being a source of factual data regarding the evacuation process. It also plays a significant role in the development of the airEXODUS aircraft evacuation model, where insight into how people actually behave during evacuation from survivable aircraft crashes is required. This paper describes the latest version of the database (Version 4.0) and includes some analysis of passenger behavior during actual accidents/incidents.

CAA paper 2006/01: a database to record human experience of evacuation in aviation accidents: the aircraft accident statistics and knowledge database (AASK)

This report concerns the development of the AASK V4.0 database (CAA Project 560/SRG/R+AD). AASK is the Aircraft Accident Statistics and Knowledge database, which is a repository of survivor accounts from aviation accidents. Its main purpose is to store observational and anecdotal data from interviews of the occupants involved in aircraft accidents. The AASK database has wide application to aviation safety analysis, being a source of factual data regarding the evacuation process. It is also key to the development of aircraft evacuation models such as airEXODUS, where insight into how people actually behave during evacuation from survivable aircraft crashes is required. With support from the UK CAA (Project 277/SRG/R&AD), AASK V3.0 was developed. This was an on-line prototype system available over the internet to selected users and included a significantly increased number of passenger accounts compared with earlier versions, the introduction of cabin crew accounts, the introduction of fatality information and improved functionality through the seat plan viewer utility. The most recently completed AASK project (Project 560/SRG/R+AD) involved four main components: a) analysis of the data collected in V3.0; b) continued collection and entry of data into AASK; c) maintenance and functional development of the AASK database; and d) user feedback survey. All four components have been pursued and completed in this two-year project. The current version developed in the last year of the project is referred to as AASK V4.0. This report provides summaries of the work done and the results obtained in relation to the project deliverables.