Fundamental attribution error

The study of patient safety is the study of complexity. The study of complexity invites us to understand key concepts that can be applied to patient safety. Basic concepts from the fleld of patient safety are sharp and blunt end active and latent failure the Swiss Cheese Model of Accident Causation slips, lapses, and mistakes and hindsight bias and the fundamental attribution error. Key concepts from organizational analysis, such as normalization of deviance, diffusion of responsibility, tightly coupled work processes, and sensemaking, introduce practical lessons from high-reliability organizations. Application of specific lessons to health care are explored in Chapter Five. 

Fundamental attribution error is the pervasive human tendency to attribute bad outcomes to an actor s personal inadequacies (dispositional causes) rather than attributing them to situational factors beyond his or her control (situational causes), such as role or context (Fiske and Taylor, 1984). The following case study describes... 

Several well-verified strategies help us escape fundamental attribution error. 

Several well-verified strategies help us escape fundamental attribution error. Perh s the simplest is just to understand the pervasiveness of the bias, and to always look first and foremost for the situational factors that may be influencing behavior. 

Social psychologists have discovered di fundamental attribution error when systematically studying how people explain the behavior of others (Ross, 1977 Ross et al., 1977). When... 

The work culture, including policies, paradigms, and personnel, can have a dramatic impact on whether victims of near hits, injuries, or other adversities experience stress or distress. The fundamental attribution error, where we overestimate personal factors to explain others behavior ("Judy broke the handle because she was tired, stressed out, and careless"), can provoke distress and pinpoint the very aspects of an incident most difficult to define and control. 

In general, people tend to explain accidents that other people have been involved in by referring to their stable personal characteristics. This corresponds to the third quadrant in Figure 6.7. However, people explain accidents that they themselves have been involved in by referring to transient external causes, i.e. the second quadrant. This so-called fundamental attribution error has great implications for the routines for accident investigations. 

Lame and Defize [334] showed that the fundamental sampling error for soil only affects the analytical variance when sample sizes are less than 10 g [335]. For larger samples, the variance is determined by the segregation error. A sampling board method for estimation of the segregation error was described. Skalski and Ward [335] showed that a two-way compositing strategy could be used to attribute detected contamination in composited samples directly to constituent samples without further analyses. 

The HPI principles along with an understanding of human error precursors can be used to enhance the development of the JHA process. If a fundamental attribute of humans is that they can make mistakes and make wrong decisions then it becomes important to ensure that job requirements... 

I see the error of attribution of causation concerning psychedelics as representative of the same error on the larger scale of the whole question of mind-brain relationships, in most current models of consciousness, of which there recently have been many, there seems to me a fundamental ignorance of the logical repercussions of saying, for instance, that the mind, or consciousness, must be caused by the brain. John Searle, the author of one of the more cautious and measured treatises on consciousness... 

At the same time, examples where the GB model breaks down are also well known. Part of the overall error in these cases is attributable to the PB GB approximation, while the remainder comes from the more fundamental limitations of the general implicit solvent framework itself. These examples are extremely important for defining the current boundaries of applicability of the GB model they also suggest directions for future improvements. 

The need for size-consistency is an illustration of a fundamental difficulty of the supermolecule method. For a single system the variation principle ensures that the better the calculation, the better the energy. When we are interested in energy differences, however, the variational principle does not apply. In fact, there is a very serious source of error that can be attributed to the variational principle itself. 

To apply a significance test, a hypothesis must be clearly stated and must have a quantity with a calculated probability associated with it. This is the fundamental difference between a hunch and a hypothesis test—a quantity and a probability. The hypothesis will be accepted or rejected on the basis of a com-oarison of the calculated quantity with a table of values relating to a normal istribution. As with the confidence interval, the analyst selects an associated e/el of certainty, typically 95%. The starting hypothesis takes the form of the null hypothesis Hq. "Null" means "none," and the null hypothesis is stated in such a way as to say that there is no difference between the calculated quantity and the expected quantity, save that attributable to normal random error. As regards to the outlier in question, the null hypothesis for the chemist and the trainee states that the 11.0% value is not an outlier and that any difference... 

---