Causal or contributing factors

A generalised process model constitutes the backbone of our accident-analysis framework in Chapter 6. Process models help us in understanding how a production system gradually deteriorates from a normal state into a state where an accident occurs. Time is thus a basic factor. In contrast to causal-sequence models, process models make a clear distinction between the accident sequence on the one hand and the underlying causal or contributing factors on the other hand. 

The root cause, of incidents, refers to a variety of problem-solving methods that attempt to identify and correct a problem s root causes. It assumes that the best way to solve problems is by eliminating their root causes. It also works tmder the belief that addressing obvious symptoms, sometimes referred to as causal or contributing factors, only serves as a short-term solution and does not prevent the problan from happening again. 

In 1975, the Life Sciences Research Office of the Federation of American Societies for Experimental Biology (Carr et al. 1975), upon an extensive review of the available evidence, concluded that it was doubtful whether XO in homogenized cow s milk was a causal or risk factor for heart disease. More recently, Clifford et al (1983) and Deeth (1983), in critical reviews of the homogenized cow s milk XO hypothesis, have arrived at a similar, if not more definitive, conclusion. As stated by Clifford et al. (1983), experimental evidence has failed to substantiate, and in many cases has refuted, the hypothesis that homogenized bovine milk xanthine oxidase intake or plasmalogen depletion are causal factors in the development of atherosclerosis. And, according to Deeth (1983), there appears to be no unequivocal evidence that the absorbed enzyme has any pathological effects that may contribute to development of atherosclerotic heart disease. ... 

There are two traditional approaches to collecting and analyzing human factors data related to driving. The first approach is to use data gathered through epidemiological studies (often collected on a national level). These databases, however, lack sufficient detail to be helpful for many applications, such as the development of countermeasure systems or the assessment of interactions between causal and contributing factors that lead to crashes. 

Figure 21.2 illustrates how the starting point, the directions and the scope of each method fit into the accident-analysis framework of Chapter 6. Two of the methods. Fault tree analysis and Comparison analysis are deductive in that they start with the unwanted event. They proceed by analysing the underlying incidents and deviations (Fault tree analysis) or contributing factors (Comparison analysis). Several of the methods are mainly inductive in that they start with a deviation and proceed by studying the effects of this deviation. This applies to HAZOP, Failure mode and effect analysis. Event tree analysis and CRIOP, although they also have a component of causal analysis. Coarse analysis and Job-safety analysis start with the hazard and use a combination of inductive and deductive analyses. 

A causal factor, also known as a critical factor or contributing cause, is a major unplanned, unintended contributor to the incident (a negative occurrence or undesirable condition), that if eliminated would have either prevented the occurrence, or reduced its severity or frequency. 

Diabetes mellitus, or Type II diabetes, is a related disease in which diet is a possible causal or at least a strong contributing factor. Diet is the basis for the control of Type II diabetes. Interestingly, people with diabetes have a high incidence of atherosclerosis. 

Hypertension is associated with increased TXA2 and decreased PGE2 and PGI2 synthesis in some animal models, eg, the Goldblatt kidney model. It is not known whether these changes are primary contributing factors or secondary responses. Similarly, increased TXA2 formation has been reported in cyclosporine-induced nephrotoxicity, but no causal relationship has been established. 

Healthcare facilities must conform to a certain standard of care for flooring and protect people from unreasonable risks. Failure to conform to a reasonable standard of care can create liability issues. Negligence can involve any reasonable, close, or contributing causal factor as related top conduct and an injury. Proximate cause relates to actual loss or damage experienced by another as the result of an event (Table 5.1). 

The procedure relies on building a tree structure as shown in Figure 36-3. At the top is the principal or top undesired event. The tree continues by breaking the event into contributing factors and further subdividing them into event causes. Fault tree analysis is a deductive process that moves from the general to the specific. A tree chart considers the causal chain of factors leading to the top event. Interactions between events and elements of the system are a vital part of this method. 

This theory promotes the idea that accidents result from various hazards or other factors interacting in some manner. Accident prevention professionals use different terms to describe these factors. Some refer to the factors as primary and secondary causes, whereas others use terms such as immediate and contributing causes, surface and root causes, or causes and subcauses. Most investigators agree that accidents happen due to multiple and sometimes complex causal factors. 

Causal factors seldom contribute equally in their ability to trigger an event or contribute to accident severity. Accidents result from some type of interaction of causal factors. Human factors such as an unsafe act, error, poor judgment, lack of knowledge, and mental impairment can interact with other contributing factors, creating an opportunity for an accident to occur. 

The committee s analysis was conducted on several levels. First, members investigated the causal factors for each of the seven events listed in Tables 2-1 and 2-2. They then developed a notional causal tree for each of the two events in Table 2-2 that were analyzed in depth. For illustrative purposes, a causal tree developed by the committee for the December 3-5,2000, incident at JACADS appears at Appendix F. The tree is a standard tool in reliability analysis and is particularly useful in human reliability analysis where operator actions contribute either positively or negatively to an incident. Lastly, the committee provides a series of general and specific observations about the events. 

Darveau et al. (2002, 2003) propose that the relationship between body mass and metabolic rate reflects the contribution of multiple factors - ATP-utilization processes in parallel, supply processes in series - that each have different power functions. This hierarchical layering results in an allometric cascade that has different scaling implications for different measures of metabolism. They contend that only a multiple-factor account, and not West s (or any) single-cause account, can explain the scaling difference between basal and maximum metabolic rate (Bishop, 1999). However, the mathematical formulation of their model has been severely criticized (Banavar etal., 2003 West etal., 2003), and in any case it does not provide an account of why individual processes scale as power functions of mass or why the causal cascade results in a whole-organism metabolism that approximates the 3/4 rule (Bokma, 2004 West et al., 2003 West and Brown, 2004). 

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