- QUESTION
Association and Causation
Part 1
Answer to question part 1 should be 250 words.
Develop a question from the topic and discuss about it 50 words
Develop another question from the topic and discuss about it 50 words.
QUESTION:
What are your reactions to causal loop diagrams and group model building? Do you think the benefits outweigh the limitations?
1. Introduction
In this module, we will revisit the differences between linear and systems thinking, explore causal loop diagrams as a way to understand system behaviour and how to create these diagrams in a participatory way. Causal loop diagrams may seem overwhelming to begin with but be assured that once you grasp the simple conventions and with practice, they are a useful method for recognising systemic structures and identifying possible leverage points for action.
2. System Dynamics
System dynamics is an umbrella term used to describe methods that aim to understand the nonlinear behaviour of complex problems over time. It includes methods such as causal loop diagrams, stock and flow diagrams and simulation modelling.
System dynamics, which was originally developed by Jay Forrester in the late 1950’s, helps to visualise problems and how the different parts of the problem “fit together and interact to create dynamics and change through time” (Reynolds & Holwell 2010, p. 25). System dynamics demonstrate how system behaviour is affected by feedback loops and time delays in a nonlinear way.
In module 1 we highlighted the differences between linear and systems thinking, whereby linear thinking is characterised by simple cause-and-effect relationships. Diagram 1 illustrates a linear approach and diagram 2 provides some examples of what this might look like in practice. The solutions in Diagram 2 may provide some short-term relief but in the longer-term, the problems are likely to return and the solution could make the problem worse.
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| Subject | Nursing | Pages | 6 | Style | APA |
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Answer
ASSOCIATION AND CAUSATION
A causal loop diagram (CLD) helps in showing how different variables within a system are interrelated through visual representations. The diagram consists of nodes and edges, where nodes represent variables while edges stand for the inter relationship between various variables. Casual lop diagrams are essential in providing more insight into a system and how the variables are interrelated (Dhirasasna et al. 2019). The links represented by the edges on a causal loop diagram can be positive or negative, where a link marked positive depicts a positive correlation while a link with a negative mark depicts a negative correlation.
On the other hand, group model building entails conducting data analysis with a group of people having a significant interest in the issue at hand. During the analysis, changing trends and links between key factors are taken into consideration. An important feature of the group model building is that it leads to the development of new methods and approaches to the situation under analysis. Moreover, the group members can flashback on important information whenever it is mentioned by a participant in the process of analysis and model development.
However, causal loop diagrams have limitations including the inability to properly organize data, which is very key for information conceptualization (Delgado-Maciel et al. 2018). CLDs have inconsistent feedback criteria in comparison with the basic information representation principles. Moreover, given that group model building heavily relies on the participation of individual group members in analyzing system gaps, it presents relatively high limitations.
What are some disadvantages of the causal loop diagram?
A CLD has no reliable meaning on its own unless supported by various assumptions taken into consideration at the point of its formulation. Moreover, it can be difficult to illustrate to individuals who were not involved in the construction of the causal loop diagram the important highlights.
How do you create a causal loop diagram?
To develop a diagram providing absolute insight concerning a particular system, it is necessary to highlight individual blocks of the system and their interrelationships. For instance, it is necessary to determine the key events, identification of system dynamics, actual system building and highlight the mental models.
Causation Relationship between Television Viewing and Early Smoking Initiation
While early smoking can be caused by other factors such as low self-esteem or growing up with parents who smoke, holding these factors constant, I believe that television viewing has some significant relationship with early smoking initiation (Rogerson et al. 2016). Research has shown that slightly over 90 percent of smokers developed the behavior when they were under the age of 18 years. Moreover, it has been demonstrated that college going teens and youths are more likely to develop smoking habits than their peers who are not in college. During the teenage years, young people generally acquire behavior based on the environment they are exposed to for various reasons. Such reasons may include publicity or desire to stand out of their peers and not to forget and masculinity pressures among the developing males.
While television movies and programs provide entertainment to the younger population, it is highly probable that they would acquire certain behaviors relative to the programs they often view. In this light, there is a high probability for television programs or movies with many scenes of smoking to influence initiation of smoking habits, mostly among the younger population (Dempsey et al. 2016). In addition, prolonged television commercials or advertisements with positive messages on smoking are more likely to influence the initiation of smoking habits. This can be fueled even more when a respected and successful public figure is used to convey the message since the population looking up to them would notice that smoking does not necessarily derail success. However, more study needs to be done to establish the relationship between television viewing and smoking initiation among relatively older population.
Does constant high traffic jam depict low poverty levels in a random population?
There is no evidence to prove that traffic jams would explicitly depict low poverty index in a given population. Other factors such as poor road infrastructure or drainage would be a contributing factor to increased traffic jams. Therefore, traffic jams would still exist in an area with high poverty index because of other underlying factors which does not necessarily depict high net worth population.
Does smoking reduce lifespan?
While smoking of tobacco has been linked to high cases of lung and other types of cancer, there is little evidence showing that smoking in general automatically reduces the lifespan of an individual. However, due to the underlying conditions developed as a result of smoking, a high likelihood of the disease contraction and thereafter death would provide a positive link of smoking to a reduced life span. Figure 1 below depicts a determinant analysis diagram.
Figure 1. Determinant Analysis Diagram
List of References
Delgado-Maciel, J., Cortés-Robles, G., Alor-Hernández, G., Alcaráz, J.G. and Negny, S., 2018. A comparison between the Functional Analysis and the Causal-Loop Diagram to model inventive problems. Procedia CIRP, 70, pp.259-264.
Dempsey, P.C., Owen, N., Yates, T.E., Kingwell, B.A. and Dunstan, D.W., 2016. Sitting less and moving more: improved glycaemic control for type 2 diabetes prevention and management. Current diabetes reports, 16(11), p.114.
Dhirasasna, N. and Sahin, O., 2019. A Multi-Methodology Approach to Creating a Causal Loop Diagram. Systems, 7(3), p.42.
Rogerson, M.C., Le Grande, M.R., Dunstan, D.W., Magliano, D.J., Murphy, B.M., Salmon, J., Gardiner, P.A. and Jackson, A.C., 2016. Television viewing time and 13-year mortality in adults with cardiovascular disease: data from the Australian diabetes, obesity and lifestyle study (AusDiab). Heart, Lung and Circulation, 25(8), pp.829-836.