Parent and physician attitudes regarding electronic communication

Parent and physician attitudes regarding electronic communication

1. Kleiner, K. D., Akers, R., Burke, B. L., & Werner, E. J. (2002). Parent and physician attitudes regarding electronic communication in pediatric practices. Pediatrics, 109(5), 740-744.
2. Can the participants in this study be considered random samples? Why or why not?

The parties in this study cannot be considered random samples. Every object has a similar probability of being selected with no bias according to the simple random sampling principle. The participants in this study are there because they have sick children who may need specialists for their medical conditions. The participants are a convenience sample; participation in the study was based on availability at the time of the survey.

1. Table 1 provides frequency distribution tables for several variables (e.g., ethnicity, education, annual income). By “eyeballing” the charts, what general differences can you identify between individuals from general pediatric (GP) offices and those from specialty pediatric (SP) offices?

From the frequency distribution tables, there are minor demographic differences in the annual family income and the parental age. Specialty pediatric office parents had a higher median age range compared to general pediatric office parents. The yearly salary of individual pediatric parents was also higher compared to that of general pediatric parents. The mean patient loads for physicians in pediatric specialty offices were lower compared to that of the general pediatric offices.

1. Based on Figure 1, what can you conclude about the willingness of physicians versus parents to communicate via e-mail?

According to figure 1, parents were more willing to communicate via e-mail, unlike the physicians. In this article, most parents were interested in physician-patient communication via e-mail, whereas the physicians showed no interest.

1. Figure 2 shows two histograms for the variable “level of concern” (one for parents at SP offices, one for parents at GP offices).  How would you describe the shape of these histograms? 

The shapes of the histograms on the levels of concern for parents in the specialty and general pediatric offices portrays a binomial distribution.

1. The authors point out that the samples of parents in this study might not generalize to the population of parents. Why is this? 

The sample of parents does not generalize to the population of parents because a small number of physicians were sampled. The small sample of physicians limits the widespread application and interpretation of physician-based results. The pediatric healthcare system sample was drawn from a suburban and urban setting. The ethnic population is highly diverse, with a majority of low-income earners, which affects access to technology; hence the conclusions are slightly skewed.

2. Read the article, “The median isn’t the message,” by Stephen Jay Gould. This article can be found in the “External” section of Blackboard. Briefly explain why the “median wasn’t the message” for him.

The article by Stephen Jay Gould is about the measures of central tendencies in statistics and their interpretation based on the data obtained. He gives an example of a politician who says the mean income of citizens having a higher value compared to that of the maximum income earned by half of the low earning population said by another politician. According to Stephen, both parties are right; the difference is one gave the mean the other the median. The mean had a higher value because the income of the rich outweighs that of the poor hence the median is not the message it all about interpretation.

Stephen talks of how statistical output affects attitude giving an example of his condition, abdominal mesothelioma, and available data analysis. His physician disregards available statistical literature, and his situation was quite different from what should have been expected based on research. Reading available statistical data might have affected his treatment process based on his attitude and interpretation of the data. Despite the averages, a situation may be right or left-skewed. Therefore, the average value or rather, the central tendency is not usually the case. He recovered from his condition, although available data showed there was no treatment for his condition.

3. Read the article, “The cancer cluster myth.” This article can be found in the Course Documents section of Blackboard. Briefly explain why “the author believes cancer clusters are a ‘myth.'”

Cancer clusters are groups of people with an unusual number of cancer cases. The author thinks cancer clusters are a myth because of public pressure, which makes health workers look for existing cancer cases and give reasons for their causes. The reasons for cancer cases provided are hard for scientists to prove. Public health workers tend to find a reason for diseases to ease the tension among residents. Most of the time, they relate cancer to environmental causes, yet human genealogy has a contribution to the development of cancer. Some of these cancer cases occur by chance and not necessarily an extreme ecological condition was the cause. Some clusters put together tumours of different biologies and cause, e.g. the group in Mc Farland with eleven children with nine types of cancer. Cancers of other organs metastasized to the brain in Los Alamos though it was identified as a brain cancer cluster. The issues explained above show why the author believed cancer clusters are a myth.