Communication Science Review of Literature 

Introduction

The starter article is Predictors of supportive message expression and reception in an interactive cancer communication system by Kim et al. (2011), and the second article is # Stupidcancer: Exploring a typology of social support and the role of emotional expression in a social media community by Myrick, Holton, Himelboim & Love (2016).

The topic addressed in the two articles is the use of communication technology to mediate communication between cancer patients in order for them to cope or share their experiences. The first article focuses on the predictors for the expression and reception of supportive messages (Kim et al., 2011). The second article focuses on the typology of social support as well as the role that emotional expression plays in the cancer group in a social media application (Myrick et al., 2016). The topic investigated by the two articles is significant due to the development and increased usage of internet-based technology.  Internet-based technology has moved to play a significant role in coping and social support for patients with chronic illnesses (Kim et al., 2011). Many people are using digital communication networks since they provide convenience. Before the growth of the internet, social support groups for cancer were face-to-face, and in some cases, people were not able to attend the meetings (Myrick et al., 2016). The possible benefits of investigating the topic include identifying ways to improve social support individuals with cancer give or receive. Having a proper understanding of the factors that influence social media’s social support or internet technology will enable healthcare workers and communication personnel to utilize and enhance coping through internet-based technology (Kim et al., 2011). The topic is also significant since it enables researchers to learn about the specific messages exchanged to enable coping among cancer patients (Myrick et al., 2016). 

Research Process

The process of finding the starter article started with reviewing the proposed communication studies journals. This involved opening some of the journals and analyzing the research topics examined by the journals. The next step taken was conducting a google search on the common communication topics researched. Healthcare communication and the use of social media or technology to communicate were the most common topics found. The next step was looking for articles, which combine healthcare and social media communication. This was done through a search in the Google Scholar database. This search yielded more than 300 articles. Articles found were then eliminated based on the use of the word “communication” in the title. Articles that did not have the word “communication” were eliminated. The journals were also used to eliminate the articles. Articles that were not contained in communication studies journals were eliminated. Another elimination criterion was the availability of full-text articles. Only full-text articles were selected. After elimination, the article by Kim et al. (2011) was found to be the most suitable for the study. After finding the starter article, the process of finding the second article was initiated. The goal of this process was to find an article with a comparable topic. This search started from the reference list of the starter article. The articles in the reference list were found unsuitable for the study, as many of them were not contained in the recommended communication studies journals. The topic for the starter article was then used to look for the second article through a Google Scholar search. The search yielded more than 20 articles. The articles were then eliminated based on relevance to the study. Articles not contained in communication studies journals were eliminated. At the end of the elimination process, the article by Myrick et al. (2016) was found to be the most suitable for the study. 

Summary of the Two Articles

Starter Article 

Kim et al. (2011) wanted to conduct a study that would go beyond examining the holistic view of computer-mediated social support (CMSS) groups by evaluating the specific social support exchanges between the members of the groups. This involved analyzing the characteristics of the patients. The research questions posed by Kim et al. (2011) were: 

  • Research Question 1: What is the relation between sociodemographic factors and providing and/or receiving support?
  • Research Question 2: What is the relation between disease-related factor and providing and/or receiving support?
  • Research Question 3: What is the relation between psychosocial factors and providing and/or receiving support?
  • Research Question 4: What is the relation between strategies for coping with breast cancer and providing and/or receiving support?
  • Research Question 5: For these predictors, what differentiates the total number of messages written and read versus the content-specific measure of supportive messages written and read?

The research method used in the article was a cross-sectional study through a secondary analysis of the information collected in the “Digital Divide Pilot Project of the Comprehensive Health Enhancement Support System “Living With Breast Cancer” program” (Kim et al., 2011; 1111). The information collected in the study included survey results, data of system use, and discussion posts by the patients. The patients recruited to the initial study were 341. However, only 286 joined the study while 55 decided not to participate. Two hundred thirty-one completed the pretest survey, and 177 were active participants in the CMSS group. The 177 were used in the research by Kim et al. (2011). The findings of the research by Kim et al. (2011) included that individuals with the most resources at the pretest had a higher likelihood of providing emotional support to others than individuals who lacked resources. People who lacked resources were more likely to seek emotional support from others due to their social network deficits. Another finding was that younger patients were more likely to provide emotional support as compared to older patients. Another finding was that people who believed that they had little social support had a higher likelihood of seeking social support as opposed to those who believed they had available support. More educated individuals were also more likely to receive emotional support as compared to less educated people. Another finding was that content-specific discussions were more critical in understanding the support behaviors in comparison to the discussion use measure. The study’s findings show that individuals who are willing to give emotional support are more likely to have resources and support to cope with cancer. In contrast, those who are more likely to receive emotional support lack the resources or ability to receive social support from outside the group.

Second Article 

The general purpose of the research by Myrick et al. (2016) was to examine where message sharing, emotional expression, and social support intersect in an online grass-roots cancer community. The research questions that were posed by Myrick et al. (2016) were: 

  • Research Question 1: Which forms of social support (using the proposed typology based on type and direction of social support) will be most common in a Twitter-based cancer community?
  • Research Question 2: What is the relationship between emotional expression and social support categories within a Twitter-based cancer community?
  • Research Question 3: Which types of discrete emotional expressions and social support messages are related to message sharing in a Twitterbased cancer community?

The research method used was content analysis. The content analysis examined the emotions of the people who shared twitter messages for the hashtag “#stupidcancer.” The twitter messages were examined for a span of 2 years. One finding was that the process of social support is active dynamic as people ask for support before receiving support. The study also found that emotional expressions are different from social support. Another finding was that emotional expression is easier using social media as it allows the quick sharing of emotions. The emotional expression then leads to stronger social bonds. Another finding was that negative emotions had less sharings. Messages with detailed information or religious references were also less likely to be shared. The findings are significant since they show the type of messages that are more likely to provide social support to cancer patients. 

Discussion of the Similarities and Differences between the Two Articles 

The similarities of the two articles include the importance of content-specific discussions. Kim et al. (2011) found that content-specific discussions were more critical in understanding the support behaviors in comparison to discussion use measure or the frequency of discussions. The content-specific discussions in the study included emotionally supportive messages (Kim et al., 2011). The study by Myrick et al. (2016) also found that the contents of the discussions were essential to the quality of discussions. Emotional messages were found to influence the sharing of support messages. The main difference in the findings of the two articles is on the focus. The starter article focused on the group participants’ behavior and identified the individuals who are more likely to share and receive information (Kim et al., 2011). The second article focused on the messages shared and determined the type of messages that are more likely to be shared (Myrick et al., 2016). 

References

Kim, E., Han, J. Y., Shah, D., Shaw, B., McTavish, F., Gustafson, D. H., & Fan, D. (2011).          Predictors of supportive message expression and reception in an interactive cancer       communication system. Journal of Health Communication, 16(10), 1106-1121. doi:             10.1080/10810730.2011.571337

Myrick, J. G., Holton, A. E., Himelboim, I., & Love, B. (2016). # Stupidcancer: Exploring a        typology of social support and the role of emotional expression in a social media          community. Health Communication, 31(5), 596-605. DOI: 10.1080/10410236.2014.981664