Read: Kanat, S. (2019). The Relationship between Digital Game Addiction, Communication Skills and Loneliness Perception Levels of

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Read: Kanat, S. (2019). The Relationship between Digital Game Addiction, Communication Skills and Loneliness Perception Levels of University Students. International Education Studies, 12(11), 80-93. (t-test, anova and correlation)

Throughout this study, Kanat (2019) seeks to explore the relationship between digital game addiction and communication skills and the relationship between digital game addiction and loneliness perception levels of a diverse sample of students at Turkey's nn University (p. 80-82). To accomplish this, Kanat (2019) collected participant data through the use of a survey of 646 students selected by simple random sampling and categorized by gender, grade in university, number of siblings, hours spent per day playing games, father's education level, mother's education level, and income level (p. 82-83). Furthermore, the researcher incorporated the UCLA Loneliness Scale, Digital Game Addiction Scale, and Communication Skills Scale into the survey, allowing participants to answer and give relevant information supporting the study's research questions (Kanat, 2019, p. 83).

Kanat (2019) used descriptive analyses, such as the mean and standard deviation, and parametric analyses, such as ANOVA, independent t-test, and Pearson's Product-Moment Correlation Analysis, to determine the study's results (p. 83-87). The ANOVA is essential in this study, as it allows for a complete comparison of averages from multiple data sets, further allowing for statistical outliers and differences to be determined. Importantly, Kanat (2019) found that 4.3% of participants scaled as digital game addicts based on a monthetic format, where participants scored the maximum on each indicator of addiction, and 22.1% according to the polythetic form, where participants scored a maximum on four of seven indicators (p. 84).

Kanat (2019) found significant statistical differences concerning digital game addiction, loneliness levels, and communication, based on gender, status in university, and the highest degree earned by participants' parents (p. 88-90). Notably, male students were significantly more likely to scale as digital game addicts than female students, first-level or Freshman-level university students were more prone to addiction and communication issues, and a high level of education by either parent correlated with addiction levels (Kanat, 2019, p. 88-89). Furthermore, students with more than one sibling were likelier to score well on communication skills, indicating a lower probability of suffering from digital game addiction. It is important to note that throughout the study, Kanat (2019) refers to existing research on digital game addiction, communication, and loneliness and concludes that although there are similarities between studies, there is ultimately an array of varying results. Kanat (2019) concludes by noting a weak negative correlation between communication skills and digital game addiction exists within the study, or that as addiction rises, communication skills decrease, and that they found no significant correlation between loneliness and addiction levels (p. 89-90).

This topic is especially prescient due to the significantly increasing digitalization of everyday life, in which conditions allowing for the greater likelihood of digital game addiction becomes more common and accessible. This study produces findings that can be applied to better understand the nature of digital game addiction, the demographics particularly susceptible to its effects, and the long-term issues that can arise due to the negative correlation between addiction and communication levels.

Discussion Questions

1. The study did not incorporate nor thoroughly discuss limitations through a dedicated section. Did you find limitations to the study or methodology that could have affected the study's reliability, applicability to real-world applications, or generalizability? If so, are there any potential consequences of such limitations?

2. As the research occurred in Turkey in 2019, some sociocultural constructs and characteristics could influence the study. Are there any ways you would alter the sample or participant segmentation to make the study more applicable to different demographics or cultures? If so, what could be an impact of expanding the scope beyond Turkish students?

3. In what ways was ANOVA a preferred tool for analysis, and why was it impactful for Kanat to use it throughout the study? Additionally, would you find any benefits in constricting or expanding the methodology?