The Effects Of Social Media On Teenagers And Their Mood And The Possible Manifestation Of Depressive Symptoms

The Effects Of Social Media On Teenagers And Their Mood And The Possible Manifestation Of Depressive Symptoms

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This paper focuses on the research and evaluation of such research described in the article “Research Links Heavy Facebook And Social Media Usage To Depression” by Amit Chowdhry. First, I will describe the hypothesis, experiment strategies and statistical analysis used in this article. Then, I will describe what the author of the article did well. Finally, I will discuss what the article could have done better and could have improved upon.
This article focuses on the links found between frequency of social media usage in teenagers and their mood and the possible manifestation of depressive symptoms. This study found that people that use social media frequently have a higher likelihood of depression, as they tend to compare their accomplishments with those of their peers, making them feel inadequate.
The goal of this article was to inform the general public of the links found between social media use and depression. Also, this article aimed to encourage psychiatrists to inquire about patients social media usage when providing a diagnosis. The research question explored was if the common usage of social media had an effect on the occurrence of depressive symptoms in adults from the ages of nineteen to thirty-two, which was explored through the use of a correlational study (Chowdhry, 2016).
Due to this study’s correlational nature, it uses predictor and criterion variables. The predictor variable for this study was the amount of time spent on various social media sites a day (measure in number of minutes), and the criterion variable is the amount of depression indicators that an individual exhibited. The sample that was studied consisted of 1,787 adults between the ages of nineteen and thirty-two years of age, which was obtai...

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... as exactly how depression was measured, and how it was classified as “severe”. The article stated that depression was measured through a standardized assessment, but this does not explain how depression is quantified. Also, when describing the data found in this study, the article simply states that a certain group will be 2.7 times more likely to have depression than another group, however, this provides no baseline to compare this with (Chowdhry, 2016). For example if the original likelihood was .01, this would result in a much different meaning than on original likelihood of 20.01 of having depression. Without knowing the original chance of having depression, it is hard to determine the statistical significance of this data. Although the article was easy to understand, this caused several pieces of important statistical and experimental information to be missed.

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