Kircaburun Griffiths 2018

• Paste quoted text from the Methods section of the article on the next line. Do not include quotation marks or a bullet mark:

  The Self-Liking/Self-Competence Scale was developed by Tafarodi and Swann (2001) and was adapted into Turkish by Do˘ gan (2011). The scale comprises 16 items on a 5-point Likert scale from“absolutely disagree” to “absolutely agree” comprising two dimensions (i.e., self-liking and self-competence). In this study, only the self-liking dimension was used. The Self-liking subscale has higher correlations (0.78 and 0.75) with global self-esteem assessed using the Self-Esteem Scale and Rosenberg Self-Esteem Scale (Do˘ gan, 2011). The self-liking subscale consists of items that indicate self-worth and value regarded by individuals to themselves such as“I am secure in my sense of self-worth,”“I have a negative attitude toward myself,” “I feel great about who i am,” and“I do not have enough respect for myself.” Previous studies have reported optimal validity and reliability of the scale (Do˘ gan, 2011). The Cronbach’s α of the scale in the present study was also high (.83).

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The authors used an already available test which they slightly altered to determine only an individual’s self-liking, rather than both self-liking and self-competence. Self-liking was defined as one’s own ability to feel happy for themselves in regard to their perceived social value, and this is heavily influenced by their acceptance from their peers. The test was composed of 16 multiple-choice questions with the answers being a range from “absolutely disagree” to “absolutely agree”.

• Paste quoted text from the Introduction of the article on the next line. Do not include quotation marks:

The I-PACE model asserts that there are several components that contribute to specific Internet-use disorders, such as an individual’s core characteristics (e.g., personality, social cognitions, psychopathology, specific motives for engaging in a behavior, and biopsychological constitution), subjectively perceived situations (e.g., being exposed to addiction-related factors, negative mood, and personal conflicts), affective responses (e.g., coping style and Internet-related expectancies), and gratifications (Brand et al., 2016). According to I-PACE model, even though some personality traits have consistently been found to relate with problematic use and addiction (e.g., high neuroticism, impulsivity and shyness, low conscientiousness, and self-esteem; Griffiths, 2017), specific personality profiles are related to different types of Internet-use disorders and therefore it is important to investigate common and unique relationships between problematic use of specific applications and different personality pro les (Brand et al., 2016). Using the I-PACE model, several studies have explained influences of various factors on different types of Internet-use disorders including Internet gaming disorder (Zhou et al., 2017), Internet communication disorder (Wegmann, Oberst, Stodt, & Brand, 2017), and addictive use of online sexual activity (Wéry, Deleuze, Canale, & Billieux, 2018). Moreover, a recent study developed an affective neuroscience framework to offer further explanation to the role of personality on different dimensions of Internet addiction (Montag, Sindermann, Becker, & Panksepp, 2016). Consequently, the authors have found that genetics plays a role in both personality and Internet addiction, and that different personality domains were associated with different Internet-use disorders. They argued that the affective neuroscience framework can be integrated in the I-PACE model to further explain the role of individual differences in different type of Internet-use disorders. Based on such models, this study expected to find relationship between personality and Instagram addiction.

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The I-PACE model claims that not one single factor is associated with negative internet use, rather that four main factors of individuals contribute to this. These factors are a person’s personality (including their ability to interact with others, their motives, psychology, etc), how the person reacts in a given situation (their coping mechanisms and their motives for using the internet – Instagram specifically in this study), the situational trigger that lead someone to use the internet (like being in a bad mood or having a fight with a friend), and the satisfaction the person gets from being on the internet. This model has been used in previous studies to explain these four factors in relation to other internet-use disorders like internet gaming disorder (spending too much time playing games on the internet) and the over-use of seeking sexual gratification online. The study hypothesised that there is a connection between the factors and Instagram addiction, although the authors did not state whether this would be a positive or negative association.

• Paste quoted text from the Results section in the article on the next line. Do not include quotation marks:

The prevalence rate of the Instagram addiction using the IAS was examined. According to cut-off points of the IAS, 66.5% of the participants were non-addicted, 26.5% were mildly addicted, 6.1% were moderately addicted, and 0.9% were severely addicted to Instagram. Overall, 33.5% of the participants were risky Instagram users (Table 2). Bivariate correlation coefficients (Table 3) indicated that Instagram addiction was weakly correlated with daily Internet use, agreeableness, self-liking, conscientiousness, and neuroticism. Self-liking was moderately correlated with extraversion, conscientiousness, neuroticism and weakly with agreeableness, and openness to experience.

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Using the Instagram Addiction Scale (IAS), a similar test to the self-liking questionnaire but with a focus on how much time one spends on instagram and their emotional state when using the app, the authors were able to determine the total number of students who were addicted to Instagram. According to the survey, the authors reported that 26.5% of students were mildly addicted, 6.1% were moderately addicted, 0.9% were severely addicted, and the rest was considered non-addicted. The authors also stated that 33.5% of students were considered risky Instagram users, but did not say what specifically this entails. Additionally, it was found that there was a weak relationship between Instagram addiction and daily Instagram use and specific personality traits (those being agreeableness, self-liking, conscientiousness, and neuroticism). The authors included information about the relationship between an individual’s self-liking and their personality, although they did not state whether this was directly related to Instagram addiction.

• Paste quoted text from the Discussion section of the article on the next line. Do not include quotation marks:

Finally, daily time spent on the Internet was a significant positive predictor of Instagram addiction. This result concurs with the findings of Kırcaburun (2016b) and Karada˘g et al. (2015) who reported positive associations between daily Internet use and social media addiction. Social networking platforms, such as Instagram, have become highly popular on the Internet and have become the most used and accessed online applications that constantly upgrade their features according to the need of their users. Recent statistics show that two-thirds of the Internet users are also active social media and SNS users and that the number of users is increasing annually (Kemp, 2017). The findings of this study support the assertions made almost two decades ago that addictions on the Internet are not the same as addictions to the Internet (Griffiths, 1998), and that even among social media addictions, there are differences in the personality characteristics of potentially addicted Instagram users and other types of SNS addicts using different platforms (e.g., Facebook, Twitter, and Tinder).

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The authors found that the amount of time that one spends on Instagram is directly related to Instagram addiction. They state that due to the increased popularity of social networking sites like Instagram, how these sites retain a user’s attention, and the app’s constant updating to increase a user’s use on the platform that this relationship is not surprising. Supporting this, roughly 2/3rds of people who use the internet also use a social media platform and this number continues to increase every subsequent year. This study supports previous research that one can be addicted to using the internet, not just that a person can feed their already formed addictions on the internet. Essentially, the authors are confirming that internet addiction is its own problem, not just a continuation of other issues. Lastly, the authors conclude that one’s personality does influence how addicted they can be to Instagram (or other social media platforms), meaning that while Instagram can be addicting on its own how a person uses and views their relationship with Instagram influences addiction as well.

The authors included information on their suggestions for future research. They stress the importance of future researchers realising that social media use is a personal experience, meaning that different people use and approach Instagram in different ways. One’s personality and reasons for using social media are key aspects in determining addiction and must be factored in when evaluating Instagram addiction.

One thing I found particularly difficult to wrap my head around was the statistical analysis for determining the value points for several of the tests. While I did not need to understand why the authors chose the cut-off points they did to understand the results, it absolutely confused me. Several terms and different methods for evaluating this were thrown around and had no explanation for what they meant, and while I am sure I could have preformed my own research to understand them, it would have taken so much time and not really aided in my understanding of the article as a whole. What could have help was including at least a few of the equations the authors used, as I could have probably gained some insight of how they got the numbers they did rather than just stating certain a bunch of different statistical analysis methods that meant nothing to me as an average reader.