Abstract:Background and aims
Perceived stress has been regarded as a risk factor for problematic social networking site (SNS) use, yet little is known about the underlying processes whereby confounding variables may mediate or moderate this relationship. To answer this question, this study examined whether depression and anxiety mediated the relationship between perceived stress and problematic SNS use, and whether these mediating processes were moderated by psychological resilience and social support.
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“…Various measures were used to assess SNUD with the authors of studies adapting measures into Chinese/Mandarin and to assess Chinese SNSs (i.e., western SNS name, such as Facebook R , was exchanged for a Chinese SNS name such as WeChat R ). Hou et al (2019) and Wang et al (2018) utilized adapted versions of the Facebook Intrusion Questionnaire (Elphinston and Noller, 2011;Li et al, 2018a,b) used the Online Social Networking Addiction Scale (Li et al, 2016), Liu and Ma (2018a) used the Social Media Addiction Scale (Liu and Ma, 2018b), Chen et al (2019) used the Social Networking Websites Addiction Scale (SNWAS; Turel and Serenko, 2012) and the Social Networking Sites Addiction Tendency Scale (SNSATS; Wilson et al, 2010). (Yam et al, 2019) used the Bergen Social Media Addiction Scale (Andreassen et al, 2012), Li et al (2017) used an adapted version of the Facebook Addiction Scale (Koc and Gulyagci, 2013), and Hong et al (2014) used the Internet Addiction Test (Young, 1996).…”
Section: Methods Of Assessing Social Network Use Disordermentioning
confidence: 99%
“…Four studies examined the associations between SNUD and anxiety (i.e., Liu and Ma, 2018a;Chen et al, 2019;Hou et al, 2019;Yam et al, 2019). A significant, positive association between SNUD and anxiety was reported in four studies (i.e., Liu and Ma, 2018a;Chen et al, 2019;Hou et al, 2019;Yam et al, 2019).…”
Section: Social Network Use Disorder and Anxiety Symptomsmentioning
confidence: 99%
“…Bivariate correlations were typically in the range of 0.19-0.56. Three of the studies reported inferential statistical results (i.e., Chen et al, 2019-high anxiety was associated with high levels of SNUD (β simple slope =.32, p < 0.001); (Liu and Ma, 2018a)-SNUD was a significant predictor of anxiety, anxiety was a mediator between SNUD and burnout (mediation effect = 0.0795 (95% CI, [0.0546, 0.1075]); (Hou et al, 2019)-anxiety was positively associated with SNUD (β = 0.14, 0.12, p < 0.05). Several scales were used to measure anxiety in the studies.…”
Section: Social Network Use Disorder and Anxiety Symptomsmentioning
confidence: 99%
“…Eight studies examined the associations between SNUD and depression (i.e., Hong et al, 2014;Li et al, 2017Li et al, , 2018aNiu et al, 2018;Tian et al, 2018;Wang et al, 2018;Hou et al, 2019;Yam et al, 2019). A significant and positive association between SNUD and depression was reported in seven studies (i.e., Hong et al, 2014;Li et al, 2017Li et al, , 2018aNiu et al, 2018;Wang et al, 2018;Hou et al, 2019;Yam et al, 2019). Tian et al (2018) reported a significant negative association between SNUD and depression.…”
Section: Social Network Use Disorder and Depression Symptomsmentioning
confidence: 99%
“…Chen et al (2019) used the Chinese version of the Social Phobia Scale (Ye et al, 2007). Hou et al (2019) used the State-Trait Anxiety Inventory (Spielberger et al, 1970). Liu and Ma (2018a) used the Social Anxiety Scale for Social Media Users (SAS-SMU; Alkis et al, 2017).…”
Section: Social Network Use Disorder and Anxiety Symptomsmentioning
Background: An increasing number of studies have investigated Social Networks Use Disorder (SNUD) among Western samples. In this context, the investigation of SNUD in Asia and especially in China has been much neglected. This poses a gap in the literature; it has been estimated that more than one billion Chinese people are using Chinese social networking sites (SNSs). Of note, many of these Chinese SNSs are rather unknown to researchers in Western countries. Aims: The primary objective of the present systematic review was to identify and evaluate studies that investigated Chinese SNS use and associations between SNUD and depression and anxiety symptoms.
“…Various measures were used to assess SNUD with the authors of studies adapting measures into Chinese/Mandarin and to assess Chinese SNSs (i.e., western SNS name, such as Facebook R , was exchanged for a Chinese SNS name such as WeChat R ). Hou et al (2019) and Wang et al (2018) utilized adapted versions of the Facebook Intrusion Questionnaire (Elphinston and Noller, 2011;Li et al, 2018a,b) used the Online Social Networking Addiction Scale (Li et al, 2016), Liu and Ma (2018a) used the Social Media Addiction Scale (Liu and Ma, 2018b), Chen et al (2019) used the Social Networking Websites Addiction Scale (SNWAS; Turel and Serenko, 2012) and the Social Networking Sites Addiction Tendency Scale (SNSATS; Wilson et al, 2010). (Yam et al, 2019) used the Bergen Social Media Addiction Scale (Andreassen et al, 2012), Li et al (2017) used an adapted version of the Facebook Addiction Scale (Koc and Gulyagci, 2013), and Hong et al (2014) used the Internet Addiction Test (Young, 1996).…”
Section: Methods Of Assessing Social Network Use Disordermentioning
confidence: 99%
“…Four studies examined the associations between SNUD and anxiety (i.e., Liu and Ma, 2018a;Chen et al, 2019;Hou et al, 2019;Yam et al, 2019). A significant, positive association between SNUD and anxiety was reported in four studies (i.e., Liu and Ma, 2018a;Chen et al, 2019;Hou et al, 2019;Yam et al, 2019).…”
Section: Social Network Use Disorder and Anxiety Symptomsmentioning
confidence: 99%
“…Bivariate correlations were typically in the range of 0.19-0.56. Three of the studies reported inferential statistical results (i.e., Chen et al, 2019-high anxiety was associated with high levels of SNUD (β simple slope =.32, p < 0.001); (Liu and Ma, 2018a)-SNUD was a significant predictor of anxiety, anxiety was a mediator between SNUD and burnout (mediation effect = 0.0795 (95% CI, [0.0546, 0.1075]); (Hou et al, 2019)-anxiety was positively associated with SNUD (β = 0.14, 0.12, p < 0.05). Several scales were used to measure anxiety in the studies.…”
Section: Social Network Use Disorder and Anxiety Symptomsmentioning
confidence: 99%
“…Eight studies examined the associations between SNUD and depression (i.e., Hong et al, 2014;Li et al, 2017Li et al, , 2018aNiu et al, 2018;Tian et al, 2018;Wang et al, 2018;Hou et al, 2019;Yam et al, 2019). A significant and positive association between SNUD and depression was reported in seven studies (i.e., Hong et al, 2014;Li et al, 2017Li et al, , 2018aNiu et al, 2018;Wang et al, 2018;Hou et al, 2019;Yam et al, 2019). Tian et al (2018) reported a significant negative association between SNUD and depression.…”
Section: Social Network Use Disorder and Depression Symptomsmentioning
confidence: 99%
“…Chen et al (2019) used the Chinese version of the Social Phobia Scale (Ye et al, 2007). Hou et al (2019) used the State-Trait Anxiety Inventory (Spielberger et al, 1970). Liu and Ma (2018a) used the Social Anxiety Scale for Social Media Users (SAS-SMU; Alkis et al, 2017).…”
Section: Social Network Use Disorder and Anxiety Symptomsmentioning
Background: An increasing number of studies have investigated Social Networks Use Disorder (SNUD) among Western samples. In this context, the investigation of SNUD in Asia and especially in China has been much neglected. This poses a gap in the literature; it has been estimated that more than one billion Chinese people are using Chinese social networking sites (SNSs). Of note, many of these Chinese SNSs are rather unknown to researchers in Western countries. Aims: The primary objective of the present systematic review was to identify and evaluate studies that investigated Chinese SNS use and associations between SNUD and depression and anxiety symptoms.
Background: The use of new technologies is growing, and some authors have suggested that frequent use might hide a non-chemical addiction (i.e., technological addiction). Over the last 5 years, several studies investigating the role of metacognitions in technological addictions have been published. We aim to provide the first systematic review focused on this topic, by updating the initial evidence highlighted by a previous systematic review on metacognitions across addictive behaviours (Hamonniere & Varescon, 2018). Methods: Electronic literature databases (Pubmed, PsychINFO, SCOPUS and Web of Science) were searched to identify studies that examined the relationship between metacognitions and four different technological addictions (Internet Gaming Disorder, IGD; problematic Internet use, PIU; problematic smartphone use, PSU; and problematic social networking sites use, PSNSU). Results: We found 13 empirical studies published between 2018 and 2021. Positive low to moderate cross-sectional associations between the four technological addictions and both generic and specific metacognitions were found, in accordance with the metacognitive model of addictive behaviours. Positive beliefs about worry, negative beliefs about thoughts concerning uncontrollability and danger, beliefs about the need to control thoughts and a lack of cognitive confidence were associated with IGD, PIU, PSU and PSNSU. Conclusions: The absence of longitudinal studies prevents us from providing definitive answers about the role of metacognitions in technological addictions. Despite this limitation, interventions that target metacognitions could be beneficial for people presenting with technological addictions.
University students are a high-risk population with problematic online behaviours that include generalized problematic Internet/smartphone use and specific problematic Internet uses (for example, social media or gaming). The study of their predictive factors is needed in order to develop preventative strategies. This systematic review aims to understand the current state of play by examining the terminology, assessment instruments, prevalence, and predictive factors associated with problematic smartphone use and specific problematic Internet uses in university students. A literature review was conducted according to the PRISMA guidelines using four major databases. A total of 117 studies were included, divided into four groups according to the domain of problem behaviour: problematic smartphone use (n = 67), problematic social media use (n = 39), Internet gaming disorder (n = 9), and problematic online pornography use (n = 2). Variability was found in terminology, assessment tools, and prevalence rates in the four groups. Ten predictors of problematic smartphone use, five predictors of problematic social media use, and one predictor of problematic online gaming were identified. Negative affectivity is found to be a common predictor for all three groups, while social media use, psychological well-being, and Fear of Missing Out are common to problematic smartphone and social media use. Our findings reaffirm the need to reach consistent diagnostic criteria in cyber addictions and allow us to make progress in the investigation of their predictive factors, thus allowing formulation of preventive strategies.
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