Keyword | CPC | PCC | Volume | Score | Length of keyword |
---|---|---|---|---|---|
tlumacz | 1.26 | 0.8 | 4644 | 72 | 7 |
Keyword | CPC | PCC | Volume | Score |
---|---|---|---|---|
tlumaczenie google | 1.53 | 0.2 | 554 | 27 |
tlumacz angielsko polski | 1.29 | 0.3 | 5788 | 77 |
tlumaczenie | 1.23 | 1 | 9811 | 5 |
tlumaczenie polsko angielskie | 0.81 | 0.9 | 66 | 15 |
tlumacz ang pol | 1.99 | 0.2 | 519 | 43 |
tlumacz google uk | 1.11 | 0.6 | 9355 | 20 |
tlumacz google translate | 1.85 | 0.6 | 5940 | 68 |
tlumacz angielski | 1.37 | 0.5 | 3427 | 68 |
tlumacz onet | 1.45 | 1 | 3186 | 34 |
tlumacz hiszpansko angielski | 0.48 | 0.3 | 3877 | 31 |
tlumacz hiszpanski | 1.05 | 0.9 | 5988 | 86 |
tlumacz eng pol | 1.15 | 0.9 | 2260 | 63 |
tlumacz pl ang | 0.48 | 0.4 | 2204 | 89 |
tlumacz deep pl | 1.47 | 0.2 | 3271 | 80 |
tlumacz islandzko polski | 0.31 | 0.8 | 9877 | 36 |
tlumacz przysiegly | 1.22 | 0.8 | 9550 | 79 |
tlumacz angielsko polski google | 1.7 | 1 | 389 | 26 |
tlumacz polsko szwedzki | 1.68 | 1 | 7093 | 95 |
tlumacz ukrainsko polski | 1.58 | 0.4 | 7924 | 44 |
tlumacz angielsko hiszpanski | 1.46 | 1 | 6724 | 70 |
tlumacz google angielsko polski google | 0.24 | 0.6 | 9532 | 18 |
tlumacz polsko niemiecko | 1.06 | 0.4 | 2061 | 20 |
tlumacz polski na angielski | 0.75 | 0.7 | 4923 | 30 |
tlumacz polsko angielski online darmowy | 1.76 | 0.6 | 7943 | 34 |
tlumacz z angielskiego na polski | 0.28 | 0.8 | 9899 | 39 |
https://www.instagram.com/
Create an account or log in to Instagram - A simple, fun & creative way to capture, edit & share photos, videos & messages with friends & family.
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https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6211134/
1. Introduction 1. IntroductionBehavioral addiction researchers argue that the psychological processes that explain problematic behavior require greater attention [,,,,]. Understanding underlying processes is particularly relevant when examining problematic forms of (digital) media use. Digital devices, such as mobile phones, can be used and misused in a variety of different ways. It is likely that the way in which problem use manifests itself depends on the particular underlying psychological mechanism [,].One psychological process that may underlie problematic digital media use is the Fear-Of-Missing-Out (FOMO). FOMO refers to the “pervasive apprehension that others might be having rewarding experiences from which one is absent” []. Persons who have a greater FOMO are assumed to have a greater desire to stay continually up-to-date of what others are doing, for example via the use of social media. According to Przybylski et al. [], FOMO originates from psychological deficits in people’s competence and relatedness needs []. One way of satisfying these needs, the authors claim, is through the use of social media applications, because the dynamic nature of social media applications provides users with a consistent stream of social and informational rewards [].The purpose of the current study is to contribute to the extant body of research on FOMO in relation to social media use. The study has four aims. First, it investigates whether teenagers with higher levels of FOMO have more social media accounts (i.e., the breadth of social media use) and whether they access these accounts more frequently (i.e., the depth of social media use []) than teenagers with lower levels of FOMO. Second, assuming that teenagers with higher levels of FOMO are mostly motivated to check up on people in their personal social networks, we examine whether FOMO is a stronger predictor of the use of platforms that connect teenagers to their offline networks (e.g., Facebook, Snapchat) than of the use of platforms that connect to a largely unknown audience (e.g., Youtube, Twitter). Third, the study examines if teenagers with greater FOMO report higher levels of problematic social media use (PSMU) and, four, are more likely to report one particular form of problematic social media use, which is the use of social media during conversations with co-present others (cf. “phubbing”). These research aims are addressed with data from a large-scale cross-sectional survey that was administered to 2663 Flemish adolescents.2. Theoretical Framework 2. Theoretical FrameworkPeople have always had a tendency to think about what others are thinking and doing []. In the 1970 and 1980 scholars already identified that some people developed anxieties around missing out, contemplating on the rewarding experiences that others might be having (e.g., in the context of romantic relationships) []. FOMO is thus not an entirely new concept.FOMO can be understood as such an anxiety around missing out on rewarding experiences that results from people’s desire for interpersonal attachments []. This desire, which is grounded in people’s need to belong, is an innate and fundamental motivation which humans have []. People gratify this need by seeking belongingness to social groups. Social groups nowadays exist in both physical and virtual shapes and people have access to their social groups in both ways, online and offline. Social media, which can be defined as “Internet-based applications that build on the ideological and technological foundations of Web 2.0, and that allow the creation and exchange of User Generated Content” [,], offer a place where users can keep in touch with their social circles. Social network sites (SNS) such as Facebook or Instagram, for example, offer users an online connection to persons in their personal networks, facilitating the practice of keeping in touch.Nowadays the digital world is considered an extension of the Self [,]. In addition to the personal mind and physical body, the Self can be thought to include people, places, physical possessions, as well as affiliation groups to which a person feels attached []. Social media platforms are a part of this: they are the digital portals to affiliation groups. In contemporary society we thus manage the affiliation network both offline and online; virtual groups are as real and important as the physical ones. Not being able to connect with those affiliation groups on social media may cause feelings of being out of touch with “real” life []. After all, losing or missing a person one is attached to, can bring feelings of loss and grieving as much as if a part of the Self was damaged [].The fear of being socially excluded plays a role in experiencing a FOMO []. Social exclusion produces a loss of belongingness, and therefore causes anxiety. Thus, when people cannot access their social media accounts, they might feel anxiety because of a fear that they are being socially excluded [].Social exclusion also elicits feelings of worthlessness []. These feelings lead people to the act of comparing themselves to others on social media [] with the purpose of deciding upon their own personal value []. Social networks offer a place where consumers, particularly young generations, can continuously keep up with what peers are doing and checking on what they are missing out on (e.g., social events, life experiences, life opportunities, and so on and so forth). FOMO can thus drive social media use, as checking up on other people may lead to a temporary relief of one’s anxiety.2.1. FOMO and the Use of Different Social Media PlatformsUsers may use different media to gratify different needs [,,]. This can explain differences in the popularity of certain social media platforms. In January 2015, the Global Web Index summary showed that the most popular social media platform was the social network site Facebook, immediately followed by YouTube, Twitter and Instagram. The same year Instagram’s popularity outperformed Twitter. According to some, this is because pictures are more effective than words in achieving self-presentational objectives, which are central motivations for social media use []. Given that each social media platform is characterized by its own features and affordances, it is relevant to differentiate between social media platforms in research on social media use: Different platforms may connect users to different persons and networks, and give access to different forms of information of which users may wish to stay up-to-date.Current research findings reveal that FOMO is a predictor of the use of SNS with which users connect to people in their personal networks, such as Instagram [] and Facebook []. Instagram use, for example, is found to be motivated by the desire to keep in touch with others [] and to “to keep up with or gain knowledge about what others (i.e., friends, family and strangers) are doing” []. FOMO has also been found to predict Facebook use [,] and Instagram use [,]. The above study findings thus indicate that FOMO predicts the use of at least these social network sites, but potentially also the use of other social media platforms.With respect to social media use, a difference can be made between the ”depth” and the “breadth” of one’s use, where the depth of use refers to aspects such as the frequency and duration of social media use, and the breadth of use refers to the variety of social media platforms that are actively used. For teens in particular, not only frequent use, but also the use of a broad variety of social media platforms may serve the purpose of relieving anxieties with regard to not knowing what others are thinking and doing, as the differences in the relational affordances of different platforms [] mean that they may give access to at least partially different networks and contents. Hence, for the current study we expect that not only the depth, operationalized as the frequency of social media use, but also the breadth, operationalized as the number of active social media platforms teenagers use, are predicted by FOMO: Hypothesis 1.Teens who experience greater FOMO, use social media more frequently (Hypothesis 1a; i.e., the depth of social media use), and use more different social media accounts (Hypothesis 1b; i.e., the breadth of social media use).2.2. FOMO and the Use of More Private versus More Public Social Media PlatformsAs mentioned above, the use of different social media platforms may gratify different underlying needs. For example, a recent study shows that users significantly differ in the gratifications they derive from using Facebook, Instagram, Twitter and Snapchat []. One affordance in which platforms may differ is in the extent to which content is restricted to a (sub-)set of contacts, or fully public—in other words, whether content is shared with a mostly known versus a mostly unknown audience. On platforms such as Facebook, Instagram or Snapchat, people’s online social network usually overlaps with their offline affiliation group (e.g., Facebook/Snapchat contacts need to know each other’s names or phone numbers to see each other’s posts and profiles). Platforms such as Twitter or Youtube, on the other hand, usually make content accessible to a wider audience of mainly unknown individuals, and resemble a broadcasting platform rather than a platform in which content is restricted to people who have been accepted as “contacts”, “followers” or “friends”.Given this difference in the public accessibility of platform content, it seems logical to assume that SNSs such as Facebook or Snapchat are more apt at providing relief from FOMO than, for example, video sharing platforms such as Youtube or microblogging services such as Twitter because the former provide greater relief from anxieties surrounding what friends and family are doing.Indeed, platforms such as Facebook or Instagram are more personal SNS that enable teens to limit content accessibility to the desired public (e.g., friends or friends-of-friends). As a result, these SNS may be especially attractive venues for teens with a high FOMO because it lets them know what people in their primary affiliative groups are thinking and doing. We explore this assumption by asking the following research question: Research Question.Is FOMO a stronger predictor of the use of more private social media platforms (that connect mostly to offline networks) than more publicly accessible social media platforms (that connect mostly to online networks)?2.3. FOMO and Problematic Social Media Use (PSMU)When social media use is excessive, it can become problematic. Several studies have addressed problematic social media use (PSMU) [,,]. There is an ongoing debate in the literature around the differences between problematic social media use and a possible social media behavioral addiction [,]. An in-depth discussion of this debate goes beyond the scope of this work. In the current study, however, we use the term problematic social media use, which we define as an unhealthy excessive form of social media use, characterized by a lack of control over the behavior, and continued behavior despite adverse life consequences. Our focus is on revealing the factors that predict to problematic social media use in a general population of teenagers (i.e., the aim is not to diagnose or identify pathological cases).As mentioned before, one of the aims of this study is to explore if teenagers with a greater FOMO report a higher levels of PSMU. Previous studies suggest that this is the case [,,,,,], and suggest that those who experience FOMO may try to relieve their anxiety by checking up on other people on social media. Ironically, however, the more people check their social media accounts, however, the more they may find events they are missing out on. Using social media to reduce the anxiety may end up to be another source of FOMO. Therefore this vicious circle may reinforce itself, gradually turning social media use into problematic social media use. Hence we expect: Hypothesis 2.Teens who experience greater FOMO, report higher PSMU.2.4. FOMO and PhubbingA final study purpose is to focus on FOMO as a predictor of one particular form of problematic social media use, which is the use of social media during conversations with co-present others. This practice is termed “phubbing” (derived from phone + snubbing), which refers to “the act of snubbing someone in a social setting by concentrating on one’s phone instead of talking to the person directly” [,]. Experimental studies show that phubbing negatively impacts relational outcomes such as impression formation [].Recent findings show that people prefer to use smartphones when going online []. Smartphones allows us to be in contact with our affiliation groups on social media, everywhere we are. Therefore, we assume that if people experience anxiety, they may temporary try to reduce it by accessing their social media accounts on their smartphones []. It is likely that those high in FOMO, who use social media to address their anxiety, may overuse social media on their smartphones in such a way that it intersects with their offline social interactions, leading them to phub their offline interaction partners.Hence, the last aim of this study is to explore whether teens with a greater FOMO report to engage in phubbing behavior more frequently, and whether the latter relationship is mediated by PSMU: Hypothesis 3a.Teens with a greater FOMO, are more likely to use social media during conversations with co-present others (cf. “phubbing”). Hypothesis 3b.PSMU mediates the former relationship.3. Method 3. Method3.1. Sample and ProcedureIn Flanders, a consortium of non-profit organizations collaborates bi-annually on a large-scale survey project that examines the state of affairs of digital media ownership and use of Flemish youths. Apart from a large set of recurring questions, every edition of the survey includes a number of questions on topics that are considered relevant at the time.The data gathered for the current study were part of the 2016 research project []. An omnibus survey was administered to the high school pupils of 11 geographically dispersed high schools in Flanders, Belgium. Using the information made available by the ministry of education, quota sampling was used to select schools, and—within the schools—years and classrooms. This procedure resulted in a final sample that is representative for the population in terms of gender, age and school track (see Van Waeg, D’Hanens, Dooms & Naesens [] for further details).Within each school, a local collaborator (e.g., the school’s information and communications technology coordinator) organized the survey administration process, according to a set of instructions provided by the project leaders. The survey was administered online, but to avoid self-selection bias, the data collection took part during school hours, in the computer rooms of the schools. Unfortunately, no response rates were registered. However, the local collaborators stated that few pupils did not receive permission to participate. In total, the responses of 3291 pupils were gathered. The project leaders subjected these responses to a rigorous data cleaning procedure, leading to removal of 452 responses that were either substantially incomplete, either contained multiple invalid responses to validation screening items. This procedure resulted in a final sample of 2663 pupils (57.1% girls; Mage = 14.87, SD = 1.67). This final dataset was distributed by the consortium to the collaborating researchers for further analysis.Informed consent was collected from both the participating teenagers and their parents. Given the large sample-size, an opt-out procedure was used for collecting consent from parents. The university’s institutional review board approved the study.3.2. Measures3.2.1. Breadth of Social Media Platforms UsedBased on interviews with young persons, a list of 25 frequently used social media applications was constructed. We adhered to Kaplan and Haenlein’s [] definition of social media, which includes all platforms in which users can generate content that is (semi-)publicly available to others. The latter definition excludes platforms that focus exclusively on instant messaging (e.g., Whatsapp, Facebook Messenger). The list of included platforms can be consulted in . The breadth of social media use was assessed by asking for each platform whether the teenager had an active account (1 = yes, 0 = no), and then summing the total number of active accounts per participant.Table 1Scale items, means and standard deviations. Fear-of-Missing-Out (FOMO) Items M SD 1I fear my friends have more rewarding experiences than me2.331.112It is important that I understand my friends’ “inside jokes”3.091.053It bothers me when I miss an opportunity to meet up with friends4.160.904When I go on summer camp or vacation, I continue to keep tabs on what my friends are doing2.661.14 Problematic Social Media Use (PSMU) Items M SD 1How frequently do you find it difficult to quit using social media?2.891.192How frequently do others (e.g., your parents or friends) tell you that you should spend less time on social media? 2.721.283How frequently do you prefer using social media over spending time with others (e.g., with friends or family)?1.890.974How frequently do you feel restless, frustrated or irritated when you can’t access social media? 2.331.165How frequently do you do your homework poorly because you prefer being on social media? 2.511.176How frequently do you use social media because you feel unhappy? 2.311.237How frequently do you lack sleep because you spent the night using social media?2.441.35 Phubbing Items M SD 1How frequently do you use your mobile phone during a conversation in a bar or restaurant?2.390.992How frequently are you engaged with your phone during a conversation?2.130.963How frequently do you check social media on your phone during a personal conversation?1.890.923.2.2. Depth of Social Media Platforms UsedThe depth of social media use was measured by assessing for each active platform how frequently it was used (1 = less than once per week, 5 = multiple times per day). Questions with respect to the usage frequency of a platform were only answered by participants who had an active account for the platform. As visible in , a substantial number of platforms was used by (very) few participants. We opted to only include those platforms who were used by at least 5% of the sample. The analyses for Hypothesis 1a, concerning FOMO as a predictor of platform usage frequency (see and ) are performed on the basis of the subsample of users of each platform. Table 2Percentage of teenagers with an account on various social media platforms and average frequency of use among account holders (1 = less than once/week, 5 = multiple times/day).Social Media PlatformN% of Total SampleAverage Usage FrequencyLess than Once per WeekOnce per WeekMultiple Times per WeekDailyMultiple Times per Day M SD %%%%%Facebook236089%4.490.871.43.66.422.266.5Snapchat193773%4.361.002.44.510.120.562.5Instagram168063%4.360.971.54.415.731.846.6YouTube159660%4.170.952.14.49.722.361.4Google+92535%2.671.4028.221.519.816.414.1Twitter58222%3.631.358.814.919.418.638.3Swarm51019%4.261.093.75.510.820.659.4We Heart It32912%3.421.3410.616.421.922.228.9Pinterest32412%2.61.3428.121.624.414.511.4Tumblr29811%3.521.359.416.421.118.834.2Vine2329%3.121.3815.919.823.318.522.4Foursquare1726%3.031.7234.38.79.913.433.7Tinder1205%2.521.5136.72015.89.218.3Kiwi1174%31.5825.618.813.713.728.2Ask.fm923%3.61.6020.76.51214.146.7Runkeeper723%2.171.1031.934.723.64.25.6Reddit602%3.071.48202018.316.725Happening482%2.651.4229.220.820.814.614.6Vimeo321%2.911.6134.46.315.621.921.9Strava251%2.61.442828161216LinkedIn241%2.081.385016.720.812.5/Periscope151%3.071.2813.32026.726.713.3Endomondo110%2.731.7436.418.29.19.127.3Ello80%1.51.4187.5///12.5Meerkat60%2.332.0766.7///33.3Table 3Gender, age, school track and Fear-of-Missing-Out (FOMO) as predictors of the frequency of Facebook, Snapchat, Instagram, Youtube, Google Plus and Twitter. FacebookSnapchatInstagramYoutubeGoogle PlusTwitterPESEWaldPESEWaldPESEWaldPESEWaldPESEWaldPESEWaldGender (boy)−0.500.0932.55 ***−0.680.0952.79 ***−0.610.1035.85 ***0.720.1056.21 ***0.180.122.23−0.250.152.58Gender (girl)a Age0.150.0328.1 ***0.020.030.300.120.0314.36 ***−0.010.030.14−0.090.046.42 *0.020.050.15School track (voc)0.410.148.72 **0.400.148.00 **−0.340.145.75 *0.540.1513.58 ***0.510.178.79 **0.360.252.18School track (s-voc)0.280.125.67 *0.350.128.88 **−0.010.120.00−0.010.120.000.400.156.84 **0.760.1819.06 ***School track (ac)a FOMO0.480.0755.09 ***0.280.0716.89 ***0.340.0722.48 ***0.180.077.08 **0.040.090.220.150.112.02Pearson GOFX2(1821) = 1635.34, p = 1.00X2(1731) = 1842.31, p = 0.031X2(1643) = 1716.37, p = 0.102X2(1623) = 1621.94, p = 0.503X2(1335) = 1370.00, p = 0.247X2(1083) = 1131.58, p = 0.148−2LL GOFX2(5) = 150.10, p < 0.001X2(5) = 88.07, p < 0.001X2(5) = 79.19, p < 0.001X2(5) = 75.47, p < 0.001X2(5) = 17.20, p = 0.004X2(5) = 29.41, p < 0.001Nagelkerke R20.070.050.050.050.020.05* p < 0.05, ** p < 0.01, *** p < 0.001, Note 1: PE = parameter estimate, SE = standard error, Wald = Wald test statistic, voc = vocational, s-voc = semi-vocational, ac = academic, GOF = goodness-of-fit, a = reference category.Table 4Gender, age, school track and Fear-of-Missing-Out (FOMO) as predictors of the frequency of Swarm, We Heart It, Pinterest, Tumlbr, Vine, Foursquare and Tinder. SwarmWe Heart ItPinterestTumblrVineFoursquareTinderPESEWaldPESEWaldPESEWaldPESEWaldPESEWaldPESEWaldPESEWaldGender (boy)−0.480.196.58 **−1.410.585.87 *−0.590.294.18 *−0.410.292.010.190.240.64−0.040.290.02−0.110.340.11Gender (girl)a Age0.210.0611.25 *−0.120.072.69−0.030.070.16−0.030.070.16−0.130.082.480.030.110.10−0.170.112.36School track (voc)−0.580.255.34 *0.650.314.36 *−0.100.270.15−0.500.332.30−0.210.360.330.250.370.460.750.482.45School track (s-voc)0.360.222.780.010.240.00−0.170.250.430.070.250.080.050.290.030.330.340.930.480.421.33School track (ac)a FOMO0.160.131.490.240.142.860.190.171.280.290.153.77 *0.370.184.22*0.470.215.26 *0.040.230.03Pearson GOFX2(915) = 856.28, p = 0.917X2(571) = 607.49, p = 0.141X2(619) = 627.27, p = 0.400X2(619) = 620.67, p = 0.474X2(599) = 616.26, p = 0.304X2(475) = 488.52, p = 0.324X2(371) = 373.34, p = 0.456−2LL GOFX2(5) = 28.53, p < 0.001X2(5) = 12.53, p = 0.028X2(5) = 6.24, p = 0.283X2(5) = 689.76, p = 0.123X2(5) = 8.29, p = 0.141X2(5) = 7.47, p = 0.188X2(5) = 4.26, p = 0.513Nagelkerke R20.060.040.020.030.040.050.04* p < 0.05, ** p < 0.01, *** p < 0.001, Note 1: PE = parameter estimate, SE = standard error, Wald = Wald test statistic, voc = vocational, s-voc = semi-vocational, ac = academic, GOF = goodness-of-fit, a = reference category. Note 2: The results for We Heart It, Pinterest and Tinder have to be interpreted with caution as the assumption of proportional odds was violated.3.2.3. Private Versus Public Accessibility of Social Media Platforms UsedWith respect to the private versus public accessibility of platforms, we consider Facebook and Snapchat as social media platforms on which content is generally less publicly accessible (i.e., content is oftentimes shielded off to a public of “approved” contacts), and Youtube and Twitter as social media platforms on which content is generally publicly accessible (i.e., content is usually accessible to everyone who visits the platform).3.2.4. Fear of Missing Out (FOMO)The omnibus format of the survey implied a constraint on the number of items we could use. We chose to select four items from Przybylski et al.’s [] 10-item FOMO-scale, as this scale had been pre-validated by the authors. In Przybylski et al.’s study, the ten scale items loaded on one factor, and were internally consistent. In the absence of information on the factor loadings of the individual items in the original study, we chose to select a subset of four items that reflect the diversity of the original scale items well. Those items were: “It bothers me when I miss an opportunity to meet up with friends”, “I fear my friends have more rewarding experiences than me”, “When I go on vacation or summer camp, I continue to keep tabs on what my friends are doing”, and “It is important that I understand my friends “inside jokes””. The items were measured on a 5-point Likert-scale (1 = completely disagree; 5 = completely agree).A well-known risk of using a diverse set items to construct a short scale, is that internal consistency may be jeopardized []. Indeed, although an exploratory factor analysis revealed that the four items loaded onto one factor, with all factor loadings above 0.55, the total variance explained by the factor (42%) was below the advised 60% threshold, and the overall Kaiser-Meier-Olkin measure (0.65) indicated mediocre sampling adequacy. A further examination of the scale’s reliability, confirmed that the internal consistency of the scale was weak (α = 0.56), and revealed that it could not be further improved via item selection, as the highest inter-item correlation was 0.36 (p < 0.001). shows the inter-item correlation matrix. Means and standard deviations can be consulted in .A solution to the issue of low internal consistency, is to perform analyses with individual scale items, rather than with a scale variable. For the current study, however, such procedure would imply an inflation of results—particularly when answering Hypothesis 1a, which reduces the comprehensibility of the study findings. The alternative is to continue with a sub-optimal measure, knowing that the main risk of using a scale-measure that suffers from a weak Cronbach alpha, is underestimation of the real relationship []. In the context of the current study, we opted for the latter solution for reasons of comprehensibility, and thus work with the scale variable to answer Hypothesis 1. The risk of an underestimation of the real relationship should be kept in mind, however, when interpreting the results. For Hypotheses 2, 3 and 4, we report both the results using the FOMO scale variable and the individual scale items.3.2.5. Problematic Social Media Use (PSMU)Problematic social media use was assessed using an adapted version of the C-VAT instrument [], which is a scale based on the CIUS-scale that was developed and validated by Meerkerk, Van den Eijnden et al. [] and Meerkerk []. The adapted version addresses social media use rather than videogaming. The items were measured on a 5 point Likert-scale (α = 0.82). The scale items, their means and standard deviations, and their factor loadings can be consulted in .3.2.6. Phubbing BehaviorAt the time of constructing the questionnaire, we were unaware of scales measuring phubbing behavior. Hence, we measured phubbing behavior with three self-constructed items: “How frequently do you use your mobile phone during a conversation in a bar or restaurant?”, “How frequently are you engaged with your phone during a conversation?”, and “How frequently do you check social media on your phone during a personal conversation?”. The items were measured on a 5-point Likert scale, ranging from 1 (never) to 5 (almost all the time; α = 0.77). The scale items, their means and standard deviations can be consulted in .3.2.7. Control variablesGender (1 = boy, 2 = girl), age and school track (1 = vocational, 2 = semi-vocational, 3 = academic) were included as control variables in the linear regression analyses.3.3. AnalysesHypothesis 1a states that teens who have a greater FOMO use social media platforms more frequently. We used ordinal regression analysis in to test this hypothesis because the frequency of use-measures have ordinal response scales. In the analyses with the frequency of use of Snapchat, We Heart it, Pinterest and Tinder as the dependent variables, the assumption of proportional odds was violated; this occurs more frequently in large samples, because minor violations of the parallel lines test may already be statistically significant []. Nonetheless, we advise to interpret these results with caution.Hypothesis 1b states that FOMO positively predicts the breadth of social media use. The “breadth of social media use” variable was operationalized by counting the number of active social media accounts that teens have (min = 0, max = 25). We used multiple linear regression analysis to test the hypothesis, after assessing that the standardized residuals of the variable were normally distributed (and thus that the assumption of normality was not violated: because measurements gathered in large samples typically have very small standard errors, it is advised to assess normality on the basis of the absolute values of skewness and kurtosis rather than on Z-scores of skewness and kurtoses. Advised critical values for skewness, respectively kurtosis in large samples are 2, respectively 7 []. Using these guidelines, the skewness (1.22) and kurtosis (5.95) values of the residuals indicated that the assumption of normality for regression analysis was sufficiently met). To explore our research question on the comparative strength of the correlations between FOMO and private platforms on the one hand, and between FOMO and public platforms on the other, we first calculated the correlations, and next compared the strength of these correlations using Steiger’s Z-test [] in Lee and Preacher’s [] web-based software. The Steiger Z-test operates on the basis of Pearson correlations between two dependent correlations with one variable in common. Because the correlations have to be drawn from the same sample, we first recoded the ‘frequency of platform use’ variables so that persons without an active account received the lowest usage score (rather than a missing value). This recoding procedure ensured that there were 2663 responses for each variable. Next, we calculated the Pearson correlation coefficients, which form the input for the Steiger’s Z-test. The reader may notice that the Pearson correlation test is a parametric test, whereas the “frequency of platform use” variables are ordinal. However, the variables met the standard guidelines for skewness and kurtosis in large samples [], and the Pearson correlation coefficients and the Spearman rho correlation coefficients were highly similar (i.e., for only two out of ten correlations the difference between the Pearson and the Spearman correlation coefficient exceeded a value of 0.03).In social science research, scale variables are oftentimes treated as interval variables, based on the idea that the sets of items that comprise each scale form an index that represents an underlying latent factor []. The required assumptions for parametric testing were met. Hence, to examine Hypotheses 2 and 3, we fitted a mediation model using model 4 of Hayes’ []. Process macro for SPSS with FOMO as the independent variable, PSMU as the mediator and phubbing behavior as the dependent variable. The indirect effect was estimated for 5000 bootstrap samples with a 95% bias-corrected confidence interval.4. Results 4. Results4.1. DescriptivesBefore addressing the hypotheses and research questions, we briefly report some descriptive statistics for the media use variables. The means and standard deviations for the items of the FOMO-scale, the PSMU-scale and the phubbing scale can be consulted in .For 25 social media platforms, we asked the teenagers in our sample whether they had an active account, and if so, how frequently they use it. In terms of active account ownership, Facebook (89% of teens with an active account), Snapchat (73%), Instagram (63%) and Youtube (60%) are the most popular social media platforms. The teenagers in our sample had on average 4.35 (Median = 4, Mode = 4, Min = 0, Max = 25) active social media accounts. The standard deviation (SD = 2.29) reveals that there is substantial variability between teenagers. Most teens who have an active account on Facebook, Snapchat, Instagram and Youtube, reported using the platform more than once per day (see ). There are other social media platforms that are frequently used, such as the location-sharing platform Swarm (M = 4.26, SD = 1.09), but these oftentimes have small user bases (e.g., only 19% of teens has an active Swarm account).The teenagers in our sample on average had a fairly neutral FOMO score (M = 3.06, SD = 0.69). Using a multiple regression analysis, we explored whether FOMO was predicted by gender, age and school track. Our analysis showed that girls (ß = 0.08, p < 0.001) reported a higher FOMO, whereas age (ß = 0.03, p = 0.109) and school track (ß = −0.01, p = 0.800) were no significant predictors, R² = 0.01, F(3.2659) = 5.96, p < 0.001).4.2. FOMO as a Predictor of the Depth and Breadth of Social Media UseHypotheses 1a and 1b concern FOMO as a predictor of the depth and breadth of social media use. We tested Hypothesis 1a using ordinal regression analysis, with gender, age, school track and FOMO as the predictor variables, and the frequency of use of each respective social media platform that was used by 5% of the sample or more as the dependent variable. and show the results. After controlling for gender, age and school track, FOMO positively predicted the use of the four most popular social media platforms: Facebook, Snapchat, Instagram and Youtube, as well as the frequency of using foursquare, Tumblr and Vine. These findings lend partial support to our hypothesis. While FOMO appears to be a modest predictor of the most common social media platforms, as well as of platforms that are used more rarely, it was not a consistent predictor of social media platform use.With respect to the breadth of social media use (Hypothesis 1b), a multiple linear regression analysis with gender, age, school track and FOMO as predictors, revealed that gender (ß = 0.08, p < 0.001), age (ß = 0.20, p < 0.001), school track (ß = −0.05, p = 0.006) and FOMO (ß = 0.14, p < 0.001; R² = 0.08, F(4.2658) = 57.27, p < 0.001) were significant, positive predictors of the number of active social media accounts that teenagers have (H1b supported).4.3. FOMO in Relation to the Public Accessibility of PlatformsWe posited that FOMO would be a stronger predictor of social media use when the social media platform examined is a more private platform than when it as a more public platform (RQ1), because more private platforms such as Facebook or Snapchat connect teenagers more strongly to their offline ties, which can be considered the dominant affiliative group on which they want to keep tabs. We calculated Steiner’s Z to statistically compare the correlations between FOMO and Facebook, respectively Snapchat use on the one hand, and between FOMO and YouTube, respectively, and Twitter on the other hand (see and ).Table 5Correlations between FOMO and frequency of use of less publicly accessible platforms versus more publicly accessible platforms.Pearson’s rFacebookSnapchatYouTubeTwitterSnapchat0.48 ***1 Youtube0.13 ***0.04 *1 Twitter0.15 ***0.19 ***0.18 ***1FOMO0.16 ***0.17 ***0.000.06 **** p < 0.05, *** p < 0.001, Note 1: For these analyses, participants with no active account on the platform were assigned a value of ‘0′ on usage frequency to ensure that the analyses were performed on the same sample size. Note 2: We used Pearson’s correlation coefficient, to enable the calculation of a Steiger Z value (see the subsequent set of analyses in ). Note 3: The normality assumption was not violated.Table 6Comparison of Pearson correlation strength between FOMO and more private platforms versus FOMO and more public platforms.Steiner’s Z (rFOMO, column var vs. rFOMO, row var)FacebookSnapchatYouTubeTwitterSnapchat−0.41 Youtube6.37 ***6.38 *** Twitter4.18 ***4.62 ***−2.30 * * p < 0.05, *** p < 0.001.The findings show that the correlations between FOMO and Facebook (r = 0.16, p < 0.001), respectively Snapchat use (r = 0.17, p < 0.001), are significantly stronger than the correlations between FOMO and YouTube (r = 0.00, p = 0.921), respectively Twitter use (r = 0.06, p = 0.002), thus lending support to our research question.4.4. FOMO as a Predictor of PSMU and Phubbing BehaviorHypotheses 2 stated that FOMO positively predicts PSMU and Hypothesis 3a stated that FOMO positively predicts phubbing behavior. Hypothesis 3b stated that PSMU mediates the relationship between FOMO and phubbing behavior. We tested these hypotheses by estimating a mediation model. The results are depicted in . All hypotheses were supported. FOMO has a direct, positive predictor of both PSMU (ß = 0.40, p < 0.001) and phubbing behavior (ß = 0.20, p < 0.001). When PSMU is accounted for, the relationship between FOMO and phubbing behavior weakens considerably. The indirect effect is significant (ß = 0.16, p < 0.001).Mediation model of the relationship between FOMO, PSMU and phubbing behavior (*** p < 0.001). FOMO: Fear-of-missing-out; PSMU: problematic social media use.Given that the internal consistency of the FOMO scale was unsatisfactory, we performed the mediation analysis on the individual items of the FOMO scale (see ). For three items, the mediation analysis resulted in a similar results pattern. For the item “It bothers me when I miss an opportunity to meet with friends”, however, the direct relationship with PSMU was much weaker (albeit still significant; ß = 0.05, p = 0.008), and the direct relationship with phubbing behavior was negative (ß = −0.04, p = 0.011).Table 7Mediation analysis results for the individual items of the FOMO scale and the FOMO scale variable. abcc’Indirect Effect EstimateFOMO (4-item scale)0.40 ***0.41 ***0.040.20 ***0.16 [0.14; 0.19]Individual items I fear my friends have more rewarding experiences than me0.21 ***0.42 ***0.000.09 ***0.09 [0.07; 0.10]It is important that I understand my friends’ “inside jokes”0.15 ***0.43 ***−0.010.05 ***0.06 [0.05; 0.08]It bothers me when I miss an opportunity to meet up with friends0.05 **0.43***−0.04 *−0.020.02 [0.00; 0.04]When I go on summer camp or vacation, I continue to keep tabs on what my friends are doing0.22 ***0.38 ***0.09 ***0.18***0.09 [0.07; 0.10]* p < 0.05, ** p < 0.01, *** p < 0.001. Notes: a = effect of FOMO on PSMU. b = effect of PSMU on phubbing. c = effect of FOMO on phubbing. c’= total effect of FOMO on phubbing.5. Discussion 5. DiscussionDrawing from the results of a survey study among 2663 Flemish teenagers, the aims of this study were fourfold: (1) to examine FOMO as a predictor of the depth and breadth of social media use; (2) to examine whether FOMO relates more strongly to the use of more private social media platforms than more public platforms; (3) to test whether FOMO predicts PSMU and (4) whether FOMO predicts, both directly and indirectly via PSMU, phubbing behavior.With respect to the breadth of social media use (Hypothesis 1b), we found support for the hypothesis that teens who have a greater FOMO use a wider variety of social media platforms. With respect to the depth of social media use, the study findings partially support the hypothesis that teenagers with a higher FOMO use social media more frequently (Hypothesis 1a), as FOMO was identified as a predictor for the frequency of use of some, but not all social media platforms examined. We did find a consistent relationship with the usage frequency of the four most used platforms: Facebook, Snapchat, Instagram and YouTube. This finding suggests that the relationship between FOMO and the frequency of use of these popular platforms is generalizable to the population of at least Flemish teenagers. These findings also support the findings of earlier work that characterize FOMO as an intrapersonal characteristic that predicts the use of Facebook [,] and Instagram [,].The relationships found between FOMO and the frequency of using less popular social media platforms such as Foursquare, Tumblr and Vine are more difficult to interpret, as these social media platforms differ considerably from each other in what they afford the user to do: Foursquare is a location-based social network site, Tumblr is a blogging service, and Vine let users share short videoclips. Future research may explore the relationship between FOMO and the use of these particular platforms more in-depth via the use of interviews with teenagers, as greater insight into their personal experiences with these platforms and their anxieties concerning missing out may shed new light on what makes these particular platforms attractive.As mentioned above, a pertinent question is whether the social gratification provided by social media use sooths or aggravates the anxieties of teenagers; after all, studies on social comparison on social media platforms [] suggest that exposure to other people’s social media accounts may make the experience of missing out on rewarding experiences even greater. A limitation of our study is its correlational nature, which prevents from making claims concerning the potential bi-directional causality of the relationship between FOMO and social media use. Future research may address this question via the use of longitudinal study designs that enable the modelling of cross-lagged path models.It is essential for our understanding of FOMO to unravel how it resemblances, but also differs from other, associated personality factors. One factor that has been identified in the extant literature and that appears relevant to consider, is sociotropy [], which refers to an insatiable need for belongingness to others, visible in an over-reliance on approval from others, which can go at the expense of personal autonomy. In recent work, sociotropy is linked to the ritualistic monitoring of, oftentimes multiple social media platforms []. Future research may explore how the fear of negative feedback or rejection that is typical for sociotropic individuals aligns with a fear of missing out.We questioned whether FOMO would be a stronger predictor of more private social media platforms such as Facebook or Snapchat than of more public platforms such as YouTube and Twitter (RQ1). Our exploratory analysis suggests this is indeed the case. This is unsurprising, given that FOMO itself has been conceptualized and operationalized in the current study as a fear to miss out on what friends are thinking and doing, and information about these friends can be found mostly on platforms that connect to people who are part of one’s offline network. Nonetheless the stronger relationship between FOMO and these private platforms, we need to remark that FOMO still remains a weak, yet significant predictor of some more publicly accessible platforms (e.g., Tumblr). A pertinent question is what still drives those higher on FOMO to use the latter platforms, then. As mentioned above, qualitative research seems relevant to further expand on the affordances in which various social media platforms resemble or differ from one another, and how these affordances are perceived, valued and acted upon by those with a higher versus lower FOMO.FOMO was found to predict PSMU (Hypothesis 2), a result that aligns with the findings from other recent studies which showed that greater FOMO is associated with more problematic internet and smartphone use [,,]. Moreover, FOMO was also associated with phubbing behavior (Hypothesis 3a), consistently with previous research that showed a similar pattern of associations []. Interestingly, our results showed that the relationship between FOMO and phubbing behavior was mediated by PMSU (cf. Hypothesis 3b), accordingly to the proposed conceptual model by Chotpitayasunondh & Douglas [], which found that FOMO was a positive predictor of smartphone addiction, and that smartphone addiction predicted smartphone behavior. Thus, adolescents who are high in their fear of missing out are more likely to overuse the social media and smartphones, which in turns leads them to phub their offline interaction partners []. Scholars in the field of problematic media use research advocate to invest greater effort into the study of the pathways that lead to problem behavior []. Our study findings represent such an effort, as they reveal that FOMO is an intra-personal characteristic that leads to phubbing behavior by inducing excessive, uncontrolled social media use.The findings reported in this study are generalizable as they stem from a large-scale survey study that was administered to representative sample of Flemish teenagers. There are a number of limitations to the current study, however. We used a shortened, four item version of the FOMO-scale developed by Przybylski et al. [] to assess teenagers’ FOMO. The internal consistency of the scale was unsatisfactory, which increases the risk of underestimating the real relationship (see Schmitt []). The low internal consistency for our scale illustrates the importance for research in this field to use complete and validated scales—for the reason of making reliable claims about one’s study, and for enabling valid comparisons between studies.In light of the unsatisfactory internal consistency of our FOMO-scale, we tested Hypotheses 2 and 3 using both the scale variable and the individual items. This analysis revealed that for one item the relationship with phubbing behavior was reversed: The more teens agreed to feel bothered when missing an opportunity to meet with friends (i.e., indicative of a greater fear-of-missing-out), the less they report phubbing their interaction partner during a face-to-face interaction. This finding indicates that some teenagers attach great importance to face-to-face interactions with friends, leading them to prioritize these interactions over smartphone interactions. This finding suggests that it is relevant to further investigate how FOMO relates to relational behavior, not only online (in the form of social media use), but also offline.Second, our study used a narrow definition of social media [], which excludes mobile messaging applications. It is likely that those with a greater FOMO also heavily rely on the use of these messengers to soothe their anxieties about what others in their social networks are doing. The latter applications are different from social media, however, in that they are oftentimes used for small-group communication, and therefore are more dialogical in nature []. It is more difficult—if not impossible—to “lurk” in dyadic and small-group conversations, as they generally rely on a certain degree of reciprocity. With respect to FOMO, this difference in the interactional affordances of social media platforms and (mobile) instant messengers raises interesting questions. It may be the case that people with a high FOMO are particularly attracted to social media because they can lurk on these platforms without risking a label of “voyeur”, and without having to engage in reciprocal disclosures about themselves. As mentioned above, it seems relevant to explore the difference between FOMO and sociotropy [] in this context, as active disclosures on social media platforms and messaging platforms may provide sociotropic individuals with a means to gather the social approval they long for, while those with a high FOMO may seek information about other people’s experiences without necessarily wanting to engage in interactions with them. Future research may explore this. In short, this study is valuable because it provides generalizable findings on the relationships between FOMO, social media use, PSMU and phubbing behavior among teenagers. As such, it can serve as a starting ground for future research. This research needs to look into the pathways via which FOMO leads to particular forms of (problematic) media use, and how these pathways are similar to or different from other pathways.6. Conclusions 6. ConclusionsTo conclude, and on the basis of the findings presented in this article, FOMO is an important factor explaining teenagers’ social media use. The present study found support for the hypothesis that teens who have a greater FOMO use a wider variety of social media platforms. Also, the present study found partially support for the hypothesis that teenagers with a higher FOMO use social media more frequently: FOMO was identified as a predictor for the frequency of use of some, but not all social media platforms examined. In particular, there was a consistent relationship between FOMO and the usage frequency of Facebook, Snapchat, Instagram and YouTube. Moreover, FOMO was found to predict PSMU. This result aligns with the findings from other recent studies which showed that greater FOMO is associated with more problematic internet and smartphone use [,,]. Finally, FOMO was associated with phubbing behavior. Our results additionally showed that the relationship between FOMO and phubbing behavior was mediated by PSMU. Teens who are high in their fear of missing out are more likely to overuse the social media and smartphones, which in turns may lead them to phub their offline interaction partners [].
DA: 77 PA: 16 MOZ Rank: 89
https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7838524/
1. Social Media: An Increasing Phenomenon in Human Behavior 1. Social Media: An Increasing Phenomenon in Human BehaviorIn our global digital world, social connections are embedded within the external environment we are physically engaged in and the life that we virtually share on social media. Social media is a class of mobile and Internet-based applications that allow people to receive information and to build and share user-generated content. Through the creation of a virtual profile, it is possible to interact with real-life friends, meet new people from all over the world, connect with one's favorite celebrities, and to maintain both online and offline relationships. Since 2004, the use of social media has been increasing rapidly, with the possibility to be connected to the Internet anytime and anywhere. According to the nature of the content, the user can choose, from a wide range of applications, the platform that best suits the purpose of the communication. For example, Facebook is more focused on real-life friends and relatives and encourage interactions through services such as sharing pictures, videos, status updates, and joining groups with specific interests. Social platforms like Twitter, which are also known as “microblogs,” are characterized by brief communication. Other applications, like Instagram or Snapchat, provide photo- and video-sharing services, together with the possibility to like, comment, and re-post preferred content. shows the popularity of the leading social networks, ranked by the worldwide number of active users (source: ).Number of people using social media from 2004 until the end of 2019; estimates correspond to monthly active users, defined as those who logged in during the past 30 days. Source: Esteban Ortiz-Ospina (2019)—“The Rise of Social Media,” published online at and retrieved from .Social media platforms are widely used across different age groups and cultures, but especially for children and teenagers, online communication represents “a window into the secret world of adolescent peer culture, even as it offers young people a new screen for the projection of adolescent developmental issues” (). While social media offers tremendous potential in allowing self-expression of personality and maintaining contact with a network of friends, some studies have also highlighted the risk of negative consequences of excessive online social platforms usage (, ). Online social interaction, the blurring of lines between offline and virtual life (, ), and the concept of digital identity () have become topics of great interest in psychology and mental health fields (). Researchers in the field are attempting to find a consensual definition of the concept of “problematic social media use,” as it is often confused with a description of addictive behavior related to general Internet services, which has been included in the 5th edition of the Diagnostic and Statistical Manual of mental disorders (). In accordance with a biopsychosocial framework, problematic use of social media involves a set of alterations affecting biological functions (i.e., neurotransmitters regulation and circadian rhythm); cognitive, psychological, and affective mechanisms (i.e., attention, salience, mood fluctuation, and anxiety), and aspects related to the social sphere (i.e., social desirability, popularity, and conflicts), resulting in a decreased perceived quality of life. Feedback from people belonging to the virtual social community can affect individual self-esteem and, generally, well-being (–). A problematic use can also affect other aspects of a teenager's daily life, such as academic performance, time management issues, procrastination, distraction (), and sleep disturbances (). In severe cases, averse outcomes could arise and, if prolonged, can become highly impactful, with the further risk of developing psychiatric disorders (). As the Internet and social media are a recent phenomenon, it is more likely that the effect of excessive or problematic usage will affect individuals during more sensitive temporal frames, such as childhood and adolescence. A survey conducted in the United States in 2018 reported that 45% of the teenagers interviewed say they are almost constantly online, without differences among sexes, ethnicities, family incomes, and parental level of education (for the full report, see Teens, Social Media & Technology 2018). Given the continuous exposure to the virtual environment, it is essential to understand the impact that online social relationships have on mental health and interpersonal functioning in developmental stages. The aim of our review, compared to other recent publications [see (, )], is to provide a detailed overview of not only the effect of social media in general but also of the associations between specific platforms and psychopathology. We believe that this point is relevant, as it is important to distinguish among the different social media platforms given that each of them has specific, unique features that drive young users' preferences. Furthermore, social media usage is often included in the broader category of Internet usage, despite the social connotation that primarily describes and defines these kinds of sites. Moreover, the included articles were discussed according to specific disorders that can develop during childhood and adolescence, not merely depression and anxiety that are the most explored disorders but also addictive behaviors toward substances and eating disorders (EDs), as both start to develop during adolescence. In fact, developmental stages are more vulnerable to environmental insults just because of the greater plasticity of the central nervous system, the multiple biological changes, and the formation of psychological mechanisms that drive social behaviors (, ). Due to the differences that define each platform, one of the main purposes of the present review is to provide evidence related to targeted social media services, instead of a more general discussion on social media. In fact, we retain that the multifaceted manifestation of diverse psychological issues might be expressed differently through the multiple ways of communication, such as text, video, or picture. As social behavior and the risk for psychiatric disorders is related to the activity of determined brain regions and biological features (, ), and since we are addressing the outcomes of problematic social media usage (PSMU) under a biopsychosocial perspective, we will also provide an overview about the neuroscientific and gene-by-environment contribution to the interplay between social media and the development of psychiatric disorders in adolescence.2. Methods and Results 2. Methods and ResultsThe review adopted the Preferred Reporting Items for Systematic reviews and Meta-Analyses (PRISMA) model in conducting a systematic literature review. A search of four scientific electronic databases yielded 42 papers for qualitative evaluation. We searched PubMed Central, PubMed, PsycInfo, and Scopus databases for articles on psychiatric disorders in youths related to social media. Since this topic embraces multiple fields, such as computer science and information and communication technologies, we also browsed the Association for Computing Machinery Digital Library and the Institute of Electrical and Electronics Engineers Xplore Digital Library to find relevant research articles in the proceedings of conferences focused on the role of social media in explaining psychological issues in the developmental age. We comparatively analyzed the literature from 2006 up to the end of July 2020, combining different keywords and Boolean operators. A database was generated by combining terms and Boolean operators, such as “social media” AND “child*,” “social media use” AND “child*,” “social media” AND “disorder” AND “youth*”. To include more targeted records, we conducted a further search on the same databases using terms describing the specific issues we meant to address in this review: (“YouTube” OR “WeChat” OR “TikTok” OR “Reddit” OR “Pinterest” OR “Facebook” OR “Instagram” OR “Twitter” OR “Tumblr” OR “MySpace” OR “Whatsapp”) AND (“psychiatric disorder” OR “mental health” OR “psychological well-being”) AND (“adolescent*” OR “youth*” OR “teenager*”).2.1. Eligibility CriteriaFrom a methodological perspective, studies had to fulfill the following criteria to be included: journals and proceedings of conference papers published up to the end of July 2020, published in English, and meeting the following criteria:participants: children and adolescents until the age of 19 with a profile on at least one of the most popular social media platforms (Facebook, YouTube, WhatsApp, WeChat, Instagram, Twitter, TikTok, Tumblr, Reddit, Pinterest, Snapchat, MySpace, Q-Zone); we opted to consider the age of 19 as the upper limit of adolescence, in accordance with the definition provided by the World Health Organization ;interventions: assessment of psychiatric disorders in the developmental ages (depressive symptoms, anxiety and related issues, EDs and body dissatisfaction, neurodevelopmental disorders, substance misuse or abuse);comparison: it is not applicable, as we only included studies based on the sample of social media users;outcomes: we considered the levels of psychological well-being or diagnosis of psychiatric disorders as the outcome;study design: we included studies containing quantitative approaches to produce empirical data and qualitative designs.2.2. ResultsFor the selection procedure for the included articles, please refer to . In the results, we will discuss only the studies resulting from the literature research. In , all the articles included in the review are listed, together with the principal information. Effect size computations for each study have been performed using an effect size calculator () or calculated manually. When more variables were analyzed in the study, we reported the range of values for effect sizes (Cohen's d). Disorders will be discussed in distinguished macro-categories, divided by diagnostic class, according to the DSM-5(). Relevant topics such as involvement/changes of neural correlates and genetic contribution will also be discussed. A total of 31,823 papers were screened by title and abstract, 1,394 were considered for further screening, and 511 duplicate papers were removed. Note that 839 papers were removed after assessment for eligibility according to the exclusion criteria, resulting in 44 papers included in the review.Flow chart of procedural articles shortlisting according to the Preferred Reporting Items for Systematic reviews and Meta-Analyses (PRISMA) guidelines.Table 1List of the studies included in the review.nArticleAgeNSocial mediaDisorder/symptomsFindingsES1Szwedo et al. ()13/2089, MSDepressive symptoms, social anxiety– (depr); + (s.anx)0.40–0.602Moreno et al. ()18–1966Alcohol use+0.723Pumper and Moreno ()12–14315Alcohol use+0.154Tiggemann and Slater ()13–151,087, MSBody image concerns+0.265D'Angelo et al. ()18–19312Alcohol use+0.206Huang et al. ()14–151,563, MSAlcohol and cigarette usensna7Birnbaum et al. ())12–2180, , Psycotic-spectrum and mood disordernana8Nesi and Prinstein ()12–16619, Depressive symptoms+0.539Bert et al. ()18341Pro-anorexianana10Ehrenreich and Underwood (2016)18125Internalizing symptoms+0.5811Frison et al. ()12–191,612Depressive symptomsns0.5812Marczinski et al. ()19146Alcohol use+0.4413Moreno et al. ()17–1994, Alcohol use+0.47–0.9214Naeemi and Tamam ()13–16401Psychological well-being–0.6715Sampasa-Kanyinga and Chaput ()11–194,468, , , Body image concerns+0.3916Abar et al. ()19252Substance usenana17Frison and Eggermont ()12–19671Depressed mood+0.4218Gul et al. ()13–19289ADHD+0.6919Jacob et al. ()16–2421Self-injury+na20Nesi et al. ()15–16658Alcohol use+0.4321Nesi et al. ()13–16816, Depressive symptoms+0.8522Pontes ()10-18509Depressive symptoms, anxiety+0.62–0.6823Spilkova et al. ()164,887, , , Binge drinking, marjiuana use+ (drink); ns (marj)0.8824van Rooij et al. ()12–153,945Depressive symptoms, social anxiety+0.45–0.9525Weinstein ()14–18507Depressive symptoms+0.6826Brown et al. ()1652Self-injury, suicidal ideationnana27Muzaffar et al. ()12–20102Depressive symptoms, social anxietynsna28Niu et al. ()12–18764QZDepressive symptoms+0.4429Settanni et al. ()15283ADHD symptoms+0.5630Chang et al. ()12–16303Body esteem–0.5831de Vries et al. ()12–19440Body dissatisfaction+0.4932Louragli et al. ()12–19541Anxiety, nomophobia+0.50–0.9833Negriff ()13/21319Depressive symptoms-0.5834Przepiorka and Blachnio ()12–17426Depressive symptoms+0.8335Raudsepp and Kais ()13397, , Depressive symptoms+0.7236Savolainen et al. ()15–254,816, , , Alcohol use+0.12–0.4337Shakir et al. (2019)12–18537, , , , Cyberbullyingnana38Steers et al. ()17–19316alcohol use+0.6939Vannucci and Ohannessian ()11-141205, , , , Depressive symptoms, panic disorder symptoms+0.28-.9240Yurdagül et al. ()14–19491Depressive symptoms, anxiety, social anxiety, body dissatisfaction+0.28–0.5041Boursier et al. ()13–19693, , , Body image concerns+0.3642Fardouly et al. ()10–12528, , Depressive symptoms, social anxiety, body satisfaction+ (depr.); ns (s.anx); – (body)0.43–0.8243Stockdale and Coyne ()17/19385, , Depressive symptoms, anxietyns (depr.); + (anx)0.3644Brown et al. ()1659Self-injurynanaAge, range of age of the participants; N, sample size; ES, effect size; +, directly proportional; –, inversely proportional; ns, non-significant; na, not applicable; , Facebook; , Instagram; , Twitter; , YouTube; , Snapchat; , Tumblr; , Skype; MS, MySpace; QZ, QZone. Icons of social media platforms have been created using the fontawesome package ().2.3. Depressive Symptoms and Mood DisordersDepression is a prevalent mood disorder, in which symptoms include persistent sadness and a loss of interest in activities that the person enjoys typically, together with the inability to carry out daily activities (). With regard to childhood and adolescence, interpersonal models of depression in developmental ages accentuate the cyclical associations between social experiences and depressive symptoms. New schemes in the interpersonal environment, with more articulated, frequent, and unsupervised contacts, may represent a further complication as the influence of peer relationships may affect a person's identity and psychological well-being (). As depression and internalizing symptoms have increased among youths in the last decade (), it is vital to question to what extent social media usage is directly linked to this and to understand how they impact each other.2.3.1. Effects of Social Media Usage on Depressive Symptoms Given that social media provide users with a range of possible activities, it is possible to identify specific patterns of usage. For instance, a set of actions such as browsing other users' photos or scrolling through comments or news feeds has been labeled as passive social media use. Recent research indicates that this sort of behavior and depression are linked in both directions. Passive social media usage could directly aggravate depressive symptoms, like loss of interest or blue mood, and thwart personal well-being (, , , ). High social media use appears to be predictive of depressive symptoms and low offline social support from both family and peers (). It might also act indirectly through mediators such as reduced sense of belonging (), hence increasing levels of loneliness first () and, subsequently, depressive mood and stress (), which, in turn, reinforce each other ().2.3.2. Effects of Depressive Symptoms on Social Media Usage Passive social media use appears to be increased by depressive symptoms, loneliness, and high levels of stress. In a longitudinal study, Kross and colleagues have demonstrated that a sense of loneliness is a predictor for more intense usage of social media (), as it might represent a solution to alleviate depressed mood, reinforcing PSMU (). Specific kinds of actions on social media, related to the peculiarity of the site, were found to be associated with adverse emotional and relational outcomes at different times and vice versa. With regard to Instagram, Frison and Eggermont reported that former browsing behavior was related to a later increase in depressed mood (). Moreover, levels of depressed mood at Time 1 were associated with increased Instagram posting at Time 2, without differences between boys and girls (). As for Facebook, levels of depressive symptoms at the first stage can be predictive of a lower number of Facebook friends and fewer ties between friends in the second stage (). Another study based on Facebook data highlights the relationships between internalizing symptoms and online communication in terms of received comments offering support in response to posts indicating negative or depressive emotional states, with girls receiving more backing compared to boys. Such rumination-like behavior through social media might affect negatively not only the mood of the person who posts but also of those who respond, increasing levels of internalizing symptoms and depression (). Depressive symptoms, together with sleep problems, can represent a positive predictor for excessive involvement in Facebook-related activities (). Similarly, emotional dependence on Facebook has been found to be negatively correlated to several aspects of adolescents' psychological well-being, such as autonomy, purpose in life, positive relationships, personal growth, self-acceptance, and ability to manage one's environment (). An addictive attitude toward Facebook was found to be positively correlated with depression, regardless of age (age range 10–18) and gender (). Longitudinal research on adolescent girls found an association between changes in PSMU and changes in depressive symptoms in both directions, with baseline levels of depressive symptoms being predictive of PSMU ().2.3.3. Social Comparison and Negative Affect Social comparison is a mechanism highly involved in the development of a person's identity starting from childhood, where evaluations are more distorted especially in a positive way, throughout adolescence, when the greater development of cognitive skills permit the generation of more realistic estimates (). Social comparison, as a consequence, can generate both a positive or a negative self-appraisal, affecting the way people, especially teenagers, perceive themselves and their quality of life. Evidence in literature suggests that PSMU and depressive symptoms might be mediated by social comparisons with others' lives as they appear on their profiles (, , ), generating a sense of inferiority and feelings of worthlessness (–). As a consequence, people showing downward social comparisons are more likely to seek offline feedback for reassurance (). Social comparison is closely linked to self-esteem, which, in turn, resents of the effect of individual cognitive appraisal, acting as a moderator in the processing of comparison. As a consequence, lower levels of self-esteem can represent a risk factor when making comparisons with others' lives (). These results appear to be more evident in girls, compared to boys, (, ) suggesting that intrinsic features of female identity development can represent a vulnerability for a more negative self-appraisal, especially when comparing or evaluating physical features or attractiveness (, ). Moreover, it is possible that online parasocial relationships may amplify distorted perceptions, due to the filtered and selective nature of the information shared, principally when evaluating profiles of users that do not belong to a close or offline network ().2.3.4. Controversial Results in the Association Between Depressive Symptoms and Social Media Usage Amid the research investigating the connection between social media usage and depressive symptoms, a few studies reported no evidence linking social media sites and depression. A recent study investigated the relationships between reasons for Facebook use and psychological and mental health outcomes for a 3-year period in late adolescents, aged from 17 to 19 years. According to their results, none of the possible motivations, which were social connection, boredom, and information seeking, were correlated to depression at any stage of the experimental procedure (). As for the short-term consequences of negative experiences on Facebook, online peer victimization is not predictive of increased depressive symptoms after 6 months (). In addition, Fardouly and colleagues did not find differences between users and non-users of the most popular social media platforms (Youtube, Instagram, and Snapchat) among Australian preadolescents in terms of depressive symptoms. Taken together, these results suggest that low mood derived from social media usage might be explained through different factors, such as worry about how youths appear on their preferred social networks sites and their tendency to compare their own image to someone else's image (). Finally, a longitudinal study by Szwedo and colleagues investigated the preference for Facebook and/or MySpace communication in a cohort of adolescents in relation to depressive symptoms, assessing the sample at the age of 13 (Time 1) and 20 (Time 2). Interestingly, higher depressive symptoms at Time 1 predicted a preference for communication via social media, but at Time 2, higher depressive symptoms were predictive of lesser online disclosure (). This change in direction might be explained by the different ways, especially social withdrawal, through which depression is manifested in early adolescence and early adulthood. With regard to psychotic and non-psychotic mood disorders, social platforms such as Facebook and Twitter represent an initial avenue to seek help by diagnosed youths () and a potential base to examine depressive symptoms and perceived social support from online friends ().2.4. Anxiety DisordersSymptoms relating to anxiety often overlap with depression, especially in youths; just like depression, anxious manifestations may result from a set of internal and external circumstances. In social media, where the relational component is strong, anxiety can derive from a perception of being connected inappropriately, from negative online peer-comparison, or from reduced emotion-regulation abilities, as online interaction can be used as a surrogate for offline physical interaction (). Targeted Facebook features, such as seeking online approval and support through the number of "likes," or only retaining the visibility of posts and pictures that received lots of positive feedback on one's profile, can promote or elicit non-adaptive behaviors (i.e., excessive social comparison and rumination) and increase anxiety-related traits, such as socially prescribed perfectionism, aggravating pre-existing symptoms in youths diagnosed with an anxiety disorder (). Facebook can also be used by teenagers as a pastime when feeling bored: a 3-year study found that usage of Facebook in order to alleviate boredom at stage 1 (17 years old) was correlated with increased levels of anxiety at a following stage (19 years old), indicating that the anxiety might be a secondary product of the problematic use of social media developed over the two time-points (). This could reflect the fact that a 3-year window frame can encompass different stages of a teenager's life, especially when approaching emerging adulthood. As the high school period is over, fewer amounts of structured time, coupled with less monitoring behavior by parents and teachers and greater accessibility to smartphones or other electronic devices, can result in an increase in problematic usage of social media and, as a consequence, underlying anxiety-related mechanisms (). The type and the reiteration of a set of behaviors that Facebook users could engage in (e.g., posting a photo/comment/status update, “liking" behavior, or using the instant message) can be linked with levels of general anxiety. This might be explained by the need to keep worries related to that driving the person to frequently check a previous posting behavior (). With regards to Instagram, which is more focused on visual contents, one study reported a direct association between Instagram usage with general anxiety in boys, while in girls this link was mediated by body image dissatisfaction, leading to different adverse outcomes in the two groups (). This difference between genders suggests that females might be more prone to engage in social comparison, especially when it involves physical appearance. This might be because their perception of their ideal body image as being thin is affected by their excessive exposure to attractive celebrity and peer images on Instagram. Moreover, it underlines once again the importance of considering the possible concurrent mechanisms that contribute to the development of psychological issues.2.4.1. Online Social Anxiety Social anxiety is described by the enduring preoccupation of being judged negatively by others during a social performance or social circumstances (). The worry of receiving unfavorable feedback is even stronger during adolescence, when the identity of the self is developing. Online activity on social media can be very attractive, especially for young people with such fears, as it is possible to share information or content in a more controllable environment. Although this allows people with social anxiety issues to overcome, even partially, the fear of being exposed to public judgment, it can lead to the development of a problematic usage of social media platforms. With regard to Facebook, a longitudinal study by Szwedo and colleagues found that at 13 years of age (Time 1), social anxiety does not explain preference for virtual communications, and at 20 years of age (Time 2), it was positively correlated with a predilection for online relations, especially for those expressing increased levels of maternal behavior undermining autonomy at Time 1 (). Levels of social anxiety in social media young users have been shown to be positively correlated with online behavioral dimensions such as the attitude of comparing one's appearance with other people's pictures on YouTube, Instagram, and Snapchat (). As a consequence, the approach toward social media can be conflicting: the person desires at the same time to be recognized as interesting and “liked,” but would also like to avoid being judged negatively or ridiculed. The awareness of these mechanisms might intensify pre-existing symptoms of social anxiety, leading to non-adaptive patterns of behavior ().2.4.2. Fear of Missing Out and Nomophobia: The Urge to Be Constantly Online The more people share their lives on their online profiles, the more they are at risk of being afraid of missing updates and feeling the urge to check their profiles for feedback (, ). This specific phenomenon has been labeled “fear of missing out" (FoMO), defining the pervasive anxiety experienced by a user when thinking that other people might be enjoying gratifying experiences in their physical absence, pushing him/her to be connected constantly to check upon updates about these experiences, hence fostering the addictive behavior circuit (, –). FoMO has been shown to be associated with the severity of Facebook usage through a process that is likely to be activated by users as a way to temporarily compensate or regulate negative affect and anxious manifestations (). Specific social needs may underlie FoMO and reasons for social media usage, like the desire to be popular, or at least not unpopular in the eyes of peers and the need for social affiliation, especially during adolescence when peers acquire greater value compared to the family (). To this purpose, online interaction can represent a constantly available means of gratification but, at the same time, an attractive risk as it might trigger addictive behaviors and aggravate symptoms of anxiety. This combination of behavioral and cognitive patterns, in the context of social media usage, appears to be mediated by nomophobia, which is described as the fear of not being able to use the mobile phone. Evidence in literature reports a direct association among levels of anxiety, addictive behavior toward social media () and nomophobia, with a negative impact on academic performances ().2.5. Feeding, Eating Disorders, and Body DissatisfactionAdolescence is a temporal frame during which physical changes and identity development occur, and teenagers acquire a greater awareness of the body, both their own and those of their peers (). Posting pictures on social media is one of the most common practices among young people, especially self-photos (commonly known as “selfies”) (). Exposing and being exposed massively to pictures of body might lead to negative outcomes, such as body image dissatisfaction, defined as “the discrepancy between identification of one's own figure (actual) and the figure chosen as the desirable self-image” (), or alterations in nutrition habits, to the extent of the development of EDs. With regard to Instagram, body image dissatisfaction mediates the relationship between PSMU and internalizing symptoms differently in males and females, with the latter showing a stronger indirect effect (). Evidence from a study involving Singaporean girls showed that selfie practice on Instagram (browsing and editing) and body esteem are mediated by appearance comparison operated by peers' groups with a negative association, while posting self photos and body esteem are directly correlated (). With regard to Facebook, Tiggemann and colleagues investigated social media exposure and body image concerns in girls, finding that time spent on the online platform was strongly correlated to body surveillance and the ideal of a thin body shape (). An analysis of a Canadian sample of teenagers highlights that more frequent and prolonged usage of social media services is associated with body dissatisfaction, with a trend to perceive oneself overweight in both boys and girls (). Recent findings from a study by Fardouly and colleagues indicate that more frequent appearance comparisons with others on social media and considering them to be more attractive than oneself is negatively correlated with body image satisfaction and positively linked with eating-related disorders in both male and female teenagers (). Evidence from a sample of Italian adolescents highlights the role played by appearance control beliefs and body image control in photos, as these dimensions could be configured as predictors of problematic usage of social media and negative mental health outcomes (). Overall, the findings indicate a higher vulnerability for girls to develop a negative image of their own body. This risk can be compounded by misleading and harmful content that can be found on social media.2.5.1. Presentation of Eating Disorders on Social Media Platforms In recent years, groups supporting anorexia nervosa in several ways (endorsement and promotion of dysfunctional eating behavior, maintenance of the disorder, and interference with recovery) have been spreading across social media platforms. The dynamics of the Proana Movement, which promotes behaviors relating to anorexia nervosa, have been examined using Twitter, finding that adhering people and/or promoters were almost totally teenage girls (). In the midst of the factors mediating the risk to develop body dissatisfaction or EDs, one study focused on teenagers' offline social environment, finding that a positive mother-adolescent relationship can exert a protective function against the adverse effects of social media usage on body perception (). An alarming factor is determined by the support of pro-EDs in online networks. As popular platforms started blocking pro-ED related terms, users supporting dangerous eating habits have begun altering the hashtags, bringing forward their approval toward endangering conducts. On the other hand, it is not unusual that people rehabilitating from an ED seek support during their journey to recovery by sharing their testimony through textual posts or visual media (i.e., pictures, video, and gif). This dual nature of online communication represents a great challenge for research, as the analysis focused uniquely on hashtags may be misleading (). Moreover, people supporting ED behaviors often alter the terms in hashtags or post them in comments in order to overcome social media censorship policy, with a possible risk to expose more fragile or sensitive people to explicit content.2.6. Alcohol Use/Abuse and AddictionAdolescence is the stage of life where people gain more independence and make new experiences in their social environment, where peer influence might encourage and provide opportunities to come into contact with alcohol, potentially leading to the development of an addictive behavior toward the substance. As the social environment is now composed of two realities, online and offline, it is crucial to understand the contribution of social media in fostering, maintaining, or conveying contents related to substances. Studies on drinking behavior among teenagers and social media use highlight that online platforms like Facebook might represent a helpful tool to detect problematic alcohol use (, , , , ), or advertise for healthy behavior in settings such as popular alcohol-related events and parties (). A higher number of alcohol-related posts has been shown to be linked to greater drinking conduct and approval from friends, although heavier consumers seem to tend to post less over time compared to light drinkers (). A longitudinal study revealed that in the Facebook profiles of individuals identified as dependent alcohol users, alcohol references increased and half of those identified referenced intoxication or problematic drinking after 1 year (), while another longitudinal study indicated that alcohol references at a first stage can predict binge drinking later in time (). With regard to alcohol-related attitudes, binge drinkers appear to be more prone to use social media excessively (). Moreover, posts containing references to alcohol predict the number of weekly substance consumption (), the risk of developing an addiction, and alcohol cravings (). In order to predict drinking conduct, Marczinski and colleagues have developed the Alcohol-Related Facebook Activity (ARFA) questionnaire () based on a sample of college students. The preference for the virtual environment as a platform to share alcohol-related experiences has been studied by Moreno and colleagues, who report that students owning a profile on both Facebook and Twitter tended to post more alcohol references on Facebook compared to Twitter (), as they were entertaining more social connections on the former site. Online social networks often include connections with offline friends; therefore, the exposure to a friend's drinking pictures or posts can be associated with higher alcohol consumption (, ). Risky alcohol behavior can differ according to the country; a cross-cultural study examined the relationship between daily usage of popular social media platforms and alcohol consumption among youths in the United States, Spain, Finland, and South Korea. In the targeted countries, the different platforms were correlated with greater hazardous alcohol usage as follows: Facebook and Instagram in Spain, Finland, and South Korea, YouTube in South Korea, and Twitter in Spain (). These results suggest that specific social media sites might play an attractive or inspiring role in risky alcohol consumption but, on the other hand, they could also turn out to contribute greatly to online-based interventions. According to a study on nicotine, alcohol, and marijuana consumption in high school, being friends on Facebook with one's own parents and not hiding contents can represent a protective factor against substance use (). Parental inclusion on social media interactions, without undermining autonomy and privacy of youths, can depict an important element in substance use prevention targeted toward youths.2.7. Self-Harm and Suicidal IdeationAmid the psychological issues potentially occurring in young people, self-harm is a primary concern, with harmful behaviors lying on a continuum between non-suicidal self-injury (NSSI) and suicidal intention (). Social media can influence self-injury tendencies negatively, through fostering conducts, contagion, or competitions (), but they can also represent the first foothold when support is needed. A study based on the analysis of MySpace profiles indicates that teenagers utilize personal virtual space to share their suicidal ideation and behaviors directly or by reporting desperation, hopelessness, and despair (). From the interviews with adolescents recently collected by Jacob and colleagues about self-harm behaviors, it emerges that Tumblr is the preferred platform to share self-injuring content, like pictures, in an anonymous way, with the consequent risk to normalize such harmful behaviors (). Looking into the motives that push young people to share self-injury related content such as their own wounds on Instagram, there are mostly social purposes, like the need to belong to a group where the person can feel understood (). Another reason might be the need to self-disclose in an environment that can guarantee anonymity. These reasons are reported to be valid both for the first NSSI post and for the general NSSI ones. Beyond self-oriented motives, another aim is to raise awareness about the topic in order to help other people (). Although results concerning Instagram do not report any risk for acute suicidality (), photos of self-injury practices might play a reinforcement role as they are often posted () and frequently concealed behind ambiguous hashtags (). In fact, as users often resort to the use of hashtags to track the shared contents and to find images or discussions related to specific topics, those regarding self-harming behaviors can contain non-related words (i.e., “blithe” for self-cutting pictures) or be constantly changed, in order to make them easily accessible only to a restricted community (). Social media-related suicidal behavior is a topic of increasing interest and critical importance that has garnered the attention of newspapers and newscasts all over the world, concerning popular and unpopular people (see for a recent episode). Although researchers attempted to study the extent of social media on suicidal behaviors in-depth, complexities derive from legal and privacy issues, as well as from the indirect association between the usage on web-based platforms and the suicide itself ().2.8. CyberbullyingSuicidal ideation can also derive from the non-adaptive usage of online communication by others, as in the case of cyberbullying. Cyberbullying can be defined as the intentional use of information and communication technologies such as electronic mail, smartphone, short message services, and social media platforms, carried out repeatedly by a group or an individual, to support deliberate, repeated, and hostile behaviors against a victim who cannot easily defend him- or herself (, ). Cyberbullying constitutes a possible worrisome phenomenon, given its devastating, occasionally even fatal, consequences on a person's life. Recent statistics point out that cyberbullying is prevalent on platforms based on visual content, such as Instagram (42%), Facebook (37%), and Snapchat (31%) (see . As the contents are shared and spread quickly online, the victim can experience, besides a lack of control, a series of highly negative psychological consequences, such as social anxiety (), depression, and suicidal ideation and attempt, especially when bullying behavior perpetuates across time (, ). An investigation on social media usage and youths' mental health revealed that cyberbullying appears to mediate this relation occurring in a set of negative outcomes, such as sleep problems and anxiety, more than the frequency of exposure to social media itself, with girls being more exposed to these effects (). However, social media started adding certain features including the ability to report inappropriate content, comments, and to block users in order to stem violent and inappropriate behaviors.2.8.1. Safety Measures Adopted by Social Media Sites Initially, the different platforms did not take responsibility for single users' online behaviors. However, the growing prevalence of cyberbullying in recent years has gained increased relevance, resulting in the implementation of several measures aimed at both children and parents. For instance, in 2013, Facebook launched a safety section on its site, providing information on policies, tools to increase profile protection, and relevant resources and contacts to access in the case of cyber abuse (see page). Likewise, in 2015, Twitter activated a safety center for parents and teens with guidelines for a more secure navigation and utilization of the site. Furthermore, they founded the Twitter Trust and Safety Council that works in partnership with several institutions and organizations in order to direct users to the appropriate service in case of abuse (see ). With regard to Instagram, which has been owned by Facebook since 2012, the platform presents the community guidelines and another section where parents can find more information about the accessibility and visibility of their children by other users. Moreover, an online form is available for reporting self-injury material, hate comments, abusive or inappropriate content, and profiles belonging to teens younger than 13 years old, which is the requirement to own a profile (see page). The same subscription criteria are applied to YouTube, although videos posted by other users are accessible even without owning a profile. Because of this, it is possible for parents to set restrictions in order to avoid potentially dangerous or improper material. In addition, together with the site policies, informative material about harmful behaviors such as self-injury, suicide, harassment, and cyberbullying is provided (see ). So far, statistics about the efficacy of these safety measures have not being available. Generally, targeted services for prevention have been made known on the most popular online platforms by providing users with links to websites, hotlines, and information about how to detect warning signs of suicide. Web communities focused on suicide prevention have been founded, giving their members the opportunity to share their own direct or indirect experience in an anonymous way and to support each other, without the constraints of physical boundaries ().2.9. Neurodevelopmental DisordersNeurodevelopmental disorders are characterized by altered functioning of the neurological system and brain, affecting cognitive functions and social behavior. Although social media interfere with offline interaction by reducing the investment of time and resources in them while offering a more immediate alternative to satisfy social needs, they can also simplify the engagement in social contacts. This feature might be suitable, for instance, for youths with autism spectrum disorders, as they can have difficulties in decoding complex social information (, ). As adolescence is a crucial developmental stage where interactions with peers occur both online and offline, it is of pivotal relevance to understand the impact of social media platforms on teenagers with neurodevelopmental disorders. With regard to ASD, evidence shows a positive association between Facebook usage and friendship quality, moderated by anxiety levels, suggesting that online platforms might act as a means to improve friendship quality (). For this purpose, Gwynette and colleagues explored Facebook's therapeutic potential as a tool to improve social skills in adolescents with ASD. Their web-based intervention, according to the authors, could have the potential to facilitate interventions, leading to higher engagement with peers through the virtual environment (). In the context of neurodevelopmental disorders, Asperger syndrome is characterized by significant difficulties in social interaction and non-verbal communication; as a consequence, they could be more vulnerable to cyberbullying victimization on online applications. Findings in the literature suggest that, although adolescents with Asperger syndrome use social media less than their peers, the percentage and frequency of cyberbullying are similar (). Another neurodevelopmental condition is attention-deficit/hyperactivity disorder (ADHD), which is defined by persistent inattention, hyperactivity, and sometimes impulsivity. These features, combined with online-based platforms, might lead to addictive social media behaviors, with further consequences on mental health, productivity, and academic scores (). Studies analyzing the correlation between ADHD traits and social media found that a large number of adolescents with ADHD own more than one Facebook account, showed greater overuse compared to their counterparts (), and ADHD symptoms are positively associated with Facebook addictive use (). Furthermore, teenagers with more marked ADHD traits were more likely to develop problematic usage of Internet-based services and less likely to remit from problematic Internet usage ().3. Gene-by-Environment Contribution to Understand Behavior on Social Media 3. Gene-by-Environment Contribution to Understand Behavior on Social MediaThe hypothesis that genetic features influence behavior and social interactions has been corroborated in several studies [for a review, see ()], and so is the notion that human behavior and psychological traits are modulated by the interaction between genetic variation and environmental factors (). Due to the intrinsic interactional nature of social media platforms, it is important to deepen the exploration of concurrent factors that could explain underlying mechanisms related to online interaction adopting integrated methodologies widely used for offline social behavior, that is, the gene-by-environment interaction framework. Few studies report results about genetic contribution in Internet-related usage. Two studies on Turkish twins on communication and social media reported that genetic and environmental effects were equally influential on problematic Internet usage especially in male twin-pairs (). Another twin study highlighted the impact of genetics on mobile phone use (). These results have been corroborated by a more recent investigation by York, who focused specifically on social media use (e.g., contact friends and contact family) even after controlling for demographic factors (). A recent study by Deryakulu and Ursavaş examines the extent to which nomophobia can be explained by genetic and environmental factors, revealing that the dimensions which were more explained by genes were “losing connectedness” and “giving up convenience,” while environmental factors were more related to the fear of “not being able to communicate” and “not being able to access” (). Familiar context represents a factor of great interest in shaping social behavior, especially at the developmental stage, and perception of parental warmth or intrusiveness can influence social media usage in adolescents. With regard to the genetic contribution within the frame of recalled parental bonding, a recent exploration found that people who are genetically more sensitive to environmental factors, represented by oxytocin receptor polymorphisms, with a history of perceived high maternal overprotection tend to show a higher social desirability index on Instagram (). This index, which describes the ratio between the number of following and followed profiles, could be used for future studies to unveil some tendencies underlying user behavior on Instagram.4. Social Media Usage and Neural Mechanisms 4. Social Media Usage and Neural MechanismsEvidence deriving from the neuroscientific field reveals a link between online social behaviors and regulation of neural mechanisms. A functional magnetic resonance imaging (fMRI) study conducted by Meshi and colleagues reports that social media engagement is linked to activity in the ventral striatum (vSTR) and adjoining structures of the nucleus accumbens (). More precisely, the authors found an association between levels of activation of these areas and in response to social feedback identified that were relevant to participants' social reputation (a surrogate for “likes” on Facebook). Another study describes greater recruitment of the vSTR in relation to more popular shared pictures compared to less socially endorsed ones (). As for structural evidence on gray matter volume and social media habits, the striatal region was found to be linked to daily smartphone checking () and heavy social media usage (). Recent evidence also suggests the involvement of the right lateral orbitofrontal cortex, linking a decreased volume in that area with an excessive usage of social media sites (). With regard to impulse control, reduced gray matter volume in the anterior cingulate cortex was found in people with high tendencies in developing an addictive attitude toward instant messaging services () and “multitasking" users, suggesting that social media usage is highly involved in the control of inhibitory mechanisms (). Another relevant study by Moisala and colleagues on media multitasking showed increased activity in the right side of the prefrontal cortex while participants were subjected to a cognitive task; this result was explained by the authors as a reflection of mental struggle in recruiting resources in executive control (). With regard to social cognition in adolescence, fMRI studies found that online rejection by peers or other users elicits an increased activity in the medial prefrontal cortex, which is strongly associated with offline rejection (), and elicits neural responses in the dorsal anterior cingulate cortex, the subgenual anterior cingulate cortex, and the anterior insula, which are areas generally linked to “social pain” (, ) and depression (). The immediate and long-term effects of frequent and prolonged social media usage on neural structures and activity have yet to be elucidated.5. Conclusion 5. ConclusionIn just one decade, individuals' lives and their social behavior have been tremendously changed by the phenomenon of social media. Emerging technologies and platforms provide users with a wide range of activities, leisure, and the possibility to interact with friends, families, or strangers. Although different patterns of usage are moderated by a set of individual features concerning genetic, environment, temperament, and personal needs, it is undeniable that online social media have become an integrated part of people's daily lives. This leads to the necessity, in research fields linked to human behavior, to understand if, how, and to what extent these platforms are modifying our brain mechanisms, interactions, and the concept of well-being. During developmental stages, such as adolescence and early adulthood, several changes occur not only with regard to neural functions but also in social patterns, as young people have increasing opportunity to test themselves as individuals in more autonomous social interactions. As for social media, the most popular platforms require users to be at least 13 years old to own a profile and have access to the services. Although this limit is easily bypassed, it is difficult to have a clear overview of the sociodemographic information of young users and of different patterns of usage or effects of social media in early adolescence (10–14), middle adolescence (15–17), and young adulthood (18–21), as the early adolescence population should not be able to access and be engaged in virtual interactions on such platforms. This issue rebounds in a lack of studies considering this distinction, representing a further challenge to future research. Lots of efforts have been invested in creating new tools for assessing people's attitudes toward social media usage, such as the creation and validation of new scales (, –) and to interpret results within a fitting theoretical frame. Social media provide unprecedented opportunities to trace online activity and to keep track of interaction dynamics at different stages. This allows researchers to overcome issues related to self-report questionnaires and to benefit from leveraging real-time data over time more easily. Specifically, the increasing utilization of hashtags might help in detecting and monitoring targeted topics or risky behaviors, despite the risk of misappropriate use of words (for instance, sometimes people refer to “anxiety" or “depression" when perceiving alterations in preoccupation or mood but with these not being of clinical interest or diagnosed. For sure, the use of hashtags is a powerful tool to build communities and support people's journey to recover, to witness, to join a cause, or to increase awareness around a specific topic related to mental health. As the number of social media applications increases, with each having its own specific features, there is a need to separate problematic behaviors or effects according to the platforms. In fact, since the advent of social networks sites, multiple platforms have succeeded one another, gaining immediate popularity. Some of them are not used anymore, such as Google+, or had a drastic loss of users, like MySpace. Lately, a new social network site named TikTok, formerly known as Musical.ly, has risen especially among the youth, changing to some extent the way social media are used. From the simple sharing of text, music, or pictures, social media has rapidly evolved, becoming more dynamic and providing the possibility to get immediate and abundant feedback, to join wide online communities based on common interests, and to involve users' talents or attitudes with so-called “challenges." Although TikTok had gained terrific popularity in the course of the last year, no studies regarding the potential outcomes deriving from a problematic usage are available. As social media sites are quickly developing, research appears to struggle in keeping pace with not only the new online functionalities but also with ways of interactions among users that, in turn, might alter parameters in longitudinal studies, like the amount of time spent online. This is partially due to the fact that effects can be explored in terms of both a short and long term, each with different consequences. Moreover, the social media platforms resent of the users' preferences and mass tendencies, and what is new and trendy today might swiftly lose people's interest (). Since keeping track of how communication technologies evolve across the years can be a precious resource on developmental trajectories, it becomes of great importance for researchers to build and rely on constantly updated evidence. The creation and rise of new technologies has resulted in new behaviors and, consequently, new names for these behaviors. Neologisms like “nomophobia,” “selfie,” “phubbing,” “FoMO,” and “vaguebooking” have appeared for some years, defining specific behaviors or state of minds, that need further analysis, as they represent new, unexplored facets of human behavior. Research in psychological fields would also benefit from the exploration of specific types of interaction, such as the creation of multiple accounts, the fruition of live streaming video services, and behaviors like un-tagging people from posts or pictures or unfollowing/unfriending people in order to better understand the effects of mechanisms related to virtual social inclusion or exclusion. Although social media allows for greater ease of recruitment and testing of a greater number of participants in more efficient ways—sometimes comparable to laboratory testing sessions ()—a lack of knowledge still persists regarding the involvement of specific brain regions or genetic susceptibility in developing a certain social media-related disorder. In addition, only a few studies adopted a longitudinal design, while most of the evidence is still based on a cross-sectional methodology that does not fully allow researchers to study in detail the direction of the association between social media usage and psychological well-being. Furthermore, the mental health community should commit to find a solution in considering social media-related issues as being separate from other forms of problematic online behaviors or usage. As there is no separated diagnosis, social media concerns are often included or subsumed within the Internet addiction frame, leading to an incorrect framing of the problem, especially with regard to the social connotation that primarily describes and defines these kinds of services. New evidence in these fields would be of great support for practitioners in a twofold way: on the one hand, information shared on social media sites and patterns of usage of new technologies could be implemented in clinical work for both a more complete assessment, and, on the other hand, it would be possible to profile more user-based interventions merging both online and offline strategies.
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https://www.indiatvnews.com/technology/apps-how-to-change-instagram-logo-655161
Oct 07, 2020 . Instagram is in the celebration mode on its 10th birthday and introduced a fun thing to try out on the app. Read on to know more about it. Vanshika Malhotra @vanshika1628 New Delhi Updated on ...
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https://www.fvtc.edu/courses/health-science/31-509-1/medical-assistant
With this diploma, you become an essential part of the healthcare team. Your role is to take vital signs, assist the physician with examinations and minor office procedures, and administer medications. This career combines business and administrative duties with clinical laboratory functions. You’ll learn the necessary office skills as well as specimen collection, basic lab tests and ...
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https://www.humanresourcesonline.net/sops-for-vaccinated-individuals-in-malaysia-phases-1-2-and-3-aug-2021
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https://oncologypro.esmo.org/education-library/factsheets-on-biomarkers/microsatellite-instability-defective-dna-mismatch-repair
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https://www.scienceforsport.com/star-excursion-balance-test/
Oct 02, 2016 . Test Procedure. Warm-up. Participants should thoroughly warm-up prior to the commencement of the test. Warm-ups should correspond to the biomechanical and physiological nature of the test. In addition, sufficient recovery (e.g. 3-5 minutes) should be administered following the warm-up and prior to the commencement of the test. Conducting the test
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https://aacnjournals.org/aacnacconline
Call for papers. AACN Advanced Critical Care is seeking submissions.Please review our list of topics.. COVID-19 resources Please visit our collection of free-access articles related to the care of …
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https://metapress.com/
Nov 18, 2021 . Metapress is a fast growing digital platform that helps visitors to answer questions, solve problems, learn new skills, find inspiration and provide the latest Technology news.
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https://www.calvinklein.us/en
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https://jobs.unchealthcare.org/jobs/6006916-rn-clinical-nurse-iv-team-leader-general-surgery-slash-7-west
Become part of an inclusive organization with over 30,000 diverse employees, whose mission is to improve the health and well-being of the unique communities we serve. 7 West is a 30 bed general surgery/urology unit, currently undergoing renovation. Most co-workers on 7 West are CMSRN certified and are experienced nurses with UNC REX tenure.
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https://www.mintresume.com/resumes/epic-analyst
Create an Epic Analyst Resume. How to write Epic Analyst Resume. Epic Analyst role is responsible for health, analytical, training, reporting, design, education, insurance, travel, software, clinical. To write great resume for epic analyst job, your resume must include: Your contact information. Work experience.
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https://www.sfccmo.edu/academics-programs/one-year/
Year One (Level 1) The successful applicant must have at least a 2.75 GPA for all prerequisite and required courses. An overall GPA of at least 2.5 is required. All science courses must have been completed within the last 10 years at the time of application …
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https://free-litecoin.com/
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https://bmjopen.bmj.com/content/11/11/e052259
Nov 18, 2021 . Introduction The global COVID-19 pandemic has reported to have a negative impact on the mental health and well-being of individuals around the world. Mental health system infrastructure, primarily developed to support individuals through in-person care, struggled to meet rising demand for services even prior to COVID-19. With public health guidelines requiring the use of physical distancing ...
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https://paincarelabs.com/research/
[VibraCool] Patients reported using an average of 10.1±3 opioid tablets in the first week following surgery….and only 4 patients continued to use opioids by their first post-operative visit (4.3±2.3 days post-surgery). In a coached group attempting to reduce opioids at the same institution, the average was 35% higher (15.6±8.5). REFERENCE:
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