Figures
Abstract
Since the outbreak of Covid-19, the use of digital devices, especially smartphones, remarkably increased. Smartphone use belongs to one’s daily routine, but can negatively impact physical and mental health, performance, and relationships if used excessively. The present study aimed to investigate potential correlates of problematic smartphone use (PSU) severity and the mechanisms underlying its development. Data of 516 smartphone users from Germany (Mage = 31.91, SDage = 12.96) were assessed via online surveys in April and May 2021. PSU severity was significantly negatively associated with sense of control. In contrast, it was significantly positively linked to fear of missing out (FoMO), repetitive negative thinking (RNT), and daily time spent on smartphone use. In a moderated mediation analysis, the negative relationship between sense of control and PSU severity was significantly mediated by FoMO. RNT significantly moderated the positive association between FoMO and PSU severity. Specifically, the higher the RNT, the stronger the relationship between FoMO and PSU. The present findings disclose potential mechanisms that could contribute to PSU. Potential ways of how to reduce PSU severity are discussed.
Citation: Brailovskaia J, Stirnberg J, Rozgonjuk D, Margraf J, Elhai JD (2021) From low sense of control to problematic smartphone use severity during Covid-19 outbreak: The mediating role of fear of missing out and the moderating role of repetitive negative thinking. PLoS ONE 16(12): e0261023. https://doi.org/10.1371/journal.pone.0261023
Editor: Frantisek Sudzina, Aalborg University, DENMARK
Received: June 22, 2021; Accepted: November 22, 2021; Published: December 22, 2021
This is an open access article, free of all copyright, and may be freely reproduced, distributed, transmitted, modified, built upon, or otherwise used by anyone for any lawful purpose. The work is made available under the Creative Commons CC0 public domain dedication.
Data Availability: All relevant data are within the manuscript and its Supporting information files.
Funding: We acknowledge funding support by the Volkswagen Foundation awarded to Julia Brailovskaia (JB) (Nr. 99 327). The funder had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.
Competing interests: The authors have declared that no competing interests exist.
Introduction
During the 21st century, smartphones became people’s daily companions. Through mobile Internet access, smartphones allow permanent availability and provide up-to-date news around the globe and in the life of family and friends [1]. Oral communication through phone calls is complemented by typed interaction and exchange of photos and videos anywhere and at any time using various social media applications on our smartphone—that is social platforms such as Facebook, Instagram, and Twitter, as well as instant messengers such as WhatsApp, Telegram, and Signal [2]. In addition to the active online interaction, one can passively observe the online behavior of others by checking their updates. Depending on privacy settings, we can track when our friends are online, and for example whether they have read our recent messages on WhatsApp [3, 4]. To sum up, through the smartphone we can participate in the lives of other people and allow them to be part of our lives [5]. These functions of our smartphone not only satisfy our need for belonging; they also can contribute to the satisfaction of another important human need—the sense of control [6, 7].
Sense of control is an essential element of humans [8]. People want to control the course of events in the own lives and to decide on their own what to do, where to go, with whom to meet and how to present themselves [9, 10]. The lack of control over important life events can be experienced as a high psychological burden and foster symptoms of anxiety, depression, and helplessness [11–13]. Individuals who lack functional coping strategies to regain control, or to manage life despite loss of control, often resort to inadequate and dysfunctional strategies such as substance abuse, overeating or restrictive eating. In the short-term, these strategies seem to reduce negative emotions and provide some control; but in the longer-term, they negatively impact mental and physical health and contribute to interpersonal problems [14–16]. Nowadays, people who experience loss of control in important life areas often gravitate to using digital devices (that is, often and over a long period of time), especially smartphones, as a form of coping strategy [e.g., 17, 18].
Smartphone use allows individuals to escape negative feelings, to forget overwhelming problems of everyday life at least temporarily, and to experience positive emotions [19]. The permanent possibility of social interaction and observation of others’ online behavior can reduce the individual perception of control loss [7, 20, 21]. Previous research assumed that the positive effects can be maintained as long as the intensity of smartphone use remains moderate. However, its increase may negatively impact the individual health and behavior [22].
The Interaction of Person-Affect-Cognition-Execution (I-PACE) model for addictive behavior provides a theoretical framework for this assumption [23]. Following this model and further available research, in the longer-term, due to the interaction between various mediating and moderating factors, excessive use can contribute to development of a strong emotional bond to the digital device, closely associated with habit formation of prolonged smartphone use [21, 23–25]. If this happens, the individual may tend to progressively engage in excessive smartphone use in different situations as an impulsive response, even if alternative behavior would be more functional, reasonable and productive [23]. In addition, non-use can provoke negative consequences such as mental and physical withdrawal, mood deterioration, aggressive behavior, and an unconscious grasp of the smartphone [26, 27].
This phenomenon has been termed as compulsive, dependent, addictive, or problematic smartphone use (PSU) [28]. It is defined by characteristics such as salience, tolerance, mood modification, relapse, withdrawal, and interpersonal conflicts [2, 24]. The characteristics are close to substance abuse [29]. However, addictive use of smartphones has not been recognized as a formal psychiatric disorder in the Diagnostic and Statistical Manual of Mental Disorders (DSM-5; [30]) or International Classification of Diseases (ICD-11; [31]), so far. Moreover, earlier research warned of over-pathologization of the impact of intensive media use on mental health [32, 33]. Against this background and considering the current lack of a standardized term, we will use the term PSU as proposed by Panova and Carbonell [34] and avoid terms such as “addictive smartphone use” in the current study.
Available cross-sectional and longitudinal studies have detailed negative mental and physical health of PSU severity, as well as adverse effects on daily performance in different areas [35, 36]. For instance, PSU severity is positively correlated with depression, anxiety, irritability, and suicide ideation, and it may reduce happiness and life satisfaction [for overview, see 37]. Time spent on intensive smartphone use was negatively associated with sleep quality and sleepiness during bedtime. Its link to daytime sleepiness was positive [7, 36, 38]. Screen time during bedtime was positively related to PSU severity [39]. Furthermore, time spent on smartphone use was negatively related to individual fitness and physical activity, and positively to obesity [40–42]. In addition to enhanced interpersonal problems [43], PSU severity was positively linked to increased procrastination, and reduced academic and work performance [44–46].
Considering these findings and the high involvement of smartphones in everyday life, it seems highly desirable and relevant to investigate potential correlates of PSU severity and the mechanisms linked to its development (mediation and moderation effects) and, therefore, to be able to identify and to protect people at risk for this form of problematic behavior.
In the present study, we will specifically focus on the relationship between sense of control due to important events in everyday life and PSU, because both—sense of control and smartphone use—have become of specific relevance during the global outbreak of the coronavirus disease (Covid-19; severe acute respiratory syndrome coronavirus 2, SARS-CoV-2) in the year 2020 [47, 48].
Notably, the outbreak and rapid spread of Covid-19 required significant changes in everyday life worldwide [49]. Since the beginning of 2020, restrictive rules to fight the pandemic were introduced by many governments and authorities around the globe. Many of those restrictions remained applicable in the course of 2021 [50, 51]. The rules included closing public institutions, recreational venues, shops, and non-essential businesses, bans on traveling and non-family gatherings, overnight or fulltime curfews, as well as behavioral measures such as maintaining distance from other people (“social distance”), and wearing of face masks [52, 53]. While some people quickly adapted to the required changes, others experienced them as a significant psychological burden and loss of control of their daily routine [54, 55].
The need for “social distance” and enhanced staying at home due to home-working and home-schooling resulted in enhanced use of digital devices, especially smartphones, to obtain news, stay in touch with others outside the home via telephony and social media, and as recreation by playing games and watching videos [47, 56]. Also the characteristics of problematic use increased [57]. Based on earlier research [7, 58], it can be assumed that, on the one hand, people who experience the Covid-19 crisis as a significant loss of control might engage in PSU as a dysfunctional coping strategy. On the other hand, individuals with high sense of control might be less at risk for PSU. They could experience the Covid-19 pandemic as less burdensome and tend to functional coping strategies (e.g., maintaining daily routine as much as possible, enhancement of physical activity) [59].
The negative link between sense of control and PSU severity could be impacted by different factors. Based on previous research (e.g., [60, 61]), one such factor might be the fear of missing out (FoMO) that is defined as “pervasive apprehension that others might be having rewarding experiences from which one is absent” ([62]; p. 1841). FoMO is closely associated with the strong desire to know what other people—especially friends—are doing. Satisfaction of this desire contributes to the individual sense of control. The lack of such information and connection can evoke stress, frustration, and uneasiness and negatively impact mental health [25, 63–65]. High levels of FoMO can result in dysfunctional coping strategies such as alcohol abuse [66, 67]. Smartphones that connect us with social media via mobile Internet allow us to permanently update our knowledge of others’ lives, and thus to stay socially involved. Notably, this technical development also means that updates might be missed when we do not visit the online world. This, however, can contribute to enhanced FoMO [62, 68]. As a consequence, FoMO can be reduced by a permanent checking of other people’s updates via the smartphone which, however, may foster the characteristics of PSU such as salience, tolerance and withdrawal [69].
The Covid-19 crisis requires “social distance” to slow down the pandemic spread. Possibilities of social interaction and of receiving updates from other people in-person are strongly reduced. This might enhance the FoMO that results in permanent checking of online updates via smartphone, and, thus, at least partly explain the increase of PSU [18]. Following available findings, low sense of control is positively linked to the experience of FoMO [67]. Furthermore, recent research showed that individuals who experience the Covid-19 crisis and required changes in daily routine as a significant control loss are prone to problematic media use [6]. Therefore, we hypothesized that individuals with low sense of control could be at enhanced risk for FoMO, and thus also for PSU. Specifically, FoMO could mediate the relationship between sense of control and PSU.
A further factor that might be involved in the relationship between sense of control and PSU is repetitive negative thinking (RNT). RNT describes the tendency of perseverative thinking about negative experiences and problems that is partly intrusive and difficult to disengage from [70]. Rumination and worry are two forms of RNT [71]. Rumination is defined as a repetitive thinking in response to sadness and depressiveness. The person focuses on the meaning and implications of the negative mood, and the past events that caused this mood [72]. In contrast, worry refers to negative affect-laden, mostly uncontrollable repetitive thinking that focuses on events with the potential for future negative outcomes [73]. RNT is closely linked to anxiety and depression [71, 74]. It belongs to predictors of dysfunctional coping strategies in stressful situations, for example of problematic alcohol consumption [75, 76]. Moreover, earlier research found a positive association between RNT and PSU severity [77, 78]. Recent studies showed that especially individuals who tend to worry and rumination experience the uncertainly and unpredictability of the Covid-19 crisis as a high burden [59, 79]. By trying to cope with the negative emotions, some of them tend to problematic smartphone use [80]. Furthermore, a positive relationship between rumination and FoMO was reported [81, 82].
Considering the definitions of FoMO [62] and RNT [83], we conceptualized that the negative effect of FoMO on mental health and behavior might be enhanced in persons who tend to RNT. This assumption can be explained as follows. The fear of missing out on important experiences (including important news) is the definition characteristic of FoMO [84]. This fear might also be accompanied by negative mood and thoughts. For instance, because of the missed experience, one could lose connection to other people—the person might no longer belong to the in-group connected by a mutual experience. In addition, one might lose important future opportunities [85]. This could foster specific activities to reduce the aversive state such as PSU that belongs to the easiest ways to do so during the Covid-19 crisis [18]. In individuals with high levels of RNT who are prone to sad mood and an uncontrollable repetition of negative thoughts [71], the urge for these activities—that in the short-term seem to reduce the aversive state—could be especially high. In contrast, people who are less prone to RNT could tend to less dysfunctional coping strategies even if they experience FoMO. Against this background, we hypothesize that RNT could moderate the positive association between FoMO and problematic smartphone use. Specifically, the higher the RNT, the closer the link between both variables.
Considering the presented background and our aim to investigate the mechanisms that are linked to PSU, we formulated the following hypotheses:
- Sense of control is expected to be negatively associated with FoMO (Hypothesis 1a) and PSU severity (Hypothesis 1b). FoMO is assumed to be positively related to PSU severity (Hypothesis 1c).
- Furthermore, FoMO is expected to mediate the relationship between sense of control and PSU severity (Hypothesis 2).
- RNT is assumed to be positively associated with FoMO (Hypothesis 3a) and PSU severity (Hypothesis 3b).
- Moreover, RNT is assumed to moderate the relationship between FoMO and PSU severity (Hypothesis 4). That is, the higher the level of RNT, the closer the positive link between FoMO and PSU severity.
Fig 1 illustrates the hypothesized relationships as a moderated mediation model (cf., [86]; p. 450).
We investigated the hypotheses in a sample from Germany. In spring 2021, there were about 3.5 million Covid-19 cases in Germany [87]. The first national Covid-19 lockdown was introduced in March 2020 in this country. The timeline and extent of the lockdown differed between the federal German states. In some states curfews were imposed, while other states only encouraged a “stay-at-home” and home-working requirement. Nationalwide, public gatherings of more than two non-family members were prohibited, mass events were cancelled, many public establishments and services were closed, school and university teaching was transferred to online classes (home-schooling). The wearing of face masks in public places and the keeping of 1.5m (4.9 ft) distance to non-family members became compulsory [88, 89]. After an easing of some measures in summer and autumn 2020, they became effective again with the beginning of the second national Covid-19 lockdown that was introduced in December 2020 in all German states. A slow easing of the measures began only in the end of spring 2021 [90, 91].
Materials and methods
Procedure and participants
The current sample comprised 516 smartphone users from Germany (75.2% women; Mage = 31.92, SDage = 12.96, range: 18–79; occupation: 48.6% students, 3.9% apprentices, 45% employed, 1% unemployed, 1.6% retired). Data were collected between April and May 2021 via an online survey in German language. Participants were recruited by participation invitations displayed at several universities in Germany, on social media (Facebook, Twitter), and at public places (like bakeries, shops). Participation was voluntary, and required ownership of a smartphone and legal age due to German law (i.e., age of 18). University students were compensated by course points. All participants were provided instructions and gave informed consent to participate via an online form. The study implementation was approved by the Ethics Committee of the Faculty of Psychology of the Ruhr-Universität Bochum. The survey was completed by 516 (97%) of the 532 people who started it. No data were excluded. The dataset used in the present study is available in S1 Dataset.
Measures
Sense of control.
Following Niemeyer, Bieda [92] sense of control was assessed with the original German language items “Do you experience important areas of your life (i.e., work, free-time, family, etc.) to be uncontrollable, meaning that you cannot, or barely can, influence them?” and “Do you experience these important areas of your life as unpredictable or inscrutable?”. The two items are rated on a 5-point Likert-type scale (0 = not at all, 4 = very strong). For the calculation of the sum score, both items were reversed. Higher sum scores indicate higher sense of control. Earlier reported scale reliability was Cronbach’s α = .820 [48]; the scale reliability in the present study was α = .792.
Fear of Missing Out (FoMO).
The Fear of Missing Out Scale (FoMO Scale; original version: [62]; German language version: [93]) assessed FoMO with ten items (e.g., “I get anxious when I don’t know what my friends are up to”). The items are rated on a 5-point Likert-type scale (1 = not at all true of me, 5 = extremely true of me). Higher sum scores indicate higher FoMO. Earlier reported scale reliability was α = .770 [93]; the scale reliability in the present study was α = .831.
Repetitive negative thinking.
Following Brailovskaia, Margraf [94] the level of RNT was assessed with two original German language items that were construed based on available longer RNT measures (Perseverative Thinking Questionnaire, PTQ; [70]). The items focused, respectively, on one of the two RNT forms—worry (“I am often worried”) and rumination (“I often tend to ruminate”). The items are rated on a 5-point Likert-type scale (1 = does not apply to me at all, 5 = applies to me very much). The higher the sum score, the higher the level of RNT. Notably, previous research emphasized the validity, reliability, and efficiency of single-item instruments and encouraged their use [95–97]. Earlier reported scale reliability was α = .830 [94]. The scale reliability in the present study was: α = .851.
Problematic smartphone use.
PSU was assessed with a modified version of the brief Bergen Social Media Addiction Scale (BSMAS; original version: [98]; German version: [99]). Earlier research reported the BSMAS to have good psychometric properties (scale reliability: α = .880 [100]). In the six items that are formulated according to the six characteristics of problematic social media use (i.e., salience, tolerance, mood modification, relapse, withdrawal, conflict) the term “Social Media” was replaced by “Smartphone” (e.g., “Felt an urge to use the Smartphone more and more?”). The items are rated on a 5-point Likert-type scale (1 = very rarely, 5 = very often). Higher sum scores indicate higher problematic smartphone use. The scale reliability in the present samples was α = .843.
Furthermore, participants were asked to rate how much time they daily spent on smartphone use (in minutes) (i.e., “How much time do you on daily spent on smartphone use?”).
Statistical analyses
Statistical analyses were conducted using SPSS 26 and the Process macro version 3.5 (www.processmacro.org/index.html). After descriptive analyses, associations between the investigated variables were assessed by zero-order bivariate correlations. Next, a moderated mediation analysis that included a conditional indirect effect (see Fig 1) was computed (Process: model 14). This analysis examined the multiple effects simultaneously (integration of the hypothesized mediation and moderation models) [101, 102]. The moderated mediation effect was assessed by the bootstrapping procedure (10,000 samples) that provides percentile bootstrap confidence intervals (CI 95%). The analysis included sense of control as predictor, FoMO as mediator, RNT as moderator, and PSU as outcome (see Fig 1). Younger age, female gender and time spent on smartphone use were previously reported to be positively related to PSU [37]. Thus, considering the rather young and female composition of our sample, we controlled for age and gender by including both as covariates in the moderated mediation model. In addition, we also controlled for daily smartphone use time. Path a denoted the link between sense of control and FoMO; the relationship between FoMO and PSU was denoted by path b; path c’ (the direct effect) denoted the association between sense of control and PSU after the inclusion of FoMO and RNT in the model.
Results
Table 1 presents descriptive statistics of the investigated variables and their correlations. The correlation analyses revealed that sense of control was significantly negatively correlated with FoMO, RNT, and PSU severity (all: p < .001), as well as with time spent daily on smartphone use (p < .05). Furthermore, there were significant positive correlations between FoMO, RNT, smartphone use time and PSU severity (all: p < .001) (see Table 1).
The moderated mediation analysis showed significant findings (see Table 2). The overall model was significant, F(5,508) = 54.433, p < .001, R2 = .391. The direct effect (path c’) of sense of control on PSU severity was not significant (p = .250) after controlling for FoMO, RNT, and their interaction, as well as the covariates age, gender and daily time spent on smartphone use. The conditional indirect effect of sense of control on PSU severity through FoMO was significant in participants with low, medium, and high levels of RNT. However, as shown in Table 2, this effect was stronger for participants with high rather than medium or low levels of RNT (effect: high level > medium level > low level). Fig 2 visualizes the moderation effect of RNT on the link between FoMO and PSU severity.
Discussion
Smartphone use can facilitate one’s daily routine and reduce loneliness, but it can also have negative impact on health, work, and relationships [37]. As shown by recent research, during the Covid-19 outbreak the role of smartphones on life remarkably increased, as well increased the problematic characteristics of smartphone use [18, 56, 57]. Against this background, the current study investigated potential correlates of PSU severity during the Covid-19 outbreak and the mechanisms that might explain PSU to contribute to the identification of individuals at risk and to protect them. Our findings reveal that sense of control, FoMO and repetitive negative thinking are significantly associated with PSU severity. Furthermore, they show how the investigated variables could interact.
As expected, sense of control was negatively associated with FoMO (confirmation of Hypothesis 1a) and PSU severity (confirmation of Hypothesis 1b). FoMO was positively related to PSU severity (confirmation of Hypothesis 1c). Moreover, FoMO served as a mediator between sense of control and PSU severity (confirmation of Hypothesis 2). Notably, our cross-sectional study design does not reveal causal conclusions. But based on available research [25, 67, 103, 104], our results allow the hypothetical assumption that individuals who experience loss of control of important life events could be at risk for enhanced levels of FoMO. To reduce this negative emotional state, they could consequently engage with their smartphones. The gratification experienced by this behavior could contribute to habit formation of prolonged smartphone use. In the longer-term, this might foster impulsive use and the development of PSU [23]. In contrast, people with high sense of control could be less prone to FoMO and PSU. Considering the negative association between sense of control and time spent daily on smartphone use in the present study, they could spend more time on adaptive activities that are not linked to smartphone use and be less preoccupied with issues that happen online. Thus, those without substantial negative affect, and with perceived self-control should have enough fulfilling and satisfying experiences that they would not feel compelled to experience FoMO or PSU to alleviate distress. This assumption is supported by previous research that described individuals who regularly engage in fulfilling leisure activities to have low levels of FoMO and problematic Internet use [105]. Moreover, satisfying leisure activities can contribute to one’s sense of control [106].
Thus, it might be that people, who engage in meaningful (leisure) activities during the required stay-at-home period since the Covid-19 outbreak, experience the overall situation as less burdensome and keep an adequate level of sense of control. Therefore, they experience less FoMO and engage less in PSU. Notably, sports engagement belongs to leisure activities that foster sense of control, physical and mental health, and can reduce problematic media use [107–109]. In a recent cross-national study, physical activity reduced the negative impact of depression symptoms on the experience of psychological burden by the Covid-19 crisis [59]. Thus, regular physical activity that does not require expensive equipment (e.g., jogging, gymnastics, yoga) could be an adequate way to protect us against PSU.
Furthermore, we found a positive association between RNT and FoMO (confirmation of Hypothesis 3a), as well as between RNT and PSU severity (confirmation of Hypothesis 3b). Moreover, RNT served as a moderator between FoMO and PSU (confirmation of Hypothesis 4): The higher the RNT, the closer the positive link between FoMO and PSU severity. The present results allow the hypothetical assumption—due to the cross-sectional data no causal conclusion can be drawn—that worry and rumination as subtypes of RNT [71] could foster the negative mood and thoughts involved with FoMO, and therefore contribute to PSU. Thus, people who typically engage in RNT could be at enhanced risk for PSU and its potential negative consequences. In contrast, smartphone use of individuals who are less prone to RNT might be less problematic, even if they experience FoMO.
RNT is a transdiagnostic construct that is common for different mental disorders [74]. Moreover, previous research described that RNT can amplify the effect of risk factors on psychopathological outcomes, for example the development of depression [110]. Our findings correspond to available studies that reported RNT to be also positively linked to FoMO and PSU severity [77, 78, 80–82]. Furthermore, they complement this knowledge by showing for the first time that RNT could serve as a moderator between FoMO and PSU severity. Thus, we can assume that factors that reduce RNT could also contribute to the protection against PSU.
Mindfulness is described as the enhanced attention to and nonjudgment awareness of the current moment [111]. It belongs to the factors that can reduce RNT and is often included in psychotherapeutic treatment [112, 113]. Earlier research showed that mindfulness can contribute to the reduction of the negative impact of intensive social media use on mental health and on work performance [79, 114], and it can also reduce problematic social media use [115] and PSU severity [116]. Against this background, mindfulness might be a further protective factor against PSU. Its training and cultivation in everyday life [117] could be specifically beneficial for people with low sense of control, high FoMO and the tendency to RNT.
The present study has some limitations that need to be considered when interpreting the results. First, the cross-sectional online survey design does not allow true conclusions on causality; only hypothetical assumptions are possible. Therefore, our findings should be extended by longitudinal/experimental investigations. For example, in could be investigated by an experimental study design, whether the reduction of participants’ level of RNT by mindfulness practice [112] can influence the association between FoMO and PSU. Second, our sample was assessed only in Germany, and participants were mostly female and rather young. This might bias the results and limit their generalizability to other populations. Age and gender were controlled for in the moderated mediation analysis which partly tackled this limitation. Nevertheless, future studies are suggested to replicate our investigation in more age and gender balanced samples from other countries. Third, we assessed data via self-report that can be prone to social desirability and perception mistakes. The inclusion of a social desirability measure (for example, Balanced Inventory of Desirable Responding (BIDR; [118]) and additional measure of objective data (for example, usage of applications that assess the daily time spent on smartphone use) could tackle this limitation in future studies. Fourth, available research described that the Covid-19 crisis including restrictive governmental measures to slow down the pandemic spread significantly changed the everyday routine of many people in Germany (e.g., [119]) as well as in other countries (e.g., [47, 120]). Most of our participants were students or employees. In spring 2021, university lectures in Germany were held online and many employees were advised for home-working [90, 91]. However, we did not explicitly assess whether the daily routine of our participants in the present study changed during the Covid-19 crisis. Thus, we can only speculate whether they experienced the Covid-19 crisis and required changes in daily routine as a significant control loss.
To conclude, the present study reveals that low sense of control might contribute to PSU. Enhanced experience of FoMO combined with increased levels of RNT could reinforce this association. Thus, activities—for instance physical and mindfulness exercises (both can be practiced despite Covid-19-related restrictions on everyday life)–that allow positive experiences in the offline world and thus contribute to the increase of sense of control, reduction of RNT and FoMO might foster less PSU. This is of specific importance during the Covid-19 outbreak that has been accompanied by enhanced smartphone use in many countries.
Supporting information
S1 Dataset. Dataset used for analyses in present study.
https://doi.org/10.1371/journal.pone.0261023.s001
(SAV)
References
- 1. Elhai JD, Levine JC, Hall BJ. The relationship between anxiety symptom severity and problematic smartphone use: A review of the literature and conceptual frameworks. Journal of Anxiety Disorders. 2019;62: 45–52. pmid:30529799
- 2. Sohn S, Rees P, Wildridge B, Kalk NJ, Carter B. Prevalence of problematic smartphone usage and associated mental health outcomes amongst children and young people: a systematic review, meta-analysis and GRADE of the evidence. BMC Psychiatry. 2019;19(1): 1–10.
- 3. Rozgonjuk D, Sindermann C, Elhai JD, Montag C. Comparing Smartphone, WhatsApp, Facebook, Instagram, and Snapchat: Which Platform Elicits the Greatest Use Disorder Symptoms? Cyberpsychology, Behavior, and Social Networking. 2021;24(2): 129–34. pmid:32907403
- 4. David ME, Roberts JA, Christenson B. Too much of a good thing: Investigating the association between actual smartphone use and individual well-being. International Journal of Human–Computer Interaction. 2018;34(3): 265–75.
- 5. Rozgonjuk D, Sindermann C, Elhai JD, Christensen AP, Montag C. Associations between symptoms of problematic smartphone, Facebook, WhatsApp, and Instagram use: An item-level exploratory graph analysis perspective. Journal of Behavioral Addictions. 2020;9(3): 686–97. pmid:32986606
- 6. Brailovskaia J, Margraf J. The relationship between burden caused by coronavirus (Covid-19), addictive social media use, sense of control and anxiety. Computers in Human Behavior. 2021;119: 106720. pmid:33785982
- 7. Li J, Lepp A, Barkley JE. Locus of control and cell phone use: Implications for sleep quality, academic performance, and subjective well-being. Computers in Human Behavior. 2015;52: 450–7.
- 8. Seligman MEP. Learned helplessness. Annual Review of Medicine. 1972;23(1): 407–12. pmid:4566487
- 9. Vollmayr B, Gass P. Learned helplessness: unique features and translational value of a cognitive depression model. Cell and Tissue Research. 2013;354(1): 171–8. pmid:23760889
- 10. Madell DE, Muncer SJ. Control over social interactions: an important reason for young people’s use of the Internet and mobile phones for communication? CyberPsychology & Behavior. 2007;10(1): 137–40. pmid:17305461
- 11. Miller WR, Seligman ME. Depression and learned helplessness in man. Journal of Abnormal Psychology. 1975;84(3): 228. pmid:1169264
- 12.
Skaff MM. Sense of control and health. In: Adldwin CM, Park CL, Spiro A, editors. Handbook of health psychology and aging. New York, NY: Guilford Press; 2007. p. 186–209
- 13. Keeton CP, Perry-Jenkins M, Sayer AG. Sense of control predicts depressive and anxious symptoms across the transition to parenthood. Journal of Family Psychology. 2008;22(2): 212–21. pmid:18410208
- 14. Volpicelli JR. Uncontrollable events and alcohol drinking. British Journal of Addiction. 1987;82(4): 381–92. pmid:3555574
- 15. MacKinnon N, Colman I. Factors associated with suicidal thought and help-seeking behaviour in transition-aged youth versus adults. The Canadian Journal of Psychiatry. 2016;61(12): 789–96. pmid:27578771
- 16. Haynos AF, Wang SB, Fruzzetti AE. Restrictive eating is associated with emotion regulation difficulties in a non-clinical sample. Eating Disorders. 2018;26(1): 5–12. pmid:29384461
- 17. Horwood S, Anglim J. Emotion Regulation Difficulties, Personality, and Problematic Smartphone Use. Cyberpsychology, Behavior, and Social Networking. 2021;24(4): 275–81. pmid:33090002
- 18. Elhai JD, McKay D, Yang H, Minaya C, Montag C, Asmundson GJG. Health anxiety related to problematic smartphone use and gaming disorder severity during COVID‐19: Fear of missing out as a mediator. Human Behavior and Emerging Technologies. 2021;3(1): 137–46. pmid:33363275
- 19. Brand M, Young KS, Laier C, Wölfling K, Potenza MN. Integrating psychological and neurobiological considerations regarding the development and maintenance of specific Internet-use disorders: An Interaction of Person-Affect-Cognition-Execution (I-PACE) model. Neuroscience & Biobehavioral Reviews. 2016;71: 252–66. pmid:27590829
- 20. Lapierre MA, Zhao P, Custer BE. Short-term longitudinal relationships between smartphone use/dependency and psychological well-being among late adolescents. Journal of Adolescent Health. 2019;65(5): 607–12. pmid:31477510
- 21. Yang J, Fu X, Liao X, Li Y. Association of problematic smartphone use with poor sleep quality, depression, and anxiety: A systematic review and meta-analysis. Psychiatry Research. 2020;284: 112686. pmid:31757638
- 22. Montag C, Walla P. Carpe diem instead of losing your social mind: Beyond digital addiction and why we all suffer from digital overuse. Cogent Psychology. 2016;3(1): 1157281.
- 23. Brand M, Wegmann E, Stark R, Müller A, Wölfling K, Robbins TW, et al. The Interaction of Person-Affect-Cognition-Execution (I-PACE) model for addictive behaviors: Update, generalization to addictive behaviors beyond internet-use disorders, and specification of the process character of addictive behaviors. Neuroscience & Biobehavioral Reviews. 2019;104: 1–10. pmid:31247240
- 24. Montag C, Błaszkiewicz K, Lachmann B, Sariyska R, Andone I, Trendafilov B, et al. Recorded behavior as a valuable resource for diagnostics in mobile phone addiction: evidence from psychoinformatics. Behavioral Sciences. 2015;5(4): 434–42. pmid:26492275
- 25. Elhai JD, Levine JC, Alghraibeh AM, Alafnan AA, Aldraiweesh AA, Hall BJ. Fear of missing out: Testing relationships with negative affectivity, online social engagement, and problematic smartphone use. Computers in Human Behavior. 2018;89: 289–98.
- 26. Chen C-Y. Smartphone addiction: psychological and social factors predict the use and abuse of a social mobile application. Information, Communication & Society. 2018: 1–14.
- 27. Sapacz M, Rockman G, Clark J. Are we addicted to our cell phones? Computers in Human Behavior. 2016;57: 153–9.
- 28. Elhai JD, Dvorak RD, Levine JC, Hall BJ. Problematic smartphone use: A conceptual overview and systematic review of relations with anxiety and depression psychopathology. Journal of Affective Disorders. 2017;207: 251–9. pmid:27736736
- 29. Griffiths MD. A ‘components’ model of addiction within a biopsychosocial framework. Journal of Substance Use. 2005;10(4): 191–7.
- 30.
American Psychiatric Association. Diagnostic and Statistical Manual of Mental Disorders (5th ed.). Washington, DC: American Psychiatric Association; 2013.
- 31.
World Health Organization. International classification of diseases for mortality and morbidity statistics (11th Revision) 2018. https://icd.who.int/browse11/l-m/en.
- 32. Carbonell X, Panova T. A critical consideration of social networking sites’ addiction potential. Addiction Research & Theory. 2017;25(1): 48–57.
- 33. Orben A. The Sisyphean cycle of technology panics. Perspectives on Psychological Science. 2020;15(5): 1143–57. pmid:32603635
- 34. Panova T, Carbonell X. Is smartphone addiction really an addiction? Journal of Behavioral Addictions. 2018;7(2): 252–9. pmid:29895183
- 35. Thomée S. Mobile phone use and mental health. A review of the research that takes a psychological perspective on exposure. International Journal of Environmental Research and Public Health. 2018;15(12): 2692. pmid:30501032
- 36. Heo J-Y, Kim K, Fava M, Mischoulon D, Papakostas GI, Kim M-J, et al. Effects of smartphone use with and without blue light at night in healthy adults: A randomized, double-blind, cross-over, placebo-controlled comparison. Journal of Psychiatric Research. 2017;87: 61–70. pmid:28017916
- 37. Busch PA, McCarthy S. Antecedents and consequences of problematic smartphone use: A systematic literature review of an emerging research area. Computers in human behavior. 2021: 106414.
- 38. Ng KC, Wu LH, Lam HY, Lam LK, Nip PY, Ng CM, et al. The relationships between mobile phone use and depressive symptoms, bodily pain, and daytime sleepiness in Hong Kong secondary school students. Addictive Behaviors. 2020;101: 105975. pmid:31076240
- 39. Randjelovic P, Stojiljkovic N, Radulovic N, Stojanovic N, Ilic I. Problematic smartphone use, screen time and chronotype correlations in university students. European Addiction Research. 2021;27(1): 67–74. pmid:32172240
- 40. Kenney EL, Gortmaker SL. United States adolescents’ television, computer, videogame, smartphone, and tablet use: associations with sugary drinks, sleep, physical activity, and obesity. The Journal of Pediatrics. 2017;182: 144–9. pmid:27988020
- 41. Fennell C, Lepp A, Barkley J. Smartphone use predicts being an “active couch potato” in sufficiently active adults. American Journal of Lifestyle Medicine. 2019.
- 42. Lepp A, Barkley JE, Sanders GJ, Rebold M, Gates P. The relationship between cell phone use, physical and sedentary activity, and cardiorespiratory fitness in a sample of US college students. International Journal of Behavioral Nutrition and Physical Activity. 2013;10(1): 79. pmid:23800133
- 43. Hwang Y, Jeong S-H. Predictors of parental mediation regarding children’s smartphone use. Cyberpsychology, Behavior, and Social Networking. 2015;18(12): 737–43. pmid:26544162
- 44. Hawi NS, Samaha M. To excel or not to excel: Strong evidence on the adverse effect of smartphone addiction on academic performance. Computers & Education. 2016;98: 81–9.
- 45. Yang Z, Asbury K, Griffiths MD. An exploration of problematic smartphone use among Chinese university students: Associations with academic anxiety, academic procrastination, self-regulation and subjective wellbeing. International Journal of Mental Health and Addiction. 2019;17(3): 596–614.
- 46. Duke É, Montag C. Smartphone addiction, daily interruptions and self-reported productivity. Addictive Behaviors Reports. 2017;6: 90–5. pmid:29450241
- 47. Cellini N, Canale N, Mioni G, Costa S. Changes in sleep pattern, sense of time and digital media use during COVID-19 lockdown in Italy. Journal of Sleep Research. 2020;29(4): e13074. pmid:32410272
- 48. Brailovskaia J, Margraf J. Predicting adaptive and maladaptive responses to the Coronavirus (COVID-19) outbreak: A prospective longitudinal study. International Journal of Clinical and Health Psychology. 2020;20(3): 181–91. pmid:32837518
- 49.
World Health Organization. Coronavirus disease 2019 (COVID-19): Situation Report, 51: World Health Organization; 2020. https://apps.who.int/iris/bitstream/handle/10665/331475/nCoVsitrep11Mar2020-eng.pdf.
- 50. Howard J, Huang A, Li Z, Tufekci Z, Zdimal V, van der Westhuizen H-M, et al. An evidence review of face masks against COVID-19. Proceedings of the National Academy of Sciences. 2021;118(4): e2014564118. pmid:33431650
- 51. Sohrabi C, Alsafi Z, O’Neill N, Khan M, Kerwan A, Al-Jabir A, et al. World Health Organization declares global emergency: A review of the 2019 novel coronavirus (COVID-19). International Journal of Surgery. 2020;76: 71–6. pmid:32112977
- 52. Tso RV, Cowling BJ. Importance of face masks for COVID-19–a call for effective public education. Clinical Infectious Diseases. 2020;71(16): 2195–8. pmid:32614045
- 53. Su Z, Wen J, McDonnell D, Goh E, Li X, Šegalo S, et al. Vaccines are not yet a silver bullet: The imperative of continued communication about the importance of COVID-19 safety measures. Brain, Behavior, & Immunity-Health. 2021;12: 100204.
- 54. Settersten RA Jr, Bernardi L, Härkönen J, Antonucci TC, Dykstra PA, Heckhausen J, et al. Understanding the effects of Covid-19 through a life course lens. Advances in Life Course Research. 2020;45: 100360.
- 55. Taylor S, Landry CA, Paluszek MM, Fergus TA, McKay D, Asmundson GJG. COVID stress syndrome: Concept, structure, and correlates. Depression and Anxiety. 2020;37(8): 706–14. pmid:32627255
- 56. Ohme J, Abeele MMPV, Van Gaeveren K, Durnez W, De Marez L. Staying Informed and Bridging “Social Distance”: Smartphone News Use and Mobile Messaging Behaviors of Flemish Adults during the First Weeks of the COVID-19 Pandemic. Socius. 2020;6: 1–14. pmid:34192139
- 57. Masaeli N, Farhadi H. Prevalence of Internet-based addictive behaviors during COVID-19 pandemic: a systematic review. Journal of Addictive Diseases. 2021: 1–27. pmid:33749537
- 58. Jeong S-H, Kim H, Yum J-Y, Hwang Y. What type of content are smartphone users addicted to?: SNS vs. games. Computers in Human Behavior. 2016;54: 10–7.
- 59. Brailovskaia J, Cosci F, Mansueto G, Miragall M, Herrero R, Baños RM, et al. The association between depression symptoms, psychological burden caused by Covid-19 and physical activity: An investigation in Germany, Italy, Russia, and Spain. Psychiatry Research. 2021;295: 113596. pmid:33261924
- 60. Elhai JD, Levine JC, Dvorak RD, Hall BJ. Fear of missing out, need for touch, anxiety and depression are related to problematic smartphone use. Computers in Human Behavior. 2016;63: 509–16.
- 61. Wolniewicz CA, Tiamiyu MF, Weeks JW, Elhai JD. Problematic smartphone use and relations with negative affect, fear of missing out, and fear of negative and positive evaluation. Psychiatry Research. 2018;262: 618–23. pmid:28982630
- 62. Przybylski AK, Murayama K, DeHaan CR, Gladwell V. Motivational, emotional, and behavioral correlates of fear of missing out. Computers in Human Behavior. 2013;29(4): 1841–8.
- 63. Stead H, Bibby PA. Personality, fear of missing out and problematic internet use and their relationship to subjective well-being. Computers in Human Behavior. 2017;76: 534–40.
- 64. Milyavskaya M, Saffran M, Hope N, Koestner R. Fear of missing out: prevalence, dynamics, and consequences of experiencing FOMO. Motivation and Emotion. 2018;42(5): 725–37.
- 65. Elhai JD, Yang H, Montag C. Fear of missing out (FOMO): Overview, theoretical underpinnings, and literature review on relations with severity of negative affectivity and problematic technology use. Brazilian Journal of Psychiatry. 2021;43(2): 203–9. pmid:32401865
- 66. Scalzo AC, Martinez JA. Not All Anxiety is the Same: How Different" Types" of Anxiety Uniquely Associate With College Students’ Drinking Intentions. Journal of College Student Development. 2017;58(6): 943–7.
- 67. Riordan BC, Flett JAM, Hunter JA, Scarf D, Conner TS. Fear of missing out (FoMO): The relationship between FoMO, alcohol use, and alcohol-related consequences in college students. Annals of Neuroscience and Psychology. 2015;2(7): 1–7.
- 68. Beyens I, Frison E, Eggermont S. “I don’t want to miss a thing”: Adolescents’ fear of missing out and its relationship to adolescents’ social needs, Facebook use, and Facebook related stress. Computers in Human Behavior. 2016;64: 1–8.
- 69. Elhai JD, Yang H, Fang J, Bai X, Hall BJ. Depression and anxiety symptoms are related to problematic smartphone use severtity in Chinese young adults: Fear of missing out as a mediator. Addictive Behaviors. 2020;101: 1–7. pmid:31030950
- 70. Ehring T, Zetsche U, Weidacker K, Wahl K, Schönfeld S, Ehlers A. The Perseverative Thinking Questionnaire (PTQ): Validation of a content-independent measure of repetitive negative thinking. Journal of Behavior Therapy and Experimental Psychiatry. 2011;42(2): 225–32. pmid:21315886
- 71. McEvoy PM, Watson H, Watkins ER, Nathan P. The relationship between worry, rumination, and comorbidity: Evidence for repetitive negative thinking as a transdiagnostic construct. Journal of affective disorders. 2013;151(1): 313–20. pmid:23866301
- 72. Nolen-Hoeksema S. Responses to depression and their effects on the duration of depressive episodes. Journal of Abnormal Psychology. 1991;100(4): 569–82. pmid:1757671
- 73. Borkovec TD, Ray WJ, Stöber J. Worry: a cognitive phenomenon intimately linked to affective, physiological, and interpersonal behavioral processes. Cognitive Therapy and Research. 1988;22: 561–76.
- 74. Spinhoven P, van Hemert AM, Penninx BW. Repetitive negative thinking as a predictor of depression and anxiety: A longitudinal cohort study. Journal of Affective Disorders. 2018;241: 216–25. pmid:30138805
- 75. Devynck F, Rousseau A, Romo L. Does repetitive negative thinking influence alcohol use? A systematic review of the literature. Frontiers in psychology. 2019;10: 1482. pmid:31333536
- 76. Hamonniere T, Laqueille X, Vorspan F, Dereux A, Illel K, Varescon I. Toward a better understanding of the influence of repetitive negative thinking in alcohol use disorder: An examination of moderation effect of metacognitive beliefs and gender. Addictive Behaviors. 2020;111: 106561. pmid:32739590
- 77. Elhai JD, Tiamiyu M, Weeks J. Depression and social anxiety in relation to problematic smartphone use. Internet Research. 2018;28(2): 315–32.
- 78. Elhai JD, Rozgonjuk D, Yildirim C, Alghraibeh AM, Alafnan AA. Worry and anger are associated with latent classes of problematic smartphone use severity among college students. Journal of Affective Disorders. 2019;246: 209–16. pmid:30583147
- 79. Hong W, Liu R-D, Ding Y, Fu X, Zhen R, Sheng X. Social media exposure and college students’ mental health during the outbreak of CoViD-19: the mediating role of rumination and the moderating role of mindfulness. Cyberpsychology, Behavior, and Social Networking. 2021;24(4): 282–7. pmid:33050721
- 80. Elhai JD, Yang H, Dempsey AE, Montag C. Rumination and negative smartphone use expectancies are associated with greater levels of problematic smartphone use: A latent class analysis. Psychiatry Research. 2020;285: 112845. pmid:32045821
- 81. Bayın Ü, Makas S, Çelik E, Biçener E. Examination of Individuals’ Level of Fear of COVID-19, Fear of Missing Out (FoMO), and Ruminative Thought Style. Education Quarterly Reviews. 2021;4(2): 264–73.
- 82. Dempsey AE, O’Brien KD, Tiamiyu MF, Elhai JD. Fear of missing out (FoMO) and rumination mediate relations between social anxiety and problematic Facebook use. Addictive Behaviors Reports. 2019;9: 100150. pmid:31193746
- 83. Ehring T, Watkins ER. Repetitive negative thinking as a transdiagnostic process. International Journal of Cognitive Therapy. 2008;1(3): 192–205.
- 84. Oberst U, Wegmann E, Stodt B, Brand M, Chamarro A. Negative consequences from heavy social networking in adolescents: The mediating role of fear of missing out. Journal of Adolescence. 2017;55: 51–60. pmid:28033503
- 85. Zhang Z, Jiménez FR, Cicala JE. Fear of missing out scale: A self‐concept perspective. Psychology & Marketing. 2020;37(11): 1619–34.
- 86.
Hayes AF. Introduction to mediation, moderation, and conditional process analysis. London: Guilford Press; 2013.
- 87. Hasell J, Mathieu E, Beltekian D, Macdonald B, Giattino C, Ortiz-Ospina E, et al. A cross-country database of COVID-19 testing. Scientific Data. 2021;7(345): 1–7. pmid:33033256
- 88.
Waschinski G. Deutschland im Shutdown-Modus—Die Alternativlos-Kanzlerin kehrt zurück. Handelsblatt. 2020. https://www.handelsblatt.com/politik/deutschland/coronakrise-deutschland-im-shutdown-modus-die-alternativlos-kanzlerin-kehrt-zurueck/25650658.html?ticket=ST-5297440-ClIuuU5cdAdes0gcSE2n-ap3.
- 89.
Bundesministerium für Gesundheit. Coronavirus SARS-CoV-2: Chronik der bisherigen Maßnahmen 2020. https://www.bundesgesundheitsministerium.de/coronavirus/chronik-coronavirus.html.
- 90.
deutschland.de. Latest coronavirus updates 2021. https://www.deutschland.de/en/news/coronavirus-in-germany-informations.
- 91.
Robert Koch Institut. COVID-19 (Coronavirus SARS-CoV-2) 2021. https://www.rki.de/DE/Content/InfAZ/N/Neuartiges_Coronavirus/nCoV.html.
- 92. Niemeyer H, Bieda A, Michalak J, Schneider S, Margraf J. Education and mental health: Do psychosocial resources matter? SSM-Population Health. 2019;7: 100392. pmid:30989104
- 93. Rozgonjuk D, Sindermann C, Elhai JD, Montag C. Fear of Missing Out (FoMO) and social media’s impact on daily-life and productivity at work: Do WhatsApp, Facebook, Instagram, and Snapchat Use Disorders mediate that association? Addictive Behaviors. 2020;110: 106487. pmid:32674020
- 94. Brailovskaia J, Margraf J, Teismann T. Repetitive negative thinking mediates the relationship between addictive Facebook use and suicide-related outcomes: A longitudinal study. Current Psychology. 2021. pmid:34220175
- 95. Konrath S, Meier BP, Bushman BJ. Development and validation of the single item narcissism scale (SINS). PLOS one. 2014;9(8): e103469. pmid:25093508
- 96. Brailovskaia J, Margraf J. How to measure self-esteem with one item? Validation of the German Single-Item Self-Esteem Scale (G-SISE). Current Psychology. 2018: 1–11.
- 97. Szrek H, Chao L-W, Ramlagan S, Peltzer K. Predicting (un) healthy behavior: A comparison of risk-taking propensity measures. Judgment and Decision Making. 2012;7(6): 716–27. pmid:24307919
- 98. Andreassen CS, Billieux J, Griffiths MD, Kuss DJ, Demetrovics Z, Mazzoni E, et al. The relationship between addictive use of social media and video games and symptoms of psychiatric disorders: A large-scale cross-sectional study. Psychology of Addictive Behaviors. 2016;30(2): 252–62. pmid:26999354
- 99. Brailovskaia J, Schillack H, Margraf J. Tell me why are you using social media (SM)! Relationship between reasons for use of SM, SM flow, daily stress, depression, anxiety, and addictive SM use–An exploratory investigation of young adults in Germany. Computers in Human Behavior. 2020;113: 106511.
- 100. Andreassen CS, Pallesen S, Griffiths MD. The relationship between addictive use of social media, narcissism, and self-esteem: Findings from a large national survey. Addictive Behaviors. 2017;64: 287–93. pmid:27072491
- 101. Edwards JR, Lambert LS. Methods for integrating moderation and mediation: a general analytical framework using moderated path analysis. Psychological Methods. 2007;12(1): 1–22. pmid:17402809
- 102. Hayes AF. Partial, conditional, and moderated moderated mediation: Quantification, inference, and interpretation. Communication Monographs. 2018;85(1): 4–40.
- 103. Rozgonjuk D, Elhai JD, Ryan T, Scott GG. Fear of missing out is associated with disrupted activities from receiving smartphone notifications and surface learning in college students. Computers & Education. 2019;140: 103590.
- 104. Li L, Griffiths MD, Mei S, Niu Z. Fear of Missing Out and Smartphone Addiction Mediates the Relationship Between Positive and Negative Affect and Sleep Quality Among Chinese University Students. Frontiers in Psychiatry. 2020;11: 877. pmid:33192635
- 105. Tomczyk Ł, Selmanagic-Lizde E. Fear of Missing Out (FOMO) among youth in Bosnia and Herzegovina—Scale and selected mechanisms. Children and Youth Services Review. 2018;88: 541–9.
- 106. Coleman D, Iso-Ahola SE. Leisure and health: The role of social support and self-determination. Journal of Leisure Research. 1993;25(2): 111–28.
- 107. Rebar AL, Stanton R, Geard D, Short C, Duncan MJ, Vandelanotte C. A meta-meta-analysis of the effect of physical activity on depression and anxiety in non-clinical adult populations. Health Psychology Review. 2015;9(3): 366–78. pmid:25739893
- 108. Brailovskaia J, Teismann T, Margraf J. Physical activity mediates the association between daily stress and Facebook Addiction Disorder (FAD)–a longitudinal approach among German students. Computers in Human Behavior. 2018;86: 199–204.
- 109. Haible S, Volk C, Demetriou Y, Höner O, Thiel A, Sudeck G. Physical Activity-Related Health Competence, Physical Activity, and Physical Fitness: Analysis of Control Competence for the Self-Directed Exercise of Adolescents. International Journal of Environmental Research and Public Health. 2020;17(1): 39–53. pmid:31861577
- 110. Spasojević J, Alloy LB. Rumination as a common mechanism relating depressive risk factors to depression. Emotion. 2001;1(1): 25–37. pmid:12894809
- 111. Bishop SR, Lau M, Shapiro S, Carlson L, Anderson ND, Carmody J, et al. Mindfulness: A proposed operational definition. Clinical Psychology: Science and Practice. 2004;11(3): 230–41.
- 112. Perestelo-Perez L, Barraca J, Peñate W, Rivero-Santana A, Alvarez-Perez Y. Mindfulness-based interventions for the treatment of depressive rumination: Systematic review and meta-analysis. International Journal of Clinical and Health Psychology. 2017;17(3): 282–95. pmid:30487903
- 113. Brown KW, Ryan RM. The benefits of being present: mindfulness and its role in psychological well-being. Journal of Personality and Social Psychology. 2003;84-848(4): 822. pmid:12703651
- 114. Charoensukmongkol P. Mindful Facebooking: The moderating role of mindfulness on the relationship between social media use intensity at work and burnout. Journal of Health Psychology. 2016;21(9): 1966–80. pmid:25680915
- 115. Apaolaza V, Hartmann P, D’Souza C, Gilsanz A. Mindfulness, compulsive mobile social media use, and derived stress: The mediating roles of self-esteem and social anxiety. Cyberpsychology, Behavior, and Social Networking. 2019;22(6): 388–96. pmid:31070455
- 116. Regan T, Harris B, Van Loon M, Nanavaty N, Schueler J, Engler S, et al. Does mindfulness reduce the effects of risk factors for problematic smartphone use? Comparing frequency of use versus self-reported addiction. Addictive Behaviors. 2020: 106435. pmid:32335396
- 117.
McCown D, Reibel D, Micozzi MS. Teaching mindfulness. A practical guide for clinicians and educators. New York: Springer; 2010.
- 118. Musch J, Brockhaus R, Bröder A. An inventory for the assessment of two factors of social desirability. Diagnostica. 2002;48: 121–9. pmid:22489614
- 119. Lemenager T, Neissner M, Koopmann A, Reinhard I, Georgiadou E, Müller A, et al. COVID-19 Lockdown Restrictions and Online Media Consumption in Germany. International Journal of Environmental Research and Public Health. 2021;18(1): 14–26. pmid:33375139
- 120. Margraf J, Brailovskaia J, Schneider S. Behavioral measures to fight COVID-19: An 8-country study of perceived usefulness, adherence and their predictors. PLoS One. 2020;15(12): e0243523. pmid:33284865