Mobile phone addiction and sleep quality in college students: a mediation model of rumination and fear of missing out

doi:10.21203/rs.3.rs-4322644/v1

Download PDF

Research Article

Mobile phone addiction and sleep quality in college students: a mediation model of rumination and fear of missing out

https://doi.org/10.21203/rs.3.rs-4322644/v1

This work is licensed under a CC BY 4.0 License

Version 1

posted

You are reading this latest preprint version

Purpose

The impact of mobile phone addiction (MPA) on college students' sleep quality (SQ) has received increasing attention in recent years.On this basis, the mediating roles of rumination and FOMO (fear of missing out) on MPA and SQ were examined in this study.

Methods

In a cross-sectional study, preliminary data were gathered via questionnaires from 1401 college students (19.35 ± 0.81) from 5 universities in Jiangxi Province, China. Mobile Phone Addiction Tendency Scale, Rumination Response Scale, Fear of Missing Out Scale and Sleep Quality Scale were employed in the research. The mediation model was tested using SPSS 26.0 and AMOS26.0 software, with FOMO and rumination acting as the mediating variables.

Results

Between MPA and SQ, rumination and FOMO each had their own unique mediation effect. Furthermore, rumination and FOMO function as a chain of mediators between college students' MPA and SQ.

Conclusion

This study provided confirmation and clarification that in college students, the association between MPA and SQ was mediated by rumination and FOMO.This study improves our understanding of MPA, SQ and how MPA may affect SQ in college students. It also shows that the impact of MPA and SQ of college students should be given more consideration by educators, parents, and college students themselves.

college students

mobile phone addiction

rumination

fear of missing out

sleep quality

Since information technology is developing so quickly, we are using mobile phones more and more in our daily lives.In particular, as Internet technology has advanced, smartphones have become an essential component of peoples' lives[1]. The convenience of smart phones meets our various needs in daily life, such as traffic navigation, social interaction, online shopping and entertainment and leisure. As of June 2022, China had 1.051 billion Internet users, of which 1.047 billion were mobile users, making up 99.6% of all Internet users, according to the 50th Statistical Report on the Development of the Internet in China [2]. But as time goes by, overuse of smart phones can lead people to develop addiction — MPA. MPA, often referred to as problematic mobile phone use and mobile phone dependence, is an addictive behavior that impairs daily functioning and is unable to be controlled when using a phone[3]. Billieux points out that individuals with a mobile phone addiction struggle to control their usage, resulting in a range of social, behavioral, and emotional problems in daily life[4]. Research has indicated that MPA can result in significant emotional, mental, and physical issues, which means that a person's physical and mental health are greatly impacted by MPA, and it also has an impact on our interactions with others and at work[5]. Studies have also pointed out that MPA is closely related to various problems, such as headache, visual impairment, lack of sleep and even depression[6–8]. Because they lack the mental power and self-control to resist, college students are highly dependent on their mobile phones,compared with other groups[9–10]. According to research findings, the current rate of MPA among Chinese college students has reached 23% and is still growing[8]. Therefore, it is necessary to explore college students' MPA and its influence.

Literature and Hypothesis

Sleep Quality and Mobile Phone Addiction

A key component of helping college students do better academically is their sleep quality[11], that is, getting enough sleep is crucial to ensuring that college students' academic performance improves. Many studies have shown that good sleep is an important physiological and psychological guarantee for human survival, which affects our health in many aspects, such as promoting metabolism, improving cognitive ability, eliminating brain fatigue and maintaining mood[12]. According to a Becker et al. study, 64% of students met the threshold for sleep disorders, and more than one-third of college students slept less than 7 hours on average at night[13]. Studies have shown that students with poor SQ report significantly more psychological problems, that is, the overall SQ shows a linear downward trend[14]. Unfortunately, as MPA intensifies, college students' SQ problems are more serious. Poor SQ is also one of the multiple effects of MPA, in other words, the intensification of MPA will inevitably lead to the reduction of SQ[3]. Studies at home and abroad have shown that teenagers' use of mobile phones for a long time or long time before going to bed will make sleep problems worse[15–16]. Surobhi et al. found through a survey of 224 medical students that another significant factor contributing to college students' declining physical function and low SQ was their excessive usage of mobile phones[17]. In summary, we propose the hypothesis that mobile phone addiction among college students positively predicts their sleep quality(H1).

Therefore, from the standpoint of MPA to explore the factors affecting the SQ of college students, in-depth analysis of the ways and conditions of influence, on this basis to protect and promote the SQ of college students to provide empirical support and practical inspiration, may have more obvious prevention and intervention effects. On the other hand,more attention is being paid to the direct correlation between MPA and SQ in the current study[18], and the mediating or moderating effect between MPA and SQ (how MPA affects SQ). Thus, the purpose of this study is to investigate how MPA affects SQ in college students as well as its mechanism.To more thoroughly examine the connection between MPA and SQ, the mediating mechanism between the two should be considered. This study hypothesizes that rumination and FOMO could be its mediating variables based on literature research.

Rumination as A Mediator

Rumination is the cognitive process of continually reflecting on the experiences one has had[19]. The cognitive theory of insomnia suggests that rumination (repetitive, nonconstructive thinking about past events) leads to increased arousal before bed, thereby reducing SQ[20]. At the same time, people who ruminate more have poorer SQ than those who ruminate less[21]. It is reasonable to show how MPA affects rumination, even if few studies have examined the direct association between MPA and rumination. For example, studies have also proved that MPA in college students will also produce rumination. The reason is that when mobile phone addicts frequently participate in social networks, they will experience social comparison and thus induce or intensify rumination thinking [22–23]. Previous studies have suggested that adolescents suffering from MPA are prone to academic procrastination and interpersonal problems, leading to rumination[24]. In a study involving 1,196 Chinese teenagers, Liu et al. discovered that rumination acted as an intermediate in the association between MPA and teenagers' SQ[18]. indicating that MPA may be a significant factor influencing low SQ. Rumination still had negative impacts and negatively predicted SQ, even after adjusting for anxiety and sadness, according to a long-term study[25]. This was especially true for high-trait ruminants. As per the cognitive theory of insomnia proposed by Harvey, individuals with high quality rumination tend to have unfavorable adjustment to cognitive activities, and are easy to trigger autonomous arousal and painful emotions. This is consistent with studies showing that rumination and poor SQ are associated with anxiety[26–27]. Therefore, Our hypothesis was that rumination acted as a moderator between college students' MPA and SQ(H2).

FOMO as A Mediator

FOMO refers to the unfavorable feelings such as unease and anxiety that occur when an individual thinks that he or she is missing out on beneficial things that others are doing or experiencing, and it has a strong dispersion[28]. The FOMO is essentially a negative state brought on by a person's need social communication, fear of being excluded from the group, and tendency to constantly check social media[29]. This negative emotion can damage personal behavior and physical and mental health, and is a common anxiety phenomenon among people, especially young people. Other studies have found that when people experience the FOMO, they will show a strong sense of unease. Thus,compared to women, men are more likely to use social media[30]. FOMO increases individual MPA and contributes significantly to social media addiction[31]. According to studies, those who experience a lot of negative emotions are more likely to experience a lot of FOMO and develop a smartphone addiction, and have poorer SQ[32]. According to the use and satisfaction theory, the FOMO originates from the lack of psychological needs, and social interaction can be established and maintained through smart phones[33]. Several researches have verified the existence of a direct or mediated correlation between FOMO and smartphone addiction[8]. Prior research has verified a positive correlation between FOMO and anxiety before going to bed, longer sleep latency and shorter sleep duration. It can also be said that FOMO will reduce the SQ of college students[13]. High sense of missing out individuals increased the likelihood of craving social media for information, extended bedtime, and decreased SQ. In conclusion, Our hypothesis is that FOMO acts as a moderator between college students' MPA and SQ(H2).

The Present Research

At present, investigating the mechanism of the relationship between college students' FOMO and rumination in MPA and SQ Still not be mentioned in the literature. In line with the I-PACE interaction model of Brand et al., MPA, as a susceptibility factor to the Internet, will produce cognitive and behavioral biases (rumination and FOMO) to specific stimuli[34]. There is a strong positive link between social media users' FOMO and rumination thinking, despite the fact that few studies have examined the relationship between rumination and FOMO[33]. Could FOMO also be affected by an individual's level of rumination?In conclusion, our study suggests that rumination and FOMO act as a chain of mediators between MPA and SQ based on the data shown above(H4). Assume the following for the model Fig. 1:

Subjects

An effective rate of 95.96% was achieved by deleting 59 invalid survey replies out of 1460 questionnaires collected from five universities and institutes in Jiangxi Province. Among them, there were 585 freshmen, 391 sophomores, 228 juniors, and 197 seniors, accounting for 41.76%, 27.91%, 16.27% and 14.06%, respectively. There were 463 female students and 938 male students, making up 33.05% and 66.95% of the student body, respectively. 422 students majored in humanities and social sciences and 979 in science, agriculture and medicine, accounting for 30.12% and 69.88% respectively. There were 1084 persons living in rural areas and 317 residing in metropolitan areas, accounting for 22.63% and 77.37% respectively. All participants were 19.35 years old on average, with a standard deviation of 0.81 years.

Measures

MPA Scale for College Students

In order to test the degree of MPA among college students, this study adopted the MPA Index Scale compiled by Professor Liang Yongchi based on the American Diagnostic and Statistical Manual of Mental Disorders (Fourth edition)[35]. There were 17 items in total, divided into four categories on the scale: inefficiency, avoidance, loss of control, and withdrawal. The scale used in this investigation had a Cronbach's α coefficient of 0.91.

Sleep Quality Scale

Assessing college students' SQ, the Chinese version of Pittsburgh Sleep Quality Index (PSQD), which was translated by Liu Xianchen et al., was adopted in this investigation[36]. This scale consists of 7 components and 18 items, each of which is calculated from the corresponding entry.The scale's Cronbach's α coefficient in this investigation was 0.91.

Rumination Scale

College students' rumination conditions were assessed using the ruminating scale, which was updated by Han Xiu and Yang Hongfei based on Nolen-Hoeksema[37]. With a total of 22 items, the measure has three dimensions: forced meditation, introspective meditation, and symptomatic rumination. The Cronbach's α coefficient, as determined by the Likert four-point scoring system (1 being never, 4 being always), is 0.96.

FOMO Scale

College students' fear of missing out was measured using the Chinese version of Li Qi's updated Fear of Missing Scale (FOMOS)[38]. There are eight questions in total on this one-dimensional scale. Level 5 score: The greater the score, the greater the person's level of FOMO. The scale's Cronbach's α coefficient in this investigation was 0.88.

Data Statistics

SPSS26.0 software and AMOS26.0 were used for data analysis. First, Model fit test and mediation effect analysis were performed using AMOS26.0 after variance and correlation analyses of the data were performed using SPSS26.0.

Common Method Deviation

The bias effect of popular approaches was tested in this study using the Harman single factor test technique[39]. Eleven factors had feature roots larger than one, according to the data, and the maximum factor variance explanation rate was 34.58%, which was less than the 40% criterion. Thus, it may be concluded that this study did not exhibit a significant common method bias impact.

3.2 Descriptive Statistics and Correlation Analysis among Variables

Table 1 shows that MPA has a substantial positive correlation with SQ (r = 0.51, p < 0.01), FOMO (r = 0.55, p < 0.01), and rumination (r = 0.62, p < 0.01). There is a positive correlation between rumination and SQ (r = 0.65, p < 0.01) and FOMO (r = 0.69, p < 0.01). The FOMO and SQ showed a strong positive association (r = 0.58, p < 0.01). Additional mediation effect tests can be carried out, according to the findings of the correlation study between the variables.Rumination and FOMO were the mediating variables, SQ was the dependent variable, gender and grade were the control variables, and MPA was the independent variable. All its variables were normalized in advance[40]. AMOS24.0 was used to model the structure, and it was found that the fitting index of the model was RMSEA = 0.06, CFI = 0.93, TLI = 0.91, SRMR = 0.04, and the fitting index was acceptable. Results were shown in Fig. 2: MPA positively predicted SQ (β1 = 0.14,p < 0.001), 95%CI [0.07, 0.17] excluding 0, H1 was established; We also found that rumination (β2 = 0.79,p < 0.001) and FOMO (β3 = 0.26,p < 0.001) were positively predicted by MPA. FOMO and SQ were positively predicted by rumination (β4 = 0.58, p < 0.001) and (β5 = 0.46, p < 0.001). Finally, the FOMO positively predicted SQ (β6 = 0.19,p < 0.001).

Table 1

Descriptive statistics and correlation analysis among variables (n = 1401)
	M	SD	1	2	3	4
1MPA	37.81	12.40	1
2Rumination	40.14	12.58	0.62^**	1
3FOMO	15.27	5.58	0.55^**	0.69^**	1
4SQ	6.15	3.85	0.51^**	0.65^**	0.58^**	1
p < 0.05, *p < 0.01, the same below.

Further, the mediating impact was tested using the deviation-corrected percentile Bootstrap approach, which involves repeating the extraction process 5000 times[41]. Three paths make up the mediating effect test, according to the research results (Table 2): Rumination was found to have an intermediary role between MPA and SQ, as evidenced by the relationship "MPA → rumination → SQ", 95%CI [0.21, 0.31] which accounted for 52% of the entire effect;"MPA → FOMO → SQ", 95%CI [0.03, 0.07], suggests that FOMO mediates the relationship between MPA and SQ. Rumination and FOMO act as a mediating factor between MPA and SQ, as shown by the relationship "MPA → rumination → FOMO → SQ", 95%CI [0.04, 0.11].The mediating impact is estimated to be (0.62)×(0.57)×(0.22) = 0.08, or 16% of the total effect. The confidence intervals of the above three paths do not include 0, indicating significant effects of the three paths.H2, H3, and H4 are established separately

Table 2

Bootstrap analysis of mediation effect test
Path	Effect	Boot SE	BootLLCI		BootULCI	Effect ratio
MPA→SQ	0.12	0.03	0.07		0.17
MPA→Rumination→SQ	0.26	0.03	0.21	0.31		0.52
MPA→FOMO→SQ	0.04	0.01	0.03	0.07		0.08
MPA→Rumination→FOMO→SQ	0.08	0.02	0.04	0.11		0.16

The Direct Effect of MPA on SQ of College Students

According to the study's findings, college students' MPA and SQ have a substantial positive correlation and significantly positively predicts SQ, which is in line with the findings of earlier study[42]. From the theory of technology addiction, it can be inferred that college students addicted to mobile phones will use mobile phones too much, which will inevitably shorten their sleep time. Meanwhile, some studies have found that excessive use of mobile phones at night will naturally affect the activity of individual pineal gland, thus affecting the secretion of melatonin, and thus negatively affecting the quality of sleep[43]. Excessive use of mobile phones will cause various stimuli for individuals, including various cognitive, behavioral and physiological stimuli, which will inevitably increase the arousal level and lead to the decline of SQ[44].College students who are dependent on their phones may experience physical pain due to long-term use of mobile phones, such as limb numbness, cervical spine damage and even hearing loss, which will aggravate individual sleep difficulties[45].

The Mediating Role of Rumination and FOMO on MPA and SQ

Firstly, MPA of college students can affect SQ through positive prediction of rumination, which is in line with earlier research[25]. Prior research has demonstrated that stressful events such as high levels of study procrastination and poor interpersonal relationships are highly likely to lead to low self-esteem in college students, leading to MPA[46, 47]. Rumination can be induced by stressful life experiences and low self-esteem, as per the stress response model[48]. As a result, rumination is a major trigger for those who abuse mobile phones, and they encounter more unfavorable life occurrences[49]. In addition, there is indeed one study confirming that teenagers with MPA may eventually experience more ruminating after using a phone[18], and it has been demonstrated that cell phone addiction can disrupt SQ through rumination. This study also showed that rumination significantly positively predicted the SQ of college students, and further confirmed that rumination functioned as a mediator in the relationship between MPA and college students' SQ.

Secondly, this study found that MPA of college students can affect SQ through missing fear. The results of the study once again confirmed that the FOMO and problematic mobile phone use, or MPA, are intimately associated[50], and also confirmed that the FOMO is related to poor SQ[51]. This is in line with other study findings, which showed that FOMO increased with MPA degree. For instance, the majority of college students currently use their phones to access social media before going to bed.At the same time, research indicates that college students who rely more heavily on their phones also spend more time on social media, which can lead to FOMO, a delay in falling asleep, and a decrease in self-esteem. More studies have confirmed that FOMO mediates the relationship between MPA and SQ from both cognitive and behavioral aspects[52]. In particular, the use of social media through mobile phones by college students who are accustomed to staying up late exacerbates FOMO, delaying sleep time from a behavioral point of view, increasing cognitive arousal[53], and worse SQ.

Additionally, the study discovered that through the chain mediation of rumination and FOMO, college students' MPA can positively predict SQ. This finding in this study reflects the close link between rumination and FOMO, and no previous studies have explored this mechanism. These results indicate that the influence of MPA on SQ of college students can be formed through rumination and FOMO. As discussed above, The majority of college students who are dependent on their phones are more vulnerable to stressful situations such as study procrastination and interpersonal communication, and stressful events are even more inducements to rumination. Conversely, college students who are engrossed in rumination and fear missing out typically resort to social media, which blocks sleep activities and increases the bedtime time[54]. The technology addiction model theory also holds that negative emotions are easily perceived as internal triggers, thus generating emotional response (FOMO) and increasing attention to behavioral stimuli, naturally prolongs bedtime[34].Although this study's chain mediation effect size is only 0.08, which is not very large, we still need to be concerned about how rumination and the FOMO chain effect affect college students' SQ. College students should simultaneously keep a calm and cheerful demeanor, sleep at a normal hour, and use their phones in an active and responsible manner.

Significance and Deficiency of the Study

Regarding the prevention and treatment of SQ among college students, this study is extremely important. First of all,The MPA of college students can positively predict their SQ. College students must be actively encouraged to put down their phones, deliberately control their need for them, limit how much they use them, ease MPA, and ultimately increase SQ. Secondly, this study also found that MPA of college students indirectly affects their SQ through rumination and FOMO. Therefore, schools can identify students with MPA symptoms through the observation of teachers and students or the test of relevant scales. Meanwhile, the level of rumination and FOMO can be reduced through positive and effective cognitive ways or emotional responses. Finally, while using mobile phones as little as possible, students themselves should also learn and train the ability to reduce rumination and FOMO, reduce self-focus and attention, and ensure adequate sleep time.

The shortcomings of this study are as follows: First, data is collected by questionnaire and all subjects are self-reported, which is subjective to a certain extent. Second, the cross-sectional design of this study can consider longitudinal follow-up research in the future. Third, the sampling range can be appropriately expanded, not only limited to college students, but also teenagers and elderly groups.

MPA will affect the SQ of Chinese college students. Meanwhile, rumination and FOMO can indirectly affect the SQ separately, and rumination and FOMO can also have a chain effect on the SQ.

Data availability statement

The corresponding author can make the raw data in this study available to anyone who needs it.

Acknowledgments

The authors wish to thank all the participants for their efforts in the study

Competing interests

We declare that the authors do not have any conflicting interest or any other interests that might be seen to affect the results and/or discussion presented in this manuscript.

Funding

This work was supported by Social science project,College of Science and Technology,Nanchang Hangkong University(KYSK2306),and the Life Education studio, College of Science and Technology,Nanchang Hangkong University.

Authors' contributions

Junliang Zhang and Shuang zheng conceived and designed the experiments and wrote the manuscript. Yu He, Chuangang Wan, and Junliang Zhang carried out the protocol and the questionnaire survey andrevised the manuscript. Junliang Zhang analyzed the data. All authors have read and agreed to the published version of the manuscript.

Ethics approval and consent to participate

Approval for this study was granted by the Ethics Committee of College of the Science and Technology , Nanchang Hangkong University, and written informed consent was obtained from all participants. The methods adhered to the principles outlined in the 1964 Helsinki Declaration.

Informed Consent

All authors have read and agreed to the published version of the manuscript.

Zhang MX, &Wu AM. S.Effects of smartphone addiction on SQ among Chinese university students: The mediating role of self-regulation and bedtime procrastination.Addictive Behaviors.2020;111,106552.https://doi.org/10.1016/j.addbeh.2020.106552. Epub 2020 Jul 13.
CNNIC.Statistical Report on the Development of Internet in China. Retrieved April 21. 2023, from https://www.cnnic.cn/NMediaFile/2022/1020/MAIN16662586615125EJOL1VKDF.pdf.
Demirci K, Akgönül M, Akpinar. A.Relationship of smartphone use severity with SQ, depression, and anxiety in university students. J Behav Addictions. 2015;4(2):85–92. https://doi.org/10.1556/2006.4.2015.010.
Billieux J. Problematic Use of the Mobile Phone: A Literature Review and a Pathways Model. Curr Psychiatry Reviews.20102; 8(4), 299–307.
Kim EJ, Namkoong K, Ku T, Kim S. J.The relationship between online game addiction and aggression, self-control and narcissistic personality traits. Eur Psychiatry. 2008;23(3):212–8. https://doi.org/10.1016/j.eurpsy.2007.10.010. Epub 2007 Dec 31.
Auvinen A, Feychting M, Ahlbom A, Hillert L, Elliott P, Schüz J, Kromhout H, Toledano MB, Johansen C, Poulsen AH, Vermeulen R, Heinävaara S, Kojo K, Tettamanti G. Study Group. Headache, tinnitus and hearing loss in the international Cohort Study of Mobile Phone Use and Health (COSMOS) in Sweden and Finland. Int J Epidemiol. 2019;48(5):1567–79.
Lissak G. Adverse physiological and psychological effects of screen time on children and adolescents: Literature review and case study. Environ Res. 2018;164:149–57. https://doi.org/10.1016/j.envres.2018.01.015.
Li Y, Li G, Liu L, Wu H. Correlations between MPA and anxiety, depression, impulsivity, and poor SQ among college students: A systematic review and meta-analysis. J Behav addictions. 2020;9(3):551–71.
Li L, Mei S, Niu. Z.Influences of smartphone addiction and negative affect on SQ among university students (in Chinese). Chin J Public Health. 2016;32(5):646–9. https://doi.org/10.16128/j.cnki.1005-3611.2016.02.036.
Long J, Liu TQ, Liao YH, Qi C, He HY, Chen SB, et al. Prevalence and correlates of problematic smartphone use in a large random sample of Chinese undergraduates. BMC Psychiatry. 2016;16(1):408. https://doi.org/10.1186/s12888-016-1083-3.
Rathakrishnan B, Singh B, Kamaluddin SS, Yahaya MR, Mohd Nasir A, Ibrahim MA. Ab Rahman, Z.Smartphone Addiction and SQ on Academic Performance of University Students: An Exploratory Research. Int J Environ Res Public Health. 2021;18(16):8291. https://doi.org/10.3390/ijerph18168291.
Neikrug AB, Ancoli-Israel S. Sleep disorders in the older adult—a mini-review. Gerontology. 2010;56(2):181–9.
Becker SP, Jarrett MA, Luebbe AM, Garner AA, Burns GL, Kofler MJ. Sleep in a large, multi-university sample of college students: sleep problem prevalence, sex differences, and mental health correlates.Sleep health.2018;4(2), 174–181. https://doi.org/10.1016/j.sleh.2018.01.001.
Pensuksan WC, Lertmaharit S, Lohsoonthorn V, Rattananupong T, Sonkprasert T, Gelaye B, Williams MA. Relationship between Poor SQ and Psychological Problems among Undergraduate Students in the Southern Thailand. Walailak J Sci Technol. 2016;13(4):235–42.
Liu S, Wing YK, Hao Y, Li W, Zhang J, Zhang B. The associations of long-time mobile phone use with sleep disturbances and mental distress in technical college students: a prospective cohort study. Sleep 2018https://doi.org/10.1093/sleep/zsy213.
Lee JE, Jang S-I, Ju YJ, Kim W, Lee HJ, Park E-C. Relationship between Mobile Longitudinal Study of the Korean Children & Youth Panel Survey. Journal of Korean Medical Science.2017; 32(7).https://doi.org/1166.10.3346/jkms.2017.32.7.1166.
Surobhi Chatterjee&Sujita Kumar Kar. Smartphone Addiction and Quality of Sleep among. Indian Med Students Psychiatry. 2021;84:2182–191.
Liu Q-Q, Zhou Z-K, Yang X-J, Kong F-C, Niu G-F, Fan C-. Y.MPA and SQ among Chinese adolescents: A moderated mediation model. Comput Hum Behav. 2017;72:108–14. https://doi.org/10.1016/j.chb.2017.02.042.
Nolen-Hoeksema S, Wisco BE, Lyubomirsky SR, Rumination. Perspect Psychol Sci. 2008;3(5):400–24. 10.1111/j.1745-6924.2008.00088.x.
Morin CM, Rodrigue S, Ivers H. Role of stress, arousal, and coping skills in primary insomnia. Psychosom Med. 2003;65(2):259–67. https://doi.org/10.1097/01.psy.0000030391.09558.a3.
Carney CE, Harris AL, Moss TG, Edinger JD. Distinguishing rumination from worry in clinical insomnia. Behav Res Ther. 2010;48(6):540–6. https://doi.org/10.1016/j.brat.2010.03.004. Epub 2010 Mar 11.
Feinstein BA, Hershenberg R, Bhatia V, Latack JA, Meuwly N, Davila. J.Negative social comparison on Facebook and depressive symptoms: Rumination as a mechanism. Psychol Popular Media Cult. 2013;2(3):161–70. https://doi.org/10.1037/a0033111.
Shaw AM, Timpano KR, Tran TB, Joormann J. Correlates of Facebook usage patterns: The relationship between passive Facebook use, social anxiety symptoms, and brooding. Comput Hum Behav. 2015;48:575–80. https://doi.org/10.1016/j.chb.2015.02.003.
Chen L, Yan Z, Tang W, Yang F, Xie X, He. J.MPA levels and negative emotions among Chinese young adults: The mediating role of interpersonal problems. Comput Hum Behav. 2016;55:856–66. https://doi.org/10.1016/j.chb.2015.10.030.
Thomsen DK, Yung Mehlsen M, Christensen S, Zachariae R. Rumination—relationship with negative mood and SQ. Pers Indiv Differ. 2003;34(7):1293–301. https://doi.org/10.1016/s0191-8869(02)00120-4.
Harvey. AG.A cognitive model of insomnia. Behav Res Ther.2002;40(8):869–93.
Chang X, Guo C, Zhou H, Liu L. Impact of rumination on sleep quality among patients with nonalcoholic fatty liver disease: a moderated mediation model of anxiety symptoms and resilience. BMC Psychiatry. 2023;23(1):84. https://doi.org/10.1186/s12888-023-04572-8.
Przybylski AK, Murayama K, DeHaan CR, Gladwell V, Motivational. emotional, and behavioral correlates of FOMO.Computers in Human Behavior.2013;29(4), 1841–1848.https://doi.org/10.1016/j.chb.2013.02.014.
Wolniewicz CA, Tiamiyu MF, Weeks JW, Elhai J. D.Problematic smartphone use and relations with negative affect, FOMO, and fear of negative and positive evaluation. Psychiatry Res. 2018;262:618–23. https://doi.org/10.1016/j.psychres.2017.09.058.
Li L, Niu Z, Mei S, Griffiths. M.A network analysis approach to the relationship between FOMO (FoMO), smartphone addiction, and social networking site use among a sample of Chinese university students.Comput. Hum Behav. 2021;128:107086.
Li L, Griffiths MD, Mei S, Niu ZFOMO. and Smartphone Addiction Mediates the Relationship Between Positive and Negative Affect and SQ Among Chinese University Students.Frontiers in psychiatry.2020;11,877.https://doi.org/10.3389/fpsyt.2020.00877.
Ferris AL, Hollenbaugh EE, Sommer P. A.Applying the Uses and Gratifications Model to Examine Consequences of Social Media Addiction. Social Media Soc. 2021;7(2):205630512110190. https://doi.org/10.1177/20563051211019003.
Elhai JD, Levine JC, Alghraibeh AM, Alafnan AA, Aldraiweesh AA, Hall BJFOMO. Testing relationships with negative affectivity, online social engagement, and problematic smartphone use. Comput Hum Behav. 2018;89:289–98. https://doi.org/10.1016/j.chb.2018.08.0207.
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. Neurosci Biobehav Rev. 2016;71:252–66. https://doi.org/10.1016/j.neubiorev.2016.08.033.
Leung LLINKING, PSYCHOLOGICAL ATTRIBUTES TO ADDICTION AND IMPROPER USE OF THE MOBILE, PHONE AMONG ADOLESCENTS IN HONG KONG. J Child Media. 2008;2(2):93–113. https://doi.org/10.1080/17482790802078565.
Liu Xianchen, Tang Maoqin, Hu Lei, Wang Aizhen, Wu Hongxin, Zhao Guifang... Li W S. Reliability and validity of Pittsburgh SQ Index. Chinese Journal of Psychiatry .1996;(02),103-107.
Han X. Yang Hongfei.Nolen-Hoeksema Ruminative Thinking Scale in China. Chin J Clin Psychol.2009;(05),550–1.
Li Qi W, Jianing Z, Jia Yanru. The validity and reliability of error anxiety scale in college students. Chin J Mental Health. 2019;33(4):6.
Zhou H, Long LR. Statistical test and control of common method deviation. Adv Psychol Sci. 2004;12(6):942–50.
Wen ZL, Ye BJ. .Mediation effect analysis: method and model development. Adv Psychol Sci. 2014;22(5):731–45.
Fang J, Zhang MQ. Point estimation and interval estimation of intermediary effects: product distribution method, non-parametric Bootstrap method and MCMC method. Acta Physiol Sinica. 2012;44(10):1408–20.
Wang Haiyun C, Kunpan Z, Zhiqiang, et al. Study on the influence of MPA on SQ of college students in plateau area. J Practical Prev Med. 2019;30(3):325–8.
Exelmans L, Van den Bulck. J Bedtime Mob phone use sleep adults Soc Sci Med. 2016;148:93–101.
Morin CMI. Psychological assessment and management. New York, NY, USA: Guilford Press; 1993.
Gu Junjuan QUAN, Qiru ZHANG. Jiayang.Effects of MPA on SQ and learning burnout in college students. J North China Univ Sci Technol (Medical Edition). 2021;23(5):389–94.
Jung EJ. Y.J.Han.The effect of adolescents’ time perspective and self-control on academic procrastination: The mediating effect of cellular phone addiction. Korean J Child Stud. 2014;35(1):119–33.
Yan FCL, Tang Z, Yang W, Xie F, He X. Jincai.MPA levels and negative emotions among Chinese young adults: The mediating role of interpersonal problems. Comput Hum Behav. 2016;55:856–66. 10.1016/j.chb.2015.10.030.
Kuster F, Orth U, Meier LL. Rumination Mediates the Prospective Effect of Low Self-Esteem on Depression: A Five-Wave Longitudinal Study. Pers Soc Psychol Bull. 2012;38(6):747–59. .https://doi.org/10.1177/0146167212437250.
Robinson LB. Alloy Negative cognitive styles and stress-reactive rumination interact to predict depression: A prospective study. Cogn Therapy Res. 2003;27(3):275–91.
Santana-Vega L, Gomez-Munoz A, Feliciano-Garcia L. Adolescents problematic mobile phone use, FOMO and family communication. Comunicar. 2019;27(59):39–47.
Almeida F, Marques DR, Gomes AA. A preliminary study on the association between social media at night and sleep quality: The relevance of FOMO, cognitive pre-sleep arousal, and maladaptive cognitive emotion regulation. Scand J Psychol. 2023;64(2):123–32. 10.1111/sjop.12880. Epub 2022 Oct 18.
Scott H, Woods HC. Fear of missing out and sleep: Cognitive behavioural factors in adolescents' nighttime social media use. J Adolesc. 2018;68:61–5. https://doi.org/10.1016/j.adolescence.2018.07.009.
Huang T, Liu Y, Tan TC, Wang D, Zheng K, Liu W. Mobile phone dependency and sleep quality in college students during COVID-19 outbreak: the mediating role of bedtime procrastination and fear of missing out. BMC Public Health. 2023;23(1):1200. https://doi.org/10.1186/s12889-023-16061-4.
Zhang Dan HU, Xueqing LIUQ. Stress and sleep quality in college students: the chain mediating role of rumination and mental resilience. J Psychol Sci. 2019;44(01):90–6.

No competing interests reported.

Download PDF

Version 1

posted

You are reading this latest preprint version

Mobile phone addiction and sleep quality in college students: a mediation model of rumination and fear of missing out

Status:

Version 1

Abstract

Purpose

Methods

Results

Conclusion

Introduction

Literature and Hypothesis

Sleep Quality and Mobile Phone Addiction

Rumination as A Mediator

FOMO as A Mediator

The Present Research

Methods

Subjects

Measures

MPA Scale for College Students

Sleep Quality Scale

Rumination Scale

FOMO Scale

Data Statistics

Results

Common Method Deviation

3.2 Descriptive Statistics and Correlation Analysis among Variables

Discussion

The Direct Effect of MPA on SQ of College Students

The Mediating Role of Rumination and FOMO on MPA and SQ

Significance and Deficiency of the Study

Conclusion

Declarations

References

Additional Declarations

Status:

Version 1