Exploring associations between social media addiction, social media fatigue, fear of missing out and sleep quality among university students: A cross-section study

Xinhong Zhu; Taoyun Zheng; Linlin Ding; Xiaona Zhang; Zhihan Li; Hao Jiang

doi:10.1371/journal.pone.0292429

. 2023 Oct 5;18(10):e0292429. doi: 10.1371/journal.pone.0292429

Exploring associations between social media addiction, social media fatigue, fear of missing out and sleep quality among university students: A cross-section study

Xinhong Zhu ^1,^‡,^*, Taoyun Zheng ^1,^‡, Linlin Ding ¹, Xiaona Zhang ¹, Zhihan Li ¹, Hao Jiang ¹

Editor: Ahsan Ali²

PMCID: PMC10553250 PMID: 37796805

Abstract

Background

Social media use has been linked to poor sleep outcomes among university students in the cyber age, but the association between the negative consequences of social media use and sleep problems is not yet well understood. The present study investigated the relationships among social media usage, social media fatigue (SMF), fear of missing out (FoMO), social media addiction (SMA) and sleep quality in university students.

Method

An online survey was administered to 2744 respondents that included the Pittsburgh Sleep Quality Index (PSQI); questionnaires evaluating FoMO, SMF, and SMA; and questions regarding sleep duration, social media use, health status, and demographic information.

Result

A total of 19.9% of respondents suffered from sleep disturbance. A total of 15.6% of participants had sleep durations less than 5 h, and 21.6% of subjects had sleep durations longer than 9 h. Sleep quality was positively associated with SMF (OR = 1.387, 95% CI: 1.103~1.743), and SMA (OR = 1.415, 95% CI: 1.118~1.791). The relationship between FoMO and sleep disturbance was not significant. Compared to a sleep duration > 9 h, SMF increased the risk of shorter sleep durations [5–6 h sleep (OR = 2.226, 95% CI: 1.132~4.375), 6–7 h sleep (OR = 1.458, 95% CI: 1.061~2.002), and 7–8 h sleep (OR = 1.296, 95% CI: 1.007~1.670)]. FoMO and SMA did not significantly affect sleep duration. In addition, SMA (OR = 3.775, 95% CI: 3.141~4.537), FoMO (OR = 3.301, 95% CI: 2.753~3.958), and sleep disorders (OR = 1.284, 95% CI: 1.006~1.638) increased SMF.

Conclusion

Upon experiencing negative consequences of social media use, such as SMF and SMA, university students were likely to experience sleep problems. Further research exploring the interventions that improve sleep and alleviate negative consequences of social media use should be conducted.

1. Introduction

Social media platforms have penetrated all aspects of university students’ lives. According to the China Internet Network Information Center (CNNIC), the average weekly time spent online by Chinese netizens increased from 18.7 h in 2011 to 26.9 h in 2021 [1, 2]. Recent findings indicated that 99.6% of Chinese netizens used smartphones to access the internet, and 17.4% of Chinese internet users aged 20~29 years had internet dependence [1]. Multifunctional smartphone applications and consistent internet access are considered to explain the increased, and even excessive use of social media platforms [3]. For university students, social media is the main channel for communicating and sharing information, personal messages, opinions and ideas [4]. It was reported that approximately 74.5% of university students spent two to six hours on social media each day [5]. However, excessive social media use could have a series of negative consequences, such as problematic social media use [6], fear of missing out (FoMO) [7], social media fatigue (SMF) [8], social media addiction (SMA) [9], poor sleep quality [10, 11], poor mental health [10], and decreased academic performance [12].

2. Literature review and hypotheses

Individuals who experience FoMO may experience an increased level of negative emotions that may lead to impairments in social interactions [13]. There is a reciprocal relationship between FoMO and problematic social media use, which may lead individuals to experience SMF and SMA [14–16]. Constantly attending to social media may increase exhaustion levels and result in SMF [17]. SMF is defined as the subjective and negative feeling of tiredness and burnout due to social media use [17]. As time spent on social media platforms increased, an increasing number of university students experienced SMF and wanted to stop using social media [12, 18], which may contribute to a decrease in academic performance and use discontinuance [12, 19, 20]. SMA, the consequence of the compulsive use of social media platforms, manifests as behavioral addiction symptoms [21]. The pooled prevalence of SMA worldwide was found to be 5% (95% CI: 3%~7%) [22]. Accumulating evidence has shown that SMA is a growing problem among university students, and is related to self-esteem, life satisfaction, mental health and academic performance [21, 23–25]. Given that social media has become as a near-ubiquitous aspect of university students’ lives, excessive social media use is becoming increasingly evident, and the negative consequences of excessive social media usage have attracted public concern.

Recently, increasing attention has been given to the relationship between sleep disorders and social media usage. University students frequently experience poor sleep [26, 27]. The prevalence of insomnia in university students worldwide has been found to be 18.5%, which is much higher than the prevalence in the general population (7.4%) [28]. The overall pooled prevalence rates of sleep disturbances and insomnia symptoms in Chinese university students are 25.7% (95% CI: 22.5~28.9%) and 23.6% (95% CI: 18.9~29.0%), respectively [29]. The mechanisms underlying the relationships between the use of social media and sleep problems are unclear, but a theoretical model of the relationship has been proposed [30] and suggests several possible mechanisms. According to this model, social media use may directly affect sleep quality by consuming excess time or interfere with sleep by altering psychological arousal via observation of stimulating online content [30]. Relationships among delayed sleep onset, poor quality of sleep and increased time spent on the internet have been reported in previous studies [31, 32]. Frequent social media use predicted both poor mental health and poor sleep outcomes in youth [10]. Evidence showed that the impact of negative affect on sleep quality was mediated by FoMO and smartphone addiction in a sample of Chinese university students [33]. Additionally, insomnia partially mediated the significant associations of interpersonal stress and FoMO with mental health in college students [34]. Among individuals with internet addiction, the overall pooled odds ratio of experiencing sleep disturbance was 2.20 (95% CI: 1.77–2.74), and a significant reduction in sleep duration was observed [35]. Furthermore, a higher rate of insomnia was observed among Norwegian university students with higher levels of SMA [36]. In summary, FoMO and SMA are closely associated with sleep quality. Although the relationship between chronic fatigue and sleep quality was confirmed among university students [37], few studies on the relationship between SMF and sleep quality have been conducted among Chinese university students. Given that FoMO and SMA drive SMF [38], we hypothesized that SMF is related to sleep quality.

Although social media use is linked with poor sleep outcomes, few studies have focused on the relationships among FoMO, SMA, SMF and sleep quality. It is important to clarify the relationships among these four factors to determine the role of negative consequences of social media use on sleep quality and to develop interventions to improve university students’ sleep quality in further studies. Thus, this study was aimed to investigate the relationships among social media use, FoMO, SMA, SMF, sleep disturbance and sleep duration in Chinese university students.

3. Methods

3.1 Participants and data collection

Using convenience sampling, 3015 participants from 4 universities and 4 vocational and technical colleges in Wuhan were selected among junior college students, and undergraduate students and above. The inclusion criteria for participants were voluntary participation in in the study and ability to cooperate with the study. Data were collected using structured questionnaires in February, 2021. Participants completed questionnaires online via Questionnaire Star. Data from 3015 respondents were included in the analysis; data from 271 respondents were excluded due to missing values.

3.2 Instruments

Pittsburgh Sleep Quality Index (PSQI)

The Chinese version of scale was developed by Liu et al. [39]. The scale contains 19 items in 7 subscales: subjective sleep quality, sleep latency, sleep duration, habitual sleep efficiency, sleep disturbances, use of sleep medication, and daytime dysfunction. The total score ranges from 0 to 21 points (range of 0 to 3 points for each subscale), with higher scores indicating worse sleep quality. The cutoff value for sleep disturbance is 7 [39]. In this study, the Cronbach’s α value of the PSQI was 0.663.

Sleep duration

We assessed sleep duration by asking respondents the following question: “How many hours did you usually sleep at night in the past month?” The responses for sleep duration were as follows: “< 5 h”, “5–6 h”, “6–7 h”, “7–8 h”, “8–9 h”, and “>9 h”.

Social Media Fatigue (SMF)

The scale was based on previous studies [8, 40, 41]. The tool contains 18 items on three subscales: anxiety (8 items), information value (4 items), escaping from social media (6 items). Responses to each item are rated on a five-point Likert scale ranging from 1 (strongly disagree) to 5 (strongly agree). The Cronbach’s α values of the three dimensions in the present study were 0.918, 0.901 and 0.904, respectively. A high score indicates a high level of SMF. The participants were divided into two groups using the median SMF score for statistical analysis: a high score group (≥50, n = 1374), and a low score group (<50, n = 1370).

Social Media Addiction (SMA)

The scale was developed by Liu and Ma [23] and was originally used with college students in China. The tool contains 28 items rated on a 5-point Likert scale ranging from 1 (strongly disagree) to 5 (strongly agree). The Cronbach’s α value of the SMA was 0.971 in this study. The participants were divided into two groups using the median SMA score for statistical analysis: a high score group (≥84, n = 1376), and a low score group (<84, n = 1368).

Fear of Missing Out (FoMO)

The Chinese version of FoMO, which was adapted by Li et al following standardized international guidelines, was implemented to measure FoMO among university students in China [42, 43]. Each item is rated on a five-point Likert scale ranging from 1 (strongly disagree) to 5 (strongly agree). The Cronbach’s α value for FoMO in the present study was 0.924. The participants were divided into two groups using the median FoMO score for statistical analysis: a high score group (≥32, n = 1398) and a low score group (<32, n = 1346).

Social media use

Internet use was ascertained with the following items: (1) “purposes of using social media” (to stay in touch with what my friends are doing, to research/find products to buy, to find funny or entertaining content, to learn, to stay up-to-date with news and current events, to play game, to share photos or videos with others, to initiate a topic, because a lot of my friends are on them, and others). (2) “number of social media accounts” (0~2, 3~4, 5~6, 7~8, 9~). (3) “time spent on social media per day” (0~2 h, 2~4 h, 4~6 h, 6~8 h, 8 h~). (4) “Do you spend more time on social media than real world?” (less, the same, slightly, much). (5) “browsing social media before bed” (strongly disagree, disagree, not agree, agree, strongly agree).

Demographic questionnaire

A demographic information sheet was used to acquire basic information, such as gender, age, residence, education level (junior college students, undergraduate students and above), single-child, parental marital status (married, single parent/stepparent, and others), and self-reported health status (good, fair, bad, chronic disease, history of serious illness, family history of serious illness).

3.3 Ethics statement

The University Research Ethics Committee of Hubei University of Chinese Medicine approved the study which was conducted in 2021 (2018-ICE-023). The study was carried out in accordance with the requisite ethical standards (e.g., the Helsinki declaration), and written informed consent was obtained from all participants. Prior to the collection of data, the purposes and procedures of this study were explained to the respondents. Participants were informed that they could withdraw from the study at any time. Data were collected only from those who voluntarily agreed to participate and provided written informed consent.

3.4 Data analysis

All analyses were performed using SPSS 20.0, and the significance threshold level of statistical tests was set at p < 0.05. Descriptive statistics of participants’ demographic characteristics, internet use and SMF are described using number (n) and percentage (%), mean ± SD, or median and interquartile range. Logistic regression was used to identify significantly factors (p < 0.05) associated with sleep quality, sleep duration, social media use, SMF, SMA, FoMO, and demographic information. The binary regression results shown in Table 1 were obtained with the following steps: (1) In Model 1, FoMO, SMF and SMA were entered as independent variables, and sleep quality was entered as the dependent variable. (2) In Model 2, FoMO, SMF, SMA and social media use were entered as independent variables. (3) In Model 3, demographic variables were entered as independent variables along with the variables in Model 2 to identify factors significantly affecting sleep quality. Then, variables were entered with p < 0.25 into a multivariate logistic regression analysis to identify predictors of sleep duration in univariate analysis. Multivariate logistic regression analyses were conducted with short sleep duration as the outcome variable (> 9 h as the reference category), and social media use, SMF, SMA, FoMO, and demographic information as the exposure variables (Table 2). In addition, binary regression was fitted to access the factors affecting SMF after considering the effects of FoMO, SMA, sleep quality, sleep duration, social media use, and demographic information, as shown in the Table 3. The strength of the association was evaluated with odds ratios (ORs) and 95% confidence intervals (CIs). The models’ goodness of fit was checked by using omnibus tests of model coefficients for overall fitness of the model and the Hosmer and Lemeshow test for fit of the model to the data.

Table 1. Factors associated with sleep quality among university students.

Variable	Model 1	Model 2	Model 3
	OR (95%CI)	OR (95%CI)	OR (95%CI)
SMF	1.480 (1.190~1.839) ^**	1.460 (1.169~1.824) ^*	1.387 (1.103~1.743) ^*
SMA	1.582 (1.270~1.972) ^**	1.391 (1.105~1.749) ^*	1.415 (1.118~1.791) ^*
FoMO	1.225 (0.987~1.521)	1.132 (0.906~1.414)	1.143 (0.910~1.435)
Purposes
To stay up-to-date with news and current events (Yes)		0.801 (0.650~0.986) ^*	0.834 (0.673~1.035)
To share photos or videos with others (Yes)		1.347 (1.064~1.706) ^*	1.339 (1.050~1.708) ^*
Do you spend more time on social media than real world?
Less		Ref	Ref
The same		1.383 (1.022~1.872) ^*	1.302 (0.956~1.773)
Slightly		1.571 (1.149~2.162) ^*	1.520 (1.103~2.094) ^*
Much		2.007 (1.409~2.858) ^**	1.812 (1.259~2.607) ^*
Time spent on social media (h)
0~2		Ref	Ref
2~4		1.101 (0.801~1.513)	1.120 (0.809~1.551)
4~6		1.301 (0.931~1.818)	1.303 (0.922~1.841)
6~8		1.144 (0.753~1.738)	1.175 (0.764~1.807)
8~		1.983 (1.290~3.048) ^*	1.889 (1.208~2.953) ^*
Education
Junior college students			Ref
Undergraduate students and above			0.658 (0.533~0.812) ^**
Self-reported health status
Good			0.617 (0.393~0.971) ^*
Fair			1.795 (1.193~2.701) ^*
Bad			3.474 (1.462~8.256) ^*

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*: p < 0.05

**: p < 0.001

Model 1was crude model; Model 2 was adjusted for social media use; Model 3 was adjusted for social media use and demographic information.

Table 2. Factors associated with sleep duration among university students.

Variables	< 5 h ^a	5–6 h ^a	6–7 h ^a	7–8 h ^a	8–9 h ^a
	AOR (95%CI)	AOR (95%CI)	AOR (95%CI)	AOR (95%CI)	AOR (95%CI)
SMF	0.984 (0.445~2.175)	2.226 (1.132~4.375) ^*	1.458 (1.061~2.002) ^*	1.296 (1.007~1.670) ^*	1.034 (0.814~1.314)
SMA	1.848 (0.797~4.285)	1.161 (0.588~2.294)	1.110 (0.802~1.535)	1.007 (0.778~1.305)	1.046 (0.818~1.337)
FoMO	1.007 (0.455~2.228)	0.898 (0.473~1.703)	1.020 (0.744~1.398)	0.957 (0.744~1.232)	0.994 (0.783~1.261)

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*: p < 0.05

^a: > 9 h as reference category

Table 3. Factors associated with SMF among university students.

Variable	Model 1	Model 2	Model 3
	OR (95%CI)	OR (95%CI)	OR (95%CI)
SMA	3.872 (3.246~4.618) ^**	3.771 (3.142~4.526) ^**	3.775 (3.141~4.537) ^**
FoMO	3.276 (2.747~3.906) ^**	3.243 (2.708~3.882) ^**	3.301 (2.753~3.958) ^**
Sleep disturbance	1.363 (1.070~1.721) ^*	1.340 (1.057~1.699) ^*	1.284 (1.006~1.638) ^*
Sleep duration
< 5 h	0.855 (0.400~1.828)	0.870 (0.400~1.894)	0.898 (0.410~1.966)
5~6 h	1.777 (0.904~3.495)	1.972 (0.995~3.908)	1.990 (0.995~3.982)
6~7 h	1.408 (1.024~1.935) ^*	1.428 (1.035~1.970) ^*	1.353 (0.975~1.877)
7~8 h	1.279 (1.003~1.632) ^*	1.349 (1.052~1.730) ^*	1.273 (0.986~1.643)
8~9 h	1.013 (0.801~ 1.281)	1.049 (0.827~1.331)	1.026 (0.806~1.306)
> 9 h	Ref	Ref	Ref
Purposes of using social media
Because a lot of my friends are on them		1.372 (1.062~1.772) ^*	1.432 (1.106~1.854) ^*
Do you spend more time on social media than real world?
Less		Ref	Ref
The same		1.025 (0.806~1.302)	1.023 (0.804~1.302)
Slightly		1.240 (0.956~1.608)	1.233 (0.949~1.601)
Much		1.724 (1.252~2.373) ^*	1.655 (1.198~2.286) ^*
Education
Junior college students			Ref
Undergraduate students and above			1.310 (1.085~1.581) ^*

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*: p < 0.05

**: p < 0.001

Model 1was crude model; Model 2 was adjusted for Internet use; Model 3 was adjusted for Internet use and demographic information.

4. Results

4.1 Participant characteristics

Participant characteristics are shown in S1 Table. The mean age of the respondents was 20.08 (SD = 2.37) years, with a range of 18~30 years old. Of the 2744 participants, 69.2% were female, 56.3% lived in rural areas and 69.4% were single-child.

4.2 Sleep quality

Using a PSQI score > 7 to identify sleep disturbance, among the 2744 participants, 2197 (80.1%) reported normal sleep quality and 547 (19.9%) reported sleep disturbance. As shown in Table 1, SMF (OR = 1.387, 95% CI: 1.103~1.743), and SMA (OR = 1.415, 95% CI: 1.118~1.791) were positively associated with sleep quality. When time spent on social media exceeded that spent in the real world, the sleep quality decreased. Self-reported health status [good (OR = 0.617, 95% CI: 0.393~0.971)], and education level [undergraduate students and above (OR = 0.658, 95%CI: 0.533~0.812)] negatively affected sleep quality.

4.3 Sleep duration

A total of 15.6% of participants reported having a short sleep duration (< 7 hours), and 21.6% of participants had sleep durations longer than 9 hours per day. As shown in Table 2, compared to a sleep duration > 9 h duration, SMF increased the risk of short sleep durations [5–6 h sleep (OR = 2.226, 95% CI: 1.132~4.375), and 7–8 h sleep (OR = 1.296, 95% CI: 1.007~1.670)]. FoMO and SMA did not significantly affect sleep duration. As shown in Fig 1, the mean scores of SMF, SMA and FoMO were highest at 5–6 h of sleep.

4.4 SMF

The median SMF score was 50 (25, 75). As shown in Table 3, SMA (OR = 3.775, 95% CI: 3.141~4.537), FoMO (OR = 3.301, 95% CI: 2.753~3.958), sleep quality (OR = 1.284, 95% CI: 1.006~1.638), purpose [because a lot of my friends are on them (OR = 1.432, 95% CI: 1.106~1.854)], time spent on social media exceeding that spent in the real world [much (OR = 1.655, 95% CI: 1.198~2.286)] and education level [undergraduate students and above (OR = 1.310, 95% CI: 1.085~1.581)] increased SMF. However, sleep duration did not affect SMF scores.

5. Discussion

Prolonged social media use for nonacademic purposes, FoMO, SMA, SMF, poor sleep quality and decreased social interactions in the real world were reported by the participants in this study. Social media use for nonacademic purposes decreased sleep quality. Social media use for nonacademic purposes can distract university students from learning, adversely affect their academic performance and social interactions, and lead to delayed bedtime [44]. Additionally, spending more time on social media than in the real world resulted in sleep disturbance, which aligns with findings in a previous study [10]. Consistent with previous studies [45, 46], individuals with poor self-rated health and low education levels were more likely to experience poor sleep quality in this survey. This offers insights into potential targets for suggesting that minorities are particularly vulnerable to the effects of poor health and prolonged social media use on sleep quality.

In the context of social media, individuals may experience addiction and frustration induced by FoMO, which could contribute to sleep problems [16, 47]. However, FoMO did not affect sleep quality or duration in this study. It was reported that the sleep patterns of social media users may be disrupted when they are preoccupied and fear of missing out on any information on social media, which may not be well limited in time [48]. In addition, FoMO predicted shorter sleep durations as it drove late night social media use among the adolescents [49]. The inconsistent results may be explained by differences in the participants surveyed. Additionally, time spent on social media use at night, which is an important factor for sleep quality and duration, was not measured in this study. In this study, SMA positively influenced sleep quality, but was not associated with sleep duration. Furthermore, the relationship between SMA and sleep duration exhibited an inverted U curve among university students. Previous studies have confirmed that problematic social media use (operationalized as SMA) is associated with poor sleep quality [11, 33, 50], similar to our finding. The potential reasons that SMA may lead to sleep disturbance include portable smartphones and Wi-Fi access without spatial or temporal constraints that may be brought to bed. Using social media, especially before bed, may lead to difficulty falling asleep and delayed bedtime [51]. Delayed bedtime and late waking time may further lead to circadian rhythm desynchronization [31]. Additionally, light-emitting screens may suppress melatonin secretion [52]. However, a U-shaped curve between SMA and sleep duration was observed among Norwegian university students [36]. Among Korean school-age children, individuals who were at high risk for smartphone addiction were likely to have poor sleep quality and short sleep duration [53]. The different tools and cutoff values used to measure SMA and the different classifications of sleep duration may lead to inconsistent findings.

As university students heavily rely on various social media platforms to connect with others and use social media for nonacademic purposes, SMF was particularly evident. SMF is closely related to individuals’ physical and mental health and may trigger unhealthy behaviors [54]. In this study, a reciprocally relationship between sleep quality and SMF was observed in university students. Individuals experiencing SMF exhibited sleep disturbance and short sleep duration. Likewise, short sleep duration and poor sleep quality exacerbated individuals’ fatigue resulting from social media. Although few studies have focused on the relationship between SMF and sleep problems, there is a consensus that fatigue and sleep problems are associated [55, 56]. Evidence suggests that sleep disturbance may be an important contributor to fatigue in the context of students with depression and healthy employed people [57, 58]. In addition, cancer patients who reported being overly fatigued were 2.5 times more likely to have insomnia than others [59]. Moreover, FoMO was found to increase SMF, which is consistent with a previous study [15]. Furthermore, excessive social media use or SMA increases individual fatigue experience [60, 61]. Overall, individual-level factors (e. g. FoMO, decreased social interactions in the real world, addictive behaviors) play important roles in driving SMF. These findings also confirm the relationship between fatigue and sleep disturbance.

This study has some limitations. First, some of the study variables (e. g. SMA, FoMO, SMF, sleep duration and sleep quality) were reported using self-administered questionnaires. Therefore, our findings may be influenced by recall bias and social desirability. Second, we could not control for other factors, such as problematic social media use, nighttime social media use, weekend catch-up sleep, daytime naps, mobile phone use during social media outages, nomophobia and insomnia. Thus, future studies should include these variables. Third, a cross-sectional design was used; thus, the causality of relationships among the study variables could not be determined. Furthermore, the convenience sampling technique used may limit the generalizability of the findings.

6. Conclusion

Poor sleep is a common phenomenon among university students. Although social media use is related to sleep quality, the relationship between the adverse effects of excessive social media use, especially fatigue from excessive social media use, and sleep quality has received less attention. In the present study, the results suggest that university students commonly experience sleep disturbance and insufficient sleep. Individuals with SMF and SMA are likely to experience poor sleep quality. Compared to a sleep duration > 9 hours, a short sleep duration was positively associated with SMF. In addition, SMA, FoMO, and sleep quality affected SMF. Further research exploring the relationships among nighttime social media use, weekend catch-up sleep, daytime naps, insomnia and SMF, and interventions to improve these conditions should be conducted.

Supporting information

S1 File

(XLSX)

Click here for additional data file.^{(344.6KB, xlsx)}

S1 Table. General characteristics and Internet use of the participants (n = 2744).

(DOCX)

Click here for additional data file.^{(20.7KB, docx)}

Acknowledgments

We kindly thank Changjiang Polytechnic, Hubei University of Education, South-Central Minzu University, Wuhan Polytechnic, and 4 other universities and vocational colleges for their assistance in the enrollment and the assessment of participants.

Data Availability

All relevant data are within the paper and its supporting information file.

Funding Statement

This work was supported by the National Natural Science Foundation of China (No. 82003448), and Philosophy and Social Science Project of Hubei Provincial Department of Education (No. 21Q132). The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.

References

1.Chinese Internet Network Information Center. (2021). The 48rd China statistical report on Internet development. http: // www.cnnic.net.cn/hlwfzyj/hlwxzbg/hlwtjbg/202109/t20210915_71543.htm.
2.Chinese Internet Network Information Center. (2019). The 43rd China statistical report on Internet development. http: // www.cnnic.net.cn/hlwfzyj/hlwxzbg/hlwtjbg/201902/P020190318523029756345.pdf.
3.Chotpitayasunondh V, Douglas KM. How “phubbing” becomes the norm: The antecedents and consequences of snubbing via smartphone. Computers in Human Behavior. 2016;63:9–18. 10.1016/j.chb.2016.05.018 [DOI] [Google Scholar]
4.Bashir I, Malik A, Mahmood K. Social media use and information-sharing behaviour of university students. IFLA Journal. 2021;47(4):481–92. 10.1177/0340035221991564 [DOI] [Google Scholar]
5.Zhu X, Hu H, Xiong Z, Zheng T, Li L, Zhang L, et al. Utilization and professionalism toward social media among undergraduate nursing students. Nursing ethics. 2021;28(2):297–310. doi: 10.1177/0969733020952105 [DOI] [PubMed] [Google Scholar]
6.Boer M, Stevens GW, Finkenauer C, de Looze ME, van den Eijnden RJ. Social media use intensity, social media use problems, and mental health among adolescents: Investigating directionality and mediating processes. Computers in Human Behavior. 2021;116:106645. 10.1016/j.chb.2020.106645. [DOI] [Google Scholar]
7.Tandon A, Dhir A, Talwar S, Kaur P, Mäntymäki M. Dark consequences of social media-induced fear of missing out (FoMO): Social media stalking, comparisons, and fatigue. Technological Forecasting and Social Change. 2021;171:120931. 10.1016/j.techfore.2021.120931. [DOI] [Google Scholar]
8.Xiao L, Mou J. Social media fatigue-Technological antecedents and the moderating roles of personality traits: The case of WeChat. Computers in Human Behavior. 2019;101:297–310. 10.1016/j.chb.2019.08.001. [DOI] [Google Scholar]
9.Bouffard S, Giglio D, Zheng Z. Social media and romantic relationship: Excessive social media use leads to relationship conflicts, negative outcomes, and addiction via mediated pathways. Social Science Computer Review. 2022;40(6):1523–41. 10.1177/08944393211013566 [DOI] [Google Scholar]
10.Alonzo R, Hussain J, Stranges S, Anderson KK. Interplay between social media use, sleep quality, and mental health in youth: A systematic review. Sleep medicine reviews. 2021;56:101414. doi: 10.1016/j.smrv.2020.101414 [DOI] [PubMed] [Google Scholar]
11.Wong HY, Mo HY, Potenza MN, Chan MNM, Lau WM, Chui TK, et al. Relationships between severity of internet gaming disorder, severity of problematic social media use, sleep quality and psychological distress. International journal of environmental research and public health. 2020;17(6):1879. doi: 10.3390/ijerph17061879 [DOI] [PMC free article] [PubMed] [Google Scholar]
12.Malik A, Dhir A, Kaur P, Johri A. Correlates of social media fatigue and academic performance decrement: a large cross-sectional study. Information Technology & People. 2021; 34 (2): 557–580. 10.1108/ITP-06-2019-0289 [DOI] [Google Scholar]
13.James TL, Lowry PB, Wallace L, Warkentin M. The effect of belongingness on obsessive-compulsive disorder in the use of online social networks. Journal of Management Information Systems. 2017;34(2):560–96. 10.1080/07421222.2017.1334496. [DOI] [Google Scholar]
14.Buglass SL, Binder JF, Betts LR, Underwood JD. Motivators of online vulnerability: The impact of social network site use and FOMO. Computers in Human Behavior. 2017;66:248–55. 10.1016/j.chb.2016.09.055 [DOI] [Google Scholar]
15.Bright LF, Logan K. Is my fear of missing out (FOMO) causing fatigue? Advertising, social media fatigue, and the implications for consumers and brands. Internet Research. 2018, 28 (5): 1213–1227. 10.1108/IntR-03-2017-0112 [DOI] [Google Scholar]
16.Blackwell D, Leaman C, Tramposch R, Osborne C, Liss M. Extraversion, neuroticism, attachment style and fear of missing out as predictors of social media use and addiction. Personality and Individual Differences. 2017;116:69–72. 10.1016/j.paid.2017.04.039. [DOI] [Google Scholar]
17.Ravindran T, Yeow Kuan AC, Hoe Lian DG. Antecedents and effects of social network fatigue. Journal of the Association for Information Science and Technology. 2014;65(11):2306–20. 10.1002/asi.23122 [DOI] [Google Scholar]
18.Cao X, Khan AN, Zaigham GH, Khan NA. The stimulators of social media fatigue among students: Role of moral disengagement. Journal of Educational Computing Research. 2019;57(5):1083–107. 10.1177/0735633118781907 [DOI] [Google Scholar]
19.Dhir A, Kaur P, Chen S, Pallesen S. Antecedents and consequences of social media fatigue. International Journal of Information Management. 2019;48:193–202. 10.1016/j.ijinfomgt.2019.05.021 [DOI] [Google Scholar]
20.Ou M, Zheng H, Kim HK, Chen X. A meta-analysis of social media fatigue: Drivers and a major consequence. Computers in Human Behavior. 2023;140:107597. 10.1016/j.chb.2022.107597 [DOI] [Google Scholar]
21.Hawi NS, Samaha M. The relations among social media addiction, self-esteem, and life satisfaction in university students. Social Science Computer Review. 2017;35(5):576–86. 10.1177/0894439316660340 [DOI] [Google Scholar]
22.Cheng C, Lau Y-c, Chan L, Luk JW. Prevalence of social media addiction across 32 nations: Meta-analysis with subgroup analysis of classification schemes and cultural values. Addictive behaviors. 2021;117:106845. doi: 10.1016/j.addbeh.2021.106845 [DOI] [PubMed] [Google Scholar]
23.Chang L, Ma J. Development and validation of the Chinese social media addiction scale. Personality & Individual Differences. 2018;134:55–9. 10.1016/j.paid.2018.05.046 [DOI] [Google Scholar]
24.Haand R, Shuwang Z. The relationship between social media addiction and depression: A quantitative study among university students in Khost, Afghanistan. International Journal of Adolescence and Youth. 2020;25(1):780–6. 10.1080/02673843.2020.1741407 [DOI] [Google Scholar]
25.Azizi SM, Soroush A, Khatony A. The relationship between social networking addiction and academic performance in Iranian students of medical sciences: a cross-sectional study. BMC psychology. 2019;7(1):1–8. 10.1186/s40359-019-0305-0 [DOI] [PMC free article] [PubMed] [Google Scholar]
26.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):174–81. doi: 10.1016/j.sleh.2018.01.001 [DOI] [PMC free article] [PubMed] [Google Scholar]
27.Kloss JD, Nash CO, Horsey SE, Taylor DJ. The delivery of behavioral sleep medicine to college students. Journal of Adolescent Health. 2011;48(6):553–61. doi: 10.1016/j.jadohealth.2010.09.023 [DOI] [PubMed] [Google Scholar]
28.Jiang X-L, Zheng X-Y, Yang J, Ye C-p, Chen Y-Y, Zhang Z-G, et al. A systematic review of studies on the prevalence of insomnia in university students. Public health. 2015;129(12):1579–84. doi: 10.1016/j.puhe.2015.07.030 [DOI] [PubMed] [Google Scholar]
29.Li L, Wang YY, Wang SB, Zhang L, Li L, Xu DD, et al. Prevalence of sleep disturbances in Chinese university students: a comprehensive meta‐analysis. Journal of sleep research. 2018;27(3):e12648. doi: 10.1111/jsr.12648 [DOI] [PubMed] [Google Scholar]
30.Cain N, Gradisar M. Electronic media use and sleep in school-aged children and adolescents: A review. Sleep Med. 2010;11(8):735–42. doi: 10.1016/j.sleep.2010.02.006 [DOI] [PubMed] [Google Scholar]
31.Touitou Y, Touitou D, Reinberg A. Disruption of adolescents’ circadian clock: the vicious circle of media use, exposure to light at night, sleep loss and risk behaviors. Journal of Physiology-Paris. 2016;110(4):467–79. doi: 10.1016/j.jphysparis.2017.05.001 [DOI] [PubMed] [Google Scholar]
32.LeBourgeois MK, Hale L, Chang A-M, Akacem LD, Montgomery-Downs HE, Buxton OM. Digital media and sleep in childhood and adolescence. Pediatrics. 2017;140(Supplement 2):S92–S6. doi: 10.1542/peds.2016-1758J [DOI] [PMC free article] [PubMed] [Google Scholar]
33.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. 2020:877. doi: 10.3389/fpsyt.2020.00877 [DOI] [PMC free article] [PubMed] [Google Scholar]
34.Adams SK, Murdock KK, Daly-Cano M, Rose M. Sleep in the social world of college students: Bridging interpersonal stress and fear of missing out with mental health. Behavioral sciences. 2020;10(2):54. doi: 10.3390/bs10020054 [DOI] [PMC free article] [PubMed] [Google Scholar]
35.Alimoradi Z, Lin C-Y, Broström A, Bülow PH, Bajalan Z, Griffiths MD, et al. Internet addiction and sleep problems: A systematic review and meta-analysis. Sleep medicine reviews. 2019;47:51–61. doi: 10.1016/j.smrv.2019.06.004 [DOI] [PubMed] [Google Scholar]
36.Hjetland GJ, Skogen JC, Hysing M, Sivertsen B. The association between self-reported screen time, social media addiction, and sleep among Norwegian University students. Frontiers in public health. 2021;9:794307. doi: 10.3389/fpubh.2021.794307 [DOI] [PMC free article] [PubMed] [Google Scholar]
37.Luo L, Zhang Y, Huang T, Zhou F, Xiong C, Liu Y, et al. A description of the current status of chronic fatigue syndrome and associated factors among university students in Wuhan, China. Front Psychiatry. 2022;13:1047014. doi: 10.3389/fpsyt.2022.1047014 [DOI] [PMC free article] [PubMed] [Google Scholar]
38.Zheng H, Ling R. Drivers of social media fatigue: A systematic review. Telematics and Informatics. 2021;64:101696. 10.1016/j.tele.2021.101696. [DOI] [PMC free article] [PubMed] [Google Scholar]
39.Liu XC, Tang MQ. Reliability and validity of the Pittsburgh Sleep Quality Index. Chinese Journal of Psychiatry. 1996;29(2):29103–7. 10.1007/BF02951625. [DOI] [Google Scholar]
40.Lee AR, Son SM, Kim KK. Information and communication technology overload and social networking service fatigue: A stress perspective. Computers in Human Behavior. 2016;55(FEB.):51–61. 10.1016/j.chb.2015.08.011 [DOI] [Google Scholar]
41.Zhang Q. F. Scale development for social media fatigue [D]. Xiamen, Xiamen University. [Google Scholar]
42.Beaton DE, Bombardier C, Guillemin F, Ferraz MB. Guidelines for the process of cross-cultural adaptation of self-report measures. Spine. 2000;25(24):3186–91. doi: 10.1097/00007632-200012150-00014 [DOI] [PubMed] [Google Scholar]
43.Li L, Griffiths MD, Niu Z, Mei S. The trait-state fear of missing out scale: Validity, reliability, and measurement invariance in a Chinese sample of university students. J Affect Disord. 2020;274:711–8. doi: 10.1016/j.jad.2020.05.103 [DOI] [PubMed] [Google Scholar]
44.Kolhar M, Kazi RNA, Alameen A. Effect of social media use on learning, social interactions, and sleep duration among university students. Saudi journal of biological sciences. 2021;28(4):2216–22. doi: 10.1016/j.sjbs.2021.01.010 [DOI] [PMC free article] [PubMed] [Google Scholar]
45.Hale L, Hill TD, Friedman E, Nieto FJ, Galvao LW, Engelman CD, et al. Perceived neighborhood quality, sleep quality, and health status: evidence from the Survey of the Health of Wisconsin. Social science & medicine. 2013;79:16–22. doi: 10.1016/j.socscimed.2012.07.021 [DOI] [PMC free article] [PubMed] [Google Scholar]
46.Patel NP, Grandner MA, Xie D, Branas CC, Gooneratne N. " Sleep disparity" in the population: poor sleep quality is strongly associated with poverty and ethnicity. BMC Public Health. 2010;10:1–11. 10.1186/1471-2458-10-475 [DOI] [PMC free article] [PubMed] [Google Scholar]
47.Gezgin DM, Hamutoglu NB, Gemikonakli O, Raman I. Social networks users: fear of missing out in preservice teachers. Journal of Education and Practice. 2017;8(17):156–68. https://eprints.mdx.ac.uk/id/eprint/22198 [Google Scholar]
48.Van den Bulck J. Television viewing, computer game playing, and Internet use and self-reported time to bed and time out of bed in secondary-school children. Sleep. 2004;27(1):101–4. doi: 10.1093/sleep/27.1.101 [DOI] [PubMed] [Google Scholar]
49.Scott H, Woods HC. Fear of missing out and sleep: Cognitive behavioural factors in adolescents’ nighttime social media use. Journal of adolescence. 2018;68:61–5. doi: 10.1016/j.adolescence.2018.07.009 [DOI] [PubMed] [Google Scholar]
50.Moreno M, Riddle K, Jenkins MC, Singh A, Zhao Q, Eickhoff J. Measuring Problematic Internet Use, Internet Gaming Disorder and Social Media Addiction in young adults: A cross-sectional study. JMIR public health and surveillance. 2022, 8(1), e27719. 10.2196/27719 [DOI] [PMC free article] [PubMed] [Google Scholar]
51.Fossum IN, Nordnes LT, Storemark SS, Bjorvatn B, Pallesen S. The association between use of electronic media in bed before going to sleep and insomnia symptoms, daytime sleepiness, morningness, and chronotype. Behavioral sleep medicine. 2014;12(5):343–57. doi: 10.1080/15402002.2013.819468 [DOI] [PubMed] [Google Scholar]
52.Wahl S, Engelhardt M, Schaupp P, Lappe C, Ivanov IV. The inner clock—Blue light sets the human rhythm. Journal of biophotonics. 2019;12(12):e201900102. doi: 10.1002/jbio.201900102 [DOI] [PMC free article] [PubMed] [Google Scholar]
53.Park M, Jeong SH, Huh K, Park YS, Park E-C, Jang S-Y. Association between smartphone addiction risk, sleep quality, and sleep duration among Korean school-age children: a population-based panel study. Sleep and Biological Rhythms. 2022;20(3):371–80. 10.1007/s41105-022-00377-6 [DOI] [PMC free article] [PubMed] [Google Scholar]
54.Choi SB, Lim MS. Effects of social and technology overload on psychological well-being in young South Korean adults: The mediatory role of social network service addiction. Computers in Human Behavior. 2016;61(AUG.):245–54. 10.1016/j.chb.2016.03.032. [DOI] [Google Scholar]
55.Sajadi A, Farsi Z, Rajai N. The relationship between sleep quality with fatigue severity and academic performance of nursing students. Nursing Practice Today. 2014;1(4):213–20. [Google Scholar]
56.Kübra U, GÜNDOĞAN, GÜRBÜZ ÖB, ÖZÇAKAR N. Status of fatigue and sleep quality in clinical medical students. Marmara Medical Journal. 2016;29(3):164–9. 10.5472/MMJoa.2903.05 [DOI] [Google Scholar]
57.Valpiani EM, Brown RF, Thorsteinsson EB, Hine D. Poor sleep quality mediates between depression to fatigue in a university student sample. Psychology and Education: An Interdisciplinary Journal. 2011. [Google Scholar]
58.Åkerstedt T, Knutsson A, Westerholm P, Theorell T, Alfredsson L, Kecklund G. Mental fatigue, work and sleep. Journal of psychosomatic Research. 2004;57(5):427–33. doi: 10.1016/j.jpsychores.2003.12.001 [DOI] [PubMed] [Google Scholar]
59.Davidson JR, MacLean AW, Brundage MD, Schulze K. Sleep disturbance in cancer patients. Social science & medicine. 2002;54(9):1309–21. doi: 10.1016/s0277-9536(01)00043-0 [DOI] [PubMed] [Google Scholar]
60.Dhir A, Yossatorn Y, Kaur P, Chen S. Online social media fatigue and psychological wellbeing—A study of compulsive use, fear of missing out, fatigue, anxiety and depression. International Journal of Information Management. 2018;40(JUN.):141–52. 10.1016/j.ijinfomgt.2018.01.012 [DOI] [Google Scholar]
61.Lian SL, Sun XJ, Zhou ZK, Fan CY, Niu GF, Liu QQ. Social networking site addiction and undergraduate students’ irrational procrastination: The mediating role of social networking site fatigue and the moderating role of effortful control. PloS one. 2018;13(12):e0208162. doi: 10.1371/journal.pone.0208162 [DOI] [PMC free article] [PubMed] [Google Scholar]

PLoS One. doi: 10.1371/journal.pone.0292429.r001

Decision Letter 0

Ugurcan Sayili

6 Mar 2023

PONE-D-22-10183Exploring associations between social media addiction, social media fatigue, fear of missing out and sleep quality among university students: a cross-section studyPLOS ONE

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Reviewers' comments:

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Reviewer #1: Yes

Reviewer #2: Yes

Reviewer #3: Yes

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Reviewer #1: Yes

Reviewer #2: Yes

Reviewer #3: Yes

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Reviewer #1: Yes

Reviewer #2: Yes

Reviewer #3: Yes

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Reviewer #2: Yes

Reviewer #3: Yes

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5. Review Comments to the Author

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Reviewer #1: Comments on Exploring associations between social media addiction, social media fatigue, fear of missing out and sleep quality among university students: a cross-section study.

1.Paper summary

This paper mainly studied the associations between the phenomena of problems on social media and sleep quality based on Chinese university students.

2.comments

There are some problems which should be well solved before it is considered for publication.

First, relevant research background needs to be supplemented in Introduction. In this part, it is noted that the negative consequences of social media use, harmful effects of social media use, SMF, SMA and damaging relationship between social media use and sleep problems in paragraph 1 through 3 respectively. However, the summary or prospect of “little attention is on the combined impacts of adverse effects of excessive social media use” in line 80, consistency of the combined impacts didn’t be displayed in the following hypothesis and design.

Then, lots of silly mistakes are designed to get more attention.

① In Abstract. For poor sleep quality, OR of SMA, 1.409, conflicts with Table 1.

② In line 111, it is stated that model 3 had three groups, but only a high and a low group are described.

③ In line 118, participants were split into two subgroups using SMA, which included the number 2752, in contrast to the number of participants with the criteria of exclusion.

④ The description of the percentage of women and rural residents in line 164 conflicts with Table S1.

⑤ The statement in section 3.2 that "self-reported health status [not bad] (OR = 1.814)" conflicts with Table 1.

Reviewer #2: This research paper is well-structured and presents a thorough review of the literature. The analysis is clear and logical, and the conclusions are well-supported. The paper is well-written and easy to understand.

The findings of this study suggest that SMF, FoMO, and SMA are all significantly associated with sleep quality among university students. Specifically, higher levels of SMF, FoMO, and SMA were associated with decreased sleep quality. These results suggest that university students with higher levels of social media fatigue, fear of missing out, and social media addiction may be more likely to experience poorer sleep outcomes. These findings could have important implications for interventions that seek to improve the sleep outcomes of university students. It may be beneficial for such interventions to target these specific factors, such as SMF, FoMO, and SMA, to help improve sleep quality. Additionally, healthcare providers should be aware of the potential impact of these factors on university student sleep quality and consider addressing them in clinical care.

The research is relevant but the main problem is not up-to-date, and the sources need update and discussion. Mobile phone use during social media outage, nomophobia, and insomnia literature not been discussed which are all FOMO.

Reviewer #3: 1.It is appropriate for researchers to specify p values in a single format (with a lowercase p) throughout the article.

2.In the methodology section, the sleep duration categories should be corrected as “<7 h”, “7-8 h”, and “>8 h”.

3.Logistic regression is used to identify predictors of dependent variables, if more than one independent predictor variable is evaluated, the p value in univariate analysis p<0.25* is tested using multivariate logistic regression analysis of clinically significant variables. A statement should be made that the variables observed in the text and in the table were tested using multivariate logistic regression analysis (* David Hosmer, Stanley Lemeshow, Rodney Sturdivant - Applied Logistic Regression-Wiley (2013), page 91).

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Reviewer #1: No

Reviewer #2: No

Reviewer #3: No

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PLoS One. 2023 Oct 5;18(10):e0292429. doi: 10.1371/journal.pone.0292429.r002

Author response to Decision Letter 0

6 Apr 2023

Dear. Ugurcan Sayili, M.D:

On behalf of my co-authors, I thank you very much for giving us an opportunity to revise our manuscript, we also deeply appreciate the editor and reviewers for their positive and constructive comments and suggestions on our manuscript entitled “Exploring associations between social media addiction, social media fatigue, fear of missing out and sleep quality among university students: a cross-section study” (ID: PONE-D-22-10183). Those comments are all valuable and very helpful for revising and improving our paper, as well as providing important guidance for our research.

We have studied editor and reviewers’ comments carefully and have made corresponding revisions that we hope to meet with qualifications for publication. We have tried our best to revise our manuscript according to the comments. Attached please find the revised version, which we would like to submit for your kind consideration. The major changes and revisions have been highlighted in red, which can be turned into black by rejecting all the changes. We hope that these revisions are satisfactory for your serious consideration to publish this manuscript in Plos one. We would like to express our appreciation again to you and reviewers for the comments on our paper.

Looking forward to hearing back from you.

Correspondence and phone calls about the paper should be directed to Xinhong Zhu at the following address, phone, and e-mail address:

Dr. Xinhong Zhu

School of Nursing, Hubei University of Chinese Medicine, 430061 16# Huangjiahu West Road, Wuhan, China, E-mail: zxh88@hbtcm.edu.cn

Thanks for your attention to our paper.

We are very grateful to the reviewers and editor for their comments and suggestions for revisions. The manuscript has been substantially improved according to the suggestions of reviewers and editor. The main corrections in the paper and the responses to the reviewer’s comments are addressed below.

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Response: We really thank you for your careful review on our manuscript. We have downloaded MANUSCRIPT BODY FORMATTING GUIDELINES and TITLE, AUTHOR, AFFILIATIONS FORMATTING GUIDELINES and revised manuscript to meet PLOS ONE's style requirements.

Upon resubmission, please provide the following:

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A clean copy of the edited manuscript (uploaded as the new *manuscript* file).

Response: Thank you very much for your serious review and kind reminding. We invited Pro. Fen Yan to provide language editing.

Fen Yang: Nurse educator, Health Care Management, School of Nursing, Hubei University of Chinese Medicine,

So far, she has published 28 articles. Recent articles as corresponding author are as follows

1. Li, C., Wu, M., Qiao, G., Gao, X., Hu, T., Zhao, X., Zhu, X., & Yang, F. (2023). Effectiveness of Continuity of Care in Reducing Depression Symptoms in Elderly: A Systematic Review and Meta‐analysis. International Journal of Geriatric Psychiatry, e5894.

2. Hu, T., Zhao, X., Wu, M., Li, Z., Luo, L., Yang, C., & Yang, F. (2022). Prevalence of depression in older adults: A systematic review and meta-analysis. Psychiatry research, 114511.

3. Zhao, X., Hu, T., Qiao, G., Li, C., Wu, M., Yang, F., & Zhou, J. (2022). Psychometric properties of the smartphone distraction scale in Chinese college students: validity, reliability and influencing factors. Frontiers in psychiatry, 13.

4. Li, C., Yang, F., Yang, B.X. et al. Experiences and challenges faced by community mental health workers when providing care to people with mental illness: a qualitative study. BMC Psychiatry 22, 623 (2022).

Response: Thank you very much for your serious review and kind reminding. We have modified grant numbers of funds, which was consist with “Financial Disclosure” in the manuscript.

We will update your Data Availability statement to reflect the information you provide in your cover letter.

Response: We sincerely thank for your suggestion. We modified the part of “Data Availability Statement”.

All relevant data are within the manuscript and its Supporting information file.

In your revised cover letter, please address the following prompts:

We will update your Data Availability statement on your behalf to reflect the information you provide.

Response: We sincerely thank for your suggestion. All relevant data are within the manuscript and its Supporting information file.

Response: Great thanks to you for your careful review and valuable suggestion. ORCID iD of corresponding author is shown as followed.

Xinhong Zhu: https://orcid.org/0000-0001-7356-7401

Reviewers' comments:

Reviewer #1:

Comments on Exploring associations between social media addiction, social media fatigue, fear of missing out and sleep quality among university students: a cross-section study.

1. Paper summary

This paper mainly studied the associations between the phenomena of problems on social media and sleep quality based on Chinese university students.

2. comments

Comment 1: There are some problems which should be well solved before it is considered for publication.

Response: We sincerely thank Reviewer 1 for your kind and professional comments of our paper, which not only encourage us to improve our present manuscript, but also provide some useful ideas for our future studies. Accordingly, we have studied comments carefully. Point-by-point replies to Reviewer #1 are listed below. We modified the paragraph 3, and rewrote the relationship of social media use (e.g. FoMO, SMA, and SMF) and sleep quality, and added 9 new references into the text. Meanwhile, the hypothesis of this study was revised.

Paragraph 3-4:

Recently, studies concerning social media use have stressed growing problems among social media in terms of sleep disorders. The relationships of delayed sleep onset, bad quality of sleep and increased time spent on internet were reported in previous studies [27, 28]. Frequent social media use could predict both poor mental health and sleep outcomes in youth [10]. Evidence showed that the impact of negative affect on sleep quality was mediated by FoMO and smartphone addiction in the sample of Chinese university students [29]. Additionally, higher level of FoMO was associated with higher level of insomnia, which in turn was associated with poorer mental health in the college students [30]. When individuals were addicted to the Internet, the overall pooled odds ratio of experiencing sleep disturbance was 2.20 (95% CI: 1.77–2.74), and a significant reduce in sleep duration was observed [31]. Furthermore, there was higher rates of insomnia among those with higher levels of SMA among Norwegian university students [32]. Although the relationship between chronic fatigue and sleep quality was confirmed among university students [33], few surveys on association of SMF and sleep quality were conducted among Chines university students. Given FoMO and SMA acting as SMF drivers [34], we hypothesized that SMF was related to sleep quality.

University students frequently suffer from poor sleep [35, 36]. The prevalence of insomnia in university students worldwide has been found to be 18.5%, much higher than the 7.4% rate in the general population [37]. The overall pooled prevalence of sleep disturbances and those suffering from insomnia symptoms in Chinese university students are 25.7% (95% CI: 22.5 ~28.9%) and 23.6% (95% CI: 18.9~29.0%), respectively [38]. Considering that social media use has been linked to poor sleep outcomes, we hypothesized that there were relationships of sleep quality with FoMO, SMF, and SMA. Thus, this study was conducted among Chinese university students, and correlated variables were investigated in detail, such as social media use, FoMO, SMA, SMF, sleep disturbances and sleep duration.

① In Abstract. For poor sleep quality, OR of SMA, 1.409, conflicts with Table 1.

② In line 111, it is stated that model 3 had three groups, but only a high and a low group are described.

③ In line 118, participants were split into two subgroups using SMA, which included the number 2752, in contrast to the number of participants with the criteria of exclusion.

④ The description of the percentage of women and rural residents in line 164 conflicts with Table S1.

⑤ The statement in section 3.2 that "self-reported health status [not bad] (OR = 1.814)" conflicts with Table 1.

Response: We sincerely thank you for your kind and professional comments on our manuscript. We apologize for our carelessness. In this study, because grouping of respondents based upon the midpoints of the score ranges produces very unequal numbers in the two categories, we have modified the cut-off of SMA, SMF and FoMO, and used the median values as the cut-off. The median scores of SMA, SMF and FoMO were 84, 50 and 32, respectively.

Meanwhile, we have modified our mistakes as followed:

① In the abstract, for poor sleep quality, the OR of SMA is 1.415, which is consistent with Table 1.

② The participants were divided into two groups using the median SMF score for statistical analysis: a high score group (≥50, n = 1374), and a low score group (<50, n = 1370).

③ The participants were divided into two groups using the median SMA score for statistical analysis: a high score group (≥84, n = 1376), and a low score group (<84, n = 1368).

④ Of the 2744 participants, 69.2% were female, 56.3% lived in rural and 69.4% were single-child, which are consistent with data shown in Table S1.

⑤ Self-reported health status [fair (OR = 1.795, 95% CI: 1.193~2.701), bad (OR = 3.474, 95%CI: 1.462~8.256)] affected sleep quality.

Thank you again for your comments on our manuscripts.

Comment 1: The research is relevant but the main problem is not up-to-date, and the sources need update and discussion. Mobile phone use during social media outage, nomophobia, and insomnia literature not been discussed which are all FOMO.

Response: We appreciate Reviewer #2 for warm work and positive suggestions earnestly, which are very helpful for improving our paper and future research. In the paragraph 3, we modified the hypothesis and added evidence for supporting the relationship of FoMO and sleep problems as followed.

Recently, studies concerning social media use have stressed growing problems among social media in terms of sleep disorders. The relationships of delayed sleep onset, bad quality of sleep and increased time spent on internet were reported in previous studies [26, 27]. Frequent social media use could predict both poor mental health and sleep outcomes in youth [10]. Evidence showed that the impact of negative affect on sleep quality was mediated by FoMO and smartphone addiction in the sample of Chinese university students [28]. Additionally, higher level of FoMO was associated with higher level of insomnia, which in turn was associated with poorer mental health in the college students [29]. When individuals were addicted to the Internet, the overall pooled odds ratio of experiencing sleep disturbance was 2.20 (95% CI: 1.77–2.74), and a significant reduce in sleep duration was observed [30]. Furthermore, there was higher rates of insomnia in those with higher levels of SMA among Norwegian university students [31]. Although the relationship between chronic fatigue and sleep quality was confirmed among university students [32], few surveys on association of SMF and sleep quality were conducted among Chinese university students. Given FoMO and SMA acting as SMF drivers [33], we hypothesized that SMF was related to sleep quality.

Meanwhile, we modified the part of limitation as followed:

Second, the study could not control for other factors, such as problematic social media use, nighttime social media use, weekend catch-up sleep, daytime nap, mobile phone use during social media outage, nomophobia and insomnia. Thus, future studies should include these variables.

Reviewer #3:

Comment 1: 1. It is appropriate for researchers to specify p values in a single format (with a lowercase p) throughout the article.

Response: Thank you very much for your serious review and kind reminding. We revised p values in a single format (with a lowercase p) in the part of methods and results.

Comment 2: 2. In the methodology section, the sleep duration categories should be corrected as “<7 h”, “7-8 h”, and “>8 h”.

Response: Great thanks to you for your careful review and valuable suggestion. In fact, if sleep duration categories were be corrected as “<7 h”, “7-8 h”, and “>8 h” in this study, the associations of sleep duration, SMA, SMF and FoMO were not observed.

Therefore, in order to explore relationship of sleep duration, SMA, SMF and FoMO, sleep duration was divided into six categories: “< 5 h”, “5-6 h”, “6-7 h”, “7-8 h”, “8-9 h”, and “>9 h” in this study. As shown in Table 2, compared to > 9 h duration, SMF was associated with an increased risk of 5-6 h sleep (OR = 2.226, 95%CI: 1.132~4.375), while the risk of 7-8 h sleep was OR = 1.296 (95%CI: 1.007~1.670). FoMO and SMA did not significantly affect sleep duration. As shown in Fig 1, the mean scores of SMF, SMA and FoMO were highest at 5-6 h sleep.

Comment 3: 3. Logistic regression is used to identify predictors of dependent variables, if more than one independent predictor variable is evaluated, the p value in univariate analysis p<0.25* is tested using multivariate logistic regression analysis of clinically significant variables. A statement should be made that the variables observed in the text and in the table were tested using multivariate logistic regression analysis (* David Hosmer, Stanley Lemeshow, Rodney Sturdivant - Applied Logistic Regression-Wiley (2013), page 91).

Response: We deeply appreciate for your careful review on our manuscript. We modified the part of data analysis as followed:

Then, variables were entered with p < 0.25 into a multivariate logistic regression analysis to identify predictors of sleep duration in univariate analysis. Multivariate logistic regression analyses were conducted with short sleep duration as the outcome variable (> 9 h as the reference category), and social media use, SMF, SMA, FoMO, and demographic information as the exposure variables (Table 2).

Attachment

Submitted filename: Response to editor and reviewers.docx

Click here for additional data file.^{(49.4KB, docx)}

PLoS One. doi: 10.1371/journal.pone.0292429.r003

Decision Letter 1

Ahsan Ali

3 May 2023

PONE-D-22-10183R1Exploring associations between social media addiction, social media fatigue, fear of missing out and sleep quality among university students: a cross-section studyPLOS ONE

Dear Dr. Zhu,

Please submit your revised manuscript by Jun 17 2023 11:59PM. If you will need more time than this to complete your revisions, please reply to this message or contact the journal office at plosone@plos.org. When you're ready to submit your revision, log on to https://www.editorialmanager.com/pone/ and select the 'Submissions Needing Revision' folder to locate your manuscript file.

Please include the following items when submitting your revised manuscript:

A rebuttal letter that responds to each point raised by the academic editor and reviewer(s). You should upload this letter as a separate file labeled 'Response to Reviewers'.
A marked-up copy of your manuscript that highlights changes made to the original version. You should upload this as a separate file labeled 'Revised Manuscript with Track Changes'.
An unmarked version of your revised paper without tracked changes. You should upload this as a separate file labeled 'Manuscript'.

We look forward to receiving your revised manuscript.

Kind regards,

Ahsan Ali

Academic Editor

PLOS ONE

Additional Editor Comments:

I am grateful to the authors for their efforts in addressing the comments of the reviewers. However, I would like to suggest a few points before the paper moves on to the next step:

1. I recommend that the authors revise the abstract. In the "Background" section, the authors mention that "Social media use has been linked to poor sleep outcomes in the cyber age among university students, but the mechanisms underlying this association are not yet well understood." It would be appropriate to specify which mechanisms the authors studied in this article rather than making a general statement about the relationships. Additionally, a clear description of the results is needed in the abstract. Please avoid ambiguous statements such as "Poor sleep quality was significantly with SMF." Please write clearly.

2. Please clarify how this study contributes to the existing literature and what it offers for practice in the last paragraph of the introduction section. Please align this with the discussion section as well.

3. Furthermore, I suggest that the authors include another heading after the introduction to provide an explanation of the relationship they have studied in this research and why these relationships are proposed. Also explain the theoretical foundation and practical evidence of the proposed relationships.

4. Lastly, I appreciate the language improvement, but there are still a number of grammatical issues along with unclear expressions. Therefore, I recommend that the authors use the services of a professional copy-editor to help with this issue.

[Note: HTML markup is below. Please do not edit.]

Reviewers' comments:

Reviewer's Responses to Questions

Comments to the Author

1. If the authors have adequately addressed your comments raised in a previous round of review and you feel that this manuscript is now acceptable for publication, you may indicate that here to bypass the “Comments to the Author” section, enter your conflict of interest statement in the “Confidential to Editor” section, and submit your "Accept" recommendation.

Reviewer #2: All comments have been addressed

Reviewer #3: All comments have been addressed

**********

2. Is the manuscript technically sound, and do the data support the conclusions?

Reviewer #2: Yes

Reviewer #3: Yes

**********

3. Has the statistical analysis been performed appropriately and rigorously?

Reviewer #2: Yes

Reviewer #3: Yes

**********

4. Have the authors made all data underlying the findings in their manuscript fully available?

Reviewer #2: (No Response)

Reviewer #3: Yes

**********

5. Is the manuscript presented in an intelligible fashion and written in standard English?

Reviewer #2: Yes

Reviewer #3: Yes

**********

6. Review Comments to the Author

Reviewer #2: I am pleased to confirm that all comments have been thoroughly addressed and I am fully satisfied with the feedback provided to the authors.

Reviewer #3: The researchers made the desired adjustments. Acceptance of the article is appropriate and congratulations to the authors.

**********

7. PLOS authors have the option to publish the peer review history of their article (what does this mean?). If published, this will include your full peer review and any attached files.

If you choose “no”, your identity will remain anonymous but your review may still be made public.

Do you want your identity to be public for this peer review? For information about this choice, including consent withdrawal, please see our Privacy Policy.

Reviewer #2: No

Reviewer #3: Yes: Aydin, Sumeyye Nur

**********

PLoS One. 2023 Oct 5;18(10):e0292429. doi: 10.1371/journal.pone.0292429.r004

Author response to Decision Letter 1

10 May 2023

Dear. Ahsan Ali

On behalf of my co-authors, I thank you very much for giving us an opportunity to revise our manuscript, we also deeply appreciate the editor for your positive and constructive comments and suggestions on our manuscript entitled “Exploring associations between social media addiction, social media fatigue, fear of missing out and sleep quality among university students: a cross-section study” (ID: PONE-D-22-10183. R2). Those comments are all valuable and very helpful for revising and improving our paper, as well as providing important guidance for our research.

We have studied editor’s comments carefully and have made corresponding revisions that we hope to meet with qualifications for publication. We have tried our best to revise our manuscript according to the comments. Attached please find the revised version, which we would like to submit for your kind consideration. The major changes and revisions have been highlighted in red, which can be turned into black by rejecting all the changes. We hope that these revisions are satisfactory for your serious consideration to publish this manuscript in Plos One. We would like to express our appreciation again to you and reviewers for the comments on our paper.

Looking forward to hearing back from you.

Correspondence and phone calls about the paper should be directed to Xinhong Zhu at the following address, phone, and e-mail address:

Dr. Xinhong Zhu

School of Nursing, Hubei University of Chinese Medicine, 430061 16# Huangjiahu West Road, Wuhan, China, E-mail: zxh88@hbtcm.edu.cn

Thanks for your attention to our paper.

We are very grateful to the editor for your comments and suggestions for revisions. The manuscript has been substantially improved according to the suggestions of editor. The main corrections in the paper and the responses to editor’s comments are addressed below.

I am grateful to the authors for their efforts in addressing the comments of the reviewers. However, I would like to suggest a few points before the paper moves on to the next step:

Comment 1. I recommend that the authors revise the abstract. In the "Background" section, the authors mention that "Social media use has been linked to poor sleep outcomes in the cyber age among university students, but the mechanisms underlying this association are not yet well understood." It would be appropriate to specify which mechanisms the authors studied in this article rather than making a general statement about the relationships. Additionally, a clear description of the results is needed in the abstract. Please avoid ambiguous statements such as "Poor sleep quality was significantly with SMF." Please write clearly.

Response: We sincerely thank your kind and professional comments of our paper, which not only encourage us to improve our present manuscript, but also provide some useful ideas for our future studies. Accordingly, we have studied comments carefully. Point-by-point replies to editor are listed below. We had modified the part of abstract.

Background: Social media use has been linked to poor sleep outcomes in the cyber age among university students, but the association between negative consequences of social media use and sleep problems are not yet well understood. The present study investigated the relationships of social media usage, social media fatigue (SMF), fear of missing out (FoMO), social media addiction (SMA) and sleep quality among university students.

Method: Online survey was conducted with 2744 respondents, who completed questionnaires including the Pittsburgh Sleep Quality Index (PSQI), FoMO, SMF, SMA and questions regarding sleep duration, social media use, health status, and demographic information.

Result: 19.9% of respondents suffered from sleep disturbance. 15.6% of participants slept less than 5 h, and 21.6% of subjects slept more than 9 h. Sleep quality was positively associated with SMF (OR = 1.387, 95% CI: 1.103~1.743), and SMA (OR = 1.415, 95% CI: 1.118~1.791). The relationship between FoMO and sleep disturbance was not significant. Compared to > 9 h duration, SMF increased risk of 5-6 h sleep (OR = 2.226, 95%CI: 1.132~4.375), 6-7 h sleep (OR = 1.458, 95%CI: 1.061~2.002), and 7-8 h sleep (OR =1.296, 95%CI: 1.007~1.670). FoMO and SMA did not significantly affect sleep duration. In addition, SMA (OR = 3.775, 95%CI: 3.141~4.537), FoMO (OR = 3.301, 95%CI: 2.753~3.958), and sleep disorder (OR = 1.284, 95%CI: 1.006~1.638) positively affected SMF level.

Conclusion: On experiencing negative consequences of social media use, such as SMF and SMA, university students are likely to have sleep problems. Further research exploring the interventions for improving poor sleep and negative outcomes of social media use should be conducted.

Comment 2. Please clarify how this study contributes to the existing literature and what it offers for practice in the last paragraph of the introduction section. Please align this with the discussion section as well.

Response: Thank you very much for your serious review and kind reminding. We had modified the last paragraph of the introduction section.

Although social media use has been linked to poor sleep outcomes, little research has focused on the relationship of FoMO, SMA, SMF and sleep quality. It is important to clarify the relationships of these four factors in order to detect the role of negative outcomes of social media use on sleep quality, and develop interventions to improve university students’ sleep quality for further study. Thus, this study was aimed to investigated the relationship between social media use, FoMO, SMA, SMF, sleep disturbances and sleep duration among Chinese university students.

Comment 3. Furthermore, I suggest that the authors include another heading after the introduction to provide an explanation of the relationship they have studied in this research and why these relationships are proposed. Also explain the theoretical foundation and practical evidence of the proposed relationships.

Response: Great thanks to you for your careful review and valuable suggestion. We had added another heading “Literature review and hypotheses” after the introduction and revised paragraph 3 and 4 as followed.

Recently, growing attention was paid on relationship of sleep disorders and social media usage. University students frequently suffer from poor sleep [26, 27]. The prevalence of insomnia in university students worldwide has been found to be 18.5%, much higher than the 7.4% rate in the general population [28]. The overall pooled prevalence of sleep disturbances and those suffering from insomnia symptoms in Chinese university students are 25.7% (95% CI: 22.5 ~28.9%) and 23.6% (95% CI: 18.9~29.0%), respectively [29]. The mechanisms behind the relationships between use of social media and sleep problems are not well established, but a theoretical model of the relationship has been proposed [30], suggesting several possible mechanisms. According to this model, social media use directly affect sleep quality by excess time consuming, or it may interfere with sleep by psychological arousal through the stimulating online content [30]. The relationships of delayed sleep onset, bad quality of sleep and increased time spent on internet were reported in previous studies [31, 32]. Frequent social media use could predict both poor mental health and bad sleep outcomes in youth [10]. Evidence showed that the impact of negative affect on sleep quality was mediated by FoMO and smartphone addiction in the sample of Chinese university students [33]. Additionally, insomnia partially mediated significant associations of interpersonal stress and FoMO with mental health in the college students [34]. When individuals were addicted to the Internet, the overall pooled odds ratio of experiencing sleep disturbance was 2.20 (95% CI: 1.77–2.74), and a significant reduce in sleep duration was observed [35]. Furthermore, there was higher rate of insomnia in those with higher level of SMA among Norwegian university students [36]. In summary, FoMO and SMA are closely with sleep quality. Although the relationship between chronic fatigue and sleep quality was confirmed among university students [37], few surveys on association of SMF and sleep quality were conducted among Chinese university students. Given FoMO and SMA acting as SMF drivers [38], we hypothesized that SMF was related to sleep quality.

Although social media use is linked with poor sleep outcomes, little research has focused on the relationship of FoMO, SMA, SMF and sleep quality. It is important to clarify the relationships of these four factors in order to detect the role of negative outcomes of social media use on sleep quality, and develop interventions to improve university students’ sleep quality for further study. Thus, this study was aimed to investigate the relationship between social media use, FoMO, SMA, SMF, sleep disturbance and sleep duration among Chinese university students.

Comment 4. Lastly, I appreciate the language improvement, but there are still a number of grammatical issues along with unclear expressions. Therefore, I recommend that the authors use the services of a professional copy-editor to help with this issue.

Response: We deeply appreciate for your careful review on our manuscript. We invited professor to improve the grammatical issues.

Attachment

Submitted filename: Response to Reviewers.docx

Click here for additional data file.^{(20.4KB, docx)}

PLoS One. doi: 10.1371/journal.pone.0292429.r005

Decision Letter 2

Ahsan Ali

29 Aug 2023

PONE-D-22-10183R2Exploring associations between social media addiction, social media fatigue, fear of missing out and sleep quality among university students: a cross-section studyPLOS ONE

Dear Dr. Zhu,

Please submit your revised manuscript by Oct 13 2023 11:59PM. If you will need more time than this to complete your revisions, please reply to this message or contact the journal office at plosone@plos.org. When you're ready to submit your revision, log on to https://www.editorialmanager.com/pone/ and select the 'Submissions Needing Revision' folder to locate your manuscript file.

Please include the following items when submitting your revised manuscript:

A rebuttal letter that responds to each point raised by the academic editor and reviewer(s). You should upload this letter as a separate file labeled 'Response to Reviewers'.
A marked-up copy of your manuscript that highlights changes made to the original version. You should upload this as a separate file labeled 'Revised Manuscript with Track Changes'.
An unmarked version of your revised paper without tracked changes. You should upload this as a separate file labeled 'Manuscript'.

We look forward to receiving your revised manuscript.

Kind regards,

Ahsan Ali

Academic Editor

PLOS ONE

Journal Requirements:

Please review your reference list to ensure that it is complete and correct. If you have cited papers that have been retracted, please include the rationale for doing so in the manuscript text, or remove these references and replace them with relevant current references. Any changes to the reference list should be mentioned in the rebuttal letter that accompanies your revised manuscript. If you need to cite a retracted article, indicate the article’s retracted status in the References list and also include a citation and full reference for the retraction notice.

Additional Editor Comments:

I appreciate your submission of the manuscript titled "Exploring associations between social media addiction, social media fatigue, fear of missing out, and sleep quality among university students: a cross-sectional study" to Plos One. After a rigorous evaluation conducted by multiple experts in the field, I have made a decision regarding the publication of your manuscript.

While your work addresses an interesting and significant topic, and the reviewers have noted substantial improvements in the paper, there remains a concern regarding language and grammar issues. To ensure the highest quality of publication, I strongly recommend that the authors consider seeking professional copy editing services to address these language and grammar concerns. Consequently, I invite you to revise and resubmit the paper after addressing these concerns.

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Reviewers' comments:

Reviewer's Responses to Questions

Comments to the Author

Reviewer #4: All comments have been addressed

**********

2. Is the manuscript technically sound, and do the data support the conclusions?

Reviewer #4: (No Response)

**********

3. Has the statistical analysis been performed appropriately and rigorously?

Reviewer #4: Yes

**********

4. Have the authors made all data underlying the findings in their manuscript fully available?

Reviewer #4: Yes

**********

5. Is the manuscript presented in an intelligible fashion and written in standard English?

Reviewer #4: (No Response)

**********

6. Review Comments to the Author

Reviewer #4: I would like to congratulate the authors for highlighting the prevailing issues regarding over use of social media among university students, and extending the existing body of knowledge.

**********

7. PLOS authors have the option to publish the peer review history of their article (what does this mean?). If published, this will include your full peer review and any attached files.

If you choose “no”, your identity will remain anonymous but your review may still be made public.

Do you want your identity to be public for this peer review? For information about this choice, including consent withdrawal, please see our Privacy Policy.

Reviewer #4: Yes: Tahir Ashfaq

**********

PLoS One. 2023 Oct 5;18(10):e0292429. doi: 10.1371/journal.pone.0292429.r006

Author response to Decision Letter 2

1 Sep 2023

Dear. Ahsan Ali:

On behalf of my co-authors, I thank you very much for giving us an opportunity to revise our manuscript, we also deeply appreciate the editor for your positive and constructive comments and suggestions on our manuscript entitled “Exploring associations between social media addiction, social media fatigue, fear of missing out and sleep quality among university students: a cross-section study” (ID: PONE-D-22-10183.R3). Those comments are all valuable and very helpful for revising and improving our paper, as well as providing important guidance for our research.

We have studied editor’s comments carefully and have made corresponding revisions that we hope to meet with qualifications for publication. We have tried our best to revise our manuscript according to the comments. Attached please find the revised version, which we would like to submit for your kind consideration. The major changes and revisions have been highlighted in red, which can be turned into black by rejecting all the changes. We hope that these revisions are satisfactory for your serious consideration to publish this manuscript in the PLOS ONE. We would like to express our appreciation again to you and reviewer for the comments on our paper.

Looking forward to hearing back from you.

Correspondence and phone calls about the paper should be directed to Xinhong Zhu at the following address, phone, and e-mail address:

Dr. Xinhong Zhu

We are very grateful to your comments and suggestions for revisions. The manuscript has been substantially improved according to the suggestions of the editor. The main corrections in the paper and the responses to the editor’s comments are addressed below.

Comment 1

Response: We deeply appreciate your comments. We have paid for a professional English editing service in AJE, and improved the quality of written English, including spelling mistakes, sentence structure and verb tense.

Attachment

Submitted filename: Response to eidtor.docx

Click here for additional data file.^{(632.3KB, docx)}

PLoS One. doi: 10.1371/journal.pone.0292429.r007

Decision Letter 3

Ahsan Ali

21 Sep 2023

Exploring associations between social media addiction, social media fatigue, fear of missing out and sleep quality among university students: a cross-section study

PONE-D-22-10183R3

Dear Dr. Zhu,

We’re pleased to inform you that your manuscript has been judged scientifically suitable for publication and will be formally accepted for publication once it meets all outstanding technical requirements.

Within one week, you’ll receive an e-mail detailing the required amendments. When these have been addressed, you’ll receive a formal acceptance letter and your manuscript will be scheduled for publication.

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Kind regards,

Ahsan Ali

Academic Editor

PLOS ONE

Additional Editor Comments (optional):

I am thankful to you for submitting the article titled "Exploring Associations Between Social Media Addiction, Social Media Fatigue, Fear of Missing Out, and Sleep Quality Among University Students: A Cross-Sectional Study" to PLOS ONE. I have reviewed the article along with the insightful comments provided by the three independent reviewers. Based on my reviewer recommendations and my assessment, I am pleased to recommend the acceptance of this paper for publication.

Reviewers' comments:

PLoS One. doi: 10.1371/journal.pone.0292429.r008

Acceptance letter

Ahsan Ali

26 Sep 2023

PONE-D-22-10183R3

Exploring associations between social media addiction, social media fatigue, fear of missing out and sleep quality among university students: a cross-section study

Dear Dr. Zhu:

I'm pleased to inform you that your manuscript has been deemed suitable for publication in PLOS ONE. Congratulations! Your manuscript is now with our production department.

If your institution or institutions have a press office, please let them know about your upcoming paper now to help maximize its impact. If they'll be preparing press materials, please inform our press team within the next 48 hours. Your manuscript will remain under strict press embargo until 2 pm Eastern Time on the date of publication. For more information please contact onepress@plos.org.

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on behalf of

Dr. Ahsan Ali

Academic Editor

PLOS ONE

Associated Data

This section collects any data citations, data availability statements, or supplementary materials included in this article.

Supplementary Materials

S1 File

(XLSX)

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S1 Table. General characteristics and Internet use of the participants (n = 2744).

(DOCX)

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Data Availability Statement

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[pone.0292429.ref001] 1.Chinese Internet Network Information Center. (2021). The 48rd China statistical report on Internet development. http: // www.cnnic.net.cn/hlwfzyj/hlwxzbg/hlwtjbg/202109/t20210915_71543.htm.

[pone.0292429.ref002] 2.Chinese Internet Network Information Center. (2019). The 43rd China statistical report on Internet development. http: // www.cnnic.net.cn/hlwfzyj/hlwxzbg/hlwtjbg/201902/P020190318523029756345.pdf.

[pone.0292429.ref003] 3.Chotpitayasunondh V, Douglas KM. How “phubbing” becomes the norm: The antecedents and consequences of snubbing via smartphone. Computers in Human Behavior. 2016;63:9–18. 10.1016/j.chb.2016.05.018 [DOI] [Google Scholar]

[pone.0292429.ref004] 4.Bashir I, Malik A, Mahmood K. Social media use and information-sharing behaviour of university students. IFLA Journal. 2021;47(4):481–92. 10.1177/0340035221991564 [DOI] [Google Scholar]

[pone.0292429.ref005] 5.Zhu X, Hu H, Xiong Z, Zheng T, Li L, Zhang L, et al. Utilization and professionalism toward social media among undergraduate nursing students. Nursing ethics. 2021;28(2):297–310. doi: 10.1177/0969733020952105 [DOI] [PubMed] [Google Scholar]

[pone.0292429.ref006] 6.Boer M, Stevens GW, Finkenauer C, de Looze ME, van den Eijnden RJ. Social media use intensity, social media use problems, and mental health among adolescents: Investigating directionality and mediating processes. Computers in Human Behavior. 2021;116:106645. 10.1016/j.chb.2020.106645. [DOI] [Google Scholar]

[pone.0292429.ref007] 7.Tandon A, Dhir A, Talwar S, Kaur P, Mäntymäki M. Dark consequences of social media-induced fear of missing out (FoMO): Social media stalking, comparisons, and fatigue. Technological Forecasting and Social Change. 2021;171:120931. 10.1016/j.techfore.2021.120931. [DOI] [Google Scholar]

[pone.0292429.ref008] 8.Xiao L, Mou J. Social media fatigue-Technological antecedents and the moderating roles of personality traits: The case of WeChat. Computers in Human Behavior. 2019;101:297–310. 10.1016/j.chb.2019.08.001. [DOI] [Google Scholar]

[pone.0292429.ref009] 9.Bouffard S, Giglio D, Zheng Z. Social media and romantic relationship: Excessive social media use leads to relationship conflicts, negative outcomes, and addiction via mediated pathways. Social Science Computer Review. 2022;40(6):1523–41. 10.1177/08944393211013566 [DOI] [Google Scholar]

[pone.0292429.ref010] 10.Alonzo R, Hussain J, Stranges S, Anderson KK. Interplay between social media use, sleep quality, and mental health in youth: A systematic review. Sleep medicine reviews. 2021;56:101414. doi: 10.1016/j.smrv.2020.101414 [DOI] [PubMed] [Google Scholar]

[pone.0292429.ref011] 11.Wong HY, Mo HY, Potenza MN, Chan MNM, Lau WM, Chui TK, et al. Relationships between severity of internet gaming disorder, severity of problematic social media use, sleep quality and psychological distress. International journal of environmental research and public health. 2020;17(6):1879. doi: 10.3390/ijerph17061879 [DOI] [PMC free article] [PubMed] [Google Scholar]

[pone.0292429.ref012] 12.Malik A, Dhir A, Kaur P, Johri A. Correlates of social media fatigue and academic performance decrement: a large cross-sectional study. Information Technology & People. 2021; 34 (2): 557–580. 10.1108/ITP-06-2019-0289 [DOI] [Google Scholar]

[pone.0292429.ref013] 13.James TL, Lowry PB, Wallace L, Warkentin M. The effect of belongingness on obsessive-compulsive disorder in the use of online social networks. Journal of Management Information Systems. 2017;34(2):560–96. 10.1080/07421222.2017.1334496. [DOI] [Google Scholar]

[pone.0292429.ref014] 14.Buglass SL, Binder JF, Betts LR, Underwood JD. Motivators of online vulnerability: The impact of social network site use and FOMO. Computers in Human Behavior. 2017;66:248–55. 10.1016/j.chb.2016.09.055 [DOI] [Google Scholar]

[pone.0292429.ref015] 15.Bright LF, Logan K. Is my fear of missing out (FOMO) causing fatigue? Advertising, social media fatigue, and the implications for consumers and brands. Internet Research. 2018, 28 (5): 1213–1227. 10.1108/IntR-03-2017-0112 [DOI] [Google Scholar]

[pone.0292429.ref016] 16.Blackwell D, Leaman C, Tramposch R, Osborne C, Liss M. Extraversion, neuroticism, attachment style and fear of missing out as predictors of social media use and addiction. Personality and Individual Differences. 2017;116:69–72. 10.1016/j.paid.2017.04.039. [DOI] [Google Scholar]

[pone.0292429.ref017] 17.Ravindran T, Yeow Kuan AC, Hoe Lian DG. Antecedents and effects of social network fatigue. Journal of the Association for Information Science and Technology. 2014;65(11):2306–20. 10.1002/asi.23122 [DOI] [Google Scholar]

[pone.0292429.ref018] 18.Cao X, Khan AN, Zaigham GH, Khan NA. The stimulators of social media fatigue among students: Role of moral disengagement. Journal of Educational Computing Research. 2019;57(5):1083–107. 10.1177/0735633118781907 [DOI] [Google Scholar]

[pone.0292429.ref019] 19.Dhir A, Kaur P, Chen S, Pallesen S. Antecedents and consequences of social media fatigue. International Journal of Information Management. 2019;48:193–202. 10.1016/j.ijinfomgt.2019.05.021 [DOI] [Google Scholar]

[pone.0292429.ref020] 20.Ou M, Zheng H, Kim HK, Chen X. A meta-analysis of social media fatigue: Drivers and a major consequence. Computers in Human Behavior. 2023;140:107597. 10.1016/j.chb.2022.107597 [DOI] [Google Scholar]

[pone.0292429.ref021] 21.Hawi NS, Samaha M. The relations among social media addiction, self-esteem, and life satisfaction in university students. Social Science Computer Review. 2017;35(5):576–86. 10.1177/0894439316660340 [DOI] [Google Scholar]

[pone.0292429.ref022] 22.Cheng C, Lau Y-c, Chan L, Luk JW. Prevalence of social media addiction across 32 nations: Meta-analysis with subgroup analysis of classification schemes and cultural values. Addictive behaviors. 2021;117:106845. doi: 10.1016/j.addbeh.2021.106845 [DOI] [PubMed] [Google Scholar]

[pone.0292429.ref023] 23.Chang L, Ma J. Development and validation of the Chinese social media addiction scale. Personality & Individual Differences. 2018;134:55–9. 10.1016/j.paid.2018.05.046 [DOI] [Google Scholar]

[pone.0292429.ref024] 24.Haand R, Shuwang Z. The relationship between social media addiction and depression: A quantitative study among university students in Khost, Afghanistan. International Journal of Adolescence and Youth. 2020;25(1):780–6. 10.1080/02673843.2020.1741407 [DOI] [Google Scholar]

[pone.0292429.ref025] 25.Azizi SM, Soroush A, Khatony A. The relationship between social networking addiction and academic performance in Iranian students of medical sciences: a cross-sectional study. BMC psychology. 2019;7(1):1–8. 10.1186/s40359-019-0305-0 [DOI] [PMC free article] [PubMed] [Google Scholar]

[pone.0292429.ref026] 26.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):174–81. doi: 10.1016/j.sleh.2018.01.001 [DOI] [PMC free article] [PubMed] [Google Scholar]

[pone.0292429.ref027] 27.Kloss JD, Nash CO, Horsey SE, Taylor DJ. The delivery of behavioral sleep medicine to college students. Journal of Adolescent Health. 2011;48(6):553–61. doi: 10.1016/j.jadohealth.2010.09.023 [DOI] [PubMed] [Google Scholar]

[pone.0292429.ref028] 28.Jiang X-L, Zheng X-Y, Yang J, Ye C-p, Chen Y-Y, Zhang Z-G, et al. A systematic review of studies on the prevalence of insomnia in university students. Public health. 2015;129(12):1579–84. doi: 10.1016/j.puhe.2015.07.030 [DOI] [PubMed] [Google Scholar]

[pone.0292429.ref029] 29.Li L, Wang YY, Wang SB, Zhang L, Li L, Xu DD, et al. Prevalence of sleep disturbances in Chinese university students: a comprehensive meta‐analysis. Journal of sleep research. 2018;27(3):e12648. doi: 10.1111/jsr.12648 [DOI] [PubMed] [Google Scholar]

[pone.0292429.ref030] 30.Cain N, Gradisar M. Electronic media use and sleep in school-aged children and adolescents: A review. Sleep Med. 2010;11(8):735–42. doi: 10.1016/j.sleep.2010.02.006 [DOI] [PubMed] [Google Scholar]

[pone.0292429.ref031] 31.Touitou Y, Touitou D, Reinberg A. Disruption of adolescents’ circadian clock: the vicious circle of media use, exposure to light at night, sleep loss and risk behaviors. Journal of Physiology-Paris. 2016;110(4):467–79. doi: 10.1016/j.jphysparis.2017.05.001 [DOI] [PubMed] [Google Scholar]

[pone.0292429.ref032] 32.LeBourgeois MK, Hale L, Chang A-M, Akacem LD, Montgomery-Downs HE, Buxton OM. Digital media and sleep in childhood and adolescence. Pediatrics. 2017;140(Supplement 2):S92–S6. doi: 10.1542/peds.2016-1758J [DOI] [PMC free article] [PubMed] [Google Scholar]

[pone.0292429.ref033] 33.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. 2020:877. doi: 10.3389/fpsyt.2020.00877 [DOI] [PMC free article] [PubMed] [Google Scholar]

[pone.0292429.ref034] 34.Adams SK, Murdock KK, Daly-Cano M, Rose M. Sleep in the social world of college students: Bridging interpersonal stress and fear of missing out with mental health. Behavioral sciences. 2020;10(2):54. doi: 10.3390/bs10020054 [DOI] [PMC free article] [PubMed] [Google Scholar]

[pone.0292429.ref035] 35.Alimoradi Z, Lin C-Y, Broström A, Bülow PH, Bajalan Z, Griffiths MD, et al. Internet addiction and sleep problems: A systematic review and meta-analysis. Sleep medicine reviews. 2019;47:51–61. doi: 10.1016/j.smrv.2019.06.004 [DOI] [PubMed] [Google Scholar]

[pone.0292429.ref036] 36.Hjetland GJ, Skogen JC, Hysing M, Sivertsen B. The association between self-reported screen time, social media addiction, and sleep among Norwegian University students. Frontiers in public health. 2021;9:794307. doi: 10.3389/fpubh.2021.794307 [DOI] [PMC free article] [PubMed] [Google Scholar]

[pone.0292429.ref037] 37.Luo L, Zhang Y, Huang T, Zhou F, Xiong C, Liu Y, et al. A description of the current status of chronic fatigue syndrome and associated factors among university students in Wuhan, China. Front Psychiatry. 2022;13:1047014. doi: 10.3389/fpsyt.2022.1047014 [DOI] [PMC free article] [PubMed] [Google Scholar]

[pone.0292429.ref038] 38.Zheng H, Ling R. Drivers of social media fatigue: A systematic review. Telematics and Informatics. 2021;64:101696. 10.1016/j.tele.2021.101696. [DOI] [PMC free article] [PubMed] [Google Scholar]

[pone.0292429.ref039] 39.Liu XC, Tang MQ. Reliability and validity of the Pittsburgh Sleep Quality Index. Chinese Journal of Psychiatry. 1996;29(2):29103–7. 10.1007/BF02951625. [DOI] [Google Scholar]

[pone.0292429.ref040] 40.Lee AR, Son SM, Kim KK. Information and communication technology overload and social networking service fatigue: A stress perspective. Computers in Human Behavior. 2016;55(FEB.):51–61. 10.1016/j.chb.2015.08.011 [DOI] [Google Scholar]

[pone.0292429.ref041] 41.Zhang Q. F. Scale development for social media fatigue [D]. Xiamen, Xiamen University. [Google Scholar]

[pone.0292429.ref042] 42.Beaton DE, Bombardier C, Guillemin F, Ferraz MB. Guidelines for the process of cross-cultural adaptation of self-report measures. Spine. 2000;25(24):3186–91. doi: 10.1097/00007632-200012150-00014 [DOI] [PubMed] [Google Scholar]

[pone.0292429.ref043] 43.Li L, Griffiths MD, Niu Z, Mei S. The trait-state fear of missing out scale: Validity, reliability, and measurement invariance in a Chinese sample of university students. J Affect Disord. 2020;274:711–8. doi: 10.1016/j.jad.2020.05.103 [DOI] [PubMed] [Google Scholar]

[pone.0292429.ref044] 44.Kolhar M, Kazi RNA, Alameen A. Effect of social media use on learning, social interactions, and sleep duration among university students. Saudi journal of biological sciences. 2021;28(4):2216–22. doi: 10.1016/j.sjbs.2021.01.010 [DOI] [PMC free article] [PubMed] [Google Scholar]

[pone.0292429.ref045] 45.Hale L, Hill TD, Friedman E, Nieto FJ, Galvao LW, Engelman CD, et al. Perceived neighborhood quality, sleep quality, and health status: evidence from the Survey of the Health of Wisconsin. Social science & medicine. 2013;79:16–22. doi: 10.1016/j.socscimed.2012.07.021 [DOI] [PMC free article] [PubMed] [Google Scholar]

[pone.0292429.ref046] 46.Patel NP, Grandner MA, Xie D, Branas CC, Gooneratne N. " Sleep disparity" in the population: poor sleep quality is strongly associated with poverty and ethnicity. BMC Public Health. 2010;10:1–11. 10.1186/1471-2458-10-475 [DOI] [PMC free article] [PubMed] [Google Scholar]

[pone.0292429.ref047] 47.Gezgin DM, Hamutoglu NB, Gemikonakli O, Raman I. Social networks users: fear of missing out in preservice teachers. Journal of Education and Practice. 2017;8(17):156–68. https://eprints.mdx.ac.uk/id/eprint/22198 [Google Scholar]

[pone.0292429.ref048] 48.Van den Bulck J. Television viewing, computer game playing, and Internet use and self-reported time to bed and time out of bed in secondary-school children. Sleep. 2004;27(1):101–4. doi: 10.1093/sleep/27.1.101 [DOI] [PubMed] [Google Scholar]

[pone.0292429.ref049] 49.Scott H, Woods HC. Fear of missing out and sleep: Cognitive behavioural factors in adolescents’ nighttime social media use. Journal of adolescence. 2018;68:61–5. doi: 10.1016/j.adolescence.2018.07.009 [DOI] [PubMed] [Google Scholar]

[pone.0292429.ref050] 50.Moreno M, Riddle K, Jenkins MC, Singh A, Zhao Q, Eickhoff J. Measuring Problematic Internet Use, Internet Gaming Disorder and Social Media Addiction in young adults: A cross-sectional study. JMIR public health and surveillance. 2022, 8(1), e27719. 10.2196/27719 [DOI] [PMC free article] [PubMed] [Google Scholar]

[pone.0292429.ref051] 51.Fossum IN, Nordnes LT, Storemark SS, Bjorvatn B, Pallesen S. The association between use of electronic media in bed before going to sleep and insomnia symptoms, daytime sleepiness, morningness, and chronotype. Behavioral sleep medicine. 2014;12(5):343–57. doi: 10.1080/15402002.2013.819468 [DOI] [PubMed] [Google Scholar]

[pone.0292429.ref052] 52.Wahl S, Engelhardt M, Schaupp P, Lappe C, Ivanov IV. The inner clock—Blue light sets the human rhythm. Journal of biophotonics. 2019;12(12):e201900102. doi: 10.1002/jbio.201900102 [DOI] [PMC free article] [PubMed] [Google Scholar]

[pone.0292429.ref053] 53.Park M, Jeong SH, Huh K, Park YS, Park E-C, Jang S-Y. Association between smartphone addiction risk, sleep quality, and sleep duration among Korean school-age children: a population-based panel study. Sleep and Biological Rhythms. 2022;20(3):371–80. 10.1007/s41105-022-00377-6 [DOI] [PMC free article] [PubMed] [Google Scholar]

[pone.0292429.ref054] 54.Choi SB, Lim MS. Effects of social and technology overload on psychological well-being in young South Korean adults: The mediatory role of social network service addiction. Computers in Human Behavior. 2016;61(AUG.):245–54. 10.1016/j.chb.2016.03.032. [DOI] [Google Scholar]

[pone.0292429.ref055] 55.Sajadi A, Farsi Z, Rajai N. The relationship between sleep quality with fatigue severity and academic performance of nursing students. Nursing Practice Today. 2014;1(4):213–20. [Google Scholar]

[pone.0292429.ref056] 56.Kübra U, GÜNDOĞAN, GÜRBÜZ ÖB, ÖZÇAKAR N. Status of fatigue and sleep quality in clinical medical students. Marmara Medical Journal. 2016;29(3):164–9. 10.5472/MMJoa.2903.05 [DOI] [Google Scholar]

[pone.0292429.ref057] 57.Valpiani EM, Brown RF, Thorsteinsson EB, Hine D. Poor sleep quality mediates between depression to fatigue in a university student sample. Psychology and Education: An Interdisciplinary Journal. 2011. [Google Scholar]

[pone.0292429.ref058] 58.Åkerstedt T, Knutsson A, Westerholm P, Theorell T, Alfredsson L, Kecklund G. Mental fatigue, work and sleep. Journal of psychosomatic Research. 2004;57(5):427–33. doi: 10.1016/j.jpsychores.2003.12.001 [DOI] [PubMed] [Google Scholar]

[pone.0292429.ref059] 59.Davidson JR, MacLean AW, Brundage MD, Schulze K. Sleep disturbance in cancer patients. Social science & medicine. 2002;54(9):1309–21. doi: 10.1016/s0277-9536(01)00043-0 [DOI] [PubMed] [Google Scholar]

[pone.0292429.ref060] 60.Dhir A, Yossatorn Y, Kaur P, Chen S. Online social media fatigue and psychological wellbeing—A study of compulsive use, fear of missing out, fatigue, anxiety and depression. International Journal of Information Management. 2018;40(JUN.):141–52. 10.1016/j.ijinfomgt.2018.01.012 [DOI] [Google Scholar]

[pone.0292429.ref061] 61.Lian SL, Sun XJ, Zhou ZK, Fan CY, Niu GF, Liu QQ. Social networking site addiction and undergraduate students’ irrational procrastination: The mediating role of social networking site fatigue and the moderating role of effortful control. PloS one. 2018;13(12):e0208162. doi: 10.1371/journal.pone.0208162 [DOI] [PMC free article] [PubMed] [Google Scholar]

PERMALINK

Exploring associations between social media addiction, social media fatigue, fear of missing out and sleep quality among university students: A cross-section study

Xinhong Zhu

Taoyun Zheng

Linlin Ding

Xiaona Zhang

Zhihan Li

Hao Jiang

Roles

Abstract

Background

Method

Result

Conclusion

1. Introduction

2. Literature review and hypotheses

3. Methods

3.1 Participants and data collection

3.2 Instruments

Pittsburgh Sleep Quality Index (PSQI)

Sleep duration

Social Media Fatigue (SMF)

Social Media Addiction (SMA)

Fear of Missing Out (FoMO)

Social media use

Demographic questionnaire

3.3 Ethics statement

3.4 Data analysis

Table 1. Factors associated with sleep quality among university students.

Table 2. Factors associated with sleep duration among university students.

Table 3. Factors associated with SMF among university students.

4. Results

4.1 Participant characteristics

4.2 Sleep quality

4.3 Sleep duration

Fig 1. Mean score of SMF, SMA and FoMO across sleep duration.

4.4 SMF

5. Discussion

6. Conclusion

Supporting information

Acknowledgments

Data Availability

Funding Statement

References

Decision Letter 0

Ugurcan Sayili

Roles

Author response to Decision Letter 0

Decision Letter 1

Ahsan Ali

Roles

Author response to Decision Letter 1

Decision Letter 2

Ahsan Ali

Roles

Author response to Decision Letter 2

Decision Letter 3

Ahsan Ali

Roles

Acceptance letter

Ahsan Ali

Roles

Associated Data

Supplementary Materials

Data Availability Statement

ACTIONS

PERMALINK

RESOURCES

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