Skip to main content

ORIGINAL RESEARCH article

Front. Public Health, 31 October 2022
Sec. Public Mental Health
This article is part of the Research Topic Employing Digital Footprints in Measuring Mental Health Status of Adolescent Internet Users View all 8 articles

Social networking use, mental health, and quality of life of Hong Kong adolescents during the COVID-19 pandemic

\nLu Yu
Lu Yu*Meng DuMeng Du
  • Department of Applied Social Sciences, The Hong Kong Polytechnic University, Kowloon, Hong Kong SAR, China

Background: During the COVID-19 pandemic, adolescents' use of social networking sites/apps has surged, and their mental health and quality of life have also been significantly affected by the pandemic and its associated social-protection measures. The present study first examined the prevalence of social networking sites/apps use and social networking addiction, the mental health status, and the health-related quality of life among Hong Kong adolescent students. We further investigated the associations of the youths' daily use of social networking sites/apps and their social networking addiction with their mental health and quality of life during the pandemic.

Methods: A total of 1,147 students (age = 15.20 ± 0.53 years) recruited from 12 randomly selected local secondary schools in Hong Kong participated in a questionnaire survey in classroom settings between January and June, 2020, right after the COVID-19 outbreak. The questionnaire includes demographic characteristics and scales that measure social networking sites/apps use and social networking addiction, mental health, and quality of life.

Results: Approximately 46.4% of the participants reported using social networking sites/apps often or very often, and 7.8% met the criteria for social networking addiction using Bergen's Social Media Addiction Scale. The prevalence of mild to extremely severe depression, anxiety, and stress among the adolescents stood at 39.6, 37.5, 48.8%, respectively, and the participants' physical, social, and school functioning were lower than the norms of healthy adolescents before the pandemic. Participants who used social networking sites/apps but for <3 h per day (excluding students who never used social networking sites/apps) showed significantly fewer problems of depression, anxiety, and stress than did those who spent more than 3 h per day on social networking sites/apps. Social networking addiction was found to be consistently associated with poor mental health and health-related quality of life.

Conclusion: This study provides important evidence supporting the potential protective effect of guiding adolescents to use social networking sites/apps appropriately in order to mitigate their negative emotions during contexts such as that of the pandemic; it further points to the need to provide extra support to promote the well-being of young people, especially those in disadvantaged situations (e.g., non-intact family) during and after the pandemic.

Introduction

The pandemic of COVID-19 and its variants have caused an unprecedented crisis and infected more than 640 million people worldwide (1). A series of public health measures have been implemented, including but not limited to social distancing and mandatory closure of schools (2). These measures, along with the socioeconomic impact associated with COVID-19, have presented a tremendous threat to mental health, globally, especially for young people (3). The disruption of their daily lives, challenges of online learning, limited face-to-face social interactions, increased family/parental stress, and feelings of uncertainty about the future all put children and adolescents at a high risk for mental health problems (46). According to the Organization for Economic Co-operation and Development, youth (aged 15–24 years) have been found to be 30–80% more likely to report symptoms of depression or anxiety and higher levels of loneliness than adults have during the pandemic (7). It is also estimated that the adverse consequences of the pandemic on youths' mental health and quality of life will be long-term, thus making continuous monitoring and prevention strategies a necessity.

Another notable issue that has emerged in the pandemic is adolescents' increased use of the Internet, and specifically their overuse of social media and social networking sites/apps (SNSs). A recent report (8) showed that there has been a significant increase in the average time people spend on social media in the United States during the pandemic. All leading social platforms reported monthly active usage growth in 2021 compared with 2019 (9). Teenagers use SNSs to keep track of news and information about the coronavirus, maintain social interactions with friends and family, and provide entertainment, such as videos (10). There are definite benefits of using SNSs during the pandemic (11, 12).

On the other hand, the use of SNSs could also be problematic. Adolescents' overuse of the SNSs increases their risk for developing social networking addiction (SNA), which is defined as the status of “being overly concerned about social networking sites (SNSs), driven by a strong motivation to log on to or use SNSs, and to devote too much time and effort to SNSs that it impairs other social activities, studies/job, interpersonal relationships, and/or psychological health and well-being” [(13), p. 175]. In a recent study in Ukraine, 26% of the student participants reported that using social media had resulted in sleep problems, which could further lead to physical and psychological problems (14). Grave concerns about overuse of SNSs during the pandemic have also been raised in the Chinese context (15). In Hong Kong, researchers had reported a high prevalence of SNA among secondary school students before the pandemic (16, 17), and the general form of Internet addiction has been growing at a staggering rate during the pandemic (18). However, there is still a lack of specific research on the amount of time that Hong Kong adolescents spend daily on SNSs and on the prevalence of social networking/media addiction (SNA) in this population, during COVID-19. Hence, the first aim of this study was to examine the general use and the excessive/problematic use of SNSs among Hong Kong adolescents during the pandemic.

Another unanswered question is what the relationships are between adolescents' use of SNSs and their mental health status, and their SNSs use and their quality of life, during COVID-19. More generally, there is a wealth of evidence, based primarily on studies done before the pandemic, supporting the notion that overuse of SNSs has a negative impact on children and adolescents' mental health (19, 20). Other studies have suggested a mutual relationship between overuse of SNSs and an increased sense of loneliness (2123). Nonetheless, mixed findings have also been reported, suggesting that the relationship between adolescents' frequency of SNS use and their depressive/anxiety symptoms may not be significant over time (24, 25).

Still, relatively few studies have been conducted to examine the impact of SNSs use/excessive use on youths' well-being since the outbreak of the pandemic (26, 27). Among the few that have been done, Chen et al. (15) reported that school-aged children spent significantly more time on their smartphones and social media during school suspension than before, and the positive association between the children's problematic use of social media and psychological distress was stronger during the school suspension than at the baseline. On the other hand, some scholars hold positive views about using social networking sites during the pandemic. Via social networking online, adolescents can keep connected with their friends and teachers when close in-person contact is not possible, thus providing important social support that reduces the adolescents' perceived loneliness, enables them to handle negative emotions, and promotes their well-being (11, 28). In Cauberghe et al.'s study (10), online social networking was perceived by adolescents to be a constructive coping strategy to deal with their anxiety and depression during COVID-19. Abbas et al. (29) further posited that social media use provides great access for adolescents to gain health-related information, which can further lead to healthy behaviors that can prevent the spread of the virus. These findings seem to suggest that excessive social networking usage during the specific situation of COVID-19 may not necessarily be harmful to youths' mental health and quality of life, but instead may play a protective role for their well-being. Against this mixed background, the second aim of the present study was to investigate the association between Hong Kong adolescents' use and / or excessive use of SNSs during the pandemic and their mental health and their quality of life, by studying a representative sample of secondary school students in Hong Kong.

Furthermore, studies have shown that adolescents generally have displayed increased mental health problems and impairment in social functioning (3034) since the outbreak of the pandemic. With particular reference to Hong Kong, one of the most densely populated areas in the world (35), adolescents living in this city have been facing distinct challenges in the COVID-19 pandemic. The stringent public health measures have forced people to stay at home, which on the one hand may provide opportunities for families to develop family solidarity and to support each other, but on the other hand may increase family stresses and conflicts, especially when members have to share the limited living space and resources of the home that are necessary for working and studying remotely. Indeed, studies have shown that living in small, crowded living and learning spaces with a lack of outside activity are positively associated with higher than usual levels of depression (36, 37). A dense living environment also increases the risk for community-acquired infections (38), which creates more COVID-related fear in the residents (39). At the same time, parents are experiencing high levels of stress (40, 41), which in turn affects their adolescent children's adjustment through a cascading process.

However, research specifically investigating young people's well-being in terms of both mental health and health-related quality of life in Hong Kong during the pandemic has been relatively limited (42, 43), and the findings are inconsistent. In one study, high rates of depressive symptoms (59.2%), anxiety (66%), and stress (53.7%) were reported in Hong Kong university students (44). Another study, based on a secondary school student sample, revealed that 39.2% of the participants reported being more stressed; 59.5% reported feeling greater study pressures; 24.2% were feeling more horrified; 33.2% were feeling more apprehensive, and 22% were feeling more helpless during the pandemic than they were before (43). In contrast, a longitudinal survey showed that the prevalence of suicidal ideation among secondary school students decreased from 24 to 21% after the first, large wave of COVID, with 14% having recovered from the suicidal ideation group and only 10.7% first reporting suicidal ideation in the follow-up (18). Clearly, more studies are needed in order to build a comprehensive understanding of the mental health status and quality of life of Hong Kong adolescents who are now facing a long-term disturbance following the onset of the pandemic. The third aim of the present study was to address this issue.

To summarize, the purpose of this study was threefold: (a) to examine the prevalence of Hong Kong adolescents using social networking sites (SNSs) and their incidence of problematic use (i.e., social networking addiction, SNA) during the COVID-19 pandemic, (b) to estimate the mental health status and health-related quality of life of Hong Kong adolescents during the pandemic, and (c) to investigate the relationship between different degree of SNSs use behaviors (including SNA) and adolescents' well-being under the influence of the pandemic. Specifically, we attempted to answer the following research questions:

1. How often are Hong Kong adolescents using SNSs, and what is the percentage of adolescents showing social networking addiction (SNA), during the pandemic?

2. What is the mental health status of Hong Kong adolescents during the pandemic? What is their quality of life?

3. What is the relationship between different degrees of SNS use, including SNA, and Hong Kong adolescents' mental health? What is the relationship between different degrees of their SNSs use and their health-related quality of life?

Methods

Participants and procedure

This study was part of a larger longitudinal project investigating the positive youth development and Internet use of Hong Kong adolescents. The target population was Hong Kong junior secondary school students. Based on a two-stage cluster sampling, we first randomly selected 20 schools from all 471 Hong Kong local secondary schools; then all students studying in Secondary One (i.e., Grade 7) in the selected schools were invited to join the survey. The survey was conducted between January and June, 2020, right after the COVID-19 outbreak. Students who agreed to participate in the study completed the questionnaire in classroom settings. A trained research staff member administered the questionnaire survey without the presence of any school staff. Strict confidentiality was maintained during the data collection. Participants' completed questionnaires were kept strictly confidential.

Ethical considerations

The project was approved by the Human Subjects Ethics Sub-Committee (HSESC) of the first author's institution (Reference No.: HSEARS20180326015). After obtaining the approval from the participating schools, students were invited to participate in the study on a voluntary basis. Both parents' and students' written informed consents were obtained before the data collection. In order to ensure anonymity and confidentiality, participants were not identified individually and data were treated in aggregate manners for overall analyses. Data collected from the questionnaires were handled by members of the Research Team only, and the records were securely stored such that only members of the Research Team were able to gain access to.

Instruments

Demographic information on the participants was collected with a list of items that were drafted by the research team and had been used in previous large-scale studies (45, 46). Students' social networking addiction (SNA), use of SNSs, mental health, and quality of life were measured by validated Chinese versions of questionnaires, as described below.

Bergen social media addiction scale

The validated Chinese six-item version of the Bergen Social Media Addiction Scale [BSMAS; (47)] was adopted to assess the participants' addiction to social networking (48). The BSMAS measures six core symptoms of behavioral addiction (i.e., salience, mood modification, tolerance, withdrawal, conflict, and relapse), which were based on Griffith's (49) model. Participants responded to each item using a five-point rating scale to indicate the frequency of the described behavior they had displayed in the past year (1= very rarely; 2 = rarely; 3 = sometimes; 4 = often; 5 = very often). Higher scores on the BSMAS indicate greater problematic use of social media or SNSs. In the present study, we adopted the criterion (50) that participants with a total scale score above 19 would be identified as being at high risk for SNA. The Cronbach's alpha of the BSMAS in the present study was 0.89.

Two additional questions were asked to assess the adolescents' self-perceived daily amount of time spent on SNSs and their frequency of usage. The first question asked the respondents “how much time have you spent on SNSs daily in the past month,” and they answered using a five-point rating scale (1 = never; 2 = < 1 h; 3 = 1–2 h; 4 = 2–3 h; 5 = more than 3 h). Second, the respondents answered the question “how frequently did you use SNSs in the past week” on a five-point rating scale (1 = never; 2 = occasionally; 3 = sometimes; 4 = often; 5 = very often).

Depression anxiety stress scale-21

The students' mental health was measured by the Chinese version of the Depression Anxiety Stress Scale-21 [DASS 21, (51)], which has been a widely adopted measure of emotional states of depression (seven items), anxiety (seven items), and stress (seven items). Participants indicated how strongly each statement applied to them over the previous week using a four-point rating scale (0 = did not apply to me at all; 1 = applied to me to some degree or some of the time; 2 = applied to me to a considerable degree or a good part of time; 3 = applied to me very much or most of the time). Higher scores represented a higher level of emotional problems. The Cronbach's alpha for the three subscales in this study were 0.84 (depression), 0.91 (anxiety), and 0.86 (stress).

Pediatric quality of life inventory

The Pediatric Quality of Life Inventory [PedsQL, (52)] is a well-validated brief measure of health-related quality of life in children and adolescents and has been validated in Chinese population (53, 54). It is a self-reported questionnaire for adolescents that has four dimensions: physical functioning (eight items), emotional functioning (five items), social functioning (five items), and school functioning (five items). For each item, the participants rated the frequency at which the described phenomena occurred in their life during the month prior to the survey, using a five-point response scale (0 = never a problem; 1 = almost never a problem; 2 = sometimes a problem; 3 = often a problem; 4 = almost always a problem). We did not adopt the five items of the emotional functioning subscale in the present study because the DASS21 had already measured the participants' emotional status. The PedsQL is reverse-coded and computed into standardized scores (54), with higher scores representing a better health-related quality of life. Based on the present sample, the Cronbach's alpha coefficients for this study were 0.87 for physical functioning, 0.89 for social functioning, and 0.78 for school functioning.

Data analysis

We used SPSS 26.0 statistical software for data analysis in the present study. For the first two research questions, descriptive statistics were first computed to provide a profile of the prevalence of the use of SNSs and the incidence of SNA among the Hong Kong adolescents during the pandemic, as well as their mental health status and health-related quality of life. To examine the association between the amount of time that the adolescents used SNSs and their mental health and also their health-related quality of life, two MANOVA were performed, controlling for age and gender: in the first MANOVA, depression, anxiety, and stress were treated as dependent variables (DV) and the participants' self-reported daily amount of time using SNSs was treated as an independent variable (IV); in the second MANOVA, physical, social, and school functioning served as the DVs with the same IV. To investigate the relationships between SNA and the adolescents' mental health and quality of life statuses, six multiple regression analyses were performed. In each regression model, one indicator of the participants' mental health (i.e., depression, anxiety, or stress) or health-related quality of life served as the DV; the demographic characteristics of gender, age, family intactness, and immigration status (whether the individual had been born in Hong Kong or elsewhere) were entered into the first block, and their SNA scores (indicated by the participants' scores on the BSMAS) was entered into the second block.

Results

Demographic characteristics of the participants

The participants comprised 1,147 students (602 females and 546 males; 21 did not report their gender) who were recruited from 12 secondary in Hong Kong. The mean age of the participants was 15.20 years (SD = 0.53 years) at the time of data collection. The majority of the students were born in Hong Kong (N = 1024; 87.6%) and were growing up in intact families (N = 868; 74.3%).

Prevalence of SNSs use and of SNA

First, in terms of the amount of time that the participants spent on SNSs, 30.8% of the students spent 2–3 h per day, while 28.2% spent more than 3 h; and 46.4% of the participants reported that they used SNSs often or very often. Second, different problematic use-of-SNS behaviors were reported by the students and are summarized in Table 1. The students' mean total BSMAS score was 13.04 ± 4.96. Using the cutoff score of 19 (50), 7.8% of the students could be identified as having SNA. Among the six SNA behaviors, “spend a lot of time thinking about social media or planning how to use it” was the most prevalent one, with 15.8% of the participants reporting that they were preoccupied with SNSs (salience) often or very often. Notably, 10.3% of the students expressed that they “use[d] social media so much that it has had a negative impact on your job/studies” (conflict), and 9.9% reported that they often or very often “use[d] social media in order to forget about personal problems” (mood modification).

TABLE 1
www.frontiersin.org

Table 1. Descriptive statistics of the participants' SNSs use and SNA behaviors.

Mental health and health-related quality of life

Table 2 shows the means and standard deviations of the participants' scores on the DASS21. Their scores for the depression, anxiety, and stress subscales were doubled to calculate a final score for the identification of different levels of negative emotions. According to the recommended cutoffs (53), participants were categorized into groups of different levels of negative emotions. It was revealed that the prevalence of mild to extremely severe depression in the participants stood at 39.6%, anxiety was at 37.5%, and stress was at 48.8%. In particular, 14.4% of the students reported severe or extremely severe depression, 9.5% reported severe or extremely severe anxiety, and 14.8% had severe or extremely severe stress. The students' standardized scores on the physical, social, and school functioning subscales of the PedsQL were 78.80 ± 17.65, 80.53 ± 18.82, and 75.85 ± 18.11, respectively. These scores were significantly lower than the norm scores of healthy children and adolescents in different Chinese contexts before the pandemic (55).

TABLE 2
www.frontiersin.org

Table 2. Descriptive statistics of the participants' levels of depression, anxiety, and stress.

Relationship between SNS use and SNA and the adolescents' well-being

Results of two MANOVA are summarized in Table 3. The students' daily amount of time spent on SNSs was significantly associated with their mental health (F = 3.24, Wilk's lambda = 0.96, p < 0.001, η2p = 0.01, 90% CI 0.00–0.02) and their health-related quality of life (F = 2.41, Wilk's lambda = 0.97, p < 0.01, η2p = 0.01, 90% CI 0.00–0.02). Post-hoc comparisons further revealed that students who spent “ < 1 h,” “1–2 h,” and “2–3 h” per day on SNSs had lower scores on the scales for depression, anxiety, and stress than students who spent “≥ 3 h” per day did, but interestingly, there was no significant difference between the group who never used SNSs and the group who used SNSs for more than 3 h per day. In terms of health-related quality of life, post-hoc multiple comparisons showed that only in school functioning did the group who never used SNSs score higher than the group who reported their daily SNSs usage was 3 h or more. No other significant differences among the groups were observed.

TABLE 3
www.frontiersin.org

Table 3. Results of MANOVA comparing the mental health and quality of life of the participants in conjunction with their daily amount of SNSs.

Multiple regression analyses were performed to examine the relationships between SNA and the students' mental health and their quality of life. For the regression on mental health indicators (Table 4), family non-intactness was positively associated with the students' levels of depression (β = 0.08; p < 0.01), anxiety (β = 0.08; p < 0.01), and stress (β = 0.07; p < 0.05), suggesting that students from non-intact families had more symptoms of depression, anxiety, and stress than their peers from intact families did. After controlling for the demographic variables, the students' scores on the BSMAS scale–that is, their SNA scores–were positively associated with depression (β = 0.25; p < 0.001), anxiety (β = 0.28; p < 0.001), and stress (β = 0.29; p < 0.001). With regard to their health-related quality of life (Table 5), the regression results showed that the students' SNA scores were negatively associated with their physical functioning (β = −0.21, p < 0.001), social functioning (β = −0.17, p < 0.001), and school functioning (β = −0.23, p < 0.001).

TABLE 4
www.frontiersin.org

Table 4. Results of multiple regressions on the predictive effects of SNA on the participants' mental health indicators.

TABLE 5
www.frontiersin.org

Table 5. Results of multiple regressions on the predictive effects of SNA on the participants' health-related quality of life indicators.

Discussion

The present study investigated Hong Kong adolescents' use of social networking sites and their social networking addiction (SNA); their mental health and health-related quality of life status; and the associations of their SNSs use and social networking addiction with their well-being during the COVID-19 pandemic. We found that nearly half of the participants reported using SNSs often or very often, while the prevalence of SNA was no higher than the reported rates before the pandemic (56). The students' mental health status and their health-related quality of life were at a low level compared with findings for those attributes before the pandemic (55). Different amounts of time spent using SNSs daily were associated differentially with negative emotions, while SNA was consistently associated with poor mental health status and poor health-related quality of life. This study's findings point to a potential protective effect on youths' mental health from using SNSs appropriately during the pandemic.

Frequent use of SNSs by the adolescents during the pandemic was found to be a common phenomenon, and the amount of time they spent on SNSs was generally associated with their well-being. Roughly one-third of the participants (30.8%) reported that they spent ~2–3 h daily on SNSs, and 28.2% reported using SNSs for more than 3 h per day. Only <20% of the students reported that they never or only occasionally used SNSs. When we further compared mental health and health-related quality of life indicators among the students with their different usage times for SNSs, the results showed that the students who spent from <1 h to ~2–3 h per day using SNSs reported lower levels of depression, anxiety, and stress than did the students who spent more than 3 h on SNSs per day, while the group of students who never used SNSs had a level of negative emotions that was comparable with that of the group with more than 3 h daily on SNSs. Contrary to other recent findings showing that the increase in the time spent using SNSs was associated with anxiety problems during the pandemic [see the meta-analysis by Lee et al. (57)], our findings suggest that using SNSs for 3 h per day or somewhat less can have beneficial effects on adolescents' mental health during the pandemic. The SNSs can provide a convenient and safe channel for youths to use for communicating and connecting with their peers, families, and teachers when face-to-face interaction is restricted; SNSs also give adolescents access to the most updated information with reference to their studies, life, health, and the pandemic. Our present findings support the positive effect of SNSs usage and offer preliminary evidence on how much time spent on SNSs may be appropriate for adolescents without compromising their physical and mental health.

Nonetheless, we also found that addiction to social networking remained associated with increased depression, anxiety, and stress symptoms and lower scores for physical, social, and school functioning. Although this finding is consistent with those of existing studies supporting the harmful effects of SNA on adolescents' health (16, 17), our results further indicate that even during the pandemic, with online interaction having become a new normal, excessive and problematic use of the SNSs can undermine rather than promote adolescents' well-being. Excessive use of SNSs cannot help adolescents address their emotional problems, reduce their sense of loneliness, or promote their deteriorated social and school functioning associated with the pandemic. Instead, uncontrollable use of SNSs has been found to lead one to neglect other beneficial aspects of one's life during the pandemic (e.g., academic work, physical exercise, offline interpersonal communication), and that can further result in negative emotions and impaired functioning (58). In particular, people with SNA are described as “experiencing a constant urge to check their social networks for new information and updates because of the fear of missing out” [(59), p. 6]. Under the unique circumstances of COVID-19, such an urge may become stronger, thus causing even more anxiety and stress.

It should be noted that such associations between SNA and mental health problems, as well as low quality of life, could be a reverse causation–that is, adolescents' existing mental health issues could result in their problematic use of the SNSs. Prior studies have found that young people who are suffering from different health and mental health problems tend to develop a pattern of using SNSs as a coping strategy to decrease their feelings of loneliness, uncertainty, and powerlessness, to gain comfort and support from others, and to maintain a sense of belongingness to their peer group (6064). There has also been evidence for a bi-directional relationship between SNA and mental health problems: people with existing psychological problems are more likely to indulge in SNSs use to avoid or reduce their negative emotions, while compulsive use of SNSs generates additional stress and damages their well-being (64, 65). The pandemic and its associated preventive measures have jeopardized adolescents' quality of life and mental health, and that may further increase the risks that the adolescents will develop SNA. To clarify this relationship, future studies should adopt a longitudinal design that involves multiple waves of data collection of not only SNA and well-being indicators, but also of potential mediators [e.g., satisfaction of needs (66); emotional competence (67); and self-control (68)] and of moderators [e.g., offline social capital (69); mindfulness (70)]; and specific contextual factors, such as the pandemic-related social policies.

With reference to adolescents' well-being during the pandemic, 39.6% of the Hong Kong secondary school students in the present study experienced mild to extremely severe levels of depression, 37.5% experienced mild to extremely severe levels of anxiety, and 48.8% experienced mild to extremely severe levels of stress. The occurrence rates of these negative emotions were significantly higher than the rates reported for the same emotions before the pandemic (55). Participants also had significantly lower scores for their levels of physical functioning, social functioning, and school functioning as measured by the PedsQL than the norms for healthy teens (7173). These findings further support the notion that the pandemic has been detrimental to young people's mental health and quality of life, worldwide (7477). A recent study of university students in Hong Kong (78) identified “living alone” and “[having] experienced economic disadvantage” as risk factors for university students' negative emotional states during the pandemic. In our study, we also found that students from non-intact families (e.g., a divorced-parents family or a single-parent family) reported higher levels of depression, anxiety, and stress than their peers living in intact families did. In the face of the enduring pandemic, promoting the well-being of the general youth population should be given an especially high priority in terms of policy, research, and services, with special attention and extra resources provided to young people in disadvantaged situations, such as those with economic difficulties and insufficient family support, because they are more severely and disproportionately affected by the pandemic.

Adolescents' online social networking behaviors and their problematic use of SNSs have drawn considerable research attention in the past few years (56). However, the relationships between the daily amount of time adolescents spend on SNSs and their well-being during the pandemic have been inconclusive. Using a representative sample of Hong Kong secondary school students, the present study provides meaningful theoretical and practical implications by differentiating the associations between different dosages of SNS use and adolescents' well-being, and by verifying the negative relationship between youths' social networking addiction and their mental health as well as their health-related quality of life, especially under the influence of the pandemic. In terms of theory, the present findings provide insights into the positive side of SNSs use by youths and their improved well-being, and thus contribute to the current literature, which has mainly highlighted the negative effects of SNSs usage on young people's mental health (7981). Especially under the particular circumstances of the COVID-19 pandemic, appropriate use of SNSs can help young people to maintain their mental health through fulfilling their need to be socially connected and their desire to follow pandemic-related updates (82). Our findings also add to the existing knowledge by identifying an ideal range for the daily amount of time (from somewhat <1–3 h) that an adolescent can spend on SNSs without causing evident adverse effects on their well-being.

In practical terms, our findings corroborate prior findings suggesting that both excessive use of SNSs (more than 3 h per day), and SNA, are likely to jeopardize youths' mental health and well-being, and that the pandemic has disproportionately affected youths that are in disadvantaged situations (e.g., non-intact families). First, while SNSs have increasingly become a necessary and important part of young people's lives, there is a critical need to develop evidence-based effective strategies to help adolescents harness their use of SNSs to the benefit of their well-being. Second, policy makers at different levels and also school teachers need to pay extra attention to disadvantaged families and their children, in an effort to tackle the unique challenges faced by this population. Third, recommendations on the amount of daily time devoted to using SNSs should be made and incorporated into the existing guidelines for youths' healthy use of the Internet.

In interpreting the findings of the present study, several limitations should be considered. First, the data were collected from self-reported questionnaires, which makes the results likely to have been affected by responses with social desirability bias. However, the anonymous nature of the survey, the non-presence of classroom teachers in the questionnaire administration process, and the reassurance of the data confidentiality potentially reduced the social desirability bias. Still, it would be ideal to also collect data from parents, teachers, or other informants on the amount of time that adolescents really spend on SNSs daily, and on their school, social, and physical functioning. New technology that simply records the exact amount of time that a person uses SNSs per day could be further incorporated into such studies in the future. Second, this study's cross-sectional data cannot rule out the possibility of reverse or recursively causal relationships, so longitudinal data are warranted. Third, we asked the respondents to report only their time spent on SNSs, and did not inquire how they used the SNSs, nor did we ask the purposes of the usage, all of which could play an equal, if not more important, role in clarifying the relationships between SNSs use and youths' well-being. In future studies we must include measures of adolescents' different types of SNSs use, to enhance our understanding of the mechanisms underlying these relationships. Despite these limitations, however, the present study contributes to our understanding of the relationships between Hong Kong adolescents' SNSs usage and their mental health status and health-related quality of life, and also the relationships between their SNSs usage and their well-being during the unique context of the COVID-19 pandemic.

Conclusion

Based on a representative sample of Hong Kong secondary school students, the present study examined Hong Kong adolescents' use of social networking sites (SNSs), social networking addiction (SNA), mental health, and health-related quality of life status as well as their relationships during the pandemic. Frequent use of SNSs was common among Hong Kong adolescents but the prevalence rate of SNA was not increased; students' mental health status and their health-related quality of life were at a low level. We found that using SNSs for 3 h per day or somewhat less can have beneficial effects on adolescents' mental health, while excessive and problematic use of the SNSs can undermine rather than promote adolescents' well-being even during the pandemic. The findings of the present study can guide the efficient mental health promotion strategy for adolescents under the influence of the pandemic and provide recommendations for youths' healthy use of the Internet.

Data availability statement

The raw data supporting the conclusions of this article will be made available by the authors, without undue reservation.

Ethics statement

The project was approved by the Human Subjects Ethics Sub-Committee (HSESC) of The Hong Kong Polytechnic University (Reference No.: HSEARS20180326015). Written informed consent to participate in this study was provided by the participants' legal guardian/next of kin.

Author contributions

LY conceptualized and designed the study, collected the data, interpreted the data, drafted the manuscript, and approved the final manuscript as submitted. MD collected the data, interpreted the data, drafted the manuscript, and approved the final manuscript as submitted. All authors contributed to the article and approved the submitted version.

Funding

The work described in this manuscript was fully supported by a grant from the Research Grants Council of the Hong Kong Special Administrative Region, China (Project No. PolyU 15604618). The preparation and publication of the work was funded by the Departmental Large Project Funding Scheme, Department of Applied Social Science, The Hong Kong Polytechnic University (Project No. P0041161).

Conflict of interest

The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.

Publisher's note

All claims expressed in this article are solely those of the authors and do not necessarily represent those of their affiliated organizations, or those of the publisher, the editors and the reviewers. Any product that may be evaluated in this article, or claim that may be made by its manufacturer, is not guaranteed or endorsed by the publisher.

References

1. Word Health Organization. Coronavirus Disease (COVID-19) Pandemic. (2022). Available online at: https://www.who.int/emergencies/diseases/novel-coronavirus-2019 (accessed August 25, 2022).

Google Scholar

2. Kapasia N, Paul P, Roy A, Saha J, Zaveri A, Mallick R, et al. Impact of lockdown on learning status of undergraduate and postgraduate students during COVID-19 pandemic in West Bengal, India. Child Youth Serv Rev. (2020) 116:105194. doi: 10.1016/j.childyouth.2020.105194

PubMed Abstract | CrossRef Full Text | Google Scholar

3. Meherali S, Punjani N, Louie-Poon S, Abdul Rahim K, Das JK, Salam RA, et al. Mental health of children and adolescents amidst COVID-19 and past pandemics: a rapid systematic review. Int J Environ Res Public Health. (2021)18:3432. doi: 10.3390/ijerph18073432

PubMed Abstract | CrossRef Full Text | Google Scholar

4. Gonzalez T, De La Rubia MA, Hincz KP, Comas-Lopez M, Subirats L, Fort S, et al. Influence of COVID-19 confinement on students' performance in higher education. PLoS ONE. (2020) 15:e0239490. doi: 10.1371/journal.pone.0239490

PubMed Abstract | CrossRef Full Text | Google Scholar

5. Mottaleb KA, Mainuddin M, Sonobe T. COVID-19 induced economic loss and ensuring food security for vulnerable groups: policy implications from Bangladesh. PLoS ONE. (2020) 15:e0240709. doi: 10.1371/journal.pone.0240709

PubMed Abstract | CrossRef Full Text | Google Scholar

6. Strielkowski W. COVID-19 pandemic and the digital revolution in academia and higher education. Preprints. (2020) 1:1–6. doi: 10.20944/preprints202004.0290.v1

CrossRef Full Text | Google Scholar

7. Organisation for Economic Co-operation and Development. Supporting Young People's Mental Health Through the COVID-19 Crisis. (2021). Available online at: https://www.oecd.org/coronavirus/policy-responses/supporting-young-people-s-mental-health-through-the-covid-19-crisis-84e143e5/ (accessed August 25, 2022).

Google Scholar

8. Statista. Average Daily Time Spent on Social Networks by Users in the United States from 2018 to 2022. (2022). Available online at: https://www.statista.com/statistics/1018324/us-users-daily-social-media-minutes/ (accessed August 25, 2022).

9. Burhan FA. Penggunaan WhatsApp dan Instagram Melonjak 40% Selama Pandemi Corona. (2020). Available online at: https://katadata.co.id/berita/2020/03/27/penggunaan-whatsapp-dan-instagram-melonjak-40-selama-pandemi-corona (accessed August 25, 2022).

Google Scholar

10. Cauberghe V, Van Wesenbeeck I, De Jans S, Hudders L, Ponnet K. How adolescents use social media to cope with feelings of loneliness and anxiety during COVID-19 lockdown. Cyberpsychol Behav Soc Netw. (2021) 24:250–7. doi: 10.1089/cyber.2020.0478

PubMed Abstract | CrossRef Full Text | Google Scholar

11. Hamilton, JL, Nesi, J, Choukas-Bradley, S. Teens and social media during the COVID-19 pandemic: staying socially connected while physically distant. PsyArXiy. (2020) 1–35. doi: 10.31234/osf.io/5stx4

CrossRef Full Text | Google Scholar

12. Tolette A. How coronavirus has shifted the way the world works. Available online at: https://www.synthesio.com/blog/how-coronavirus-has-shifted-the-way-the-world-works/ (accessed August 25, 2022).

13. Andreassen CS. Online social network site addiction: a comprehensive review. Curr Addict Rep. (2015) 2:175–84. doi: 10.1007/s40429-015-0056-9

CrossRef Full Text | Google Scholar

14. Hudimova A. Adolescents' involvement in social media: before and during COVID-19 pandemic. Int J Innov Technol Manag. (2021) 1:1–11. doi: 10.31435/rsglobal_ijitss/30032021/7370

PubMed Abstract | CrossRef Full Text | Google Scholar

15. Chen IH, Chen CY, Pakpour AH, Griffiths MD, Lin CY, Li XD, et al. Problematic internet-related behaviors mediate the associations between levels of internet engagement and distress among schoolchildren during COVID-19 lockdown: A longitudinal structural equation modeling study. J Behav Addict (2021) 10:135-48. doi: 10.1556/2006.2021.00006

PubMed Abstract | CrossRef Full Text | Google Scholar

16. Yu L, Luo T. Social networking addiction among Hong Kong university students: Its health consequences and relationships with parenting behaviors with parenting behaviors. Front Public Health. (2021) 8:555990. doi: 10.3389/fpubh.2020.555990

PubMed Abstract | CrossRef Full Text | Google Scholar

17. Yu L, Shek DTL. Positive youth development attributes and parenting as protective factors against adolescent social networking addiction in Hong Kong. Front Pediatr. (2021) 9:649232. doi: 10.3389/fped.2021.649232

PubMed Abstract | CrossRef Full Text | Google Scholar

18. Zhu SM, Zhuang YQ, Lee P, Li JCM, Wong PWC. Leisure and problem gaming behaviors among children and adolescents during school closures caused by COVID-19 in Hong Kong: quantitative cross-sectional survey study. JMIR Serious Games. (2021) 9:e26808. doi: 10.2196/26808

PubMed Abstract | CrossRef Full Text | Google Scholar

19. Pantic I, Damjanovic A, Todorovic J, Topalovic D, Bojovic-Jovic D, Ristic S, et al. Association between Online social Networking and Depression in High School Students: Behavioral Physiology Viewpoint. Available online at: https://tinyurl.com/9ubev3np (accessed August 25, 2022).

PubMed Abstract | Google Scholar

20. Sampasa-Kanyinga H, Lewis RF. Frequent use of social networking sites is associated with poor psychological functioning among children and adolescents. Cyberpsych Beh Soc N. (2015) 18:380–5. doi: 10.1089/cyber.2015.0055

PubMed Abstract | CrossRef Full Text | Google Scholar

21. Berger M. Social media use increases depression and loneliness. Penn Today. (2018). Available online at https://penntoday.upenn.edu/news/social-media-use-increases-depression-and-loneliness (accessed August 25, 2022).

Google Scholar

22. Savci M, Aysan F. Relationship between impulsivity, social media usage and loneliness. Educ Process Int J. (2016) 5:106–15. doi: 10.12973/edupij.2016.52.2

CrossRef Full Text | Google Scholar

23. Zhou SX, Leung L. Gratification, loneliness, leisure boredom, and self-esteem as predictors of SNS-game addiction and usage pattern among Chinese college students. Int J Cyber Behav Psychol Learn. (2012) 2:34–48. doi: 10.4018/ijcbpl.2012100103

CrossRef Full Text | Google Scholar

24. Davila J, Hershenberg R, Feinstein BA, Gorman K, Bhatia V, Starr LR. Frequency and quality of social networking among young adults: associations with depressive symptoms, rumination, and corumination. Psychol Pop Media Cult. (2012) 1:72. doi: 10.1037/a0027512

PubMed Abstract | CrossRef Full Text | Google Scholar

25. Feinstein BA, Bhatia V, Hershenberg R, Davila J. Another venue for problematic interpersonal behavior: the effects of depressive and anxious symptoms on social networking experiences. J Soc Clin Psychol. (2012) 31:356–82. doi: 10.1521/jscp.2012.31.4.356

CrossRef Full Text | Google Scholar

26. Dalton L, Rapa E, Stein A. Protecting the psychological health of children through effective communication about COVID-19. Lancet Child Adolesc Health. (2020) 4:346–7. doi: 10.1016/S2352-4642(20)30097-3

PubMed Abstract | CrossRef Full Text | Google Scholar

27. Fumagalli E, Dolmatzian MB, Shrum LJ. Centennials, FOMO, and loneliness: an investigation of the impact of social networking and messaging/VoIP apps usage during the initial stage of the coronavirus pandemic. Front Psychol. (2021) 12:620739. doi: 10.3389/fpsyg.2021.620739

PubMed Abstract | CrossRef Full Text | Google Scholar

28. Kim J, Lee JE. The Facebook paths to happiness: effects of the number of Facebook friends and self-presentation on subjective well-being. Cyberpsychol Behav Soc Netw. (2011) 14:359–64. doi: 10.1089/cyber.2010.0374

PubMed Abstract | CrossRef Full Text | Google Scholar

29. Abbas J, Wang D, Su Z, Ziapour A. The role of social media in the advent of COVID-19 pandemic: crisis management, mental health challenges and implications. Risk Manag Healthc Policy. (2021) 14:1917–32. doi: 10.2147/RMHP.S284313

PubMed Abstract | CrossRef Full Text | Google Scholar

30. Ravens-Sieberer U, Kaman A, Erhart M, Otto C, Devine J, Loffler C, et al. Quality of life and mental health in children and adolescents during the first year of the COVID-19 pandemic: results of a two-wave nationwide population-based study. Eur Child Adolesc Psychiatry. (2021) 1–4. doi: 10.1007/s00787-021-01889-1

PubMed Abstract | CrossRef Full Text | Google Scholar

31. Tang F, Liang J, Zhang H, Kelifa MM, He Q, Wang P. COVID-19 related depression and anxiety among quarantined respondents. Psychol Health. (2021) 36:164–78. doi: 10.1080/08870446.2020.1782410

PubMed Abstract | CrossRef Full Text | Google Scholar

32. Zhou SJ, Zhang LG, Wang LL, Guo ZC, Wang JQ, Chen JC, et al. Prevalence and socio-demographic correlates of psychological health problems in Chinese adolescents during the outbreak of COVID-19. Eur Child Adolesc Psychiatry. (2020) 29:749–58. doi: 10.1007/s00787-020-01541-4

PubMed Abstract | CrossRef Full Text | Google Scholar

33. Guo Q, Zheng YC, Shi J, Wang JJ, Li GJ, Li CB, et al. Immediate psychological distress in quarantined patients with COVID-19 and its association with peripheral inflammation: a mixed-method study. Brain Behav Immun. (2020) 88:17–27. doi: 10.1016/j.bbi.2020.05.038

PubMed Abstract | CrossRef Full Text | Google Scholar

34. World Population Review. Hong Kong Population 2022. (2022). Available online at: https://worldpopulationreview.com/countries/hong-kong-population (accessed August 25, 2022).

35. Chan SM, Wong H, Chung RYN, Au-Yeung TC. Association of living density with anxiety and stress: a cross-sectional population study in Hong Kong. Health Soc Care Community. (2021) 29:1019–29. doi: 10.1111/hsc.13136

PubMed Abstract | CrossRef Full Text | Google Scholar

36. Sharma A, Madaan V, Petty FD. Exercise for mental health. Prim care companion. J Clin Psychiatry. (2006) 8:106. doi: 10.4088/PCC.v08n0208a

PubMed Abstract | CrossRef Full Text | Google Scholar

37. Chu CM, Cheng VC, Hung IF, Chan KS, Tang BS, Tsang TH, et al. Viral load distribution in SARS outbreak. Emerg Infect Dis. (2005)11:1882–6. doi: 10.3201/eid1112.040949

PubMed Abstract | CrossRef Full Text | Google Scholar

38. Wright LJ, Williams SE, Veldhuijzen van Zanten JJCS. Physical activity protects against the negative impact of coronavirus fear on adolescent mental health and well-being during the COVID-19 pandemic. Front Psychol. (2021) 12:580511. doi: 10.3389/fpsyg.2021.580511

PubMed Abstract | CrossRef Full Text | Google Scholar

39. Prime H, Wade M, Browne DT. Risk and resilience in family well-being during the COVID-19 pandemic. Am Psychol. (2020) 75:631–43. doi: 10.1037/amp0000660

PubMed Abstract | CrossRef Full Text | Google Scholar

40. Chung RYN, Chung GKK, Chan SM, Chan YH, Wong H, Yeoh EK, et al. Socioeconomic inequality in mental well-being associated with COVID-19 containment measures in a low-incidence Asian globalized city. Sci Rep. (2021) 11:23161. doi: 10.1038/s41598-021-02342-8

PubMed Abstract | CrossRef Full Text | Google Scholar

41. Leung CH, Mu Y. Spiritual and mental health of teenagers in Hong Kong and in mainland China under the impact of COVID-19. Asian Educ Dev Stud. (2022) 11:340–55. doi: 10.1108/AEDS-04-2021-0076

CrossRef Full Text | Google Scholar

42. Pong HK. The relationship between the spiritual well-being of university students in Hong Kong and their academic performance. Int J Child Spiritual. (2017) 22:329–51. doi: 10.1080/1364436X.2017.1382453

CrossRef Full Text | Google Scholar

43. Shek DTL. COVID-19 and quality of life: twelve reflections. Appl Res Qual Life. (2021) 16:1–11. doi: 10.1007/s11482-020-09898-z

PubMed Abstract | CrossRef Full Text | Google Scholar

44. Zhu S, Zhuang Y, Lee P, Wong PWC. The changes of suicidal ideation status among young people in Hong Kong during COVID-19: a longitudinal survey. J Affect Disord. (2021) 294:151–8. doi: 10.1016/j.jad.2021.07.042

PubMed Abstract | CrossRef Full Text | Google Scholar

45. Shek, DTL, Yu L. Internet addiction in Hong Kong adolescents: profiles and psychosocial correlates. Int J Disabil Hum. (2012) 11:133–42. doi: 10.1515/ijdhd-2012-0023

PubMed Abstract | CrossRef Full Text | Google Scholar

46. Shek DTL, Yu L. Internet addiction phenomenon in early adolescents in Hong Kong. Sci World J. (2012) 2012:104304. doi: 10.1100/2012/104304

PubMed Abstract | CrossRef Full Text | Google Scholar

47. Andreassen CS, Billieux J, Griffiths MD, Kuss DJ, Demetrovics Z, Mazzoni E, et al. The relationship between addictive use of social media and video games and symptoms of psychiatric disorders: a large-scale cross-sectional study. Psychol Addict Behav. (2016) 30:252–62. doi: 10.1037/adb0000160

PubMed Abstract | CrossRef Full Text | Google Scholar

48. Lin CY, Broström A, Nilsen P, Griffiths MD, Pakpour AH. Psychometric validation of the Persian Bergen social media addiction scale using classic test theory and Rasch models. J Behav Addict. (2017) 6:620–29. doi: 10.1556/2006.6.2017.071

PubMed Abstract | CrossRef Full Text | Google Scholar

49. Griffiths M. A ‘components' model of addiction within a biopsychosocial framework. J Subst Use. (2005) 10:191–7. doi: 10.1080/14659890500114359

CrossRef Full Text | Google Scholar

50. Banyai F, Zsila A, Kiraly O, Maraz A, Elekes Z, Griffiths MD, et al. Problematic social media use: results from a large-scale nationally representative adolescent sample. PLoS ONE. (2017) 12:e0169839 doi: 10.1371/journal.pone.0169839

PubMed Abstract | CrossRef Full Text | Google Scholar

51. Henry JD, Crawford JR. The short-form version of the Depression Anxiety Stress Scales (DASS-21): construct validity and normative data in a large non-clinical sample. Brit J Clin Psychol. (2005) 44:227–39. doi: 10.1348/014466505X29657

PubMed Abstract | CrossRef Full Text | Google Scholar

52. Varni JW, Seid M, Kurtin PS. PedsQL™ 4.0: Reliability and validity of the pediatric quality of life inventoryVersion 4.0 generic core scales in healthy and patient populations. Available online at: https://www.jstor.org/stable/pdf/3767969. (accessed August 25, 2022).

53. Lin CY, Luh WM, Yang AL, Su CT, Wang JD, Ma HI. Psychometric properties and gender invariance of the Chinese version of the self-report pediatric quality of life inventory version 4.0: short form is acceptable. Qual Life Res. (2012) 21:177–82. doi: 10.1007/s11136-011-9928-1

PubMed Abstract | CrossRef Full Text | Google Scholar

54. Hao Y, Tian Q, Lu Y, Chai Y, Rao S. Psychometric properties of the Chinese version of the pediatric quality of life inventory™ 4.0 generic core scales. Qual Life Res. (2010) 19:1229–33. doi: 10.1007/s11136-010-9672-y

PubMed Abstract | CrossRef Full Text | Google Scholar

55. Hong Kong Playground Association. Study on Life Situation Mental Well-being of Youth in Hong Kong. (2018). Available online at: https://tinyurl.com/5n8ycckw (accessed August 25, 2022).

Google Scholar

56. Cheng C, Lau YC, Chan L, Luk JW. Prevalence of social media addiction across 32 nations: meta-analysis with subgroup analysis of classification schemes and cultural values. Addict Behav. (2021) 117:106845. doi: 10.1016/j.addbeh.2021.106845

PubMed Abstract | CrossRef Full Text | Google Scholar

57. Lee Y, Jeon YJ, Kang S, Shin JI, Jung YC, Jung SJ. Social media use and mental health during the COVID-19 pandemic in young adults: a meta-analysis of 14 cross-sectional studies. BMC Public Health. (2022) 22:995. doi: 10.1186/s12889-022-13409-0

PubMed Abstract | CrossRef Full Text | Google Scholar

58. Shensa A, Escobar-Viera CG, Sidani JE, Bowman ND, Marshal MP, Primack BA. Problematic social media use and depressive symptoms among US young adults: a nationally-representative study. Soc Sci Med. (2017) 182:150–7. doi: 10.1016/j.socscimed.2017.03.061

PubMed Abstract | CrossRef Full Text | Google Scholar

59. Hussain Z, Griffiths MD. Problematic social networking site use and comorbid psychiatric disorders: a systematic review of recent large-scale studies. Front Psychiatry. (2018) 9:686. doi: 10.3389/fpsyt.2018.00686

PubMed Abstract | CrossRef Full Text | Google Scholar

60. Amin KP, Griffiths MD, Dsouza DD. Online gaming during the COVID-19 pandemic in India: strategies for work-life balance. Int J Ment Health Addiction. (2022) 20:296–302. doi: 10.1007/s11469-020-00358-1

PubMed Abstract | CrossRef Full Text | Google Scholar

61. Andreassen CS, Torsheim T, Pallesen S. Predictors of use of social network sites at work - a specific type of cyberloafing. J Comput Mediat Commun. (2014) 19:906–21. doi: 10.1111/jcc4.12085

CrossRef Full Text | Google Scholar

62. Pelling, EL, White KM. The theory of planned behavior applied to young people's use of social networking web sites. Cyberpsychol Behav. (2009) 12:755–9. doi: 10.1089/cpb.2009.0109

PubMed Abstract | CrossRef Full Text | Google Scholar

63. Rashid UK, Ahmed O, Hossain MA. Relationship between need for belongingness and Facebook addiction: mediating role of number of friends on Facebook. Int J Soc Sci Stud. (2019) 7:36. doi: 10.11114/ijsss.v7i2.4017

CrossRef Full Text | Google Scholar

64. Seabrook EM, Kern ML, Rickard NS. Social networking sites, depression, and anxiety: a systematic review. JMIR Ment Health. (2016) 3:e50. doi: 10.2196/mental.5842

PubMed Abstract | CrossRef Full Text | Google Scholar

65. Worsley JD, McIntyre JC, Bentall RP, Corcoran R. Childhood maltreatment and problematic social media use: the role of attachment and depression. Psychiatry Res. (2018) 267:88–93. doi: 10.1016/j.psychres.2018.05.023

PubMed Abstract | CrossRef Full Text | Google Scholar

66. Shek DTL, Dou D, Zhu X, Wong T, Tan L. Need satisfaction and depressive symptoms among university students in Hong Kong during the COVID-19 pandemic: moderating effects of positive youth development attributes. Front Psychiatry. (2022) 13:931404. doi: 10.3389/fpsyt.2022.931404

PubMed Abstract | CrossRef Full Text | Google Scholar

67. Yu L, Zhou X. Emotional competence as a mediator of the relationship between internet addiction and negative emotion in young adolescents in Hong Kong. Appl Res Qual Life. (2021) 16:2419–38. doi: 10.1007/s11482-021-09912-y

CrossRef Full Text | Google Scholar

68. Jiang HB, Liang HY, Zhou HL, Zhang B. Relationships among normative beliefs about aggression, moral disengagement, self-control and bullying in adolescents: a moderated mediation model. Psychol Res Behav Manag. (2022) 15:183–92. doi: 10.2147/PRBM.S346658

PubMed Abstract | CrossRef Full Text | Google Scholar

69. Glaser P, Liu JH, Hakim MA, Vilar R, Zhang R. Is Social Media Use for Networking Positive or Negative? Offline Social Capital and Internet Addiction as Mediators for the Relationship Between Social Media Use and Mental Health. Available online at: https://www.psychology.org.nz/journal-archive/NZJP-Vol-47-No-3-November-2018.pdf#page=12 (accessed August 25, 2022).

Google Scholar

70. Chi X, Liu X, Guo T, Wu M, Chen X. Internet addiction and depression in Chinese adolescents: a moderated mediation model. Front Psychiatry. (2019) 10:816. doi: 10.3389/fpsyt.2019.00816

PubMed Abstract | CrossRef Full Text | Google Scholar

71. Ji Y, Chen SY, Li K, Xiao N, Yang X, Zheng S, et al. Measuring health-related quality of life in children with cancer living in mainland China: feasibility, reliability and validity of the Chinese mandarin version of PedsQL 4.0 Generic Core Scales and 3.0 Cancer Module. Health Qual Life Outcomes. (2011) 9:1–13. doi: 10.1186/1477-7525-9-103

PubMed Abstract | CrossRef Full Text | Google Scholar

72. Limperg PF, Haverman L, van Oers HA, van Rossum MAJ, Maurice-Stam H, Grootenhuis MA. Health related quality of life in Dutch young adults: psychometric properties of the PedsQL generic core scales young adult version. Health Qual Life Outcomes. (2014) 12:1–10. doi: 10.1186/1477-7525-12-9

PubMed Abstract | CrossRef Full Text | Google Scholar

73. Barendse MEA, Flannery J, Cavanagh C, Aristizabal M, Becker SP, Berger E, et al. Longitudinal change in adolescent depression and anxiety symptoms from before to during the COVID-19 pandemic. J Res Adolesc. (2022). doi: 10.1111/jora.12781. [Epub ahead of print].

PubMed Abstract | CrossRef Full Text | Google Scholar

74. Ferreira LN, Pereira LN, Bras MD, Ilchuk K. Quality of life under the COVID-19 quarantine. Qual Life Res. (2021) 30:1389–405. doi: 10.1007/s11136-020-02724-x

PubMed Abstract | CrossRef Full Text | Google Scholar

75. Shah K, Mann S, Singh R, Bangar R, Kulkarni R. Impact of COVID-19 on the mental health of children and adolescents. Cureus. (2020) 12:e10051. doi: 10.7759/cureus.10051

PubMed Abstract | CrossRef Full Text | Google Scholar

76. Zhang L, Zhang DD, Fang J, Wan YH, Tao FB, Sun Y. Assessment of mental health of Chinese primary school students before and after school closing and opening during the COVID-19 pandemic. JAMA Netw Open. (2020) 3:e2021482. doi: 10.1001/jamanetworkopen.2020.21482

PubMed Abstract | CrossRef Full Text | Google Scholar

77. Zhu S, Zhuang Y, Ip P. Impacts on children and adolescents' lifestyle, social support and their association with negative impacts of the COVID-19 pandemic. Int J Env Res Pub He. (2021) 18:4780. doi: 10.3390/ijerph18094780

PubMed Abstract | CrossRef Full Text | Google Scholar

78. Shek DTL, Dou D, Zhu X. Prevalence and correlates of mental health of university students in Hong Kong: what happened one year after the occurrence of COVID-19? Front Public Health. (2022) 10:857147. doi: 10.3389/fpubh.2022.857147

PubMed Abstract | CrossRef Full Text | Google Scholar

79. Frost RL, Rickwood DJ. A systematic review of the mental health outcomes associated with Facebook use. Comput Hum Behav. (2017) 76:576–600. doi: 10.1016/j.chb.2017.08.001

PubMed Abstract | CrossRef Full Text | Google Scholar

80. Islam MR, Jannath S, Moona AA, Akter S, Hossain MJ, Islam SMA. Association between the use of social networking sites and mental health of young generation in Bangladesh: a cross-sectional study. J Community Psychol. (2021) 49:2276–97. doi: 10.1002/jcop.22675

PubMed Abstract | CrossRef Full Text | Google Scholar

81. Wang TX, Wong JYH, Wang MP, Li ACY, Kim SS, Lee JJ. Effects of Social Networking Service (SNS) addiction on mental health status in Chinese university students: structural equation modeling approach using a cross-sectional online survey. J Med Internet Res. (2021) 23:e26733. doi: 10.2196/26733

PubMed Abstract | CrossRef Full Text | Google Scholar

82. Karhu M, Suoheimo M, Häkkilä J. People's Perspectives on Social Media Use during COVID-19 Pandemic. In:Simeone AL, GJ, Ramakers R, Gena C, , editors. 20th International Conference on Mobile and Ubiquitous Multimedia. Leuven, Belgium. ACM (2021). p. 123–130.

Google Scholar

Keywords: online social networking, adolescent, mental health, quality of life, social networking addiction, pandemic

Citation: Yu L and Du M (2022) Social networking use, mental health, and quality of life of Hong Kong adolescents during the COVID-19 pandemic. Front. Public Health 10:1040169. doi: 10.3389/fpubh.2022.1040169

Received: 09 September 2022; Accepted: 10 October 2022;
Published: 31 October 2022.

Edited by:

Tingshao Zhu, Institute of Psychology (CAS), China

Reviewed by:

Enkeleint A. Mechili, University of Vlorë, Albania
Pei Boon Ooi, Sunway University, Malaysia

Copyright © 2022 Yu and Du. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.

*Correspondence: Lu Yu, lu.yu@polyu.edu.hk

Disclaimer: All claims expressed in this article are solely those of the authors and do not necessarily represent those of their affiliated organizations, or those of the publisher, the editors and the reviewers. Any product that may be evaluated in this article or claim that may be made by its manufacturer is not guaranteed or endorsed by the publisher.