Males are more likely to be when satisfying their need for social connectedness

Social Networking Use, Social Connectedness, and Happiness

Socialization, whether face-to-face or online, is an essential process in an individual’s everyday life. Social connectedness, defined as the subjective awareness of being close to the social world (Lee & Robbins, 1998), is what one feels when connecting and interacting with others. Many commonly perceive social connectedness as a basic psychological need, and belonging is a fundamental motivation of human to achieve a broad sense of well-being (Jose et al., 2012). With the increase in Internet technology, many factors now influence how one seeks a sense of connectedness during the digital era (Wu et al., 2016). Studies investigating SNS use have suggested that it can be associated with social connectedness through examining its components (Ryan et al., 2017). Social capital is the information, and emotional support people retrieve from their social network (Utz & Muscanell, 2015). With the height of technological advancements, social capital, the fundamental need to belong, and social connectedness significantly influence SNSs.

Previous research suggests that SNS use can be associated with emotional and psychological outcomes such as well-being and happiness. For instance, Castillo de Masa et al. (2020) observed that when young people have necessary digital skills obtained from using SNSs (such as Facebook), it improves their self-esteem, life satisfaction, and social well-being. Perceptions of social support, affection, and a sense of security increase when young people have such digital skills. However, opposite effects may also prevail, as in the study by Wheatly and Buglass (2019), who found that heavy use of social networking sites also has negative impacts such as reduced subjective well-being. The definition of happiness to be used in the present study is expressed based on the theoretical hedonic tradition, which emphasizes the balance between pleasure and pain. This definition posits that what is suitable for an individual is the balance between positive and negative affect, which emerges from experiences of fun, enjoyment, comfort, and satisfaction (Belzak et al., 2017). In a critical review by Verduyn et al. (2017), studies showed that SNSs could influence subjective well-being. However, the decision as to whether social networking usage leads to an increase or decrease in subjective happiness is highly dependent on how one uses them. Research shows that active self-presentation seems to increase subjective well-being or does not decrease its level (Vaate et al., 2020).

This study focuses on how the satisfaction of belonging through social networking use may be associated with one’s social connectedness and happiness. Guided by Baumeister and Leary’s (1995) belongingness hypothesis, social connection is viewed as an inherent need in human beings. This theory aims to demonstrate and suggest the broad applicability of the need to belong over a wide range of behaviors. The need to belong is a pervasive fundamental motivation for human beings and satisfying or disrupting this need greatly influences their cognition, emotion, and behavior. The belongingness hypothesis posits that human beings have an innate drive to form and maintain a minimum amount of non-negative and significant interpersonal relationships expected to last. To satisfy this need, the individual establishes a framework of mutual concern that extends into the past and future while maintaining a series of non-negative interactions (Baumeister, 2012, p.125).

Furthermore, there is also an expected increase in the perceived happiness upon continued use of SNSs. In Baumeister and Leary’s (1995) belongingness hypothesis, humans possess a set of internal mechanisms that guide them into social groups and long-term relationships. Some of these mechanisms are presumed to include a tendency for humans to orient themselves toward other species’ members and feel pleasure or positive affect from social interactions. Emotion seems to operate as a feedback system by making positive social contact reinforcing and social deprivation punishing (Baumeister & Leary, 1995; Baumeister, 2012, 132). Baumeister and Sommer’s commentary (1997) also emphasized how men and women are motivated to pursue belongingness in different spheres, translating into differences in social strategies and criteria. Indeed, differences were observed in the reactions of men and women in social interactions, depending on the context of the situation (Hyde, 2005). The social motivations of men are patterned to extend towards large groups and networks of shallow relationships, in contrast to women who emphasize the intimacy of close relationships (Baumeister, 2012, p.131).

Gender Differences in SNS Use

Besides age, substantial differences were found in using social networking sites across gender (Krasnova et al., 2017; Lin et al., 2017). A study on motivation indicated that men were more motivated to establish relationships, gain general information and play online games. At the same time, women were more motivated to maintain already established close relationships, gain social details, communicate with friends, and view others’ photos using social media platforms (Barker, 2009; Hogue & Mills, 2019; Krasnova et al., 2017; Muscanell & Guadagno, 2012). The difference in motivation patterns across gender can alter these motivations with indicators of psychological well-being in men and women. Guadagno et al.’s (2011) study also notes that people behave according to traditional gender role expectations; where women were reported engaging in more communal activities as compared to men who reported engaging in more agentic activities—suggesting that, even when men and women have the freedom to behave in any way they want, men and women still choose to act in a manner that is consistent with social role expectations. These role expectations may play a part in SNS engagement.

Generation Z

Generation Z, born from 1993 to 2005 (Turner, 2015), is often called “digital natives” because they never experienced life before the Internet. Technology has always been accessible to this generation (also called Generation I, Gen Tech, Gen Wii), so they have become accustomed to communicating in a connected world. No generation has demonstrated proficiency or comfort with technology at such an early age as Generation Z (Palley, 2012). This study involves Generation Z individuals as technology is part of their identity. Young adults spend increasing time using SNSs (Lin et al., 2016; Roisman et al., 2004). Kolhar et al. (2021) recently found that 97% of female undergraduates between 17 and 29 used social media applications. Most of them reported prolonged use of SNSs for not associated with their studies. Azizi et al. (2019) also pointed out that undergraduates use SNSs more extensively than other age groups of students.

SNS Use in the Philippines During the Pandemic

The 2019 novel coronavirus (COVID-19) has disrupted millions of lives across the globe since it was declared a pandemic last March 2020. In the Philippines, the COVID-19 lockdown has been deemed one of the world’s longest. Lockdown restrictions, public health protocols, and adjustments from face-to-face to work-from-home and online learning setups have been implemented for strict compliance. Recent studies report an increased mental health burden in the Philippines following the prolonged lockdown. About one in three Filipino adults can be potentially screened for moderate to severe anxiety (Mendoza & Dizon, 2021). This statement aligns with the findings of Giray et al. (2022), showing that Filipino college students report a general difficulty in adjusting towards online learning due to mental health, connectivity, and financial problems. Following these adjustments in lockdown protocols in the country, social media use has been expected to increase and become a crucial channel for communicating, keeping in touch with peers, and information dissemination regarding COVID-19.

The Aims of the Study

As social networking sites have slowly become an integral aspect of life for the new generation, this digitized world has provided more opportunities than ever to communicate and interact with one another. With this in mind, the study aims to investigate the following problems: (1) Are there significant relationships among social networking use, social connectedness, and happiness among Generation Z Filipinos across gender? And (2) can different social networking use predict Generation Z Filipinos’ perceived social connectedness and happiness?

Method

Design

The present study used a correlational research design to investigate the associations among social networking use, social connectedness, and happiness of Generation Z Filipinos during the COVID-19 pandemic. Social networking use was the independent variable, while social connectedness and happiness were the dependent variables in our study. Cronbach’s alphas above 0.6 were considered acceptable based on the generally accepted rule, and 0.8 or above were considered high (Hulin et al., 2001; Ursachi et al., 2015).

Participants

A total of 420 Gen Z Filipinos (132 male; 288 female), ages ranging from 18 to 27 years old (M = 20.7 years; SD = 1.6), comprised the study’s sample. The participants were individuals who belong to Generation Z (born between 1993 – 2002). According to Turner (2015), technology played a distinctive and centric role in Generation Z (Gen Z) individuals. Social networking sites such as Facebook had an undeniable impact on regulating their social life through online interactions such as messaging and sharing their personal lives. Participants must be Filipinos who reside in the Philippines at the time of data collection and must also be literate in English to understand the questionnaires and answer accurately. Once deemed qualified as participants for the study, we sent the online questionnaire link privately via instant messaging on SNSs, such as Facebook Messenger and Instagram. Online posts regarding the study were also posted on our social media to reach more potential participants. Data were collected online via a non-probability sampling method, specifically snowball sampling, to get a gross estimate of the results without incurring the cost or time required to select a random sample. Informed consent was obtained before online participation, which was voluntary without remuneration.

Measures

Social Networking Time Use Scale

The Social Networking Time Use Scale (SONTUS) is a standardized scale that measures time spent on social networking sites by considering the reasons for use and places or situations where it is used (Olufadi, 2016). The scale is a 29-item instrument, consisting of 5 subscales (relaxation and free periods, academic-related periods, public-place-related use, stress-related periods, motives for use), and answered using an 11-point Likert scale (1 = not applicable to me during the past week to 11 = I used it more than three times during the past week but spent more than 30 min each time). Exploratory factor analysis reveals that all five subscales are internally consistent, with a Cronbach’s alpha ranging from 0.83 to 0.91 (Olufadi, 2016). In the present study, the SONTUS subscales had the following reliability coefficients: relaxation and free periods (0.68), academic-related periods (0.69), public places-related us (0.61), stress-related periods (0.79), and motives for use (0.61). Items under motives for use included four items that ask about why people are likely to use SNSs. These items were “When you need to maintain contact with existing friends,” “When you need to communicate with your families and friends,” “When you need to find out more about people you met offline,” and “When you need to find people you haven’t seen in a while.” A Cronbach's alpha of 0.87 was found for the SONTUS global score.

Social Connectedness Scale-Revised

Lee and Robbins (1995) developed the Social Connectedness Scale to measure social connectedness as described by Kohut (1984); that people with low connectedness fail to develop appropriate interpersonal behaviors necessary to maintain relationships later in life. A series of studies validated the SCS as relatively distinct from proxy measures of connectedness such as social reassurance, social identity, loneliness, social support size, group membership, and social provisions (Lee & Robbins, 1995, 1998, 2000). In a 2001 study by the same authors, the SCS was revised to measure social connectedness, now defined as a psychological sense of belonging, specifically as cognition of enduring interpersonal closeness with the social world in toto (Lee et al., 2001). The SCS-R is a self-report questionnaire consisting of 20 items; 10 positive (e.g., “I am in tune with the world”) and ten negative items (e.g., “I feel disconnected from the world around me”) and uses a Likert scale for its response options (1 = strongly agree, 6 = strongly disagree) The SCS-R has internal item reliability with a coefficient alpha of 0.92 (Lee et al., 2001).In the current study, the Social Connectedness Scale-Revised has a Cronbach’s alpha reliability of 0.92.

Affectometer 2: A Scale to Measure Current Level of General Happiness

The Affectometer 2 is a scale designed to measure the current state of general happiness (Kammann & Flett, 1983). It is a 5-min inventory of general happiness or sense of well-being to measure the balance of positive and negative feelings in recent experiences. The scale consists of 40 self-report items, 20 positive items, and 20 negative items, each split into ten sentences and ten adjectives. The Affectometer 2 instructs examinees to report their feelings “over the past few weeks,” then asks how often the feeling was present on a graded response scale with the following choices: “not at all,” “occasionally,” “some of the time,” “often,” and “all of the time.” Well-being is also characterized into 10 “qualities of happiness,” specifically (1) confluence, (2) optimism, (3) self-esteem, (4) self-efficacy, (5) social support, (6) social interest, (7) freedom, (8) energy, (9) cheerfulness, and (10) thought clarity. The basic psychometric properties include a coefficient alpha of 0.95, with a median item correlation of 0.57; with the sentences and adjectives items representing two equivalent subscales, their alpha coefficients being 0.88 and 0.93, respectively. In the present study, alpha reliability of 0.76 is found for the total score of Affectometer 2.

Procedure

Online data gathering using the Google Forms platform occurred after receiving approval from the Ethics Review Committee of the University of Santo Tomas – College of Science. Likewise, permission was also sought from the original test authors if their tests could be administrated online. The online questionnaire included the Social Networking Time Use Scale (SONTUS) test battery, the Social Connectedness Scale-Revised, and the Affectometer 2, together with an informed consent and debriefing section. The order effect was controlled in the test administration by programming the order of presentation of the three scales in the test battery. The participants did not take the three scales in the same order. The online questionnaire was successfully administered to 508 Gen Z Filipinos from November to December 2020, but 88 participants were excluded due to incomplete responses and an apparent response set. Thus, final data from 420 Gen Z Filipinos composed of 132 males and 288 females ages 18–27-years-old were scored, interpreted, profiled, and were analyzed.

Statistical Analysis

Descriptive statistics were calculated using SPSS 21.0 (IBM SPSS Inc., Chicago, Illinois), while the multiple-sample path analysis was performed using Mplus 7.4 (Muthén & Muthén, 1998–2015). The robust maximum likelihood estimator (MLR) was used, robust to non-normal data distribution. A fully saturated model was performed; therefore, fit indices were set at χ2 = 0; df = 0, comparative fit index (CFI) = 1.00; Tucker-Lewis index (TLI) = 1.00; root-mean-square error of approximation (RMSEA) = 0.00 by default. All variables were defined as observed variables in the model. Independent (predictor) variables were the five SONTUS subscales (i.e., relaxation and free periods, academic-related periods, public places-related use, stress-related use, motives for use). In contrast, the two dependent variables (i.e., social connectedness and happiness) were entered simultaneously. Age was used as a control variable. Applying the generally accepted rule of thumb (i.e., 15–20 observations per predictor) (Siddiqui, 2013), we needed at least 90 participants for the models (6 predictors). One model was conducted using gender as a grouping variable. A schematic figure of the model is presented in Fig. 1.

Fig. 1

Schematic representation of the multivariate multiple-regression model in this study. The control variable is presented using a dashed box and arrows

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Results

Based on the mean scores calculated from the data gathered, the participants were within the average range for social networking use (M = 12.70, SD = 3.34) and happiness (M = 3.38, SD = 13.54). In addition, the mean scores for social connectedness indicated that the participants scored high on the social connectedness scale (M = 78.99, SD = 15. 89), reflecting a strong sense of connectedness.

When investigating the associations across gender, it was found that social networking use was not associated with either social connectedness or happiness among women (see Table 1 for details). Specifically, neither social connectedness nor happiness was significantly correlated to the Social Networking Time-Use Scale (SONTUS) components. However, two social networking use components (i.e., SONTUS stress-related use and SONTUS motives for use) showed a weak, negative association with happiness among men (r = 0.25, p < 0.01 for stress-related use; r = 0.26, p < 0.01 for motives for use). In addition, social connectedness and happiness were strongly associated among both men (r = 0.65, p < 0.001) and women (r = 0.69, p < 0.001).

Table 1 Partial correlations between study-variables among men (n = 132) and women (n = 288) while controlling for age

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To further explore possible gender differences, a multiple-sample path analysis was conducted. Results in Table 2 showed that social networking use during stress-related periods significantly predicted social connectedness (β =  − 0.19, p < 0.05) and happiness (β =  − 0.24, p < 0.01) in men after controlling for age. The negative coefficients entail that social connectedness and happiness decrease with the stress-related period component increase. Likewise, the fifth component of the social networking time use scale, which accounts for motives for use, was significantly associated with happiness in men (β =  − 0.27, p < 0.01). Due to the negative association between motives for use and happiness, an increase in social networking use based on motives for use is associated with decreased happiness in men. There were no associations between social networking use and social connectedness or happiness among women, although happiness was weakly associated with age. Age predicted happiness in both men (β = 0.22, p < 0.05) and women (β = 0.12, p < 0.05), indicating that levels of happiness slightly increase with age. The explanatory power of these variables was limited (5% for social connectedness and 13% for happiness in men, see Table 2).

Table 2 Multivariate multiple-regression analysis exploring the associations of social networking time use with social connectedness and happiness across gender

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Discussion

This study investigated social networking use and its association with social connectedness and happiness across gender. These findings suggest important implications for SNS use and its effects on the target population, Gen Z, during the COVID-19 pandemic. We explored the research problem through two research questions: (1) Are there significant relationships among SNS use, social connectedness, and happiness across gender? And (2) Can different ways of social networking use predict perceived social connectedness and happiness? Are there any gender differences?

Contrary to our first research question, data analysis revealed that social networking use seems to have no significant relationship with either social connectedness or happiness among women. Only two aspects (i.e., stress-related use and motives of use) were weakly associated with happiness in men. These unexpected results are not as uncommon as initially thought upon investigating previous research. Williams et al. (2000) found no relationship between belongingness and SNS use in a gaming context. They found that social networking use outcomes can vary systematically, affecting a user’s experience of belongingness within an online community. This diversity in attitudes Gen Z has towards SNSs, in terms of overall experience and reasons for use, may have resulted in the lack of a significant relationship among our study variables. Overall, person-specific effects seem to play an integral role when investigating variables related to SNS use (Beyens et al., 2020).

Aside from time spent on social media, another factor that may have significantly affected the results of this study is the social media environment and the societal context and significant events, which in this case, is the COVID-19 pandemic. Regardless of social media’s many benefits in a time wherein face-to-face communication has become limited in the Philippines. Social media remains a threat to its users because of its power to spread fake news, rumors, and misinformation from updates regarding the coronavirus and other relevant social issues (Chan et al., 2020). Social media also has an adverse emotional climate and toxicity during crisis times (Steinert, 2020). The pandemic may have consequently triggered a contrast or conflict in SNS user behavior—if users would either increase or decrease social media use to feel more connected or happy, depending on how they perceive social media to serve them.

The shift from in-person to purely online classes poses challenges for Generation Z college students. Universities in the Philippines, especially state-funded colleges, find the change difficult. It is a stark contrast to the traditional learning environment, coupled with its abrupt demand during the pandemic’s beginning (Giray et al., 2022). These problems include lack of access to reliable bandwidth, lack of pedagogical innovation, and the proclivity to replace traditional, teacher-led lectures—limiting independent learning among students (Giray et al., 2022). All of these factors can influence a student’s time spent on SNSs, as the modalities used for learning involve extensive use of social media. With that in mind, the study’s findings generally reveal those associations with SNS usage, which may stem from the accumulation of different within-person and external factors, greatly influence SNS use and the outcomes felt from it.

Regarding the study’s second research question, our findings revealed significant gender differences in how SNS use is associated with Gen Z users’ social connectedness and happiness. While controlling for age, the regression model showed that SNS use during stress-related periods significantly predicted social connectedness and happiness in males. This association was negative, implying that males’ social connectedness and happiness decrease with increased SNS use during stress-related periods.

These findings highlight how gender differences may play a critical role in explaining why people use the Internet through different pathways and outcomes (Tang & Koh, 2017). Specifically, gender was found to be associated with each element in the stress process as much in the input by determining whether a situation will be perceived as stressful, and as in the output, influencing coping responses and the health implications of stress reactions (Matud, 2004). Several studies have also found that men were less likely than women to seek social support (Ptacek et al., 1994). It is possible that men in our study used social media when they were stressed as a coping strategy, not for socialization, but for the platform’s other functions.

There is a limited opportunity to experience social connectedness as social capital is absent, which may explain the negative association of SNS use during stress-related periods with social connectedness for men.

Indeed, men’s happiness was found to decrease with an increase in SNS use during stress-related periods. Studies with similar results include Huang et al.’s (2020) findings that the emotions of men, which were extracted from SNS use, were found to be biased—reflecting that male SNS users in real life may not be as happy as they present themselves in an online context. Since it is culturally more common for men than women to mask their emotions, online feelings may not reflect their real feelings. With the changed atmosphere of SNSs during the COVID-19 pandemic, higher emotional investment in social media use has been associated with anxiety and depression (Alsunni & Latif, 2021), which may apply to the men of our study, as they may be less likely to seek support to alleviate negative feelings.

Our study also showed that Motives of Use (Component 5 of the SONTUS) was negatively associated with happiness for men. Highlighting Weinstein’s (2018) study, they explored participants’ affective expression across four functional dimensions of social media use and found that relational interactions are the most common positive defining affective experience. However, they have also mentioned feeling overwhelmed and anxious about the volume of content and perceived social obligations. The latter three dimensions: self-expression, exploration, and browsing, were all reported to have both advantages and disadvantages concerning well-being. Regardless of the motive, SNS users may find that dimensions of social media each have their strengths and weaknesses that can vary with subjective experiences.

Additionally, one possible explanation for the negative association of motives for use with happiness for men could be the gender differences in prosocial behaviors. (Paulin et al., 2014) contended that although both genders engage in prosocial behaviors, men and women appear to do so differently. Women’s behaviors are more communal and relational, whereas men’s behaviors are more agentic and self-assertive. Women may recognize the benefits of social media use for any motive more than men since they may see it as a more “relational” platform than men’s predisposition to view it as a “competitive” platform. As the findings of our study, male SNS users may have perceived the motives for social media use as unfavorable, which decreased their feelings of happiness.

With the study’s results in mind, participants frequently using social media could know how these technologies promote neither happiness nor connectedness. This awareness can lead to self-contemplation regarding their online practices and exploration of other modes or instruments that can be used to gain these feelings. Educational institutions would also benefit from these findings, especially in the Philippines. It may provide a better understanding of how the online class setup and online communication may not enhance students’ well-being. These findings may point out the importance that teachers and guidance counselors should remain observant of how the online setup is affecting their students and how using SNSs can impact their well-being and, eventually, their learning capabilities during the online setup. As of writing, the Department of Education (DepEd) and the Commission on Higher Education (CHED), the two government offices holding jurisdiction over national policies and welfare of the country’s educational system, have made guidelines for students and educational institutions to offer two learning online modalities. Namely, synchronous and asynchronous, the students can choose the most suitable model for their preferences (Giray et al., 2022).

Lastly, mental health professionals could better understand how their Gen Z patients struggle with anxiety and mood problems. Social media is one of the few available modes of communication, especially in areas with strict lockdown restrictions. Mental health professionals may devise and research more effective strategies for people at this age to cope with the lack of quality relationships in this “new normal.”

Other than SNS use, Gen Z SNS users may prefer offline means to attain better contentment with feelings of connectedness and happiness during the COVID-19 pandemic. Given the prevalence and importance of SNSs as the pandemic remains a barrier to face-to-face communication, studying how it affects individuals’ well-being and social connectedness has never been more critical.

Limitations and Future Directions

Caution in interpreting and generalizing the results is advised since the present study holds certain limitations. First, the present study was correlational research. Therefore, it would prove not easy to make causal inferences. Second, the study group was composed of Gen Z Filipinos, with most female college students, limiting the generalizability of the findings. For this reason, further research targeting other age groups or populations is recommended. Third, to date, no validated evidence of the scales (Social Networking Time Use Scale, the Social Connectedness Scale-Revised, Affectometer 2) used exists in the Philippines’ context. We assumed these scales to be valid for use in our study because these are standardized scales that have good psychometric properties. Moreover, the scales have acceptable reliability coefficients in our study despite the lack of validity evidence from the literature. However, we recommend that future studies test the validity of the scales in the Philippine context. Fourth, extraneous variables such as the living standards of the participants and the time of data collection may have influenced the participants’ responses since the last quarter of 2020. The Philippines was at the height of a crisis, with the pandemic and typhoons hitting vulnerable areas of the country. Fifth, our study did not require the participants to report the pleasant and unpleasant moods and emotions they felt specifically during SNS interactions. Hence, the type of affective interactions during SNS use may have contributed to its non-significant associations with other variables in this study.

Future studies may investigate these specific factors to understand SNS use and its associations with social connectedness. Lastly, previous studies have shown that the pandemic could have had a crucial effect on the use patterns of social networking sites and their associations with people’s feelings of social connectedness and happiness (Fernandes et al., 2020; Fox, 2020; Nabity-Grover et al., 2020). Investigating social networking use and its implications during stress-related periods could provide better insights and further exploration.

Availability of Data and Material

Not applicable.

Code Availability

Not applicable.

References

• Alsunni, A. A., & Latif, R. (2021). Higher emotional investment in social media is related to anxiety and depression in university students. Journal of Taibah University Medical Sciences, 16(2), 247–252. https://doi.org/10.1016/j.jtumed.2020.11.004

  Article  PubMed  Google Scholar 

• Azizi, S. M., Soroush, A., & Khatony, A. (2019). The relationship between social networking addiction and academic performance in Iranian students of medical sciences: A cross-sectional study. BMC Psychology, 7(1), 1–8. https://doi.org/10.1186/s40359-019-0305-0

  Article  Google Scholar 

• Barker, V. (2009). Older adolescents’ motivations for social network site use: The influence of gender, group identity, and collective self-esteem. Cyberpsychology & Behavior, 12(2), 209–213. https://doi.org/10.1089/cpb.2008.0228

• Baumeister, R. F. (2012). Need-to-belong theory. In P. A. M. Van Lange, A. W. Kruglanski, & E. T. Higgins (Eds.), Handbook of theories of social psychology (pp. 121–140). Sage Publications Ltd. https://doi.org/10.4135/9781446249222.n32

• Baumeister, R. F., & Leary, M. R. (1995). The need to belong: Desire for interpersonal attachments as a fundamental human motivation. Psychological Bulletin, 117(3), 497–529. https://doi.org/10.1037/0033-2909.117.3.497

• Baumeister, R. F., & Sommer, K. L. (1997). What do men want? Gender differences and two spheres of belongingness: Comment on Cross and Madson (1997). Psychological Bulletin, 122(1), 38–44. https://doi.org/10.1037/0033-2909.122.1.38

  Article  PubMed  Google Scholar 

• Belzak, W. C., Thrash, T. M., Sim, Y. Y., & Wadsworth, L. M. (2017). Beyond hedonic and eudaimonic well-being: Inspiration and the self-transcendence tradition. 117–138. https://doi.org/10.1007/978-3-319-58763-9_7

• Beyens, I., Pouwels, J.L., van Driel, I., Loes, K., & Valkenburg, P. (2020). The effect of social media on well-being differs from adolescent to adolescent. Scientific Reports, 10(10763). https://doi.org/10.1038/s41598-020-67727-7

• Boyd, D. M., & Ellison, N. B. (2007). Social network sites: Definition, history, and scholarship. Journal of Computer-Mediated Communication, 13(1), 210–230. https://doi.org/10.1111/j.1083-6101.2007.00393.x

  Article  Google Scholar 

• Castillo de Masa, J., Gomez-Jacinto, L., Pelaez, A. L., & Erro-Garces (2020). Social networking sites and youth transition: The use of Facebook and personal well-being of social work young graduates. Frontiers in Psychology, 11(230). https://doi.org/10.3389/fpsyg.2020.00230

• Chan, A. K. M., Nickson, C. P., Rudolph, J. W., Lee, A., & Joynt, G. M. (2020). Social media for rapid knowledge dissemination: Early experience from the COVID-19 pandemic. Anaesthesia, 75(12), 1579–1582. https://doi.org/10.1111/anae.15057

  Article  PubMed  PubMed Central  Google Scholar 

• Fernandes, B., Biswas, U. N., Tan-Mansukhani, R., Vallejo, A., & Essau, C. A. (2020). The impact of COVID-19 lockdown on internet use and escapism in adolescents. Revista De PsicologiaClinica Con Ninos Y Adolescentes, 7(3), 59–65. https://doi.org/10.21134/rpcna.2020.mon.2056

• Fox, L. (2020, April 15). COVID fears spawn social media shaming. The Alpena News. https://www.thealpenanews.com/news/local-news/2020/04/covid-fears-spawn-social-media-shaming/. Accessed 5 Feb 2021.

• Giray, L., Gumalin, D., Jacob, J., & Villacorta, K. (2022). Exploring the online learning experiences of Filipino college students during COVID-19 pandemic. Jurnal Ilmaih Peuradeun, 10(1), 227–250.

  Article  Google Scholar 

• Guadagno, R. E., Muscanell, N. L., Okdie, B. M., Burke, N. M., & Ward, T. B. (2011). Even in virtual environments women shop and men build: Gender differences in second life. Computers in Human Behavior, 27, 304–308. https://doi.org/10.1016/j.chb.2010.08.008

• Hogue, J. V., & Mills, J. S. (2019). The effects of active social media engagement with peers on body image in young women. Body Image, 28, 15.https://doi.org/10.1016/j.bodyim.2018.11.002

• Huang, Y., Li, J., Wu, G., & Fei, T. (2020). Quantifying the bias in place emotion extracted from photos on social networking sites: A case study on a university campus. Cities, 102, 102419. https://doi.org/10.1016/j.cities.2020.102719

  Article  Google Scholar 

• Hulin, C., Netemeyer, R., & Cudeck, R. (2001). Can a reliability coefficient be too high? Journal of Consumer Psychology, 10(1), 55–58.

  Article  Google Scholar 

• Hyde, J. S. (2005). The gender similarity hypothesis. American Psychologist, 60, 581–592. https://doi.org/10.1037/0003-066X.60.6.581

  Article  PubMed  Google Scholar 

• Jose, P., Ryan, N., & Pryor, J. (2012). Does social connectedness promote a greater sense of well-being in adolescence over time? Journal of Research on Adolescence, 22(2), 1–17. https://doi.org/10.1111/j.1532-7795.2012.00783.x

  Article  Google Scholar 

• Kamman, R., & Flett, R. (1983). Affectometer 2: A scale to measure current level of general happiness. Australian Journal of Psychology, 35(2), 259–265. https://doi.org/10.1080/00049538308255070

  Article  Google Scholar 

• Kohut, H. (1984). How does analysis cure? International Universities Press.

  Book  Google Scholar 

• Kolhar, M., Kazi, R. N. A., & Alameen, A. (2021). Effect of social media use on learning, social interactions, and sleep duration among university students. Saudi Journal of Biological Sciences, 28(4), 2216–2222. https://doi.org/10.1016/j.sjbs.2021.01.010

  Article  PubMed  PubMed Central  Google Scholar 

• Krasnova, H., Veltri, N. F., Eling, N., & Buxmann, P. (2017). Why men and women continue to use social networking sites: The role of gender differences. The Journal of Strategic Information Systems, 26(4), 261–284. https://doi.org/10.1016/j.jsis.2017.01.004

• Lee, R. M., & Robbins, S. B. (1995). Measuring belongingness: The social connectedness and the social assurance scales. Journal of Counseling Psychology, 42(2), 232–241.

  Article  Google Scholar 

• Lee, R. M., & Robbins, S. B. (1998). The relationship between social connectedness and anxiety, self-esteem, and social identity. Journal of Counseling Psychology, 45, 338–445.

  Article  Google Scholar 

• Lee, R. M., & Robbins, S. B. (2000). Understanding social connectedness in college women and men. Journal of Counseling and Development, 78, 484–491.

  Article  Google Scholar 

• Lee, R. M., Draper, M., & Lee, S. (2001). Social connectedness, dysfunctional interpersonal behaviors, and psychological distress: Testing a mediator model. Journal of Counseling Psychology, 48(3), 310–318. https://doi.org/10.1037//0022-0167.48.3.310

  Article  Google Scholar 

• Lin, L. Y., Sidani, J. E., Shensa, A., Radovic, A., Miller, E., Colditz, J. B., ... & Primack, B. A. (2016). Association between social media use and depression among US young adults. Depression and Anxiety, 33(4), 323–331. https://doi.org/10.1002/da.22466

• Lin, X., Featherman, M., & Sarker, S. (2017). Understanding factors affecting users’ social networking site continuance: A gender difference perspective. Information & Management, 54(3), 383–395. https://doi.org/10.1016/j.im.2016.09.004

• Matud, M. P. (2004). Gender differences in stress and coping styles. Personality and Individual Differences, 37(7), 1401–1415. https://doi.org/10.1016/j.paid.2004.01.010

• Mendoza, N. B., & Dizon, J. I. W. T. (2021). Prevalence of severe anxiety in the Philippines amid the COVID-19 outbreak. Journal of Loss and Trauma. https://doi.org/10.1080/15325024.2021.2023298

  Article  Google Scholar 

• Muscanell, N. L., & Guadagno, R. E. (2012). Make new friends or keep the old: Gender and personality differences in social networking use. Computers in Human Behavior, 28(1), 107–112. https://doi.org/10.1016/j.chb.2011.08.016

• Muthén, L., & Muthén, B. (1998–2015). Mplus user’s guide (8th ed.). Los Angeles, CA: Muthén & Muthén.

• Nabity-Grover, T., Cheung, C., & Thatcher, J. B. (2020). Inside out and outside in: How the COVID-19 pandemic affects self-disclosure on social media. International Journal of Information Management, 55, 102188. https://doi.org/10.1016/j.ijinfomgt.2020.102188

• Olufadi, Y. (2016). Social networking time use scale (SONTUS): A new instrument for measuring time spent on social networking sites. Telematics and Informatics, 33, 452–471. https://doi.org/10.1016/j.tele.2015.11.002

  Article  Google Scholar 

• Palley, W. (2012). Gen Z: Digital in their DNA. http://www.jwtintelligence.com/wpcontent/uploads/2012/04/F_INTERNAL_Gen_Z_0418122.pdf. Accessed 5 Feb 2021. 

• Paulin, M., Ferguson, R. J., Schattke, K., & Jost, N. (2014). Millennials, social media, prosocial emotions, and charitable causes: The paradox of gender differences. Journal of Nonprofit & Public Sector Marketing, 26(4), 335–353. https://doi.org/10.1080/10495142.2014.965069

• Ptacek, J. T., Smith, R. E., & Dodge, K. L. (1994). Gender differences in coping with stress: When stressor and appraisals do not differ. Personality and Social Psychology Bulletin, 20(4), 421–430. https://doi.org/10.1177/0146167294204009

  Article  Google Scholar 

• Roisman, G. I., Masten, A. S., Coatsworth, J. D., & Tellegen, A. (2004). Salient and emerging developmental tasks in the transition to adulthood. Child Development, 75(1), 123–133. https://doi.org/10.1111/j.1467-8624.2004.00658.x

  Article  PubMed  Google Scholar 

• Ryan, T., Allen, K., Gray, D. L., & Mclnerney, D. (2017). How social are social media? A review of online social behaviour and connectedness. Journal of Relationships Research, 8, 1–8. https://doi.org/10.1017/jrr.2017.13

  Article  Google Scholar 

• Siddiqui, K. (2013). Heuristics for sample size determination in multivariate statistical techniques. World Applied Sciences Journal, 27(2), 285–287. https://doi.org/10.5829/idosi.wasj.2013.27.02.889

  Article  Google Scholar 

• Steinert, S. (2020). Corona and value change. The role of social media and emotional contagion. Ethics and Information Technology. https://doi.org/10.1007/s10676-2020-09545-z

• Tang, C. S. K., & Koh, Y. Y. W. (2017). Online social networking addiction among college students in Singapore: Comorbidity with behavioral addiction and affective disorder. Asian Journal of Psychiatry, 25, 175–178. https://doi.org/10.1016/j.ajp.2016.10.027

• Turner, A. (2015). Generation Z: Technology and social interest. Individual Psychology, 71(2), 103–113. https://doi.org/10.1353/jip.2015.0021

  Article  Google Scholar 

• Ursachi, G., Horodnic, I. A., & Zait, A. (2015). How reliable are measurement scales? External factors with indirect influence on reliability estimators. Procedia Economics and Finance, 20, 679–686. https://doi.org/10.1016/S2212-5671(15)00123-9

  Article  Google Scholar 

• Utz, S., & Muscanell, N. (2015). Social media and social capital: Introduction to the special issue. Societies, 5, 420–424. https://doi.org/10.3390/soc502

  Article  Google Scholar 

• Vaate, N. A., Veldhuis, J., & Konijn, E. A. (2020). How online self-presentation affects well-being and body image: A systematic review. Telematics and Informatics, 47, 101316. https://doi.org/10.1016/j.tele.2019.101316

  Article  Google Scholar 

• Verduyn, P., Ybarra, O., Résibois, M., Jonides, J., & Kross, E. (2017). Do social network sites enhance or undermine subjective well-being? A critical review. Social Issues and Policy Review, 11(1), 274–302. https://doi.org/10.1111/sipr.12033

  Article  Google Scholar 

• Weinstein, E. (2018). The social media see-saw: Positive and negative influences on adolescents’ affective well-being. New Media & Society, 20(10), 3597-3623. https://doi.org/10.1177/1461444818755634

• Wheatly, D., & Buglass, S. L. (2019). Social network engagement and subjective well-being: A life-course perspective. British Journal of Sociology 2019, 0(0).

• Williams, K. D., Cheung, C. K., & Choi, W. (2000). Cyberostracism: Effects of being ignored over the Internet. Social Psychology, 79, 748–762. https://psycnet.apa.org/doi/10.1037/0022-3514.79.5.748. Accessed 5 feb 2021.

• Wu, Y.-J., Outley, C., Matarrita-Cascante, D., & Murphey, T. P. (2016). A systematic review of recent research on adolescent social connectedness and mental health with internet technology use. Adolescent Research Review, 1, 153–162.

  Article  Google Scholar 

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Funding

Ágnes Zsila was supported by the ÚNKP-21–4 New National Excellence Program of the Ministry for Innovation and Technology from the National Research, Development, and Innovation Fund source.

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Authors and Affiliations

1. Department of Psychology, College of Science, University of Santo Tomas, Manila, Philippines

   Marc Eric S. Reyes, Belen Corazon C. Morales, Gabriella E. Javier & Rachel Alysson E. Ng

2. Institute of Psychology, Pázmány Péter Catholic University, Budapest, Hungary

   Ágnes Zsila

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1. Marc Eric S. Reyes

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2. Belen Corazon C. Morales

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3. Gabriella E. Javier

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4. Rachel Alysson E. Ng

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5. Ágnes Zsila

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Correspondence to Marc Eric S. Reyes.

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Reyes, M.E.S., Morales, B.C.C., Javier, G.E. et al. Social Networking Use Across Gender: Its Association with Social Connectedness and Happiness Amidst the COVID-19 Pandemic. J. technol. behav. sci. 7, 396–405 (2022). https://doi.org/10.1007/s41347-022-00262-6

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