Internal and external factors influencing Gen Z wellbeing

Abstract

Background

Gen Z, the cohort of individuals born approximately between the mid-to-late 1990s and the early 2010s, has been noted to experience challenges regarding their wellbeing. Yet, addressing wellbeing issues among individuals in their productive years is crucial due to the significant impacts on innovation, productivity, and performance. Wellbeing is influenced by internal and external factors. One important external factor is technology. Concerns such as excessive screen time and the constant need for updated information, often referred to as the Fear of Missing Out (FoMO), have been associated with a decline in wellbeing. Nevertheless, comprehensive research examining the effects of screen time and FoMO on wellbeing remains limited. This study aims to explore both internal (such as FOMO, extraversion, and resilience) and external factors (such as social support and screen time) that contribute to the wellbeing of Gen Z individuals.

Methods

The research adopted a quantitative approach involving 408 participants, with Smart-PLS utilized for both the measurement model analysis and the structural model analysis.

Result

Findings from the study reveal how social support, as external factor, is positively influencing wellbeing and resilience. The study also shows that resilience plays a role in influencing wellbeing. Therefore, the total impact of social support to wellbeing is strong, directly and indirectly. This study also shows the positive impact of personal traits, specifically extraversion to wellbeing. However, this study fails to show the dark side of technology impacted wellbeing.

Conclusion

The study expands knowledge on the direct positive relationship between social support, resilience, and well-being, revealing that social support significantly affects well-being both directly and indirectly through resilience. Additionally, it confirms that well-being is influenced by internal factors, such as resilience and extraversion, and highlights the impact of technology, especially Fear of Missing Out (FoMO) and screen time, on well-being. Practically, it encourages parents and educators to support Gen Z by fostering open communication, guiding resilience development, and monitoring technology usage to combat potential negative effects like FoMO.

Introduction

There are five distinct generational groups among adults: the Silent Generation, covering those born between 1928 and 1945, Baby Boomers, representing those born between 1946 and 1964; Generation X, encompassing individuals born between 1965 and 1980; Millennials, born between 1981 and 1996; and Generation Z, spanning births between 1997 and 2012. Each generation exhibits its own unique characteristics, traditions, and beliefs, navigating challenges through their distinct perspectives [1–3].

In 2021, Deloitte Global surveyed 23,000 Millennials and Generation Z in 45 countries. The survey found that 41% of Millennials and 46% of Gen Zs reported feeling stressed or anxious most or all of the time. Notably, among those who took time off work for mental health reasons, 49% of Millennials and 47% of Gen Zs gave their employers a different reason for their absence. [4]. Furthermore, a McKinsey study found that 25% of Gen Z respondents reported more psychological distress. This is nearly double or more than three times the rate represented by Millennial and Gen X respondents (13%). Two studies found that women are more likely than men to experience anxiety and worry due to the epidemic [5].

The issue of wellbeing in Generation Z needs to be effectively addressed. Wellbeing is defined as an individual's personal assessment of their happiness, life satisfaction, and emotional experiences [6]. A study demonstrates a direct link between employees' mental health and creativity and innovation in the workplace. Employee mental health and wellbeing enhance productivity, performance, and retention, while reducing costs associated with talent and potential loss [7]. Yet, Gen Z is expected to occupy around 27% of workforce by 2025 [8].

Wellbeing directly contributes to employee performance [9]. Wellbeing can influence employees to make better decisions based on skills and stronger resilience [10]. It can encourage individuals to contribute to larger tasks, thereby increasing their responsibility [9]. Wellbeing has a positive impact on enhancing productivity, performance, and employee loyalty [7]

Wellbeing is influenced by external and internal factors. One important external factor is technology. Generation Z, often referred to as Gen Z, encompasses those born between 1997 and 2012. They possess unique characteristics that distinguish them from other generations. Gen Z individuals have grown up in a world dominated by the internet, smartphones, video games, and similar technologies [11]. Surrounded by the rapid advancements in technology, their worldview is significantly shaped by the information they acquire from the digital realm [12].

This strong connection to technology is believed to influence the behavior of Gen Z. Excessive screen time and the constant need to stay updated, known as the Fear of Missing Out (FoMO), have been linked to a decline in wellbeing [13]. FOMO impacts the wellbeing of Generation Z, as this generation is heavily attached to digital and social media environments. Constant exposure to curated online content and the perpetual stream of updates from peers create a heightened sense of comparison and inadequacy. However, comprehensive research examining the impact of screen time and FoMO on wellbeing remains scarce [14]. Furthermore, there are still lack of literature on the effects of prolonged use of social commerce platforms on consumers' lives, learning, and mental health [13].

Another external factor is social support. Social support is a form of affection, togetherness, and attention from friends, family, and others [15]. Social support for each individual is closely linked to wellbeing [16]. Indonesia is known to have a closed knit social system. Family, including extended family, and friends play important role in one’s life. A study from Indonesia revealed that Gen Z is one of the most impacted in wellbeing deterioration during COVID-19 [17]. However, there is still lack of study reviewing the effect of social support in Gen Z wellbeing.

This study will review two internal factors which is resilience and extraversion. Studying internal factors such as resilience is crucial for understanding Gen Z's wellbeing because resilience significantly influence how individuals cope with the unique challenges posed by their digital environment. Resilience, the ability to adapt and recover from stress, can mitigate the negative impacts of social media-induced anxiety and FOMO, promoting better mental health outcomes [18]. Previous research has extensively studied the impact of resilience to wellbeing [18–21]. However, in related to Gen Z, the available literature is still limited.

Gen Z highly values social support, often relying on close networks of friends, family, and online communities for emotional and practical assistance. This generation tends to seek out and cling to social support more than previous generations, using it as a key resource for navigating personal and societal challenges. Social support acts as a protective barrier for individuals experiencing significant stress [22]. Studies also reveal that individuals receiving support from various sources, such as friends, family, and colleagues, demonstrate greater resilience when confronted with social pressure or negative interpersonal experiences [23].

Extraversion, characterized by sociability and positive emotional expression, may enhance social support networks and increase opportunities for positive interactions, countering feelings of isolation. Several studies have link extraversion to wellbeing [24, 25]. Through the examination of these internal traits, researchers seek to develop a more comprehensive understanding to pinpoint individuals who may be particularly susceptible to mental health issues, enhance coping.

The objective of this study is to explore the determinants influencing the wellbeing of Gen Z individuals, encompassing both internal and external factors. Beyond examining technology-related variables like FoMO and Screen time, the researchers opted to emphasize communication and social support. The rationale for highlighting extraversion stems from the distinct traits observed in Generation Z individuals. Social support holds significance within the Gen Z demographic, as it serves as a crucial element in offering emotional assistance, fostering relationships, and mitigating the adverse impacts of stress.

The research questions that this study aims to answer are:

1. Whether social support has a positive impact to resilience

2. Whether social support has a positive impact to wellbeing

3. Whether resilience has a positive impact to wellbeing

4. Whether extraversion has a positive impact to wellbeing

5. Whether FoMO has a negative impact to wellbeing

6. Whether screen time has a negative impact to wellbeing

This study will contribute to the literature on wellbeing. Especially in adding the body of evidence in the impact of technology in wellbeing. This study will also contribute to the literature of Gen Z, especially Gen Z in Indonesia.

Literature review

Positive psychology

Positive psychology, a relatively recent branch of psychology, is dedicated to comprehending and advocating positivity in the world [26]. This theory emerged towards the end of the twentieth century. A resilient mindset acknowledges adverse circumstances but also focuses on strengths, happiness, and positive emotions like gratitude, love, and joy. Positive psychology aids in overcoming challenges, discovering deeper life purposes, and nurturing closer interpersonal connections. Furthermore, it employs strategies that sustain positive moods and enhance commitment to work.

Psychological wellbeing and counseling psychology share the same goal of helping people overcome conflicts and improve their emotional wellbeing [27]. Research in health psychology focuses on factors such as hope, resilience and life decisions, examining the relationships between positive emotions, behavior and physical health. Positive psychological interventions are used in organizational psychology to increase morale and productivity in the workplace [28]. These interventions focus on employee engagement, job satisfaction and wellbeing.

Positive psychology is closely related to the development of positive thinking skills and perspective [29]. The field of happiness economics studies the factors that affect happiness and health in society. Philosophy examines happiness, wellbeing, and human flourishing, while neuroscience examines the neurological basis of emotional wellbeing, wellbeing, and wellbeing [30].

Positive psychology emphases on promoting positive emotions, resilience, strengths, and overall mental wellness. Positive psychology principles, which focus on cultivating happiness, optimism, mindfulness, and positive relationships, align closely with the needs and characteristics of Gen Z individuals. By integrating these principles into research and interventions tailored to Gen Z wellbeing, there is an opportunity to empower this generation with tools to navigate challenges, foster positive mental health outcomes, and enhance overall psychological flourishing. By acknowledging the importance of nurturing positive emotions, encouraging strengths-based approaches, fostering resilience, and facilitating a supportive environment promotes wellbeing and emotional health for the unique needs of Gen Z.

Generation Z

A generation involves "a group or cohort, belonging to the same age group, who have experienced or will experience similar life experiences during the years that shape their lives" [31]. Additionally, the emergence of generational theory has brought fresh interest to individual factors, raising questions about whether one generation, in contrast to its predecessor, possesses distinct and novel attitudes and talents related to ethics, shaped by their environment.

The values held by each generational group tend to persist within an individual's life and serve as reference points when interpreting subsequent life experiences [32]. Being part of the same cohort with shared historical and social experiences can limit cohort members to a range of experiences that may be somewhat restricted. Each group appears programmed to react to situations with similar thought processes and responses when confronted with similar circumstances. It is these differences in cohort-specific life experiences and responses to situations that clearly set cohorts apart from one another [31].

Currently, there are five distinct generations of legal adults coexisting. These generations include the Silent Generation (born between 1928 and 1945), Baby Boomers (born from 1946 to 1964), Generation X (born from 1965 to 1980), Generation Y or Millennials (born approximately between 1981 and 1996), and Generation Z (born between 1997 and 2012, or in some sources, between 1995 and 2005) [1–3].

The advancement of technology has facilitated global connectivity for Gen Z, allowing them to interact with peers worldwide. They are acknowledged as the initial global citizens who adopt international trends in food, fashion, language, and self-expression. Gen Z is well-informed about global trends and remains highly connected [33]

The strong connection to technology is believed to influence the behavior of Gen Z. Excessive screen time and the persistent desire to stay current, known as the Fear of Missing Out (FoMO), have been linked to a decline in wellbeing. Nonetheless, there exists a scarcity of comprehensive research exploring the impact of screen time and FoMO on well-being [14]

Gen Z exhibits pronounced self-confidence, high initiative, and a greater capacity for creativity and innovation to create new opportunities. They showcase exceptional multitasking skills and heightened productivity in comparison to earlier generations. This is evident in their early exposure to information and social media, which equips them with adeptness in processing the vast amount of information they acquire [33].

A recent survey has highlighted that younger generations prioritize their wellbeing and autonomy. As per a recent Randstad survey, 56% of employees aged 18 to 24 expressed a preference to quit their jobs if their workplace does not contribute to their happiness. Gen Z places lifestyle and wellbeing as their top priorities, closely followed by company values [34].

Being raised amidst escalating reports of violence, sexual harassment, assault, and apprehensions regarding climate change has left a significant impact on Gen Z. Additionally, the disruptions caused by the COVID-19 pandemic in their daily routines and future aspirations have heightened uncertainties concerning financial stability, healthcare accessibility, and government assistance. These factors have attributed to elevated levels of mental health concerns among Gen Z [33]

Gen Z exhibits distinct attitudes, expectations, strengths, and weaknesses in comparison to earlier generations [35, 36]. They embody a fixed sense of self-worth influenced by the self-esteem movement [37] and are often characterized by heightened levels of narcissism, excessive confidence, avoidance of negative experiences, and a preference for accolades and high grades [38]. This generation is sometimes perceived as sheltered due to the phenomenon of helicopter parenting [39]. Given that resilience is believed to develop through exposure to adversity [40], Gen Z individuals may exhibit lower resilience levels due to their limited encounters with adversity resulting from helicopter parenting and their general risk aversion to negative circumstances. Therefore, it is essential to explore the concept of resilience among Gen Z [19].

Subjective Wellbeing (SWB)

Positive psychology places a strong emphasis on human wellbeing, aiming to enhance the positive aspects of life and achieve optimal human functioning [41]. The foundation of the idea of what constitutes a good life and optimal human functioning can be traced back to eudaimonia, a concept introduced by Aristotle, encapsulated in the notion of "living well and doing well [42]. Wellbeing is commonly viewed through two lenses: the hedonic perspective, which pertains to feeling good, and the eudemonic perspective, which pertains to effective functioning [43]. The current study will specifically investigate the subjective dimension of well-being, concentrating on happiness and life satisfaction as primary indicators [44].

Subjective wellbeing (SWB) and overall wellbeing are related but differ in their scope and evaluation methods [45]. SWB revolves around an individual's personal assessment of their happiness, life satisfaction, and emotional experiences. It includes factors like life satisfaction, positive emotions, absence of negative emotions, and a sense of purpose and meaning. SWB is typically assessed through self-report surveys, offering valuable insights into individuals' perceptions of their own wellbeing. In contrast, overall wellbeing is a broader concept that encompasses various aspects of an individual's life, such as physical and mental health, social relationships, financial stability, and environmental factors [6].

While subjective well-being (SWB) focuses on personal happiness and life satisfaction, it is essential to note that overall well-being encompasses both objective and subjective dimensions. Economic hardship and financial insecurity have been associated with higher levels of depression, anxiety, and stress, whereas well-being has demonstrated a negative correlation with these mental health issues [46]. The uncertainty stemming from challenges like job loss can significantly impact employees, presenting limited avenues for addressing these stressors [47]. During outbreaks and pandemics such as the COVID-19 crisis, unpredictability further exacerbates stress levels due to feelings of helplessness, contradictory information, sudden disruptions, and concerns regarding personal and familial well-being [48].

Despite these challenges, prioritizing wellbeing is crucial. Individuals with higher wellbeing experience reduced risks of both physical and mental illnesses, enhanced social functioning, higher academic achievement, and lower mortality rates [43]. Research indicates a 14% higher risk of death for individuals with lower happiness levels compared to those who are very happy. Wellbeing is also associated with a lower white blood cell count, independent of mental health status [49]. Moreover, wellbeing plays a crucial role in academic performance, as students experiencing depression may find themselves trapped in a negative cycle that hinders their studies and leads to poor academic outcomes [50].

Social support

Social support are close friends, partners, and family ties that are known to provide people with bonding social capital, such as instrumental and emotional support [51]. Social support is a form of affection, togetherness, and attention from friends, family, and others [52]. Social support functions as a vital resource that individuals offer one another to manage the trials of life [53]. These resources are typically segmented into four categories: emotional support, tangible support, affiliative support, and informational support [53]. Regarded as a fundamental component of real social connections, social support is viewed as a critical social asset essential for attaining elevated levels of subjective well-being, encompassing aspects like health and life satisfaction [54].

The individuals with whom we interact and communicate create a social network that is considered the primary source of social support. Social support received by individuals from external sources can reduce stress and enhance mental health [52]. According to [22] social support functions as a protective shield when individuals are under significant pressure. Based on the research mentioned above, it can be concluded that social support is a form of support provided by one individual to another through care, advice, building strong friendships, reassuring them that they are not alone, and helping them to solve their problems.

Studies show that individuals who receive support from various sources (such as friends, family, and colleagues) exhibit higher resilience when facing social pressure or negative interpersonal experiences [23]. Human relationships play a vital role in fostering and maintaining responsibility towards those we know and in developing resilience [55]. Family and friends were described as a source of building resilience. Social support through friends have been documented as one that enhances resilience [19]. A qualitative study which confirmed that resilience stemming from social support, emotion management, and self-care [20].

Hypothesis 1: social support has a positive impact to resilience

Individuals often report experiencing greater happiness when in the company of others [56]. Those who feel loved, appreciated, and respected by their social circle tend to have a reduced risk of physical and psychological illnesses [57]. Strong social relationships within groups lead to higher levels of happiness. [58]. Additionally, sharing experiences with others can amplify the quality of those experiences and boost individual satisfaction [59]. The act of sharing experiences is inherently gratifying as it fosters feelings of social connection and understanding among individuals [60, 61] and contributes to a sense of togetherness in a new environment, fostering increased participation [62, 63]. Furthermore, individuals who provide assistance to others often exhibit enhanced self-esteem and better overall health [64].

Social support plays a crucial role in the well-being of individuals [65, 66]. Social support is perceived as a valuable resource that can enhance well-being and have lasting positive effects into adulthood and older age. Providing social support fosters intimacy in relationships that promote positive emotions and provide satisfaction related to psychological wellbeing [67]. Family engagement and the provision of social support can significantly improve an individual's well-being [68]. Social support is a form of support given by individuals to others that can have a significant positive impact on their lives.

The study involved 50 male and 208 female students from the Faculty of Health Sciences at the University of Ulster UK, is revealing that social support contributes to overall well-being [69]. Similarly, another study conducted by [70] demonstrated comparable results, involving 1,523 residents who completed online surveys and 157 residents who participated in telephone surveys. The findings indicated that social support could alleviate psychological stress and exert a positive influence on stress management. A related study conducted by [71] also supported these findings, indicating that individuals with high levels of social support and social identification exhibited stronger mental well-being among the student population.

Resilience

Resilience, defined as the ability to overcome the difficulties encountered in achieving personal goals [72]. Resilience is a psychological construct observed in some individuals that accounts for success despite adversity. Resilience reflects the ability to bounce back, to beat the odds and is considered an asset in human characteristic terms [18].

It's important to note that resilience is not a fixed outcome or characteristic; rather, it's a dynamic process that is shaped by resources, adversity, and an individual's capacity. It remains adaptable, changing, and susceptible to the impact of external factors and environmental influences [73]. Resilience recognizes the importance of being flexible and adaptable in uncertain situations. It is a dynamic system’s capacity to successfully adapt to adversity that threatens the function of a system or its viability or development [74]. The concept of resilience has attracted applied researchers seeking to promote the positive strength of individuals, groups and societies at various levels.

Resilience theory, focusing on coping mechanisms, delves into the factors that bolster or moderate an individual's resilience. These factors can be classified into individual aspects like problem-solving abilities, emotional regulation, and motivation, as well as social elements such as interpersonal relationships, and environmental factors like infrastructure or school facilities [19]. The significance of social elements in enhancing individual resilience is also highlighted [18]. Additionally, it is posited that resilience is cultivated through social support, emotion regulation, and self-care practices argue [20].

Resilience has been documented as an essential component in managing stress [19]. Resilience is regarded as an asset and a valuable trait that can have a positive influence on various aspects of an individual's performance, accomplishments, health, and wellbeing [18]. Research on the relationship between individual resilience and wellbeing was conducted by [75] and [21]. The results of the studies showed a significant relationship between resilience and psychological wellbeing.

Extraversion

Personality traits have garnered considerable attention regarding their impact on mental well-being and life satisfaction [76] [77]. Research has shown that openness has a positive influence on well-being, while conscientiousness has a negative effect [77]. The link between personality traits and depression raised by [76]. They found individuals who have experienced stressful situations showing higher vulnerability. Cross-sectional studies have linked personality traits, particularly extraversion, with psychological well-being. Extraversion stands out for its strong associations with well-being, likely due to its correlation with a more positive emotional state and a greater inclination to seek social support as a coping mechanism for reducing stress. The relationship between personality traits and well-being has been studied extensively [78].

Extraversion, characterized by projecting physical energy outward, indicates individuals who are objective-oriented and inclined towards objectivity rather than subjectivity [79]. Extraversion is associated with energy, dominance, assertiveness, and ambition [80].

Individuals with extraverted tendencies, as outlined by [81], excel in activities requiring social interaction because of their effective communication skills. Additionally, individuals with extraverted personalities, as noted by [81] typically exhibit higher performance in social settings. Individuals with high extraversion scores are often described as warm, friendly, talkative, sociable, energetic, and demonstrate assertiveness and dominance in social relationships [82].

In a study [78], extraversion, along with conscientiousness, exercise habits, and specific life events (both work-related and traumatic events), emerged as the most significant predictors of well-being. The research findings highlighted that both temperament and psychological flexibility exhibited unique, direct correlations with changes in stress and depression symptoms. Furthermore, individuals with extraverted traits showed lower levels of stress and depression. Extraversion typically characterizes individuals as sociable, outgoing, desiring high status, competitive, and adventurous [83]. Extraverts are often highly motivated to attain elevated status and surpass others for rewards. In the context of work-life conflict, they are more inclined to utilize proactive, solution-oriented coping strategies for managing conflicts, as previously mentioned by [84].

FoMO

FoMO is the fear of missing out, which is the apprehension someone feels about missing out on information, leading to their desire to maintain connections and engage in what is currently happening in society [85]. Fear of missing out (FoMO) is a phenomenon where individuals fear that others are having enjoyable experiences without their direct involvement, causing them to strive to stay connected with what others are doing through media and the internet. In simpler terms, FoMO can be defined as the fear of missing interesting things and the fear of being considered outdated and not up to date.

According to [86], one of the factors causing FoMO is technology. The excessive use of technology such as smartphones and the internet can be a cause of FoMO. The availability of information and easy access to social media and other information can make someone anxious if they are not always connected or unable to access the latest information. Social media platforms like Instagram, Facebook, and Twitter can lead to negative emotions such as stress, fatigue, and a lack of motivation. Through social media, one can see what friends, family, or others they follow are doing. This can make someone feel left out or excluded from ongoing activities. The feeling of exlusion can lead to feelings of anxiety, depression, and stress.

FoMO can affect an individual's wellbeing [86]. A prior study encompassing 296 participants revealed that the Fear of Missing Out (FoMO) was significantly linked to decreased well-being concerning Facebook usage [87]. Another research study conducted in Turkey, involving 235 student participants, discovered a negative correlation between FoMO and both well-being and mental health [88]. This finding is further reinforced by a study during the COVID-19 pandemic by [85] which focused on 552 respondents aged 17–28 with internet addiction. The research indicated that FoMO was associated with lower well-being levels, with this negative relationship intensifying amid the challenges posed by the COVID-19 crisis [85].

Screen time

Screen time encompasses the amount of time an individual spends using electronic devices such as smartphones for consuming news or entertainment, playing online games, using social media, instant communication with peers and family members, online information searches, and so on [89]. Screen time has become increasingly common with the growing availability and use of electronic devices in daily life. [90] states that high levels of screen time have become difficult to break away from due to the abundance of entertainment and educational content related to technology.

Screen time can be measured in hours or minutes per day [91]. Excessive screen time can become problematic when someone spends too much time in front of a screen, leading to negative impacts on an individual's physical and mental health. There are several consequences of excessive screen time on health [89]. Excessive screen time can limit the time for physical activities like exercise, potentially increasing health problems related to obesity, such as heart disease and diabetes [92]. Conditions like stress, anxiety, and depression can result from excessive exposure to screen light and insufficient time for direct social interaction, leading to a decline in mental health [93].

Previous study conducted involving 844 respondents aged 5–19 years in the education sector, found that screen time was negatively associated with wellbeing [93]. Another study by [91], involving 460 respondents aged 4–8 years in the education sector, also stated that screen time had a negative impact on wellbeing. This is further supported by research conducted by [89], involving 12,866 respondents from the healthcare industry, which reported that screen time was negatively related to wellbeing [89].

Hypothesis 6: Screentime has a negative impact to wellbeing

Figure 1 depict the research framework with 6 hypotheses.

Fig. 1.

Research framework

Methods

Sample and procedure

The sample for this study comprises Gen Z in Indonesia. Due to resources and time constraints the respondents are collected using convenience sampling collecting method. They were given brief information about the study and were asked to declare their consent on willingness to join the study voluntarily. The respondents also well informed that their private data will be kept confidentially.

The survey was structured in two sections. The initial section gathered information on the respondents' demographics, including gender, educational background, domicile, year of birth. The second section of the survey presented statements related to the study's variables, and respondents were asked to provide their ratings. The survey was conducted in Bahasa Indonesia to ensure the respondents' full comprehension of the questions and statements. Four hundred and eight questionnaires that were returned, all of them were completed with full consent. No missing data was identified, enabling all 408 questionnaires to be included in the subsequent analysis.

Measures

Wellbeing is influenced by internal and external factors. This study employed two internal factors which are resilience and extraversion and two external factors which are social support and FoMO. All of the following measures consist of items with response options ranging from 1 “strongly disagree” to 6 “strongly agree”, unless otherwise indicated. Mid-point was omitted to avoid central tendency [94].

Social Support (SS) was measured by 12 items from [95]. The items were such as “I have friends to whom I can share my feeling” and “I can talk about my problem to my parents”. Resilience (RL) was measured by 6 items modified from [21, 95, 96]. The items were such as “I tend to bounce back quickly after tough times.” and “I have no difficulty in recovering from tough times.”. Extraversion (EX) was measured by 8 items from [97]. The items were such as “I am full of energy” and “I am not shy”. FoMO (FO) was measured by 9 items from [98]. The items were such as “I am worried that my friends having better experiences” and “I am worried when knowing that my friends are having fun without me”. Wellbeing (WB) was measured by 16 items modified from [58, 99]. The items were such as “ My life condition now is good” and” I satisfy with my life”. Screen time was measured by time interval with interval referred to [100]. In this study, only screen time for social media was measured. Screen time for studying was out of scope.

Data analysis

Smart-PLS was employed for both the measurement model analysis and the structural model analysis. PLS-SEM is a preferred method for structural equation modelling in research due to its versatility in handling small sample sizes, complex models, non-normal data distributions, and measurement errors. It accommodates both reflective and formative constructs, making it suitable for exploratory research or studies with less well-established theories where flexibility is crucial. PLS-SEM's robustness against multicollinearity, distribution-free nature, predictive power, and ability to handle diverse data types such as ordinal, categorical, and continuous variables make it a valuable tool for researchers aiming to analyse relationships, predict outcomes, and build models within social sciences, management, and related fields.

The measurement model analysis aimed to validate the measurement items and evaluate indicator reliability. The validation of indicators involved assessing convergent and discriminant validity, following [101] criteria. Convergent validity was confirmed by ensuring outer loadings should ne not less than 0.6 or 0.7 and the average variance extracted (AVE) exceeded 0.5. Discriminant validity was assessed through cross-loading analysis, Heterotrait-Monotrait (HTMT) ratios, and the Fornell-Lacker criterion. Cross-loading analysis required that indicators had higher outer loadings on their associated constructs than on any other construct. The HTMT criterion aimed for values less than 0.9, indicating discriminant validity, while the Fornell-Lacker criterion required the square root of the AVE for each construct to be larger than its highest correlation with other constructs.

For the structural model, various evaluation metrics were considered, including coefficients of determination (R²), f² effect sizes, and the statistical significance of structural path coefficients. Collinearity was assessed using the variance inflation factor (VIF), with values below 5 indicating acceptable levels. Importantly, PLS-SEM does not assume normal data distribution and employs a nonparametric bootstrap procedure with 5,000 iterations to test the significance of coefficients [101]. This bootstrapping technique was utilized in this study to enhance the robustness of the analysis.

Result and discussion

Demographic and descriptive analysis

Total questionnaires returned was 408 and all were eligible for further analysis. From 408 respondents 41.9% were male, 57.8% were female, and remaining preferred not to answer. Majority of respondents were university students (78.7%). Most of them live in Jabodetabek (Greater Jakarta) and other area in Jawa (Table 1).

Table 1.

Demographic of respondents

Profile	Items	No of Respondents	%
Gender	Male	171	41.9%
	Female	236	57.8%
	Prefer not to answer	1	0.2%
	Subtotal	408	100%
Educational Background	Bachelor	64	15.7%
	Master	5	1.2%
	Doctoral	2	0.5%
	University Students	321	78.7%
	Others	16	3.9%
	Subtotal	408	100%
Position	University Students	321	77.4%
	Professional	60	14.7%
	Entrepreneur	20	4.9%
	Others	7	1.7%
	Subtotal	408	100%
Domicili	Jabodetabek (Greater Jakarta)	181	44.4%
	Jawa excluding Jabodetabek (Greater Jakarta)	181	44.4%
	Others	46	11.3%
	Subtotal	408	100%

Descriptive analysis of variables is depicted in Table 2. Majority of respondent were slightly agree that they were extrovert. They slightly disagree that they had FoMO. They also slightly disagree that they were resilience. Respondents spent on average 1 to 3 h in front of the screen for social media. They agreed they had a good social support. They slightly disagree that they had a good wellbeing.

Table 2.

Descriptive of variables

	Mean	Min	Max	Standard Deviation
Social Support	4.69	1	6	1.27
Resilience	3.72	1	6	1.45
Extraversion	4.15	1	6	1.37
FoMO	3.24	1	6	1.62
Screening Time	5.00	1	6	1.65
Well Being	3.77	1	6	1.51

Measurement model analysis

Table 3 showed convergent validity and reliability figure. Indicator AST2, IR2, IR3, IR5, WB1,WB5-WB11 were omitted because outer loading were less than 0.6 [101]. Based on the analysis indicators which were valid was depicted in Table 3. Those indicators showed acceptable value for AVE, CR and Cronbach Alpha. Therefore the indicators can be considered convergently valid and reliable.

Table 3.

Measurement model

	Extraversion	FoMO	Individual Resilience	Screening Time	Social Support	Well Being	AVE	CR	Cronbach Alpha
EX1	0.808						0.62	0.9	0.9
EX3	0.861
EX4	0.766
EX5	0.778
EX6	0.764
EX7	0.769
EX8	0.827
FO1		0.597					0.57	0.9	0.9
FO2		0.753
FO3		0.797
FO4		0.694
FO5		0.805
FO6		0.773
FOMO7		0.784
FOMO8		0.692
FOMO9		0.811
RL1			0.876				0.75	0.88	0.87
RL4			0.902
RL6			0.825
SS1					0.770		0.56	0.91	0.9
SS10					0.726
SS11					0.727
SS12					0.713
SS2					0.785
SS3					0.664
SS4					0.772
SS5					0.771
SS6					0.791
SS7					0.728
SS8					0.699
SS9					0.769
WB12						0.805	0.6	0.9	0.9
WB13						0.750
WB14						0.772
WB15						0.761
WB16						0.802
WB2						0.815
WB3						0.775
WB4						0.727

The analysis of cross loading showed that indicators had higher outer loadings on their associated constructs than on any other construct. Fornell-Lacker analysis showed the square root of the AVE for each construct to be larger than its highest correlation with other constructs (Table 4). The HTMT value for all variables were less than 0.9. It can be concluded that indicators used were met discriminant validity criteria (Table 5).

Table 4.

Fornell-Lacker

	Extrovert	FoMO	Individual Resilience	Screening Time	Social Support	Well Being
Extroversion	0.797
FoMO	0.364	0.748
Resilience	0.528	0.184	0.868
Screening Time	-0.125	-0.031	-0.113	1.000
Social Support	0.497	0.258	0.450	-0.077	0.744
Well Being	0.665	0.255	0.587	-0.125	0.673	0.776

Table 5.

HTMT

	Extrovert	FoMO	Individual Resilience	Screening Time	Social Support	Well Being
Extroversion
FoMO	0.360
Resilience	0.600	0.184
Screening Time	0.130	0.043	0.124
Social Support	0.538	0.258	0.506	0.086
Well Being	0.727	0.243	0.673	0.132	0.726

Structural model analysis

The VIF value for all indicators and variables were less than 5. Therefore, there is no collinearity problem for all constructs. The R2 for Resilience was 0.202. It means social support can only weakly explained resilience. The R2 for wellbeing was 0.632. It means social support, extraversion, FOM moderately explained). The f2 of extrovert to wellbeing was 0.197 (moderate effect size), the f2 of FoMO to wellbeing was 0.001 (no effect size), the f2 of Resilience to wellbeing was 0.090 (small effect size), the f2 of social support to resilience was 0.25 (moderate effect size) and the f2 of social support to wellbeing was 0.304 (moderate effect size).

The path analysis revealed that social support has coefficient determination 0.430 to resilience with T-value 9.916 (Fig. 2). It means the relationship of social support is positive to resilience and the relationship is significant. Social support has coefficient determination 0.401 to wellbeing with T-value 10.236. It means the relationship of social support is positive to wellbeing and the relationship is significant. Resilience has coefficient determination 0.222 to wellbeing with T-value 4.724. It means the relationship of resilience is positive to wellbeing and the relationship is significant. Extraversion has coefficient determination 0.352 to wellbeing with T-value 8.169. It means the relationship of Extraversion is positive to wellbeing and the relationship is significant. FoMO has coefficient determination -0.018 to wellbeing with T-value 0.807. It means the relationship of FoMO is negative to wellbeing and the relationship is not significant. Screen time has coefficient determination -0.0386 to wellbeing with T-value 0.829. It means the relationship of Screen Time is negative to wellbeing and the relationship is not significant.

Fig. 2.

Path analysis

Hypothesis testing

Table 6 showed that Hypothesis 1: Social Support has a positive impact to resilience can be accepted since the T-value of relationship was greater than 1.65 (T-table for one tailed relationship). Hypothesis 2: Social Support has a positive impact to wellbeing, Hypothesis 3: Resilience has a positive impact to wellbeing, and Hypothesis 4: Extraversion has a positive impact to wellbeing are also accepted with each T-value was greater than 1.65. However, Hypothesis 5: FoMO has a positive impact to wellbeing and.

Table 6.

Hypothesis testing

Hypothesis	Co-efficient	T-Value
H1: Social Support has a positive impact to resilience	0.430	9.916	Supported
H2: Social Support has a positive impact to wellbeing	0.401	10.236	Supported
H3: Resilience has a positive impact to wellbeing	0.222	4.724	Supported
H4: Extraversion has a positive impact to wellbeing	0.352	8.169	Supported
H5: FoMO has a negative impact to wellbeing	-0.018	0.807	Not supported
H6: Screentime has a negative impact to wellbeing	-0.0386	0.829	Not supported

Hypothesis 6: Screentime has a positive impact to wellbeing were rejected, because T-value of each relationship was less than 1.65.

Discussion

The comprehensive analysis of the study results underscores the intricate dynamics shaping Gen Z's wellbeing, shedding light on the multifaceted relationships between various factors and their mental health outcomes. The positive associations observed between social support, resilience, extraversion, and wellbeing reaffirm the profound impact of both external support systems and individual traits in fostering positive psychological states among young adults. These findings align with existing literature emphasizing the importance of social connections, adaptive coping mechanisms, and personality characteristics in promoting wellbeing and resilience in the face of adversities wellbeing [18, 19] [70] and [71]. The robust correlations identified among these variables underscore the importance of holistic approaches that consider both internal strengths and external support structures in enhancing Gen Z's mental health and overall quality of life.

While the study provided compelling evidence for the beneficial impact of social support, resilience, and certain personality traits on wellbeing, the inconclusive results regarding the effects of FoMO and screen time introduce a layer of complexity to the relationship between technology use and mental health among Gen Z individuals [87]. One argument could be related to the characteristics of Gen Z themselves. Firstly, Gen Z is often considered digitally savvy or "digital natives" [102]. Growing up in the digital age, Gen Z individuals are more accustomed to the online world and better equipped to handle its associated pressures, including FoMO. They tend to be more selective in their online engagement, curating their online presence, and are less likely to be constantly glued to social media [33], which reduces the intensity of FoMO. Gen Z is also known for its resilience and adaptability, having grown up in an era where FoMO is prevalent, which may have helped them develop effective coping mechanisms to deal with it [103].

The study did not establish a significant negative link between screen time and wellbeing. Despite a slight downward trend in the standardized coefficient, the relationship did not reach a statistically significant level. This discovery contributes to the ongoing discussion regarding the impact of social media screen time on wellbeing. Previous studies have offered mixed results regarding the link between digital screen engagement and the psychosocial functioning of young people [104]. Study from [102, 105] show that the relationship between screening time and wellbeing is nonlinear. They indicate that the moderate degree of screen time may be associated with higher level of wellbeing. Since Gen Z is digital native, the threshold of screentime might be higher compared to other generation. Another possible argument against this impact comes from the characteristics of Gen Z themselves. Gen Z has come of age in a digital era where technology is deeply woven into their daily routines. They have become proficient at managing and balancing their screen time, which diminishes its adverse effects on their overall wellbeing. Gen Z is renowned for its high level of digital literacy, making them acutely aware of the potential downsides of excessive screen time. Consequently, they are more likely to take proactive measures to mitigate these effects, such as setting time limits or employing apps that monitor and control their usage.

Insights gleaned from existing research on FoMO, screen time, and digital literacy among Gen Z individuals illuminate the resilience and adaptability this generation demonstrates in managing their online engagements and mitigating potential negative impacts of technology use on their wellbeing. The study's nuanced analysis emphasizes the role of digital proficiency, active coping strategies, and social connectivity in shaping Gen Z's mental health landscape. By recognizing the complexities and nuances of Gen Z's digital experiences, researchers and practitioners can refine interventions, policies, and support mechanisms that align with the evolving needs and preferences of this tech-savvy cohort, ultimately promoting their holistic wellbeing in the digital age.

The study's results contribute valuable insights into the complex interplay between social support, resilience, personality traits, technology use, and psychological wellbeing among Gen Z individuals. The findings underscore the importance of fostering strong support systems, enhancing resilience-building skills, capitalizing on positive personality traits, and leveraging digital literacy to promote positive mental health outcomes in today's digitally connected world. Continued research into the evolving digital landscape and its impact on wellbeing is essential for developing tailored interventions, educational initiatives, and support structures that cater to the diverse needs and challenges faced by Gen Z in navigating the complexities of the digital age while safeguarding their mental health and overall wellbeing.

Conclusion

Gen Z is expected to dominate the workforce in the foreseeable future, therefore, the issue of wellbeing in Generation Z needs to be effectively addressed. Studies demonstrates a direct link between wellbeing and productivity, creativity, innovation, and retention. Findings from the study reveal how social support, as external factor, is positively influencing wellbeing and resilience. The study also shows that resilience plays a role in influencing wellbeing. Therefore, the total impact of social support to wellbeing is strong, directly and indirectly. This study also shows the positive impact of personal traits, specifically extraversion to wellbeing. However, this study fails to show the dark side of technology impacted wellbeing. The rationale behind this observation may lie in the coping mechanisms adopted by Gen Z individuals, who, as digital natives, utilize technology for selective engagement, multitasking, and even social media to enhance their social interactions.

Theoretical implications

The present study has three important theoretical implications. Firstly, our study expands the current knowledge on the consequences of social support to resilience and wellbeing by proving the direct positive relationship. Previously, scholar investigated the impact of social support to resilience and social support to wellbeing separately. This study revealed the total effect of social support to wellbeing is strong (direct and indirectly through resilience).

Secondly our study confirms the notion that wellbeing is impacted by internal and external factors. Internal factors such as resilience and extraversion are positively impacted wellbeing. Individual traits and individual capability in developing their coping mechanism similarly strongly influence wellbeing.

Thirdly, the current study delves into the influence of technology, specifically examining the effects of Fear of Missing Out (FoMO) and screen time on well-being. By adding to the existing body of evidence, this study contributes to the ongoing debate surrounding the potential negative implications of technology. Gender and generational cohort are factors that could significantly impact these effects. Thus, further research exploring gender and generational differences is recommended.

Practical implications

The study's outcomes present three practical implications for parents, the education sector, and the industry. Firstly, parents, guardians, educators, and employers of Gen Z individuals should allocate dedicated time and provide support to this cohort. Parents and guardians should engage in open dialogues, encouraging open communication to help Gen Z articulate any difficulties they may encounter. The assurance of having a supportive figure looking out for them can boost the confidence and happiness of Gen Z individuals.

Secondly, our findings can guide parents and guardians in supporting the development of resilience in Gen Z individuals. It is crucial to expose them to challenges and provide guidance through each step of the process. Cultivating the ability to effectively manage and rise above difficulties will equip Gen Z to tackle larger adversities in the future.

Even though this study did not show significant relationship between FoMO and screen time, still parents and guardians need to monitor and be aware of the negative impact. Open communication is key to ensure that parents and guardians catch early symptom of FoMO or any other technology related addiction.

Study limitation and further study

The current study has two primary constraints. Firstly, it pertains to the specific context in which the data were gathered, namely Gen Z individuals in Indonesia. Given this constrained context, the applicability or broader applicability of the findings to different cultural or demographic contexts (such as other age groups) may be limited. The second limitation concerns the research design. Our study employed a quantitative approach and had a cross-sectional design. Consequently, it lacks the capability to delve into the underlying reasons behind specific issues and cannot establish causal relationships over an extended period.

To address these limitations, we suggest potential avenues for future research. For instance, researchers should assess our research model using participants drawn from diverse cultural and demographic backgrounds. Furthermore, scholars should employ both longitudinal and qualitative research designs to explore potential shifts in the nature of the investigated relationships over time and to establish causal connections between the variables under scrutiny. Qualitative approaches could uncover additional potential precursors and outcomes related to wellbeing.

Authors’ contributions

D.D. conceptualized the study, conducted the study, reviewed manuscript; Y.P. supervised the study, conceptualized the study, reviewed manuscript; L.I. conducted the study, prepared draft; D.G. conducted the study, conducted the analysis, prepared draft.

Funding

This research is funded partially by Bina Nusantara University, Indonesia and Universitas Katolik Darma Cendika, Indonesia.

Data availability

Data of this study is available in a public repository: Tjiptadi, Diena (2025), “Gen Z wellbeing”, Mendeley Data, V1, doi: 10.17632/xnsv6g5z64.1

Declarations

Ethics approval and consent to participate

This study was conducted in accordance with the Declaration of Helsinki and was reviewed and found exempt by the Research Ethics Committee at Bina Nusantara University (No. 140/VRRTT/IX/2024, Date: 3 September 2024).

Informed consent was obtained from all participants included in the study, and all participants were assured of their rights to withdraw from the study at any time without any repercussions. Data confidentiality and anonymity were maintained throughout the research process.

Consent for publication

Not applicable.

Competing interests

The authors declare no competing interests.