Assessing Eudaimonic Factors in Young Urban Indian Students: Gender and Social Media Influence on Resilience

Assessing Eudaimonic Factors in Young Urban Indian Students: Gender and Social Media Influence on Resilience

Sutapa Goswami¹, Mannu Brahmi^*2, Riya Jain³, Greeshma Sharma⁴

^{1, 3, 4}Department of Design, IIT Delhi,

²NRCVEE, IIT Delhi

^*Corresponding Author

DOI: https://dx.doi.org/10.47772/IJRISS.2024.803217S

Received: 20 July 2024; Accepted: 24 July 2024; Published: 29 August 2024

ABSTRACT

This study investigates the role of eudaimonic factors such as ‘quiet ego’ and ‘non-attachment’ in fostering resilience among young adults in urban India, examining the interplay of these constructs with gender, social media usage, and psychological profiles. Utilizing a sample of 200 participants aged 20-25 from urban India, this study employed the ‘Quiet Ego Scale,’ ‘Non-attachment Scale,’ and ‘Resilience Scale.’ Data were analyzed using t-tests and ANOVA on R-Jamovi. The findings indicate significant gender differences, with males exhibiting higher scores in non-attachment and resilience than females. Additionally, participants with lower to moderate social media usage (1-2 hours per day) displayed greater resilience compared to heavy users (more than 3 hours/day). These results underscore the need for understanding the factors that predict resilience, as gender and social media habits significantly influence resilience in young adults. This understanding can inform the development of targeted interventions and support systems that cater to diverse groups based on their unique psychological needs and social habits. For instance, interventions could be designed to help individuals, particularly females and heavy social media users, develop a ‘quiet ego’ and ‘non-attachment’ mindset, thereby enhancing their resilience.

Keywords: Resilience, Quiet Ego, Non-Attachment, Young Adults, Urban India, Gender Differences, Social Media Usage.

INTRODUCTION

The dynamic state of today’s world, characterized by swift technological advancements, economic instability, and changing societal norms, highlights the importance of individuals developing adaptability skills (Ventriglio et al., 2021). In this context, resilience is a valuable psychological resource that empowers people to rebound from setbacks, navigate uncertainties, and maintain their mental well-being amidst life’s unpredictability. The capacity to nurture and strengthen resilience has consequences for an individual’s mental health and the broader social framework (APA, 2023). In an era where stressors are diverse and ever-present, ranging from workplace demands to societal expectations, resilience emerges as a crucial factor in preserving mental health. Consequently, it becomes essential to investigate the factors that predict resilience to develop effective interventions and strategies for enhancing individuals’ ability to confront and overcome challenges.

However, a critical examination of contemporary resilience research reveals a predominant reliance on models and theoretical frameworks deeply rooted in Western reductionistic paradigms (Samani et al., 2007). While these frameworks have undoubtedly enriched our understanding of resilience, they may not fully capture the diverse factors contributing to adaptive coping across different cultural contexts. The current discourse on resilience often reflects a bias toward individualistic perspectives, overlooking the profound influence of cultural and contextual factors on psychological well-being (Raghavan & Sandanapitchai, 2020)

Quiet Ego, Non-Attachment & Resilience

The present study delves into two intriguing constructs–Quiet Ego and Buddhist Non-attachment- and their relationship to resilience, which are alternate, culturally grounded factors. According to Wayment & Bauer (2008), individuals with a quiet ego tend to have a less self-centered and less defensive view of themselves. Their egoistic desires or self-inflating tendencies do not drive them. A quiet ego allows one to work towards one’s personal growth and internal values and focus on the well-being of their community rather than being concerned with external validation or material success of their own (Liu et al., 2022). Humility, tolerance, gratitude, forgiveness, secure self-concept, responsibility, altruism, and the like indicate a quiet ego (Snyder & Lopez, 2001). The concept of Non-attachment, rooted in Buddhist philosophy, involves relinquishing undue fixation on outcomes, possessions, and identities, thereby liberating individuals from the shackles of unbridled desires. Non-attachment aligns with the principles of impermanence and interconnectedness, promoting a mindset unburdened by excessive clinging and aversion (Sahdra et al., 2010).

The modern world, characterized by heightened materialism, consumerism, hyperconnectivity through social media, global competition, and capitalistic agendas, fosters self-focused, self-indulgent, and narcissistic thinking, associated with negative affect, lower self-esteem and psychological and physiological stress (Wayment & Bauer, 2008). Similarly, excessive self-focus, inflated self-importance, and attachment to worldly desires have been linked to adverse health outcomes (Tayal et al., 2020). Positive psychology researchers emphasize quieting the ego and prioritizing values such as collectivistic interest, social harmony, and compassion for self and others to enhance coping mechanisms and foster resilience (Wayment & Bauer, 2008). Empirical evidence shows that individuals with a quiet ego exhibit less self-criticism, greater forgiveness of themselves and others, and overall better well-being (Wayment & Bauer, 2008). Mindfulness-based interventions, grounded in non-attachment and acceptance, have effectively reduced stress and anxiety among college students (Biegel et al., 2009). These practices positively impact self-esteem, emotional regulation, self-compassion, positive emotion, and social competence among youth, enhancing resilience when individuals are less attached to material possessions and egoistic desires (Singh & Raina, 2015). Brahmi et al.’s 2023 study reveals a correlation between mindfulness and conservative values in Indian youth (20-25 years). This age group, immersed in a digital-heavy lifestyle and facing unique challenges like tech-centric careers and digital media consumption (e.g., TikTok), was examined for resilience—a trait increasingly vital in today’s society, as noted by Twenge (2014). The findings provide insights into the blend of traditional values and contemporary pressures, highlighting the role of mindfulness amidst cultural and generational shifts.”

Role of Gender in Quiet Ego, Non-attachment, and Resilience

Research on resilience reveals divergent views regarding gender differences. Studies like Rodriguez-Llanes et al. (2013) suggest higher resilience in males, which aligns with traditional masculine traits of stoicism. Hirani (2016) argues for greater resilience in women, attributed to their interpersonal skills and propensity for seeking social support. Regarding the ‘quiet ego,’ a concept focusing on a balanced self-view, there appears to be no significant gender difference, indicating a highly personal and context-dependent formation. Further, Sahdra et al. (2010) highlight more attachment anxiety in women, possibly due to societal norms encouraging emotional expression, whereas men are often raised to value independence, potentially enhancing their resilience. These findings underscore the complex interplay of cultural and individual factors in shaping resilience and identity.

The Role of Education: STEM vs non-STEM Backgrounds

In education, there is a big difference between STEM (Science, Technology, Engineering, and Mathematics) subjects and non-STEM subjects. STEM areas focus on building skills and are very competitive, often leading people to want quick rewards like money (Ertl et al., 2019). This focus on doing things alone can make it hard to develop qualities like a quiet ego, which is about being humble and balanced. On the other hand, non-STEM subjects like arts and humanities are more about understanding people, society, and culture. They make students think more about life’s bigger picture, not just quick rewards. This learning helps grow empathy, compassion, and a quieter ego that does not rely on external success or pleasure.

Role of Social Media Usage

Social media platforms significantly influence psychological orientations, often emphasizing self-promotion, comparison, and external validation. This focus can lead to an inflated ego and a preoccupation with self-image, countering the concept of a quiet ego, which advocates for reduced egocentrism (Skogen et al., 2021). The attachment to external validations like likes and comments promotes a culture of instant gratification, potentially impeding the development of non-attachment, a principle in Buddhist philosophy advocating detachment from ephemeral desires.

The impact of social media on resilience is dual-faceted. Negative online experiences, such as cyberbullying or excessive comparison, may erode resilience, while positive aspects like supportive communities and informative content can bolster it (Mano, 2020). However, overuse of social media, mainly driven by fear of missing out or constant comparison, may induce stress and anxiety, undermining effective adversity navigation and resilience.

The Current Study-Towards Research Hypotheses

The present study aimed to unravel group differences in quiet ego, non-attachment, and resilience based on distinct categories such as gender, STEM vs. non-STEM affiliation, and varying levels of social media usage. The following hypotheses were formed to test the same:-

Gender Differences (Hypotheses-1)

H1.1_A: There will be a significant difference in the quiet ego (QE) scores between males and females.

H1.2_A: There will be a significant difference in the non-attachment (NA) scores between males and females.

H1.3_A: There will be a significant difference in the scores of resilience (RS) between males and females.

STEM vs Non-STEM Differences (Hypotheses-2)

H2.1_A: There will be a significant difference in the scores of QE between STEM vs Non-STEM groups.

H2.2_A: There will be a significant difference in the scores of NA between STEM vs Non-STEM groups.

H2.3_A: There will be a significant difference in the scores of RS between STEM vs Non-STEM groups.

Social Media Usage (High vs Low Users; Hypotheses-3)

H3.1_A: There will be a significant difference in the scores of QE in ‘high’ volume users vs ‘low’ volume user groups. (Low-Bin: Less than 2 Hours; High-Bin: More than 2 Hours)

H3.2_A: There will be a significant difference in the scores of NA in ‘high’ volume users vs ‘low’ volume user groups. (Low-Bin: Less than 2 Hours; High-Bin: More than 2 Hours)

H3.3_A: There will be a significant difference in the scores of RS between ‘high’ vs ‘low’ social media usage groups.  (Low-Bin: Less than 2 Hours; High-Bin: More than 2 Hours)

To further analyze mean score differences among social media users, we further divided ‘low’ and ‘high’ social media usage groups into a total of 4 sub-groups, namely- ‘Low’ (under 1 hour), ‘Medium-Low’ (1-2 hours), ‘Medium High’ (2-3 hours) and ‘High’ (more than 3 hours).

H3.4_A:  There will be a significant difference in the scores of QE between ‘High’ vs. ‘Medium High’ vs. ‘Medium-Low’ vs. ‘Low’ social media usage groups.

H3.5_A:  There will be a significant difference in the scores of NA between ‘High’ vs. ‘Medium High’ vs. ‘Medium-Low’ vs. ‘Low’ social media usage groups.

H3.6_A:  There will be a significant difference in the scores of RS between ‘High’ vs. ‘Medium High’ vs. ‘Medium-Low’ vs.’ Low’ social media usage groups.

METHOD

Participants

In this research study, the participant cohort consisted of 200 individuals (males=100, females=100, mean age=21 years) recruited using purposive and snowball sampling methodologies. Participants were selected based on specific inclusion criteria, which required them to meet the following qualifications: they had to be current residents of India, fall within the age range of 20 to 25 years, and possess a higher education background, defined as either holding a bachelor’s or master’s degree. Most of the study’s participants were found to reside in urban areas, with a notable concentration in New Delhi, Haryana, and Rajasthan regions. Regarding their educational attainments, it was observed that 72% of the participants were currently pursuing bachelor’s degree programs, while 18.5% had completed their bachelor’s degrees. A smaller proportion of participants were actively engaged in master’s degree programs; the fewest participants had already attained their master’s degrees. Furthermore, in terms of academic backgrounds, 59% of the sample possessed qualifications in non-STEM disciplines, whereas 41% of the participants hailed from STEM backgrounds. We obtained ethical clearance from the Indian Institute of Technology, Delhi (IEC-IITD), under Proposal No. P021/P0101.

Measures Used

Quiet Ego Scale (QES)

QES, developed by D. Wayment and J. Bauer in 2014, measured an individual’s “quiet ego” level. Quiet ego consists of four first-order factors: detached awareness, inclusive identity, perspective-taking, and growth. Cronbach’s alpha coefficient for the QES was 0.83, indicating high internal consistency, and has good overall psychometric properties (Wayment & Bauer, 2014).

Non-attachment Scale (NAS-7)

NAS, developed by N. Sahdra and his colleagues in 2010, was used to measure non-attachment. The Buddhist concept of non-attachment involves letting go of attachment, fixations, and expectations to achieve inner peace and happiness. It originally had 29 items, which could have been time-consuming for participants; therefore, a shortened version consisting of just seven items was created (NAS-7). Its reliability and validity have been tested, and its Cronbach values range from 0.86 to 0.96 and show good convergent validity (Sahdra et al., 2010).

Resilience Scale (RS-14)

RS-14, developed by M. Wagnild & Heather M. Young in 1993, conceptualizes resilience as a total of the following characteristics viz. Meaningful Life (or Purpose), Perseverance, Self-Reliance, Equanimity, Existential Aloneness. The Cronbach’s alpha coefficient for the RS-14 was 0.89, indicating high internal consistency according to the original study by Wagnild & Young (1993). It has demonstrated good construct and convergent and discriminant validity and has been used in various research and clinical contexts.

Procedure

The research inquiry was structured around specific research questions, and an online questionnaire was designed utilizing standardized psychological assessment scales. Data collection was conducted via Google Forms to mitigate potential bias, with particular care taken to ensure that the form title did not explicitly reference the psychological constructs being investigated. In addition, informed consent was explicitly obtained from all participants. The initial phase of data collection yielded a total of 208 raw responses. Subsequently, a rigorous screening was undertaken to assess the validity of responses and adherence to the predefined inclusion criteria. As a result of this screening, the final dataset consisted of 200 valid responses, meticulously ensuring an equitable representation of male and female participants. The preliminary analysis stage involved applying Pearson’s Product-Moment Correlation Coefficient test to assess initial correlations among variables of interest. Subsequently, a multiple regression model was employed, wherein resilience served as the dependent variable, while the independent variables or predictors included measures of quiet ego and non-attachment.

RESULTS

The data was analyzed using R-Jamovi (The Jamovi Project, 2023; R Core Team, 2021), and descriptive and inferential analyses were conducted. Statistical assumptions like normality testing, multicollinearity, and homoscedasticity were checked, leading to the application of a multiple regression model (Fox & Weisberg, 2020). A prior study exploring the relationships between Quiet ego, non-attachment, and resilience has shown positive correlational links between the three constructs (Goswami et al., 2023), warranting further research on exploring individual group differences.

Gender Differences

Table 1: Table showing descriptive statistics for males and females and independent t-test statistics pertaining to gender differences.

*p < .05, ** p < .01, *** p < .001

Findings of the descriptive and t-test analyses are presented in table 1. Mean scores for non-attachment and resilience were significantly different between males and females. A significant difference was found between genders on non-attachment  [t(198) = -2.483, p < .05], with males (M=29.2, SD=5.18) scoring higher than females (M=27.2 SD=6.22). Thus, we failed to reject H1.2_A. Mean scores of resilience scores also differed significantly between males and females [t(198) = -2.240, p < 0.05], with males (M=68.2, SD=10.94)  scoring higher than females (M=64.7, SD=11.41). Consequently, we failed to reject H1.3_A. In H1.1_A, the outcomes of an independent group t-test revealed no significant distinctions in quiet ego scores between males and females. Consequently, H1.1_A cannot be substantiated.

STEM vs. Non-STEM Differences

In H2.1_A, the outcomes of an independent group t-test indicated that there were no noteworthy disparities in quiet ego scores between STEM and non-STEM groups [t(198) = -0.2013, p > 0.05]. Consequently, H2.1_A is not supported. Turning to H2.2_A, the results from an independent group t-test demonstrated that there were no significant differences in non-attachment scores between STEM and non-STEM groups [t(198) = 0.2180, p > 0.05]. As a result, H2.2_A cannot be upheld. Finally, in H2.3_A, the findings arising from an independent group t-test revealed no significant disparities in resilience scores between STEM and non-STEM groups [t(198) = -0.0798, p > 0.05]. Therefore, H2.3_A is not substantiated.

Social Media Usage (High vs Low Users)

Table 2: Table showing descriptive statistics and independent t-test statistics for High and Low social media users.

 *p < .05, ** p < .01, *** p < .001

Findings of the descriptive and t-test analyses are presented in Table 2. Mean scores for non-attachment [t(198) = 1.78, p > 0.05] and quiet ego  [t(198) = 1.22, p > 0.05 were not found to be significantly different between low and high social media users. Therefore, H3.1_A and H3.2_A were not supported. However, a marginally significant difference was found in resilience mean scores between low and high social media users [t(198) = 1.91, p = 0.057], with participants in the ‘low’ social media usage group scoring (M=67.8, SD=12.09) higher on resilience than those in the ‘high’ social media usage group  (M=64.8, SD=9.99). Consequently, H3.3_A was not accepted.

In H3.4_A, ANOVA analysis demonstrated no significant differences in quiet ego scores among the ‘High,’ ‘Medium-high,’ ‘Medium-low,’ and ‘Low’ social media usage groups [F(3, 99.2) = 0.671, p > 0.05]. Hence, H3.4_A could not be upheld. Similarly, H3.5_A‘s ANOVA analysis revealed no significant differences in non-attachment scores between the ‘High,’ ‘Medium-high,’ ‘Medium-low,’ and ‘Low’ social media usage groups [F(3, 98.8) = 1.818, p > 0.05], leading to the non-acceptance of H3.5_A. In H3.6_A, ANOVA analysis identified a marginally significant difference in resilience scores between the ‘low medium’ and ‘high’ social media usage groups [F(3, 98.5) = 2.696, p = 0.05]. Tukey post hoc analyses revealed the strength of differences among groups of varying social media usage studied. A significant difference between the ‘medium-low’ and ‘high’ social media user groups [t(196) = 2.68, p = 0.040]. The descriptive table further revealed that the ‘low medium’ (M=68.8, SD=11.15) group had higher resilience than heavy social media users (M=62.8, SD=10.04). Consequently, H3.6_A was partially failed to be rejected.

DISCUSSION & CONCLUSIONS

Understanding factors contributing to resilience is crucial in today’s fast-paced and competitive environment. The constructs of ‘quiet ego,’ characterized by a balanced and humble self-view, and ‘non-attachment,’ a concept from Buddhist philosophy implying a lack of emotional dependency on personal expectations, are explored in their capacity to foster resilience. This study uniquely combines these psychological constructs with demographic variables like gender and social media habits, providing a comprehensive view of their impact.

The study’s results shed light on unique differences in quiet ego, non-attachment, and resilience based on gender, educational background, and social media usage. These three background variables play a massive role in shaping one’s psychological orientation and values, and their salience has been described in the aforementioned sections.

Gender Differences

Results suggested that men exhibited greater resilience as well as non-attachment in comparison to women. The difference in resilience highlights the nuanced interplay of multifaceted factors deeply ingrained in coping strategies, societal expectations, and cultural conditioning. For instance, the inclination of females toward emotion-focused coping strategies, as documented by Graves and colleagues (2021), might be one explanation. These strategies, while significant, might wield less effectiveness in fostering resilience in the face of adversity. Conversely, males, per societal norms, are often socialized to embrace independence and self-reliance, which may promote heightened resilience (Graves et al., 2021). Supporting this, the study by Rajeev and Hebbani (2020) in Indian samples underscores significant gender differences, indicating males’ proclivity for greater resilience, aligning with the outcomes of the present study. Another dimension contributing to this observed gender-based resilience disparity could be the inherent biases within the resilience measurement instrument. Existing literature, notably the work of Hirani et al. (2016), has pointed out potential biases in resilience scale items, suggesting a tilt towards masculine manifestations of resilience. This bias might inadvertently favor identifying resilient traits more aligned with traditional perceptions of masculinity, influencing the study’s outcomes.

No statistically significant distinctions emerged between male and female participants in the quiet ego scores. This concurs with the findings of a study conducted by Gupta and Agrawal (2022), where the researchers explored the concept of ‘ahamkara’ or ego, denoting the amalgamation of ‘aham’ (self) and ‘kara’ (do-er), within a sample of Indian adults. The outcomes of their study revealed a lack of significant differences between genders, except for the observation that males exhibited higher scores on the ‘agency’ or ‘kartatva’ component (Gupta & Agrawal, 2022), denoting a heightened sense of being a doer or an agent in their actions.

Next, we also found that males scored significantly higher than females in non-attachment. Historically, men have been encouraged to adopt a stoic demeanor, emphasizing emotional restraint (Wagstaff et al., 1995). This cultural conditioning may inadvertently foster a sense of detachment from emotional outcomes and situations, possibly contributing to the development of non-attachment and resilience in males. Gendered narratives surrounding resilience often uphold traits such as emotional strength and self-reliance, conforming to societal ideals of masculinity. In contrast, females may grapple with societal pressures prioritizing emotional expression and interpersonal connections, potentially fostering greater attachment to relationships. The heightened emotional awareness, empathy, and sense of compassion often associated with females could engender a deeper investment in emotional ties, potentially conflicting with the concept of detachment from people and situations. Overall, the observed gender differences in resilience may be intricately linked to societal expectations and gender roles, shaping individuals’ coping mechanisms and responses to adversity.

STEM vs. Non-STEM Differences

Despite initial expectations of finding distinctions between STEM and non-STEM groups’ quiet ego and non-attachment scores, our study did not reveal statistically significant differences in the two variables. One plausible explanation could be the multifaceted nature of the quiet ego, which extends beyond academic disciplines. While STEM fields emphasize technical proficiency, developing a quiet ego might be influenced by various individual and environmental factors (Chew et al., 2023). Non-attachment involves relinquishing excessive fixation on desires and expectations, encompassing material and relational aspects. STEM and non-STEM students might converge in their abilities to adopt a non-attached perspective, especially given the universality of life stressors. The shared experiences of academic challenges, personal growth, and exposure to various perspectives (Krendl, 2023) could contribute to the similarities observed in quiet ego and non-attachment scores.

We also did not find significant differences in resilience levels between STEM and non-STEM students. This is in line with Kuzmishin’s findings in 2018, which revealed that despite gender differences in resilience, STEM and non-STEM students did not differ in their resilience levels (Kuzmishin, 2018). The intricate interplay of factors influencing resilience may eclipse the influence of academic focus. Resilience is shaped by diverse life experiences, coping mechanisms, and individual traits, which may overshadow the potential impact of academic specialization. Furthermore, the shared challenges of university life, irrespective of the field, might contribute to everyday resilience among STEM and non-STEM students (Yeo et al., 2023; Beiter et al., 2015).

Group Differences in Social Media Usage

Finally, we found that participants in the low social media usage group had higher resilience than high social media users. However, when we delineated further into 4 group classifications of social media users, we found that the low-medium group had higher resilience than heavy social media users. One potential factor contributing to the higher resilience observed in individuals with lower social media usage is the quality of their social connections and harnessing social support in times of stress and coping (Hurley, 2018). Research has also highlighted the importance of perceived social support, a sense of community and belonging derived from genuine, tangible relationships, and a well-established pillar of resilience, offering a buffer against life’s challenges (Bilgin & Tas, 2018).

Furthermore, the reduced digital connectivity associated with lower social media use allows individuals to be more present in the moment. Individuals who spend less time immersed in the constant stream of digital information and social comparisons are better positioned to engage in mindfulness practices (Khoury et al., 2015). Lower mindfulness has been associated with compulsive social media addictive behaviors (Apaolaza et al., 2019). Heavy social media users are often bombarded with curated representations of others’ lives, fostering unrealistic comparisons, inadequacy, and lower self-esteem (Jan et al., 2017). In contrast, individuals with lower social media engagement maintain a more realistic appraisal of their lives. This realistic self-perception is instrumental in mitigating the risk of succumbing to the pressures of societal expectations and enhances the ability to navigate challenges with a grounded perspective (Throuvala et al., 2020).  Moreover, the observed link between lower social media use and higher resilience is intertwined with developing a more robust internal locus of control. Research shows that heavy social media users have a weaker locus of control (Hussin et al., 2021). Individuals less dependent on external validation, particularly from the transient realm of social media, tend to cultivate a more autonomous sense of self. This autonomy, coupled with a reduced reliance on external sources for validation and pleasure, equips individuals with the inner resources needed to confront and overcome life’s stressors.

Limitations & Future Work

While the study offers insightful findings, it acknowledges limitations, such as its focus on a specific age group and urban demographic, suggesting the need for broader research to generalize these results. This research underscores the importance of individual differences in resilience and the potential influence of societal and technological factors, paving the way for more personalized and practical approaches to mental health and well-being in contemporary society. To enhance future research in this field, researchers might consider employing a variety of research designs to capture a more comprehensive understanding of the dynamics at play. Longitudinal studies, for instance, could provide valuable insights into how the constructs of quiet ego, non-attachment, and resilience interact and evolve. Cross-cultural studies would be particularly beneficial in understanding how these concepts manifest across different societal contexts, potentially offering a more global perspective on these psychological constructs.

REFERENCES

1. American Psychological Association: Dictionary of Psychology (2023). Retrieved from https://dictionary.apa.org/resilience.
2. Apaolaza, V., Hartmann, P., D’Souza, C., & Gilsanz, A. (2019). Mindfulness, compulsive mobile social media use, and derived stress: The mediating roles of self-esteem and social anxiety. Cyberpsychology, Behavior, and Social Networking, 22(6), 388-396.
3. Beiter, R., Nash, R., McCrady, M., Rhoades, D., Linscomb, M., Clarahan, M., & Sammut, S. (2015). The prevalence and correlates of depression, anxiety, and stress in a sample of college students. Journal of Affective Disorders, 173, 90–96. doi:10.1016/j.jad.2014.10.054
4. Biegel, G. M., Brown, K. W., Shapiro, S. L., & Schubert, C. M. (2009). Mindfulness-based stress reduction for the treatment of adolescent psychiatric outpatients: A randomized clinical trial. Journal of Consulting and Clinical Psychology, 77(5), 855-866.
5. Bilgin, O., & Taş, İ. (2018). Effects of perceived social support and psychological resilience on social media addiction among university students. Universal journal of educational research.
6. Brahmi, M., Goswami, S., Vidushi, Kumar, J. (2023) Is Mindfulness Related to Socially Conservative Behaviours? Exploring Mindfulness’s Relationship with Schwartz’s Conservation Values. (pp. 154-155). 10th Annual Conference of Cognitive Science ACCS-X 2023, Association for Cognitive Science, Department of Cognitive Science, Indian Institute of Technology Kanpur (IITK) https://www.cgs.iitk.ac.in/user/accs10/files/ACCSX_Booklet.pdf
7. Chew, L. C., & Ang, C. S. (2023). The relationship among quiet ego, authenticity, self-compassion and life satisfaction in adults. Current Psychology, 42(7), 5254-5264.
8. Ertl, B., & Hartmann, F. G. (2019). The interest profiles and interest congruence of male and female students in STEM and non-STEM fields. Frontiers in Psychology, 10, 897.
9. Fox, J., & Weisberg, S. (2020). Car: Companion to Applied Regression. [R package]. Retrieved from https://cran.r-project.org/package=car.
10. Goswami, S., Brahmi, M., Suresh, G., Sharma, G., Arunkumar, G. (2023). An Indian Knowledge Perspective on Resilience: Examining the Role of Quiet Ego and Non-Attachment. Dr Arnav Bhavsar, Dr. Chayan, Dr. Amit Prasad, Dr. Kunal Mooley (Eds.), Mind, Brain, and Consciousness Conference, (pp. 164-349). Indian Knowledge System and Mental Health Applications (IKSMHA) Centre, IIT Mandi. https://iksmha.iitmandi.ac.in/mbcc/#proceedings
11. Graves, B. S., Hall, M. E., Dias-Karch, C., Haischer, M. H., & Apter, C. (2021). Gender differences in perceived stress and coping among college students. PloS one, 16(8), e0255634.
12. Gupta, K. & Agrawal, J. (2022). An empirical study of ancient wisdom. Effect of Anasakti (Non-Attachment) and Ahamkara (Ego) on well-being amongst Indians. European Journal of Mental Health, 17(3), 78–95. https://doi.org/10.5708/EJMH.17.2022.3.6
13. Hirani, S., Lasiuk, G., & Hegadoren, K. (2016). The intersection of gender and resilience. Journal of psychiatric and mental health nursing.
14. Hurley, L. N. (2018). The relationship between resilience, coping, and social media.
15. Hussin, H., Huzili, A. I., & Hamzah, M. R. (2021, May). The relationship of locus of control and social media use among undergraduate students. In AIP Conference Proceedings (Vol. 2339, No. 1). AIP Publishing.
16. Jamovi – open statistical software for the desktop and cloud. (n.d.). https://www.jamovi.org./
17. Jan, M., Soomro, S., & Ahmad, N. (2017). Impact of social media on self-esteem. European Scientific Journal, 13(23), 329-341.
18. Khoury, B., Sharma, M., Rush, S. E., & Fournier, C. (2015). Mindfulness-based stress reduction for healthy individuals: A meta-analysis. Journal of psychosomatic research, 78(6), 519-528.
19. Krendl, A. C. (2023). Changes in stress predict worse mental health outcomes for college students than does loneliness; evidence from the COVID-19 pandemic. Journal of American College Health, 71(1), 40-43.
20. Kuzmishin, C. B. (2018). Resilience in STEM students: An analysis of the demographic, intrapersonal, and interpersonal predictors of resilience.
21. Liu, G. (2022). Quiet Ego and Well-Being: The What, Why, and How–An
22. Investigation of the Implications of the Quiet Ego for Psychological Well-Being.
23. Mano, R. (2020). Social media and resilience in the COVID-19 crisis. Advances in Applied Sociology, 10(11), 454.
24. Raghavan, S., & Sandanapitchai, P. (2020). The relationship between cultural variables and resilience to psychological trauma: A systematic review of the literature. Traumatology
25. Rajeev, A., & Hebbani, S. (2020). Anasakti and resilience in older adults in south India: a correlation study. International Journal of Indian Psychȯlogy, 8(4).
26. R Core Team. (2021). R: A language and environment for statistical computing. R Foundation for Statistical Computing. https://www.R-project.org/
27. Rodriguez-Llanes, J. M., Vos, F., & Guha-Sapir, D. (2013). Measuring psychological resilience to disasters: are evidence-based indicators an achievable goal?. Environmental Health, 12(1), 1-10.
28. Sahdra, B. K., Shaver, P. R., & Brown, K. W. (2010). A scale to measure nonattachment: A Buddhist complement to Western research on attachment and adaptive functioning. Journal of Personality Assessment, 92(2), 116-127.
29. Sahdra, B., Ciarrochi, J., Parker, P., Marshall, S., & Heaven, P. (2015). Empathy and nonattachment independently predict peer nominations of prosocial behavior of adolescents. Frontiers in Psychology, 6. 1-.3389/fpsyg.2015.00263.
30. Samani, S., Jokar, B., & Sahragard, N. (2007). Effects of resilience on mental health and life satisfaction. Iranian Journal of psychiatry and clinical psychology, 13(3), 290-295.
31. Singh, K., & Raina, M. (2015). Development and validation of a test on Anasakti (non-attachment): An Indian model of well-being. Mental Health, Religion & Culture, 18(9), 715-725.
32. Skogen, J. C., Hjetland, G. J., Bøe, T., Hella, R. T., & Knudsen, A. K. (2021). Through the looking glass of social media. Focus on self-presentation and association with mental health and quality of life. A cross-sectional survey-based study. International journal of environmental research and public health, 18(6), 3319.
33. Snyder, C. R., & Lopez, S. J. (2001). Handbook of positive psychology. Oxford, England: Oxford University Press.
34. Tayal, N., Priya, M., & Sharma, N. (2020). Ahamkara and health: an empirical review. Journal of Indian Health Psychology.
35. The jamovi project (2023). jamovi (Version 2.3) [Computer Software]. Retrieved from https://www.jamovi.org
36. Throuvala, M. A., Griffiths, M. D., Rennoldson, M., & Kuss, D. J. (2020). Mind over matter: testing the efficacy of an online randomized controlled trial to reduce distraction from smartphone use. International journal of environmental research and public health, 17(13), 4842
37. Twenge, J. M. (2014). Generation me-revised and updated: Why today’s young Americans are more confident, assertive, entitled–and more miserable than ever before. Simon and Schuster.
38. Ventriglio, A., Torales, J., Castaldelli-Maia, J. M., De Berardis, D., & Bhugra, D. (2021). Urbanisation and emerging mental health issues. CNS spectrums, 26(1), 43-50.
39. Wagnild GM, Young (1993) HM. Development and psychometric evaluation of the Resilience Scale. J Nurs Meas;1:165–178.
40. Wagstaff, G. F., & Rowledge, A. M. (1995). Stoicism: Its relation to gender, attitudes toward poverty, and reactions to emotive material. The Journal of Social Psychology, 135(2), 181-184.
41. Wayment, H. A., & Bauer, J. J. (2008). Transcending self-interest: Psychological explorations of the quiet ego. In H. A. Wayment & J. J. Bauer (Eds.), Transcending self-interest: Psychological explorations of the quiet ego (pp. 3-17). American Psychological Association.
42. Wayment, H. A., & Bauer, J. J. (2014). The quiet ego scale: Measuring the compassionate self-identity. Journal of Happiness Studies, 15(1), 302-322.
43. Yeo, K. J., & Yap, C. K. (2023). Helping undergraduate students cope with stress: The role of psychosocial resources as resilience factors. The Social Science Journal, 60(1), 120-142.