Digital Detox or Digital Despair? Examining Fear of Missing Out (FoMO), Sleep Quality, and Mental Health among Hostel-Residing University Students in Punjab, India

 

Dr. Eric Kwasi Elliason ¹

 

¹ Research Fellow, Faculty of Allied Health Sciences, Desh Bhagat University, India   

 

1. INTRODUCTION

The rise of digital technologies globally impacts university students, particularly those living in hostels, as students across the world have started to live more technologically integrated lives Twenge et al (2012). In Punjab, India, the age group of 18 to 24 years exceeds smartphone usage of 85% Telecom Regulatory Authority of India (2023). Students living in hostels grapple with specific difficulties pertaining to their smartphones and other digital devices. This study focuses on the gaps pertaining to the relationship of Fear of Missing Out (FOMO), sleep quality, and mental health outcomes among students, creating an understanding of the digital wellbeing framework in residential educational institutions.

FOMO can be explained as being perpetually anxious about the activities others partake in, suggesting that one is not present during an experience that is enjoyable or rewarding Przybylski et al. (2013) Various studies connect FOMO to negative psychological impacts. Recent studies have demonstrated significant links between FOMO and sleep discontentment among young adults Scott and Woods (2019) due to factors such as increased alertness before bedtime and longer time to fall asleep Exelmans and Van (2017). Yet, such relationships have not been explored on the backdrop of university hostels, where there is communal living and relentless interaction may intensify these impacts Li et al (2020).

The hostel atmosphere in Punjab might accentuate digital stressors due to cultural and infrastructural considerations. WiFi is provided 24/7 with strong digital social connections in place, and thus students are perennially digitally active Sharma and Singh (2022). Early data indicates such conditions might enhance the “perfect storm” for sleep disruption, students reporting average bedtimes for the academic term as late as 2 AM Kaur and Dhillon (2023). The concern here is compounded by links associating sleep quality and academic performance Dewald et al. (2010).

Most of the available literature delving into FOMO and sleep are in relation to the West Alt (2010), leaving an entire dimension of Global South educational settings untouched. The few existing Indian works have centered on urban day scholars Gupta and Sharma (2020), thus overlooking hostel residents’ unique burdens. Additionally, no such study exists exploring presumed gender differences in FOMO -related sleep behaviors in this cultural context, despite established gendered social media usage patterns Fardouly et al. (2015).

The current study draws upon modern theoretical approaches to describe how digital behaviours such as psychological needs, social contexts interact to affect sleep and mental health quality for students at universities. One of the most significant models that can help understand the phenomenon known as Fear of Missing out (FOMO) can be described as Self-Determination Theory (SDT), developed by Deci and Ryan. Based on this model, FOMO tends to emerge in people who have not been able to satisfy their psychological needs like autonomy and independence or the feeling of being connected. In digitally connected environments like university hostels students often rely on social platforms to meet these requirements. However, instead of satisfying these needs, prolonged exposure to social updates could result in increased stress, an underlying feeling of being excluded and dependency which may ultimately affect sleeping quality and emotional well-being Ryan and Deci (2017), Przybylski et al. (2013).

Another significant conceptual lens can be found in the concept of Digital Wellbeing. This studies the impact of electronic involvement on health and overall productivity, as well as living quality. Researchers such as Sonia Livingstone have emphasized that digital well-being isn't just an individual issue, but rather determined by cultural, social and institutional influences. In university hostels in India, the communal online culture--characterized by always-online peer groups, constant messaging, and shared electronic routines--may reinforce FOMO and delay bedtime. The resulting conditions in the environment are what researchers have termed a digitally saturated lifestyle which can lead to poor sleep habits becoming normal and cause stress over the long term.

Recent studies on empirical research in India have begun to focus on the impact of using mobile phones on sleep and mental health especially in the case of students. Kaur and Dhillon (2023) discovered that screen time at night among hostel dwellers in Punjab was significantly linked with fatigue from school and increased signs of depression. Similar to this, Sharma and Singh (2022) noted that the continual usage of Instagram and WhatsApp particularly during the late hours, resulted in disturbed sleep patterns and an increase in anxiety among students at universities. These findings are consistent with general trends that show that late-night screen exposure, excessive scrolling, and hyper-connectivity can negatively impact sleep onset and depth Exelmans and Van (2017), Scott and Woods (2019).

Although these studies provide valuable information, they depend on quantitative indicators like frequency of use of devices, or the average duration of sleep. Least attention has been paid to qualitative factors such as emotion-based narratives and coping behavior as well as gendered characteristics of online interactions. This research fills this gap by combining quantitative methods and deep interviews. The mixed method approach allows students to explore sleeping issues, digital habits and mental health problems.

This broad view is relevant in situations such as India where accessibility to smartphones and internet-connected services is growing rapidly, but institutions that promote digital well-being are still limited. The study contributes to literature by highlighting the unique cultural aspects of life in hostels. These aspects can increase FOMO by fostering collective social routines and digital habits. The study also reveals the ways in which coping strategies differ between genders. Female students are more likely to utilize app timers, whereas men prefer to avoid chat for a short period of time.

 

2. Research Objectives

The study was guided by the following objectives:

2.1. Quantitative Phase

1)     To examine the relationship between Fear of Missing Out (FOMO) and sleep quality among hostel-resident university students.

2)     To determine the extent to which FOMO predicts symptoms of anxiety and depression.

3)     To explore gender differences in digital behaviors and their association with sleep and mental health.

2.2. Qualitative Phase

1)     To explore how students with extreme FOMO scores experience and interpret their digital habits, sleep patterns, and mental health.

2)     To identify culturally grounded coping strategies and environmental factors influencing digital wellbeing among hostel-residing students.

 

3. Methodology

3.1. Research Design

For this study, we used sequential explanatory mixed methods design Creswell and Creswell (2018) to determine the relationship between Fear of Missing Out (FOMO), sleep quality and mental health among hostel-residing university students in Punjab. The design had two components: first, a quantitative component that gathered prevalence and frequency data along with statistical analysis, then a qualitative component aimed at capturing the interpretation of students’ experiences.

 

3.2. Participants and Sampling

A stratified random sample of 450 students was drawn from the hostels of three major universities in Punjab. The criteria included active residents of university hostels, aged between 18-24 years, smartphone users (more than two hours a day), and no diagnosed sleep-related disorders. The sample was divided by gender (225 male students and 225 female students), academic year (150 from first year, second year, and final year students), and academic discipline (STEM disciplines 270 students and 180 were from humanities).

 

3.3. Quantitative Assessments

Three validated tools were applied to the quantitative phase.

1)     The Fear of Missing Out Scale (FOMO s) created by [3] is a 10-item scale measuring the intensity of FOMO which, in this study, displayed strong internal consistency (α = 0.89).

2)     Sleep quality was evaluated with the Pittsburgh Sleep Quality Index (PSQI) Buysse et al. (1989), a 19-item questionnaire targeting various aspects of sleep dis/order(s) which has a reliability coefficient (α) of 0.83.

3)     Mental health symptoms: depression, anxiety, and stress were evaluated using the Depression Anxiety Stress Scales – 21 (DASS-21) developed by Lovibond and Lovibond (1995). It consists of 21 items and demonstrates excellent internal consistency (α = 0.91)

 

3.4. Qualitative Component

For the qualitative phase, semi-structured interviews were conducted with 30 participants (15 male and 15 female) selected at the extreme ends of the FOMO scale scores, top and bottom 15%. The purpose of these interviews was to capture students' daily digital routines, sleep-related habits and challenges, coping strategies and impacts, and academic performance.

 

3.5. Data Collection Procedures

During class hours, students responded to online surveys which helped in the collection of quantitative data. For the qualitative part, there was an interview that was face to face and was most performed in private hostel common rooms by trained research assistants. The participants in the interview were recorded with consent and all recordings were transcriptions as well that were editable. Each interview session was captured from 45 minutes to 60 minutes.

 

4. Data Analysis

The analysis of quantitative data was carried out with SPSS version 26.0 which gave answers to the objectives through descriptive statistics, Pearson correlation analysis, and multiple regression analysis as well as independent samples t-tests. Braun and Clarke (2006) thematic analysis framework had been applied and NVivo 12 was used to analyze qualitative data. Patterns and themes were established using the constant comparative method and validating the interpretation was done through member checking.

 

5. Ethical Considerations

The participants who were willing to participate in the study were provided information sheets for them to sign and were allowed to withdraw at any given moment without being penalized. Destruction of data was carried out through the global method system with the aid of alphanumeric codes so anonymity was secured and confidentiality preserved.

 

6. Results

Table 1

Table 1 Participant Demographics (N=450)
Characteristic	Category	Frequency	Percentage
Gender	Male	225	50%
	Female	225	50%
Age	18-20 years	210	46.70%
	21-22 years	180	40.00%
	23-24 years	60	13.30%
Academic Year	First Year	150	33.30%
	Second Year	150	33.30%
	Final Year	150	33.30%
Discipline	STEM	270	60.00%
	Humanities	180	40.00%
Smartphone Use	2-4 hrs/day	135	30.00%
	4-6 hrs/day	180	40.00%
	>6 hrs/day	135	30.00%

 

The study sample comprised 450 hostel-residing students with balanced gender representation (50% male, 50% female) from three major universities in Punjab. Table 1 presents the complete demographic profile:

Key demographic observations:

1)     The sample showed balanced representation across academic years

2)     STEM students constituted a larger proportion (60%) of participants

3)     70% reported smartphone use exceeding 4 hours daily

4)     No significant gender differences existed in age distribution (χ²=1.24, p=0.54) or academic year (χ²=0.89, p=0.64)

Table 2

Table 2 Distribution of FOMO Scores among Participants (N = 450)
FOMO Level	Score Range	Frequency	Percentage
Low FOMO	10–24	72	16.00%
Moderate FOMO	25–34	198	44.00%
High FOMO	35–50	180	40.00%
Total	—	450	100%
Note: Categories based on Adapted Ranges from the FOMO Scale Przybylski et al. (2013).

 

The overall mean FOMO score was 34.2 (SD = 5.6), indicating generally elevated levels across the sample. As shown in Table 2A, 40 percent of participants scored in the high FOMO range, while only 16 percent fell into the low FOMO category. These figures suggest that a substantial proportion of students experience persistent FOMO symptoms.

Table 3

Table 3 Sleep Quality Distribution (PSQI Scores)
PSQI Category	Cut-off Score	Frequency	Percentage
Good Sleep	≤5	144	32.00%
Poor Sleep	>5	306	68.00%
Notably, 68% of participants met criteria for poor sleep quality, with average sleep duration of 5.8 hours (SD=1.2) on weeknights.

 

Table 4

Table 4 Pearson Correlations Between Study Variables
Variable	FOMO	Sleep Quality	Anxiety	Depression
FOMO	1	-0.52**	0.48**	0.43**
Sleep Quality	-0.52**	1	-0.56**	-0.51**
Anxiety	0.48**	-0.56**	1	0.72**
Depression	0.43**	-0.51**	0.72**	1
**p<0.01

 

7. Key findings

1)     Strong negative correlation between FOMO and sleep quality (r=-0.52)

2)     Sleep quality showed stronger association with anxiety than depression

3)     All correlations were statistically significant (p<0.01)

Table 5

Table 5 Hierarchical Regression Predicting Sleep Quality and Anxiety
Predictor	B	SE	β	t	p
Model 1: Sleep Quality
Constant	7.4	0.56	—	13.21	< .001
FOMO	-0.09	0.01	-0.42	-9.18	< .001
R² = .27, F(1, 448) = 84.30, p < .001
Predictor	B	SE	β	t	p
Model 2: Anxiety
Constant	2.85	0.42	—	6.79	< .001
FOMO	0.21	0.03	0.43	7.00	< .001
Sleep Quality	0.38	0.05	0.45	6.11	< .001
R² = .39, F(2, 447) = 70.45, p < .001

 

A hierarchical regression was conducted to determine the predictive power of FOMO on sleep quality and anxiety symptoms. In Model 1, FOMO significantly predicted sleep quality (β = -0.42, p < .001), accounting for 27 percent of the variance in PSQI scores. In Model 2, FOMO and sleep quality together explained 39 percent of the variance in anxiety scores, with both predictors contributing significantly. Follow-up subgroup analysis revealed stronger effects among female students, although a formal interaction test was not conducted.

 

8. Qualitative Results

Thematic analysis of 30 semi-structured interviews with students at the highest and lowest ends of the FOMO scale yielded three dominant themes. These themes provide insight into the daily realities, behaviors, and emotional experiences associated with digital life in hostel settings.

1)    The Vicious Cycle of Nighttime Connectivity

Participants commonly described a self-perpetuating cycle of digital engagement at night, especially before sleep. High FOMO scorers expressed a fear of being left out of social updates, which prompted repeated checking of phones late into the night.

“I know I should sleep, but I keep checking messages fearing I'll miss something important. Then I can't sleep, so I scroll more.” (Male, 20)

This behavior aligns with the quantitative finding that FOMO significantly predicted poor sleep quality (r = -0.52), highlighting how cognitive and emotional vigilance prolong bedtime routines. Students explained that even after turning off notifications, the anticipation of new messages disrupted sleep.

2)    Academic Impairment and Daytime Exhaustion

Sleep disruption had clear consequences for academic engagement. Participants reported chronic fatigue, missed lectures, and impaired focus due to late-night digital activity.

“My 2 AM Instagram sessions leave me sleeping through morning lectures.” (Female, 19)
“All-night gaming with hostel mates destroys my next-day concentration.” (Male, 21)

These narratives reinforce the study’s regression findings where FOMO and sleep quality jointly explained 39% of the variance in anxiety symptoms. Poor sleep was not only a physiological issue but also contributed to academic and emotional stress, creating a loop of performance anxiety, further reinforcing late-night digital engagement as a coping mechanism.

3)    Gendered Digital Coping Strategies

Gendered patterns were evident in how students managed or failed to manage their digital habits. Female participants often reported passive scrolling on appearance-focused content, while males were more involved in interactive group activities such as gaming and chatting.

“I’ve started using app timers for social media after 11 PM. It helps a little.” (Female, 20)
“I mute group chats during exams but always check back later.” (Male, 22)

These insights correspond with the moderation effect observed in the quantitative data, where females showed stronger correlations between FOMO and sleep problems. While both groups struggled with self-regulation, the content they engaged with and the tools they used to cope differed, suggesting a need for gender-sensitive intervention strategies.

 

 

 

9. Summary of Qualitative Insights

These themes confirm and enrich the statistical findings by offering nuanced understandings of how FOMO, sleep, and anxiety unfold in real life. They illustrate that:

·        FOMO is not a static trait but a lived experience shaped by digital environments

·        Sleep disruption is reinforced by digital culture and group norms within hostels

·        Coping is attempted but often insufficient without structural boundaries (e.g., quiet hours or app restrictions)

 

10. Discussion

The study results on the relationships of FOMO, sleep quality, and mental health concerning hostel residing university students from Punjab, India, uncovered critical cultural and gender-specific nuances. The moderate prevalence rates of hostel students’ poor sleep quality (68%) align with, but exceeds global estimates ranging between 40-60% for sleep problems among university students Hershner and Chervin (2014). Hostel environments seem to aggravate sleep disturbances. This increase effect is most likely due to the unparalleled blend of Indian university hostels' digital connectedness and living space Sharma and Singh (2022)

The correlation between FOMO and sleep quality is arguably the greatest negative correlation among the constructs with an r=-0.52. It confirms and builds on prior work linking the problematic use of smartphones with sleep-related issues Exelmans and Van (2017). This emerged from our qualitative data as an interplay whereby FOMO related social media activity at night leads to lack of sleep, thereby increasing vulnerability to FOMO experiences the next day. These findings are consistent with the cognitive behavioral model of insomnia Harvey (2002), indicating that some modern day digital behaviors do act as perpetuating factors for sleep issues.

The most notable moderating effect was observed in the gender difference, where female students tended to have stronger associations between FOMO and sleep complications. This finding supports previous research highlighting women’s vulnerability to social media distress Fardouly et al. (2015) while adding the disturbing new understanding that the effects may be harsher in residential academic environment. The qualitative data indicates that this gap might be explained by different patterns of social media use, where women reported passive consumption of appearance-centric material, unlike men who described active gaming and chatting.

These findings expand the work done in Western contexts on the relationship of FOMO, sleep quality, and anxiety by showing that together they account for 39% of the variance in anxiety symptoms Scott and Woods (2019) but this present study was done in an Indian university setting. This finding aligns with proposed frameworks discussing FOMO’s impact on mental health through several avenues, including disrupted sleep and negative self-related thoughts Elhai et al. (2016)

Importantly, our qualitative analysis suggests these phenomena take on culture-specific forms. Many participants pointed out the "hostel culture" of the Punjab universities, where social groups are always in constant digital contact through WhatsApp and regularly check each other's Instagram updates. This context seems to perpetuate and even support the very tendencies that aggravate FOMO and sleep issues, making it harder to change.

The study adds to the corpus of knowledge about coping strategies. Previous research has mostly focused on individual-level interventions, such as mindfulness apps; however, our participants pointed to the need for more systemic changes within the hostels, like enforced quiet hours or limited WiFi availability. This adds to the debate on the need for more ecological approaches to digital wellbeing Livingstone et al. (2017), indicating that individual self-regulation might not be effective in isolation from surrounding changes.

 

11. Study Strengths and Limitations

Strengths

One of the main strengths of this research lies in its mixed method design which provides a thorough comprehension of both quantifiable and personal elements associated with Fear of Missing Out (FOMO) and its effect on mental and sleep. Through the combination of validated instruments such as the FOMO Scale and the Pittsburgh Sleep Quality Index (PSQI) as well as the Depression Anxiety Stress Scales (DASS-21) along with deep qualitative interviews, this study has the ability to capture statistical trends as well as actual experiences of students living in hostels.

The sampling method used was stratified and balanced to ensure that there was equal representation of gender and academic year as well as academic discipline. This increases the relevancy and practicality of the findings in the university student hostel population of Punjab. In addition, the study provides novel insights by analyzing digital behaviours within the context of the cultural and institutional context of Indian hostels at universities. This is often lacking in existing research.

Another advantage is the emphasis on gender-specific behaviors, which showed significant differences in female and male students' interactions and respond to FOMO -related digital behavior. The inclusion of validation for participants during the qualitative stage also added credibility and reliability to the findings.

 

12. Limitations

While it is a valuable contribution to the field, the study has a number of drawbacks. The first is that its cross-sectional nature of quantitative components makes it difficult to establish causal links between sleep quality, FOMO and mental health effects. Longitudinal research is better suited to monitoring changes and determining causality over time.

The second reason is that the data collection was restricted to three universities in the Punjab region. This could limit the generalizability of the results to students at universities in other locations or contexts. Different institutional policies or expectations regarding culture and digital infrastructure could create different outcomes and experiences elsewhere.

Thirdly, relying on self-reported information can result in biases like recall bias and the tendency for people to react in socially acceptable ways. Although the methods employed are well-tested, they are still subject to the individual's perception and report accuracy.

In addition, while the study looked at digital habits in detail, it did not look into other factors that are relevant, such as educational performance, physical issues or socio-economic background that can also impact sleep quality and mental health outcomes.

Future research should employ longitudinal and experimental designs that include a wider range of student environments, and also explore the effects of environmental and systemic factors. This will help to develop a more comprehensive and actionable understanding of student digital wellbeing.

 

13. Conclusion

This study reveals the damaging effects of Fear of Missing Out (FOMO) on the sleep and mental health of university students living in hostels in the Punjab region of India. It was noted that a staggering 68% of participants reported having poor sleep, a phenomenon strongly correlated with high levels of FOMO (M = 34.2), especially amongst female students. The circulation of digital activities and disturbances of sleep reinforces a self-contained cycle which heightens anxiety and makes academic performance even more challenging.

The study contributes to the existing literature by explaining how cultural constituents such as the ‘hostel culture’ of Punjab also serve to aggravate the situation. Other gender differences in the digital world, like females focusing more on looks-related social comparisons and males on gaming or hopping into chats, warrant the call for bespoke solutions.

Appeals to policy from this study focus on the development that needs to be applied at an institutional level like a ban on internet connected devices (digital curfews), a reinforced focus on sleep hygiene, and even quiet time zones in hostels. Further areas of study should include looking at the long-term impact of such interventions as well as measuring their effectiveness. Finally, to mitigate the FOMO -related sleep disruption, doing so will require changing personal behaviors while simultaneously addressing system-wide policies that steer students towards better digital engagement within living-learning environments.

 

CONFLICT OF INTERESTS

None. 

 

ACKNOWLEDGMENTS

None.

 

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