Predictors of Sleep Quality Among Emerging Adults in India: Exploring the Role of FoMO,Nomophobia and Evening Chronotype

Abstract

Background

The increasing integration of mobile technology into daily life has raised concerns about its effects on sleep quality and mental health, particularly among emerging adults. The interplay between evening chronotype, nomophobia (no mobile phone phobia), and FoMO is crucial to understanding these impacts, especially in the digital age. The current study investigated whether nomophobia mediates the relationship between evening chronotype and sleep quality and between chronotype and FoMO with sleep quality in emerging adults.

Methods

A cross-sectional survey was conducted among N = 501 emerging adults (Males = 144, Females = 356), aged 18–25 (21.2 ± 1.85 years), after approval from the Institutional Review Board. The participants completed measures of demographic information, sleep quality, FoMO, nomophobia and chronotype. Data were analysed using Jamovi and Statistical Package for the Social Sciences (SPSS).

Results

Significant negative associations were found between evening chronotype, FoMO, and sleep quality, indicating that individuals with an evening chronotype and those with higher FoMO tend to experience poorer sleep. Nomophobia significantly mediated the relationships between evening chronotype and sleep quality (Indirect estimate = −0.00896, p < .05), and between FoMO and sleep quality (Indirect estimate = 0.0185, p < .05), amplifying these negative impacts.

Conclusion

The study highlights nomophobia’s critical role in exacerbating the effects of evening chronotype and FoMO on sleep. Interventions targeting nomophobia and digital habits could improve sleep and mental health among emerging adults.

Keywords

Evening chronotype nomophobia fear of missing out sleep quality emerging adults

Introduction

The period of life between 18 and 25, known as emerging adulthood, marks a critical phase when individuals make important decisions related to education, career paths, and personal relationships. In today’s digital world, young adults are especially at risk for sleep problems because of their continuous use of smartphones and other electronic devices.¹ Their biological clocks often do not match up with the schedules imposed by society, creating a sense of mismatch as described in the Social Jetlag Theory.² Moreover, many individuals are exposed to screens late at night, and it disrupts their natural sleep cycles in two major ways. First, melatonin, which helps in the regulation of sleep, gets restricted by the blue light emitted from the screen.³ Second, the digital stimulation through endless scrolling through social media keeps the brain in a state of high alertness, making it difficult for people to relax and have a restful sleep. In India, this has been a challenge, where the young adults make up roughly 32% of the population (2011 Census), and the prevalence of sleep problems is even seen to be higher among the adolescents and young adult males (20.3% and 29%) and females (36.8% and 48.9%).⁴

FoMO and Sleep Quality

Building on this digital-behaviour backdrop, a psychological phenomenon called Fear of Missing Out (FoMO) has gained considerable spotlight in recent times. It is an individual’s anxiety about missing out on socially and individually satisfying experiences that others have which is characterised by a desire to stay connected to what others are doing,⁵ and has emerged as a prevalent and significant psychological phenomenon in the digital age, particularly among emerging adults who are heavily engaged with social media and digital technologies.^{6, 7} Examining FoMO during this developmental period can provide insights into its role in shaping identity development, social relationships and comparisons, and real-time decision-making processes. Not surprisingly, individuals who experience FoMO at higher levels tend to feel stress and fear when unable to connect with social media.⁸

Consequently, problematic use of smartphones has been attributed to time banishment, such as smartphone use that transcends to delay in bedtime due to surfing the content of the media, which might be because of FoMO, provoking arousal, and interfering with the ability to fall asleep. Further, the smartphone has a biological impact through light emitted from the device in the blue spectrum, leading to melatonin suppression and making it harder to fall asleep and get non-restorative rest.⁹ This poor sleep quality further leads to emotional and psychological issues, deteriorating emotional resilience, leading to a feedback loop in which heightened FoMO additionally derails healthy sleep patterns.^{10, 11}

Although FoMo has received growing attention, its impact on sleep quality, particularly among emerging adults in India, remains underexplored. This gap underscores the importance of understanding the relationship between FoMO and sleep quality, given their significant implications on mental health, cognitive development, and overall well-being.

Evening Chronotype and Sleep Quality

Beyond psychological drivers, one’s chronotype adds another layer to sleep quality. Sleep is a physiological phenomenon as well as a behavioural process that affects the growth, cognitive development, learning, and good health of adolescents.¹² According to the US National Sleep Foundation, the required sleep for emerging adults is around 7–9 hours per night to promote basic optimal health and development.^{13, 14} Chronotype is our natural body clock, which follows a 24 hour cycle. We have different natural preferences for when we feel most awake and when we prefer to sleep. It is the physiological process that involves synchronising the circadian cycle. This synchronisation is characterised by the earlier timing of synchronisation in early chronotypes and the delayed timing in evening types. It determines whether you are naturally a morning person (lark), a night person (owl), or somewhere in between.¹⁵

Notably, evening chronotypes are more prone to smartphone-related problems and, in turn, sleep disturbances.^{16, 17} Moreover, genetics play a role,¹⁸ and lifestyle factors, such as higher rates of smoking and alcohol use cluster within evening types.¹⁹ Chronotypes remain consistent but may shift with age. People often stay up late when young but become morning-oriented as they age.²⁰ These disruptions often interfere with the body’s natural mechanisms that govern sleep, altering sleep architecture, as explained by the sleep-wake regulation theory, which emphasises the role of both circadian rhythm and homeostatic sleep pressure in maintaining healthy sleep.²¹

On the contrary, it was found that 64% of India’s urban population wakes up before 7 am and 61% sleep less than 7 hours a day, indicating the need to prioritise quality sleep more than ever, highlighting the urgency of prioritising sleep quality.¹¹

Nomophobia as a Mediator

Along with FoMO, an even more acute smartphone-related anxiety, nomophobia, an abbreviation for ‘no mobile phone phobia’, is the term derived in 2008, used to describe the anxiety, distress, or panic that people experience when they are unable to use or access their smartphones.^{22, 23} In one way, high levels of nomophobia result in more sleep problems, particularly sleepiness and the duration of sleep.²⁴ Smartphone use may have an impact on physiological elements that influence brain function, such as melatonin rhythm and sleep quality, especially in the pineal gland. Exposure to electromagnetic fields in the evening may cause altered cerebral blood flow and brain electrical activity.^{25, 26}

In the study, Nomophobia mediates the relationship between FoMO, evening chronotype, and sleep quality by exaggerating the negative effects of digital dependency on sleep patterns. Nomophobia’s role as a mediator, in particular, highlights how anxiety about being disconnected perpetuates prolonged nighttime phone use, leading to disrupted sleep quality among emerging adults.

Purpose and Background

Quality sleep is vital for mental, physical, and emotional health.²⁷ Factors like evening chronotype can influence sleep patterns, while technology-driven issues such as nomophobia and FoMO disrupt sleep and impact psychological well-being.²⁸ This research aims to better understand how these factors collectively impact sleep behaviour in the context of modern technology use. By exploring the interactions between these elements, the study hopes to offer valuable insights for developing strategies to improve sleep hygiene and promote healthier relationships with technology. The specific goal of the study is to investigate how nomophobia functions as a mediator in the interaction between evening chronotype, FoMO, and sleep quality, indicating that FoMO and an individual’s evening chronotype influence on sleep quality is amplified by anxiety about being disconnected from one’s phone.

Objectives

To examine the relationship between emerging adults’ evening chronotype and their quality of sleep.

To analyse the connection between sleep quality and FoMO.

To examine how nomophobia functions as a mediator in the relationship between evening chronotype, FoMO, and sleep quality.

Hypothesis

The present study aimed to further explore the relationship between sleep quality and nomophobia by examining the associations between nomophobia, FoMO, evening chronotype, and sleep quality. The proposed associations are both theoretically and empirically conceptualised.

H₁: Evening chronotype is negatively associated with sleep quality.

H₂: FoMO is negatively associated with sleep quality.

H₃: Nomophobia mediates the relationship between evening chronotype and sleep quality.

H₄: Nomophobia mediates the relationship between FoMO and sleep quality.

Methodology

Ethics

Ethical approval from the Institutional Review Board (IRB), Centre for Research at CHRIST (Deemed to be University), Delhi NCR, for the study was received after the ethical aspects were assessed. Informed consent was obtained from all participants for voluntary participation and that the data might be used for publication purposes. Further ensuring their understanding of the study’s purpose, procedures, and their right to withdraw at any time. Confidentiality was maintained throughout the study.

Research Design

This study adopted a quantitative, cross-sectional survey design to assess the relationships between evening chronotype, nomophobia, FoMO, and sleep quality among emerging adults. Data were collected using standardised questionnaires to examine these variables and their interconnections.

Sample

A total of 501 emerging adults participated in the study, comprising 144 males (28.74%), 356 females (71.05%), and one individual identifying as other (0.19%). The participants had a mean age of 21.04 years and were selected from various regions across India to ensure demographic diversity. This distribution accurately represented the emerging adult demographic aged 18–25.

Inclusion Criteria

Participants in the study met specific inclusion criteria. They were required to be between 18 and 25 years of age, be smartphone users, and possess fluency in either English (to complete the survey) or Hindi. Additionally, all participants were Indian citizens, ensuring cultural and contextual relevance to the study.

Exclusion Criteria

The exclusion criteria disqualified individuals who fell outside the age range of 18–25 years, faced language barriers that prevented fluency in either English or Hindi, or were not Indian citizens. These criteria ensured a focused and relevant sample for the study’s objectives.

Sampling Techniques

Convenience sampling was employed to select participants for the study. This method ensured timely and efficient data collection.

Data Collection

Participants provided demographic information, including their age, gender, and area of residence. Additionally, data on their daily phone screen time and phone usage before bedtime were collected. Sleep-related factors such as average sleep duration and the amount of catch-up sleep they typically get on weekends were also assessed. These variables were gathered to better understand potential relationships between phone usage patterns and sleep habits.

Measures/Tools

The Nomophobia Questionnaire (NMP-Q): The NMP-Q is a 20-item tool assessing four key aspects of nomophobia: (a) inability to communicate (six items), (b) loss of connectedness (five items), (c) inability to access information (four items), and (d) relinquishing convenience (five items). Items are rated on a seven point Likert scale (1 = strongly disagree, 7 = strongly agree). Total scores range from 20 to 140, with higher scores indicating more severe nomophobia. The scoring guidelines are: ≤20 (no nomophobia), 21–59 (mild), 60–99 (moderate), ≥100 (severe). The tool has high internal consistency (Cronbach’s alpha = 0.95) and has been validated across multiple cultures (e.g., Chinese and Iranian populations).²⁹

The Morningness–Eveningness Questionnaire (MEQ): MEQ is a 19-item self-report tool used to assess chronotype. Scores below 42 indicate evening preference, 42–58 indicate intermediate preference, and above 58 indicate morning preference. The scale combines Likert-type and time-scale questions, resulting in a global score that categorises individuals as either morning, intermediate, or evening types.³⁰ The tool has high internal consistency (Cronbach’s alpha = 0.742).

Pittsburgh Sleep Quality Index (PSQI): The Pittsburgh Sleep Quality Index (PSQI) is a widely used tool to assess sleep quality over one month and is commonly used to evaluate sleep patterns and identify sleep disorders.³¹ It consists of 19 self-reported items across seven components, including subjective sleep quality, sleep latency, sleep duration, and daytime dysfunction. The total score ranges from 0 to 21, with scores above five indicating poor sleep quality. The PSQI has moderate internal consistency reliability (Cronbach’s alpha = 0.538) in this study. Thus, results based on the incorporation of PSQI values have been interpreted with caution.

Fear of Missing Out (FoMO) Scale: The FoMO Scale contains 10 items that assess anxiety about missing out on rewarding experiences, particularly through social media. It was developed through qualitative interviews and psychometrically validated through factor analysis, offering insights into the social comparison and well-being of individuals in the digital age.³² FoMO scale had high internal consistency (Cronbach’s alpha = 0.841).

Data Analysis

The data was analysed using Jamovi statistical software. Correlation, linear regression, and mediation analysis were employed to investigate the relationships between nomophobia, evening chronotype, and FoMO, specifically focusing on examining nomophobia as a mediator in these relationships. The analysis also explored the combined impact of these psychological factors on sleep quality.

Results

Discussion

Sleep Quality and Its Correlates

The results of this study reveal significant correlations between sleep quality and several key variables, including FoMO, nomophobia, and chronotype. As shown in Table 1, nomophobia and FoMO are positively correlated, while evening chronotype is negatively correlated with these variables and sleep quality.

Fear of Missing Out (FoMO) and Sleep Quality

The observed positive correlation between FoMO and poor sleep quality (r = 0.272, p < .001) aligns with previous research suggesting that individuals with higher levels of FoMO may experience greater difficulty in achieving restful sleep. This relationship could be attributed to increased anxiety and cognitive arousal associated with the fear of missing social experiences or information, potentially leading to delayed sleep onset and reduced sleep duration. This dependency is due to the constant desire to stay connected and monitor social networks for updates.^{33, 34} Curiosity toward the lives of others also heightens the addictive nature of social media usage, further worsening FoMO and disturbed sleep. Being bombarded with excessive information through the phone could lead to negative aspects, a dimension of distress encompassing emotions like anger, fear, and guilt. This can worsen FoMO and smartphone addiction, ultimately leading to poor sleep.³⁵ The results of a study conducted showed that an excessive concern about missing out on social events can result in delaying one’s sleep to catch up on posts on social media and waking up in the middle of the night to respond to messages and racing thoughts before going to bed, leading to fragmented sleep and reduced sleep time.³⁶ Another study explored how FoMO, anxiety, and sleep issues are interconnected among college students. Their findings suggested that students with higher levels of FoMO took longer to fall asleep and were generally less satisfied with their sleep quality.³⁷ Interventions should aim at decreasing the dependence on social media and encouraging digital well-being to eventually improve the sleep habits of young adults. Table 2 presents the model fit indices of the regression analysis, indicating a moderate relationship between predictors and sleep quality.

Nomophobia and Sleep Quality

The significant positive correlation between nomophobia and poor sleep quality (r = 0.021, p < .001) highlights the potential negative impact of excessive smartphone use and attachment on sleep patterns. This finding supports existing literature on the detrimental effects of technology use on sleep hygiene, possibly due to factors, such as blue light exposure, psychological stimulation, and disrupted bedtime routines. These results of the study are in accordance with the research studies, which indicate that if an individual uses excessive mobile phones or fears of appearing anxious or unable to reach or use mobile phones, individuals will experience sleep deprivation or lack of sleep.³⁸ Furthermore, a study found that self-reported smartphone addiction is prevalent among young adults attending university and is associated with later usage times and total duration of use.³⁹ These studies imply that not just the duration of smartphone use but nomophobia significantly impacts sleep quality. Table 3 displays the regression coefficients, highlighting significant contributions of FoMO and evening chronotype to sleep quality, whereas nomophobia showed a non-significant effect.

In addition to these findings, various mechanisms have been proposed to explain the detrimental impact of smartphone use on sleep. Studies have shown that using a phone at night reduces sleep duration and increases anxiety and emotional arousal.^{40, 41} A study revealed that nomophobia is associated with sleep quality, and the escalation of phone addiction may lead to a deterioration in general health, potentially impacting academic performance among health students.⁴² This calls for the need for interventions to help the young adults limit their phone usage, helping them to improve sleep quality, and consequently, better health. Table 4 presents the mediation analysis, showing both direct and indirect significant effects of FoMO on sleep quality through nomophobia.

Evening Chronotype and Sleep Quality

The correlation between evening chronotype and poor sleep quality (r = −0.214, p < .001) observed in this study, which is significant, aligns with previous research on circadian rhythms and sleep patterns. The sleep-wake regulation theory, which states that disrupted natural circadian rhythms can lead to sleep-related issues, including sleep insufficiency, declined sleep quality, and excessive daytime sleepiness, is supported by additional empirical studies.⁴³ Moreover, referring to the Social Jetlag Theory, a delayed sleep phase makes it challenging for individuals with evening chronotypes to get to school or work on time. As a result, those with an evening preference are often forced to reduce their sleep duration on weekdays, affecting subjective sleep quality.⁴⁴ A study explained how students with evening chronotypes exhibited poorer sleep quality than those with morning or intermediate chronotypes. As shown in Table 5, evening chronotype also demonstrated a significant mediated effect on sleep quality via nomophobia, with both paths being statistically significant.⁴⁵

Regression Analysis Findings

The regression analysis results indicate that evening chronotype and FoMO are significant predictors of sleep quality. Nomophobia was also shown to affect sleep quality to an extent. R, the correlation coefficient’s value being 0.361, shows the establishment of a relationship between the observed and expected values of the Global PSQI Score, indicating a moderate association between the predictors and sleep quality. R², the coefficient of determination, with a value of 0.130, indicates that chronotype, FoMO, and nomophobia combined can explain only 13% of the variance of the Global PSQI Score. This is a modest effect, which implies that although these variables play a role in affecting sleep quality, they are not the only factors that can impact the quality of sleep. Figure 1 illustrates the conceptual model of the study, demonstrating how evening chronotype and FoMO impact sleep quality both directly and indirectly through nomophobia.

Figure 1.

Note: This figure illustrates the proposed model of the current study. Evening chronotype and FoMO relate to sleep quality via nomophobia.

Evening Chronotype as a Predictor

The significant predictive power of evening chronotype on poor sleep quality (Estimate = −0.0739, SE = 0.01420, t = −5.21, p < .001) underscores the importance of considering individual circadian preferences in understanding sleep patterns. This finding may have implications for developing targeted interventions to improve sleep quality among evening-type individuals.

FoMO and Nomophobia as Predictors

The predictive roles of FoMO (Estimate = 0.0787, SE = 0.01951, t = 4.03, p < .001) and nomophobia (Estimate = 0.0115, SE = 0.00645, t = 1.78, p = .076) in sleep quality highlight the growing influence of digital technology and social media on sleep behaviours. These results imply that improving young individuals’ sleep quality may require addressing psychological aspects of technology use.

Mediation Analyses

The mediation analyses reveal that nomophobia plays a significant role in mediating the relationships between FoMO and sleep quality and between evening chronotype and sleep quality. Mediation analysis was carried out in this study to ascertain whether nomophobia explains the link between FoMo and evening quality in influencing sleep quality. This can help in understanding how these factors affect sleep and can facilitate targeted strategies to address nomophobia, thereby improving sleep quality.

FoMO-Nomophobia-Sleep Quality Pathway

After the massive entrance of smartphones into our lives, the negative consequences of FoMO bring further proof that supports the existence of this type of addiction, which leads people to spend a lot of time on social networks out of FoMO. FoMO and nomophobia together create a cycle of smartphone overuse driven by the desire to stay connected to social interactions and events.⁴⁶ This increased reliance on smartphones, in turn, disrupts sleep quality.

Several studies have confirmed how smartphone use leads to poor sleep quality.^{47, 48} The negative impact of nighttime phone use and sleep is mediated by being the mediator, not only standing as a direct link between FoMO and poor sleep quality, but also amplifying the anxiety and psychological stimulation that contributes to disturbances.

Evening Chronotype-Nomophobia-Sleep Quality Pathway

The mediating role of nomophobia in the relationship between evening chronotype and sleep quality indicates that evening-type individuals may be more prone to excessive smartphone use, potentially exacerbating sleep difficulties. According to the findings of the current study, people with an evening chronotype score higher for nomophobia and poor sleep quality than those with the morning and intermediate types.

The study suggested that if the individual has an evening chronotype, they might be at greater risk for both nomophobia and sleep problems. Additionally, there exists a statistically significant association between nomophobia and insomnia, nomophobia and the evening chronotype, and nomophobia and screen time.⁴⁹ Moreover, the importance of reducing smartphone use before sleep to improve sleep hygiene and overall well-being, especially among students, has been emphasised in previous studies.⁵⁰

Implications

The findings from this study have strong implications and significant important for understanding and enhancing sleep quality among emerging adults. The study reveals the necessity of performing intervention programs that will address the impact of FoMO, nomophobia, and evening chronotype on sleep quality. The research identified an association between evening chronotype and nomophobia; thus, future studies should include targeted interventions such as digital hygiene practices, such as a limit on app use, screen time restrictions, which could be helpful to reduce nomophobia levels, especially among people with evening chronotype. Further promoting sleep-aware user experience, including sleep tracking, and bedtime reminders, can be incorporated for better sleep quality. Strategies promoting circadian-aligned routines are essential for evening chronotypes. Incorporation these interventions by mental health professionals in educational institutes can aid in a holistic understanding of sleep disruptions among emerging adults residing in India.

Limitations and Scope for Future Research

While the present study examined the impact of India’s evening chronotype, nomophobia, and FOMO on the sleep quality of emerging adults in India, several limitations emerged that indicate new avenues for future research. The findings of this study need to be interpreted with a few important limitations in perspective. The cross-sectional design limits the ability to understand the causal relationship between variables; future longitudinal studies would help gain a better understanding of these dynamics. Convenience sampling limits the external validity of the findings; therefore, for the sake of higher external validity, future research should aim to collect larger, more diverse samples. Employing objective measures would get around the bias that can be brought in by self-reported data, such as social desirability or recall bias, that would undermine accuracy. The measures that would be used to overcome this limitation could be qualitatively tested in future studies. By comparing variations between the high-scoring and low-scoring groups on the nomophobia scale, further research can help qualitatively assess the factors influencing sleep quality. This would help gain a better insight into the influence of mobile phone addiction on sleep by shedding light on the dimensions of nomophobia that are most relevant to sleep disturbance. Other lifestyle variables, such as diet, caffeine use, academic stress, physical activity, and study routines were not considered in this study, even though they may significantly influence sleep quality. Last, it is important to note that the PSQI, which was used in the study as a measure of sleep quality, showed moderate internal consistency (Cronbach’s alpha = 0.538) in this sample. Despite this limitation, we chose the PSQI in the present study because it is the most popular subjective self-report measure for evaluating sleep quality. It is not only used as a gold standard for convergent validity in sleep research, but also has widespread acceptance and validation in both clinical and non-clinical populations.⁵¹

Table 1.

Correlation Between Variables.

		NMPQ	FoMO	MEQ	PSQI
NMPQ	Pearson’s r	–
	df	–
	p value	–
FoMOs	Pearson’s r	0.426***	–
	df	499	–
	p value	<.001	–
MEQ	Pearson’s r	−0.171***	−0.214	–
	df	499	499	–
	p value	<.001	<.001	–
PSQI	Pearson’s r	0.201***	0.272	−0.279	–
	df	499	499	499	–
	p value	<.001	<.001	<.001	–

Notes: Table 1 presents correlations among psychological variables, revealing significant positive correlations between nomophobia and FoMO, and negative correlations between evening chronotype and the other variables, all significant at p < .001.

*p < .05.

**p < .01.

***p < .001.

Table 2.

Linear Regression.

Model	R	R²
1	0.361	0.130

Note: Table 2 reports the correlation coefficient and the coefficient of determination of the model of the study.

Table 3.

Model Coefficients: Global PSQI Score.

Predictor	Estimate	SE	t	p
Intercept	7.3343	0.96103	7.63	<.001
MEQ	−0.0739	0.01420	−5.21	<.001
FoMOs	0.0787	0.01951	4.03	<.001
NMPQ	0.0115	0.00645	1.78	.076

Note: Table 3 reports the linear regression results predicting the Global PSQI Score, indicating significant effects for evening chronotype and FoMO, while nomophobia is not statistically significant for regression, but it does play a role in affecting sleep quality.

Table 4.

Mediation Analyses.

Effect	Estimate	SE	Z	p
Indirect	0.0185	0.00857	2.16	.031
Direct	0.0948	0.01970	4.81	<.001
Total	0.1133	0.01792	6.33	<.001

Note: Table 4 shows mediation analysis results, with FoMO as the predictor and nomophobia as the mediator, indicating both significant direct and indirect effects on sleep quality.

Table 5.

Mediation Analysis.

Effect	Estimate	SE	Z	p
Indirect	−0.00896	0.00335	−2.68	.007
Direct	−0.08303	0.01419	−5.85	<.001
Total	−0.09198	0.01417	−6.49	<.001

Note: Table 5 presents mediation analysis with evening chronotype as the predictor and nomophobia as the mediator, highlighting significant negative effects on sleep quality for both direct and indirect pathways.

Conclusion

The study examines how nomophobia, FoMO, and evening chronotype influence sleep quality among emerging adults with a focus on understanding nomophobia as a mediating role. Findings confirmed the proposed hypotheses, demonstrating that nomophobia significantly mediates the relationship between FoMO and sleep quality and between evening chronotype and sleep quality. The strong mediating role of nomophobia implies that mobile phone-related anxiety plays a central role in the experience of poor sleep quality among emerging adults in India. The influence of FoMO and nomophobia, both originating from digital dependency and anxiety, further worsens sleep quality by increasing cognitive arousal and delaying sleep onset. Evening chronotype, which can be described as a natural ability to remain active during the night, also poses a problem because of its prolonged smartphone use, driven by the fear of disconnection. It is often linked to sleep hygiene. These findings underline the complex interplay of psychological, technological, and biological variables, namely FoMO, nomophobia, and evening chronotype, respectively, in sleep disruption among emerging adults, pointing towards the requirement of tailored interventions focusing on technology-free practices before going to bed, reducing their frequency of social media use, and promoting better sleep hygiene.

Footnotes

Authors’ Contribution

Ms. Sabornee K. Basu and Dr. Payal Sharma planned, supervised and assisted in the statistical evaluation of the study. They provided oversight and guidance to Ashi Singh, Diya Makhija, Pavana Raghu, Prapti Mohanty, and Shradha Mourya, who were actively involved in data collection, data analysis and drafting the manuscript. Ms. Sabornee K. Basu and Dr. Payal Sharma also handled manuscript editing and proofreading. All authors read and approved the final manuscript.

Data Availability

The data that support the findings of this study are not publicly available. Access to the data can be provided upon request, but permission must first be obtained from the Research Committee at CHRIST (Deemed to be University), Delhi NCR, India.

Statement of Ethics

Ethical approval for the study was granted by the IRB, Centre for Research at CHRIST (Deemed to be University), Delhi NCR.

Declaration of Conflicting Interests

The authors declared no potential conflicts of interest with respect to the research, authorship, and publication of this article.

Funding

The authors received no financial support for research, authorship, and/or publication of this article.

Patient Consent

Informed consent was obtained from all participants, ensuring their understanding of the study’s purpose, and procedures, and the right to withdraw at any time.

ORCID iD

Prapti Mohanty

References

Bruce

, Lunt

and McDonagh

JE.

Sleep in adolescents and young adults. Clin Med 2017; 17(5): 424–428.

Wittmann

, Dinich

, Merrow

. Social jetlag: Misalignment of biological and social time. Chronobiol Int 2006; 23(1–2): 497–509.

Silvani

, Werder

and Perret

The influence of blue light on sleep, performance and wellbeing in young adults: A systematic review. Front Physiol . 2022; 13: 943108.

Maurya

, Muhammad

, Maurya

, . The association of smartphone screen time with sleep problems among adolescents and young adults: Cross-sectional findings from India. BMC Public Health 2022; 22(1):1686.

Przybylski

, Murayama

, DeHaan

. Motivational, emotional, and behavioral correlates of fear of missing out. Comput Human Behav 2013; 29(4): 1841–1848.

Jabeen

, Tandon

, Sithipolvanichgul

. Social media-induced fear of missing out (FoMO) and social media fatigue: The role of narcissism, comparison and disclosure. J Bus Res 2023; 159(113693): 113693.

Gupta

and Sharma

Fear of missing out: A brief overview of origin, theoretical underpinnings and relationship with mental health. World J Clin Cases 2021; 9(19): 4881–4889.

Beyens

, Frison

and Eggermont

“I don’t want to miss a thing”: Adolescents’ fear of missing out and its relationship to adolescents’ social needs, Facebook use, and Facebook related stress. Comput Human Behav 2016; 64: 1–8.

Karki

, Singh

, Maharjan

. Internet addiction and sleep quality among adolescents in a peri-urban setting in Nepal: A cross-sectional school-based survey. PLoS ONE 2021; 16(2): 1–10.

10.

Devnani

and Bhalerao

Assessment of sleepiness and sleep debt in adolescent population in Urban Western India. Indian J Sleep Med 2011; 6(4): 140–143.

11.

Watson

and Badr

MS.

Recommended amount of sleep for a healthy adult: A joint consensus statement of the American Academy of Sleep Medicine and Sleep Research Society. Sleep 2015; 38(6): 843–844.

12.

Tarokh

, Saletin

and Carskadon

MA.

Sleep in adolescence: Physiology, cognition and mental health. Neurosci Biobehav Rev 2016; 70(1): 182–188.

13.

National Sleep Foundation.

What is sleep quality?

National sleep foundation . 2024.

14.

Suni

How much sleep do we really need? In: Singh

(ed) Sleep foundation . 2021.

15.

Almoosawi

, Vingeliene

, Gachon

. Chronotype: Implications for epidemiologic studies on chrono-nutrition and cardiometabolic health. Adv Nutr 2019; 10(1): 30–42.

16.

Nowakowska-Domagała

, Juraś-Darowny

, Pietras

. Chronotype and poor sleep quality in young adults – A pilot study on the role of rumination. Sleep Med 2022; 100: 206–211.

17.

Zou

, Zhou

, Yan

, . Chronotype, circadian rhythm, and psychiatric disorders: Recent evidence and potential mechanisms. Front Neurosci . 2022; 16: 811771.

18.

Rodríguez-García

, Moreno-Guerrero

, López Belmonte

Nomophobia: An individual’s growing fear of being without a smartphone—A systematic literature review. Int J Environ Res Public Health 2020; 17(2): 580.

19.

Bhattacharya

, Bashar

, Srivastava

. NOMOPHOBIA: NO MObile PHone PhoBIA. J Fam Med Prim Care 2019; 8(4): 1297–1300.

20.

Jahrami

, Trabelsi

, Boukhris

. The prevalence of mild, moderate, and severe nomophobia symptoms: A systematic review, meta-analysis, and meta-regression. Behav Sci 2023; 13(1): 35.

21.

Nollet

, Franks

and Wisden

Understanding sleep regulation in normal and pathological conditions, and why it matters. J Huntington’s Dis 2023; 12(2): 105–119.

22.

Rafique

, Al-Asoom

, Al Sunni

. Effects of mobile use on subjective sleep quality. Nat Sci Sleep 2020; 12: 357–364.

23.

Loughran

, Wood

, Barton

. The effect of electromagnetic fields emitted by mobile phones on human sleep. NeuroReport 2005; 16(17): 1973–1976.

24.

Kalmbach

, Schneider

, Cheung

, . Genetic basis of chronotype in humans: Insights from three landmark GWAS. Sleep . 2016; 40(2): zsw048.

25.

Aguilar-Galarza

, García-Gasca

, Mejía

. Evening chronotype associates with increased triglyceride levels in young adults in two independent populations. Clin Nutr 2021; 40(4): 2373–2380.

26.

Fischer

, Lombardi

, Marucci-Wellman

. Chronotypes in the US – Influence of age and sex. PLoS One 2017; 12(6): e0178782.

27.

Vandekerckhove

and Wang

Emotion, emotion regulation and sleep: An intimate relationship. AIMS Neurosci 2017; 5(1): 1–17.

28.

Elhai

, Dvorak

, Levine

. Problematic smartphone use: A conceptual overview and systematic review of relations with anxiety and depression psychopathology. J Affect Disord 2017; 207(207): 251–259.

29.

Nomophobia Questionnaire (NMP-Q). http://cs.oswego.edu/~caglar/publications/NMPQ_English.pdf.

30.

Shahid

, Wilkinson

, Marcu

. Morningness-eveningness questionnaire. In: STOP, THAT and one hundred other sleep scales . 2011, pp.231–234.

31.

Buysse

, Reynolds

, Monk

. The Pittsburgh sleep quality index: A new instrument for psychiatric practice and research. Psychiatry Res 1989; 28(2): 193–213.

32.

Przybylski

, Murayama

, DeHaan

. Motivational, emotional, and behavioral correlates of fear of missing out. Comput Hum Behav 2013; 29: 1814–1848.

33.

Roberts

and David

ME.

The social media party: Fear of missing out (FoMO), social media intensity, connection, and well-being. Int. J Hum Comput Interact 2019; 36(4): 386–392.

34.

Pellegrino

, Stasi

, Bhatiasevi

. Research trends in social media addiction and problematic social media use: A bibliometric analysis. Front Psychiatry . 2022; 13: 1017506.

35.

Liu

, Zhu

, Zhang

, . The relationship between fear of missing out and mobile phone addiction among college students: The mediating role of depression and the moderating role of loneliness. Front Public Health . 2024; 12: 1374522.

36.

Kalia

, Jaiswal

and Sharma

Fear of missing out (FOMO) and sleep disturbances amongst young adults: A correlational study. Int J Sci Soc Sci Res 2025; 2(4): 332–338.

37.

Zhu

, Zheng

, Ding

. Exploring associations between social media addiction, social media fatigue, fear of missing out and sleep quality among university students: A cross-section study. PLoS One 2023; 18(10): e0292429.

38.

Kurnia

, Satiadarma

and Wati

The relationship between nomophobia and poorer sleep among college students . www.atlantis-press.com. Atlantis Press, 2021, pp.1254–1261.

39.

Albursan

, Al-Qudah

, Al-Barashdi

. Smartphone addiction among university students in light of the COVID-19 pandemic: Prevalence, relationship to academic procrastination, quality of life, gender and educational stage. Int J Environ Res Public Health 2022; 19(16): 10439.

40.

Demircioğlu

and Genç

The effects of nomophobia on posture, anxiety, sleep quality, and physical activity in university students. BAU Health Innov 2023; 1(1): 12–17.

41.

Lin

and Zhou

Bedtime smartphone use and academic performance: A longitudinal analysis from the stressor-strain-outcome perspective. Comput Educ Open . 2022; 3: 100110.

42.

Gong

and Liu

Mobile phone addiction and sleep quality: The mediating role of anxiety and the moderating role of emotion regulation. Behav Sci 2023; 13(3): 250.

43.

Foster

RG.

Sleep, circadian rhythms and health. Interface Focus 2020; 10(3): 20190098.

44.

Vitale

, Banfi

, La Torre

, . Effect of a habitual late-evening physical task on sleep quality in neither-type soccer players. Front Physiol . 2018; 9: 1582.

45.

Khan

, Sharma

, Saleem

Chronotype and its relationship with sleep quality among professional students at Indian University. Indian J Phys Ther Res 2023; 5(2): 198–202.

46.

Ceobanu

, Marian

and Apostolache

Glimpse on 21st century new phobias; a predictive model of nomophobia. Front Public Health . 2023; 11: 1252099.

47.

Chang

, Chiu

, Chen

. Smartphone addiction and victimization predicts sleep problems and depression among children. J Pediatr Nurs 2022; 64: e24–e31.

48.

Mac Cárthaigh

, Griffin

and Perry

The relationship between sleep and problematic smartphone use among adolescents: A systematic review. Dev Rev 2020; 55: 100897.

49.

Jahrami

The relationship between nomophobia, insomnia, chronotype, phone in proximity, screen time, and sleep duration in adults: A mobile phone app-assisted cross-sectional study. Healthcare (Basel) 2023; 11(10): 1503.

50.

White

, Buboltz

and Igou

Mobile phone use and sleep quality and length in college students. Int J Humanit Soc Sci . 2010; 1(18): 51–58.

51.

Fabbri

, Beracci

, Martoni

. Measuring subjective sleep quality: A review. Int J Environ Res Public Health 2021; 18(3): 1082.