The role of FoMO and nomophobia in explaining the relationship between doomscrolling and poor sleep quality

Abstract

The increasing use of technology in daily life can significantly affect individuals’ habits and lifestyles. With the widespread use of digital devices, sleep quality has become one of the key areas influenced by technological change. This study aims to examine the mediating roles of FoMO and nomophobia in the relationship between doomscrolling and poor sleep quality. The hypotheses were tested using a descriptive-correlational design with a sample of 663 adults, including 531 women and 132 men, aged between 18 and 77 (Mean = 25.00, SD = 7.53). PROCESS Macro 4.1 (Model 6) was applied to assess multiple mediation effects. According to the results, doomscrolling was positively associated with poor sleep quality (b = .059, 95% CI [.028, .089]). Doomscrolling also significantly predicted FoMO (b = .279, 95% CI [.211, .346]) and nomophobia (b = .092, 95% CI [.056, .129]). FoMO significantly predicted nomophobia (b = .343, 95% CI [.304, .382]). However, FoMO did not significantly predict poor sleep quality (b = –.014, 95% CI [–.053, .024]). Nomophobia, on the other hand, was a significant predictor of poor sleep quality (b = .219, 95% CI [.156, .281]). Mediation analysis showed that nomophobia had a significant mediating role in the relationship between doomscrolling and poor sleep quality (b = .020, 95% CI [.011, .031]). Although FoMO alone was not a significant mediator (b = -.004, 95% CI [-.015, .007]), FoMO and nomophobia together showed a positive combined mediation effect (b = .021, 95% CI [.013, .030]). These findings suggest that increasing awareness of smartphone and social media use may contribute to improving sleep quality. Including strategies to reduce nomophobia, FoMO, and doomscrolling in sleep-related psychoeducational programs may be beneficial.

Introduction

It can be said that today’s technological products have become an integral part of modern life, altering individuals' methods of obtaining information and their daily routines. However, excessive use of technology causes various mental health problems such as depression and anxiety [1], stress [2], loneliness [3], hopelessness [4], irritability [5], attention deficit [6], an increase in manic symptoms [7], decreased quality of life [8], increased anxiety [9], reduced life satisfaction [10], and an increase in suicidal ideation [11]. In addition to negatively affecting individuals’ mental health, excessive use of technology also causes physiological problems such as musculoskeletal pain [12], back and neck pain [13, 14], vision problems [15], language development problems [16], fatigue [17], impairment of cognitive functions [18], and obesity [19].

In addition to psychological and physiological problems, it is also estimated that excessive use of technology affects sleep quality. According to ResMed’s ‘Discover Your Sleep Superpowers’ report [20]—a large non-academic industry survey whose findings should be interpreted with caution—53% of the 36,000 participants reported browsing social media before going to bed, and 40% stated that they do not get enough sleep on more than three nights per week. “Samsung Electronics’ Sleep Research [21]—a non-academic industry report that should be interpreted with caution—reported that the global average sleep duration declined from the previous year. Another result of this study revealed that individuals spent more time in bed but slept less. Recent large-scale sleep surveys, such as the 2024 Sleep Habits Survey by Sleep Savvy Magazine [22], report that screen use before bedtime is among the most commonly observed sleep-disrupting behaviors. Recent large-scale survey data, such as the 2025 Great Indian Sleep Scorecard by Wakefit [23], indicate that a considerable proportion of adults do not feel rested upon waking (44%), frequently use their phones before sleep (84%), and attribute their alertness at night to watching digital content (51%). According to the IKEA Sleep Report [24]—a non-academic industry report whose findings should be interpreted with caution—there is a difference of approximately 1 h and 20 min between the amount of sleep people desire and the amount they actually obtain worldwide. The report also notes that about 72% of individuals spend roughly 40 min on their phones before going to bed. In a study conducted with 45,000 university students in Norway, it was found that one hour of screen time before sleep increased the likelihood of experiencing insomnia by 60% and that social media use reduced sleep duration by approximately five minutes [25]. As can be understood from the above research results, excessive use of technology can negatively affect individuals’ sleep quality. Despite the growing evidence linking general screen use to poor sleep quality, prior studies have rarely examined doomscrolling together with fear of missing out (FoMO) and no mobile phone phobia (Nomophobia) within a single integrated model. Existing research typically focuses on one or two variables in isolation, which limits understanding of how these psychological mechanisms jointly contribute to pre-sleep arousal. Moreover, most studies have not tested whether FoMO and nomophobia function as potential mediators between doomscrolling and sleep quality. Therefore, the present study aims to address this gap by examining these constructs simultaneously and proposing a comprehensive model to explain their interrelationships. Within the scope of this study, the relationships between doomscrolling, nomophobia, FoMO, and poor sleep quality, all of which are among the negative consequences of excessive use of technological devices, were examined.

Sleep quality

Sleep, a vital biological process, is essential for the health of many living beings [26]. It is defined as a state of unconsciousness in which a person can be awakened by emotional or various stimuli [27]. Sleep quality refers to an individual’s perception of feeling rested at the end of sleep, with bodily functions ready for the day and a sense of relaxation [28]. In other words, sleep quality is a subjective condition related to how deeply a person sleeps, how rested they feel upon waking, and how satisfied they are with their sleep [29]. Sleep quality encompasses not only quantitative aspects, such as sleep latency, duration, and the number of awakenings during the night, but also more subjective aspects, including the depth of sleep and the extent to which it is restorative [30]. High-quality sleep has a profoundly positive impact on an individual’s work productivity and overall quality of life [31]. Poor sleep quality, on the other hand, leads to fatigue and irritability, functional impairments in daily life, slower reactions, and increased consumption of caffeine or alcohol [32].

It is thought that one of the factors affecting sleep quality is technology use. Studies on this subject have found a positive relationship between poor sleep quality and digital game addiction [33], smartphone addiction [34–36], increased screen time [37], and excessive use of social media before bedtime [38, 39]. In a study conducted by Mortazavi et al. [40], it was found that the light emitted by smartphones, tablets, and computers at night suppresses the secretion of the melatonin hormone, negatively affecting sleep quality. Additionally, it is emphasized that keeping a TV in the bedroom and being exposed to digital devices at night can lead to sleep problems, including delayed sleep onset, nightmares, frequent nighttime awakenings, and difficulty waking up in the morning [41]. Hjetland et al. [25] found that spending one hour on a screen after going to bed resulted in a 24-min reduction in sleep duration. Some studies have suggested that excessive screen exposure increases the risk of sleep disorders [42] and leads to daytime sleepiness [43, 44]. Recent studies have suggested that excessive screen exposure is linked to increased sleep disorders and excessive daytime sleepiness [45]. Another study found that as individuals’ smartphone use increased, their sleep quality decreased, and their daytime dysfunctions and psychiatric symptoms increased [46]. In an experimental study, it was observed that the sleep quality of the experimental group, whose screen time was restricted by approximately two hours, improved [47].

Poor sleep quality and doomscrolling

It is stated that negative information attracts people’s attention more than positive information [48]. Today, the use of social networks and news sources has become widespread, enabling faster access to information about adverse events, such as wars, epidemics, economic crises, natural disasters, and accidents [49]. The concept of doomscrolling, introduced in 2018 and popularized by journalist Karen Ho, is defined as individuals obsessively focusing on distressing or worrying negative information in social media news feeds and persistently browsing such content [50]. In another definition, doomscrolling is described as the inability to escape from the continuous and uncontrolled monitoring of negative news [51]. Similarly, doomscrolling can be conceptualized as an immersive scanning of negative information and explained within the framework of anxiety and uncertainty [50]. Therefore, it is essential to understand how doomscrolling affects individuals’ digital behaviors at night and their sleep processes.

According to Harvey’s [52] cognitive model of insomnia, individuals’ excessive negative cognitive activities, the emotional distress triggered by these activities, and the resulting physiological arousal all negatively affect the process of falling asleep. In this model, intense negative thoughts and an increased perception of threat activate the autonomic nervous system, leading to heightened internal arousal that makes it more difficult to fall asleep. Based on this view, doomscrolling, defined as excessively browsing harmful content on social media and news platforms at night, may increase mental and emotional arousal, thereby making it more difficult to fall asleep. Additionally, individuals may turn to media to alleviate the stress and insecurity they experience in their daily lives [53]. However, continuous monitoring of harmful content in the media may lead individuals to employ maladaptive strategies for emotion regulation. Indeed, according to Gross’s [54] emotion regulation model, individuals’ failure to use proper emotion regulation strategies negatively affects their physiological activation. Moreover, it has been emphasized that the inappropriate use of the suppression strategy may have adverse physiological consequences [55]. In this context, it is considered that individuals’ engagement in doomscrolling behavior while using media as a means of emotion regulation may reduce their sleep quality. In fact, research has shown that doomscrolling increases individuals’ negative affect and anxiety, leading to sleep problems [56–58]. In light of these explanations, it is hypothesized that there is a positive relationship between doomscrolling and poor sleep quality (H₁: Doomscrolling positively and significantly explains poor sleep quality).

Poor sleep quality, FoMO, and nomophobia

It is emphasized that social media has become widespread and plays a vital role in people’s lives today [59]. One of the consequences of excessive social media use is the fear of missing out (FoMO), which is defined as the anxiety that other people are having rewarding experiences in one’s absence and the constant desire to stay connected with what others are doing [60]. FoMO, also referred to as the “fear of missing something,” is defined as the feeling of anxiety that arises from the concern of missing out on exciting events, particularly influenced by what a person sees on social media [61]. In other words, FoMO expresses the concern individuals feel about not being able to stay connected with the satisfying events and experiences that are taking place in social environments [62]. According to Elhai et al. [63], at the core of FoMO lies the need for individuals to be continuously connected with their social environment, which leads to excessive use of social media accounts. Additionally, it has been noted that the uncontrolled use of smartphones can be a triggering factor for FoMO. As individuals follow social media and similar platforms, their likelihood of missing content in these areas increases, creating a vicious cycle that leads to greater smartphone use [64, 65] and social media addiction [66].

While the primary function of smartphones is to make life easier, they can also give rise to technological disorders [67]. The concept of “no mobile phone phobia/nomophobia,” which emerged in the United Kingdom in 2008, is described as the discomfort and anxiety experienced when being away from a mobile phone, tablet, or computer [68, 69]. In another definition, nomophobia is described as the fear of losing mobile phone connection or the fear of being unable to leave one’s location without a mobile phone [70]. Yıldırım and Correia [71] defined the dimensions of nomophobia as: inability to communicate via smartphone, losing connection, inability to access information, and losing the sense of comfort provided by smartphones. According to Bragazzi and Puente [72], the symptoms of nomophobia are explained under seven categories: (1) spending excessive time with a smartphone, owning more than one phone, and always carrying a charger, (2) feeling tense due to thoughts about losing the smartphone, not having it nearby, poor network coverage, the phone battery running out, or insufficient credit; (3) trying to avoid places or situations where smartphone use is prohibited; (4) constantly checking the smartphone to see whether messages or calls have been received; (5) always keeping the smartphone on and sleeping with it; (6) limiting face-to-face communication and preferring to communicate via smartphone; and (7) spending large amounts of money or going into debt due to smartphone use. Exposure to evening blue-wavelength light from electronic devices has been shown to suppress melatonin secretion and disrupt circadian rhythms, thereby impairing sleep initiation and quality [73, 74]. The suppression of melatonin not only delays falling asleep but also leads to a decrease in total sleep duration and a decline in sleep quality [75]. Additionally, shifts in the circadian rhythm lead to a reduction in individuals’ cognitive functions and impairments in daytime alertness [76]. Based on these explanations, it is predicted that FoMO may trigger the need to stay constantly updated. At the same time, nomophobia may create pressure to remain continuously connected, thereby increasing pre-sleep screen time and harmful cognitive activity, which may, in turn, trigger insomnia. Therefore, it is considered that FoMO (H₅: FoMO positively and significantly explains poor sleep quality) and nomophobia (H₆: Nomophobia positively and significantly explains poor sleep quality) have a positive relationship with poor sleep quality. Research on this subject has revealed a negative relationship between FoMO and sleep quality [65, 77–86]. Similarly, studies have found that individuals with higher levels of nomophobia have lower sleep quality [87–93]. Since FoMO and nomophobia, which negatively affect sleep quality, are related to individuals’ fear of being away from what they want to follow on their smartphones, it is predicted that there may be a positive relationship between these two variables (H₄: FoMO positively and significantly explains Nomophobia). Indeed, studies support this view [84, 94–99].

Poor sleep quality, doomscrolling, FoMO, and nomophobia

In his theoretical model based on the continuity of arousal, Duffy [100] defined arousal as occurring on a continuous spectrum ranging from deep sleep to intense excitement, stating that there are no distinct breakpoints for either sleep or emotions along this axis. According to this theory, arousal occurs as a continuous spectrum, ranging from a low point during deep sleep to a high point during excessive effort or great excitement. In this context, doomscrolling behavior may elevate an individual’s arousal level, making it more challenging to transition into the sleep state, which requires low arousal, thereby negatively affecting sleep quality [101].

The I-PACE (Interaction of Person–Affect–Cognition–Execution) model emphasizes the interaction of individuals’ need for social connection, emotional states, cognitive responses, and executive control processes, and suggests that such personal characteristics may increase problematic internet use through their impact on emotional and mental processes [102]. According to this model, vulnerability factors such as heightened anxiety or uncertainty sensitivity shape how people react to digital environments, leading to cognitive distortions and difficulty disengaging from online content. The updated framework highlights that these affective–cognitive cycles weaken inhibitory control and reinforce compulsive checking behaviors [103]. Within this context, doomscrolling can be understood as a maladaptive response to increased negative affect and vigilance toward threatening information. Exposure to distressing content may heighten anxiety and promote persistent monitoring of negative news [50]. These mechanisms may also strengthen social-cognitive processes—such as the need to stay constantly connected—thereby fostering FoMO and greater reliance on smartphones, which can contribute to nomophobia [63]. The conceptualization of digital dependence and behavioral excess in this study aligns with recent psychometric evidence emphasizing digital overuse as a multidimensional construct encompassing cognitive, emotional, and behavioral domains [104]. Within the framework of doomscrolling behavior, an individual’s persistent desire to follow harmful content on social media may lead to a fear of missing out (FoMO) due to their unwillingness to miss out on social media developments. Consequently, an increase in FoMO is expected (H₂: Doomscrolling positively and significantly explains FoMO). In addition, considering that individuals can follow harmful content on social media through their smartphones, it is predicted that doomscrolling behavior will also increase nomophobia (H₃: Doomscrolling positively and significantly explains nomophobia). Supporting this view, studies have revealed positive and significant relationships between doomscrolling and FoMO [50, 105] as well as doomscrolling and nomophobia [106]. On the other hand, FoMO, which is related to individuals’ desire to remain constantly active on social media due to the fear of missing out on developments in their environment [107–109], and nomophobia, which leads individuals to remain dependent on their devices due to the fear of being offline or losing digital connection [110], may prolong individuals’ nighttime online activity. In this regard, it is considered that the relationship between doomscrolling behavior and poor sleep quality may be strengthened by FoMO (H₇: FoMO has a positive and significant mediating role in explaining the relationship between doomscrolling and poor sleep quality) and nomophobia (H₈: Nomophobia has a positive and significant mediating role in explaining the relationship between doomscrolling and poor sleep quality), increasing individuals’ levels of mental arousal, which in turn may make it more difficult to initiate and maintain sleep, thereby reducing sleep quality (H₉: FoMO and nomophobia together have positive and significant mediating roles in explaining the relationship between doomscrolling and poor sleep quality).

The theoretical model of the present study is grounded in the cognitive-behavioral perspective, which emphasizes that maladaptive cognitions, negative automatic thoughts, and cognitive distortions play a central role in shaping emotional responses and behavioral patterns [111, 112]. According to the cognitive-behavioral model, individuals who habitually process information through threat-oriented or catastrophizing cognitions experience heightened physiological arousal and increased emotional distress, particularly in contexts involving uncertainty or uncontrollable stimuli [113]. Doomscrolling behavior—defined by repetitive, uncontrolled exposure to harmful online content—aligns with this framework, as it continuously activates negative schemas, reinforces attentional biases toward threat, and maintains a cycle of cognitive hyperarousal that interferes with the initiation and maintenance of sleep. This mechanism is also consistent with mental models of insomnia, which highlight pre-sleep cognitive arousal, intrusive thoughts, and worry as key processes that disrupt sleep regulation [52].

In the present model, FoMO and nomophobia are conceptualized as reinforcing psychological mechanisms that perpetuate this cognitive-behavioral cycle. FoMO, characterized by a persistent anxiety about missing critical online experiences, has been shown to increase compulsive digital engagement and heighten emotional reactivity [60]. Similarly, nomophobia—the fear of being without one’s mobile device—reflects maladaptive cognitions regarding safety, connectedness, and social belonging, thereby sustaining pre-sleep device checking behaviors [114]. From a cognitive-behavioral standpoint, these constructs operate as maintaining factors that prevent cognitive deactivation before bedtime, inhibit behavioral disengagement from digital devices, and prolong exposure to negatively valenced content.

Consequently, the present model proposes a sequential pathway whereby doomscrolling indirectly contributes to poor sleep quality through elevated FoMO and nomophobia, offering a coherent CBT-based explanation for the observed associations. This pathway reflects the broader principle in CBT that maladaptive cognitions amplify emotional distress, increase physiological arousal, and lead to behavioral patterns that ultimately impair well-being [111, 113].

The present study

It has been reported that internet use in Turkey has increased each year, rising from 87% in 2023 to 88% in 2024 [115]. The internet is used for various purposes such as following social media, watching videos, receiving news, online shopping, and learning. Regarding social media use, one of these purposes, the report by We Are Social [116] indicated that there are 58.5 million social media users in Turkey (66% of the population). According to this report, the number of social media identities increased by 1.7% between 2024 and 2025. The increasing use of the internet and social media in Turkey is considered to affect sleep quality potentially. According to the results of the IKEA Sleep Report [24], although people in Turkey desire to sleep an average of 9 h, they actually sleep 6 h and 42 min. Turkey was identified as the country with the latest average bedtime in the world, at 12:45 a.m. Furthermore, results published by Sleep Cycle revealed that Turkey has the lowest average sleep duration among European countries, at 6 h and 50 min, and that approximately one in every four people does not get adequate sleep [117]. In light of this information, internet use and sleep quality are identified as areas that require further study in Turkey. Considering the significant impact of digitalization on daily routines, this study is critical in examining the consequences of individuals’ engagement in doomscrolling behavior, specifically staying online before sleep, on their sleep patterns. However, research on the effect of doomscrolling behavior on sleep quality is limited, and the cognitive and emotional processes shaping this relationship have not been sufficiently clarified. In this context, it is considered that nomophobia and FoMO may reinforce individuals’ tendency to stay in front of screens at night by increasing their levels of digital dependency, thereby supporting the relationship between doomscrolling and poor sleep quality. Therefore, this study is expected to contribute to filling the gap in the literature by revealing the interaction between these variables and developing a comprehensive understanding of sleep health. Moreover, the findings obtained are evaluated as potentially contributing to the content of educational programs on digital literacy, healthy technology use, and sleep efficiency. Additionally, such a study is expected to provide valuable insights for future research on digital dependency, physical well-being, and psychological well-being.

According to the report by We Are Social [116], the number of social media users aged 18 and above in Turkey is 55.9 million, representing 85% of adults aged 18 and over. In a study conducted in Turkey, it was reported that 50% of adults spend 4 h or more on social media [118]. Another study found that 71% of adults use smartphones for 4 h or more, and 26% sleep less than 6 h [119]. A study conducted by Karasu et al. [120] reported that 93% of adults use smartphones before bedtime, and 29% experience excessive daytime sleepiness. Based on these results, it is evident that the rate and duration of social media and smartphone use among adults in Turkey are high, and the sleep problems that may arise due to excessive screen time should be carefully addressed as a significant public health issue. This study aims to contribute to the understanding of the effects of adults’ digital habits on their sleep quality in Turkey.

Based on the explanations above, it is predicted within the scope of this study that there is a positive relationship between doomscrolling and poor sleep quality, and that nomophobia and FoMO mediate this relationship, positively influencing it. No research has been found that examines these variables together in relation to poor sleep quality. In this respect, the results obtained from the study are considered original. In light of these explanations, the study aims to investigate whether nomophobia and FoMO serve as mediating factors in the relationship between doomscrolling and poor sleep quality.

H₁: Doomscrolling positively and significantly explains poor sleep quality.

H₂: Doomscrolling positively and significantly explains FoMO.

H₃: Doomscrolling positively and significantly explains nomophobia.

H₄: FoMO positively and significantly explains Nomophobia.

H₅: FoMO positively and significantly explains poor sleep quality.

H₆: Nomophobia positively and significantly explains poor sleep quality.

H₇: FoMO has a positive and significant mediating role in explaining the relationship between doomscrolling and poor sleep quality.

H₈: Nomophobia has a positive and significant mediating role in explaining the relationship between doomscrolling and poor sleep quality.

H₉: FoMO and nomophobia together have positive and significant mediating roles in explaining the relationship between doomscrolling and poor sleep quality.

Methods

Design

In this study, it was examined whether there is a mutual relationship among doomscrolling, FoMO, nomophobia, and poor sleep quality, and if so, the degree of this relationship was determined. Accordingly, if a significant relationship is found between doomscrolling and poor sleep quality, it was investigated whether FoMO and nomophobia have a mediating role in this relationship. The present study is a quantitative research based on a descriptive-correlational design. However, due to the cross-sectional nature of this study, it is not possible to establish a cause-and-effect relationship among the variables examined [121]. Therefore, based on the results obtained from the research, no causal inferences should be made regarding how doomscrolling, nomophobia, and FoMO affect poor sleep quality.

Participants

In determining the study group of the research, the convenience sampling method was preferred. Convenience sampling involves collecting data from individuals accessible to the researcher, thereby reducing the loss of time, money, and labor [122]. Within this scope, the study sample consisted of a total of 663 adults, comprising 531 women (80%) and 132 men (20%). The ages of the participants ranged from 18 to 77 years (Mean = 25.00, SD = 7.53). Participants who provided informed consent were administered the measurement instruments via Google Forms, which was distributed through various social media platforms. This method was preferred because it allowed rapid access to a broad group of adults. The participants consisted of individuals residing in different cities across Türkiye. Apart from being over 18 years of age, no additional inclusion criteria—such as being a student, employed, unemployed, or married—were applied.

Regarding the required sample size, Büyüköztürk [123] recommends that the number of participants should be at least five times the total number of items in the measurement instruments used in a study. This criterion was considered in the present research. Four different measurement tools were utilized, comprising a total of 67 items. According to this calculation, the minimum required sample size should be at least 335 participants. As the sample of the current study consisted of 663 individuals, the sample size was deemed adequate. The average daily social media usage time of the participants was 3 h and 25 min. The applications most frequently used by participants on their smartphones were Instagram (55%), WhatsApp (21%), YouTube (11%), X (formerly Twitter) (9%), and TikTok (5%), respectively. Sixty percent of the participants reported having difficulty waking up in the morning. On average, participants used their smartphones for 35 min before going to sleep.

Instruments

Personal information form

This form, prepared by the researchers to collect the demographic information of the participants, included questions regarding gender, age, daily social media usage time, the most frequently used application on the smartphone, whether they have difficulty waking up in the morning, and the average number of minutes the smartphone is used before falling asleep.

Doomscrolling scale

The scale was developed by Sharma et al. [50] to measure the doomscrolling behavior of individuals using social media. The scale was adapted into Turkish by Satıcı et al. [105]. The sample in which the scale was developed consisted of individuals aged between 18 and 59. The study in which this scale was adapted included 460 participants who were recruited through an online survey conducted in 25 of Türkiye’s 81 provinces. Of the participants, 343 were women (74.6%), and 117 were men (25.4%). The mean age of the sample was 23.68 years (SD = 6.08). Participants reported actively using an average of 3.78 social media platforms (SD = 1.76,range: 1–14 platforms). The mean daily social media use was 4.05 h (SD = 2.31; range: 1–16 h). The majority of participants reported using Twitter (N = 294, 63.9%). The scale is a 7-point Likert-type scale consisting of a single dimension with 15 items. Higher scores on the scale indicate higher levels of doomscrolling behavior in individuals (e.g., Item 2: When I read bad news on social media, I lose track of time). In the exploratory factor analysis (EFA) conducted to test the validity of the scale, the total variance explained was found to be 54.46%. The factor loadings of the items ranged between 0.63 and 0.83. According to the confirmatory factor analysis (CFA), the fit indices were found to be at an acceptable level (χ²/df = 402.57, p < 0.001; CFI = 0.92, NFI = 0.90, IFI = 0.92, SRMR = 0.046). The Cronbach’s alpha value calculated to test the reliability of the scale was 0.94 [105]. In the present study, the Cronbach’s alpha value of the measurement tool was found to be 0.93.

Cumhuriyet subjective sleep quality scale

The scale was developed by Sarıçam [124] to measure sleep quality. In the study where this scale was initially created, a convenience sampling method was used to recruit participants. Data were collected from 428 adults who voluntarily participated in the research. Of these participants, 21.50% (N = 92) were men and 78.50% (N = 336) were women. Participants’ ages ranged from 18 to 56 years, with a mean age of 26.83 years. It is a 4-point Likert-type scale consisting of 18 items. The scale has three sub-dimensions: Psychometric Effects (e.g., Item 1: I felt tense/irritable during the day because I could not sleep well), Sleep Course (e.g., Item 4: I had difficulty falling asleep even though I had no pain or discomfort), and Sleep Satisfaction (e.g., Item 6: When I woke up, I felt as if I had not slept at all). Higher scores on the scale indicate lower sleep quality. In the exploratory factor analysis (EFA) conducted to test the validity of the scale, the total variance explained was found to be 60.45%. Items 3, 10, 11, 15, and 17 are reverse-coded. The sample in which the scale was developed consisted of individuals aged between 18 and 56. In the confirmatory factor analysis (CFA), the fit indices were calculated as follows: χ²/df = 2.78, RMSEA = 0.08, SRMR = 0.085, NFI = 0.90, IFI = 0.92, CFI = 0.92, PGFI = 0.60, and AGFI = 0.82. Cronbach’s alpha coefficients calculated to test the reliability of the scale were 0.84 for Psychometric Effects, 0.87 for Sleep Process, 0.84 for Sleep Satisfaction, and 0.91 for the overall scale [124]. In the present study, the Cronbach’s alpha value of the measurement tool was found to be 0.87.

Fear of missing out on social media scale (FoMO)

The scale was developed by Zhang et al. [125] and adapted into Turkish by Çelik and Özkara [126]. The sample in which the scale was developed consisted of individuals aged 18 and above who use social media. The study included individuals who used smartphones and social media. Data were collected from two independent samples to be used in the Exploratory Factor Analysis (EFA) and Confirmatory Factor Analysis (CFA) phases. The EFA sample consisted of 251 participants, including 147 women and 104 men. In this sample, 58.6% of the participants were women (N = 147) and 41.4% were men (N = 104). Additionally, 83.3% of the participants were single (N = 209), and 16.7% were married (N = 42). The CFA sample consisted of 353 participants, including 207 women and 146 men. In this sample as well, 58.6% were women (N = 207) and 41.4% were men (N = 146). Regarding marital status, 87.3% of the participants were single (N = 308) and 12.7% were married (N = 45). The scale is a 7-point Likert-type scale comprising nine items. It has two sub-dimensions: Personal FoMO (e.g., Item 1: I feel anxious when I cannot be active on social media) and Social FoMO (e.g., Item 7: When I cannot be active on social media, I feel that I am not worthy of the social group I belong to). Higher scores on the scale indicate higher levels of FoMO. In the exploratory factor analysis (EFA) conducted to test the validity of the scale, it was found that nine items explained 60% of the total variance of the scale and clustered under two factors. The item–total correlation scores ranged from 0.33 to 0.80. The factor loadings of the items ranged from 0.57 to 0.90. The results of the confirmatory factor analysis (CFA) showed that the fit indices of the two-dimensional model were at an adequate level (χ²/df = 3.12; RMSEA = 0.08; SRMR = 0.03; CFI = 0.98). The Cronbach’s alpha coefficients calculated for internal consistency were 0.90 for Personal FoMO, 0.89 for Social FoMO, and 0.89 for the overall scale [126]. In the present study, the Cronbach’s alpha value of the measurement tool was found to be 0.92.

Üsküdar nomophobia scale

The scale was developed by Tarhan et al. [127]. The sample in which the scale was developed consisted of individuals aged between 15 and 64.

In the study in which the scale was developed, the sample was formed in accordance with the principle of voluntariness using a random sampling method. The sample consisted of 630 women (68.5%) and 291 men (31.5%) from various regions of Türkiye. The youngest participant was 15 years old, the oldest was 64, and the mean age of the sample was 26 years. Regarding educational attainment, 43.2% of the participants were high school graduates, 43.2% held a university degree, 12% had completed postgraduate education, 1.2% were vocational school graduates, and 0.8% were primary school graduates. In terms of marital status, 23.4% of the participants were married, 70.2% were single, 4.2% were divorced or widowed, and 1.7% reported being engaged. It is a 5-point Likert-type scale consisting of 25 items. The scale has three sub-dimensions: Dysfunction in Functionality (e.g., Item 1: I sometimes cancel my plans because I am occupied with my phone), Overuse (e.g., Item 11: I spend my free time using my phone), and Inability to Communicate (e.g., Item 20: If my phone is not with me, I feel anxious because I cannot immediately communicate with my family and/or friends). In the exploratory factor analysis (EFA) conducted to determine the distinctiveness of the scale, the explained variance was found to be 69%. The factor loadings ranged from 0.59 to 0.86. According to the confirmatory factor analysis (CFA), the scale has a three-factor structure, and the fit indices obtained were found to be at an acceptable level (χ²/df = 2.53; RMSEA = 0.07; NFI = 0.89; NNFI = 0.92; CFI = 0.96; GFI = 0.94; AGFI = 0.84). To test the reliability of the scale, Cronbach’s alpha coefficients were calculated as 0.93 for Dysfunction in Functionality, 0.93 for Excessive Use, 0.94 for Inability to Communicate, and 0.96 for the overall scale [127]. In the present study, the Cronbach’s alpha value of the measurement tool was found to be 0.93.

Data collection

To administer the measurement tools selected for use in the study, permission for their use was first obtained via email from the researchers who developed them. For the collection of research data, ethical approval was obtained from the Social and Human Sciences Ethics Committee of Bursa Uludağ University, Türkiye, confirming that the procedures were ethically appropriate (Approval No: 16; Date: 03.05.2024). The first section of the measurement tools included an informed consent form. This form outlined the purpose and scope of the study, emphasized that all collected information would remain confidential, stated that participation was voluntary and no incentives would be provided, and informed participants that they could withdraw from the study at any time. Participation was anonymous, and no identifying information was requested or collected. Completing the measurement instruments took each participant approximately 15 to 20 min. Data were collected over two months, from May 2024 to June 2024. Because all items in the online form were set as mandatory, no missing data occurred, and the system did not record incomplete forms. All procedures conducted in this study adhered to the relevant ethical guidelines and regulations, including the Declaration of Helsinki.

Analytical procedure

In this study, we examined whether FoMO and nomophobia play a mediating role in explaining the relationship between doomscrolling and poor sleep quality. Mediation analysis is a method used to evaluate whether the effect of an independent variable (X) on a dependent variable (Y) is explained through a mediating variable (M) [128]. In this study, doomscrolling is the independent variable, poor sleep quality is the dependent variable, and FoMO and nomophobia are the mediating variables. Accordingly, in the model created (Fig. 1), the direct and indirect effects of the independent variable on the dependent variable were examined. The research data were analyzed using regression analysis. For regression analysis to be performed, certain assumptions must first be met (1. Sample size is sufficient, 2. Missing values are treated, 3. Univariate and multivariate normality is found, 4. Multicollinearity among the variables is low) [129], pp. 205–211). Accordingly, it was first tested whether these assumptions were met.

Fig. 1.

Model 6. (X: Independent variable, Y: Dependent variable, M₁: Mediator 1, M₂: Mediator 2) (Hayes, 2013)

Sample size is sufficient

It is recommended that the sample include at least 10 times as many participants as the number of items in the scale [130]. Among the scales used in the study, the Üsküdar Nomophobia Scale has the highest number of items, consisting of 25 items. According to this criterion, the number of participants in this study should be at least 250. Since the measurement tools were administered to 663 individuals, the sample size was considered sufficient.

Missing values are treated

The dataset was checked for missing data. The data were collected via Google Forms. While designing the scale forms, it was ensured that participants could not proceed to the following item without completing the previous one. In this way, no missing data occurred in the dataset.

Univariate and multivariate normality is found

For univariate and multivariate normality, the dataset was examined for the presence of outliers. For variables to demonstrate univariate normal distribution, skewness values must be less than |2| and kurtosis values must be less than |7| [131]. As shown in Table 1, the variables were found to have univariate normality. To check for multivariate normality, the Mahalanobis distance value was calculated. Considering that the study included one dependent variable and three independent variables, the chi-square (χ²) distribution table indicated that the critical value at the 0.01 significance level with the relevant degrees of freedom was 13.28 [132]. The analysis revealed that none of the Mahalanobis values of the variables exceeded this critical value. Therefore, the variables were accepted as having multivariate normality.

Table 1.

Descriptive statistics of the study variables

Variable	n	Min	Max	x̄	Ss	Skewness	Kurtosis
Doomscrolling	663	1.00	7.00	2.491	1.191	.855	.253
Poor Sleep Quality	663	.06	2.83	1.367	.473	.082	-.417
FoMO	663	1.00	6.89	2.131	1.101	1.187	1.210
Nomophobia	663	1.00	4.48	2.434	.684	.150	-.536

Multicollinearity among the variables is low

In the study, it was examined whether there was a multicollinearity problem among the independent variables. If the correlation among independent variables exceeds 0.90, it is considered that a multicollinearity problem exists [129]. According to the results of the Pearson correlation analysis, the correlation coefficients among the independent variables ranged between 0.201 and 0.601 (Table 2). Based on these results, it was concluded that there was no multicollinearity problem among the variables. In addition, it is recommended to calculate the Tolerance Value (TV) and Variance Inflation Factor (VIF) when testing for multicollinearity. For there to be no multicollinearity problem, the VIF value should be less than 10, and the TV should be greater than 0.2 [133]. The TV and VIF values calculated for the independent variables were as follows: Doomscrolling,TV = 0.875, VIF = 1.143; FoMO; TV = 0.626, VIF = 1.596; Nomophobia; TV = 0.615, VIF = 1.626.

Table 2.

Results of Pearson correlation analysis among the study variables

Variable	(1)	(2)	(3)	(4)
(1) Doomscrolling	1.00	.242**	.302**	.328**
(2) Poor Sleep Quality		1.00	.201**	.345**
(3) FoMO			1.00	.601**
(4) Nomophobia				1.00

^**p <.001

Based on the above results, it was understood that the necessary assumptions for performing regression analysis were met. At this stage, multiple mediation analysis was conducted within the framework of Model 6 of the PROCESS Macro 4.1 version for SPSS 25.0, developed by Hayes, based on the bootstrap method. In the mediation analysis, the bootstrap method (with 5000 resamples) was employed. In mediation effect analyses performed using the bootstrap method, the confidence interval obtained (with a 95% confidence level) must not include the value of zero (0) to confirm the research hypothesis [134]. Additionally, the minimum, maximum, arithmetic mean, standard deviation, skewness, and kurtosis values of the variables were calculated during the data analysis. Furthermore, the reliability of the measurement tools used in the study was retested within the scope of this research. These analyses were conducted using the SPSS 28.0 statistical package program.

Findings

Descriptive statistics of the study variables, poor sleep quality, doomscrolling, nomophobia, and FoMO, are presented in Table 1.

Pearson correlation analysis was conducted to examine the relationships among the study variables, and the results are presented in Table 2.

First, it was examined whether doomscrolling significantly explained poor sleep quality. Then, it was investigated whether FoMO and nomophobia significantly explained poor sleep quality. In the final stage, it was examined whether FoMO and nomophobia had significant mediating roles in the relationship between doomscrolling and poor sleep quality. The results of the regression analysis based on the bootstrap method are presented in Table 3.

Table 3.

Regression analysis results for multiple parallel mediation tests

Independent Variables	Dependent Variables
	M1				M2				Y
	b	SE	LLCI	ULCI	b	SE	LLCI	ULCI	b	SE	LLCI	ULCI
Direct Effects
X	.279	.034	.211	.346	.092	.018	.056	.129	.059	.015	.028	.089
M1					.343	.019	.304	.382	-.015	.019	-.053	.024
M2									.219	.031	.156	.281
Constant	1.436	.094	1.250	1.622	1.471	.056	1.361	1.582	.717	.065	.588	.846
	R2 =.091**				R2 =.385**				R2 =.138**
Indirect Effects	b	SE	LLCI	ULCI	Completely Standardized Indirect Effect Size
X → M1 → Y	-.004	.005	-.015	.007	(b =.094, %95 BCA CI [.061 –.129])
X → M2 → Y	.020	.005	.011	.031
X → M1 + M2 → Y	.021	.004	.013	.030

Doomscrolling: X, Poor Sleep Quality: Y, FoMO: M_1; Nomophobia_: M₂, Standardized beta coefficients: b, Standard error: SE, Lower-limit of confidence interval: LLCI, Upper-limit of confidence interval: ULCI, Biased corrected accelerated: BCA, Confidence interval: CI

^**p <.001

When the direct effects in Table 3 are examined, it is found that doomscrolling is positively and significantly associated with poor sleep quality. It was also revealed that doomscrolling positively and significantly predicted FoMO and nomophobia. Furthermore, FoMO was found to positively and significantly predict nomophobia. However, poor sleep quality was not significantly predicted by FoMO. On the other hand, poor sleep quality was found to be positively and significantly predicted by nomophobia. According to the standardized regression coefficient (β), the formula f² = R²/(1 – R²) was used to determine the effect size of the predictor variables on poor sleep quality. Values were accepted as 0.02 ≤ f² < 0.15 = small effect, 0.15 ≤ f² < 0.35 = medium effect, and f² ≥ 0.35 = large effect [135]. The R² values in this formula were calculated through simple linear regression analysis conducted to determine the extent to which each independent variable explained the dependent variable. According to the findings, doomscrolling was found to have a small level effect on explaining poor sleep quality (f² = 0.06), nomophobia (f² = 0.12), and FoMO (f² = 0.10). Similarly, nomophobia was found to have a small effect (f² = 0.13) in explaining poor sleep quality. Additionally, it was found that FoMO had a low-level effect on explaining poor sleep quality (f² = 0.04).

The findings regarding the mediating role of FoMO indicated that this variable did not function as a significant mediator within the tested model. As shown in Table 3, the indirect effect of doomscrolling on poor sleep quality through FoMO was not significant, as the 95% bootstrap confidence interval included zero. Although the path from doomscrolling to FoMO was significant, the path coefficient from FoMO to poor sleep quality was small in magnitude and statistically non-significant. These results suggest that FoMO did not make a meaningful contribution to the explained variance in the model and that its mediating role was not supported. However, nomophobia was found to have a positive and significant mediating effect in explaining poor sleep quality through doomscrolling. In addition, FoMO and nomophobia together demonstrated a positive and significant mediating role in the relationship between doomscrolling and poor sleep quality. As shown in Table 3, the fully standardized effect size of the mediation effect was R² = 0.094. The fully standardized effect size of the mediation was f² = 0.10, indicating that the mediation effect in the tested model was of small magnitude.

The overall pattern of results suggests that doomscrolling has a small yet significant direct effect on poor sleep quality, while its indirect influence primarily operates through nomophobia. Although FoMO was significantly predicted by doomscrolling, its impact on sleep quality remained weak and statistically non-significant, consistent with its very small effect size. In contrast, nomophobia accounted for a greater proportion of variance in sleep outcomes, supporting its role as the central explanatory mechanism in the model. Overall, the effect sizes suggest that the pathways from doomscrolling to impaired sleep are present but modest in magnitude. Other values obtained for the tested model are presented in Fig. 1.

As shown in Fig. 1, the independent variable doomscrolling significantly and positively predicted the dependent variable poor sleep quality before the mediating variables were included (c = 0.059^**). When the mediators were added to the relationship between the independent and dependent variables, the strength of the association increased slightly (c¹ = 0.094^**). Among the mediating variables, only nomophobia was found to have a significant association with both the independent and dependent variables. Therefore, it can be concluded that nomophobia is the only significant mediator in the relationship between doomscrolling and poor sleep quality.

Discussion, conclusion, and recommendations

A positive and significant relationship was found between doomscrolling and poor sleep quality (H₁: Accepted). Consistent with this finding, Syunyakov et al. [136] reported that exposure to harmful online content was associated with late bedtimes, fragmented sleep, and nightmares. Similarly, Yang et al. [58] identified a positive link between doomscrolling and insomnia symptoms. This relationship can be understood within the framework of Harvey’s [52] cognitive model of insomnia, which posits that heightened pre-sleep cognitive and emotional arousal interferes with sleep initiation. Exposure to harmful online content may contribute to such arousal by increasing stress responses [137]. Supporting this explanation, Kinsella and Chin [138] noted that emotionally charged content before bedtime keeps the brain alert and elevates cognitive arousal, making it more challenging to relax and fall asleep. This finding suggests that the relationship between doomscrolling and poor sleep quality is consistent with the mechanisms proposed in the literature.

A positive and significant relationship was found between doomscrolling and FoMO (H₂: Accepted), a result supported by previous research [139]. Within the framework of the I-PACE model, doomscrolling may trigger cognitive biases such as “a crisis could happen at any moment” or “I must stay connected,” while also increasing anxiety and stress levels [139–141]. According to the model, such heightened cognitive and emotional reactions can impair self-control [103]. In this context, the negative thoughts and arousal generated by doomscrolling may weaken individuals’ self-regulation and contribute to a behavioral cycle that reinforces FoMO,however, this interpretation should be approached with caution, as the underlying mechanisms were not directly measured in the present study. As demonstrated in the studies by Elhai et al. [9] and Zhang et al. [65], the negative affect and mental arousal accompanying doomscrolling may weaken self-regulation processes and increase the repetitive online checking behaviors associated with FoMO.

A positive and significant relationship was found between doomscrolling and nomophobia (H₃: Accepted). According to the Compensatory Internet Use Theory (CIUT), individuals may rely on digital devices to regulate negative emotions, which can contribute to problematic smartphone use [142]. In this context, the negative emotions triggered by doomscrolling—such as heightened anxiety, perceived threat, and loss of control—may increase individuals’ tendency to turn to their smartphones as a psychological safety object [143]. This emotional dependence can, in turn, intensify nomophobic reactions when the device is lost or becomes inaccessible. Therefore, the fact that negative affect associated with doomscrolling strengthens the tendency to use the smartphone as a safety object—and the resulting nomophobic reactions—is consistent with the literature [144, 145].

A positive and significant relationship was found between FoMO and nomophobia (H₄: Accepted), a finding supported by numerous studies [84, 94–99, 146–148]. According to the I-PACE model, FoMO can function as a cognitive bias that heightens anxiety when individuals are away from their smartphones [149]. This cognitive sensitivity may intensify the urge to remain online, leading to frequent social media checks [150] and maintain constant communication, which in turn can contribute to increased anxiety and nomophobic reactions when the device is inaccessible.

No significant relationship was found between FoMO and poor sleep quality (H₅: Rejected). Similar to the present findings, Zhu et al. [151] reported that FoMO did not affect sleep quality or sleep duration. These results indicate that FoMO alone may not be sufficient to influence sleep quality [152, 153]. Although a positive correlation was observed in this study, FoMO did not significantly predict poor sleep quality in the regression model, suggesting that its effect becomes nonsignificant when variables such as doomscrolling and nomophobia are taken into account. The small effect size observed, combined with the participants’ moderate daily social media use (3 h and 25 min, may have limited the emergence of FoMO-related behaviors,however, this interpretation should be approached cautiously, as the study did not include analyses capable of confirming this explanation. Additionally, the content consumed before sleep may not have been related to FoMO; nevertheless, this interpretation should be viewed cautiously because pre-sleep media content was not measured in the study.

A positive and significant relationship was found between nomophobia and poor sleep quality (H₆: Accepted), a result supported by prior studies [154, 155]. In addition to this relationship, evidence suggests that nighttime smartphone use can disrupt circadian rhythms by suppressing melatonin, thereby reducing sleep quality [73], however, this biological mechanism was not assessed in the present study and should be interpreted with caution. Bootzin’s [156] Stimulus Control Theory further suggests that the bed should be associated solely with sleep, and that engaging in non-sleep-related behaviors—such as smartphone use—in bed may weaken this association, making it more difficult to fall asleep. Consistent with these explanations, studies have demonstrated that using smartphones before bedtime is linked to poorer sleep quality [157, 158].

The mediating role of FoMO in the relationship between doomscrolling and poor sleep quality was not found to be significant (H₇: Rejected). This finding may be explained by the sensitivity of FoMO to contextual factors, such as social media use patterns, platform preferences, and online social sensitivity. However, this interpretation should be approached cautiously, as these contextual factors were not assessed in the present study. Although FoMO is grounded in the fear of missing out, the extent to which this construct influences individuals at behavioral or physiological levels may vary depending on the purposes of social media use. In the present study, the fact that participants most frequently used Instagram (55%), WhatsApp (21%), and YouTube (11%) may have led to relatively limited social comparison processes that typically trigger FoMO, although this explanation is tentative because platform-specific social comparison was not measured. Indeed, it has been reported that active use does not always increase FoMO and may, in some cases, reduce FoMO by enhancing social connectedness [159]. In this context, the communication-based and passive-consumption nature of WhatsApp and YouTube may reduce visibility and social comparison pressure, thereby preventing the intensification of FoMO. Still, this mechanism was not directly examined in this study and should be interpreted cautiously. Moreover, the low use of platforms that are associated with higher FoMO risk, such as X (Twitter) (9%) and TikTok (5%) [160–162], may also have weakened FoMO’s potential mediating role in the model, which carry high FoMO risk, may also have weakened FoMO’s role in the model. However, this possibility has not been empirically tested and should be viewed with caution. Another factor that may contribute to the absence of mediation is the developmental nature of FoMO. The literature suggests that FoMO is a developmentally sensitive construct, declining markedly after adolescence [163, 164]. This indicates that the behavioral impact of FoMO may be relatively weaker in adult samples. Therefore, the adult composition of the current sample may have prevented FoMO from reaching a level that would increase pre-sleep cognitive arousal. Another explanation for the lack of a mediating role is the cultural and behavioral characteristics of the adult population in Türkiye. In societies with collectivistic traits, such as Türkiye, social connectedness is maintained mainly through face-to-face relationships [165], and online social comparison is given relatively less importance, which may reduce the emotional intensity of FoMO. This may indicate that FoMO does not operate as a strong standalone mechanism and may become more pronounced only when interacting with other psychological processes such as nomophobia, stress, digital burnout, or low self-control. However, this explanation should be interpreted cautiously since these factors were not measured in this study.

Nomophobia was found to have a positive and significant mediating role in the relationship between doomscrolling and poor sleep quality (H₈: Accepted). This suggests that while doomscrolling contributes to poorer sleep quality [136], the presence of nomophobia intensifies this effect. Doomscrolling has also been linked to heightened stress and increased cognitive arousal, making relaxation more challenging [166, 167]. Additionally, nomophobia is associated with a greater online presence and prolonged smartphone use [89, 168]. According to Displacement Theory [169], increased media use may result in a reduction of time allocated to essential activities, such as sleep. Therefore, individuals who both consume distressing online content and experience fear of being separated from their smartphones may allocate more time to phone use at night, further weakening their sleep quality [170, 171].

FoMO and nomophobia together were found to have positive and significant mediating roles in explaining poor sleep quality through doomscrolling (H₉: Accepted). Within the CIUT framework, doomscrolling—defined as scanning negative news and social media content to cope with stress, uncertainty, or loneliness—may initially provide temporary relief but gradually increases the need to stay online continuously [172]. This heightened emotional and cognitive arousal can foster both FoMO [173], through concerns about missing developments, and nomophobia, as individuals rely on their smartphones to regulate anxiety and perceived threats. Consequently, smartphones may be used as tools for emotional compensation, leading to excessive and late-night use that undermines sleep quality [174]. The Pathways Model of Problematic Mobile Phone Use [175] further supports this process by emphasizing that difficulties in self-control, impulsivity, and reassurance-seeking can intensify uncontrolled smartphone use. In the context of doomscrolling, elevated arousal from harmful content may impair self-regulation [176], reinforcing FoMO-driven checking behaviors and nomophobia-related anxiety when offline. Therefore, doomscrolling may reduce sleep quality through a combination of cognitive mechanisms (e.g., fear of missing out) and emotional mechanisms (e.g., seeking security), which together promote prolonged nighttime smartphone use.

The examination of doomscrolling, FoMO, nomophobia, and sleep quality together within a single multiple mediation model in this study extends the limited body of research that addresses the links between digital behaviors and sleep outcomes within a process-oriented and holistic framework. The findings suggest that although FoMO alone does not serve as a significant mediator, the indirect effects emerging alongside nomophobia may help clarify some of the inconsistent results in the literature. In contrast, the strong and consistent mediating role of nomophobia adds a new explanatory dimension to the literature by indicating that technology-related anxiety may play a central role in the relationship between doomscrolling and sleep quality. Moreover, the findings provide an opportunity to evaluate in greater detail the interaction of emotional and cognitive processes proposed by the I-PACE model and offer an additional perspective on how cultural context may shape understanding in the field through data obtained from an adult sample in Türkiye.

Limitations and recommendations

This study has several limitations that should be taken into account when interpreting the findings. First, the data were obtained from a Turkish adult sample with an uneven age and gender distribution, which restricts the generalizability of the results. Future research could benefit from more balanced and diverse samples, allowing for a more precise examination of age- and gender-related differences. In addition, FoMO did not demonstrate a significant mediating effect in the present model; therefore, future studies may explore this construct alongside other psychological variables, such as stress, digital dependence, or self-regulation, to clarify its contextual role. Because the study employed a correlational design, causal conclusions cannot be drawn. Longitudinal or experimental studies are needed to test whether doomscrolling, FoMO, and nomophobia exert direct causal effects on sleep outcomes. Finally, the findings highlight practical implications: digital hygiene interventions and psychoeducation programs could incorporate content aimed at reducing technology-based anxieties (e.g., doomscrolling, nomophobia) and promoting healthier pre-sleep routines such as limiting nighttime social media exposure, increasing awareness of sleep-disruptive digital behaviors, and encouraging screen-time boundaries.

The data of the present study were collected from participants selected through convenience sampling and were based on self-report responses. This may limit the representativeness of the sample and lead to response bias due to participants’ subjective perceptions. However, the fact that all measurement instruments used in the study have been established as valid and reliable in previous research may partially mitigate potential self-report bias. In addition, although convenience sampling facilitates access to a large and diverse participant pool, future studies using more representative samples would enhance the generalizability of the findings. Therefore, employing different sampling frames, probabilistic sampling methods, and multiple data sources in subsequent research would be beneficial.

The measurement instruments used in the study were administered via Google Forms. To minimize potential data accuracy issues, several protective measures were implemented. First, the instructions within the form clearly explained how each item should be answered. The form settings were configured to allow each participant to submit responses only once, and all items were made mandatory. Participants were also informed that they could contact the researchers via e-mail if they were unsure about how to respond to any of the scale items. Additionally, the dataset was screened for potential irregularities, such as excessively fast or slow response times. Although the use of an online self-report form carries inherent limitations, these measures are considered to provide a methodological framework that enhances data accuracy and reliability.

Conclusion

According to the study's results, doomscrolling was found to be positively and significantly associated with poor sleep quality. Doomscrolling was a significant predictor of both FoMO and nomophobia, and FoMO also had a significant predictive effect on nomophobia. However, while FoMO did not directly predict poor sleep quality, nomophobia was found to be a positive and significant predictor of poor sleep quality. In line with these results, it was concluded that nomophobia had a positive and significant mediating role in the relationship between doomscrolling and poor sleep quality. In contrast, FoMO did not have a significant mediating role in this relationship. Nevertheless, FoMO and nomophobia together were found to have a statistically significant mediating role in the effect of doomscrolling on poor sleep quality.

Abbreviations

FoMO

Fear of Missing Out

Nomophobia

No Mobile Phone Phobia

I-PACE

Interaction of Person–Affect–Cognition–Execution

CIUT

Compensatory Internet Use Theory

Authors’ contributions

FC and ÖU collaborated on the research design. ÖU made significant contributions to the data collection process. FC contributed significantly to data analysis and interpretation. FC and ÖU read and approved the final manuscript draft.

Funding

Not applicable.

Data availability

Data can be retrieved at OSF: [https://doi.org/10.17605/OSF.IO/R7BWG] (https:/doi.org/10.17605/OSF.IO/R7BWG).

Declarations

Ethics approval and consent to participate

Research permission was received from the Social and Human Sciences Ethics Committee of Bursa Uludağ University, Türkiye (Approval No: 16; Date: 03.05.2024). The purpose and content of the study were introduced to the participants. The Informed Consent Form for the research was presented to the participants, and their consent forms were obtained for voluntary participation. We confirm that all practices described in the article were carried out in accordance with relevant guidelines and regulations, including the Declaration of Helsinki.

Consent for publication

Not applicable.

Competing interests

The authors declare no competing interests.