Nomophobia, Attachment Styles, and Loneliness: A Study Among Adults in Cyprus

Abstract

The rapid increase in global smartphone usage and the range of capabilities they offer have resulted in an overdependence on them, leading to the term nomophobia. Nomophobia refers to the psychological discomfort or anxiety experienced when an individual is unable to use or does not have access to their mobile phone, and it is a phenomenon that warrants research attention due to its psychological and social implications. The aim of the current study was to examine the relationship between nomophobia and the time spent on mobile usage, attachment in close romantic relationships, and loneliness. Participants included 300 adults from Cyprus who were recruited through convenience and snowball sampling methods. Data were gathered using an internet-based questionnaire that assessed participants’ time spent on mobile usage, their attachment styles in close relationships, and their level and type of loneliness. The results suggest that (a) anxiety dimension and time spent on mobile phone are significant predictors of nomophobia, (b) higher levels of nomophobia are associated with an insecure attachment style, (c) more severe levels of nomophobia are associated with higher levels of loneliness, and (d) increased time spent on mobile usage is linked to higher levels of nomophobia. The findings suggest that the widespread emergence of nomophobia raises important concerns, highlighting the need for the development of educational programs that promote balanced mobile usage and encourage direct social interaction. The significance of targeted interventions that address mobile phone regulation and attachment-related vulnerabilities is emphasized.

1. Introduction

The term Nomophobia derives from “no mobile phone phobia”, and refers to the psychological discomfort or anxiety experienced when an individual is unable to use or does not have access to their mobile phone [1,2,3,4,5]. Nomophobia includes fears related to communication loss, disconnection, lack of access to information, and absence of connectivity [6]. Although not currently recognized as a mental disorder in the Diagnostic and Statistical Manual of Mental Disorders (DSM-5), given the rapid increase in smartphone usage globally, some researchers have described it as the disorder of the 21st century, resulting from technological advancements [7,8]. Thus, understanding this phenomenon has become increasingly relevant.

Mobile phones, once considered a luxury, have rapidly evolved into an essential part of daily life [9]. Studies suggest that mobile phones can act as a psychological comfort during stressful times, serving as a “security blanket” similar to attachment objects in children [10]. While their development is often linked to broader technological progress [11], their widespread adoption has significantly changed how people communicate daily [12]. In recent decades, smartphone usage has surged dramatically, with global smartphone market revenue projected to reach USD 485.3 billion by 2025 and continue to grow annually by 3.76% between 2025 and 2029 [13].

The widespread use of smartphones serves users not only as tools for enhanced communication but also as gateways to unlimited information, entertainment, gaming, video, music, social interaction, education, and study networks [14,15,16]. This highlights their essential role in contemporary society. In fact, mobile phones enable people to stay connected with others, providing a sense of security. Individuals can use them in various ways, such as chatting, taking pictures, working, buying goods and services, or controlling home appliances in a faster and more efficient way [17,18]. Despite their advantages, extensive reliance on smartphones raises concerns about their potential overuse and dependence [19], while simultaneously creating new problems for users [20,21]. This smartphone overuse poses an emerging threat to physical, mental, and social health [22], including eye fatigue and neck pain [23], headaches [24], musculoskeletal problems [25], spine issues, and sleep disturbances [4,14,26,27,28,29,30].

One of the most significant adverse outcomes of smartphone overuse is smartphone addiction, which significantly affects daily life [31,32]. This growing concern about smartphone addiction has intensified research interest in nomophobia, with the literature suggesting a positive relationship between the two [26,33,34,35]. Given this connection, understanding the dynamics of nomophobia is essential for addressing its broader psychological and social implications.

Importantly, the phenomenon of nomophobia is prevalent globally, with studies indicating very high rates across different countries. For example, research in Australia reported rates of 99% [36]. Similarly, high rates have been documented in countries like Italy [17], Croatia [37], India, the Philippines, Tunisia, and Malaysia [4,23,38,39,40]. A study in Greece showed that 99.9% of the participants exhibited some level of nomophobia, with moderate and severe levels at 75.9% [10]. Similarly, data from our broader research project in Cyprus, examining various aspects of nomophobia, indicated comparably high prevalence rates, showing that nearly all participants (99.3%) experience some level of nomophobia, with more than half (51.3%) exhibiting moderate levels [41].

Nomophobia has also been extensively examined in relation to physical and mental health, with multiple studies identifying a positive relationship with various adverse health conditions [29,39,42]. These include social anxiety (formerly known as social phobia) [1,43], anxiety [14,37,44,45,46], separation anxiety [47,48] depression [2,37,44,45,49], and stress [2,37,44,50].

In addition to mental health conditions, nomophobia has been linked to several other factors, such as alexithymia and metacognitive problems [51], emotional difficulties [37], emotional intelligence [52], shyness [46], and low self-esteem [52,53,54]. Further associations include problematic smartphone use [36], smartphone addiction [4,26,38], high engagement in social media [16,41,45,55], mobile phone attachment [56], insomnia symptoms and poor sleep quality [26,28], fear of missing out (FoMO) [5,27,57,58,59], emotional exhaustion at work [60], and poor academic performance [5,61,62]. The literature has also examined the relationship between nomophobia and coping styles, indicating a correlation between the two variables [41,50,63]. Collectively, these findings emphasize the need for further research into nomophobia as a significant psychological concern that carries broader health implications.

Building on these associations, researchers have also examined how smartphone usage patterns relate to nomophobia. Data from our broader research project in Cyprus indicated that communication was the most common reason for phone use, with 89.7% of participants identifying it as their primary activity. Social media closely followed, showing a strong association with nomophobia [41]. The literature supports this connection, with studies indicating that social media habits significantly predict nomophobia [55] and that individuals with severe nomophobia exhibit higher rates of social media use via smartphones [45].

Despite growing awareness, nomophobia is not yet recognized by the World Health Organization (WHO) as a mental health condition [30]. However, researchers argue that it closely aligns with established diagnostic criteria for mental disorders [64], suggesting that it could be classified either as a specific phobia [17,36] or a form of smartphone addiction [4,65]. Regardless of its eventual classification, acknowledging nomophobia as a mental health concern is vital as it could influence research, awareness, and interventions.

Based on this ongoing debate, it remains unclear which theoretical framework best captures the concept of nomophobia. While some researchers highlight the psychological dependence resulting from fear and anxiety related to the absence of access or inability to use a mobile phone [6], others consider nomophobia as a situational phobia that is related to agoraphobia [7]. For instance, a study indicated that communication dependency, a characteristic of nomophobia, might uncover underlying disorders [8]. Specifically, it suggested that social anxiety disorder (formerly known as social phobia disorder) leads to dysfunctional behaviors in individuals experiencing nomophobia. The researchers argue that information technology offers a protective and secure way for individuals with social anxiety to interact both personally and socially, thereby alleviating the symptoms and conflicts related to their anxiety.

Furthermore, nomophobia can be discussed within the framework of attachment theory, which considers the emotional and psychological aspects of an individual’s interaction with mobile phones [15]. According to Bowlby [66], attachment originates in early childhood as a bond between infants and caregivers. Ainsworth later classified attachment styles into secure and insecure categories, including anxious and avoidant types, based on children’s reactions to caregiver separation and reunion [67,68]. In later years, Main and Solomon [69] introduced a third category of insecure attachment, referred to as disorganized insecure attachment, which is characterized by both elevated anxiety and avoidance. In relationships, attachment is commonly conceptualized along two dimensions: avoidance attachment, which reflects discomfort with dependency and closeness to others, and anxiety attachment, which reflects fear of rejection and abandonment [70]. Individuals low in both avoidance and anxiety attachment are typically securely attached, while other combinations reflect insecure attachment patterns [71]. These dynamics extend into adulthood, where secure attachment is characterized by confidence in emotional support, while insecure attachment is marked by doubt, fear of rejection, and emotional distancing [72,73]. Individuals often seek similar attachment figures in adult relationships, such as romantic partners or close friends [74].

Building on this theoretical foundation, recent studies have begun to explore the connection between attachment and nomophobia. For example, low parental responsiveness has been associated with higher levels of nomophobia [75]. Additionally, several studies have shown that insecure attachment, particularly anxious and avoidant styles, is positively associated with nomophobia [15,76,77,78]. For instance, Liang [78] found that attachment anxiety had a strong effect on nomophobia, while Sun et al. [79] noted that attachment anxiety was strongly associated with nomophobia, especially in relation to losing internet or social media access. Similarly, research indicates that smartphone attachment was a significant predictor of nomophobia among individuals with high levels of insecure anxious attachment [80].

Most research on attachment and nomophobia has concentrated on parent–child relationships. However, few studies have explored nomophobia in the context of romantic or close interpersonal relationships. These patterns suggest that nomophobia may reflect deeper relational insecurities. Problematic smartphone use, strongly associated with nomophobia, has also been linked to insecure attachment use [36,81]. These findings emphasize the need for further investigation into attachment in adult close relationships.

Researchers have also explored the connection between nomophobia and loneliness. Loneliness is broadly defined as the emotional state experienced when individuals perceive their relationships as insufficient or unsatisfying [80,82], often resulting from a lack of social belonging or intimate emotional connections [83]. It is typically categorized into social loneliness, referring to the perceived absence of a social network, and emotional loneliness, which reflects the lack of close relationships and emotional support [84,85]. Emotional loneliness appears more common, affecting 45% of individuals compared to 21.5% for social loneliness, with severe levels reported at 7.7% and 3.2%, respectively [86]. Recognized as an increasing public health concern [85], loneliness impacts approximately 33% of the general population in industrialized nations, with 8% experiencing severe loneliness [87]. Among university students in Germany, 32.4% reported moderate feelings of loneliness, while 3.2% faced severe loneliness [86]. Loneliness has also been linked to irritability, depression, and a 26% higher risk of premature mortality [86]. Several studies have found positive associations between nomophobia and loneliness [46,79,80,88], with some suggesting that loneliness may contribute to difficulties in emotional regulation and social interaction linked to nomophobia [54]. However, findings remain mixed, as other research has shown weak or non-significant associations across different dimensions of loneliness, such as familial, social, or romantic [89]. The inconsistent and inconclusive findings highlight the need for a deeper exploration of this connection.

It is worth mentioning that loneliness has also been studied in relation to smartphone and internet addiction. Several studies have identified a positive relationship between loneliness and smartphone addiction, indicating that lonely individuals may be more susceptible to excessive smartphone use [90,91,92]. However, some research has found no significant association between loneliness and problematic smartphone use [35]. Similarly, studies focusing on internet addiction and problematic internet use, which are also related to nomophobia, have produced mixed results. While numerous studies report a positive correlation between loneliness and internet addiction [82,90,93,94,95,96,97,98], others indicate no or even negative relationships [99]. These findings further highlight the importance of investigating loneliness in the context of nomophobia.

Based on the gaps identified in the existing literature, the present study aims to examine nomophobia in relation to attachment styles in romantic relationships and loneliness. Given the strong associations between nomophobia, problematic smartphone use, and relational insecurity, understanding how these psychological factors interact may offer important insights into the emotional and interpersonal dimensions of nomophobia. To the best of our knowledge, nomophobia has only been previously studied in Cyprus by Mousoulidou et al. [41], as part of our broader research project. That study investigated the relationship between nomophobia, coping styles, phone usage patterns, and demographic factors such as age, gender, and education. Findings indicated that 99.3% of participants exhibited some level of nomophobia, with younger adults, women, and individuals with lower education levels being more prone to it. Additionally, communication and social media use were positively linked to nomophobia, while maladaptive and avoidant coping strategies seemed to intensify its severity [41]. While the limited research on nomophobia in the Cyprus highlights an important gap, the true innovation of the current study lies in addressing the cultural specificity of the psychological constructs under investigation. As mentioned before, nomophobia is shaped by culturally embedded fears, such as losing communication or access to information, that may hold different meanings and intensities across populations [6]. While the high percentage of participants exhibiting some level of nomophobia in Cyprus is comparable to neighboring Mediterranean countries, it is driven by distinct factors like communication dependency. These patterns likely reflect broader sociocultural traits. For instance, Cypriots show lower attachment anxiety and higher avoidance compared to global averages [100], suggesting a relational style that values autonomy but may foster emotional reliance on smartphones as safer forms of connection. Likewise, despite strong familial bonds common in Mediterranean societies, Cyprus reports loneliness levels (16–17%) that exceed the EU average, pointing to the emotionally insular nature of these networks [85,86,101]. These findings underscore that while associations between nomophobia, attachment, and loneliness have been documented elsewhere [78,80], such relationships may operate differently in Cyprus due to its distinct sociocultural context. These factors, along with rising smartphone penetration and high engagement with communication and social media apps in Cyprus [102,103], shape a unique context in which nomophobia may manifest differently than in other populations. Therefore, by situating nomophobia, attachment, and loneliness within Cyprus’s distinct socio-emotional landscape, this study offers culturally nuanced insights that go beyond merely replicating existing models, underscoring its originality and relevance. Based on the existing literature and the purpose of the study, the following hypotheses were formulated:

Hypothesis 1 (H1). 

Associations between time spent using mobile phones and nomophobia are expected. Consistent with previous research indicating a positive correlation between mobile phone use and nomophobia, it is anticipated that individuals who spend more time on their phones will exhibit higher levels of nomophobia.

Hypothesis 2 (H2). 

Insecure attachment style is expected to be positively associated with nomophobia, while secure attachment style is expected to be negatively associated with it. This is in line with previous research showing that individuals with insecure attachment tend to report higher levels of nomophobia, whereas those with secure attachment are less likely to do so. Additionally, since insecure attachment is characterized by elevated levels of either anxiety or avoidance, the anxious dimension and avoidant dimension explored in the current study are also expected to be positively associated with nomophobia.

Hypothesis 3 (H3). 

A positive association between the subjective feeling of loneliness and nomophobia is expected. Although research in this area is still limited, existing studies suggest a positive relationship between loneliness and nomophobia. Moreover, loneliness has been linked to problematic smartphone usage and smartphone addiction, both associated with nomophobia. Therefore, higher levels of loneliness are expected to be positively correlated with nomophobia.

2. Materials and Methods

2.1. Procedure

This study is part of a broader research project previously published by Mousoulidou et al. [41], which examined the prevalence of nomophobia in Cyprus and its associations with demographic characteristics and coping strategies. While the same recruitment strategy and data collection procedure were followed, the current study examines previously unexplored variables: time spent on mobile phone use, attachment styles, and loneliness. Ethical approval was granted by the Cyprus National Bioethics Committee (EEBK EΠ 2024.01.94), and data were collected through a self-administered Google Forms questionnaire from 10 April–29 April 2024, utilizing convenience and snowball sampling methods. Recruitment was carried out via social media platforms (e.g., Facebook), messaging apps (e.g., Viber, WhatsApp, Messenger), and email. Informed consent was obtained prior to participation, and the questionnaire required approximately 10 min to complete.

2.2. Sample

The current study draws on the same participant pool as the previously published study by [41]. Eligibility criteria included being 18 years of age or older, a native Greek speaker, and residing on the mainland of Cyprus. After screening for age eligibility, the final sample consisted of 300 adults (68.4% female, 31.3% male, and 0.3% other), aged 18 to 77 years (M = 34.9, SD = 13.8). The age distribution classified participants into three groups: (a) emerging adults (N = 103, 34.3%), (b) early-aged adults (N = 90, 30%), and (c) middle-and-late-aged adults (N = 107, 35.7%). Education level ranged from secondary education (26.7%) to doctoral degree (2.6%).

2.3. Measures

Demographic Information: In the context of the broader research project [41], participants completed a demographic questionnaire developed by the research team. A previously unused item from that questionnaire, regarding daily mobile phone usage, was included for the current analysis. Participants reported their average daily mobile phone use by selecting from three predefined categories: (a) 0–2 h, (b) 3–5 h, and (c) more than 5 h. These categories corresponded to low, moderate, and high phone usage. The categorization is based on global data indicating that the average daily phone usage is approximately 4 h and 37 min [104], placing the 3–5 h range around global average.

Nomophobia: Participants’ levels of nomophobia were assessed using the 20-item Nomophobia Questionnaire (NMP-Q) developed by [6] and validated in the Greek language by [105]. Items are rated on a seven-point Likert-type scale, ranging from 1 (strongly disagree) to 7 (strongly agree), with total scores ranging from 20 to 140. Higher scores indicate greater nomophobia severity and are categorized as follows: absence (≤20), mild (21–59), moderate (60–99), and severe (100–140). In addition to the overall score, the NMP-Q comprises four factors that provide a qualitative understanding of the condition [105,106]. These factors are: (a) “not being able to communicate”, (b) “losing connectedness”, (c) “not being able to access information”, and (d) “giving up convenience”. The items’ internal reliability for the current sample was excellent, with a Cronbach’s alpha value of 0.945. Reliability was excellent for Factor “not being able to communicate” (α = 0.951) and Factor “losing connectedness” (α = 0.9), and very good for Factor “not being able to access information” (α = 0.825) and Factor “giving up convenience” (α = 0.864).

Close Relationships: Participants’ attachment styles in adult romantic relationships were assessed using the Experiences in Close Relationships Scale Revised (ECR-R-36), developed by [71] and validated in Greek by [107]. The questionnaire consists of 36 items (e.g., “I’m afraid that I will lose this person’s love”) rated on a seven-point Likert-type scale ranging from 1 (strongly disagree) to 7 (strongly agree), and covers romantic relationships, including marriage. The ECR-R includes two subscales that measure two dimensions: (a) the avoidant dimension, which reflects discomfort with closeness and dependence, and (b) the anxious dimension, which reflects fear of rejection and abandonment [70]. Scores for each dimension are calculated by averaging responses across the 18 corresponding items. Based on these averages, individuals are characterized as having high or low anxiety and high or low avoidance. A mean score above 4 indicates a high level on the respective dimension, while a score below 4 indicates a low level. In addition to the dimensions, the scores of the subscales of the ECR-R can also be used to classify participants into different attachment styles. In the current research, we adopted a two-category approach: (a) secure attachment, characterized by low scores on both subscales, and (b) insecure attachment, characterized by any other combination of scores on the two subscales. This classification was used to ensure sufficient group sizes and statistical power for the planned analyses. It is worth noting that an alternative approach involves classifying attachment into four attachment styles: (a) secure (low anxiety, low avoidance), (b) anxious (high anxiety, low avoidance), (c) avoidant (low anxiety, high avoidance), and (d) disorganized (high anxiety, high avoidance) [108]. The internal consistency of each subscale was high, with Cronbach’s alpha values of 0.862 for avoidant dimension and 0.926 for anxiety dimension.

Loneliness: To assess participants’ level of loneliness, the 20-item UCLA Loneliness Scale, developed by [109] and validated in Greek by [110] was employed. The scale includes 20 questions (e.g., “How often do you feel isolated from others?”), which are rated on a four-point Likert-type scale ranging from 1 (never) to 4 (often). This results in a total score between 20 and 80, with higher scores indicating greater loneliness. A commonly used categorization includes: (a) low degree of loneliness (score between 20 and 34), (b) moderate degree of loneliness (score between 35 and 49), (c) moderately high degree of loneliness (score between 50 and 64) and high degree of loneliness (score between 65 and 80) [111]. The scale demonstrated excellent internal consistency, with a Cronbach’s alpha of 0.930.

2.4. Data Processing and Measures

Upon completion of data collection, preliminary data processing and scoring were conducted. Participants were initially divided into three categories based on their self-reported time spent on mobile phone usage: (a) low, (b) medium, and (c) high phone usage. However, since no participants reported using their phones for more than five hours per day, the high-usage category was not included in the subsequent analyses. Consequently, 72.3% of the participants reported low phone usage, while 27.7% reported medium phone usage. For the Nomophobia Questionnaire (NMP-Q), participants were categorized into four nomophobia levels based on their total scores: (a) absence of nomophobia, (b) mild nomophobia, (c) moderate nomophobia, and (d) severe nomophobia. Notably, only two participants (0.7%) fell into the “absence of nomophobia” category; therefore, these cases were excluded from analyses examining associations between nomophobia type and other variables. Among the remaining participants, 23.3% exhibited mild nomophobia, 51.3% moderate, and 24.7% severe. In addition, scores were calculated for each of the NMP-Q’s subscales: (a) not being able to communicate, (b) losing connectedness, (c) not being able to access information, and (d) giving up convenience. Participants’ scores on the ECR-R were used to calculate the two dimensions: avoidant and anxious. Each dimension was classified as either low or high based on a cut-off score of 4, resulting in four possible combinations. These combinations were used to identify participants’ attachment styles as: (a) secure attachment: low avoidance, low anxiety, and (b) insecure attachment: any other combinations of avoidance and anxiety, apart from low avoidance and low anxiety. Of the total sample, 67% were identified as having a secure attachment style, and 33% as having an insecure attachment style. Finally, using the total score from the UCLA Loneliness Scale, participants were categorized into four levels of loneliness: (a) low, (b) moderate, (c) moderately high, and (d) high. Descriptive statistics showed that 27.3% of participants exhibited low loneliness, 46% moderate, 22.7% moderately high, and 4% high loneliness.

2.5. Statistical Analysis

All data were entered into the Statistical Package for Social Sciences, Version 29.0 (SPSS 29, IBM Corporation, Armonk, NY, USA), with the significance level set at 5%. Preliminary analyses included calculating descriptive statistics for mobile phone usage, loneliness levels, and attachment dimensions (anxiety and avoidance). Demographic variables were not analyzed in the current study, as they were addressed in a previous publication [41]. Quantitative variables were tested for normality using the Kolmogorov–Smirnov test. Although the results indicated that, with the exception of total nomophobia, all variables significantly deviated from normality (p < 0.05), parametric tests were used in the analyses. This decision was based on the fact that skewness and kurtosis values fell within the acceptable range of ±1, suggesting that the distributions were approximately normal. Consequently, Pearson correlations, t-tests, ANOVAs, and linear regressions were conducted. Regression assumptions of normality were assumed. The assumptions of normality for regression analyses were assumed. An independent t-test was used to examine differences in nomophobia according to phone usage time. Chi-square tests were used to examine associations between phone usage time and nomophobia types. Regarding attachment, Pearson correlation coefficients were calculated to assess the relationships between the two attachment dimensions and both total nomophobia and its subscales. Chi-square tests were conducted to examine the relationship between attachment type (secure/insecure) and nomophobia type. Additionally, independent samples t-tests were used to assess differences in nomophobia based on attachment type. Pearson correlations were also conducted to examine associations between total loneliness and nomophobia (overall and subscales). Chi-square tests were used to explore associations between loneliness types and nomophobia types, while a one-way ANOVA tested differences in total nomophobia based on loneliness type. Finally, linear regression analysis was used to examine the predictive role of each independent variable on nomophobia.

3. Results

To examine Hypothesis 1 and the statistical differences between nomophobia and the time spent on mobile phone usage, an Independent Sample t-test was computed using the total nomophobia score and the two time-use categories (i.e., low and medium). Levene’s test for equality of variances was not significant, F(1, 298) = 0.401, p = 0.527, indicating homogeneity of variances. The analysis showed statistically significant differences between participants with low phone usage (N = 217, M = 75.94, SD = 25.17) and those with medium usage (N = 83, M = 91.43, SD = 23.81), t(298) = −4.841, p < 0.001, indicating that medium mobile phone users reported more severe levels of nomophobia, compared to low mobile phone users. Thus, increased time spent on mobile phone use is associated with more severe levels of nomophobia. A Chi-Square test further showed a significant association between time spent on mobile usage and nomophobia χ²(2, N = 298) = 15.250, p < 0.001. Crosstabs analysis showed that among low-usage participants, 27.9% exhibited mild, 52.6% moderate, and 19.5% severe nomophobia. Among the medium-usage participants, the corresponding rates were 12%, 49.4%, and 38.6%. Thus, Hypothesis 1 was supported.

To examine Hypothesis 2 and possible associations between nomophobia and attachment, several analyses were conducted. First, a Chi-Square test was conducted to examine the relationship between the three severity levels of nomophobia (i.e., mild, moderate, severe) and attachment style (i.e., secure, insecure). The results revealed a statistically significant association χ²(2, N = 298) = 10.544, p = 0.005, indicating that nomophobia severity level differed significantly by attachment style. Among participants with secure attachment, 27% exhibited mild nomophobia, 53.5% moderate, and 19.5% severe nomophobia. For participants with insecure attachment, 16.3% demonstrated mild nomophobia, 48% moderate, and 35.7% severe. An Independent Samples t-test was also computed to compare total average nomophobia scores between participants with secure and insecure attachment styles. Levene’s test for equality of variances was not significant, F(1, 298) = 0.531, p = 0.467, indicating that the assumption of homogeneity of variance was met. The results showed statistically significant differences between participants with secure attachment (N = 201, M = 77.14, SD = 24.76) and those with insecure attachment (N = 99, M = 86.48, SD = 26.61), t(298) = 2.999, p < 0.003, indicating that participants with insecure attachment style exhibit more severe levels of nomophobia compared to those with secure attachment style. The effect size was calculated using Cohen’s d, which was found to be equal to 0.368, indicating a small-to-moderate effect. Therefore, individuals with insecure attachment styles tend to experience higher levels of nomophobia, thus supporting this part of Hypothesis 2.

Pearson correlation analysis was conducted to investigate the second part of Hypothesis 2 and the possible associations between the nomophobia total score and the two attachment subscales.

Table 1. Correlations between nomophobia factors and attachment dimensions.

	1	2	3	4	5	6	7	8
1. Nomophobia Total Score	---
2. Nomophobia “Not being able to communicate”	0.853 **	---
3. Nomophobia “Losing connectedness”	0.831 **	0.554 **	---
4. Nomophobia “Not being able to access information”	0.690 **	0.431 **	0.482 **	---
5. Nomophobia “Giving up convenience”	0.898 **	0.684 **	0.704 **	0.545 **	---
6. Anxiety Dimension	0.335 **	0.255 **	0.349 **	0.156 **	0.321 **	---
7. Avoidance Dimension	0.120 *	00.071	0.143 *	0.027	0.142 *	0.576 **	---
8. Loneliness Total Score	0.222 **	0.185 **	0.229 **	0.090	0.205 **	0.605 **	0.468 **	---

Note. ** Correlation is significant at the 0.01 level (2-tailed); * Correlation is significant at the 0.05 level (2-tailed).

shows the associations between the four nomophobia factors, the two attachment dimensions (i.e., anxiety and avoidance), and the loneliness total score. As is clear from the table, the nomophobia total score was found to be positively correlated with both anxiety and avoidance dimensions. These findings provide support for the second part of Hypothesis 2.

To examine Hypothesis 3 and the relationship between loneliness and nomophobia, Pearson correlation analysis was conducted. Nomophobia total score was found to be significantly positively related to the subjective feeling of loneliness r(298) = 0.222, p < 0.001. Further analysis of the nomophobia factors revealed statistically significant positive correlations between loneliness and three factors of nomophobia: “not being able to communicate”, r(298) = 0.185, p = 0.001; “losing connectedness”, r(298) = 0.229, p < 0.001; and “giving up convenience” r(298) = 0.205, p < 0.001. The correlation between loneliness and the nomophobia factor “not being able to access information” was not statistically significant, r(298) = 0.09, p = 0.119.

To investigate differences in nomophobia across levels of loneliness, a one-way ANOVA was conducted, with nomophobia total score as the dependent variable and the loneliness categories (i.e., low, moderate, moderately high, and high) as the independent variables. Before conducting the one-way ANOVA test, Levene’s test for homogeneity of variances was performed showing a statistically significant result, F(3, 294) = 3.178, p = 0.024, indicating that the assumption of homogeneity of variance was not met. Therefore, Welch’s ANOVA was conducted, which is considered to be robust in cases where the assumption of equal variances is violated. Welch’s test revealed that there were statistically significant differences between nomophobia and loneliness F(3, 47.49) = 4.848, p = 0.005. The effect size as measured by Omega squared (ω2) was 0.043, indicating a small to medium effect and thus the difference in nomophobia total scores across loneliness levels explains about 4.3% of the variance in the data. In addition, post hoc comparisons showed that participants with moderate loneliness reported significantly higher nomophobia than those with low loneliness (MD = 3.472, p = 0.022). Furthermore, individuals with moderately high loneliness had statistically significantly more severe nomophobia than those with low loneliness (MD = 4.074, p < 0.001). It is noted that any other comparisons between groups were not statistically significant. A Chi-Square test was also performed to examine the association between loneliness categories (i.e., low, moderate, moderately high, and high) and nomophobia severity level (i.e., mild, moderate, severe). Results indicated a statistically significant relationship χ²(6, N = 298) = 27.0044, p < 0.001. Statistically significant differences in nomophobia severity level were observed across all loneliness categories. Among participants with low loneliness, 37% exhibited mild nomophobia, 47% moderate, and 16% severe. For moderate loneliness, the respective figures were 18.2%, 60.6%, and 21.2%. In the moderately high loneliness group, 16.2% exhibited mild nomophobia, 45.6% moderate, and 38.2% severe. Finally, in the high loneliness group, 33.3% showed mild nomophobia, 16.7% moderate, and 50% severe. Therefore, Hypothesis 3 was supported.

Further to the above analyses, a hierarchical linear regression was conducted to examine the predictive value of anxiety dimension, avoidance dimension, and loneliness (Model 1), the added contribution of mobile usage time (Model 2), and finally the contribution of attachment style (Model 3) on nomophobia. Please note that socio-demographic factors were not examined in the current research, so they were not included in any of our analyses.

Table 2. Hierarchical regression analysis predicting nomophobia.

Model	B	S.E.	β	t	R2	ΔR2	ΔF
Step 1					0.122	0.122	13.675
Constant **	62.631	5.974		10.485
Anxiety Dimension **	7.578	1.538	0.371	4.929
Avoidance Dimension	−3.263	1.856	−0.119	−1.759
Loneliness Total Score	0.123	0.159	0.054	0.771
Step 2					0.163	0.041	14.388
Constant **	50.211	6.698		7.497
Anxiety Dimension **	6.735	1.520	0.330	4.430
Avoidance Dimension	−3.039	1.816	−0.111	−1.673
Loneliness Total Score	0.101	0.156	0.044	0.519
Mobile Usage Time **	11.863	3.128	0.207	3.793
Step 3					0.164	0.002	0.583
Constant *	40.318	14.591		2.763
Anxiety Dimension **	7.359	1.727	0.360	4.261
Avoidance Dimension	−2.216	2.113	−0.081	−1.049
Loneliness Total Score	0.094	0.156	0.041	0.602
Mobile Usage Time **	11.818	3.130	0.206	3.775
Attachment Style (Secure vs. Insecure)	3.604	4.721	0.066	0.763

Note. * p < 0.01, ** p < 0.001.

shows the regression analysis. Model 1 was statistically significant, F(3, 296) = 13.675, p < 0.001, with R² of 0.122, indicating that 12.2% of the variance in nomophobia could be explained by the model. Among the predictors, only the anxiety dimension emerged as significant. In Model 2, the inclusion of time spent significantly improved the model, ΔR² = 0.041. The overall model remained statistically significant, F(4, 295) = 14.317, p < 0.001, with R² increasing to 0.163, explaining 16.3% of the variance in nomophobia. In this extended model, anxiety dimension and time spent on mobile usage were significant predictors. In Model 3, the inclusion of attachment style (i.e., secure vs. insecure) did not significantly improve the model, ΔR² = 0.002. The overall model remained statistically significant, F(5, 294) = 11.554, p < 0.001, with R² increasing to 0.164, explaining 16.4% of the variance in nomophobia. In this extended model, anxiety dimension and time spent on mobile usage were significant predictors. These results suggest that higher the total anxiety and increased mobile use, predict more severe nomophobia levels, while attachment style does not contribute significantly to the prediction of nomophobia after adjusting for the previous predictors.

4. Discussion

The current study explored the relationship between nomophobia, time spent on smartphone use, loneliness, and attachment styles among adults in Cyprus. As smartphones have become an essential part of everyday functioning [9,10], concerns about overdependence have intensified. Nomophobia, often referred to as the “phobia of the modern age” [7,8] and the “disorder of the modern world” [10], captures the anxiety individuals feel when they are unable to use or access their mobile phones, although it is not formally recognized as a disorder in DSM-5. While mobile phones offer clear benefits to users, such as communication, access to information, social interaction, and entertainment [15,16], their excessive use has been linked to negative physical and psychological outcomes [20,21]. Within this context, the current study found that hours of mobile phone use are positively associated with nomophobia severity. Insecure attachment styles and more severe levels of loneliness are also positively related to nomophobia. Among these factors, the anxious dimension and time spent on mobile phone use are significant predictors of nomophobia. These findings contribute to the growing body of literature on nomophobia and its psychological correlates [78,112,113].

First, our results show that mobile phone usage is not only significantly related to nomophobia, but as the regression analysis showed, it plays a predictive role in its development. The regression model suggests that mobile phone usage is one of the two significant predictors of nomophobia. This supports the first hypothesis of the current study, which proposed that greater time spent on mobile phones would be associated with a more severe level of nomophobia. It also aligns with existing literature that has shown a positive relationship between mobile phone usage time and nomophobia [114,115]. In the present study, a higher percentage of participants who reported using their mobile phone for at least three hours per day (88%) exhibited moderate to severe nomophobia, compared to 72.1% of those who used their phones for up to two hours. While both groups reported more severe levels of nomophobia, the difference supports a trend suggesting that higher mobile phone usage is associated with increased nomophobia severity. These findings are consistent with earlier research by Schwaiger and Tahir [113], who identified hours of daily mobile phone use as a significant predictor of nomophobia. Similarly, Gonçalves et al. [112] found that the number of hours spent on smartphones per day was one of the strongest predictors of nomophobia. Overall, the current findings align with existing literature indicating that time spent on mobile phones is a key factor in nomophobia.

Second, this study indicates a consistent relationship between nomophobia and attachment style. That is, more severe levels of nomophobia are associated with insecure attachment style. Specifically, 83.7% of participants with insecure attachment reported moderate to severe nomophobia, compared to 73% of those with secure attachment. This finding supports existing literature that suggests insecure attachment is associated with greater nomophobia [15,76]. Further analysis revealed that both attachment dimensions (i.e., anxiety and avoidance) were positively related to nomophobia, in line with earlier findings [15]. However, the association with the avoidance dimension was weaker and only marginally significant (p = 0.039). This partially contrasts with the findings of Sun et al. [79], who reported no significant relationship between nomophobia and the avoidance dimension. By comparison, the anxiety dimension demonstrated a stronger and more consistent association with nomophobia. Additional insights emerged when examining the relationship between the four nomophobia factors and the two attachment dimensions. The anxiety dimension was significantly associated with all four nomophobia factors, reinforcing its strong link to the condition. The avoidance dimension, however, was significantly related to only two factors and showed no significant association with “not being able to communicate” and “not being able to access information”, further highlighting the stronger and more consistent role of the anxiety dimension. Regression analysis further supported the role of anxiety as a significant predictor of nomophobia, while the avoidance dimension did not contribute meaningfully to the model. This is consistent with previous research highlighting the predictive role of the anxiety dimension in nomophobia [78,80]. Notably, research examining nomophobia in the context of adult close relationships remains limited. Existing studies mainly focus on smartphone attachment or attachment patterns in parent–child relationships. Therefore, further investigation into how adult relationship attachment influences nomophobia is recommended.

Third, while loneliness was not found to be a significant predictor of nomophobia in the regression analysis, the consistent positive association between the two variables indicates a meaningful relationship. Specifically, more severe levels of nomophobia are associated with higher levels of loneliness, a finding that aligns with the previous research [46,79,80,88,116]. Moreover, when analyzing the relationship between loneliness and the four nomophobia factors, significant positive associations emerged for three of them. The exception was the factor “not being able to access information”, which showed no significant relationship with loneliness. This partially diverges from research conducted by Hussien [116], who found positive associations across all four nomophobia factors. Supporting the overall relationship, the present study also found that individuals with moderate loneliness exhibited more severe levels of nomophobia compared to those with low loneliness. Similarly, those with moderately high loneliness reported more severe levels of nomophobia than those in the moderate group. Further analysis of nomophobia levels by loneliness category showed that 62.9% of participants with low loneliness had a moderate to severe level of nomophobia. This proportion rose to 81.8% among those with moderate loneliness and to 83.8% among those with moderately high loneliness. Interestingly, in the high loneliness group, the percentage dropped to 66.7%, suggesting that extremely high loneliness does not consistently correspond with higher levels of nomophobia. Nonetheless, the lack of a significant predictive effect of loneliness in the regression analysis is not consistent with previous studies, which suggest that loneliness predicts nomophobia to some extent [77,80,88]. The variation in findings across studies underscores the necessity for further investigation into the complex relationship between nomophobia and loneliness.

The current study offers important theoretical insights, particularly within the framework of attachment theory. The findings suggest that the anxiety dimension may play a role in nomophobia and that individuals with insecure attachment styles tend to report higher levels of nomophobia. Although this study did not directly assess smartphone attachment, prior research has described nomophobia as a form of smartphone addiction [4,65] and positively linked it to smartphone attachment [56]. These connections suggest that smartphone attachment may function within broader frameworks of attachment. Specifically, our results align with earlier studies indicating that individuals with high attachment anxiety are more likely to form strong emotional dependencies, whether on people or objects [117]. Such individuals often engage in compensatory attachment strategies to maintain a sense of security [118], making their mobile phones important sources of emotional support. This dynamic may explain the heightened discomfort and fear they experience when separated from their phones [6]. Additionally, the hierarchical regression analysis indicated that the anxiety dimension and time spent on mobile use are significant predictors of nomophobia. These findings may; therefore, inform the design of prevention and intervention strategies to reduce phone dependency and its psychological impact.

Building on the above, the findings of this study highlight the need for practical measures to address nomophobia. Specifically, the results can inform targeted prevention and intervention strategies for individuals with high mobile use and those experiencing loneliness. While reducing screen time is challenging in today’s technology-driven environment, encouraging more in-person social interactions may help individuals fulfill their need for connection and minimize dependence on mobile devices. Educational programs should promote balanced phone use and emphasize the importance of real-world relationships, which digital interactions cannot substitute. These efforts should prioritize young adults, who appear to be more vulnerable [41], and involve parents and educators in raising awareness and fostering early support.

Despite the valuable findings of the current study, several limitations must be acknowledged. First, the cross-sectional design of the study, the sample size, and the sampling method limit the generalizability of the results. The relatively small sample and the use of convenience sampling reduce the study’s representativeness and generalizability. Furthermore, the sample was also unevenly distributed by gender, with a predominance of female participants. This imbalance may have introduced bias and limited the ability to generalize the findings across genders. Given that previous research [15] suggests that attachment styles and experiences of nomophobia may differ between males and females, the gender imbalance of the study could have influenced the observed relationships between these variables. Therefore, the interpretation and generalizability of these findings should be approached with caution. Additionally, while the study identified an association between mobile phone usage and nomophobia, this finding should be interpreted cautiously due to the broad categorization of time spent on mobile use. In particular, the present study divided participants into two groups: those who used their phones for zero to two hours daily and those who used them for three to five hours daily. Although a third option was available (more than five hours), no participants selected it, suggesting the original categories may have been too broad or misaligned with actual usage patterns. Therefore, the absence of participants in the high usage category may have affected the observed findings. Notably, the gap between two and three hours may have led to misclassification, indicating a need for more precise time brackets in future research. Generally, a larger sample that encompasses all categories of mobile usage time is believed to yield more reliable results. This could be accomplished by including a higher proportion of young people in the study sample, as they tend to spend more time on their phones. Finally, like many survey-based studies, the reliance on self-report measures carries the potential of response bias.

Future research should broaden the scope of psychological variables examined beyond time spent on mobile phones, attachment styles, and loneliness, which have been the focus of the current study. Factors such as anxiety, social media addiction, and other psychosocial influences should be considered to deepen the understanding of the mechanisms underlying nomophobia [2,44,119,120]. Subsequent studies should also aim to include larger and more diverse samples, particularly in terms of gender balance and varying levels of phone use. This would enhance the generalizability of findings and help clarify inconsistencies reported in the literature. Furthermore, the present study relies on subjective self-report measures, which may be considered a limitation. Future research would benefit from incorporating more objective methods for assessing nomophobia and related variables, such as hormone levels or non-invasive physiological indicators (e.g., buccal swabs), to enhance validity and clarify inconsistencies in the literature. Finally, given the high prevalence of nomophobia among younger populations globally [10,36,121,122], and in Cyprus specifically [41], future investigations should prioritize adolescents and young adults to support early, targeted interventions.

5. Conclusions

While mobile phones offer undeniable benefits to their users, the widespread emergence of nomophobia raises essential concerns. This study contributes to the growing literature by identifying time spent on mobile phones and attachment anxiety as key predictors of nomophobia, while also supporting associations with insecure attachment styles and loneliness. These findings have important practical implications. They suggest that interventions targeting excessive phone use and attachment-related insecurities may be effective in mitigating nomophobia and its mental health consequences. Promoting face-to-face interactions, encouraging emotionally secure relationships, and providing guidance on balanced technology use could be key components of mental health strategies. Moreover, there is a clear need to develop educational initiatives that promote balanced mobile use and reinforce the importance of direct social interaction. By addressing the psychological factors of excessive phone use, such efforts can promote healthier digital engagement and enhance overall emotional well-being. To that end, educational programs promoting digital self-regulation could help individuals recognize patterns of mobile overuse and adopt strategies for healthier engagement, such as setting daily usage limits. In parallel, mental resilience programs targeting anxiety and social pressure linked to constant connectivity may equip users with coping mechanisms for stress and emotional dysregulation associated with excessive phone and social media use. Developing targeted educational and psychological interventions, particularly for individuals with high attachment anxiety, could be essential for fostering healthier phone habits and supporting emotional well-being. These initiatives may serve as preventive tools for improving emotional regulation and ultimately reducing nomophobia. Finally, future research would benefit from incorporating more objective measures (e.g., physiological indicators) to deepen our understanding of this phenomenon.