Nomophobia Levels in Turkish High School Students: Variations by Gender, Physical Activity, Grade Level and Smartphone Use

Abstract

The rapidly changing dynamics of the digital age reshape the addiction relationship that high school students establish with technology. While smartphones remove boundaries in terms of communication and access to information, their usage triggers a source of anxiety and nomophobia. The increase in students’ anxiety levels because of their over-reliance on mobile phone use leads to significant behavioral changes in their mental health, academic performance, social interactions and financial dependency. This study examined the nomophobia levels of high school students according to selected socio-demographic indicators. Using the relational screening model, the multistage sampling technique was used to select a sample of 884 participants: 388 from Science High School and 496 from Anatolian High School (459 female, 425 male, Mage = 16.45 ± 1.14 year). Independent sample test and One-way ANOVA were applied. Depending on the homogeneity assumption of the data, Welch values were considered, and Tukey tests were applied as a second-level test from post hoc analyses. Comprehensive analyses of nomophobia levels revealed that young individuals’ attitudes towards digital technology differ significantly according to their demographic and behavioral characteristics. Variables such as gender, physical activity participation, grade level and duration of smartphone use are among the main factors affecting nomophobia levels. Female individuals and students who do not participate in physical activity exhibit higher nomophobia scores.

1. Introduction

The influx of technological tools and models to enhance human development and progression has skyrocketed. These tools range from mobile smartphones, laptops, computers, tablets, projectors and cameras to pen drives. The use of these tools has become essential due to the ease in accessing them and the increased use of social media and for fun and entertainment from other digital platforms. Smartphones are one of the most widely used tools offered by technology (Le Steunf et al., 2024). Smartphones can perform various functions like computers. People have started to access information more easily with their smartphones, and this has caused smartphones to become a part of individuals’ lives (Liébana-Cabanillas et al., 2014). In addition to communicating, they are also used for a wide variety of purposes such as connecting to the internet, accessing social networks, taking photos, shopping, listening to music, playing games and navigation (Lee et al., 2014; Prasad et al., 2017). The digitalization of society has profoundly changed the way individuals interact socially. While digitalization has enabled us to communicate, acquire knowledge, develop ideas and maximize opportunities, it has also brought challenges and risks that lead to new psychosocial pathologies, especially for young people (Salmela-Aro & Motti-Stefanidi, 2022). While anonymity allows individuals to interact by hiding their online identities, ease of access can lead to uncontrolled internet use. Accelerated intimacy allows online relationships to develop faster than those in the real world, while time distortion causes individuals to stay online for a long time without realizing it and changes in their perception of reality. When these factors come together, they contribute to the reinforcement of internet addiction (Greenfield, 1999). With the advancement of technology, social networks and access to the internet have enabled individuals to communicate and express themselves in the virtual world, but this has also led to addictions such as nomophobia (Lin & Huang, 2025). It occurs when an individual loses control over the use of technology, and this increases their dependence on technological tools. According to Bragazzi and Del Puente (2014), nomophobia is considered as a disorder of contemporary virtual and digital society and refers to anxiety, discomfort, irritability or distress caused by lack of contact with a computer or cell phone (Bragazzi & Del Puente, 2014). Nomophobia can cause pathological consequences such as depression, anxiety, distraction and aggressive behavior in adolescents (Black et al., 2022; Hällgren & Björk, 2022). Frequent use of mobile phones causes psychological, physical and behavioral problems in adolescents, exposing them to misinformation and inappropriate or risky contacts, and jeopardizing privacy and personal data security (Cerisola, 2017). Although there is no agreement on how we label or conceptualize problematic use of smartphones, we need to better understand this phenomenon and improve the way we intervene psychosocially to prevent and treat it (Ruiz-Ruano et al., 2020).

Nomophobia, defined as the fear or anxiety of being without or unable to use a mobile phone, has emerged as a growing public health problem worldwide. Extensive research shows that mobile device addiction negatively affects individuals’ sleep quality, academic performance and social interactions (Durak, 2019). Long-term smartphone use is associated with increased social isolation and decreased physical activity (Buke et al., 2021; Dwyer et al., 2023; Kardos et al., 2018; Lepp et al., 2014; Srivastava, 2005). These patterns are particularly prominent among adolescents and young adults, whose developmental stages increase susceptibility to digital overuse (Dursun et al., 2024). Recent studies show that the ubiquity of smartphones contributes to a sedentary lifestyle in youth and adult populations (Brailovskaia et al., 2023; Gonçalves et al., 2020; Precht et al., 2024). The captivating nature of digital content, including social media platforms, mobile games and short form videos, often replaces outdoor and physical activities, increasing health risks such as obesity and cardiovascular disorders (Geçgel, 2020; Brailovskaia et al., 2023). Moreover, excessive screen time has been associated with disrupted sleep routines and reduced motivation for physical activity (Al Battashi et al., 2021; Daraj et al., 2023). There is a strong correlation between mobile device addiction and sedentary behaviors, especially among university-aged individuals (AlMarzooqi et al., 2022; Daraj et al., 2023).

While global trends highlight the rise of nomophobia, its effects on the adolescent population in Turkey warrant closer scrutiny. Turkey has experienced rapid growth in smartphone penetration rates, and adolescents exhibit some of the highest levels of daily screen engagement. Cultural norms, educational pressures and urban lifestyle factors uniquely shape young people’s interaction with digital technologies in Turkey. Moreover, limited local data on the behavioral and health-related consequences of smartphone addiction creates a critical gap in understanding how nomophobia manifests in this context. Therefore, investigating nomophobia among high school students in Turkey is essential to inform region-specific preventive strategies and educational interventions.

This study examined nomophobia levels among high school students in Turkey, aiming to identify potential differences according to gender, physical activity participation, grade level and duration of smartphone use. The following research questions guided the study:

• Does the gender variable affect the level of nomophobia?
• Does the participation in physical activity affect the level of nomophobia?
• Does the high school type affect the level of nomophobia?
• Does the grade level affect the level of nomophobia?
• Does the smartphone usage affect the level of nomophobia?

2. Materials and Methods

2.1. Research Design and Participants’ Selection

Relational survey design was used to conduct this study. The study was conducted within the scope of the comparison type relationship model, which is preferred to examine the differences of two or more groups on a specific variable (Creswell, 1994).

The participants include high schools affiliated with the Eskişehir Provincial Directorate of National Education (Turkey), and the sample group consists of individuals studying in high schools affiliated with Eskişehir Central districts (Odunpazarı, Tepebaşı, Turkey). The data used in the study were collected during the 2024–2025 academic year. A total of 884 participants (male = 425, female = 459) from Science High School and Anatolian High School were sampled for the study using multistage sampling procedures (cluster, simple random, quota and purposive). More details on participants’ characteristics are presented in

Table 1. Distribution of demographic information of the participants.

Variable		N	%
Gender	Male	425	48.1
	Female	459	51.9
Participation in Physical Activity	Yes	371	42.0
	No	513	58.0
High School Type	Science High School	388	43.9
	Anatolian High School	496	56.1
Grade Level	9. class	250	28.3
	10. class	205	23.2
	11. class	209	23.6
	12. class	220	24.9
Smartphone Usage Time	Less than 1 year	22	2.5
	1–2 years	87	9.8
	3–4 years	296	33.5
	5 years and above	479	54.2

.

2.2. Measures

In this study, five sociodemographic characteristics of the participants were evaluated: gender, participation in physical activity, school type, grade level and duration of smartphone use. The Nomophobia Scale developed by Yildirim and Correia (2015) was used to measure the nomophobia levels of the participants. This scale was adapted to the Turkish context by Yildirim et al. (2016), and this Turkish version was used in this study. The scale consists of 20 items on a 7-point Likert-type scale with four sub-dimensions: not being able to access information, losing connectedness, not being able to communicate and giving up convenience.

In the validity study conducted by Yildirim et al. (2016), the combined reliability coefficient (Cronbach α) of the whole scale was reported as 0.92. The reliability coefficients of the four sub-dimensions are 0.90, 0.74, 0.94 and 0.91, respectively. In this study, the overall reliability of the scale was found to be 0.82, and the Cronbach α values of the sub-dimensions ranged between 0.78 and 0.86. These findings show that the scale has a satisfactory level of internal consistency across all dimensions. High scores obtained in the measurement tool indicate that individuals have high levels of nomophobia.

2.3. Ethical Statements

The necessary ethics committee permissions were obtained from the Kütahya Dumlupınar University Social and Human Sciences Research and Publication Ethics Committee (Code N°11/2023; dated on 28 November 2023). In addition, the research was carried out in accordance with the latest Helsinki guidelines for ethical principles in research involving human participants (Association, 2025).

2.4. Data Collection Procedures

To collect the research data, official high schools affiliated with the Provincial Directorate of National Education in the Eskişehir city center were visited, and students were asked to fill out the form. Participants were briefed on the purpose of the study, the confidentiality and anonymity of responses, how to fill out the scales and the liberty to withdraw from the study at any time. A total of 995 participants filled out the form. The incomplete or incorrectly completed forms of 86 participants were excluded from the study, and the responses of the remaining 884 participants were prepared for statistical analysis.

High school students between the ages of 14 and 18 who extensively use smartphones—defined as those who have used a smartphone every day for at least the last six months—were included in this survey. Furthermore, participants who understand the content of the survey must provide informed consent; for minors, parental permission must be requested. Study participants excluded were those without smartphones, those not enrolled in school and those with cognitive problems preventing accurate self-reporting. Individuals participating in ongoing digital detox initiatives and inconsistent or partial survey responses were also excluded.

2.5. Statistical Analysis

The data obtained were transferred to the SPSS 24.0 package program, and the Kolmogorov–Smirnov normality test was applied to the data, and although the results obtained did not show a normal distribution, it was accepted that the data had a normal distribution because the skewness and kurtosis values were between −2 and +2 (Kim, 2013). Accordingly, an independent sample test (t-test) and one-way analysis of variance (One-Way ANOVA) tests were applied to the data. Depending on the homogeneity assumption of the data, Welch values were considered, and Tukey tests were applied as second-level post hoc tests (Agbangba et al., 2024; Takane et al., 2025). Additionally, we used RStudio, Version 2025.05.0 for Windows (R Core Team, 2024) including the “ggplot2” (Wickham, 2016) and “dplyr” (Wickham et al., 2023) packages to generate the figure for the summary of the study results. The findings were evaluated according to the p < 0.05 significance value.

3. Results

3.1. Normality Assumption

Skewness and kurtosis values of the sub-dimensions of the measurement tool were between −2 and +2 (

Table 2. Descriptive measures and univariate normality.

Sub-Dimension	Mean	Sd	Skewness	Kurtosis
Participation in physical activity	1.58	0.494	−0.326	−1.136
High school type	1.56	0.496	−0.247	−0.944
Grade level	2.45	1.14	0.052	−1.420
Smartphone usage time	3.39	0.765	0.431	0.164
Not being able to access information	15.7	5.84	−0.074	−0.760
Not being able to communicate	25.6	6.40	−0.336	−0.733
Losing connectedness	18.6	6.92	0.146	−0.639
Giving up convenience	13.0	6.88	0.821	0.095
Nomophobia total	72.9	22.9	0.077	−0.333

).

3.2. Variation in Nomophobia Levels by Gender

Nomophobia levels of the study participants were analyzed across gender. Statistically significant differences were found across all the sub-dimensions of nomophobia such as the not being able to access information sub-dimension (t(882) = −4.494; p < 0.05), not being able to communicate sub-dimension (t(882) = −8.571; p < 0.05), losing connectedness sub-dimension (t(882) = −8.232; p < 0.05) and giving up convenience sub-dimension (t(882) = −3.643; p < 0.05).

Statistically significant differences were found in nomophobia total scores (t(882) = −8.286; p < 0.05) (see

Table 3. Nomophobia levels according to gender.

Sub-Dimension	Gender	N	X ± SS	t	p
Not being able to access information	Male	425	14.8 ± 5.97	−4.494	0.00 *
	Female	459	16.6 ± 5.59
Not being able to communicate	Male	425	22.9 ± 9.19	−8.571	0.00 *
	Female	459	28.1 ± 8.90
Losing connectedness	Male	425	16.7 ± 6.52	−8.232	0.00 *
	Female	459	20.4 ± 6.80
Giving up convenience	Male	425	12.1 ± 6.82	−3.643	0.00 *
	Female	459	13.8 ± 6.85
Nomophobia total	Male	425	66.5 ± 22.2	−8.286	0.00 *
	Female	459	79.0 ± 21.9

* p < 0.05.

and Appendix A for details). Analysis of the mean scores indicated that female participants had higher nomophobia levels than the male participants.

3.3. Nomophobia Level Variations by Physical Activity Participation

This section analyzed nomophobia differences because of participation in physical activities. Statistically significant differences were found in all the sub-dimensions of nomophobia such as inability to access information (t(882) = −0.212; p < 0.05), giving up convenience (t(882) = −1.038; p < 0.05), inability to communicate (t(882) = −2.246; p < 0.05) and losing connectedness (t(882) = −2.121; p < 0.05). Statistically significant differences were found in nomophobia total scores (t(882) = −1.925; p < 0.05) (see

Table 4. Nomophobia levels by physical activity participation.

Sub-Dimension	Participation in Physical Activity	N	X ± SS	t	p
Not being able to access information	Yes	371	15.7 ± 5.83	−0.212	0.032 *
	No	513	16.8 ± 5.84
Not being able to communicate	Yes	371	24.7 ± 9.44	−2.246	0.025 *
	No	513	27.2 ± 9.34
Losing connectedness	Yes	371	18.0 ± 6.75	−2.121	0.034 *
	No	513	20.0 ± 7.01
Giving up convenience	Yes	371	12.7 ± 6.88	−1.038	0.017 *
	No	513	14.2 ± 6.89
Nomophobia total	Yes	371	71.2 ± 23.3	−1.925	0.045 *
	No	513	78.2 ± 22.6

* p < 0.05.

and Appendix A for details).

According to Table 4, nomophobia levels of individuals who did not participate in physical activity were higher than those of individuals who participated in physical activity in all sub-dimensions and the total score.

3.4. Nomophobia Levels According to High School Type

Nomophobia levels of the participants were analyzed according to the high school type variable. Statistically significant differences were not found in all sub-dimensions of nomophobia (p > 0.05) (see

Table 5. t-test results according to the high school variable.

Sub-Dimension	High School Type	N	X ± SS	t	p
Not being able to access information	Science High School	388	15.7 ± 5.72	−0.166	0.408
	Anatolian High School	496	15.8 ± 5.93
Not being able to communicate	Science High School	388	25.3 ± 9.64	−0.647	0.312
	Anatolian High School	496	25.7 ± 9.21
Losing connectedness	Science High School	388	18.67 ± 7.11	0.099	0.518
	Anatolian High School	496	18.62 ± 6.77
Giving up convenience	Science High School	388	13.01 ± 6.97	−0.105	0.226
	Anatolian High School	496	13.06 ± 6.83
Nomophobia total	Science High School	388	72.8 ± 24.0	−0.309	0.760
	Anatolian High School	496	73.7 ± 22.1

and Appendix A for more details).

3.5. Nomophobia Levels According to High School Students’ Grade Level

This section analyzed nomophobia levels of study participants’ grade level. Statistically significant differences were found across all the sub-dimensions of nomophobia such as inability to access information (F_(3;883) = 3.077; p < 0.05), inability to communicate (F_(3;883) = 3.016; p < 0. 05), losing connectedness (F_(3;883) = 3.201; p < 0.05) and giving up convenience (F_(3;883) = 3.428; p < 0.05). Statistically significant differences were found in nomophobia total scores (F_(3;883) = 3.748; p < 0.05). When the multiple comparison (Tukey) post hoc test was examined, the following grade level differences were identified: (a) level 9 and level 10 on inability to access information; (b) level 11 and level 12 on inability to communicate and losing connectedness; and (c) level 12 and levels 9 and 11 on giving up convenience. When the total scores were analyzed, significant differences were observed in nomophobia levels according to the grade levels of the students. Significant differences were found between 9th grade students and 10th and 12th grade students; between 10th grade students and 11th grade students; and between 11th grade students and 12th grade students. This shows that students’ nomophobia levels change as the grade level increases (see

Table 6. Nomophobia levels according to the students’ grade level.

Sub-Dimension	Grade Level	N	X ± SS	F	p	Tukey
Not being able to access information	9. class	250	15.6 ± 5.87	3.077	0.027 *	b–c
	10. class	205	14.8 ± 5.49
	11. class	209	16.5 ± 6.08
	12. class	220	16.0 ± 5.80
Not being able to communicate	9. class	250	25.8 ± 9.60	3.016	0.029 *	c–d
	10. class	205	25.0 ± 9.66
	11. class	209	27.1 ± 8.43
	12. class	220	24.5 ± 9.67
Losing connectedness	9. class	250	18.6 ± 6.71	3.201	0.023 *	c–d
	10. class	205	18.3 ± 7.09
	11. class	209	19.8 ± 6.73
	12. class	220	17.8 ± 7.05
Giving up convenience	9. class	250	13.8 ± 7.07	3.428	0.017 *	a–d c–d
	10. class	205	12.8 ± 6.71
	11. class	209	13.4 ± 6.83
	12. class	220	11.9 ± 6.77
Nomophobia total	9. class	250	74.0 ± 22.8	3.748	0.011 *	a–b a–d b–c c–d
	10. class	205	71.0 ± 23.1
	11. class	209	76.9 ± 22.1
	12. class	220	70.3 ± 23.2

* p < 0.05. (a) 9. class. (b) 10. class. (c) 11. class. (d) 12. class.

and Appendix A).

3.6. Nomophobia Levels by Duration of Smartphone Use

This section looked at the nomophobia levels of the participants based on the duration of smartphone use. While no statistically significant difference was found across the sub-dimensions of inability to access information, inability to communicate and giving up convenience, a statistically significant difference was found in the sub-dimension of losing connectedness (F_(3;883) = 2.794; p < 0.05). There were no statistically significant differences in nomophobia total scores (F_(3;883) = 1.861; p < 0.05) (see

Table 7. Nomophobia levels by duration of smartphone use.

Sub-Dimension	Smartphone Usage Time	N	X ± SS	F	p	Tukey
Not being able to access information	Less than 1 year	22	14.5 ± 6.78	1.532	0.205
	1–2 years	87	15.12 ± 5.78
	3–4 years	296	15.4 ± 5.72
	5 years and above	479	16.13 ± 5.86
Not being able to communicate	Less than 1 year	22	21.3 ± 12.3	2.112	0.097
	1–2 years	87	24.5 ± 9.61
	3–4 years	296	25.9 ± 9.29
	5 years and above	479	25.7 ± 9.25
Losing connectedness	Less than 1 year	22	15.0 ± 8.79	2.794	0.039 *	a–d
	1–2 years	87	17.7 ± 6.63
	3–4 years	296	18.82 ± 6.71
	5 years and above	479	18.87 ± 6.96
Giving up Convenience	Less than 1 year	22	12.1 ± 7.58	0.209	0.890
	1–2 years	87	13.5 ± 7.14
	3–4 years	296	13.2 ± 6.94
	5 years and above	479	13.0 ± 6.79
Nomophobia Total	Less than 1 year	22	62.9 ± 31.7	1.861	0.135
	1–2 years	87	70.8 ± 23.3
	3–4 years	296	73.3 ± 22.5
	5 years and above	479	73.7 ± 22.9

* p < 0.05. Less than 1 year (a), 1–2 years (b), 3–4 years (c), 5 years and above (d).

and Appendix A).

A multiple comparison test (Tukey post hoc) revealed that a difference between the participants with less than 1 year of smartphone use and those with 5 years or more in the sub-dimension of losing connectedness existed. Hence, the nomophobia levels of study participants who have used mobile phones for a long time are higher than those who have used phones for a short duration.

4. Discussion

The study examined the nomophobia levels of high school students across selected socio-demographic indicators such as gender, participation in physical activity, class level and duration of smartphone use. In this study, statistically significant differences were found in the sub-dimensions of the nomophobia levels across the gender variable. In line with previous studies (e.g., Göktaş & Demirer, 2023), current findings showed that the nomophobia levels of female participants are higher than male participants. In the study conducted by Yılmaz et al. (2018) on nomophobia, the phenomenon became widespread among students in the sub-dimensions of “Losing Communication” and “Inability to Access Information” (Yılmaz et al., 2018). It was also found that the nomophobia levels of women differed significantly from men. It was observed that the nomophobia levels of women in the dimensions of “Losing Communication and Device Deprivation” were significantly higher than men. Society’s emphasis on women’s socialization and communication roles may have triggered women’s dependence on mobile devices.

Participation in physical activity revealed statistically significant differences in all the sub-dimensions of the nomophobia scale. Further comparisons revealed that individuals who participated in physical activity were lower in the sub-dimensions where significant differences were observed than those of individuals who did not participate in physical activity. Atıcı and Erbaş (2021) examined the nomophobia levels of students studying at the faculty of sports sciences during the COVID-19 pandemic process and found that the inability of students to do sports due to restrictions on going out during the pandemic period, social isolation and the closure of sports facilities pushed them to a sedentary life at home (Atıcı & Erbaş, 2021). This situation inevitably directed them to digital tools at home which affected their nomophobia levels. An experimental study by (AlMarzooqi et al., 2022) to determine the effects of sports activities on nomophobia revealed statistically significant differences between pre- and post-test nomophobia intervention in the experimental group. Liu et al. (2022) also reported significant relationships between nomophobia and physical activity (Liu et al., 2022). Physical activity can reduce digital anxiety by supporting individuals’ mental health. Elements such as time management and face-to-face social interactions can balance the dependence on the online world. Given Turkey’s rapidly digitalizing society, these results suggest the need for a strategic approach to reduce digital addiction, especially among the young population, by promoting physical activity. Furthermore, by decreasing in-person social interactions and encouraging digital engagement as the main socialization method, physical inactivity could make nomophobia more severe. Thus, the higher levels of nomophobia among subgroups may stem from adolescent’s developmental need for autonomy and peer approval, which smartphones conveniently fulfill.

There was no statistically significant difference in the sub-dimensions of the nomophobia according to the type of high school study participants attended. This finding corroborates the finding of a similar study by Terzi et al. (2024) on nomophobia perceptions of high school students which did not differ according to the type of school they attended (Terzi et al., 2024). This suggests that the type of high school may not be a determining variable on nomophobia levels and that nomophobia may develop more due to individual or environmental factors.

Regarding the grade level, a statistically significant difference was found among all the nomophobia sub-dimensions. Further comparisons revealed differences among certain grade levels on specific nomophobia sub-dimensions, a finding that is in line with previous studies (Çelebi et al., 2020; Çilek et al., 2024). Both studies found that the nomophobia levels of students differ according to the grade level. Class level differences also characterized nomophobia sub-dimensions of inability to access information and sacrifice of comfort (Aygün et al., 2024). The finding of statistically significant differences in the sub-dimensions of the nomophobia scale according to the grade level of the participants suggests that individuals’ relationships with digital technologies may be related to developmental processes and age. For example, the difference between 9th and 10th grade students in the sub-dimension of inability to access information may be due to the diverse needs or expectations of students in this age group to access information. Similarly, the differences between 11th and 12th graders in the sub-dimensions of not being able to communicate and losing online connection may be influenced by the increased social responsibilities and communication needs of higher-grade students. The fact that 12th graders did not differ in the sacrifice of convenience dimension suggests that this group’s attitudes towards technology may be more established and stable. These findings suggest that grade level is a key factor that can affect students’ behaviors and perceptions towards technology use. Moreover, different academic expectations and changing social dynamics may lead to differences in nomophobia across grades. For example, older students may use their phones for stress management or to interact with friends in increasingly complicated social networks.

Depending on the duration of the participants’ smartphone usage, no significant difference was found in the sub-dimensions of not being able to access information, not being able to communicate and giving up convenience. However, a statistically significant difference was found in the sub-dimension of losing connectedness. The multiple comparison (Tukey) test showed a significant difference in the sub-dimension of losing connectedness between participants with less than 1 year of smartphone usage and participants with 5 years or more. This finding supports an earlier study by (Arslan et al., 2019). Arslan et al. found significant differences among teachers’ mobile phone deprivation. The nomophobia levels of the participants who used the devices for 1–3 h, 4–7 h and 7 h or more were higher than those of the participants who used the devices for less than 1 h. In the study conducted by Sırakaya (2018), it was concluded that the increase in years of smartphone use, years of mobile internet use and daily mobile internet usage time significantly differentiated nomophobia levels (Sırakaya, 2018). Contrary to the above findings, Adnan and Gezgin (2016) did not find any significant difference between the nomophobia levels of students on mobile phone usage time (Adnan & Gezgin, 2016). Though the research included Turkish students, variations in findings could stem from variations in sample size, geographical or institutional settings, or the method of measuring cell phone use and nomophobia.

4.1. Strengths and Limitations

Given the considerable sample size, this study offers insights into nomophobia levels among Turkish students, hence supporting the validity of the statistical analysis and allowing significant sub-group comparisons. In addition, including several sub-dimensions of nomophobia helps to clarify this condition as well. Conversely, the research has certain limitations. First, it was based on a single sample from a specific community which restricts the generalizability of the findings to broader or diverse populations. Second, the cross-sectional design of the study could restrict any causal conclusion, either directly or indirectly.

4.2. Practical Implications

Sports or club activities organized in schools can be an effective tool in reducing the effect of physical activity on nomophobia levels. School authorities of Science High and Anatolian High schools should from time to time organize physical education, cultural and other co-curricular activities to engage the students during and after school hours. Considering that female students exhibit higher levels of nomophobia, training programs on digital awareness and healthy technology use can be organized for this cohort. During these training programs, the benefits and harms of technology can be addressed in a balanced manner. School authorities can also educate students on the causes and effects of nomophobia and institute remedial measures to curb that anxiety. Observing differences by grade level requires the development of strategies specific to age groups. For example, workshops on stress management and technology use can be organized for upper-grade students. This approach will equip them with the requisite knowledge on how to manage anxious moments of phone unavailability or usage. Considering the effect of duration of smartphone use on the sub-dimension of losing online connection, individual or group counseling sessions can be organized by telecommunication agencies and school authorities to assess long-term users’ relationship with technology. The lack of significant differences according to high school type suggests further studies to examine the effect of cultural and environmental factors on nomophobia in more detail.

5. Conclusions

The analyses of nomophobia levels revealed that digital addiction status of individuals showed significant differences according to various demographic and behavioral characteristics. The gender findings show that female individuals exhibit significantly higher addiction tendency in all sub-dimensions and total nomophobia scores compared to males. This situation emphasizes that addiction to digital technologies differs according to gender and the importance of developing policies and programs to ensure digital balance, especially for female users.

For physical activity participation, movement-based lifestyles may have a reducing effect on nomophobia levels. It was observed that individuals who did not participate in physical activity were more dependent on digital connectivity, which revealed that physical activities should be supported in improving technology use habits. In contrast, there was no significant effect of school type on nomophobia levels, suggesting that digital addiction is more closely related to individual and environmental factors.

Evaluations by grade level revealed that nomophobia levels were higher especially among 11th grade students, revealing the effect of age and developmental periods on digital addiction. Accordingly, awareness and intervention programs should be differentiated according to age groups and educational levels. Regarding the duration of smartphone use, a significant difference was found only in the “losing connectedness” sub-dimension; the fact that long-term users had higher nomophobia levels in this dimension showed that the duration of use should be considered when combating technology addiction. All these findings show that nomophobia is a multifaceted phenomenon and that combating strategies should be shaped according to the individual’s lifestyle, developmental period and behavioral characteristics.