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. 2026 Mar 10;16(3):e71212. doi: 10.1002/brb3.71212

Sleep Quality and Healthy Lifestyle Beliefs in Adolescents: The Mediating Role of Screen Exposure

Tuğba Solmaz 1,✉, Mukaddes Demir Acar 2, Osman Demir 3
PMCID: PMC12975654  PMID: 41807978

ABSTRACT

Objective

Increased screen exposure among adolescents leads to short‐ or long‐term health problems. This study aimed to examine the mediating role of screen exposure in the relationship between sleep quality and healthy lifestyle among adolescents.

Methods

This cross‐sectional and correlational study was conducted between February and May 2025 in a province in the Black Sea region of Turkey with 700 adolescents attending two high schools affiliated with the Provincial Directorate of National Education. Data were collected using the Descriptive Characteristics Form, the Richard–Campbell Sleep Questionnaire, the Adolescent Healthy Lifestyle Belief Scale, and the Screen Exposure of Adolescents (ESEA) Scale. Descriptive, Pearson correlation, regression, and mediation analyses were performed on the data.

Results

Participants' screen exposure levels and healthy lifestyle beliefs were found to be moderate, while their sleep quality was good. Bootstrapping results revealed that screen exposure in adolescents led to a decrease in sleep quality (β = −0.091; p < 0.05). Increased screen exposure worsened healthy lifestyle beliefs (β = −0.327; p < 0.05). Sleep quality did not significantly affect healthy lifestyle beliefs (β = 0.061; p = 0.076). The study revealed that screen exposure played a mediating role in the relationship between sleep quality and healthy lifestyle (β = 0.030; 95% CI [0.008: 0.053]).

Conclusion

It has been concluded that increased screen exposure affects sleep quality and beliefs about healthy lifestyles in adolescents. To improve sleep quality and healthy lifestyle beliefs among adolescents, it is necessary to reduce their screen exposure levels. Planning and implementing nursing interventions for this purpose is extremely important in terms of protecting and improving adolescent health.

Keywords: adolescent, health behaviors, screen exposure, sleep quality

Screen exposure is becoming an increasingly significant problem among adolescents. Adolescents should devote more time to activities that support a healthy lifestyle. It has been demonstrated that screen exposure in this population significantly affects sleep quality and healthy lifestyle behaviors.

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1. Introduction

The human brain is excessively stimulated and driven toward impulsive consumption, from television screens to massive billboards. Digital devices are widely used both on social media and for educational purposes, and adolescents constitute the majority of viewers in the virtual world. It has been reported that the average screen time spent in the digital world has increased in this population group (Majeed 2023; Zeyrek et al. 2024).

The time spent using a television, computer, tablet, or smartphone is defined as “screen exposure” (Schmidt et al. 2020). With the increasing prevalence of easily accessible mobile devices, numerous short‐ and long‐term health problems are emerging as a result of increased screen exposure among adolescents (Lavados‐Romo et al. 2023). Among these issues are unhealthy eating behaviors (Encarnação et al. 2023), lower quality of life (Lavados‐Romo et al. 2023), postural disorders (Mcallister et al. 2021), behavioral disorders (Encarnação et al. 2023), depressive symptoms (Glover et al. 2022), anxiety (Nguyen et al. 2022), hyperactivity (Vuriyanti et al. 2023), weaker self‐esteem (Glover et al. 2022), and poor sleep outcomes (Stiglic and Viner 2019).

Technologically advanced societies have seen poor sleep quality emerge as a significant public health issue, with increasing technology use contributing to the rise in sleep difficulties (Cheung and Wong 2011; Bilgrami et al. 2017; Maurya et al. 2022). Spending three or more hours per day in front of a screen has been associated with an increased risk of frequent sleep problems (Hysing et al. 2015). Problems in the sleep cycle have been reported to affect melatonin levels and increase the likelihood of mental health issues such as depression, anxiety, stress, and social dysfunction (Yogesh et al. 2014; Zeyrek et al. 2024). Sleep quality is of great importance in human life, both physiologically and socially, and significantly affects an individual's healthy lifestyle (Plaford 2009).

Adolescence is an important period during which the foundations for healthy lifestyle choices and behaviors are laid. Adolescents make independent decisions about healthy lifestyle behaviors, including physical activity and nutrition (Chen et al. 2014; Özdemir et al. 2020). Adolescents who turn health‐related behaviors into habits can maintain a healthier status, gain knowledge about health‐related issues, and improve their health status to a higher level (Fleary et al. 2018).

Investigating the relationship between sleep quality and healthy lifestyle in adolescents in relation to screen exposure is extremely important. Current studies have primarily addressed internet, technology, and social media addiction in adolescents (Shimoga et al. 2019; Infante and Mardikaningsih 2022) separately from healthy lifestyle and healthy living beliefs (Fleary et al. 2018; Akdeniz Kudubeş and Bektas 2020; Özdemir and Bülbül 2023), and have focused on how excessive use of online communication tools such as the internet addiction and smartphones affects sleep quality (Kurugodiyavar et al. 2018; Yücel and Ünsalver 2019; Coşkun and Kılıç 2022). However, the mediating role of screen exposure in the relationship between sleep quality and healthy lifestyle beliefs in this population has not been sufficiently investigated. Therefore, this study aims to comprehensively evaluate the relationship between screen exposure and sleep quality and healthy lifestyle beliefs among adolescents. By examining these relationships, the study will help identify new strategies to reduce screen exposure among adolescents and promote positive health behaviors.

1.1. Research Hypotheses

  • H11 :

    There is a relationship between sleep quality and screen exposure in adolescents.

  • H12 :

    There is a relationship between screen exposure and healthy lifestyle beliefs in adolescents.

  • H13 :

    There is a relationship between sleep quality and beliefs about healthy lifestyles in adolescents.

  • H14 :

    Screen exposure mediates the relationship between sleep quality and healthy lifestyle beliefs in adolescents.

2. Methods

2.1. Study Design and Participants

A cross‐sectional and correlational design was adopted. The study consisted of adolescents (aged 12–19) attending two high schools in a city center in the Black Sea region (n = 700). Schools were selected based on ease of access, choosing schools with similar socioeconomic levels. The sample size was calculated based on a previous study (Korkmaz and Tek Ayaz 2024) with a population size of 11,800, using a single‐sample design, 80% power, a 5% margin of error, and an effect size of 0.135, resulting in a minimum of 417. Considering that losses may occur during data collection, it was decided to include approximately 500 people in the study, which is 20% more than the sample size calculated. The study was completed with 700 adolescents. PASS version 15.0.5 was used for the sample size calculation (NCSS, LLC 2017). The inclusion criteria were: (1) willingness to participate in the study and (2) parental consent. The exclusion criterion was having a physical, cognitive, or psychological disability.

2.2. Data Collection Tools

The data were collected using the Descriptive Characteristics Form, the Screen Exposure of Adolescents (ESEA) Scale, the Richard—Campbell Sleep Questionnaire, and the Adolescent Healthy Lifestyle Belief Scale.

2.3. Descriptive Characteristics Form

The form was developed by researchers based on the literature and contained 16 questions covering students' descriptive characteristics such as age, gender, class, weight, height, family structure, income level, status of social security, parent's education status, parent's working status, sleep disorder status, etc. (Kurudirek et al. 2019; Sezer Efe et al. 2021; Coşkun and Kılıç 2022; Durak and Muslu 2023; Li et al. 2023; Gökçay et al. 2024; Korkmaz and Tek Ayaz 2024).

2.4. Screen Exposure of Adolescents (ESEA) Scale

Each sub‐dimension of the scale developed by Korkmaz and Tek Ayaz (2024) is evaluated independently. The total score evaluation of the scale indicates that an increase in the total score and the scores of the sub‐dimensions “willingness/desire for screen exposure, socialization, family control, procrastination tendency, and effects of prolonged screen exposure” indicates that the adolescent has a high level of screen exposure. In the family control sub‐dimension, the opposite is true. An increase in the score indicates that the adolescent's screen exposure is low. Scores range from 7 to 35 for the screen willingness/desire sub‐dimension, 3 to 15 for the socialization sub‐dimension, 3 to 15 for the family control sub‐dimension, 5 to 25 for the procrastination tendency sub‐dimension, and 5 to 25 for the effects of prolonged screen exposure sub‐dimension. The total scale score ranges from 23 to 115. Items 11, 12, and 13 on the scale are reverse‐scored. The Cronbach's alpha value of the scale is 0.79 (Korkmaz and Tek Ayaz 2024). In this study, the Cronbach's alpha value was found to be 0.78.

2.5. Richard—Campbell Sleep Questionnaire

The scale developed by Richards (1987) was validated and reliability tested in Türkiye (2015) by Karaman Özlü and Özer. The scale consists of 6 items that assess the depth of nighttime sleep, the time it takes to fall asleep, the frequency of waking up, the time spent awake after waking up, the quality of sleep, and the noise level in the environment. Each item is assessed on a scale from 0 to 100 using the visual analog scale technique. A score between “0 and 25” on the scale indicates very poor sleep, while a score between “76 and 100” indicates very good sleep. As the scale score increases, patients' sleep quality also improves. The Cronbach alpha value of the scale is 0.82 (Richards 1987; Karaman Özlü and Özer 2015). In this study, the Cronbach alpha value was found to be 0.77.

2.6. Adolescent Healthy Lifestyle Belief Scale

The scale was developed by Kelly et al. (2011) to assess beliefs related to a healthy lifestyle, and its Turkish adaptation study was conducted by Akdeniz Kudubeş and Bektas (2020). The scale emphasizes beliefs related to various aspects of maintaining a healthy lifestyle. The scale consists of 16 items and three sub‐dimension (health beliefs, physical activity, and nutrition). Items 4, 5, 6, 11, 12, 13, and 16 constitute the health beliefs sub‐dimension, items 2, 7, 9, 14, and 15 constitute the physical activity sub‐dimension, and items 1, 3, 8, and 10 constitute the nutrition sub‐dimension. The scale, prepared according to a five‐point Likert system, is answered on a scale of “1 = Strongly Disagree” to “5 = Strongly Agree.” A minimum of 16 and a maximum of 80 points can be obtained on the entire scale. A higher score on the scale indicates an increase in adolescents' belief in healthy living. The Cronbach's alpha value of the scale is 0.90 (Kelly et al. 2011; Akdeniz Kudubeş and Bektas 2020). In this study, Cronbach's alpha value was found to be 0.91.

2.7. Data Collection

The data were collected by researchers through face‐to‐face interviews between February and May 2025. Two separate interviews were conducted with students in the school environment. In the first interview, the purpose of the study was explained to the students, and then the parental consent form and voluntary participation form were distributed. Students were given two days to submit the forms. In the second interview, the forms were distributed to students who gave their consent, and the students filled them out independently under the researcher's supervision. The researchers also informed the students that there were no wrong answers on the forms and that they should mark all items on the scale completely. It took approximately 10–15 min to complete the questionnaires.

2.8. Data Analysis

Descriptive statistics such as frequency, percentage, mean, and standard deviation were used in the data evaluation of the study. Skewness and kurtosis values between +2 and ‐2 were considered as criteria for normality in the data analysis. The internal consistency coefficient was calculated using the Cronbach's alpha test. Pearson's correlation coefficient was used to determine the direction and strength of the linear relationship between quantitative variables. To determine whether screen exposure played a mediating role in the relationship between sleep quality and healthy lifestyle beliefs, regression‐based mediation analysis was performed using the bootstrap test. In all analyses, the significance level was set at p < 0.05 (IBM Corp. 2013).

2.9. Ethical Considerations

Ethics committee approval was received from the Social and Humanities Research Ethics Committee of Tokat Gaziosmanpaşa University (Decision no: 01/01‐58, Date: January 14, 2025), and institutional permission from the Tokat Provincial Directorate of National Education was obtained. Participants and their families were informed about the purpose of the study, and their written consent was obtained. The research was conducted according to the Declaration of Helsinki. Personal information was removed from the data to ensure anonymity, and the data obtained was protected by encryption on the researcher's computer.

3. Results

The average age of adolescents participating in the study was 15.81 ± 1.03 years, the average sleep duration was 7.39 ± 1.63 h, the average screen time was 4.29 ± 3.1 h (weekdays) and 6.02 ± 3.29 h (weekends), the average exercise duration was 1.44 ± 1.51 h (weekdays) and 1.65 ± 1.62 h (weekends), and the average body mass index value was 21.35 ± 3.4. It was determined that 60.7% of the participants were female, 35.1% were ninth grade students, 65.9% were of normal weight, and 73.7% experienced sleep disorders. 82.9% of the students came from nuclear families, 48.3% had sufficient income to cover their expenses, and 72.6% had health insurance. Of the participants' mothers, 39.9% had a high school education, and 38.3% of their fathers had a high school education. It was determined that 68.0% of the mothers did not work, and 92.0% of the fathers worked (Table 1).

TABLE 1.

Descriptive characteristics of adolescents (N = 700).

Descriptive characteristics Number (n) Percentage (%)
Gender Female 425 60.7
Male 275 39.3
Grade 9th grade 246 35.1
10th grade 188 26.9
11th grade 209 29.9
12th grade 57 8.1
BMI < 18.5 139 19.9
18.5–24.9 461 65.9
≥ 25 100 14.3
Family structure Nuclear family 580 82.9
Extended family 86 12.3
Divorced family 34 4.9
Income status Income < expense 50 7.1
Income = expense 338 48.3
Income > expense 312 44.6
Status of social security Yes 508 72.6
No 192 27.4
Mother education status Illiterate 6 0.9
Literate 17 2.4
Primary education 240 34.3
High school 279 39.9
University and above 158 22.6
Father education status Illiterate 6 0.9
Literate 11 1.6
Primary education 126 18.0
High school 268 38.3
University and above 289 41.3
Mother working status Working 224 32.0
Not working 476 68.0
Father working status Working 644 92.0
Not working 56 8.0
Sleep disorder status Yes 183 26.1
No 184 26.3
Sometimes 333 47.6
Descriptive characteristics Mean SD
Age (years) 15.81 1.03
BMI (kg/m2) 21.35 3.4
Sleep time (h) 7.39 1.63
Mean screen time, weekdays (h) 4.29 3.1
Mean screen time, weekends (h) 6.02 3.29
Daily exercise time, weekdays (h) 1.44 1.51
Daily exercise time, weekends (h) 1.65 1.62
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Abbreviations: BMI = body mass index, h = hours, SD = standard deviation.

Table 2 presents the descriptive statistics obtained from the evaluation of the scales used in the study. The mean scores of participants on the sleep quality, screen exposure, and healthy lifestyle belief scales were found to be 62.05 ± 22.52, 62.42 ± 12.32, and 59.18 ± 12.57, respectively (Table 2).

TABLE 2.

Distribution of Richard—Campbell Sleep Questionnaire, Screen Exposure Scale, and Adolescent Healthy Lifestyle Belief Scale scores.

Scales Min. Max. Mean SD
Richard – Campbell Sleep Questionnaire 0 100 62.05 22.52
Screen Exposure Scale 31 103 62.42 12.32
Adolescent Healthy Lifestyle Belief Scale 16 80 59.18 12.57
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Abbreviations: Max: maximum; Min: minimum; SD = standard deviation

A Pearson correlation analysis was conducted to determine the relationships between screen exposure, sleep quality, and belief in a healthy lifestyle among adolescents, and the findings are presented in Table 3. A high level of negative (r = −0.091) and significant (p < 0.05) relationship was found between sleep quality and screen exposure among adolescents. The relationship between sleep quality and healthy lifestyle was found to be highly positive (r = 0.091) and significant (p < 0.05). The relationship between screen exposure and healthy lifestyle was found to be weakly negative (r = −0.032) and significant (p < 0.001) (Table 3).

TABLE 3.

Correlation values of the study variables.

Scales Sleep Quality Screen Exposure Healthy Lifestyle Belief
Sleep quality r 1 −0.091 0.091
p 0.016 0.017
n 700 700 700
Screen exposure r −0.091 1 −0.332
p 0.000 <0.001
n 700 700 700
Healthy lifestyle belief r 0.091 −0.332 1
p 0.017 <0.001
n 700 700 700
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Note: *Bold indicates important values, p < 0.05, r = Pearson correlation.

To determine whether screen exposure plays a mediating role in the relationship between sleep quality and belief in a healthy lifestyle, a bootstrapping analysis was performed, and the findings are presented in Table 4. The results showed that screen exposure was negatively related to sleep quality (β = −0.091; p < 0.05). An increase in screen exposure led to a decrease in healthy lifestyle (β = −0.327; p < 0.05). Sleep quality did not significantly affect healthy lifestyle (β = 0.061; p = 0.076). Analysis of the total effect excluding screen exposure, the mediating variable in the model, showed that the effect was statistically significant and positive (β = 0.091; p < 0.05). Screen exposure mediates the relationship between sleep quality and healthy lifestyle (β = 0.030; 95% CI [0.008: 0.053]) (Table 4; Figure 1).

TABLE 4.

Path coefficients for direct, indirect and total effects of the model.

Path Coefficient β p %95 confidence
Interval lower limit Upper limit
Sleep quality ‐ screen exposure (direct effect a) −0.091 0.015 −0.170 −0.025
Screen exposure ‐ healthy lifestyle belief (direct effect‐b) −0.327 0.009 −0.398 −0.267
Sleep quality ‐ healthy lifestyle belief (direct effect‐c’) 0.061 0.076 −0.005 0.118
Sleep quality ‐ healthy lifestyle belief (indirect effect a.b) 0.030 0.020 0.008 0.053
Sleep quality ‐ healthy lifestyle belief (total effect‐ c) 0.091 0.022 0.025 0.153
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Note: *Bold indicates important values, p <  0.05, β = unstandardized regression coefficient.

FIGURE 1.

FIGURE 1

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Model for the mediating role of screen exposure.

4. Discussion

Before starting the discussion, we would like to briefly summarize the main findings of the study. Sleep quality was associated with beliefs about healthy lifestyles. In line with our study hypotheses, we found that increased screen exposure in adolescents leads to a decline in sleep quality and worsens beliefs about healthy lifestyles. Furthermore, we concluded that screen exposure plays a mediating role in the relationship between sleep quality and beliefs about healthy lifestyles.

Adolescence is a special period characterized by a certain level of self‐definition and self‐uncertainty, along with numerous changes in cognition, emotions, roles, and behavior (Kuang et al. 2023a). Under varying psychological conditions, adolescents may explore and develop different lifestyles, and the likelihood of deviating from a healthy lifestyle may be higher during this period. It also leads to problems such as low self‐control, cell phone or screen addiction, weaker health beliefs, and lower levels of physical activity (Kuang et al. 2023b). A study conducted in China reports that students' health beliefs improve their sleep quality and that physical activity also increases sleep quality (Gao et al. 2023). Current studies reveal that sleep quality is closely related to physical activity, mindfulness, health literacy, and belief in a healthy lifestyle (Ji et al. 2022, Mirolli et al. 2021, Ono et al. 2021). Adequate sleep duration seems to be highly influenced by factors related to individual lifestyles, family and school eating behaviors, and diet quality (Godos et al. 2025). Our study suggests that health‐protective and health‐promoting activities aimed at increasing healthy lifestyles among adolescents are very important and are also closely related to sleep quality.

Our study found that adolescents had a moderate average screen exposure score; they were exposed to screens for 4.29 ± 3.1 h on weekdays and 6.02 ± 3.29 h on weekends. According to data reported by parents in the 2016 National Children's Health Survey, every hour spent in front of a digital screen was associated with a 3–8 min decrease in sleep duration on weeknights and more irregular bedtimes. This indicates that 5 h of screen time per day can reduce sleep duration by 40 min or more, while 10 h of screen time per day can result in 80 min less sleep (Przybylski 2019). In a study conducted by Shochat et al. (2010), difficulty falling asleep is a common problem among adolescents, and exposure to electronic screens may have stimulating effects (Shochat et al. 2010). With the proliferation of the internet and smartphones, mobile phone addiction has become a significant factor triggering sleep disorders (Cui et al. 2021).

A study has reported that excessive screen time and its effects, while varying depending on the type of screen activity, have been identified as a significant risk factor for poor sleep, and that excessive social media use is associated with sleep deprivation (χ2 = 8.1726; p < 0.001) (Zhong et al. 2025). Another study reported that internet‐addicted students had significantly shorter sleep durations and delayed bedtimes compared to those with less screen time (Kawabe et al. 2019). A study conducted with adolescents in Sweden found that nighttime messaging is a significant factor contributing to delayed bedtimes, sleep deprivation, daytime fatigue, and disrupted sleep patterns (Garmy and Ward 2018). A study by Chang et al. (2015) shows that using light‐emitting electronic devices in the hours before bedtime can have a significant effect on sleep, wakefulness, and the circadian clock (Chang et al. 2015). Another study concluded that increased screen exposure among adolescents is associated with sleep problems, mental health issues (Santos et al. 2023), and physical problems such as myopia (Zong et al. 2024; De Sá et al. 2023). Similar to the literature, this study also found that the relationship between sleep quality and screen exposure in adolescents was highly negative (r = −0.091) and significant (p < 0.05). Therefore, parents and policymakers should consider taking important strategic steps to improve sleep quality in adolescents.

This study demonstrates that increased screen exposure worsens healthy lifestyle habits (β = −0.327; p < 0.05). One study found that cell phone addiction was associated with a significant reduction in the effect size of health belief on sleep quality, the effect size of health belief on physical activity, and the effect size of physical activity on sleep quality (Gao et al. 2023). These findings raise significant public health concerns regarding adolescents' lifestyle and sleep quality. Parents should take steps to reduce screen exposure in adolescents, and the physical and mental health of today's youth, who are shaping the future of a healthy society, should be protected. In this context, the development of national and international policies is recommended. Future researchers are encouraged to design experimental studies to evaluate the relationships and potential causes between increasing screen exposure, sleep outcomes, and healthy lifestyle factors in adolescents.

4.1. Limitations

The limitations of this study include the fact that it was conducted in two high schools in a province located in Türkiye's Black Sea Region and that it relied on self‐reported data from adolescents.

4.2. Implications to Practice

Our study has revealed that the increasing screen exposure among adolescents negatively impacts sleep quality and beliefs about healthy lifestyles, highlighting the urgent need for preventive public health initiatives. For example, since increased screen time is particularly associated with a decrease in sleep quality and healthy lifestyle behaviors, public health campaigns that collaborate with adolescents and their families in schools to direct adolescents toward sports or artistic activities that protect them from screen exposure may be beneficial. At the same time, it is thought that the existing evidence could guide the integration of healthy lifestyle behaviors into school‐based health education curricula and the development of age‐appropriate screen time guidelines in schools by policymakers.

5. Conclusion

In conclusion, this study emphasizes that increased screen exposure among adolescents negatively impacts sleep quality and healthy lifestyle habits. It also highlights the need for interventions promoting digital hygiene to establish healthier sleep routines and healthy lifestyle behaviors among adolescents. Accordingly, it is considered extremely important to plan interventions aimed at reducing screen exposure among adolescents, increasing social interactions, and developing alternative activities. Accordingly, it is recommended to promote interventions aimed at reducing screen exposure, increasing social interaction, and developing alternative activities among adolescents. Implementing these recommendations may help adolescents adopt healthier lifestyles, regulate their sleep quality, and reduce their screen exposure. Furthermore, experimental studies can be designed in the future to test the effectiveness of interventions aimed at reducing screen exposure among adolescents.

Author Contributions

Tuğba Solmaz: conceptualization, investigation, writing – original draft, methodology, writing – review and editing, project administration. Mukaddes Demir Acar: investigation, writing – original draft, methodology, writing – review and editing, supervision. Osman Demir: data curation, formal analysis, supervision. AI was used to improve the language and edit of the text.

Funding

The authors have nothing to report.

Conflicts of Interest

The authors declare no conflicts of interest.

Ethics Statement

Ethics committee approval was received from the Social and Humanities Research Ethics Committee of Tokat Gaziosmanpaşa University (Decision no: 01/01‐58, Date: January 14, 2025) and institutional permission from the Tokat Provincial Directorate of National Education were obtained. Participants and their families were informed about the purpose of the study, and their written consent was obtained. The research was conducted according to the Declaration of Helsinki.

Acknowledgments

We would like to thank the study participants.

Data Availability Statement

The data are available on reasonable request from the corresponding author. The data are not publicly available due to privacy or ethical restrictions.

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