Nomophobia, Insomnia, and Coping Strategies in Relation to Academic Achievement and Psychological Well-Being Among Medical Students: A Cross-Sectional Study

1. Introduction

A healthy lifestyle encompasses a set of health-related behaviors shaped by both individual choices and environmental opportunities (Cockerham et al., 2020). Previous research has shown that physical activity, reduced sedentary behavior, and limited screen time positively influence mental health, thereby indirectly improving academic performance (Maitiniyazi et al., 2025). Physical exercise significantly contributes to maintaining physical and mental health through enhancing brain function, resulting in improved learning and memory (Yang, 2019; Chang et al., 2012). In the long term, aerobic exercise increases neuroplasticity and cognitive functions (Yang, 2019; Chang et al., 2012; Hötting & Röder, 2013), while acute or anaerobic activity provides short-term benefits, including improved mood, attention, and better cognitive performance (Clemente-Suárez et al., 2023). Students with high physical fitness are less likely to have poor academic performance than those with low physical fitness, while a sedentary lifestyle may adversely affect academic functioning (Redondo-Flórez et al., 2022; Burrows et al., 2017).

The widespread popularity and excessive use of smartphones can lead to problematic addictive behaviors, which disrupt general well-being and have negative effects on mental health (Paterna et al., 2024). One manifestation of problematic smartphone use, common among university students, is nomophobia, a psychological condition characterized by fear of being disconnected from the mobile phone (Bhattacharya et al., 2019). Noted negative impacts of nomophobia on the social, psychological, and health domains include increased stress levels, lower self-esteem, depression symptoms, reduced quality of life, and challenges with day-to-day functioning (Al-Mamun et al., 2025).

Healthy sleep is essential for overall health and quality of life, as well as for normal neurocognitive functioning and emotional regulation (Oliveira et al., 2025). In academic settings, a demanding environment and irregular schedules often lead to impaired sleep and frequent sleep disturbances (Dąbrowska-Galas et al., 2021). High stress levels, late bedtime, and sleep deprivation are associated with a higher prevalence of sleep disorders among medical students (Oliveira et al., 2025; Dąbrowska-Galas et al., 2021). Furthermore, sleep quality, duration, and consistency are correlated with grade point averages (GPAs) among college students (Okano et al., 2019), while sleep deprivation is associated with impaired cognitive functioning (Hartmann & Prichard, 2018).

Medical students experience disproportionately high levels of stress, depression, and psychological distress, driven by heavy workload, constant evaluations, intense competition, and the overwhelming volume of required information (Rotenstein et al., 2016). Prolonged exposure to such stressors may lead to emotional strain, reduced well-being, and burnout, which can negatively affect motivation, daily functioning, and academic performance (Ishak et al., 2013). Reduced well-being among medical students has been linked to emotional exhaustion, decreased academic engagement, and impaired professional development (Rotenstein et al., 2016). Coping strategies, conceptualized as cognitive and behavioral efforts aimed at managing internal or external demands exceeding one’s resources (Folkman & Lazarus, 1984), may be adaptive or associated with higher psychological distress and less favorable outcomes (Eisenberg et al., 2012). Greater reliance on self-controlling coping strategies was associated with higher academic performance, suggesting that deliberate regulation of emotions and impulses in response to academic stress may confer academic benefits by supporting sustained engagement, effective goal pursuit, and adaptive responses to academic demands (Kassaw & Demareva, 2025).

Although each of these factors has been independently associated with academic performance, limited research has examined their combined contribution within a single model among medical students. Thus, this study aimed to examine the associations among coping strategies, well-being, physical activity, sleep, and smartphone use and academic performance among medical students. We hypothesized that nomophobia, insomnia severity, psychological distress, and maladaptive coping strategies would be significant negative predictors of academic achievement among medical students.

2. Materials and Methods

This cross-sectional study was approved by the Ethics Committee of the University of Split School of Medicine (Class: 029-01/24-02/0001; Reg. No.: 2181-198-03-04-24-0032). The study included 216 students from all six years of the University of Split School of Medicine.

Data was collected through an anonymous digital questionnaire created in Google Forms. The inclusion criteria were enrolment as a medical student at the University of Split School of Medicine at the time of the study. No specific exclusion criteria were applied; however, incomplete questionnaires were excluded from the final analysis. The data collection process was completely anonymous. Participants provided informed consent after reading the study information and confirming their participation by selecting the appropriate option at the beginning of the questionnaire. The data collection period lasted from March 1 to June 21, 2024. The survey was initially distributed online, but due to a low response rate, it became necessary to approach students in class and invite them directly to participate in the study.

The first part of the questionnaire collected general information about the participants, including demographic and anthropometric characteristics (age, gender, race, year and duration of study, GPAs, body height and weight, and chronic disease information). Academic performance was assessed using students’ self-reported arithmetic and weighted grade point averages (wGPA).

The second part of the questionnaire focused on physical activity. For this section, the long version of the International Physical Activity Questionnaire (IPAQ) was used (21). IPAQ evaluates physical activity across five domains: work, transportation, household activities, recreation, and time spent sitting. Scoring for IPAQ is based on calculating MET-minutes (metabolic equivalents), using standardized values: walking = 3.3 METs, moderate activity = 4.0 METs, vigorous activity = 8.0 METs. Total MET-minutes were calculated by multiplying the duration of each activity by its corresponding MET value and summing the results. Based on total weekly MET-minutes, participants were categorized into three levels of physical activity: low (less than 600 MET-min/week), moderate (600–2999 MET-min/week), and high (3000 or more MET-min/week).

In the third part, the Nomophobia questionnaire (NMP-Q) was used to gather information on smartphone use habits (22). Participants responded to twenty claims using a Likert scale, where 1 represents „strongly disagree”, and 7 represents „strongly agree”. After completing the questionnaire, the results were summed and ranged from 20 to 140. A total score of 20 or less indicates the participant does not have nomophobia; scores of 21 to 59 indicate mild nomophobia; 60 to 99, moderate nomophobia; and 100 to 140, severe nomophobia.

Participants were also screened for insomnia using the Insomnia Severity Index (ISI), in which respondents rated the nature and symptoms of their sleep problems using a Likert scale (23). The questionnaire is structured into three parts: the first assesses the severity of sleep-related problems, the second evaluates satisfaction with sleep patterns, and the third examines the extent to which insomnia affects daily functioning and how noticeable it is to others. In the first part, responses are scored on a scale from 0 to 3, and in the remaining two parts on a scale from 0 to 4. A higher score indicates more severe insomnia symptoms.

Student well-being was assessed using the Medical Student Well-Being Index (MSWBI), a validated screening instrument comprising 7 dichotomous (yes/no) items assessing burnout, emotional distress, depressive symptoms, fatigue, and reduced functioning (25). Each affirmative response was scored as 1 point, and each negative response as 0 points, yielding a total score ranging from 0 to 7. Higher MSWBI scores indicate poorer well-being and greater distress, whereas lower scores indicate better well-being and lower distress, with the cut-off value of 4.

Coping strategies were assessed using the Brief COPE questionnaire, consisting of 28 items designed to measure effective and ineffective coping responses to stress (24). The questionnaire is structured into three higher-order coping styles: problem-focused coping (items 2, 7, 10, 12, 14, 17, 23, 25), emotion-focused coping (items 5, 9, 13, 15, 18, 20, 21, 22, 24, 26, 27, 28) and avoidant coping (items 1, 3, 4, 6, 8, 11, 16, 19). Responses are rated on a 4-point Likert scale ranging from 1 (“I usually don’t do this at all”) to 4 (“I usually do this a lot”). Scores for each coping style were calculated as the mean value (sum of item scores divided by the number of items within the coping style). Mean scores ranged from 1 to 4, with higher scores indicating more frequent use of the respective coping style and lower scores indicating less frequent use.

Data collected via Google Forms was exported to Microsoft Excel (Microsoft Office 365) for data cleaning and preparation. Statistical analyses were conducted using the MedCalc online statistical platform and Jamovi (version 2.6). Descriptive statistics (means, standard deviations, medians, and frequencies) were used to summarize the data. Differences between the groups were analyzed using the Student’s t-test, associations between continuous variables were assessed using Pearson’s correlation coefficient, and relationships between categorical variables were examined using the chi-square (χ²) test. A hierarchical multiple regression analysis was conducted to examine whether demographic, lifestyle, digital, and psychological variables predict students’ cumulative wGPA. Statistical significance was set at P < 0.05.

3. Results

3.1. Participant Characteristics

A total of 216 medical students from all six academic years participated in the study. The sample included 57 (26.4%) male and 156 (72.2%) female students, while 3 (1.4%) participants reported another gender identity. The mean age of participants was 22.03 ± 2.48 years. Mean arithmetic GPA was 4.16 ± 0.43, while wGPA was 3.85 ± 0.55. The mean duration of study was 4.26 ± 2.15 years (Table 1).

3.2. Psychological and Behavioral Measures

The mean nomophobia total score was 71.35 ± 25.43. A total of 2 (0.9%) participants had no nomophobia (nomophobia total score was <21), 67 (31.0%) had mild nomophobia (total score was 21-59), 119 (55.1%) had moderate nomophobia (total score 60-99), and 28 (13.0%) had severe nomophobia (total score 100-140). The mean ISI score was 7.32 ± 5.18. A total of 122 participants (56.5%) had no insomnia, 74 (34.3%) had subthreshold insomnia, 18 (8.3%) had moderate, and 2 (0.9%) had severe clinical insomnia. The MSWBI score averaged 3.27 ± 1.89, and 110 (50.9%) students scored ≥4, indicating poor well-being. Regarding coping strategies, participants reported greater use of problem-focused coping (1.93 ± 0.56) than emotion-focused coping (1.68 ± 0.47) and avoidance strategies (0.77 ± 0.46). The psychological and behavioral measures are presented in Table 2.

Internal consistency reliability in the present sample was good to excellent: Cronbach’s α was 0.953 for the nomophobia questionnaire, 0.859 for the ISI, 0.714 for the MSWBI, 0.796 for the problem-focused coping, 0.703 for the emotion-focused coping, and 0.733 for the avoidant coping.

3.3. Correlation Analysis

The correlation analysis presented in Table 3 demonstrated that the sitting time was negatively correlated with physical activity (r = -0.250, p < 0.001) and positively correlated with academic achievement GPA (r = 0.167, p = 0.014) and wGPA (r = 0.185, p = 0.003).

Nomophobia was positively correlated with insomnia severity (r = 0.172, p = 0.011) and with MSWBI (r = 0.268, p < 0.001), while insomnia severity was positively correlated with MSWBI (r = 0.387, p < 0.001). Emotion-focused and avoidant coping strategies were significantly positively correlated with nomophobia, insomnia severity, and poorer well-being (all p < 0.05, Table 3). Furthermore, the emotion-focused coping strategy was positively correlated with both the problem-focused coping strategy (r = 0.563, p < 0.001) and the avoidant coping strategy (r = 0.296, p < 0.001).

Finally, academic achievement (wGPA) was negatively correlated with insomnia severity (r = -0.172, p = 0.011) and with avoidant coping strategies (r = -0.167, p = 0.014; Table 3).

3.4. Hierarchical Regression Analysis

In the first step of the hierarchical regression analysis (Table 4), demographic variables (age, sex, body mass index, and year of study) were entered into the model. This model explained 3.5% of the variance in GPA (R² = 0.035). None of the predictors reached statistical significance. In the second step, lifestyle variables (average daily sitting time and total physical activity) were added to the model. The inclusion of these variables increased the explained variance to 6.0% (R² = 0.060). However, neither physical activity nor sitting time was a significant predictor at this stage. In the third step, digital and sleep-related variables (insomnia and nomophobia) were included. This resulted in a small increase in explained variance to 7.4% (R² = 0.074), but neither variable significantly predicted GPA. Finally, psychological variables (MSWBI and coping strategies) were added in the fourth step. The final model explained 9.0% of the variance in GPA (R² = 0.090). None of the predictors were statistically significant in the final model, although average daily sitting time approached statistical significance (p = 0.050, Table 5).

4. Discussion

This study reveals a high prevalence of digital dependence and psychological vulnerability among medical students, with the majority demonstrating clinically relevant levels of nomophobia that were associated with insomnia severity and impaired well-being. Insomnia severity emerged as a central factor, showing the strongest relationship with poor well-being, thereby positioning sleep disturbance as a potential link between technology overuse and psychological distress. Moreover, emotion-focused and avoidant coping strategies were associated with nomophobia, insomnia severity, and diminished well-being, delineating a coherent maladaptive coping profile. Furthermore, both insomnia severity and reliance on avoidant coping were negatively correlated with academic performance, indicating that psychological dysregulation and coping styles are meaningfully reflected in objective educational outcomes. The results of the regression analysis indicate that the examined demographic, lifestyle, digital, and psychological variables explain only a small proportion of the variance in students’ GPAs.

The high prevalence of moderate to severe nomophobia in this cohort is consistent with recent epidemiological findings (Al-Mamun et al., 2025) and reflects the increasing centrality of smartphones in academic, social, and emotional domains (Bhattacharya et al., 2019). The positive association between nomophobia and insomnia severity may be interpreted through several complementary mechanisms. First, from a behavioral conditioning perspective, smartphone use may reinforce cognitive-emotional arousal through repeated social connectivity and information-access behaviors (Bhattacharya et al., 2019; Yildirim & Correia, 2015), particularly when these behaviors delay bedtime and disrupt sleep patterns (Oliveira et al., 2025). Second, circadian misalignment may arise from bedtime procrastination and blue light exposure, contributing to prolonged sleep latency and fragmented sleep (Oliveira et al., 2025). Third, problematic smartphone use has been associated with poorer academic outcomes (Paterna et al., 2024), suggesting that digital over-engagement may operate as both a stress amplifier and a coping substitute. Within the transactional model of stress and coping (Folkman & Lazarus, 1984), nomophobia may reflect maladaptive appraisal processes in which perceived disconnection from the device triggers anxiety responses (Bhattacharya et al., 2019; Yildirim & Correia, 2015). The positive correlations observed between nomophobia and emotion-focused and avoidant coping further support this observation (Folkman & Lazarus, 1984; Eisenberg et al., 2012; Carver, 1997). Rather than addressing stressors directly (problem-focused coping), students with higher nomophobia may rely on emotion modulation or disengagement strategies, which are less effective in high-demand academic contexts (Eisenberg et al., 2012; Kassaw & Demareva, 2025).

Previous studies demonstrated that sleep quality, duration, and regularity are robust predictors of academic performance in university students (Okano et al., 2019) and that sleep disturbances contribute substantially to academic underachievement (Hartmann & Prichard, 2018). Insufficient or fragmented sleep impairs executive functioning, working memory consolidation, attentional stability, and emotional regulation (Okano et al., 2019; Hartmann & Prichard, 2018). These domains are particularly critical in medical education, where sustained cognitive load and rapid knowledge integration are required (Hötting & Röder, 2013; Clemente-Suárez et al., 2023). Chronic sleep restriction may attenuate neurobiological adaptive processes, thereby diminishing cognitive performance. Moreover, sleep disturbance exacerbates affective dysregulation, which is highly prevalent among medical students (Rotenstein et al., 2016; Ishak et al., 2013), and may partly explain the strong association between insomnia severity and poorer MSWBI scores found in this study. Thus, insomnia may function as an important linking factor between behavioral dysregulation (e.g., excessive smartphone use), maladaptive coping, psychological distress, and academic outcomes.

The significant positive associations of emotion-focused and avoidant coping with nomophobia, insomnia, and poorer well-being align with the foundational stress-appraisal-coping framework (Folkman & Lazarus, 1984). In high-demand environments such as medical school, coping strategies modulate the impact of stressors on psychological and functional outcomes. Avoidant coping has been shown to exacerbate functional impairment in clinical populations (Eisenberg et al., 2012) and may similarly undermine academic efficiency by delaying task engagement, increasing rumination, and triggering physiological stress. The negative correlations observed between wGPA and both emotion-focused and avoidant coping are consistent with psychosocial models identifying adaptive self-regulation as a key predictor of academic achievement (Kassaw & Demareva, 2025). Interestingly, emotion-focused coping was positively correlated with problem-focused coping, suggesting that coping repertoires are not mutually exclusive and multiple strategies can be deployed depending on situational appraisal (Folkman & Lazarus, 1984; Carver, 1997). However, reliance on maladaptive strategies in response to chronic academic stress may contribute to cumulative dysregulation, including sleep disruption and digital overuse (Eisenberg et al., 2012; Kassaw & Demareva, 2025).

The finding of approximately half of the participants with poor well-being is consistent with prior meta-analytic evidence of high psychological morbidity in medical students (Rotenstein et al., 2016) and documented burnout risk (Ishak et al., 2013). The association between insomnia severity and well-being suggests that sleep modifications might have downstream effects on psychological health and academic performance. Moreover, emerging research highlights the importance of psychological well-being and academic readiness in preventing attrition and optimizing performance in early medical training (Hefny et al., 2024).

The negative correlation between sitting time and physical activity is consistent with established physical activity frameworks and measurement validation (Craig et al., 2003). The modest positive association between sedentary time and GPA warrants nuanced interpretation. Physical activity is widely recognized to enhance cognitive performance by increasing cerebral blood flow, releasing neurotrophic factors, and enhancing synaptic plasticity (Chang et al., 2012; Hötting & Röder, 2013). Furthermore, physical fitness has been positively associated with academic performance in student populations (Redondo-Flórez et al., 2022). However, health lifestyle theory (Cockerham et al., 2020) emphasizes that behaviors cluster in context-dependent ways. Sitting time was assessed using the IPAQ, which captures total sedentary behavior without distinguishing between academic and non-academic contexts (Craig et al., 2003). In a medical student population characterized by high academic demands (Hefny et al., 2024), increased sitting time may partly reflect study-related sedentary engagement rather than passive inactivity. Given the established links between psychosocial factors and academic achievement (Kassaw & Demareva, 2025), sedentary time in this context may represent academic investment rather than exclusively health-compromising behavior. Future investigations should disentangle cognitively engaged sedentary time from passive screen-based behavior to clarify these divergent pathways.

Due to the demanding nature of medical studies, characterized by a high academic workload and an intensive pace, medical students represent a relevant population for investigating how the combined influence of physical activity, sleep, psychological resilience, stress-coping strategies, and smartphone use behaviors affects academic performance (Rotenstein et al., 2016; Hefny et al., 2024). They experience higher rates of depressive symptoms and suicidal ideation compared to the general population, as well as substantial levels of burnout (Rotenstein et al., 2016; Ishak et al., 2013). In parallel, sleep disturbances and insomnia are highly prevalent in this group and have been directly linked to poorer academic outcomes, further amplifying their vulnerability to stress-related impairment (Oliveira et al., 2025; Dąbrowska-Galas et al., 2021; Okano et al., 2019; Hartmann & Prichard, 2018). Moreover, problematic smartphone use and nomophobia are increasingly documented among university students and are negatively associated with academic achievement, adding a contemporary behavioral risk factor to an already high-stress educational context (Paterna et al., 2024; Bhattacharya et al., 2019; Al-Mamun et al., 2025).

This study possesses several notable strengths that enhance its scientific contribution. It captured a multidimensional profile of medical students by simultaneously assessing lifestyle behaviors (physical activity and sedentary time), technology-related behavioral patterns (nomophobia), sleep disturbances (insomnia severity), psychological well-being, coping strategies, and academic achievement. This integrative design enables a systems-level perspective rather than an isolated examination of single risk factors, thereby reflecting the complex biopsychosocial reality of medical education. The inclusion of students from all six years of medical training provides a comprehensive cross-sectional snapshot of academic exposure across different phases. The sample size was adequate for detecting small-to-moderate associations, and the instruments employed are internationally validated and widely used in comparable populations. The good to excellent internal consistency coefficients observed in this sample further strengthen measurement robustness. Importantly, the study bridges traditional lifestyle determinants of academic performance (such as physical activity and sleep) with emerging digital-era constructs such as nomophobia, offering timely and contextually relevant insights.

However, several methodological considerations warrant careful interpretation of the findings. Foremost, the cross-sectional design precludes causal conclusions. Second, exclusive reliance on self-reported data introduces the risk of recall bias, reporting inaccuracies, and social desirability effects. In particular, self-estimated physical activity and sedentary time are known to be prone to over- or underestimation, while perceived smartphone dependence may not directly correspond to objectively recorded usage patterns. Third, the study was conducted at a single medical school, which may limit generalizability. Although students from all six academic years were included, participation was voluntary and partly facilitated through in-class recruitment due to initial low response rates, raising the possibility of selection bias. Students experiencing either higher distress or greater academic engagement may have been differentially motivated to participate. Additionally, potential confounding variables, such as socioeconomic status, baseline mental health diagnoses, caffeine or substance use, and personality traits, were not controlled for, which may have influenced the observed associations. Since the third sex category included only three participants, it was excluded from the final regression analysis to avoid unstable parameter estimates. Finally, although statistically significant, the observed correlations were small in magnitude, suggesting that academic performance is influenced by a broader constellation of factors beyond the variables assessed in this study.

5. Conclusions

In conclusion, this study identifies a tightly interconnected network of digital dependence, sleep disturbance, maladaptive coping, and psychological distress that meaningfully relates to academic performance in medical students. These findings suggest that academic outcomes in medical education are not solely determined by cognitive ability or study effort, but are substantially intertwined with behavioral, emotional, and lifestyle factors. The clustering of technology-related behaviors, sleep disruption, and coping style underscores the need for integrated prevention strategies rather than isolated interventions. Early identification of maladaptive coping patterns and compromised well-being is essential, as these factors may persist into later professional life. Our findings may inform targeted preventive strategies as part of institutional support, including sleep hygiene education, resilience and coping skills training, promotion of physical activity, and responsible digital behavior interventions to support both academic success and student well-being.