The study, led by Akgün Yeşiltepe of Munzur University and Canan Demir Barutcu of Burdur Mehmet Akif Ersoy University, surveyed 296 undergraduate nursing students during the 2022–2023 academic year. Participants completed a sociodemographic information form along with two validated instruments: the Smartphone Addiction Scale and the Nomophobia Questionnaire. The researchers then applied a battery of statistical techniques, including Pearson correlation, multiple linear regression, confirmatory factor analysis, and structural equation modeling, to untangle the relationships between problematic phone use and the fear of being disconnected.

The headline result is striking. Smartphone addiction was positively and moderately correlated with nomophobia, with a correlation coefficient of r = 0.544 and a p-value below 0.001, meaning the association is extremely unlikely to be a statistical fluke. In plain terms, students who scored higher on measures of compulsive smartphone use also reported markedly greater anxiety at the prospect of losing phone access. The multiple linear regression model was statistically significant and explained 47.0% of the variance in nomophobia scores, an unusually high figure for behavioral research, where models often account for far less.

Within that regression model, higher smartphone addiction scores significantly predicted higher nomophobia levels, with an unstandardized coefficient of B = 1.109, a standardized coefficient of β = 0.493, and p < 0.001. This means that even after accounting for other variables, smartphone addiction remained the dominant predictor of nomophobia in the sample. But the model also revealed a supporting cast of significant predictors that the researchers say deserve attention in their own right.

Age emerged as a significant predictor, with B = 2.107, β = 0.138, and p < 0.05, suggesting that older students in the sample reported higher nomophobia. Monthly income also played a role, with B = 0.002, β = 0.211, and p < 0.001, indicating that students with higher monthly income tended to report greater nomophobia, possibly because greater financial means facilitate more extensive smartphone and data use. Daily sleep duration was another significant factor, with B = 1.850, β = 0.094, and p < 0.05, hinting at a relationship between sleep patterns and phone-related anxiety that the authors say warrants further study.

Social media usage characteristics also mattered. The researchers found that use of specific platforms, namely Facebook, Instagram, and Twitter, were significant predictors of nomophobia among the students. This suggests that it is not merely the device itself but the social ecosystems it hosts that feed the fear of disconnection. For nursing students, who often rely on digital communication for coordination with peers and clinical staff, the stakes of staying connected may be particularly high.

To test the robustness of their findings, the researchers turned to structural equation modeling, a technique that allows researchers to test theoretical models rather than just correlations between individual variables. The SEM results further supported the relationship, indicating that smartphone addiction positively and significantly predicted nomophobia with β = 0.62 and p < 0.001, and explained 38% of its variance with R² = 0.38. Confirmatory factor analysis was used to verify that the measurement instruments performed as intended in this specific population, adding methodological weight to the conclusions.

The authors frame nomophobia not as an isolated quirk but as a potential signal of technology-related psychological vulnerability. Nursing students may be particularly susceptible due to a combination of academic demands, frequent smartphone use, and heavy reliance on digital communication. The concern is not trivial: nomophobia has been linked in prior research to anxiety, sleep disturbance, and reduced academic performance, and nursing students face the added pressure of preparing for a profession where attention and emotional regulation are literally matters of patient safety.

The practical implications are significant for nursing education settings. The authors suggest that early identification of problematic smartphone use, combined with educational interventions addressing healthy smartphone habits, may help reduce nomophobia and support students’ well-being. Such interventions could include digital literacy training, awareness campaigns about the signs of compulsive phone use, and structured guidance on balancing screen time with clinical and academic responsibilities. Because the study is cross-sectional, it cannot prove causation; it is possible that nomophobia drives compulsive use just as much as the reverse, or that both stem from a common underlying vulnerability such as anxiety proneness.

The study was approved by the Mehmet Akif Ersoy University non-interventional clinical research ethics committee, and all participants gave informed consent electronically before completing the online questionnaire. The authors declare no competing interests and received no external funding. As smartphones continue to weave themselves into every corner of professional and personal life, the researchers argue that understanding the line between healthy connectivity and harmful dependence is becoming a core competency for the next generation of healthcare workers, not just a personal habit to be managed quietly.

Understanding why these findings matter requires a closer look at what nomophobia actually measures. The term, a shorthand for “no-mobile-phone phobia,” describes the situational anxiety that arises when a person cannot access their phone, whether because the battery has died, the device has been forgotten, or network coverage is unavailable. Researchers typically assess it across several dimensions, including fear of losing communication, losing connectedness, being unable to access information, and giving up convenience or the ability to check in with others. In the present study, the Nomophobia Questionnaire captured these dimensions, and the confirmatory factor analysis step was important precisely because it verified that the questionnaire’s underlying structure held together in this particular Turkish nursing student sample, rather than simply assuming that instruments validated elsewhere would behave identically here.

The distinction between smartphone addiction and nomophobia, while related, is worth drawing out. Smartphone addiction, as measured by the Smartphone Addiction Scale, generally reflects patterns of compulsive use: preoccupation with the device, tolerance effects, withdrawal-like feelings, and interference with daily functioning. Nomophobia, by contrast, is more specifically an anticipatory or situational anxiety about disconnection. The moderate correlation of r = 0.544 observed here suggests substantial overlap between the two constructs but not identity, meaning that a student can score high on compulsive use without necessarily experiencing severe separation anxiety, and vice versa. This partial independence is one reason the regression approach was informative: it allowed the researchers to isolate how much of nomophobia is uniquely attributable to addictive use patterns once demographic and behavioral factors were held constant.

The demographic predictors deserve careful interpretation. The positive association between age and nomophobia, for instance, runs counter to a common assumption that younger students, having grown up entirely within the smartphone era, would be the most attached to their devices. One plausible reading is that older nursing students face accumulating responsibilities, including clinical placements, family obligations, and financial pressures, that make constant availability feel more consequential. Similarly, the income finding, in which higher monthly income predicted greater nomophobia, may reflect the fact that students with more disposable income can afford premium data plans, newer devices, and continuous connectivity, making disconnection both more likely to be noticed and more disruptive when it occurs.

The sleep duration finding is particularly intriguing given the broader literature. Prior research has repeatedly documented bidirectional relationships between problematic smartphone use and sleep: late-night scrolling delays sleep onset, blue light exposure suppresses melatonin, and sleep deprivation in turn weakens the self-regulation capacities that normally restrain compulsive checking. The present study’s finding that daily sleep duration significantly predicted nomophobia, with a positive coefficient suggesting that longer sleepers reported somewhat higher nomophobia in this sample, complicates the simple narrative that phone use merely erodes sleep. It may instead reflect students using extended sleep as recovery from the fatigue of constant connectivity, or it may signal that the relationship between rest and phone-related anxiety is more nuanced than commonly assumed. The authors themselves flag this as an area warranting further study, and the cross-sectional design means no causal direction can be established.

The platform-specific findings also merit attention. That Facebook, Instagram, and Twitter use each emerged as significant predictors suggests that the architecture of social platforms, with their notification systems, algorithmic feeds, and social validation loops, may cultivate the very attachment patterns that underlie nomophobia. For nursing students, whose professional socialization increasingly occurs through digital channels, including group chats for clinical scheduling, online learning platforms, and professional networking, the boundary between necessary and problematic use becomes genuinely difficult to draw. A student cannot simply disconnect without risking professional consequences, which may amplify the anxiety associated with unavailability.

Methodologically, the use of structural equation modeling alongside multiple regression strengthens the study’s contribution. Whereas regression treats predictors as independent contributors to an outcome, SEM allows researchers to specify and test a theoretical structure, in this case one in which smartphone addiction functions as a latent driver of nomophobia. The convergence of the two approaches, with the regression model explaining 47.0% of variance and the SEM model explaining 38%, provides internal consistency, though the difference between the figures reflects the different variables and constraints each model incorporates. The very high proportion of variance explained in the regression model is notable for behavioral research, where models explaining 20 to 30 percent of variance are common, and suggests that the measured variables capture much of what drives nomophobia in this population.

Several limitations frame how these results should be generalized. The sample consisted of 296 nursing students at Turkish universities, and cultural context, nursing curricula structure, and institutional norms around phone use during clinical placements may differ substantially elsewhere. The cross-sectional design precludes causal inference, and self-report instruments are vulnerable to response biases, including social desirability and inaccurate self-assessment of usage. Longitudinal follow-up would help clarify whether smartphone addiction precedes nomophobia, follows from it, or whether both emerge from shared vulnerabilities such as trait anxiety or low emotional regulation. Nonetheless, the consistency of the findings across analytical methods, combined with the careful psychometric validation, makes this study a useful reference point for educators designing interventions. Screening for problematic smartphone use during nursing education, the authors suggest, could identify students at risk before phone-related anxiety interferes with clinical performance or well-being, an approach that aligns with growing interest in behavioral health support within health professional training programs.

Subject of Research: Smartphone addiction, social media use, and nomophobia among Turkish nursing students: a cross-sectional study

Article Title: Smartphone addiction, social media use, and nomophobia among Turkish nursing students: a cross-sectional study

Article References: Yeşiltepe, A., & Demir Barutcu, C. (2026). Smartphone addiction, social media use, and nomophobia among Turkish nursing students: a cross-sectional study. BMC Nursing. https://doi.org/10.1186/s12912-026-05265-9

Image Credits: AI Generated

DOI: 10.1186/s12912-026-05265-9

Keywords: Smartphone, addiction, social, media, nomophobia, Turkish, nursing, students, cross-sectional, scientific research