The sample’s psychological dimension produced the highest mean scores, followed by the social and biological dimensions. In unadjusted comparisons, television viewing and attendance in the afternoon shift were associated with higher overall scores. Older pupils had higher social and biological scores, but age and school grade overlapped in the sample, so the researchers did not attribute an independent effect to either variable.

Students who practiced sports had lower biological-dimension scores. These were reported associations between measured variables; they do not show that television viewing, class schedules or sports participation changed the children’s nomophobia scores. The results became more limited after accounting for the number of statistical comparisons.

Following false-discovery-rate correction, television viewing remained associated with higher scores in the general comparison, while the afternoon shift retained a significant association in the biological dimension. Multilevel models accounted for students being clustered within 23 educational establishments and found that television viewing remained associated with higher nomophobia scores. That model association was not significant after correction across the model coefficients.

Effective sample sizes for some comparisons were about 136 to 310 students rather than the full sample of 954, an important limitation when interpreting the school-level structure and the smaller analysis-specific samples. The authors placed the findings in the context of education policy and digital citizenship, treating school mobile-phone use as a governance issue rather than testing the effects of a particular regulatory approach. Their contextual comparison examined Ecuador’s regulatory approach alongside those of four Latin American countries with national laws governing mobile phones in schools.

That comparison provides a legal and policy frame for the analysis, but it does not measure governance outcomes or establish whether any of the regulatory approaches is more effective. The research data were collected before Ecuador’s April 2025 ministerial agreement on mobile phones in schools, meaning the study is not an evaluation of that agreement or its implementation. Overall, the research presents nomophobia scores as a multidimensional pattern among the participating pupils and identifies television viewing as the most persistent association in the reported analyses.

Its principal contribution is descriptive: the study shows how responses on psychological, social and biological components differed across a school-age sample while demonstrating how multiple testing and clustering across schools constrained the interpretation of small associations. Nor does it show that school regulation, television viewing, schedules or extracurricular activities can prevent nomophobia. The supported conclusion is narrower: in this group of 954 pupils, psychological scores were highest, several sociodemographic and activity-related differences appeared in unadjusted analyses, and television viewing remained associated with higher scores under the study’s adjusted statistical procedures.

Subject of Research: Patterns of nomophobia scores and associated sociodemographic factors among 954 Ecuadorian schoolchildren aged 10 to 13

Article Title: Nomophobia among Ecuadorian schoolchildren: sociodemographic patterns and implications for digital citizenship and educational governance

Article References: Clavijo-Castillo, R., Reyes-Guaranda, M., & Cabrera-Ortiz, F. (2026). Nomophobia among Ecuadorian schoolchildren: sociodemographic patterns and implications for digital citizenship and educational governance. Frontiers in Political Science, 8, Article 1965153. https://doi.org/10.3389/fpos.2026.1965153

Image Credits: AI Generated

DOI: 10.3389/fpos.2026.1965153

Keywords: nomophobia, schoolchildren, Ecuador, mobile-phone anxiety, television viewing, school schedules, extracurricular sports, digital citizenship, educational governance, multilevel modeling, Ecuadorian, sociodemographic

Nomophobia describes anxiety or unease arising when a person cannot access a mobile phone or mobile communication services. Smartphone addiction, by contrast, refers to excessive, compulsive and uncontrolled smartphone use despite negative consequences. The distinction is central to the analysis: nomophobia captures an emotional response to potential separation from a device, while smartphone addiction measures a problematic behavioural pattern. Both were assessed among undergraduates at a university where smartphones support communication, academic coordination and access to information but can also become tools for coping with distress or unmet emotional needs.

Researchers used a quantitative, cross-sectional correlational design and recruited 411 students through convenience sampling during a one-month data-collection period. Participants were approached at selected halls, hostels, shuttle terminals and summer huts, mainly between 6 p.m. and 8 p.m. Eligibility required participants to be at least 18 years old, enrolled as undergraduates and smartphone owners. Questionnaires were completed anonymously after written informed consent, and the researchers reported a return rate of about 99.5%. All questionnaires included in the final analysis were sufficiently complete, with no missing data.

The measures covered nomophobia, financial stress, love addiction, academic stress and smartphone addiction. The 20-item Nomophobia Questionnaire used seven-point responses and produced total scores from 20 to 140, with higher scores indicating more severe nomophobia. The study also used a 13-item financial stress scale, a 24-item love addiction inventory, a 35-item academic stress questionnaire and a 10-item smartphone addiction scale. The mean score for nomophobia was 94.0 ± 24.5, compared with 26.3 ± 7.9 for financial stress, 53.0 ± 23.7 for love addiction, 121.8 ± 23.5 for academic stress and 31.8 ± 12.1 for smartphone addiction.

Nomophobia showed weak positive correlations with financial stress, love addiction and academic stress, but its strongest reported correlation was with smartphone addiction. The corresponding Pearson coefficients were 0.139, 0.218, 0.200 and 0.512, respectively, with all reported p-values below 0.01. A multiple linear regression found that financial stress, love addiction and academic stress jointly explained 8.8% of the variance in nomophobia, with an adjusted R² of 0.081: F(3, 407) = 13.04, p < .001. Love addiction and academic stress were significant individual associates in that model, whereas financial stress was not.

Process analysis produced statistically significant indirect associations for all three predictors through smartphone addiction. The estimated indirect effect was 0.247 for financial stress, with a 95% bias-corrected bootstrap confidence interval of 0.083 to 0.419; 0.135 for love addiction, with an interval of 0.083 to 0.192; and 0.134 for academic stress, with an interval of 0.078 to 0.195. None of these intervals included zero. In each model, the direct association became non-significant after smartphone addiction was included, which the authors described as evidence consistent with indirect-only statistical mediation.

The pattern is compatible with several psychological mechanisms, but it does not establish one. Compensatory Internet Use Theory proposes that people may turn to digital devices to cope with distress, adverse events or unmet social and emotional needs. Stress and coping theory similarly suggests that smartphones may temporarily help students manage academic demands, communicate with others or regulate emotional responses. Attachment theory adds a relational dimension: students who seek frequent reassurance may depend on mobile communication to preserve closeness with romantic partners. Collectively, these frameworks suggest a sequence in which stress or emotional dependence is associated with greater smartphone reliance, which is then associated with heightened discomfort when access is lost.

The direct results nevertheless require cautious interpretation. Academic stress and love addiction together with financial stress accounted for only a modest proportion of the observed variation in nomophobia, leaving most of it unexplained. The study did not measure potential influences such as anxiety, fear of missing out, self-control, social support, personality traits or patterns of smartphone access. Conceptual overlap between smartphone addiction and nomophobia may also have inflated their association. The authors noted that alternative temporal orders remain possible: nomophobia could contribute to smartphone addiction, academic stress or financial stress, and the relationships could be reciprocal rather than unidirectional.

Generalisation is further constrained by the recruitment method and setting. All participants came from one institution, and convenience sampling may have favoured students who were available in the selected campus locations during evening collection. Students attending evening classes, working, living off campus or otherwise unavailable may have been underrepresented. Reliance on self-report also creates the possibility that participants overestimated or understated their nomophobia, smartphone addiction, financial stress, love addiction and academic stress. Because the measurements were collected at one point, longitudinal research is needed to determine whether stress and emotional factors precede problematic smartphone use, whether such use precedes nomophobia, or whether both develop together.

The results offer a more connected picture than a simple comparison between stressed and non-stressed students. Financial stress did not retain a statistically significant direct association with nomophobia after the three predictors were considered together, yet its indirect association through smartphone addiction was significant. Love addiction and academic stress showed direct associations as well as significant indirect pathways. For the University of Cape Coast sample, the clearest statistical signal was not that any single stressor automatically produced fear of being without a phone, but that problematic reliance on smartphones formed part of the observed connection. Larger, longitudinal and mixed-method studies across multiple Ghanaian universities would be needed to test the pathway’s temporal direction and determine whether the same relationships hold in other student populations.

Subject of Research: Statistical mediation of nomophobia among University of Cape Coast students by smartphone addiction

Article Title: Predictors of nomophobia and the mediating role of smartphone addiction among students at the university of cape coast ghana

Article References: Mfodwo, R. D., Bamfo, H. D., & Cudjoe, R. C. (2026). Predictors of nomophobia and the mediating role of smartphone addiction among students at the university of cape coast ghana. Discover Education, 5(1), Article 1200. https://doi.org/10.1007/s44217-026-02318-8

Image Credits: AI Generated

DOI: 10.1007/s44217-026-02318-8

Keywords: nomophobia, smartphone addiction, academic stress, financial stress, love addiction, university students, cross-sectional study, mediation analysis, Ghana, Cape Coast, Predictors, mediating

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

The research team recruited 111 nurses working at a university hospital in Türkiye, a sample drawn from a workforce that is simultaneously among the most demanding in healthcare and among the most digitally connected. Ethical approval was obtained from the Ethics Committee of Biruni University under decision number 2023/85-60, and the study was conducted in accordance with institutional and national ethical guidelines as well as the 1964 Declaration of Helsinki and its later amendments. Every participant provided informed consent before data collection began, and the authors declared no competing interests and no external funding for the work.

Methodologically, the study rested on two well-established psychometric instruments. The first was the Nomophobia Questionnaire, or NMP-Q, a 20-item scale that yields scores reflecting the severity of nomophobic symptoms across dimensions such as fear of losing communication, loss of connectedness, lack of access to information, and giving up convenience. The second was the Individual Work Performance Questionnaire, the IWPQ, which measures perceived job performance across task performance, contextual performance, and counterproductive behavior. Participants also completed a nurse information form capturing demographic details and patterns of smartphone use, including daily screen time, phone use during working hours, and whether they personally considered their smartphone use excessive.

The headline numbers from the survey are striking in their own right. The mean NMP-Q score among the 111 nurses was 73.37 with a standard deviation of 27.25, indicating a substantial degree of nomophobic tendency in this population. The mean IWPQ total score was 3.86 with a standard deviation of 0.69, a figure that sits toward the favorable end of the performance scale. In other words, these were nurses who reported meaningful smartphone dependence but who nonetheless rated their own work functioning as generally solid—a discrepancy that immediately hints at the complexity the statistical analysis would go on to reveal.

The primary analysis examined the Pearson correlation between total NMP-Q and IWPQ scores, reported with a 95 percent confidence interval. The result was a correlation coefficient of −0.098, with a confidence interval spanning −0.279 to 0.090 and a p-value of 0.305. Because the interval crosses zero, the study could not confirm a statistically significant association between nomophobia and perceived job performance. A supplementary Spearman rank correlation, which is robust to outliers and non-normal distributions, produced a nearly identical estimate of −0.105 with a p-value of 0.274, reinforcing the same conclusion. The negative sign of both coefficients is directionally consistent with the hypothesis that higher nomophobia accompanies lower performance, but the magnitude is small and the uncertainty around it is wide.

The authors were careful to characterize what this null result actually means, and their framing is a lesson in statistical humility. The estimated association, they write, is compatible with both no association at all and a small-to-moderate negative association. With 111 participants, the study simply lacks the statistical power to distinguish between those possibilities. This is a common and underappreciated feature of correlation studies: a wide confidence interval does not prove that no relationship exists, it proves only that the data cannot yet pin one down. For hospital administrators tempted to conclude that smartphone anxiety is irrelevant to nursing performance, the honest reading is that the question remains open, pending larger samples.

Where the study did find robust signals was in its exploratory analyses of smartphone behavior, and here the statistical rigor is notable. The researchers applied false-discovery-rate, or FDR, correction to their secondary comparisons—a procedure that adjusts p-values to limit the number of false positives that inevitably arise when many tests are run simultaneously. After this correction, NMP-Q scores differed significantly according to daily smartphone use (q = 0.003), smartphone use during work (q = 0.011), and perceived excessive smartphone use (q = 0.003). Intriguingly, none of the comparisons involving IWPQ total scores survived the FDR correction, meaning that smartphone habits predicted nomophobia levels but not, in this dataset, perceived performance.

The adjusted analysis drove the point home with a multivariable linear regression using heteroskedasticity-consistent HC3 standard errors, a technique that guards against distorted confidence intervals when the variability of outcomes differs across groups. In this model, nurses who reported more than seven hours of daily smartphone use had NMP-Q scores 21.36 points higher than those reporting one to three hours per day, with a 95 percent confidence interval of 5.52 to 37.20 and a p-value of 0.008. That is a substantial effect—roughly three-quarters of a standard deviation of the nomophobia scale—suggesting that heavy daily screen time and nomophobic symptoms travel together in this population. The causal arrow, however, cannot be determined from cross-sectional data: it is equally plausible that anxious, phone-dependent individuals gravitate toward longer use, or that prolonged use itself cultivates dependence.

Why does the disconnect between nomophobia and performance matter? One plausible interpretation is that modern clinical environments have absorbed the smartphone into the workflow itself. Nurses routinely use phones for shift coordination, drug references, and institutional messaging, so device access may no longer function purely as a distraction. Alternatively, the IWPQ captures perceived performance, and self-assessments may be insensitive to subtle attentional lapses that nomophobia could produce—objective measures such as medication error rates or task-completion times might reveal effects that self-reports miss. The study’s authors emphasize that their findings should be interpreted cautiously given the sample size and the exploratory nature of the secondary analyses, and this restraint is warranted: a single-site study of 111 nurses cannot speak for the profession globally.

Nevertheless, the research adds a valuable data point to a growing literature on digital behavior in high-stakes workplaces. Its most actionable finding may be the strong link between daily smartphone duration and nomophobia scores, which identifies heavy users as a group worth monitoring—not because their performance is demonstrably suffering, but because the psychological burden of phone dependence is real and the long-term consequences in safety-critical settings remain unresolved. As hospitals worldwide grapple with mobile device policies, this study suggests the conversation should be grounded in measured evidence rather than reflexive alarm: the fear of being phoneless is prevalent among nurses, but its impact on the quality of care they deliver is, for now, statistically unproven and scientifically undecided.

Subject of Research: The relationship between nomophobia and job performance among hospital nurses

Article Title: Investigation of the relationship between nomophobia and job performance among nurses

Article References: Ersoy, F., & Karaca, A. (2026). Investigation of the relationship between nomophobia and job performance among nurses. BMC Nursing. https://doi.org/10.1186/s12912-026-05445-7

Image Credits: AI Generated

DOI: 10.1186/s12912-026-05445-7

Keywords: nomophobia, nurses, job performance, smartphone use, BMC Nursing, cross-sectional study, NMP-Q, IWPQ, occupational health psychology, nursing research, statistical correlation, hospital workforce