There is evidence to suggest that nomophobia is associated with learning performance, but the results of investigations on this topic are controversial in terms of the direction of the association. For instance, Essel et al. (2021) concluded that lower nomophobic behavior in university students was associated with better academic achievement, expressed as the cumulative weighted average of the academic year. Conversely, in a study by Aldhahir et al. (2023), medical students with the highest cumulative grade point average had the highest nomophobia scores. The findings from a descriptive correlational study (Qutishat et al., 2020) indicate a lack of significant differences in tertiary students’ perceived nomophobia across various academic performance levels. In regard to mediation analysis, Lin et al. (2021) documented the function of nomophobia as a mediator between the influence of non-educational use of a mobile device (e.g., social media) on learning performance of college students; in that framework, nomophobia was responsible for late sleep and insomnia, which in turn, directly or indirectly, brought about deviations in learning behavior. Instead, our study views the effect of nomophobia on academic performance as mediated by other variables, namely anxiety and depression.

Depression is a condition characterized by a reduction in mood, lack of pleasure, persistent contemplation, and decreased cognitive function (Ma et al., 2023). Anxiety can be described as a state of heightened arousal that involves both emotional and mental changes in response to a stimulus (Rustamov et al., 2023). Overall, there is agreement in the extant research on the significant contribution of depression and anxiety to undergraduate students’ problematic smartphone use. In a study on university students (Boumosleh and Jaalouk, 2017), multiple linear regression revealed that anxiety and depression scores reported by the participants were related to smartphone addiction. Additionally, a systematic review of 23 publications (Elhai et al., 2017) inferred the presence of a relationship between excessive smartphone use and anxiety, as well as depression. In another study (Kuru and Celenk, 2021), mediation analyses revealed that problematic smartphone use among undergraduate students was independently predicted by both depression and anxiety, with psychological inflexibility as a mediator.

However, although smartphone addiction and nomophobia are related concepts, they are not identical: nomophobia is a more specific concept, centered on a sense of fear, while smartphone addiction denotes a broader pattern of overuse. Furthermore, our hypothetical model posits a contrary causal pathway, in which nomophobia is a precursor of depression and anxiety. In doing so, we rely mainly on a cognitive-behavioral model that assumes that negative cognitive biases such as rumination can potentially catalyze negative emotions and behaviors (Hofmann, 2014; Catanzano et al., 2022). Additionally, research in the field of addiction psychology emphasizes the contribution of increased smartphone use to the onset of addiction-related symptoms, including withdrawal, tolerance, and loss of control (Larsen et al., 2022). These symptoms may further exacerbate anxiety and depression symptoms, leading to a cycle of negative affect and maladaptive coping behaviors (Wacks and Weinstein, 2021). In the case of nomophobia, the constant need to check one’s phone, the fear of being without it, or being unable to use it may be perceived as a stressor, leading to the development of negative cognitive biases and subsequent anxiety and depression, which in turn impair their academic success owing to decreased motivation and engagement in learning activities.

Nevertheless, research evidence on the link between these emotional disorders and learning gain is inconclusive. In a study by Awadalla et al. (2020), a longitudinal survey was administered among university students at baseline and after 6 months, and linear regression detected a weak but significant association between higher levels of depression and anxiety and worse academic performance. Wallin et al. (2019) longitudinally observed 26,766 individuals born between 1967 and 1982 in Sweden, from around the age of 16 up to 48; eventually, those who scored in the lowest quartile of grade point average had a higher likelihood of receiving a diagnosis of depression when compared to those who scored in the highest quartile.

On the other hand, a survey by Jamil et al. (2022) unearthed a negative correlation between the National Medical Unified Examination scores of medical students and their anxiety and depression; withal, this correlation was insignificant after considering other weighty predictors within multiple regression analysis, so the authors reject causation. According to a meta-analytic paper (Brumariu et al., 2023), anxiety is not a significant impediment to academic achievement, although it is a crucial factor associated with dropout rates and academic self-concept. Similarly, a recent network analysis of college students’ cross-sectional data (Wang et al., 2023) reports that feeling depressed was the most central symptom for those with a bottom 27% grade point average.

This research adopted a quantitative approach using a cross-sectional survey design.

Two separately working English to Kazakh translators created two Kazakh-language versions for each questionnaire, which were then merged by a third translator and mailed to three Kazakh-speaking education psychologists with at least 5 years of experience in the field. They confirmed the adequacy of the Kazakh items. These drafts were then back-translated to English to see whether they accurately reflected the original tools. Each resultant measurement was then preliminarily tested on three to five undergraduate students to evaluate its clarity and practicality. For each scale, the students uniformly agreed that the items were properly phrased and straightforward. Following that, consensus was reached on final Kazakh-language versions of the CES-D, NMP-Q, and STAI. Split-half reliability coefficient for the translated instruments ranged from 0.73 to 0.91.

Convenience sampling was employed to recruit participants. The present study complies with the Helsinki Declaration. Participation was anonymous and voluntary. The Ethics Committee of the corresponding author’s university reviewed and approved the study protocol (ВНД-ZU-27-02).

Faculty members at three universities in Kazakhstan disseminated an electronic letter inviting students to participate in the study, explaining its purpose and providing a brief description of the questionnaires that would need to be completed. Two inclusion criteria for participants were articulated: (a) consent to the collection of data, including those on academic performance and (b) completion of the electronic survey (all items were set mandatory, ensuring the lack of incomplete responses). From end-April to late September 2023, informed consent was obtained from 321 students who agreed to be enrolled in the study and received a confidential e-mail with a link to the self-selection survey in October 2023. Faculty members gathered data on cumulative grades for each person who agreed to participate in the study. Apart from basic demographics (gender and age), the survey form included a field to enter the number assigned to each respondent up front. Upon survey closure, these numbers were provided to the faculty members who in turn excluded those who had not submitted a response, so that we obtained data on grade point averages that did not contain any personal data. In late November 2023, the online survey was closed and we ended up with a final sample of 307 appropriate returned questionnaires from 307 undergraduate students who were majoring in diverse fields including education, computer science, psychology, and foreign language studies. The participants had an average age of 19.09 years (standard deviation = 1.52) and 181 (59%) of them were female. There were no restrictions on the grade levels of the respondents.

The use of multiple self-report questionnaires to obtain data from the same individuals in this study may have begot common method variance (also known as common method bias), which could slant the relationship between constructs (Fajriyati et al., 2020). To address this issue, the Harman single-factor test was performed as an initial step (Podsakoff et al., 2003). The test was run in the conmet R package and was interpreted in such a way that if the average variance extracted is >0.50, it was inferred that the dataset was likely to be affected by common method bias. Statistical normality of the data was confirmed by skewness within −2.0 to 2.0 and kurtosis within −7.0 and 7.0. Further, Pearson’s correlation analysis was executed to explore bivariate correlations coefficients between the variables. The magnitude of the relationship was interpreted as low, moderate, or strong when the correlation coefficient (r) was 0 to 0.29, 0.30 to 0.59, and > 0.60, respectively. Finally, the data were subjected to statistical mediation using the PROCESS computational tool (see, for example, Igartua and Hayes, 2021) to explore whether nomophobia predicted academic success and whether depression and anxiety mediated this link. The model number two was employed as it was structurally consistent with the set of our hypotheses. Gender and age were inputted as covariates. The indirect effects as per unstandardized coefficients (b) and bias-corrected 95% confidence intervals (CIs) were computed based on 200 bootstrap replications drawn from the original 307 subjects. The presence of a mediating effect was accepted if the 95% CI did not cross zero (Mao et al., 2023). All tests were two-tailed with a significance level of α = 0.05. Descriptive analysis included calculating the mean and standard deviation for the collected data.

The findings of this paper highlight a critical issue at the intersection of technology use, mental health, and academic success. When juxtaposing our findings with the study (Aydin and Kus, 2023) that investigated the parallel mediating role of social media tools usage and digital gaming behavior in the relationship between nomophobia and smartphone addiction among secondary school students, it becomes apparent that while both studies address nomophobia, they focus on different variables and education contexts. This distinction reaffirms the research gap we spotted earlier and plays up the importance of tailored research approaches that account for contextual factors and individual differences in understanding and addressing the multifaceted challenges posed by excessive technology use.

The results outlined here can contribute to education research and practice. First, we confirmed the validity of the CES-D, STAI, and NMP-Q beyond the Turkish-and English-speaking populations. Second, we evaluated depression and trait anxiety as mediators between nomophobia and learning success, bridging the research gap to some extent. Third, this study adds to the growing body of research on the impact of technology on mental health and academic performance, as our findings may provide valuable and complementary insights into the impact of nomophobia on academic performance among tertiary students. For practitioners, these results highlight the need to design interventions that support students’ ability to regulate their mobile phone use, particularly in academic settings. Furthermore, this study may serve as a foundation for future research aimed at identifying the underlying psychological mechanisms that connect nomophobia to academic performance. Our findings suggest that there is a negative association between nomophobia and learning performance; that is, the more symptoms of nomophobic behavior a student has, the lower their average grade.

Our research also found that depression was not a significant mediator in the relationship between nomophobia and learning performance, while anxiety was. Specifically, nomophobia did not just affect academic performance directly, but this effect was exacerbated by amplified anxiety levels among the learners; that is, those who reported higher nomophobia scores were more likely to have more severe anxiety, which was connected to lower academic gain. This suggests that while nomophobia is linked to mental health issues, its impact on learning performance may be more directly related to anxiety than depression. One possible explanation is that anxiety is a common emotional response associated with the fear of being separated from one’s mobile phone, and this emotion can have detrimental effects on learning by reducing concentration and attentional resources. This is because anxiety can consume cognitive resources that would otherwise be available for learning and problem-solving tasks. On the other hand, depression may not mediate the relationship between nomophobia and learning performance, since depression may have a separate effect on learning performance, whereas it may not be related to nomophobia or dysfunctional smartphone use.

Evidence offers several factors allegedly explaining the progression of anxiety against the background of nomophobia. For instance, a case study of an individual with dependency on virtual communication devices and social phobia (King et al., 2013) suggests that the changes in daily habits resulting from nomophobic behavior may bring about coexisting mental disorders. Bragazzi et al. (2019) administered an online survey among young adult participants (mainly undergraduate students) and revealed that individuals with nomophobia tended to use maladaptive coping techniques, such as self-blame, denial, and behavioral disengagement. Correlation and multivariate regression analyses of the survey data determined that these coping strategies were “independently associated with anxiety.” Finally, the anxiety that emerges in nomophobic individuals may be due to a variety of factors, such as fear of missing out (Bacaksiz et al., 2022) or low self-esteem (Vagka et al., 2023).

As technology use becomes increasingly ubiquitous in education, it is crucial for researchers and educators to continue investigating the associations between technology and mental health to develop evidence-based strategies for promoting healthy technology use and improving academic outcomes. One implication of our study is that educational institutions should consider implementing programs or interventions that help students manage anxiety and nomophobia. For example, institutions could provide students with resources to manage stress and anxiety, such as counseling services, mindfulness programs, or stress-reduction techniques. Furthermore, institutions could consider incorporating technology or digital literacy skills training into their curricula to help students develop healthier relationships with technology.

It is suggested that programs for the prevention of nomophobia should not only focus on individuals’ smartphone adhesion but also on the underlying psychological mechanisms through which nomophobia elicits self-destructive behaviors in undergraduate students. An experimental study (Tams et al., 2018) focused on the relationship between nomophobia and stress in young business professionals as well as the factors that influence this relationship. Their results imply that nomophobia is a situation-specific condition that emerges in response to situations that prevent access to a smartphone, and feelings of uncertainty and lack of control aggravate the adverse impacts of nomophobia on stress levels. The authors believe that managers can lessen the undesirable effects of nomophobia by promoting trust and social connectivity among personnel and granting them greater control over smartphone usage during meetings. This can be partially extrapolated to the education field in the vein that teachers could foster a supportive classroom environment by encouraging students to connect with each other and by providing opportunities for students to discuss their experiences and feelings about technology use. On the whole, further research is needed to better understand the causes and consequences of nomophobia, as well as the most effective interventions for addressing it.

This research, like most others, has limitations that should be considered when interpreting the findings. Firstly, the sample size was relatively small, consisting of 307 undergraduate students and the survey was carried out in Kazakhstan, which has a unique cultural and educational context. Therefore, the findings may not be generalizable to other countries or educational systems, particularly to those with different levels of technological advancement or cultural attitudes toward mobile phone use. Secondly, this study relied on self-report measures, which may be subject to social desirability bias or recall bias. Participants may have underreported or overreported their levels of nomophobia, anxiety, or depression, which could have impacted the accuracy of the results.