Smartphones were introduced to the market in 2007 and have since become an indispensable part of life for millions of people worldwide. ¹ By 2021, the GSM Association of the Global System for Mobile Communications reported that 75% of people in the world owned a smartphone. ^{2 , 3} According to the National Institute of Statistics and Informatics (INEI), in the first three months of 2023, 89.2% of people aged 6 and over in the country had access to the Internet from a cell phone; this figure exceeds by 7.8% that obtained in 2019. ⁴ This increase can be justified by its multiple functions such as facilitating communication, vast access to information; it also fulfills the function of a computer, a camera, an entertainment game, a multimedia player and provides access to e-books and thousands of entertainments, education and social interaction applications. ^{5 , 6}

On the other hand, because of the Covid-19 pandemic and the lockdown, changes in lifestyle were generated, ⁷ so that it was necessary to adapt to virtuality. Also, the figures of young people who are not in education, employment, or training (NEETs) increased, who before the pandemic represented 16.73% of the young population and became 26.82%, this represents a great barrier that limits economic growth and development in the country. ⁸

The term addiction can be defined as a pathological behavioral condition in which one cannot think or judge rationally due to certain ideas or objects, ⁹ this addiction leads to a lack of ability to properly manage actions that can have harmful results. ⁷

Considering the negative impact that smartphone addiction has, it is thought that it is a conditioning factor for the appearance and development of different disorders such as bruxism, which is a condition that consists of a repetitive pattern of the masticatory muscles characterized by clenching and grinding the teeth. ^{10 , 11}

Two complementary, non-mutually exclusive pathways have been proposed to explain how excessive smartphone use might favour bruxism. The first is biomechanical-postural: prolonged neck flexion to look at the screen promotes a sustained forward head posture, which alters the resting position of the mandible, reduces the craniovertebral angle and increases the load on the cervical and masticatory muscles, generating chronic hyperactivity of the masseter and temporalis that is shared with bruxism and temporomandibular disorders. ¹² Consistent with this, electromyographic studies in heavy smartphone users have documented increased fatigue and altered resting activity of the masticatory muscles after device use. ¹³ The second pathway is psychosocial-behavioural: smartphone dependence and addiction are associated with stress, anxiety and sleep disturbances, and these psychological factors are, within the biopsychosocial model, among the most consistently reported predisposing factors for bruxism. ¹⁴ Excessive device use may therefore act on bruxism both directly, through muscular overload, and indirectly, by amplifying psychological distress and disrupting sleep.

The expression of bruxism varies considerably between populations and settings. Reported prevalences differ widely across studies, reflecting not only methodological and diagnostic heterogeneity but also differences in psychosocial stressors, lifestyle and socioeconomic context. ¹⁴ This contextual variability justifies examining the smartphone–bruxism relationship in more than one geographical setting rather than assuming a uniform effect, and it is one reason why two coastal cities with different demographic and care-seeking profiles (Piura and Chincha) were compared in the present study.

Accordingly, the aim of this study was to determine the association between smartphone dependence and addiction and bruxism in NEET young people in two coastal cities in Peru, Piura and Chincha. We hypothesised that (i) smartphone dependence or addiction would be positively associated with the presence of bruxism symptoms, and (ii) that the strength of this association could differ between the two cities given their distinct sociodemographic and contextual characteristics. Given its exploratory design, the study was intended to be hypothesis-generating rather than confirmatory.

Table 1 shows that in the city of Chincha, the distribution by sex of young “NEETs” is similar. The group between 25 and 29 years of age stands out with 41.4%. Regarding bruxism, 56.8% are considered to have improbable symptoms, while 22.2% present probable symptoms, and 20.1% show definite symptoms. Regarding smartphone dependence or addiction, a significant 63.4% show dependence, and 2.4% show addiction.

On the other hand, in Piura, a higher proportion of female participants (77.0%) is observed. The 25-29 age group also stands out with 42.5%. Regarding bruxism, 60.7% report unlikely symptoms, while 18.7% have probable symptoms and 20.5% present definite symptoms. Smartphone dependence or addiction is also notable, with 61.9% showing dependence and 3.5% addiction.

Table 2 shows that in Chincha, sex presents a significant association with bruxism, with a p-value of 0.034, where men present higher prevalence (55.0%) of probable or definitive bruxism. However, age and smartphone dependence or addiction did not show statistically significant differences.

In Piura, although sex and age did not show significant associations, smartphone dependence or addiction did show a significant correlation, with a p-value of 0.003. Here it is observed that those with smartphone dependence or addiction present a higher prevalence (49.3%) of probable or definite bruxism.

Table 3 presents PR through two models: a simple model and an adjusted model. In the simple model we observe that, in the population of young “NEETs” in Piura, the proportion of bruxism is 3.77 times higher in those with smartphone dependence or addiction, with a 95% CI [1.53-9.30]. In the adjusted model of the same population of young “NEETs” from Piura, this association is amplified since the group with smartphone dependence or addiction has a proportion of bruxism 5.38 times higher than those without such dependence (95% CI [2.05-14.12]).

The population of young “NEETs” in Chincha shows a different pattern. The proportion of bruxism in those with smartphone dependence is 0.52 times that of those without dependence or addiction (95% CI [0.21-1.33]). Regarding the adjusted model for Chincha, the proportion of bruxism continues to show no significant association with sex, age or smartphone dependence or addiction. These observations suggest that in Chincha, bruxism is not strongly associated with sex, age, or smartphone dependence in the population studied.

Our study revealed a significant association between bruxism and smartphone dependence or addiction in Piura, contrasting with the lack of significant relationship in Chincha. The significant association in Piura suggests that excessive smartphone use may be related to a higher occurrence of bruxism in this population, although the cross-sectional design does not allow the direction of this relationship to be established. The lack of a significant relationship in Chincha suggests that other factors may be more directly related to bruxism in this area, or that the way in which technological dependence affects individuals may vary depending on the urban environment and its specific characteristics. ⁸

Several factors may account for the regional difference observed between Piura and Chincha. First, the two samples differed substantially in composition and recruitment setting: in Piura participants were recruited at a maternal and child centre and were predominantly women (77.0%), whereas in Chincha they came from a private dental office with a balanced sex distribution (50% women). Differences in the underlying populations, in care-seeking behaviour and in the prevalence of unmeasured psychosocial stressors could plausibly modify the strength of the smartphone–bruxism association across settings. ¹⁴ Second, because daily hours of smartphone use were not recorded, we cannot determine whether the two cities differed in the intensity or pattern of use, which limits the mechanistic interpretation of the contrast. Third, the modest size of the city-specific subgroups reduces statistical power and increases the influence of sampling variability, so part of the difference may reflect chance. These elements should be weighed together, and the regional contrast is best read as a hypothesis to be tested in larger, adequately powered studies rather than as established evidence of effect modification by city.

The association between male sex and bruxism observed in Chincha also deserves comment, as it runs counter to the broader literature. Systematic reviews tend to report a slightly higher prevalence of (especially awake) bruxism in women, generally attributed within the biopsychosocial model to differences in exposure and response to psychosocial stress, in awareness and in reporting behaviour, rather than to a clear biological predisposition. ¹⁴ Our discrepant finding in Chincha may stem from the specific characteristics of male NEET youth in that setting—who may face particular socioeconomic and psychosocial stressors—from differences in self-report between sexes, or simply from the small cell counts and multiple comparisons involved. Because the present study did not measure anxiety, stress, sleep quality or other recognised etiological factors of bruxism, we cannot identify which parameter underlies the sex difference; this is an explicit limitation and a priority for future work, which should incorporate validated psychosocial and sleep instruments to disentangle these pathways.

Comparing our findings with those of Prado et al., ¹⁷ we note that both studies highlight a worrying correlation between intensive smartphone use and oral health problems such as bruxism. What distinguishes our research is the focus on young “NEETs”, ¹⁸ this specificity proposes that technological dependence is a generalized problem that has greater effects in groups with certain sociodemographic and economic characteristics. ^{19 , 20} The observation by Carrillo et al. ²¹ on the impact of lifestyle changes, such as increased physical inactivity during confinement, and its relationship with increased bruxism, finds a parallel in our results. However, our study was conducted outside periods of confinement, suggesting a more persistent and less circumstantial problem. This aligns with the findings of Emodi-Perlman et al. ²² and Tinastepe and Iscan, ²³ who evidence a link between smartphone use and bruxism and reinforce our findings within a global context. On the other hand, the research by Chen et al. ²⁴ expands the picture by linking sleep problems and Internet addiction to health disturbances, which enriches our understanding of how the overuse of digital technologies may affect other aspects of physical and mental well-being as well. ^{23 , 24}

Among the strengths of our study is the focus on young “NEETs”, a segment of the population that is rarely the focus of attention in research on oral health and technology. This specific demographic focus offers crucial insights into how the particularities of this group may influence their relationship with technology and its impact on health.

Despite its strengths, our study faced limitations, such as the reliance on self-reports to assess bruxism; this approach, although practical and widely used, may lead to response biases given that participants may underestimate or overestimate their smartphone use or the presence of bruxism symptoms. ²⁵ Beyond self-report, several limitations should be emphasised. The cross-sectional design captures exposure and outcome simultaneously and therefore cannot establish temporality or causality. The use of non-probabilistic convenience sampling at two care settings introduces potential selection bias and limits the generalisability of the findings to the wider NEET population. Importantly, we did not measure daily hours of smartphone use or recognised predisposing factors of bruxism—such as sleep disorders, anxiety, stress and other psychogenic factors, or swallowing problems—so residual confounding cannot be ruled out and the underlying mechanisms cannot be disentangled. Finally, the modest size of the city-specific subgroups, together with the multiple stratified comparisons performed without correction and without an a priori power analysis, means that some associations may be unstable or due to chance. Taken together, these limitations do not invalidate the findings but require that they be interpreted with caution as exploratory and hypothesis-generating. They highlight the importance of conducting future research using mixed methods, combining self-reports with clinical examinations for bruxism and digital tracking of smartphone use. These more diversified methodological approaches would allow us to validate and deepen our findings, and to explore in greater detail the complex dynamics underlying the relationship between technology and oral health.

The identification of a significant relationship between bruxism and smartphone dependence or addiction among socially and economically vulnerable youth, such as the “NEETs” group, underscores the urgent need to study technology dependence, and to consider strategies to prevent bruxism and other related oral health problems. ²⁶ In addition, it is crucial to foster a collaboration between health professionals, educators, parents, and policy makers to create a supportive environment that facilitates young “NEETs” to adopt more balanced and healthy lifestyles. Future actions should include more detailed research that explores the underlying mechanisms of this relationship and evaluates the efficacy of specific interventions for this population.

The study was approved with Official Letter from the Research Ethics Committee of the School of Stomatology N° 0109-2023-/UCV/P dated December 20, 2023. We adhered to the principles of the Declaration of Helsinki. Written consent was obtained from all participants.