The Mediating Effect of Smartphone Distraction Between Nomophobia and Intuitive Eating Among Lebanese Young Adults: A Cross‐Sectional Study

ABSTRACT

Background and Aims

Significant apprehension has been triggered concerning various behavioral modalities in humans, including eating habits, which have been influenced by the increasing omnipresence of smartphone reliance. In fact, extreme digital interaction, known as nomophobia, disturbs both cognitive functions and behavioral regulation. To illustrate, smartphone distraction, which is characterized as the attentional intrusion stemming from screen mediation, plays a major role in adjusting nutritional intake. However, the processes driving these relationships have yet to be investigated. This study aims to understand the possible effect of smartphone‐induced interference as a mechanism motivating the relationship between nomophobia and intuitive eating patterns among young citizens in Lebanon.

Methods

A cross‐sectional design was done, including 397 Lebanese people aged between 18 and 30 years. An online survey was completed involving validated scales. The latter measured nomophobia through a Nomophobia Questionnaire, device distraction through a Smartphone Distraction Scale, and intuitive eating through Intuitive Eating Scale‐2.

Results

Higher levels of nomophobia were knowingly associated with greater smartphone distraction (β = 0.29, p < 0.001). Device distraction displayed a negative correlation with intuitive eating (β = −0.10, p < 0.05), revealing that the greater the digital cognitive encroachment, the lower the intuitive eating levels. Remarkably, there was no direct consequence of nomophobia on intuitive eating (β = −0.01, p > 0.05). Mediation analysis showed that smartphone interference may statistically serve as an intermediary between nomophobia and intuitive eating. This suggests that amplified attentional disruptions might be driving their relationship.

Conclusion

Vigilant alimentary habits and reduced screen usage must be endorsed by public health initiatives among young adults vulnerable to device overconsumption.

1. Introduction

Intuitive eating is a self‐regulatory approach that prioritizes internal physiological signals, such as hunger and satiety, over external dietary constraints or emotional initiations to control food ingesting [1, 2]. This approach has led to several advantageous consequences which include lower levels of disordered eating, improved body image, and better psychological well‐being [3, 4]. Nevertheless, numerous contextual and behavioral aspects may affect one's ability to eat intuitively. Such factors may not only disrupt attention to internal indications, but they can also impair self‐regulation [5]. Device use is one of the many factors influencing intuitive eating.

Nowadays, young adults suffer from new behavioral issues as a result of the swift incorporation of smartphones into their daily lives. An example of such issues would be nomophobia. The latter is defined as the anxiety or discomfort experienced when people are unable to access or use their mobile phones [6, 7]. Nomophobia has been generally reported in strongly linked populations and is associated with compulsive smartphone use, emotional dysregulation, and increased psychological distress [8]. This critical condition is highly prevalent in Lebanese households, where around half the adults seem to be suffering from moderate to severe levels of nomophobia [9]. This pattern has been connected to constant sociopolitical and economic pressures, which could increase dependence on digital connectivity as a coping mechanism [10].

There is increasing evidence that detrimental smartphone‐related habits may affect eating patterns alongside psychological effects [11, 12, 13, 14]. Specifically, food addiction, emotional eating, and other dysregulated dietary behaviors have been linked to nomophobia [11, 12, 15, 16]. Augmented psychological discomfort and excessive device usage are associated with reduced self‐regulatory ability, which may lessen sensitivity to internal hunger and satiety cues, according to studies looking at smartphone reliance and related categories [5, 6]. The consistency of results across research on smartphone‐related behaviors implies a possible negative connection between nomophobia and intuitive eating, even though there is currently little direct longitudinal data relating nomophobia particularly to intuitive eating [6].

Device distraction, which is characterized as the disruption of existing tasks due to attention being grabbed by smartphone‐related stimuli like notifications or digital content, is a likely mechanism behind this relation [17]. It has been established that those with greater degrees of nomophobia use their devices more frequently, have obsessive checking habits, and find it difficult to turn off smartphone‐related stimuli [11, 18]. According to behavioral and observational studies, such patterns contribute to attentional fragmentation during daily activities, supporting a link between nomophobia and increased susceptibility to smartphone‐related distraction [17, 19].

Considerable indications prove that distraction during eating affects nutritional self‐regulation and encourages mindless consumption [17]. According to earlier research, using a smartphone while eating is linked to ingesting more calories, favoring items high in energy, and consuming less healthier options [20]. These effects are believed to result from decreased interoceptive awareness, which makes people less sensitive to internal hunger and satiety cues [20]. The ability to regulate food intake based on physiological needs may be directly compromised by smartphone distraction, since intuitive eating is essentially dependent on this awareness [1, 20].

When considered collectively, current research points to a theoretically supported road in which nomophobia may promote smartphone distraction, which in turn hinders intuitive eating [11, 17, 18]. Even though most accessible evidence is cross‐sectional, the convergence of results across behavioral, epidemiological, and experimental studies supports the likelihood of this mediation model, particularly through mechanisms involving attentional interference and impaired self‐regulation [5, 12, 20]. However, these relationships have seldom been inspected simultaneously within a united analytical framework, especially among young adults. This gap is highly applicable in Lebanon where developing lifestyle patterns and environmental pressures which are able to affect eating habits intersect with great levels of device usage [19, 21]. Accordingly, the study conducted aims to inspect the role of digital distraction in the link between nomophobia and intuitive eating among young Lebanese citizens.

Three hypotheses may be formulated based on this theoretically grounded framework:

• 1. H1: Increasing levels of nomophobia will be positively correlated with greater digital interference.
• 2. H2: Amplified smartphone distraction will be correlated with fewer levels of intuitive eating.
• 3. H3: The relationship between nomophobia and intuitive eating will be mediated by smartphone distraction.

2. Methods

2.1. Study Design and Participants

The cross‐sectional study was conducted between September and November of 2024 among Lebanese young adults. The inclusion of participants was limited to young adults aged from 18 to 30 residing in Lebanon who had access to a smartphone. Meanwhile, a strict exclusion policy was applied to anyone previously diagnosed with a severe mental illness or a physician‐diagnosed eating disorder, which removes participants whose conditions might overlap with the study's goals. The rationale behind this was to minimize data noise from clinical outliers, ensuring the analysis remained focused on subclinical or typical eating behaviors, even if it meant the findings wouldn't apply to those with diagnosed clinical conditions.

To reach the target audience, the research was conducted online using Google Forms and followed a snowball sampling approach. The process started by sharing the survey link across the research team's own social and professional circles, mostly using WhatsApp, Instagram, and Facebook to spread the word. This was a deliberate choice to connect with a tech‐savvy group that likely experiences a wide range of smartphone habits and nomophobia levels. Ultimately, the group that participated was made up of university students and those who had recently graduated, which lined up perfectly with the study's intended age group.

Before the survey could be completed, participants were required to read an online summary of the study's objectives. Informed consent was obtained through a mandatory checkbox, which confirmed that involvement was voluntary and that the participant understood the confidentiality protocols. To maintain the integrity of the dataset, rigorous quality control was used; any submissions with missing information were omitted from the final study. To prevent duplicate entries, the survey allowed only one submission per device, and the data was thoroughly cross‐checked for any inconsistencies. Although a specific response‐time filter was not used due to the survey's online format, every entry was manually reviewed to ensure the answers were reasonable and internally consistent; furthermore, all statistical reporting followed clinical research standards. Lastly, no artificial intelligence was employed for data collection, analysis, or statistical procedures.

2.2. Ethical Approach and Participation Agreement

Official ethical clearance for this study was granted by the Notre‐Dame des Secours University Hospital Ethics Committee under the reference CR 2/2024 on July 9, 2024. To ensure voluntary participation, informed consent was collected via an electronic format; the act of submitting the completed online form served as the formal indication of each participant's agreement. Throughout the research process, all protocols were strictly aligned with the Declaration of Helsinki and other applicable ethical requirements.

2.3. Calculating the Minimal Size Sample

To ensure the study was powered to identify mediation effects, the Fritz and MacKinnon approach was utilized to determine the necessary sample size. Based on this specific methodology, it was calculated that a minimum of 123 participants would be required for the analysis [15]. The formula implemented by the estimation is the following: $n=\frac{L}{f2}+k+1$, assuming a small‐to‐moderate effect size (f = 0.26), L = 7.85 for an α level of 0.05% and 80% power, and k = 7 predictors included in the model.

2.4. Questionnaire

Organized into three distinct parts, the Arabic‐language questionnaire took participants ~20–25 min to finish. The initial section provided a summary of the research objectives and secured informed consent via a mandatory checkbox. The following section focused on sociodemographic profiles, capturing data on gender, age, residency, and marital status, along with academic majors (categorized as scientific or non‐scientific). These specific metrics were chosen to investigate if behavioral differences in eating patterns emerge across different fields of study or backgrounds. In line with existing literature, several other factors were tracked as covariates:

The Household Crowding Index (HCI): This was used as an indicator of socioeconomic stress and status which are known to affect eating habits. It is calculated by dividing the total number of residents in a home by the number of rooms, though bathrooms and kitchens are not included in this total [15].

The Single‐Item Financial Stress scale (SIFiS): This measured financial stress on a scale from 1 to 10. This was included because financial pressure is known to impact psychological vulnerability and food accessibility [16].

Body Mass Index (BMI): Participants provided their own weight and height to calculate BMI. This allowed the study to account for physical health differences across the sample.

The Physical Activity Index: This composite score evaluates exercise intensity, frequency, and duration; the tool was originally created by researchers [22] and has been validated in Arabic [23].

The Nomophobia Questionnaire (NMP‐Q): To measure the level of anxiety caused by smartphone separation, the study utilized the NMP‐Q, which has been validated for Arabic speakers [24]. This 20‐item tool was chosen to analyze four areas of concern: losing connectivity, being unable to communicate, having limited information access, and the loss of convenience [25]. Using a 7‐point Likert scale (where 1 represents “strongly disagree”, 4 is “neutral” and 7 represents “strongly agree”), participants evaluated various scenarios, such as the discomfort felt when a signal is unavailable or when they cannot check their device. The resulting total scores range from 20 up to 140; in this system, a higher numerical value serves as a sign of more intense nomophobia severity. Scores of 20 reveal a lack of nomophobia, 21–59 indicate mild levels, 60–99 moderate levels, and 100–140 severe levels [25] (Cronbach's α = 0.97).

Intuitive Eating Scale‐2 (IES‐2): This 23‐item instrument, which has been validated in the Arabic language [26], was employed to assess behaviors related to intuitive eating. Participants provided responses on a 5‐point Likert scale, with values ranging from 1 (strongly disagree) to 5 (strongly agree). The questionnaire includes items that measure how individuals respond to their own food preferences and their ability to honor internal satiety signals. To interpret the results, the average scores are calculated; higher averages indicate a more adaptive and intuitive eating style [27] (Cronbach's α = 0.78).

Smartphone Distraction Scale: Validated in Arabic [28], the scale demonstrated excellent internal consistency in the present study (Cronbach's α = 0.93). A 5‐point Likert scale is used to score each of the 16 items, with 1 representing “almost never” and 5 representing “almost always.” Examples of items include, “I get distracted by smartphone notifications while working” and “I feel the urge to check my phone frequently during conversations.” Higher scores indicate a greater level of smartphone‐induced distraction [17].

2.5. Statistical Analysis

All analyses were conducted using SPSS version 27. Confirmatory factor analysis (CFA) was performed using the weighted least squares mean‐ and variance‐adjusted (WLSMV) estimator [29]. Model fit was evaluated using multiple indices, including the Comparative Fit Index (CFI) and Tucker–Lewis Index (TLI), with values ≥ 0.90 indicating excellent fit, and the Root Mean Square Error of Approximation (RMSEA) and Standardized Root Mean Square Residual (SRMR), with values ≤ 0.08 considered acceptable [30]. The distribution of the intuitive eating score was considered approximately normal based on skewness and kurtosis values within the range of −1 to +1. To compare the two groups, Student's t‐tests were utilized, while Pearson's correlation coefficients were calculated to investigate the relationships between continuous variables. For the mediation analysis, the research employed the PROCESS macro (Model 4, version 3.4). this process involved 5000 bootstrap samples and the calculation of 95% confidence intervals. The model specifically measured path a (from the independent variable to the mediator) and path b (from the mediator to the outcome), alongside the total (c) and direct (c') effects.A mediation effect was deemed statistically significant if the indirect effect's confidence interval did not cross zero. Regarding variable selection, any indicators with a p‐value below 0.25 in the initial bivariate analysis were integrated as covariates. This specific cutoff was chosen to ensure that no relevant confounders were prematurely omitted, a strategy supported by established methodological literature for variable selection in multivariate models [31]. Multicollinearity diagnostics were assessed prior to the mediation analysis using tolerance values and variance inflation factors (VIF). In terms of the output, all findings in this study are documented through standardized regression coefficients (β) along with their corresponding standard errors (SE). Additionally, 95% confidence intervals (CI) were provided to indicate the precision of these results. The mediation model was defined in advance, guided by theoretical and empirical evidence. Analyses were conducted as prespecified, and no additional exploratory or post hoc subgroup analyses were undertaken. Statistical significance was set at a two‐tailed p < 0.05.

3. Results

Three hundred ninety‐seven young adults filled the survey, with a mean age of 22.22 ± 3.86 years and 63.2% females. Based on established cut‐offs, the majority of participants exhibited moderate (36.3%, 144/397) to severe (39.8%, 158/397) levels of nomophobia, while 23.4% (93/397) had mild nomophobia. Additional details are provided in Table 1.

Table 1.

Characteristics of the sample (n = 397).

Gender
Male	146 (36.8%)
Female	251 (63.2%)
Major
Scientific	299 (75.3%)
Non‐scientific	98 (24.7%)
Social status
Single	380 (95.7%)
Married	17 (4.3%)
Nomophobia severity
No nomophobia	2 (0.5%)
Mild	93 (23.4%)
Moderate	144 (36.3%)
Severe	158 (39.8%)
Age (years)	22.22 ± 3.86
Body Mass Index (kg/m2)	23.88 ± 4.74
Household crowding index (person/room)	1.02 ± 0.52
Financial burden	5.51 ± 2.33
Physical activity	29.50 ± 20.93
Intuitive eating	47.32 ± 7.97
Nomophobia	85.43 ± 30.19
Smartphone distraction	46.96 ± 12.91

3.1. Confirmatory Factor Analysis of the Smartphone Distraction Scale

CFA indicated that the three‐factor model of the SDS scale demonstrated poorer fit: χ² (101) = 424.21, CFI = 0.990, TLI = 0.988, RMSEA = 0.090 [90% CI 0.081, 0.099], and SRMR = 0.059. Although the CFI and TLI values were high, the RMSEA exceeded the acceptable threshold, indicating inadequate model fit.

CFA indicated that the four‐factor model demonstrated superior and acceptable fit: χ² (98) = 269.04, CFI = 0.995, TLI = 0.993, RMSEA = 0.066 [90% CI 0.057, 0.076], and SRMR = 0.047.

3.2. Bivariate Analysis of Factors Associated with Intuitive Eating

Participants enrolled in scientific majors, compared to those in non‐scientific majors, had significantly higher intuitive eating scores (Table 2). Furthermore, higher nomophobia and smartphone distraction scores were significantly associated with reduced intuitive eating scores, as presented in Table 3.

Table 2.

Bivariate analyses of factors associated with intuitive eating score.

	Mean ± SD	p
Gender		0.21
Male	47.99 ± 7.55
Female	46.94 ± 8.19
Major		0.02
Scientific	47.84 ± 7.97
Non‐scientific	45.76 ± 7.78
Social status		0.44
Single, divorced or widowed	47.41 ± 8.06
Married	45.88 ± 6.16

Note: Bolded values represent statistically significant p‐values.

Table 3.

Pearson Correlation Matrix.

	1	2	3	6	7
1. Intuitive eating	1
2. Age	−0.02	1
3. Financial burden	−0.06	0.09	1
6. Household Crowding Index	0.03	−0.13*	0.09	1
7. Nomophobia	−0.17***	0.07	0.11*	−0.07	1
8. Smartphone distraction	−0.19***	−0.02	0.07	−0.07	0.68***

^* p < 0.05;

^*** p < 0.001.

3.3. Analysis of Mediation

In the mediation model, intuitive eating was specified as the dependent variable, and the analysis was adjusted for the following covariates: gender, major and body mass index. Despite the relatively high correlation between nomophobia and smartphone distraction (r = 0.68), multicollinearity diagnostics indicated no significant collinearity concerns (nomophobia: tolerance = 0.523, VIF = 1.914; smartphone distraction: tolerance = 0.528, VIF = 1.893). Smartphone distraction mediated the association between nomophobia and intuitive eating (standardized indirect effect: Beta = −0.011; Boot SE = 0.05; 95% CI [−0.21; −0.02]). Higher nomophobia was significantly associated with higher smartphone distraction but not directly associated with intuitive eating. Higher smartphone distraction was significantly associated with lower intuitive eating. The completely standardized indirect effect was −0.11, suggesting a small‐to‐moderate indirect association between nomophobia and intuitive eating through smartphone distraction. The indirect pathway through smartphone distraction accounted for around 68.25% of the total association between nomophobia and intuitive eating (Figure 1).

Figure 1.

Mediation model illustrating the association between nomophobia, smartphone distraction, and intuitive eating among Lebanese young adults. Standardized regression coefficients (β), standard errors (SE), and P‐values were reported for each pathway. Path (a) reflects the link between nomophobia and smartphone distraction, while path (b) captures the association between smartphone distraction and intuitive eating. Path (c) represents the overall effect of nomophobia on intuitive eating, and path (c′) corresponds to the direct effect after accounting for the mediator. The indirect effect is presented with its 95% confidence interval (CI). All coefficients are standardized. *p < 0.05; ***p < 0.001. No artificial intelligence tools were used in the generation or editing of figures.

3.4. Sensitivity Analysis

The robustness of the mediation model was further examined through a sensitivity analysis conducted without adjustment for covariates. In this unadjusted model, higher nomophobia was significantly associated with higher smartphone distraction (Standardized Beta = 0.68; p < 0.001) and directly associated with lower intuitive eating (Standardized Beta = −0.17; p < 0.001). However, higher smartphone distraction was significantly associated with lower intuitive eating (Standardized Beta = −0.13; p = 0.049). The completely standardized indirect effect was −0.09, suggesting a small‐to‐moderate indirect association between nomophobia and intuitive eating through smartphone distraction; however, the bootstrap confidence interval included zero, indicating that the mediation effect did not reach statistical significance (standardized beta = −0.09; Boot SE = 0.05; 95% CI −0.18, 0.003).

4. Discussion

This study examined whether smartphone distraction functions as a mediating mechanism within the association connecting nomophobia with intuitive eating among Lebanese young individuals. These results highlight the significant behavioral influence of problematic smartphone habits and their possible connection to eating‐related patterns. When analyzing these outcomes, a clear distinction must be made between nomophobia, smartphone distraction, and smartphone addiction. Although smartphone addiction is characterized by an overall pattern of behavioral dependency, nomophobia is defined by an anxiety‐driven fear of being disconnected from the digital world. Meanwhile, smartphone distraction refers specifically to the ways in which device use interferes with an individual's focus during active tasks [7, 8, 11, 17].

The findings of this study are consistent with theoretical frameworks that prioritize the role of cognitive focus and behavioral self‐regulation [5, 19]. From an attentional standpoint, smartphone distraction can be viewed as a rival stimulus that reallocates mental energy away from crucial interoceptive cues, specifically those related to hunger and satiety [17, 19]. This interpretation is supported by recognized models of attentional interference, which argue that external triggers can interrupt internal mindfulness and weaken one's self‐regulatory systems [19]. Within this specific context, the frequency of device‐related interruptions likely diminishes an individual's potential for intuitive eating [20].

Furthermore, from the lens of behavioral regulation, nomophobia may represent a foundational psychological vulnerability characterized by an anxiety‐driven reliance on mobile technology [7, 8]. In practice, this dependence is expressed through increased distraction, which in turn degrades the ability to regulate eating habits effectively [5, 11]. This causal sequence aligns with broader self‐regulation models, which suggest that emotional or cognitive stressors do not always affect behavior directly; instead, they work by impairing attention and internal control mechanisms [5, 19].

4.1. The Relationship between Nomophobia and Intuitive Eating

No significant direct link was identified between nomophobia and levels of intuitive eating. Instead, the data revealed an indirect pathway that operated through an increase in smartphone distraction. Such findings suggest that the anxiety associated with nomophobia may not influence eating habits unless it is accompanied by the interruption of regulatory processes or attentional resources. Essentially, smartphone distraction seems to function as a central behavioral mediator, bridging the gap between psychological distress and a decline in the self‐regulation of eating. This specific trend mirrors earlier research, which associates nomophobia with problematic device usage and similar behavioral habits [11, 24]. Furthermore, it is well‐documented that digital interruptions during mealtime are regularly tied to a diminished sensitivity to internal hunger and satiety signals, often leading to maladaptive eating [4, 20]. These results are in harmony with psychological frameworks proposing that attentional mechanisms frequently mediate the way emotional states are converted into actual behavioral results [19].

4.2. The Mediating Role of Smartphone Distraction between Nomophobia and Intuitive Eating

The present model was based on a theoretically grounded ordering of variables, in which nomophobia is considered an antecedent psychological factor, smartphone distraction a behavioral manifestation, and intuitive eating a downstream behavioral outcome. The results of the mediation analysis confirm the hypothesis that smartphone distraction functions as a vital bridge between nomophobia and the practice of intuitive eating. Given the high proportion mediated, it appears that the relationship between these two variables is predominantly explained by the attentional processes tied to smartphone usage. These results lend weight to a conceptual model where digital reliance is linked to heightened levels of distraction, which subsequently correlates with a decrease in eating self‐regulation. Although existing studies specifically addressing the intersection of nomophobia and intuitive eating remain scarce, this identified pattern aligns with the broader body of evidence regarding attentional interference and its impact on health‐related behaviors.

The link between nomophobia and smartphone distraction is in agreement with earlier research identifying nomophobia—defined as an anxiety‐based reaction to being disconnected—as a predictor of attentional interference and compulsive device habits [24]. Individuals who report higher levels of this anxiety often struggle with persistent digital thoughts and frequent checking behaviors, both of which serve to disrupt their concentration during routine activities [18, 25]. Within the scope of the present study, these tendencies were linked to heightened levels of distraction, especially in situations that demand a high degree of self‐regulation, such as during meals.

Our findings show that smartphone distraction is negatively linked to intuitive eating. This supports wider research on how digital interruptions change the way individuals eat. Many studies already confirm that using technologies (like TVs or phones) during meals makes it harder to notice when one is full [32], this often leads to overeating [17, 20, 33]. Our research adds to this by showing that smartphone distraction specifically messes with the attention needed to feel internal eating cues. It is worth noting that being distracted doesn't stop a person from feeling their body's signals entirely. It just makes those signals less obvious to their brain. While ignoring these internal cues might theoretically make someone rely more on external factors (like seeing food or just having it available), this study did not examine external cue responsivity. As such, interpretations of these compensatory processes should remain strictly tentative.

Overall, these findings contribute to the field by suggesting that smartphone‐related distraction follows a disruptive path similar to more traditional distractions, such as watching television or multitasking while eating. Crucially, the sample size (n = 397) was well above the minimum requirement for detecting mediation effects according to standard statistical guidelines. This reveals that the analysis was adequately powered to capture small‐to‐moderate indirect effects, thereby supporting the robustness and reliability of the findings.

4.3. Clinical Implications

These findings carry important implications for clinical practice and public health initiatives. Clinicians, including dietitians and psychologists, should screen for nomophobia and excessive smartphone use among patients presenting with disordered eating patterns. Effective interventions may include digital mindfulness training to enhance smartphone awareness and reduce mealtime attentional disruptions, alongside educational programs in school and university settings to raise awareness of digital distraction's impact on dietary behaviors. Practical strategies—such as establishing phone‐free mealtime zones, implementing scheduled smartphone breaks, and promoting mindful eating practices—could further support adaptive behavioral regulation. Public health campaigns might emphasize the benefits of minimizing digital engagement during meals and highlight the effects of chronic smartphone use on eating patterns.

4.4. Limitations

The present findings must be interpreted in light of several limitations. First, the cross‐sectional design precludes establishing causality among nomophobia, smartphone distraction, and intuitive eating. Although mediation analysis was employed, the temporal ordering of these variables cannot be ascertained, rendering the results associative rather than indicative of causation. Future longitudinal or experimental investigations are warranted to elucidate directionality and causal mechanisms. Second, the use of snowball sampling and online recruitment may have introduced selection bias. Participants were predominantly accessed via personal networks and digital platforms, potentially resulting in a sample that does not represent the broader population of young Lebanese adults. This method likely favored individuals with high digital engagement and smartphone use, thereby possibly inflating the observed prevalence of nomophobia and smartphone distraction relative to population norms. This non‐probabilistic approach may reduce the broader applicability of the findings and could underrepresent individuals with limited digital access or differing socio‐demographic profiles. Third, the use of self‐reported measures may lead to social desirability and recall bias, particularly when assessing psychological and behavioral variables such as eating habits and smartphone use. Fourth, although we adjusted for several relevant covariates, residual confounding may still be present as a result of unaccounted psychological variables, including stress, anxiety, and depression. These variables have been shown to affect both problematic smartphones use as well as eating behaviors, and could therefore serve as confounding factors in the observed associations. Further research should take these variables into account to better clarify the relationships examined. Additionally, a large proportion of the sample consisted of participants from scientific fields, which may reduce the generalizability of the findings. Participants, primarily from scientific disciplines, may exhibit distinct profiles in health literacy, behavioral awareness, or technology engagement compared to those in other fields, potentially influencing intuitive eating tendencies and susceptibility to smartphone distraction. Furthermore, interpretations must consider Lebanon's unique socio‐cultural context, characterized by prolonged economic instability, financial pressures, and societal challenges. These conditions may heighten reliance on digital technology as a distress buffer [34], while dietary patterns bear imprints from intertwined psychological and ecological pressures [35] —factors likely underpinning the observed associations and necessitating caution in extrapolating to other cohorts.

5. Conclusion

This study shows that smartphone distraction plays a mediating role in the relationship between nomophobia and intuitive eating among young Lebanese adults. Nomophobia was not directly linked to eating behaviors; instead, its effect appeared indirectly through increased distraction, pointing to an important behavioral pathway. These findings offer a useful framework for future research and for interventions aimed at supporting healthier eating habits while reducing the negative effects of compulsive smartphone use. In settings where technology is deeply embedded in daily life, public health efforts that encourage digital detox and mindful eating at mealtimes may be especially valuable. Future longitudinal designs are imperative to delineate causality and appraise cross‐cultural generalizability.

Author Contributions

Jane Ziade: writing – original draft, writing – review and editing, validation. Elie Kesrewani: resources, writing – review and editing, validation. Joe Al Sarrouh: resources, writing – review and editing, validation. Feten Fekih–Romdhane: conceptualization, methodology, validation, writing – review and editing, project administration, supervision. Souheil Hallit: conceptualization, methodology, writing – original draft, writing – review and editing, formal analysis, project administration, supervision, data curation, validation. Sahar Obeid: conceptualization, methodology, supervision, project administration, validation, writing – review and editing.

Funding

The authors have nothing to report.

Ethical Statement

The study protocol was reviewed and approved by the Ethics and Research Committee of Notre‐Dame des Secours University Hospital.

Consent

Participants provided informed consent electronically upon submission of the completed questionnaire. All procedures were conducted in accordance with the principles of the Declaration of Helsinki.

Conflicts of Interest

The authors declare no conflicts of interest.

Transparency Statement

Souheil Hallit confirms that this manuscript provides a truthful, accurate, and transparent account of the study. No essential aspects have been omitted, and any deviations from the original study plan have been clearly addressed.

Ziade J., Kesrewani E., Al Sarrouh J., Fekih‐Romdhane F., Hallit S., and Obeid S., “The Mediating Effect of Smartphone Distraction Between Nomophobia and Intuitive Eating Among Lebanese Young Adults: A Cross‐Sectional Study,” Health Science Reports 9 (2026): e73325, 10.1002/hsr2.73325.

Data Availability Statement

The datasets generated and/or analyzed during the current study are not publicly available but are available from the corresponding author on reasonable request (SH). The datasets generated and/or analyzed during this study are not publicly available but can be obtained from the corresponding author (SH) upon reasonable request.