Smartphone Addiction and Screen Time Show Distinct Links to Student Mental Health

Smartphones have become so woven into the fabric of student life that the average Lebanese university student now spends more than six hours a day looking at a screen, according to a new cross-sectional study published in BMC Psychiatry. The research, led by Sarah Christina Badr and colleagues at the Gilbert and Rose-Marie Chagoury School of Medicine of the Lebanese American University, examined 404 university students and found that two different aspects of smartphone use — the raw duration of screen time and the psychological pattern of smartphone addiction — are associated with two different mental health outcomes. Smartphone addiction was independently linked to greater depressive symptom severity, while screen time itself was associated with greater anxiety symptom severity. Perhaps most strikingly, the relationship between screen time and depression was not fixed: it flipped direction depending on how addicted a student was to their device.

The study arrives at a moment when concerns about the mental health consequences of smartphone use have become a global conversation, spanning debates about social media, adolescent wellbeing, and the design of attention-grabbing apps. Yet the scientific literature has been surprisingly inconsistent. Some studies report strong associations between heavy smartphone use and psychological distress, while others find weak or negligible effects. Part of the problem, the authors note, is methodological: most previous research has relied on self-reported estimates of smartphone use, which are notoriously unreliable. People routinely misjudge how long they spend on their phones, and subjective recall can distort the very associations researchers are trying to measure. Few studies have used device-recorded data, which capture what the phone itself logs rather than what the user believes.

To address this gap, the Lebanese team designed a cross-sectional online survey that combined validated psychological questionnaires with objective smartphone measurements. Smartphone addiction was assessed using the Smartphone Addiction Scale, a widely used instrument that probes patterns such as tolerance, withdrawal, compulsive checking, and interference with daily life. Depressive symptoms were evaluated with the Patient Health Questionnaire-9, a nine-item screening tool that scores the severity of depression symptoms on a scale from zero to twenty-seven. Anxiety symptoms were measured with the Generalized Anxiety Disorder-7 questionnaire, which similarly quantifies the severity of anxiety on a seven-item scale. Crucially, screen time was not self-reported: participants provided data directly from their smartphone settings, giving the researchers an objective record of daily use.

The numbers are revealing. Among the 404 students surveyed, mean daily screen time was 6.33 hours, with a standard deviation of 2.50 hours — meaning that a typical student spent roughly a quarter of each day looking at a screen, and many spent considerably more. This is an extraordinary figure when compared with the total hours of waking life, and it underscores just how central smartphones have become to the daily routines of young adults in Lebanon, a country that has faced economic crisis, political instability, and the ongoing aftermath of conflict. The researchers used multivariable regression analyses to examine the associations between smartphone variables and mental health outcomes, adjusting for potential confounders to isolate the independent effects of each variable.

The results showed that smartphone addiction was independently associated with greater depressive symptom severity, with a regression coefficient of 0.088 and a 95 percent confidence interval of 0.046 to 0.129, reaching statistical significance at p less than 0.001. In plain terms, the more a student exhibited the psychological pattern of smartphone addiction — tolerance, withdrawal, compulsive checking — the more severe their depressive symptoms tended to be, regardless of how much time they actually spent on the phone. This distinction matters because it suggests that the psychological relationship with the device, not merely the raw hours of use, is what tracks with depression.

Screen time, by contrast, was associated with greater anxiety symptom severity, with a regression coefficient of 0.169 and a 95 percent confidence interval of 0.018 to 0.321, reaching significance at p equal to 0.028. This means that the raw duration of daily smartphone use, independent of addiction patterns, was linked to anxiety. The finding hints at a possible mechanism: prolonged screen exposure may reflect constant connectivity, information overload, or the stress of perpetual availability, all of which could feed anxious feelings. Alternatively, anxious students may simply use their phones more, using the device as a coping mechanism or distraction. The cross-sectional design of the study cannot determine which direction the causality flows, and the authors are careful to note this limitation.

The most technically intriguing result, however, is the interaction between screen time and smartphone addiction for depressive symptoms. The screen time by smartphone addiction interaction was significant, with a regression coefficient of 0.029 and a 95 percent confidence interval of 0.012 to 0.045, reaching significance at p equal to 0.001. What this means is that the association between screen time and depression was not uniform across the sample: it varied according to the level of smartphone addiction. Specifically, at relatively low levels of addiction, greater screen time was associated with fewer depressive symptoms, while at relatively high levels of addiction, greater screen time was associated with greater depressive symptoms. This crossover pattern is a sophisticated statistical finding that suggests the psychological context of smartphone use — the pattern, not just the duration — fundamentally shapes its mental health consequences.

Interpreting this interaction requires care. One possibility is that at low addiction levels, heavy screen time may reflect productive or socially enriching use — studying, connecting with friends, engaging with content that supports wellbeing — and thus tracks with better mood. At high addiction levels, however, heavy screen time may reflect compulsive, distress-driven use that reinforces depressive patterns. Another possibility is that students with depression may become more addicted to their phones as a form of escape, and the addiction pattern itself is what carries the depressive signal. The study cannot disentangle these possibilities, and the authors emphasize that longitudinal research is needed to clarify the temporal direction of the associations. Notably, no significant interaction was observed for anxiety symptoms, with a regression coefficient of 0.002 and a 95 percent confidence interval of −0.014 to 0.017, at p equal to 0.833 — suggesting that the addiction-moderated relationship is specific to depression rather than a general phenomenon across mental health outcomes.

The study was conducted with ethical approval from the Institutional Review Board of the Lebanese American University, in accordance with the principles of the Declaration of Helsinki. All participants provided informed consent electronically before completing an anonymous questionnaire, and no personally identifiable information was collected. The research did not receive any specific grant from funding agencies, and the authors declare no competing interests. The open-access article is published under a Creative Commons license, making the full findings freely available to researchers, clinicians, and the public worldwide.

The broader implications of the study extend well beyond Lebanon. The finding that smartphone addiction and screen time show distinct associations with different mental health outcomes — depression tracking with the addiction pattern, anxiety tracking with the raw duration — suggests that researchers and clinicians need to consider both the duration and the pattern of smartphone use when examining its relationship with mental health. A student who spends six hours a day on their phone but uses it productively may face different risks than a student who spends the same six hours in a compulsive, addiction-driven pattern. The crossover interaction for depressive symptoms adds a layer of nuance that could reshape how future studies are designed, pushing the field toward more sophisticated models that treat smartphone use as a multidimensional behavior rather than a single exposure. As debates about digital wellbeing intensify globally, this Lebanese study offers a technically rigorous reminder that the story of smartphones and mental health is not a simple tale of hours spent, but a complex interplay between how long we look and how our relationship with the device shapes what we feel.

Subject of Research: Psychiatry

Article Title: Patterns of screen time and smartphone addiction and their relation to mental health among university students in Lebanon: a cross-sectional study

Article References: Badr, S. C., Bedran, J., Kamel, J., Kmeid, R., Daccache, R., Assaf, R., Al Hammoud, M., Safwan, J., Iskandar, K., & Cherfane, M. (2026). Patterns of screen time and smartphone addiction and their relation to mental health among university students in Lebanon: a cross-sectional study. BMC Psychiatry. https://doi.org/10.1186/s12888-026-08770-y

Image Credits: AI Generated

DOI: 10.1186/s12888-026-08770-y

Keywords: smartphone addiction, screen time, depression, anxiety, university students, Lebanon, mental health, BMC Psychiatry, Patterns, screen, time, smartphone