The Impact of Nomophobia Levels on Sleep Quality Among Medical Students

Technical Summary: The Impact of Nomophobia Levels on Sleep Quality Among Medical Students

Problem Statement
The study addresses the growing prevalence of nomophobia (the fear of being without a mobile phone) and its potential detrimental effects on sleep quality among medical students. While smartphones are integral to modern education and communication, their uncontrolled use is linked to attention deficits, psychological issues, and disrupted circadian rhythms due to blue light exposure. The authors posit that the anxiety associated with smartphone deprivation may severely compromise sleep hygiene, leading to fatigue and impaired concentration, yet the specific relationship between nomophobia levels and sleep profiles in the high-stress environment of medical education requires further investigation.

Methodology
This prospective, descriptive, and cross-sectional study was conducted at Muğla Sıtkı Koçman University Faculty of Medicine in Türkiye.

• Participants: A stratified random sample of 307 voluntary medical students (Grades 1–6) was selected from a total population of 1,338. Inclusion criteria required participants to be at least 18 years old, active smartphone users, and to complete the survey fully. Exclusion criteria included diagnosed sleep disorders or regular use of medications/illnesses affecting sleep patterns.
• Data Collection: Data were gathered digitally via Google Forms over two months using three instruments:
  1. Sociodemographic Form: Assessed age, gender, grade, lifestyle habits (smoking, alcohol), living arrangements, and smartphone usage patterns.
  2. Pittsburgh Sleep Quality Index (PSQI): A validated Turkish scale evaluating sleep quality over the past month across seven components (subjective quality, latency, duration, efficiency, disturbances, medication use, daytime dysfunction). A global score >5 indicates "poor sleep quality."
  3. Nomophobia Questionnaire (NMP-Q): A 20-item scale measuring anxiety levels regarding smartphone deprivation, categorized into four subscales: inability to access information, losing connectedness, inability to communicate, and giving up convenience.
• Statistical Analysis: Data were analyzed using IBM SPSS 27.0. Descriptive statistics, independent t-tests, ANOVA, correlation analyses (Spearman), and multivariable binary logistic/multiple linear regression models were employed to identify risk factors and relationships. Significance was set at p < 0.05.

Key Results

• Prevalence: Nomophobia was detected in 99.3% of participants, with 47.2% exhibiting moderate levels and 13.7% severe levels. Only 0.7% showed no nomophobia. Regarding sleep, 68.1% of students were classified as having poor sleep quality.
• Demographic and Behavioral Risk Factors:
  • Gender: Female students had significantly higher total nomophobia scores and poorer sleep quality (PSQI) compared to males.
  • Smoking: Smokers exhibited significantly worse sleep quality (PSQI mean 8.0 vs. 7.0) and a 2.18 times higher risk of poor sleep quality in regression analysis. Paradoxically, smokers had lower total nomophobia scores than non-smokers.
  • Smartphone Usage: Longer daily smartphone usage duration was a significant risk factor for poor sleep quality (OR=1.172 per unit increase) and correlated positively with total nomophobia scores.
  • Academic Year: Second-year students reported significantly higher anxiety regarding "inability to access information" and "losing connectedness" compared to other years.
• Sleep Characteristics: The median daily smartphone usage was 5.0 hours. While the mean actual sleep duration was 7.0 hours, 94.4% of students rated their subjective sleep quality as "fairly bad" or "very bad." The most common sleep disturbance was "waking up in the middle of the night or early morning" (35.8% reported this 3+ times/week).
• Correlation and Regression Findings:
  • No statistically significant correlation was found between the Total Nomophobia Score and the Total PSQI Score.
  • Multivariate logistic regression confirmed that gender, smoking status, and daily phone usage duration were independent predictors of poor sleep quality, but the Total Nomophobia Score did not have an independent predictive effect on sleep quality deterioration (p=0.376).
  • However, a detailed analysis revealed that all individual subscales of nomophobia were significantly associated with the "Sleep Disturbances" component of the PSQI. Specifically, the "giving up convenience" subscale showed a weak but significant correlation with the total PSQI score.

Significance and Claims
The authors claim that while nomophobia is nearly ubiquitous among medical students (99.3%), its impact on sleep is complex and indirect rather than linear. The study concludes that nomophobia does not necessarily shorten total sleep duration but severely disrupts sleep continuity and quality, manifesting as nocturnal awakenings and sleep fragmentation.

The paper emphasizes that the anxiety of being unreachable or disconnected drives specific sleep disturbances, particularly "waking up in the middle of the night." The authors argue that the high prevalence of poor sleep quality (68.1%) combined with the near-universal presence of nomophobia necessitates institutional interventions, such as "digital detox" programs and sleep hygiene education, rather than viewing these issues as isolated behavioral traits. The study highlights that medical students often normalize sleep deprivation as an inevitable cost of their training, rarely seeking pharmacological help despite significant daytime dysfunction.

Limitations
The authors acknowledge limitations including the single-center sample (restricting generalizability), reliance on self-reported data (potential recall and social desirability bias), and the relatively low explanatory power of the regression model (Nagelkerke R² = 0.051), suggesting other unmeasured factors influence sleep quality. They suggest future research should utilize longitudinal designs and objective physiological measurements (e.g., actigraphy, screen time logs).