Sürdürülebilir Kalkınma Amaçları

• 2
• 1

• MakaleAçık Erişim2026/r/kostu/10822
  Artificial Intelligence Addiction, Technostress, and Work-Life Balance Among Academics: An Employee Health Perspective

  Tozak, Fatoş; Efetürk, Nida; Asik, Raife

  Aim: This study aims to examine the relationships between artificial intelligence addiction tendencies, technostress levels, and work-life balance among academics within the framework employee health.Method: This study was designed using a correlational survey model within the framework of quantitative research methods. The population of the study consisted of academics working at universities in Türkiye. Data were collected using a sociodemographic information form, the Artificial Intelligence Addiction Scale, the Technostress Scale, and the Work-Life Balance Scale. Statistical analyses were performed using SPSS for Windows 25.0 software.Results: The findings indicated that the levels of artificial intelligence addiction (11.12±4.17) and technostress (56.13±12.85) among the participating academics (n=450) were moderate, with techno-overload identified as the most prominent subdimension of technostress. The analyses revealed positive and statistically significant correlations among the variables (p<0.01). Regression analysis demonstrated that both artificial intelligence addiction and technostress significantly and positively predicted work-life balance (R²=0.315). From a sociodemographic perspective, younger academics (research assistants) exhibited higher levels of artificial intelligence addiction and work-life balance compared to professors. Additionally, a heavy teaching load of 16 hours or more per week was found to significantly increase the technostress level.Conclusion: Artificial intelligence addiction and technostress are thought to be viewed not as destabilizing risk factors for academics but rather as a “functional adaptation tool” used to manage academic workload. While this resulting “good stress state” positively supports work-life balance, implementing human-centered digital policies at the corporate level is necessary to prevent long-term cognitive fatigue.

  • 
  • 
  İncele
• MakaleAçık Erişim2025/r/kostu/10904
  Comparison of Fatigue Severity in Individuals with Vestibular Hypofunction

  Kılıç, Gamze; Gülçelik, Gönül Ertunç; Aktürk, Adem; Sever, Ebru

  Aim: The aim is to compare fatigue severity in patients with unilateral and bilateral vestibular hypofunction. Method: Patients with complaints of dizziness and balance were included in the study. The degree and direction of hypofunction of the patients were determined with videonystagmography test. Numerical Pain Scale was used to evaluate fatigue severity. Fatigue severity in patients with unilateral and bilateral vestibular hypofunction (VH) was compared. Results: 100 patients with a mean age of 49.25±14.67 years were included in the study. It was observed that 37% of these patients had Right VH, 30% had Left VH and 33% had Bilateral VH. According to the hypofunction table, the fatigue severity of the groups was 6.57±1.96 in Right VH, 6.79±1.34 in Left VH and 7.51±1.44 in Bilateral VH. When fatigue severity was compared between the groups, no statistical superiority was found (p≥0.05). Conclusion: There is no difference between the fatigue levels in Unilateral and Bilateral VH patients.

  • 
  İncele