Investigating Young Adult Cell Phone Use: Implications for Sleep Quality, Academic Performance, and Psychological Well-Being

The primary aim of this dissertation was to investigate the impact of cell phone use (CPU) on sleep quality, academic performance, and the psychological well-being (PWB) of young adults. This goal was achieved by 1) examining the relationship between undergraduate students' CPU and the sleep quality components, i.e., sleep latency and sleep difficulty, 2) examining the relationship between CPU and academic performance (GPA) of undergraduate students, and 3) investigating the relationship between CPU and PWB of undergraduate students. A sample of 525 undergraduate students (75.4% female) at Texas A&M University with an average age of 20.2 years, participated in the study during fall 2019. The data was collected using a validated self-reported quantitative questionnaire. Concerning the first research question, ordinal logistic analyses indicated that there were higher odds of sleep latency occurring with the exposure to the use of cell phones for unstructured leisure activities before sleep (CPU_BeforeBed) [Exp (B) = 1.091, p < 0.001]. Ordinal logistic analyses also indicated that there were higher odds of sleep difficulty occurring when undergraduate students assessed sexually explicit, violent, or emotionally charged media content using cell phones before sleep (CPU_Arousal) [Exp (B) = 1.065, p < 0.001]. As for my second research question, nonparametric correlational analysis showed that the frequency of CPU during a class/lecture, lab, and/or study session (CPU_Switch) was negatively correlated to the GPA of undergraduate students (Spearman rank-order correlation = 0.094, p < 0.05). However, the use of cell phones for self-regulated learning strategies (CPU_SRLBehavior) was unrelated to the academic performance of undergraduate students (Spearman rank-order correlation = 0.002, p = 0.961), as determined by nonparametric correlational analysis. Finally, for the third research question, there were higher odds of PWB occurring with both cell phone social media feeling (CPU_SMF) [Exp (B) = 1.798, p < 0.001] and cell phone social media response (CPU_SMR) [Exp (B) = 1.352, p < 0.01] of undergraduate students, as determined by ordinal logistic. Findings suggested that CPU_BeforeBed adversely affects the sleep latency of undergraduate students, more frequently that of females than males. Findings also suggested that CPU_Arousal affects the sleep difficulty of undergraduate students badly, with a higher occurrence of the impact in male undergraduate students. Switching between cell phones and academic tasks during a class/lecture, lab, and/or study session affects the academic performance of undergraduate students negatively, with no statistically significant difference in the occurrence of impact in male and female undergraduate students. However, using cell phones for self-regulated learning strategies does not affect academic performance. The use of cell phones for social media feelings and the use of cell phones for social media responses help undergraduate students improve their PWB, with no statistically significant difference in the occurrence of impact in male and female undergraduate students. CPU_BeforeBed predicted sleep latency and CPU_Arousal predicted the sleep difficulty of undergraduate students. CPU_Switch was not found as a significant predictor of the GPA of undergraduate students. Lastly, CPU_SMF strongly predicted the PWB of undergraduate students. However, CPU_SMR of undergraduate students did not predict their PWB