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Depression is a most commonly-diagnosed type of mental health disease among African American college students, and the prevalence rate is higher compared to their White counterparts. Literature has reported significant relationships of depression with psycho-social-economic factors, including age, gender, income, distress, and resilience. Recent studies have revealed depression is positively associated with Internet addiction as maladaptive Internet use that interferes with daily life. Despite such burdens facing African American students, their utilization of mental health services has been consistently low. Thus, this study aimed to (1) explore mental health help-seeking behaviors among African American college students and (2) examine factors of depression among them.
Methods Data were collected from a cross-sectional survey using a purposive sampling. A total of 323 undergraduate and graduate students in a Historically Black University participated in this study. Their mean age was 23.4 (SD=6.54). Most were female (81%), undergraduate students (72%), and employed (60%) with an annual household income below $25,500 (53%).
Primary measures include the Brief Resilience Scale, the Psychological Distress Scale, Young’s Internet Addiction Test (IAT), and the CES-D, and Internet use time. Control variables include gender, income, and age. Structural Equation Modeling (SEM) was used to explore the mediating role of Internet addiction between resilience and psychological distress, and depression. The hypothesis model was examined first and then the alternative model was analyzed after removing statistically non-significant paths.
Results Descriptive statistics showed 7% (n=24) were identified as maladaptive Internet users possibly experiencing troubles in daily activities or relationships. 28% (n=88) reported their willingness of utilizing mental health services for their mental health issues specifically associated with Internet use, while only 21% (n=5) of the maladaptive Internet users reported positive attitudes toward mental health service utilization.
The test of the measurement model revealed a satisfactory fit (chi-squared=68.966, df=48, p<.05, CFI=.992, IFI=.975, TLI=.987, RMSEA=.037); the test of the hypothesis model also showed a satisfactory fit (chi-squared=156.236, df=90, p<.001, CFI=.975, IFI=.975, TLI=.957). Model fit of the alternative model remained good (Δchi-squared=2.809, Δdf=6, p>.05) after model re-specification in which six paths were deleted.
SEM results showed IAT scores have a negative association with Internet use time for essential purposes (β=-.186; p<.01) and resilience scores (β=-.246; p<.001), respectively. SEM results revealed that IAT scores have a positive association with Internet use time for recreational purposes (β=.248; p<.001), psychological distress scores (β=.139; p<.05), and depression (β=.138; p<.01), respectively. Finally, the results showed the direct effect of resilience (β=-.331; p<.001) and psychological distress (β=.581; p<.001), respectively, on depression.
Conclusion/Implications
The findings provide implications for social work practice and interventions for African American college students. Since Internet addiction mediates the link between psychological distress and depression, intake interviews with depressed African American students especially concomitantly with maladaptive Internet use should assess both psychological distress and Internet addiction levels. Practitioners need to integrate treatment plans for such students with strategies for enhancing their resilience. Lastly, given the mental health help-seeking behaviors, it is critical that interventions for African American college students focus on reducing cultural barriers to mental health services.