Risk and Promotive Factors of Social and Emotional Wellbeing for University Students: Adversity and Resilience

Abstract

The prevalence of depression in university students is increasing and attributable to academic, financial and social stressors. Other factors that place students at a higher risk of experiencing depression include adversity in childhood and present. However, there are crucial promotive factors that support students and induce resilience, such as social support, hope and coping strategies. Despite the growing number of studies focusing on risk and promotive factors among students, there is a lack of a multidimensional approach to these factors. Thus, three studies were conducted to better understand such factors in university students by implementing a cross sectional design using online surveys. Study one showed that childhood adversity current adversity and lack of sources of social support were significant predictors of depression, poor academic performance, and a low quality of life. In study two, dissociation had significant positive relationships with current adversity and depression as well as a significant negative relationship with academic performance. Study three revealed that hope, coping strategies, social support from significant others, university belonging and university support were significant predictors of resilience, while hope, university support, and university belonging were the only significant predictors of academic performance. Further, lack of hope, coping strategies, social support from significant others and university belonging were significant predictors of depressive symptoms. From these results, the present thesis contributed to the scientific knowledge in the literature by tackling multidimensional risk and promotive factors for the wellbeing of university students that previous studies may have failed to capture. The results can help universities in designing a holistic preventive and intervention programmes for students. Future research might focus on longitudinal approach to reach deeper understanding of these variables.