An exploration into the factors impacting the maintenance of depression in UK university students

This thesis sought to explore and elucidate the understanding of the 'every day' depression experience in university students and to, more precisely, investigate the various factors that impact depression maintenance. The work done in this project sought to lay the foundation for a more complex yet comprehensive understanding of how depression arises, is maintained, and is accentuated by further education and day-to-day life. In Chapter 1, I provide an overview of the existing understanding of depression. More specifically, I explain the role of maintenance cycles and the concept of 'depression maintenance'. This is examined as both a 'problem' in that it perpetuates many depressive symptoms and the depression mode, but also as a 'solution' and area for targetable interventions. In Chapter 2, using depression maintenance as a guide, I review how emotion (namely, sadness) works to perpetuate depressive symptoms. Different states of sadness (originally derived from an understanding of music-induced sadness) are uncovered and confirmed through a factor analysis. Two sad states were strongly associated with different aspects of depressive symptomology, while one was strongly associated with positive emotion regulation. In Chapter 3, I explore how depression maintenance is affected by the environment through everyday stressors and how this impacts our cognition. Phone use was found to strongly predict increased depressive symptoms. The two follow-up studies investigated cognitive biases. In the first cognitive study, traditional paradigms were used to investigate the presence of cognitive biases in depression. A path model was designed to capture how these biases interconnect and may cause detriments to cognitive processing in those with more depressive symptoms. However, very few pathways were found to be significant, with emotion dysregulation (a much higher level of processing) was found to be the main driving force behind depression maintenance in this sample). In the second cognitive study, cognitive bias modification paradigms were used. Here, no manipulation checks were significant and there was no impact on depression versus the control group. This was possibly due to the sub-clinical nature of the university student sample, or due to the study being underpowered. Finally, in Chapter 4, education was explored as an environmental stressor for students. This identified the key role played by adaptability and a sense of belonging (coming from educational support, affiliation, and faculty support). This then culminated in a final study bringing all key aspects together to explore 'student mental health profiles' through use of latent profile analysis. Emotion, phone-use, adaptability, and belonging measures were used to determine five student profiles. Depression was used as a distal outcome and this revealed important connections between each profile, its characteristics, and its link to depression. A key finding here was that at the high-end of depression, adaptability and university belonging appeared to serve as a protective factor, but this was not seen at lower levels of depression. This research could be used to lay the foundation for specific targeting of interventions at higher education institutions. Rather than simply increasing the number of interventions and support services on offer, they can instead by used more effectively.