199 General Discussion additional treatment by the end of the first treatment course, but only by a slight difference to higher-income patients. These findings are the first to comprehensively and in-depth answer the research question above through rich patient record data that captures the whole treatment pathway and covers a nationwide patient population. We concluded that different or concurrent diagnoses, severity at baseline, treatment minutes, or type of therapies did not explain disparities in the outcomes of improved functioning and additional treatment. Similarly, different or concurrent diagnoses and severity at baseline did not explain differences in treatment time. We also investigated whether our findings differed depending on the type of disorder: depression, anxiety and other disorders grouped. No differences were found, suggesting that the disparities observed result from standard features of the mental health treatment process rather than disorder-specific mechanisms. This is in line with findings from RCTs showing that disparities in treatment effectiveness are not therapy-specific, as these can be observed across several types of pharmacotherapy and psychotherapy approaches [1, 2]. Our findings are seminal in first showing that disparities in mental health outcomes are not explained by patient need or treatment intensity. They are, however, just a first step towards an actionable understanding of the reasons behind these disparities. Additional research is warranted to explore how the social environment and quality of care act as complementary mechanisms explaining the inequalities. While identifying the appropriate policy solutions to this challenge was not the scope of Chapter 2, our findings should raise concerns about initiatives that solely focus on improving access to treatment, without monitoring what happens next. They should also motivate further research and policy efforts to unlock the potential of (specialist) mental health treatment towards reducing the mental health gap instead of contributing to widening it. Using quasi-experimental methods to identify the effects of interventions, programs, and policies impacting the most vulnerable patient groups Interventions, programs and policies are often designed, implemented and evaluated focusing on their average effects on the population. Distributional effects are often disregarded. In this thesis, the focus was on identifying policies that impact mental health inequalities. For that, several aspects were taken into consideration. First, Chapters 3 to 5 cover domains that remain considerable challenges to contemporary mental health policy agendas. The transitional gap in mental health care (Chapter 3) in which lack of continuity in treatment can substantially impact the life trajectory of young adults [3, 4], but has been poorly addressed outside of the psychiatry field. The challenge of providing an optimal level of support to individuals with mental health conditions within the community (Chapter 4) which persists since the early deinstitutionalisation efforts in 1950s [5, 6]. The discussion on the appropriateness and over/underuse of pharmacological vs. psychological treatment approaches for depression (Chapter 5), which has recently been 7
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