Economics of Youth Mental Health:essays on Juvenile Delinquency, Education and Policy

Mental health problems largely originate during youth and affect one out of five individuals worldwide. The corresponding individual disease burden lead to significant societal costs, as youth mental health problems have a long-lasting impact over the life-cycle. Through an economic lens youth mental health can be seen as a pivotal element of human capital, associated with educational progress and labour market participation, required to produce economic value. Despite the relevance of youth mental health from both a health and economic perspective, there is still an imperative need for research to reduce the burden of mental health for future generations. In this thesis we have focused on one piece of the puzzle, i.e. the lack of data-driven evaluation strategies to identify (cost-)effective youth mental health interventions. One of the challenges is the fact that in many cases, experiments (i.e., randomized controlled trials) remain difficult or impossible to implement, for financial, political, or ethical reasons, or because the population of interest is too small. Therefore, I demonstrate in this thesis that observational data could be used to provide crucial insights for clinical and policy decision-making in order to make more optimal budget allocations. We were able to identify the role of policies in youth mental health trajectories (chapter 2), the effect of mental health interventions on societal outcomes (chapter 3), the relationship between monitoring compliance to compulsory education and student’s test scores (chapter 4), and the long-run return to government expenditures in special education (chapter 5)

The persistence of child and adolescence mental healthcare:results from registry data

Background: Previous studies on the persistence of child and adolescent mental healthcare do not consider the role of time-invariant individual characteristics. Estimating persistence of healthcare using standard linear models yields biased estimates due to unobserved heterogeneity and the autoregressive structure of the model. This study provides estimates of the persistence of child and adolescent mental healthcare taking these statistical issues into account. Methods: We use registry data of more than 80,000 Dutch children and adolescents between 2000 and 2012 from the Psychiatric Case Registry Northern Netherlands (PCR-NN). In order to account for autocorrelation due to the presence of a lagged dependent variable and to distinguish between persistence caused by time-invariant individual characteristics and a direct care effect we use difference GMM-IV estimation. In further analyses we assess the robustness of our results to policy reforms, different definitions of care and diagnosis decomposition. Results: All estimation results for the direct care effect (true state-dependence) show a positive coefficient smaller than unity with a main effect of 0.215 (p<0.01), which indicates that the process is stable. Persistence of care is found to be 0.065 (p<0.05) higher for females. Additionally, the majority of persistence of care appears to be associated with time-invariant characteristics. Further analyses indicate that (1) results are robust to different definitions of care and (2) persistence of care does not differ significantly across subgroups. Conclusions: The results indicate that the majority of mental healthcare persistence for children and adolescents is due to time-invariant individuals characteristics. Additionally, we find that in the absence of further shocks a sudden increase of 10 care contacts in the present year is associated with an average of less than 3 additional care contacts at some point in the future. This result provides essential information about the necessity of budget increases for future years in the case of exogenous increases in healthcare use

Association between socioeconomic status and self-reported, tested and diagnosed COVID-19 status during the first wave in the Northern Netherlands:a general population-based cohort from 49 474 adults

Objectives Studies in clinical settings showed a potential relationship between socioeconomic status (SES) and lifestyle factors with COVID-19, but it is still unknown whether this holds in the general population. In this study, we investigated the associations of SES with self-reported, tested and diagnosed COVID-19 status in the general population. Design, setting, participants and outcome measures Participants were 49 474 men and women (46±12 years) residing in the Northern Netherlands from the Lifelines cohort study. SES indicators and lifestyle factors (i.e., smoking status, physical activity, alcohol intake, diet quality, sleep time and TV watching time) were assessed by questionnaire from the Lifelines Biobank. Self-reported, tested and diagnosed COVID-19 status was obtained from the Lifelines COVID-19 questionnaire. Results There were 4711 participants who self-reported having had a COVID-19 infection, 2883 participants tested for COVID-19, and 123 positive cases were diagnosed in this study population. After adjustment for age, sex, lifestyle factors, body mass index and ethnicity, we found that participants with low education or low income were less likely to self-report a COVID-19 infection (OR [95% CI]: low education 0.78 [0.71 to 0.86]; low income 0.86 [0.79 to 0.93]) and be tested for COVID-19 (OR [95% CI]: low education 0.58 [0.52 to 0.66]; low income 0.86 [0.78 to 0.95]) compared with high education or high income groups, respectively. Conclusion Our findings suggest that the low SES group was the most vulnerable population to self-reported and tested COVID-19 status in the general population.</p

Centralising acute stroke care within clinical practice in the Netherlands:lower bounds of the causal impact

Background: Authors in previous studies demonstrated that centralising acute stroke care is associated with an increased chance of timely Intra-Venous Thrombolysis (IVT) and lower costs compared to care at community hospitals. In this study we estimated the lower bound of the causal impact of centralising IVT on health and cost outcomes within clinical practice in the Northern Netherlands. Methods: We used observational data from 267 and 780 patients in a centralised and decentralised system, respectively. The original dataset was linked to the hospital information systems. Literature on healthcare costs and Quality of Life (QoL) values up to 3 months post-stroke was searched to complete the input. We used Synthetic Control Methods (SCM) to counter selection bias. Differences in SCM outcomes included 95% Confidence Intervals (CI). To deal with unobserved heterogeneity we focused on recently developed methods to obtain the lower bounds of the causal impact. Results: Using SCM to assess centralising acute stroke 3 months post-stroke revealed healthcare savings of $US 1735 (CI, 505 to 2966) while gaining 0.03 (CI, − 0.01 to 0.73) QoL per patient. The corresponding lower bounds of the causal impact are$US 1581 and 0.01. The dominant effect remained stable in the deterministic sensitivity analyses with $US 1360 (CI, 476 to 2244) as the most conservative estimate. Conclusions: In this study we showed that a centralised system for acute stroke care appeared both cost-saving and yielded better health outcomes. The results are highly relevant for policy makers, as this is the first study to address the issues of selection and unobserved heterogeneity in the evaluation of centralising acute stroke care, hence presenting causal estimates for budget decisions