The administrative healthcare data used in this study comes from two primary sources, the Finnish Institute for Health and Welfare and the Social Insurance Institution of Finland. Since these data measure treatment use, a few words on mental healthcare in Finland are in order. Finland is, with some reservations, part of the Nordic welfare state regime (Bambra et al., 2009). The Finnish public healthcare system consists of primary healthcare, which is organised by municipalities, and specialised healthcare organised by larger hospital districts.4 The public sector is supplemented by private healthcare and occupational healthcare, as well as various third sector agents providing health and social services (Teperi et al., 2009). Each permanent resident is entitled to public healthcare, which in principle is free-of-charge, although small out-of-pocket payments may apply (EU-healthcare.fi, 2022;
Teperi et al., 2009). Outpatient mental health services are free of charge but there are small daily fees in inpatient care (EU-healthcare.fi, 2022).
Patients come into contact with healthcare professionals first in the primary healthcare, either public, private or within the occupational healthcare system. After the initial assessment and treatment in the primary sector, patients may be referred to specialised healthcare, including specialised psychiatric services. Regarding self-harm and acute mental health crises, the
4 This organisational structure was in place until the end of 2022. From 1 January 2023, organisation
Finnish context
first contact is often in emergency departments, which are usually located in hospitals. From emergency rooms, individuals are referred to follow-up treatment, when deemed necessary (Keskimäki et al., 2019).
Mental health services are usually divided into different departments for child, youth and adult psychiatry. Different age limits apply depending on the hospital districts: for instance, in the Helsinki and Uusimaa (HUS) hospital district the age limit for adolescent psychiatry is 13–17 (HUS, 2022), but higher upper limit ages ranging up to 22 are also used in other districts (Korkeila, 2021). Overall, there has been a shift from inpatient mental healthcare to outpatient services during the recent four decades (Korkeila, 2021). Psychiatric treatment is usually voluntary, however, in some instances involuntary care and other coercive measures are possible (Kaltiala-Heino, 2010; Siponen et al., 2007, 2012). These conditions are strict, but one of the reasons for involuntary care is suicidality (Mental Health Act, 1990).
During the 2010s, there has been a general increase both in prevalence of psychiatric inpatient treatment and rates of psychiatric hospital episodes among 13–17-year-old girls (Figure 2), although at the same time the number of inpatient days has steadily decreased, indicating an increase in shorter inpatient episodes. Similar trends can also be observed among 18–24-year- old women in the late 2010s, but the prevalence and rates of inpatient treatment are lower in this age group. Among boys and young men, trends in prevalence and rates of inpatient treatment episodes have remained similar between 2006 and 2020, but the number of days has decreased, indicating that the average length of inpatient stays has become shorter.
In addition to low-cost mental health care services, prescribed psychotropic medication purchases are reimbursed in Finland. Depending on medication, the reimbursed sum is either 40, 65 or 100% of the purchase price (Social Insurance Institution of Finland, 2022c). Most antidepressants and
medications used to treat anxiety disorders are in the lowest reimbursement category, but antipsychotics are fully reimbursed (Social Insurance
Institution of Finland, 2022b). In addition, there is a maximum annual limit of out-of-pocket costs, around 600€/year (Social Insurance Institution of Finland, 2022c). Finally, medication expenses and healthcare user fees may be covered by social assistance receipt (Social Insurance Institution of Finland, 2022a). There has been an increasing trend of antidepressant use during the 2010s, both among 13–17-year-olds and 18–24-year-olds, but mostly this increase has occurred among girls (Figure 2). Antidepressant use is more common among 18–24-year-old girls than 13–17-year-olds, whereas the opposite was the case in inpatient treatment (Figure 2).
Despite the principles of universalism, the Finnish healthcare system has been criticised of being considerably unequal in terms of access to healthcare (OECD, 2019). The major disparities are in unmet need of treatment and the
first contact with healthcare (Blomgren & Virta, 2020; OECD, 2019).
Individuals in higher SEPs use more specialised services, but they also have more opportunities to access primary healthcare due to higher use of private and occupational healthcare (Blomgren & Virta, 2020). Nevertheless, register-based research on the population level usually documents higher levels of medication use and hospital-level treatment among individuals who have a lower SEP (Junna et al., 2019; Paananen, Ristikari, et al., 2013;
Paananen, Ristikari, et al., 2013; Suokas et al., 2020). These findings might relate to differences in the overall prevalence of health problems across socioeconomic strata since in many instances healthcare need is hard to capture with administrative data.
Figure 2 Trends in antidepressant reimbursements and psychiatric inpatient treatment among Finnish adolescents and young adults in 2006–2021. Source: Sotkanet.fi 2023a, 2023b.
Aims of the study
6 AIMS OF THE STUDY
This thesis consists of four individual sub-studies, which all aimed to deepen the understanding on the associations between adverse childhood
experiences, parental socioeconomic resources and hospital-presenting self- harm in adolescence and young adulthood. The general aim was to probe into more fine-grained features of these already well-known associations by exploiting population-level longitudinal data. All the sub-studies used rich administrative register data, which included multiple observations per individual. These observations were collected annually across childhood, adolescence and young adulthood. The administrative data contained date- level data on event timing and allowed using diagnoses rather than self- report to measure self-harm and other health-related conditions.
The main associations studied are summarised in Figure 3, each sub-study in a separate panel. For simplicity, not every association is drawn. Sub-study I (Figure 1, panel A) examined the associations between adverse childhood experiences related to biological parents and self-harm in adolescence and young adulthood. Treated parental psychiatric disorders and substance use disorders, parental crime related to substance use, other parental crime, and parental hospital episodes due to violent victimisation or self-harm were used to predict hospital-presenting episodes of self-harm in adolescence and young adulthood in a survival analysis framework. The main aims of the sub- study were to examine if maternal and paternal risk markers have different associations with offspring self-harm and to explore if income acts as an effect moderator in these associations. In addition, accumulation of adverse experiences was assessed.
Even though socioeconomic risk markers of self-harm have been studied to a considerable extent, the underlying mechanisms through which the
socioeconomic gradient in self-harm emerges remain far less studied. The main objective of sub-study II (Figure 1, panel B) was to scrutinise the mediating mechanisms in the association between low childhood income and self-harm in young adulthood. The study used a counterfactual causal mediation framework and examined multiple adolescent risk markers as mediating mechanisms. The mediators assessed included diagnosed psychiatric disorders, registered substance misuse, violent crime, violent victimisation, previous hospital-presenting self-harm, grade point average, not being in education, employment or training, and out-of-home
placements. Confounding and effect moderation by adverse childhood experiences were also explored.
While sub-studies I and II focused on population-level associations, sub- study III (Figure 1, panel C) zoomed in to those adolescents and young adults
who had self-harmed between age 16–21, thus creating an artificial population-based clinical population encompassing all hospital-level facilities in Finland. The aim of the study was to explore socioeconomic differences in psychiatric treatment use before and after hospital-presenting self-harm, which had not been previously studied. The analysis examined differences by parental education in trajectories of treatment prevalence the use of various treatment types.
Finally, sub-study IV (Figure 1, panel D) changed the focus from self-harm as an outcome into parental outcomes of offspring self-harm, which have been previously less studied. In this sub-study, the studied population were the parents of the adolescents and young adults who self-harmed at age 13–19, and the outcome was parental psychiatric treatment before and after their child’s episode of hospital-presenting self-harm. In a similar vein to sub- study III, trajectories of psychiatric treatment prevalence were examined, and differences by parental socioeconomic resources investigated. In addition, comparisons to other potentially stressful events happening to the children were also conducted. Thus, in a sense, sub-study IV circled back to the earlier sub-studies, where parental psychiatric treatment was used as a predictor of offspring hospital-presenting self-harm.
The sub-studies in this thesis aimed to describe associations between life events using observational data. Although there are assumptions of a causal nature, meaning that the directions and sequences between different events are assumed to have a certain ordering, the results are not compatible with strict causal inference due to unobserved confounding. For causal inference, randomised controlled trials are the most robust study designs (Hernán &
Robins, 2020), but these are not possible for this type of social
epidemiological study as it would be highly unethical to assign adverse childhood experiences to certain children, for instance. Quasi-experimental study designs based on, e.g., fixed effects designs, are closer to causal
inference, but such studies rely on information derived only from individuals or sibling pairs discrepant on exposure and outcome variables (Allison, 2009). Furthermore, fixed-effects designs do not allow for estimating effects of variables that are constant over time (Allison, 2009). For these reasons, comparisons between population sub-groups are challenging or impossible with these designs. Since this study was interested precisely in population sub-group differences, and since conditioning on discrepant exposures and outcomes within individuals or siblings in the case of considerably rare variables would result in rather small and selected samples, fixed-effects designs were not used during the conduct of this study.
Aims of the study
Figure 3 Simplified framework of the associations examined in the sub-studies:
A) The association of adverse childhood experiences (ACE) with self-harm (SH), and moderating effects of childhood income (I)
B) The direct effect of income (I) on self-harm, and mediated effects through proximal adolescent factors (M), adjusting for confounding by ACE
C) The moderating effects of parental education (PE) on the temporal trajectory of psychiatric treatment before and after self-harm among the adolescents and young adults
D) The moderating effects of parental socioeconomic resources (SEP) on the temporal trajectory of parental psychiatric treatment before and after their child’s self-harm.