{"paper_id":"01b63366-a1dd-4dfe-b69a-67a75b8093d9","body_text":"The Effect of Special Educational Assistance In Early Childhood Education And Care On Psycho-Social Difficulties In Elementary School Children | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Research article The Effect of Special Educational Assistance In Early Childhood Education And Care On Psycho-Social Difficulties In Elementary School Children Guido Biele, Ratib Lekhal, Kristin R. Overgaard, Mari Vaage Wang, and 3 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-819337/v1 This work is licensed under a CC BY 4.0 License Status: Published Journal Publication published 24 Feb, 2022 Read the published version in Child and Adolescent Psychiatry and Mental Health → Version 1 posted 15 You are reading this latest preprint version Abstract Background: Three to seven percent of pre-schoolers have developmental problems or child psychiatric disorders. Randomized controlled trials (RCTs) indicate that interventions in early childhood education and care improve long-term outcomes of children from disadvantaged backgrounds. It is unknown if effects generalize beyond the well-structured context of RCTs and to children who may not have a disadvantaged background but have developmental problems or psychiatric disorders. Methods: We use data from the population-based Norwegian Mother, Father and Child Cohort Study, recruiting pregnant women from 1999 to 2009, with child follow-up from ages 6, 18, and 36 months to ages 5, 7, and 8 years. This sub-study included 2499 children with developmental problems or psychiatric disorders at age five. We investigate the effects of special educational assistance at age five on mother-reported internalizing, externalizing, and communication problems at age eight. We analyse bias due to treatment by indication with directed acyclic graphs, adjust for treatment predictors to reduce bias, and estimate effects in different patient groups and outcome domains with a hierarchical Bayesian model. Results: In the adjusted analysis, pre-schoolers with special educational assistance had on average by 0.1 (0.04-0.16) standardised mean deviation fewer psycho-social difficulties in elementary school. Mean effect sizes varied between groups and outcomes. Conclusion: We estimate positive effects of educational assistance during the transition from preschool to the school years. It should therefore be considered as an intervention for pre-schoolers with developmental or behaviour problems. More research with improved measurements of treatment and outcomes is needed to identify success factors for their implementation. Pediatrics Psychiatry ADHD ASD Language difficulties Behaviour problems early childhood education and care psycho-social intervention special education inattention hyperactivity/impulsivity oppositional behaviour mood anxiety and communication directed acyclic graph hierarchical Bayesian modelling Figures Figure 1 Figure 2 Figure 3 Introduction Between three and seven percent of pre-schoolers have developmental problems or child psychiatric disorders [ 1 , 2 ], which are an important risk factor for mental disorders in adulthood [ 3 ]. Efforts to promote healthy growth and development in children who struggle in the early years can accordingly improve children’s long-term life opportunities [ 4 ]. Indeed, a recent review reported overwhelmingly positive effects of non-cognitive skills on academic, psychosocial, cognitive and health outcomes [ 5 ], though effect sizes are typically not large. It has been hypothesized that the effect of interventions decreases as children grow older and therefore, investing resources later, at the age of school entry or beyond, may show less of an effect [6, but also see 7]. Interventions in early childhood are often described as an effective method to improve the long-term outcomes of children from disadvantaged backgrounds [ 6 ] or those with specific developmental or behavioural problems like attention deficit hyperactivity disorder, autism, or behaviour or language problems [ 9 ]. Interventions in early childhood education and care (ECEC) can be especially effective because in contrast to parental training programs, their implementation relies less on parents’ abilities or motivation, and on average 93% of three to five year old children in Organisation for Economic Co-operation and Development (OECD) countries are enrolled in ECEC [10, more then 95% or 5 year old children in Norway are in ECEC]. Randomized controlled trials (RCTs) reported clear effects of early interventions in ECEC for a horizon of up to nine months, for instance for language problems [ 11 ], children with ADHD or autism [ 12 ], and for teacher classroom management programs [ 13 ]. However, the effect sizes of such interventions are not generally large, and less is known about their effect when interventions are provided outside the well-structured context of RCTs. Even though RCTs are, due to their interval validity, the gold standard for estimating treatment effects, differences between study sample and target population and differences in treatment-implementation between study and regular care contexts, make a generalization of findings from RCT samples to populations of interest difficult [ 14 – 17 ]. Since RCTs often take place in a controlled setting, it may be difficult to replicate the results in other, less rigid settings. For instance, field professionals in ECEC institutions will draw on a much wider range of sources than formal experimental evidence in order to inform their actions. Thus, while evidence from RCTs is encouraging, it remains unclear how it generalizes to interventions in ECEC provided in regular care. Only a handful of studies examined the effects of special educational assistance (SEA) interventions in ECEC when they are implemented outside of RCTs. These studies used propensity scores to deal with the problematic internal validity in observational studies—due to treatment by indication—and found that children who received SEA in ECEC showed the same or worse outcomes compared children who did not receive SEA [ 18 , 19 ]. The Norwegian ECEC-system facilitates the investigation of SEA, because children who cannot fully benefit from standard education and care have the right to receive free SEA. Similar to other OECD countries [ 2 ], around 4.5% of pre-schoolers in Norwegian ECEC have impaired functioning, the most common impairment being language and communication difficulties, followed by psycho-social difficulties and behaviour problems [ 20 ]. Around 2.6% of pre-schoolers receive SEA, which is provided for several hours per week for individual children [ 20 ]. After stimulation of language development, social- and behaviour-training are the most frequent types of SEA provided. To date, no study has–to the best of our knowledge–examined the effect of SEA in ECEC on children’s psycho-social difficulties. Related studies on SEA in Norwegian schools report that students who received it have similar or slightly worse scholastic outcomes compared to those who did not receive it [21, 22, see also 23]. In sum, the few studies examining effects of SEA in ECEC outside the context of RCTs reported small negative, to no effects of SEA. Moreover, most studies focused on educational outcomes, such that the effect of SEA on the development of psycho-social difficulties remains largely unclear. Hence, this large-scale prospective cohort study adds to the existing literature by investigating how SEA in ECEC provided outside RCTs affects the psycho-social development of children with developmental or behavioural problems. Methods Participants The sample is a sub-sample of the Norwegian Mother, Father and Child Cohort Study (MoBa), a prospective population-based pregnancy cohort study conducted by the Norwegian Institute of Public Health [24, 25]. Participating mothers from all over Norway were recruited during routine ultrasound assessment in week 17 or 18 of their pregnancy in the period from 1999 to 2009. 41% of the invited women consented to participate. MoBa participants received questionnaires in gestational week 17 or 18, week 22 and week 30, at child’s age 6 and 18 months, 3, 5, and 8 years and onward. The study is still on-going. The reported analyses also use information from the Medical Birth Registry of Norway [26]. The study sample is comprised of children whose mothers indicated developmental or behaviour problems in MoBa’s age five years questionnaire, and for whom information about outcomes in the age eight years questionnaire are available. This study focuses on children with one or more of the following developmental or behavioural problems: Attention deficit hyperactivity disorder, language development, oppositional defiant or conduct disorder, autism spectrum disorder, and learning disabilities. Materials The current study used rating scales from MoBa questionnaires sent out at child ages five, and eight years. Exposure and inclusion criteria were based on responses in the five year questionnaire, whereas outcome measures were taken from the eight year questionnaire. The first, 1.5 and three year MoBa questionnaires and the Medical Birth Registry of Norway provided covariates. Exposure. To measure the provision of SEA, we relied on following question: “Does your child receive, or has received any extra resources in the kindergarten?” If mothers responded “Yes” to this question, they were additionally asked about the number of hours per week. SEA is provided to individual children, both inside and outside the context of regular preschool activities. Outcome variables. Outcome variables ( PSD 8 in Figure 2) were sum scores from different scales about psycho-social difficulties. Outcome dimensions were attentional, hyperactivity/impulsivity, and behavioural (ODD or CD) problems measured with the Parent Rating Scale for Disruptive Behaviour Disorders (RS-DBD, [27]), emotional problems measured with the Short Mood and Feelings Questionnaire (SMFQ, [28]) and the Screen for Child Anxiety Related Disorders (SCARED, [29]), and communication problems measured with the Children’s Communication Checklist-2 (CCC-2, [30]). Adjustment variables. Adjustment variables and those to control for loss to follow up were chosen based on the directed acyclic graph (DAG) shown in figure Figure 2. One important set of confounders includes children’s psycho-social difficulties at baseline, because these can be seen as causes of treatment and are related to later psycho-social difficulties. A number of scales in MoBa assessed psycho-social difficulties at age five and served as baseline measures ( PSD 5 in Figure 2). These included the Conners’ Parent Rating Scale-Revised, Short Form (CPRS-R (S), [31]), Child Behaviour Checklist (CBCL, [32]), the Ages and Stages Questionnaire (ASQ, [33]), and the Children’s Communication Checklist-2. While the baseline assessment considers the same mental health and development difficulties as the outcome, MoBa used different scales for five and age year olds. Additional variables used for adjustment or prediction of loss to follow-up included maternal age, education, ADHD symptoms measured with the Adult ADHD Self-Report Scale [34] at child age three and depressive symptoms measured with the SCL-5 [35] at child age five, parity, preterm birth, birth-month, hours special education per week, number of developmental of behaviour problems, and contact with rehabilitation services, Child and Adolescent Psychiatric Units, or Educational and Psychological Counseling Service at child age five years. Classification into groups with different developmental or behavioural problems To classify if and in which area a child had developmental or behavioural problem (DBP), we used MoBa questions about mental health problems at age five. Mothers were asked if their child “suffered, or is currently suffering from any of the following long-term illnesses or health problems.” In addition, mothers were asked if they had been in contact with a Child and Adolescent Psychiatric Unit or the Educational Psychology Counseling Services and if the health problem was confirmed by a professional. Only children for whom mothers reported a health problem and who indicated that the problem was evaluated by a mental health professional were included in the sample. Disorders or health problems for which MoBa’s age 5 questionnaire has questions included Epilepsy, Cerebral Palsy, impaired hearing, which were excluded from the current analysis, together with children for whom mothers indicated a chromosomal defect. MoBa also asked mothers about autism spectrum disorders (ASD), hyperactivity and attention problems (ADHD), language difficulties (Lang), and behavioural problems (Beh). Additional questions about learning disabilities (LD) were also used to identify cases of interest for this study. Each child was classified in one of the following DBP groups: 1. ASD, 2. LD, 3. ADHD & Beh & Lang, 4. ADHD & Beh, 5. ADHD & Lang, 6. ADHD, 7. Lang, 8. Beh. For some children, mothers indicated multiple DBP, in which case the child was assigned to the first group it fell into. If, for example, a mother indicated ASD, ADHD, and language problems, the child was assigned to the ASD group (details in supplementary materials and Table S1). The rational underlying this classification scheme was to use existing psychiatric diagnoses, and to classify children according to their most impairing problem because these have typically more severe and persistent effects on psycho-social development. Data analysis All analyses were performed using R [36]. The Bayesian hierarchical regression model was implemented with the brms package [37]. The analyses are described in more detail in the supplementary material, and analysis scripts are available at https://github.com/gbiele/SPS358. Bias from treatment by indication and loss to follow up. Estimation of treatment effects from observational data is difficult because treatment is not assigned randomly. Instead, individuals with more psycho-social difficulties at age five, who are also more likely to have psycho-social difficulties in the future, more likely receive treatment (treatment by indication). In addition, loss to follow up makes estimation of treatment effects difficult. Therefore, we used a directed acyclic graph [DAG, 38, see Figure 2] to explicate the assumed causal structure and to determine with which approach to deal with potential biases. Given this structural model, inverse probability of continued participation weighting was needed to reduce bias from loss to follow up [39], whereas adjustment for predictors of SEA was sufficient to control bias from treatment by indication. This means that we effectively estimated the effect of SEA on the change of psycho-social difficulties from preschool to elementary school. Estimation of the treatment effects. We used a Bayesian adjusted and weighted hierarchical ordinal regression to estimate effects of SEA [37, 40, 41]. A hierarchical regression induces partial pooling (shrinkage) of estimates, which reduces the variance of estimates [42] and controls the multiple comparison problem [43]. Importantly, when analysing related patient groups hierarchical regression results in more accurate association estimates then independent analysis of these groups [42]. We used an ordinal regression model, because the estimation of latent, normally distributed traits that underlie the rating-scale responses facilitates the presentation of results in terms of standardised mean differences (SMD). The reported results were obtained by pooling over the independent analyses of the 50 imputed data sets [44]. Consistent with recent recommendations to focus on estimation of effect sizes instead of significance testing [45, 46] we generally report means and the 90% credible intervals. Results The study sample includes 2499 participants (c.f., Figure 1). Thirty-three percent of the children in the sample received SEA. Table 1 describes the study sample. Figures S4 and S5 show that children with more severe problems (e.g. ASD) were more likely to receive SEA and also received SEA from better educated personnel. Table 1 Study sample Variable w/o SEA with SEA Total Special educational assistance (SEA) boy 1063 (63.8%) 586 (70.3%) 1649 (66%) girl 602 (36.2%) 248 (29.7%) 850 (34%) Hours 0 (0, 0) 4.76 (1, 6) 1.59 (0, 1) Developmental or behaviour problem (DBP) group ASD 11 (0.7%) 32 (3.8%) 43 (1.7%) LD 19 (1.1%) 63 (7.6%) 82 (3.3%) ADHD & Beh & Lang 12 (0.7%) 19 (2.3%) 31 (1.2%) ADHD & Lang 58 (3.5%) 85 (10.2%) 143 (5.7%) ADHD & Beh 108 (6.5%) 38 (4.6%) 146 (5.8%) ADHD 330 (19.8%) 71 (8.5%) 401 (16%) Lang 847 (50.9%) 486 (58.3%) 1333 (53.3%) Beh 280 (16.8%) 40 (4.8%) 320 (12.8%) Psycho-social difficulties (PSD) at child age five Attention 6.03 (2, 9) 6.98 (2, 10) 6.34 (2, 9) Hyperactivity 4.67 (3, 6) 4.68 (3, 6) 4.67 (3, 6) Externalizing (CBCL) 3.98 (2, 6) 3.73 (1, 6) 3.9 (2, 6) Internalizing (CBCL) 2.01 (0, 3) 2.16 (0, 3) 2.06 (0, 3) Communication (CCC) 3.93 (2, 6) 4.76 (3, 7) 4.21 (2, 6) Development (ASQ) 1.34 (0, 2) 2.31 (1, 3) 1.67 (0, 2) Psycho-social difficulties (PSD) at child age eight Attention (ATT, RS-DBD) 7.51 (4, 10) 8.3 (4, 12) 7.77 (4, 11) Hyperactivity (HYP, RS-DBD) 6.07 (2, 9) 5.77 (1, 8) 5.97 (2, 9) Oppositional (OPP, RS-DBD) 5.18 (2, 7) 4.44 (1, 6) 4.93 (2, 7) Mood (MOOD, SMFQ) 3.06 (1, 4) 2.96 (1, 4.75) 3.03 (1, 4) Anxiety (ANX, SCARED) 1.21 (0, 2) 1.22 (0, 2) 1.21 (0, 2) Communication (COMM, CCC) 7.75 (4, 11) 10.29 (5, 14) 8.6 (4, 12) Maternal characteristics Education (years) 14.01 (12, 15) 13.98 (12, 16) 14 (12, 15) Age (years) 30.52 (27, 34) 30.82 (28, 34) 30.62 (28, 34) ADHD (ADHD-RS) 7.38 (5, 10) 7.15 (5, 9) 7.3 (5, 10) Depression (SCL-5) 2.53 (0, 4) 2.43 (0, 3) 2.5 (0, 3) ASD = Autisum spectrum disorder, LD = Learning difficulties, Lang = Language problems, Beh = behaviour problems, SEA = special educational assistance. Abbreviations and original scales for PSD are given in parentheses (see methods section for full names). Numbers in parentheses are percent or first and third quartiles Inverse probability weights reduced the differences in mean values for covariates between participants followed up and those lost to follow up to less than 0.1 SMD (c.f. Figure S1; [47]). Cumulative distribution plots showed that weighting balanced the entire distributions of covariates (Figures S7 and S8). Effects of special educational assistance Consistent with the structural model shown in Figure 2, the analysis without adjustment showed that SEA at age five was associated with more psycho-social difficulties at age eight (c.f. Table S3 and Figure S7 ). Table S4 and Figures S9 and S10, S11, and S12 show coefficients of the adjusted regression model, which indicates that after adjustment for confounders SEA was associated with less psycho-social difficulties at age eight. Over all psycho-social outcomes and groups of developmental or behaviour problems the estimated average treatment effect (ATE) was a symptom reduction by 0.10 standardised mean deviations (SMD) (Credible Interval CI: 0.04, 0.16). Figure 3 shows that the 90% credible interval is for all groups above 0. The pairwise comparisons of all groups did not show clear differences in the estimated treatment effects between groups (c.f. Table S5 and Figure S14) Figure 3 and Table 2 also show estimated effect sizes stratified by outcomes and indicate that SEA had a positive effect on all measured psycho-social outcomes. While there were some differences in the effect size estimates for different outcomes, in particular smaller effects for anxiety and communication problems, pairwise comparisons did not show reliable differences between them (c.f. Table S6 and Figure S15). Effect size estimates did not vary substantially by the child sex (c.f. Figure S18). Table 2 Estimated average treatment effects (ATE) stratified by groups with different developmental and behavioural problems (rows) and psycho-social difficulties (columns) Group ATT HYP OPP MOOD ANX COMM Average ASD 0.08 (-0.06,0.21) 0.11 (-0.02,0.25) 0.11 (-0.02,0.25) 0.1 (-0.03,0.24) 0.08 (-0.06,0.21) 0.07 (-0.08,0.2) 0.09 (0, 0.18) LD 0.09 (-0.02,0.21) 0.11 (0,0.23) 0.11 (0,0.23) 0.11 (0,0.23) 0.1 (-0.01,0.22) 0.08 (-0.05,0.19) 0.1 (0.03, 0.18) ADHD & Beh & Lang 0.1 (-0.04,0.24) 0.11 (-0.03,0.26) 0.09 (-0.05,0.23) 0.11 (-0.03,0.25) 0.1 (-0.04,0.25) 0.08 (-0.07,0.22) 0.1 (0, 0.19) ADHD & Lang 0.07 (-0.05,0.18) 0.11 (-0.01,0.22) 0.13 (0.02,0.26) 0.1 (-0.01,0.21) 0.13 (0.02,0.26) 0.1 (-0.02,0.21) 0.11 (0.03, 0.18) ADHD & Beh 0.15 (0.03,0.29) 0.11 (-0.01,0.23) 0.11 (-0.01,0.24) 0.1 (-0.02,0.22) 0.11 (-0.01,0.23) 0.09 (-0.03,0.22) 0.11 (0.04, 0.19) ADHD 0.09 (-0.02,0.2) 0.12 (0.02,0.23) 0.14 (0.03,0.26) 0.09 (-0.03,0.19) 0.11 (0,0.23) 0.08 (-0.03,0.19) 0.11 (0.03, 0.18) Lang 0.1 (0.01,0.18) 0.15 (0.06,0.24) 0.15 (0.07,0.24) 0.1 (0.01,0.18) 0.06 (-0.03,0.15) 0.06 (-0.03,0.14) 0.1 (0.04, 0.16) Beh 0.09 (-0.03,0.2) 0.07 (-0.06,0.18) 0.11 (0,0.24) 0.06 (-0.07,0.17) 0.11 (0,0.23) 0.1 (-0.02,0.21) 0.09 (0.02, 0.16) Average 0.1 (0.01, 0.18) 0.15 (0.06, 0.24) 0.15 (0.07, 0.24) 0.1 (0.01, 0.18) 0.06 (-0.03, 0.15) 0.06 (-0.03, 0.14) ATEs are reported as standardised mean differences (SMD). Numbers are means (90% credible intervals). Discussion This research used observational data from a longitudinal population based cohort study to investigate the effect of special educational assistance (SEA) in ECEC on psycho-social difficulties of children with developmental or behaviour problems. We found that, after adjustment for treatment indicators, mothers of children who received SEA in kindergarten reported fewer psycho-social difficulties three years later, compared to mothers whose children did not receive SEA. While there was some variation in the extent of the positive effect of SEA between groups and different psycho-social difficulties, these differences were not reliably different from zero (c.f. Figures S14 and S15). Because the credible intervals for these differences are large compared to the magnitude of the estimated overall effect and the random effects standard deviations are clearly non-zero (S4), these results do not exclude the possibility of group differences. Instead, they might reflect difficulties in reliably measuring exposure, covariates, and outcomes based on parent reports only. Still, the available data were sufficient to reveal an overall positive effect of SEA. While the positive effect reported in this study is consistent with the results of randomized controlled trials [ 12 , 13 ] and with reports of the positive effects of preschool child care quality [ 48 ], it also stands in contrast to previous observational studies, which estimated no or a small negative “effects” of special education. This apparent contradiction can be due to a number of differences between the current and previous studies. We had estimates of pre-treatment difficulties, and could estimate effects of special education on the change of psycho-social difficulties. Moreover, we used adjustment for treatment predictors instead of propensity score weighting. Adjustment is the preferable approach if treatment-predictors are not colliders on a backdoor path from outcome to treatment and if the sample size is large enough to allow for inclusion of many of adjustment variables. Another important difference is that whereas previous studies focused on scholastic outcomes, we focused on the effect on psycho-social difficulties. This is a to date little examined but important outcome of SEA, because early psycho-social difficulties are associate with impaired functioning in adulthood [ 3 ]. Interestingly, the clear results of SEA on externalizing behaviour suggests that in addition to helping children with DBP, it can also benefit their families by reducing disruptive behaviour. The estimated effect size for the reduction of psycho-social difficulties is with on average 0.10 standardised mean difference small. In comparison, previous meta analysis about school– or ECEC–based interventions found effect sizes of between − .3 and 1.3 SMD for children with or at risk for ADHD [ 49 , 50 ] or SMD between 0.3 and 1.1 for children with autism [ 51 ]. Randomized trials of classroom management training for kindergarten teachers showed effect sizes similar to our results [Cohen’s d around 0.3 for high risk children at the nine-months follow up, 52]. A recent meta-analysis of reported effect sizes around 0.2–0.3 SMD from experimental manipulations of non-cognitive skill on psychosoial outcomes [ 5 ], and smaller effects around 0.1 SMD from non-experimental longitudinal studies. It is possible that the small effect sizes we estimated are, in addition to above mentioned measurement problems, due to the fact the SEA was often provided by personnel with limited training, especially for children with typically less severe problems (c.f. Figure S5). More generally, the decentralized organization of the Educational and Psychological Counselling Service is likely to lead to a large variation in the implementation of SEA [ 53 ]. MoBa did not collect more detailed data about SEA, which could help to elucidate when it is most effective. Another possible explanation is that the composition of the study sample, which over-represents well-educated families compared to the population [ 39 ], leads to an underestimation of the true effect size, because well-educated parents could reduce children’s psycho-social difficulties even without SEA [ 54 ]. While the current study showed that mothers report fewer psycho-social difficulties in elementary school when their children received SEA in ECEC, a causal interpretation of this result as reflecting an effect of SEA rests on a number of assumptions encoded in Fig. 2 . One un-testable assumption is that there are no unmeasured confounders that predict both which children receive SEA and their developmental pathway. Even though the reported analysis includes obvious confounders, other unobserved confounders like e.g. parental engagement could still account for some of the positive association of SEA and psycho-social development. However, because RCTs of SEA and similar interventions typically report positive effects, and thus confirm a causal role of SEA, it appears unlikely that the effects estimated in this study are primarily due to confounding. The current study has a number of limitations that should be addressed in future studies. Outcomes should be assessed through blinded raters or objective instruments and the quality and quantity of the treatments need to be assessed in greater detail. Moreover, it is important that study samples include participants with a higher a priori prevalence of metnal health problems (i.e. no over-representation of highly educated parents which characteriizez MoBa) and that care is taken to avoid loss to follow up. Better measurements and more representative samples will be useful to investigate reasons for the relatively small effects observed in the current study, and to identify criteria for effective interventions in ECEC. Conclusion Previous RCTs about special educational assistance and teacher management programs showed that interventions in ECEC have a positive immediate impact for children with developmental or behavioural problems, but provide little guidance on long-term effects. The current study has due to its observational character a lower internal validity than RCTs, but complements them in terms of external validity and by examining long-term effects. It thus strengthens the view that interventions in ECEC are a useful approach to support pre-schoolers with developmental or behavioural problems. In sum, the current study suggests that the psycho-social development of children with developmental or behaviour problems can be modified in a positive way through interventions in ECEC, also when provided outside the structured context of randomized controlled trials. Future research with better measurements and more representative samples should investigate under which conditions such interventions are most effective. Key Points And Relevance Parent training programs are considered a key component of early interventions against the development of developmental or mental health problems Special educational assistances in early childhood education and care (SEA in ECEC) showed positive effects on later outcomes in RCTs, but population based cohort studies reported no or even negative associations Results from our large, population based cohort study indicate that SEA in ECEC is associated with reduced psycho-social difficulties in elementary school SEA in ECEC may be effective also when implemented outside the structured context of RCTs and for children who do not come from disadvantaged backgrounds Easy access to SEA in ECEC may be a component of early intervention strategies to prevent or mitigate development of psycho-social difficulties in pre-schoolers at risk. Declarations Acknowledgements - The Norwegian Mother, Father and Child Cohort Study and the ADHD-Study is supported by the Norwegian Ministry of Health and Care Services and the Ministry of Education and Research. We are grateful to all the participating families in Norway who take part in this on-going cohort study. Funding: This research was supported by a grant of the ADHD Research Network in Norway. Availability of data and materials: The dataset supporting the conclusions of this article is available upon application to Norwegian Mother, Father and Child Cohort Study (MoBa, https://www.fhi.no/en/studies/moba/. Ethics approval and consent to participate - The establishment and data collection in MoBa was previously based on a license from the Norwegian Data Protection Agency and approval from The Regional Committee for Medical Research Ethics, and it is now based on regulations related to the Norwegian Health Registry Act. All MoBa mothers initially signed an informed consent form to be able to participate in the study, and they can withdraw from the study at any time. MoBa participants are informed about new projects and project updates through the MoBa newsletter and MoBa homepage. The study was performed in accordance with the declaration of Helsinki. The study was approved by the Regional Committees for Medical Research Ethics - South East Norway (Application-ID 9775) Consent for publication - Not applicable. Competing interests - The authors have no competing interests. References Wichstrøm L, Berg-Nielsen TS, Angold A, et al. Prevalence of psychiatric disorders in preschoolers. J Child Psychol Psychiatry Allied Discip. 2012;53:695–705. Global Research on Developmental Disabilities Collaborators. Developmental disabilities among children younger than 5 years in 195 countries and territories, 1990–2016: a systematic analysis for the Global Burden of Disease Study 2016. The Lancet Global health. 2018;6:e1100–213. Copeland WE, Wolke D, Shanahan L, Costello EJ. Adult Functional Outcomes of Common Childhood Psychiatric Problems: A Prospective, Longitudinal Study. JAMA psychiatry. 2015;72:892–9. Knudsen EI, Heckman JJ, Cameron JL, Shonkoff JP. Economic, neurobiological, and behavioral perspectives on building America’s future workforce. Proc Natl Acad Sci USA. 2006;103:10155–62. Smithers LG, Sawyer ACP, Chittleborough CR, et al (2018) A systematic review and meta-analysis of effects of early life non-cognitive skills on academic, psychosocial, cognitive and health outcomes. Nature Human Behaviour 2:867–80. https://doi.org/ 10.1038/s41562-018-0461-x . Heckman JJ. Skill formation and the economics of investing in disadvantaged children. Science. 2006;312:1900–2. Rea D, Burton T. New evidence on the Heckman curve. Journal of economic surveys. 2020;34:241–62. https://doi.org/10.1111/joes.12353 . Reynolds AJ, Temple JA, Robertson DL, Mann EA. Long-term effects of an early childhood intervention on educational achievement and juvenile arrest: A 15-year follow-up of low-income children in public schools. JAMA: the journal of the American Medical Association. 2001;285:2339–46. Perrin EC, Sheldrick RC, McMenamy JM, et al. Improving parenting skills for families of young children in pediatric settings: a randomized clinical trial. JAMA pediatrics. 2014;168:16–24. OECD. Education at a Glance 2019: OECD Indicators. Paris: OECD Publishing; 2019. Hagen ÅM, Melby-Lervåg M, Lervåg A. Improving language comprehension in preschool children with language difficulties: a cluster randomized trial. J Child Psychol Psychiatry Allied Discip. 2017;58:1132–40. Zwaigenbaum L, Bauman ML, Choueiri R, et al. Early Intervention for Children With Autism Spectrum Disorder Under 3 Years of Age: Recommendations for Practice and Research. Pediatrics. 2015;136(Suppl 1):60–81. Reinke WM, Herman KC, Dong N. The Incredible Years Teacher Classroom Management Program: Outcomes from a Group Randomized Trial. Prevention science: the official journal of the Society for Prevention Research. 2018;19:1043–54. Balzer LB. \"All Generalizations Are Dangerous, Even This One.\"-Alexandre Dumas. Epidemiology. 2017;28:562–6. Cole SR, Stuart EA. Generalizing evidence from randomized clinical trials to target populations: The ACTG 320 trial. Am J Epidemiol. 2010;172:107–15. Huitfeldt A, Stensrud MJ. Re: Generalizing Study Results: A Potential Outcomes Perspective. Epidemiology. 2018;29:e13–4. Lesko CR, Buchanan AL, Westreich D, et al. Generalizing Study Results: A Potential Outcomes Perspective. Epidemiology. 2017;28:553–61. Sullivan AL, Field S. Do preschool special education services make a difference in kindergarten reading and mathematics skills?: A propensity score weighting analysis. Journal of school psychology. 2013;51:243–60. Dempsey I, Valentine M, Colyvas K. The Effects of Special Education Support on Young Australian School Students. International Journal of Disability Development Education. 2016;63:271–92. Wendelborg C, Caspersen J, Kittelsaa AM, et al. Barnehagetilbudet til barn med særlige behov. NTNU Samfunnsforskning; 2015. Lekhal R. Does special education predict students’ math and language skills? European journal of special needs education. 2018;33:525–40. Kvande MN, Bjørklund O, Lydersen S, et al (2018) Effects of special education on academic achievement and task motivation: a propensity-score and fixed-effects approach. European journal of special needs education 1–15. Morgan PL, Frisco M, Farkas G, Hibel J. A Propensity Score Matching Analysis of the Effects of Special Education Services. The Journal of special education. 2010;43:236–54. Magnus P, Birke C, Vejrup K, et al (2016) Cohort profile update: The norwegian mother and child cohort study (MoBa). International journal of epidemiology. Magnus P, Irgens LM, Haug K, et al. Cohort profile: The norwegian mother and child cohort study (MoBa). Int J Epidemiol. 2006;35:1146–50. Irgens LM. The medical birth registry of norway. Epidemiological research and surveillance throughout 30 years. Acta obstetricia et gynecologica Scandinavica. 2000;79:435–9. Silva RR, Alpert M, Pouget E, et al. A rating scale for disruptive behavior disorders, based on the DSM-IV item pool. Psychiatr Q. 2005;76:327–39. Sharp C, Goodyer IM, Croudace TJ. The Short Mood and Feelings Questionnaire (SMFQ): A Unidimensional Item Response Theory and Categorical Data Factor Analysis of Self-Report Ratings from a Community Sample of 7-through 11-Year-Old Children. J Abnorm Child Psychol. 2006;34:365–77. Birmaher B, Brent DA, Chiappetta L, et al. Psychometric properties of the Screen for Child Anxiety Related Emotional Disorders (SCARED): a replication study. J Am Acad Child Adolesc Psychiatry. 1999;38:1230–6. Norbury CF, Nash M, Baird G, Bishop D. Using a parental checklist to identify diagnostic groups in children with communication impairment: a validation of the Children’s Communication Checklist–2. International journal of language & communication disorders / Royal College of Speech Language Therapists. 2004;39:345–64 31. Conners CK, Sitarenios G, Parker JDA, Epstein JN. The Revised Conners’ Parent Rating Scale (CPRS-R): Factor Structure, Reliability, and Criterion Validity. J Abnorm Child Psychol. 1998;26:257–68. Nøvik TS. Validity of the child behaviour checklist in a norwegian sample. Eur Child Adolesc Psychiatry. 1999;8:247–54. Achenbach TM, Ruffle TM. The Child Behavior Checklist and related forms for assessing behavioral/emotional problems and competencies. Pediatrics in review /American Academy of Pediatrics. 2000;21:265–71. Kessler RC, Adler L, Ames M, et al. The world health organization adult ADHD Self-Report scale (ASRS): A short screening scale for use in the general population. Psychological medicine. 2005;35:245–56. Strand BH, Dalgard OS, Tambs K, Rognerud M. Measuring the mental health status of the norwegian population: A comparison of the instruments SCL-25, SCL-10, SCL-5 and MHI-5 (SF-36). Nord J Psychiatry. 2003;57:113–8. R Core Team. R: A language and environment for statistical computing. Vienna: R Foundation for Statistical Computing; 2017. Bürkner P-C. brms: An R package for Bayesian multilevel models using Stan. J Stat Softw. 2017;80:1–28. https://doi.org/10.18637/jss.v080.i01 . Greenland S, Pearl J, Robins JM. Causal diagrams for epidemiologic research. Epidemiology. 1999;10:37–48. Biele G, Gustavson K, Czajkowski NO, et al. Bias from self selection and loss to follow-up in prospective cohort studies. Eur J Epidemiol. 2019;34:927–38. Stan Development Team. (2018) RStan: The R interface to Stan. Carpenter B, Gelman A, Hoffman M, et al. Stan: A probabilistic programming language. Journal of statistical software. 2017;76:1–32. Greenland S. Principles of multilevel modelling. Int J Epidemiol. 2000;29:158–67. Gelman A, Hill J, Yajima M. Why We (Usually) Don’t Have to Worry About Multiple Comparisons. Journal of research on educational effectiveness. 2012;5:189–211. Buuren S van, Groothuis-Oudshoorn K. Mice: Multivariate imputation by chained equations in r. J Stat Softw. 2011;45:1–67. Sullivan GM, Feinn R. Using Effect Size-or Why the P Value Is Not Enough. Journal of graduate medical education. 2012;4:279–82. Wasserstein RL, Schirm AL, Lazar NA. Moving to a World Beyond “p < 0.05”. The American statistician. 2019;73:1–19. Austin PC, Stuart EA. Moving towards best practice when using inverse probability of treatment weighting (IPTW) using the propensity score to estimate causal treatment effects in observational studies. Statistics in medicine. 2015;34:3661–79. Vandell DL, Belsky J, Burchinal M, et al. Do effects of early child care extend to age 15 years? Results from the NICHD study of early child care and youth development. Child development. 2010;81:737–56. Richardson M, Moore DA, Gwernan-Jones R, et al. Non-pharmacological interventions for attention-deficit/hyperactivity disorder (ADHD) delivered in school settings: Systematic reviews of quantitative and qualitative research. Health technology assessment. 2015;19:1–470. Gaastra GF, Groen Y, Tucha L, Tucha O. The Effects of Classroom Interventions on Off-Task and Disruptive Classroom Behavior in Children with Symptoms of Attention-Deficit/Hyperactivity Disorder: A Meta-Analytic Review. PloS one. 2016;11:e0148841. Reichow B. Overview of meta-analyses on early intensive behavioral intervention for young children with autism spectrum disorders. J Autism Dev Disord. 2012;42:512–20. Fossum S, Handegård BH, Britt Drugli M. The Incredible Years Teacher Classroom Management Programme in Kindergartens: Effects of a Universal Preventive Effort. J Child Fam stud. 2017;26:2215–23. Nilsen S, Herlofsen C. National Regulations and Guidelines and the Local Follow-up in the Chain of Actions in Special Education. International journal of special education. 2012;27:136–47. Russell AE, Ford T, Russell G. Socioeconomic Associations with ADHD: Findings from a Mediation Analysis. PloS one. 2015;10:e0128248. Supplementary Files SM.pdf Cite Share Download PDF Status: Published Journal Publication published 24 Feb, 2022 Read the published version in Child and Adolescent Psychiatry and Mental Health → Version 1 posted Editorial decision: Major revision 16 Nov, 2021 Review # 4 received at journal 27 Sep, 2021 Review # 2 received at journal 27 Sep, 2021 Review # 3 received at journal 16 Sep, 2021 Review # 1 received at journal 16 Sep, 2021 Reviewer # 4 agreed at journal 11 Sep, 2021 Reviewer # 3 agreed at journal 09 Sep, 2021 Reviewer # 2 agreed at journal 07 Sep, 2021 Reviews received at journal 07 Sep, 2021 Reviewer # 1 agreed at journal 06 Sep, 2021 Reviewers invited by journal 05 Sep, 2021 Submission checks completed at journal 24 Aug, 2021 Editor invited by journal 24 Aug, 2021 Editor assigned by journal 19 Aug, 2021 First submitted to journal 16 Aug, 2021 You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. 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Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {\"props\":{\"pageProps\":{\"initialData\":{\"identity\":\"rs-819337\",\"acceptedTermsAndConditions\":true,\"allowDirectSubmit\":false,\"archivedVersions\":[],\"articleType\":\"Research article\",\"associatedPublications\":[],\"authors\":[{\"id\":48681827,\"identity\":\"d0063837-ffe3-45cf-8796-8a487dc6e134\",\"order_by\":0,\"name\":\"Guido Biele\",\"email\":\"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAA0klEQVRIie2PMQrCQBBFvywkzUDaFcVcYUVQU+UaloqgraU2EgkkjQfIUSwTAtqYfkEL01jHxtpEEDt3S4t91TD8N58BDIa/pBVwICXYaN02zayvMDBR6ClAo6BWLF4EGnF3Mt/JCteuw9hxnR3GGNkKry9noZfgTu3QWsjszOHtU4WSzKIOISeR0/DyiDiEnGoqfu48V5mO4vJPCyMLWoqgsv5F3Inn1oDXComz4hc3XpayWl99Jw7LKou2PXEKFC3vk+K7oN/5pkVx0mAwGAzAC6sBQyt/09L8AAAAAElFTkSuQmCC\",\"orcid\":\"https://orcid.org/0000-0002-4225-9024\",\"institution\":\"Norwegian Institute of Public Health: Folkehelseinstituttet\",\"correspondingAuthor\":true,\"prefix\":\"\",\"firstName\":\"Guido\",\"middleName\":\"\",\"lastName\":\"Biele\",\"suffix\":\"\"},{\"id\":48681828,\"identity\":\"5f3f3c64-bfc0-436b-8969-0b4b5a39e1cf\",\"order_by\":1,\"name\":\"Ratib Lekhal\",\"email\":\"\",\"orcid\":\"\",\"institution\":\"BI Norwegian Business School: Handelshoyskolen BI\",\"correspondingAuthor\":false,\"prefix\":\"\",\"firstName\":\"Ratib\",\"middleName\":\"\",\"lastName\":\"Lekhal\",\"suffix\":\"\"},{\"id\":48681829,\"identity\":\"3d7c7f61-83c8-467a-8d2c-6353d4eeea24\",\"order_by\":2,\"name\":\"Kristin R. Overgaard\",\"email\":\"\",\"orcid\":\"\",\"institution\":\"Oslo University Hospital: Oslo Universitetssykehus\",\"correspondingAuthor\":false,\"prefix\":\"\",\"firstName\":\"Kristin\",\"middleName\":\"R.\",\"lastName\":\"Overgaard\",\"suffix\":\"\"},{\"id\":48681830,\"identity\":\"de489123-358f-4a07-bef4-5bc1047da383\",\"order_by\":3,\"name\":\"Mari Vaage Wang\",\"email\":\"\",\"orcid\":\"\",\"institution\":\"Norwegian Institute of Public Health: Folkehelseinstituttet\",\"correspondingAuthor\":false,\"prefix\":\"\",\"firstName\":\"Mari\",\"middleName\":\"Vaage\",\"lastName\":\"Wang\",\"suffix\":\"\"},{\"id\":48681831,\"identity\":\"a9192172-1319-48b3-8acf-64ad3d66c70c\",\"order_by\":4,\"name\":\"Ragnhild Eek Brandlistuen\",\"email\":\"\",\"orcid\":\"\",\"institution\":\"Norwegian Institute of Public Health: Folkehelseinstituttet\",\"correspondingAuthor\":false,\"prefix\":\"\",\"firstName\":\"Ragnhild\",\"middleName\":\"Eek\",\"lastName\":\"Brandlistuen\",\"suffix\":\"\"},{\"id\":48681832,\"identity\":\"227b025d-d1af-4417-af4d-c0946ebeabfb\",\"order_by\":5,\"name\":\"Svein Friis\",\"email\":\"\",\"orcid\":\"\",\"institution\":\"Oslo University Hospital: Oslo Universitetssykehus\",\"correspondingAuthor\":false,\"prefix\":\"\",\"firstName\":\"Svein\",\"middleName\":\"\",\"lastName\":\"Friis\",\"suffix\":\"\"},{\"id\":48681833,\"identity\":\"856a293b-2b6f-40a1-a5c3-06376c595aab\",\"order_by\":6,\"name\":\"Pål Zeiner\",\"email\":\"\",\"orcid\":\"\",\"institution\":\"Oslo University Hospital: Oslo Universitetssykehus\",\"correspondingAuthor\":false,\"prefix\":\"\",\"firstName\":\"Pål\",\"middleName\":\"\",\"lastName\":\"Zeiner\",\"suffix\":\"\"}],\"badges\":[],\"createdAt\":\"2021-08-16 12:58:21\",\"currentVersionCode\":1,\"declarations\":\"\",\"doi\":\"10.21203/rs.3.rs-819337/v1\",\"doiUrl\":\"https://doi.org/10.21203/rs.3.rs-819337/v1\",\"draftVersion\":[],\"editorialEvents\":[{\"content\":\"https://doi.org/10.1186/s13034-022-00442-5\",\"type\":\"published\",\"date\":\"2022-02-24T17:49:32+00:00\"}],\"editorialNote\":\"\",\"failedWorkflow\":false,\"files\":[{\"id\":12948887,\"identity\":\"fd7a5cfb-0af7-4e29-9470-64f9fa2653d4\",\"added_by\":\"auto\",\"created_at\":\"2021-08-31 19:43:53\",\"extension\":\"png\",\"order_by\":1,\"title\":\"Figure 1\",\"display\":\"\",\"copyAsset\":false,\"role\":\"figure\",\"size\":18273,\"visible\":true,\"origin\":\"\",\"legend\":\"Inclusion flow chart. Age 5 and 8 Q are MoBa questionnaires sent out at child age five and eight years. Children in the study sample have a parent-reported developmental or behaviour problem (DBP) at age five. Children with epilepsy, cerebral palsy, chromosomal defects, severe developmental delay, or hearing loss were excluded from this study. SEA = special educational assistance in early childhood education and care (ECEC).\",\"description\":\"\",\"filename\":\"fig1.png\",\"url\":\"https://assets-eu.researchsquare.com/files/rs-819337/v1/9b842391267787e4b5f1fca5.png\"},{\"id\":12948886,\"identity\":\"a718814a-8a5a-4799-b2a6-5639185dac44\",\"added_by\":\"auto\",\"created_at\":\"2021-08-31 19:43:53\",\"extension\":\"png\",\"order_by\":2,\"title\":\"Figure 2\",\"display\":\"\",\"copyAsset\":false,\"role\":\"figure\",\"size\":37275,\"visible\":true,\"origin\":\"\",\"legend\":\"Directed Acyclic Graph of the hypothesized causal relationships between special educational assistance (SEA) psycho-social difficulties (PSD5,PSD8), loss to follow up (L), maternal mental health (MHm), unobserved environmental and genetic causes (UE,UG) and additional confounders (C, i.e. contact with mental health services, maternal education, birth order, birth month, preterm birth). Current and prior psycho-social difficulties PSD5 are confounders causing bias due to treatment by indication and can be controlled through adjustment. Because maternal mental health (MHm) predicts loss to follow up (L), which is a collider on a backdoor path between SEA and PSD8, loss to follow up has to be controlled through inverse probability weighting.\",\"description\":\"\",\"filename\":\"fig2.png\",\"url\":\"https://assets-eu.researchsquare.com/files/rs-819337/v1/763cb470bc21d965437062cb.png\"},{\"id\":12948888,\"identity\":\"30be6b5c-aaf1-461f-b90d-04e7104380c0\",\"added_by\":\"auto\",\"created_at\":\"2021-08-31 19:43:53\",\"extension\":\"png\",\"order_by\":3,\"title\":\"Figure 3\",\"display\":\"\",\"copyAsset\":false,\"role\":\"figure\",\"size\":83899,\"visible\":true,\"origin\":\"\",\"legend\":\"Estimated average treatment effects stratified by group (top) and outcome (bottom). Points indicate means, grey and dark-grey bands indicate 50 and 90% credible intervals. SMD = standardised mean deviation. Abbreviations as in Table 1.\",\"description\":\"\",\"filename\":\"fig3.png\",\"url\":\"https://assets-eu.researchsquare.com/files/rs-819337/v1/315ec92b234b5b4e74ef8e90.png\"},{\"id\":18580284,\"identity\":\"8abb8515-413c-4110-ab82-ed569292f1ee\",\"added_by\":\"auto\",\"created_at\":\"2022-02-24 17:49:35\",\"extension\":\"pdf\",\"order_by\":0,\"title\":\"\",\"display\":\"\",\"copyAsset\":false,\"role\":\"manuscript-pdf\",\"size\":447519,\"visible\":true,\"origin\":\"\",\"legend\":\"\",\"description\":\"\",\"filename\":\"manuscript.pdf\",\"url\":\"https://assets-eu.researchsquare.com/files/rs-819337/v1/d6d89bce-2fdb-448e-a81a-af6c08315a21.pdf\"},{\"id\":12948889,\"identity\":\"e848d63d-2608-4779-b66f-8ff1db37c791\",\"added_by\":\"auto\",\"created_at\":\"2021-08-31 19:43:53\",\"extension\":\"pdf\",\"order_by\":4,\"title\":\"\",\"display\":\"\",\"copyAsset\":false,\"role\":\"supplement\",\"size\":1222456,\"visible\":true,\"origin\":\"\",\"legend\":\"\",\"description\":\"\",\"filename\":\"SM.pdf\",\"url\":\"https://assets-eu.researchsquare.com/files/rs-819337/v1/29afbabc0a9a3e8be87cd69d.pdf\"}],\"financialInterests\":\"\",\"formattedTitle\":\"\\u003cp\\u003eThe Effect of Special Educational Assistance In Early Childhood Education And Care On Psycho-Social Difficulties In Elementary School Children\\u003c/p\\u003e\",\"fulltext\":[{\"header\":\"Introduction\",\"content\":\"\\u003cp\\u003eBetween three and seven percent of pre-schoolers have developmental problems or child psychiatric disorders [\\u003cspan citationid=\\\"CR1\\\" class=\\\"CitationRef\\\"\\u003e1\\u003c/span\\u003e, \\u003cspan citationid=\\\"CR2\\\" class=\\\"CitationRef\\\"\\u003e2\\u003c/span\\u003e], which are an important risk factor for mental disorders in adulthood [\\u003cspan citationid=\\\"CR3\\\" class=\\\"CitationRef\\\"\\u003e3\\u003c/span\\u003e]. Efforts to promote healthy growth and development in children who struggle in the early years can accordingly improve children\\u0026rsquo;s long-term life opportunities [\\u003cspan citationid=\\\"CR4\\\" class=\\\"CitationRef\\\"\\u003e4\\u003c/span\\u003e]. Indeed, a recent review reported overwhelmingly positive effects of non-cognitive skills on academic, psychosocial, cognitive and health outcomes [\\u003cspan citationid=\\\"CR5\\\" class=\\\"CitationRef\\\"\\u003e5\\u003c/span\\u003e], though effect sizes are typically not large. It has been hypothesized that the effect of interventions decreases as children grow older and therefore, investing resources later, at the age of school entry or beyond, may show less of an effect [6, but also see 7].\\u003c/p\\u003e \\u003cp\\u003eInterventions in early childhood are often described as an effective method to improve the long-term outcomes of children from disadvantaged backgrounds [\\u003cspan citationid=\\\"CR6\\\" class=\\\"CitationRef\\\"\\u003e6\\u003c/span\\u003e] or those with specific developmental or behavioural problems like attention deficit hyperactivity disorder, autism, or behaviour or language problems [\\u003cspan citationid=\\\"CR9\\\" class=\\\"CitationRef\\\"\\u003e9\\u003c/span\\u003e]. Interventions in early childhood education and care (ECEC) can be especially effective because in contrast to parental training programs, their implementation relies less on parents\\u0026rsquo; abilities or motivation, and on average 93% of three to five year old children in Organisation for Economic Co-operation and Development (OECD) countries are enrolled in ECEC [10, more then 95% or 5 year old children in Norway are in ECEC]. Randomized controlled trials (RCTs) reported clear effects of early interventions in ECEC for a horizon of up to nine months, for instance for language problems [\\u003cspan citationid=\\\"CR11\\\" class=\\\"CitationRef\\\"\\u003e11\\u003c/span\\u003e], children with ADHD or autism [\\u003cspan citationid=\\\"CR12\\\" class=\\\"CitationRef\\\"\\u003e12\\u003c/span\\u003e], and for teacher classroom management programs [\\u003cspan citationid=\\\"CR13\\\" class=\\\"CitationRef\\\"\\u003e13\\u003c/span\\u003e].\\u003c/p\\u003e \\u003cp\\u003eHowever, the effect sizes of such interventions are not generally large, and less is known about their effect when interventions are provided outside the well-structured context of RCTs. Even though RCTs are, due to their interval validity, the gold standard for estimating treatment effects, differences between study sample and target population and differences in treatment-implementation between study and regular care contexts, make a generalization of findings from RCT samples to populations of interest difficult [\\u003cspan additionalcitationids=\\\"CR15 CR16\\\" citationid=\\\"CR14\\\" class=\\\"CitationRef\\\"\\u003e14\\u003c/span\\u003e\\u0026ndash;\\u003cspan citationid=\\\"CR17\\\" class=\\\"CitationRef\\\"\\u003e17\\u003c/span\\u003e]. Since RCTs often take place in a controlled setting, it may be difficult to replicate the results in other, less rigid settings. For instance, field professionals in ECEC institutions will draw on a much wider range of sources than formal experimental evidence in order to inform their actions. Thus, while evidence from RCTs is encouraging, it remains unclear how it generalizes to interventions in ECEC provided in regular care.\\u003c/p\\u003e \\u003cp\\u003eOnly a handful of studies examined the effects of special educational assistance (SEA) interventions in ECEC when they are implemented outside of RCTs. These studies used propensity scores to deal with the problematic internal validity in observational studies\\u0026mdash;due to treatment by indication\\u0026mdash;and found that children who received SEA in ECEC showed the same or worse outcomes compared children who did not receive SEA [\\u003cspan citationid=\\\"CR18\\\" class=\\\"CitationRef\\\"\\u003e18\\u003c/span\\u003e, \\u003cspan citationid=\\\"CR19\\\" class=\\\"CitationRef\\\"\\u003e19\\u003c/span\\u003e].\\u003c/p\\u003e \\u003cp\\u003eThe Norwegian ECEC-system facilitates the investigation of SEA, because children who cannot fully benefit from standard education and care have the right to receive free SEA. Similar to other OECD countries [\\u003cspan citationid=\\\"CR2\\\" class=\\\"CitationRef\\\"\\u003e2\\u003c/span\\u003e], around 4.5% of pre-schoolers in Norwegian ECEC have impaired functioning, the most common impairment being language and communication difficulties, followed by psycho-social difficulties and behaviour problems [\\u003cspan citationid=\\\"CR20\\\" class=\\\"CitationRef\\\"\\u003e20\\u003c/span\\u003e]. Around 2.6% of pre-schoolers receive SEA, which is provided for several hours per week for individual children [\\u003cspan citationid=\\\"CR20\\\" class=\\\"CitationRef\\\"\\u003e20\\u003c/span\\u003e]. After stimulation of language development, social- and behaviour-training are the most frequent types of SEA provided. To date, no study has\\u0026ndash;to the best of our knowledge\\u0026ndash;examined the effect of SEA in ECEC on children\\u0026rsquo;s psycho-social difficulties. Related studies on SEA in Norwegian schools report that students who received it have similar or slightly worse scholastic outcomes compared to those who did not receive it [21, 22, see also 23].\\u003c/p\\u003e \\u003cp\\u003eIn sum, the few studies examining effects of SEA in ECEC outside the context of RCTs reported small negative, to no effects of SEA. Moreover, most studies focused on educational outcomes, such that the effect of SEA on the development of psycho-social difficulties remains largely unclear. Hence, this large-scale prospective cohort study adds to the existing literature by investigating how SEA in ECEC provided outside RCTs affects the psycho-social development of children with developmental or behavioural problems.\\u003c/p\\u003e\"},{\"header\":\"Methods\",\"content\":\"\\u003ch2\\u003eParticipants\\u003c/h2\\u003e\\n\\u003cp\\u003eThe sample is a sub-sample of the Norwegian Mother, Father and Child Cohort Study (MoBa), a prospective population-based pregnancy cohort study conducted by the Norwegian Institute of Public Health [24, 25]. Participating mothers from all over Norway were recruited during routine ultrasound assessment in week 17 or 18 of their pregnancy in the period from 1999 to 2009. 41% of the invited women consented to participate. MoBa participants received questionnaires in gestational week 17 or 18, week 22 and week 30, at child\\u0026rsquo;s age 6 and 18 months, 3, 5, and 8 years and onward. The study is still on-going. The reported analyses also use information from the Medical Birth Registry of Norway [26].\\u003c/p\\u003e\\n\\u003cp\\u003eThe study sample is comprised of children whose mothers indicated developmental or behaviour problems in MoBa\\u0026rsquo;s age five years questionnaire, and for whom information about outcomes in the age eight years questionnaire are available. This study focuses on children with one or more of the following developmental or behavioural problems: Attention deficit hyperactivity disorder, language development, oppositional defiant or conduct disorder, autism spectrum disorder, and learning disabilities.\\u003c/p\\u003e\\n\\u003ch2\\u003eMaterials\\u003c/h2\\u003e\\n\\u003cp\\u003eThe current study used rating scales from MoBa questionnaires sent out at child ages five, and eight years. Exposure and inclusion criteria were based on responses in the five year questionnaire, whereas outcome measures were taken from the eight year questionnaire. The first, 1.5 and three year MoBa questionnaires and the Medical Birth Registry of Norway provided covariates.\\u003c/p\\u003e\\n\\u003cp\\u003e\\u003cstrong\\u003eExposure.\\u0026nbsp;\\u003c/strong\\u003eTo measure the provision of SEA, we relied on following question: \\u0026ldquo;Does your child receive, or has received any extra resources in the kindergarten?\\u0026rdquo; If mothers responded \\u0026ldquo;Yes\\u0026rdquo; to this question, they were additionally asked about the number of hours per week. SEA is provided to individual children, both inside and outside the context of regular preschool activities.\\u003c/p\\u003e\\n\\u003cp\\u003e\\u003cstrong\\u003eOutcome variables.\\u0026nbsp;\\u003c/strong\\u003eOutcome variables (\\u003cem\\u003ePSD\\u003c/em\\u003e\\u003csub\\u003e8\\u0026nbsp;\\u003c/sub\\u003ein Figure 2) were \\u003cem\\u003esum scores\\u0026nbsp;\\u003c/em\\u003efrom different scales about psycho-social difficulties. Outcome dimensions were attentional, hyperactivity/impulsivity, and behavioural (ODD or CD) problems measured with the Parent Rating Scale for Disruptive Behaviour Disorders (RS-DBD, [27]), emotional problems measured with the Short Mood and Feelings Questionnaire (SMFQ, [28]) and the Screen for Child Anxiety Related Disorders (SCARED, [29]), and communication problems measured with the Children\\u0026rsquo;s Communication Checklist-2 (CCC-2, [30]).\\u003c/p\\u003e\\n\\u003cp\\u003e\\u003cstrong\\u003eAdjustment variables.\\u0026nbsp;\\u003c/strong\\u003eAdjustment variables and those to control for loss to follow up were chosen based on the directed acyclic graph (DAG) shown in figure Figure 2. One important set of confounders includes children\\u0026rsquo;s psycho-social difficulties at baseline, because these can be seen as causes of treatment and are related to later psycho-social difficulties. A number of scales in MoBa assessed psycho-social difficulties at age five and served as baseline measures (\\u003cem\\u003ePSD\\u003c/em\\u003e\\u003csub\\u003e5\\u0026nbsp;\\u003c/sub\\u003ein Figure 2). These included the Conners\\u0026rsquo; Parent Rating Scale-Revised, Short Form (CPRS-R (S), [31]), Child Behaviour Checklist (CBCL, [32]), the Ages and Stages Questionnaire (ASQ, [33]), and the Children\\u0026rsquo;s Communication Checklist-2. While the baseline assessment considers the same mental health and development difficulties as the outcome, MoBa used different scales for five and age year olds.\\u003c/p\\u003e\\n\\u003cp\\u003eAdditional variables used for adjustment or prediction of loss to follow-up included maternal age, education, ADHD symptoms measured with the Adult ADHD Self-Report Scale [34] at child age three and depressive symptoms measured with the SCL-5 [35] at child age five, parity, preterm birth, birth-month, hours special education per week, number of developmental of behaviour problems, and contact with rehabilitation services, Child and Adolescent Psychiatric Units, or Educational and Psychological Counseling Service at child age five years.\\u003c/p\\u003e\\n\\u003ch2\\u003eClassification into groups with different developmental or behavioural problems\\u003c/h2\\u003e\\n\\u003cp\\u003eTo classify if and in which area a child had developmental or behavioural problem (DBP), we used MoBa questions about mental health problems at age five. Mothers were asked if their child \\u0026ldquo;suffered, or is currently suffering from any of the following long-term illnesses or health problems.\\u0026rdquo; In addition, mothers were asked if they had been in contact with a Child and Adolescent Psychiatric Unit or the Educational Psychology Counseling Services and if the health problem was confirmed by a professional. Only children for whom mothers reported a health problem \\u003cem\\u003eand\\u0026nbsp;\\u003c/em\\u003ewho indicated that the problem was evaluated by a mental health professional were included in the sample.\\u003c/p\\u003e\\n\\u003cp\\u003eDisorders or health problems for which MoBa\\u0026rsquo;s age 5 questionnaire has questions included Epilepsy, Cerebral Palsy, impaired hearing, which were excluded from the current analysis, together with children for whom mothers indicated a chromosomal defect. MoBa also asked mothers about autism spectrum disorders (ASD), hyperactivity and attention problems (ADHD), language difficulties (Lang), and behavioural problems (Beh). Additional questions about learning disabilities (LD) were also used to identify cases of interest for this study. Each child was classified in one of the following DBP groups: 1. ASD, 2. LD, 3. \\u0026nbsp;ADHD \\u0026amp; Beh \\u0026amp; Lang, 4. ADHD \\u0026amp; Beh, 5. ADHD \\u0026amp; Lang, 6. ADHD, 7. Lang, 8. Beh. For some children, mothers indicated multiple DBP, in which case the child was assigned to the first group it fell into. If, for example, a mother indicated ASD, ADHD, and language problems, the child was assigned to the ASD group (details in supplementary materials and Table S1). The rational underlying this classification scheme was to use existing psychiatric diagnoses, and to classify children according to their most impairing problem because these have typically more severe and persistent effects on psycho-social development.\\u003c/p\\u003e\\n\\u003ch2\\u003eData analysis\\u003c/h2\\u003e\\n\\u003cp\\u003eAll analyses were performed using R [36]. The Bayesian hierarchical regression model was implemented with the brms package [37]. The analyses are described in more detail in the supplementary material, and analysis scripts are available at \\u003ca href=\\\"https://github.com/gbiele/SPS358\\\"\\u003ehttps://github.com/gbiele/SPS358.\\u003c/a\\u003e\\u003c/p\\u003e\\n\\u003cp\\u003e\\u003cstrong\\u003eBias from treatment by indication and loss to follow up.\\u003c/strong\\u003e Estimation of treatment effects from observational data is difficult because treatment is not assigned randomly. Instead, individuals with more psycho-social difficulties at age five, who are also more likely to have psycho-social difficulties in the future, more likely receive treatment (treatment by indication). In addition, loss to follow up makes estimation of treatment effects difficult. Therefore, we used a directed acyclic graph [DAG, 38, see Figure 2] to explicate the assumed causal structure and to determine with which approach to deal with potential biases. Given this structural model, inverse probability of continued participation weighting was needed to reduce bias from loss to follow up [39], whereas adjustment for predictors of SEA was sufficient to control bias from treatment by indication. This means that we effectively estimated the effect of SEA on the change of psycho-social difficulties from preschool to elementary school.\\u003c/p\\u003e\\n\\u003cp\\u003e\\u003cstrong\\u003eEstimation of the treatment effects.\\u0026nbsp;\\u003c/strong\\u003eWe used a Bayesian adjusted and weighted hierarchical ordinal regression to estimate effects of SEA [37, 40, 41]. A hierarchical regression induces partial pooling (shrinkage) of estimates, which reduces the variance of estimates [42] and controls the multiple comparison problem [43]. Importantly, when analysing related patient groups hierarchical regression results in more accurate association estimates then independent analysis of these groups [42]. We used an ordinal regression model, because the estimation of latent, normally distributed traits that underlie the rating-scale responses facilitates the presentation of results in terms of standardised mean differences (SMD). The reported results were obtained by pooling over the independent analyses of the 50 imputed data sets [44]. Consistent with recent recommendations to focus on estimation of effect sizes instead of significance testing [45, 46] we generally report means and the 90% credible intervals.\\u003c/p\\u003e\"},{\"header\":\"Results\",\"content\":\"\\u003cp\\u003eThe study sample includes 2499 participants (c.f., Figure 1). Thirty-three percent of the children in the sample received SEA. Table 1 describes the study sample. Figures S4 and S5 show that children with more severe problems (e.g. ASD) were more likely to receive SEA and also received SEA from better educated personnel.\\u003c/p\\u003e\\n\\u003cp\\u003eTable 1 Study sample\\u003c/p\\u003e\\n\\u003ctable border=\\\"0\\\" cellpadding=\\\"0\\\" cellspacing=\\\"0\\\" width=\\\"0\\\"\\u003e\\n \\u003cthead\\u003e\\n \\u003ctr\\u003e\\n \\u003ctd width=\\\"49.61479198767334%\\\"\\u003e\\n \\u003cp\\u003eVariable\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd width=\\\"18.335901386748844%\\\"\\u003e\\n \\u003cp\\u003ew/o SEA\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd width=\\\"16.640986132511557%\\\"\\u003e\\n \\u003cp\\u003ewith SEA\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd width=\\\"15.408320493066256%\\\"\\u003e\\n \\u003cp\\u003eTotal\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003c/tr\\u003e\\n \\u003c/thead\\u003e\\n \\u003ctbody\\u003e\\n \\u003ctr\\u003e\\n \\u003ctd colspan=\\\"4\\\" width=\\\"100%\\\"\\u003e\\n \\u003cp\\u003eSpecial educational assistance (SEA)\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003c/tr\\u003e\\n \\u003ctr\\u003e\\n \\u003ctd width=\\\"49.61479198767334%\\\"\\u003e\\n \\u003cp\\u003eboy\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd width=\\\"18.335901386748844%\\\"\\u003e\\n \\u003cp\\u003e1063 (63.8%)\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd width=\\\"16.640986132511557%\\\"\\u003e\\n \\u003cp\\u003e586 (70.3%)\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd width=\\\"15.408320493066256%\\\"\\u003e\\n \\u003cp\\u003e1649 (66%)\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003c/tr\\u003e\\n \\u003ctr\\u003e\\n \\u003ctd width=\\\"49.61479198767334%\\\"\\u003e\\n \\u003cp\\u003egirl\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd width=\\\"18.335901386748844%\\\"\\u003e\\n \\u003cp\\u003e602 (36.2%)\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd width=\\\"16.640986132511557%\\\"\\u003e\\n \\u003cp\\u003e248 (29.7%)\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd width=\\\"15.408320493066256%\\\"\\u003e\\n \\u003cp\\u003e850 (34%)\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003c/tr\\u003e\\n \\u003ctr\\u003e\\n \\u003ctd width=\\\"49.61479198767334%\\\"\\u003e\\n \\u003cp\\u003eHours\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd width=\\\"18.335901386748844%\\\"\\u003e\\n \\u003cp\\u003e0 (0, 0)\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd width=\\\"16.640986132511557%\\\"\\u003e\\n \\u003cp\\u003e4.76 (1, 6)\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd width=\\\"15.408320493066256%\\\"\\u003e\\n \\u003cp\\u003e1.59 (0, 1)\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003c/tr\\u003e\\n \\u003ctr\\u003e\\n \\u003ctd colspan=\\\"4\\\" width=\\\"100%\\\"\\u003e\\n \\u003cp\\u003eDevelopmental or behaviour problem (DBP) group\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003c/tr\\u003e\\n \\u003ctr\\u003e\\n \\u003ctd width=\\\"49.61479198767334%\\\"\\u003e\\n \\u003cp\\u003eASD\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd width=\\\"18.335901386748844%\\\"\\u003e\\n \\u003cp\\u003e11 (0.7%)\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd width=\\\"16.640986132511557%\\\"\\u003e\\n \\u003cp\\u003e32 (3.8%)\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd width=\\\"15.408320493066256%\\\"\\u003e\\n \\u003cp\\u003e43 (1.7%)\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003c/tr\\u003e\\n \\u003ctr\\u003e\\n \\u003ctd width=\\\"49.61479198767334%\\\"\\u003e\\n \\u003cp\\u003eLD\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd width=\\\"18.335901386748844%\\\"\\u003e\\n \\u003cp\\u003e19 (1.1%)\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd width=\\\"16.640986132511557%\\\"\\u003e\\n \\u003cp\\u003e63 (7.6%)\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd width=\\\"15.408320493066256%\\\"\\u003e\\n \\u003cp\\u003e82 (3.3%)\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003c/tr\\u003e\\n \\u003ctr\\u003e\\n \\u003ctd width=\\\"49.61479198767334%\\\"\\u003e\\n \\u003cp\\u003eADHD \\u0026amp; Beh \\u0026amp; Lang\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd width=\\\"18.335901386748844%\\\"\\u003e\\n \\u003cp\\u003e12 (0.7%)\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd width=\\\"16.640986132511557%\\\"\\u003e\\n \\u003cp\\u003e19 (2.3%)\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd width=\\\"15.408320493066256%\\\"\\u003e\\n \\u003cp\\u003e31 (1.2%)\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003c/tr\\u003e\\n \\u003ctr\\u003e\\n \\u003ctd width=\\\"49.61479198767334%\\\"\\u003e\\n \\u003cp\\u003eADHD \\u0026amp; Lang\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd width=\\\"18.335901386748844%\\\"\\u003e\\n \\u003cp\\u003e58 (3.5%)\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd width=\\\"16.640986132511557%\\\"\\u003e\\n \\u003cp\\u003e85 (10.2%)\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd width=\\\"15.408320493066256%\\\"\\u003e\\n \\u003cp\\u003e143 (5.7%)\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003c/tr\\u003e\\n \\u003ctr\\u003e\\n \\u003ctd width=\\\"49.61479198767334%\\\"\\u003e\\n \\u003cp\\u003eADHD \\u0026amp; Beh\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd width=\\\"18.335901386748844%\\\"\\u003e\\n \\u003cp\\u003e108 (6.5%)\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd width=\\\"16.640986132511557%\\\"\\u003e\\n \\u003cp\\u003e38 (4.6%)\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd width=\\\"15.408320493066256%\\\"\\u003e\\n \\u003cp\\u003e146 (5.8%)\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003c/tr\\u003e\\n \\u003ctr\\u003e\\n \\u003ctd width=\\\"49.61479198767334%\\\"\\u003e\\n \\u003cp\\u003eADHD\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd width=\\\"18.335901386748844%\\\"\\u003e\\n \\u003cp\\u003e330 (19.8%)\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd width=\\\"16.640986132511557%\\\"\\u003e\\n \\u003cp\\u003e71 (8.5%)\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd width=\\\"15.408320493066256%\\\"\\u003e\\n \\u003cp\\u003e401 (16%)\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003c/tr\\u003e\\n \\u003ctr\\u003e\\n \\u003ctd width=\\\"49.61479198767334%\\\"\\u003e\\n \\u003cp\\u003eLang\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd width=\\\"18.335901386748844%\\\"\\u003e\\n \\u003cp\\u003e847 (50.9%)\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd width=\\\"16.640986132511557%\\\"\\u003e\\n \\u003cp\\u003e486 (58.3%)\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd width=\\\"15.408320493066256%\\\"\\u003e\\n \\u003cp\\u003e1333 (53.3%)\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003c/tr\\u003e\\n \\u003ctr\\u003e\\n \\u003ctd width=\\\"49.61479198767334%\\\"\\u003e\\n \\u003cp\\u003eBeh\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd width=\\\"18.335901386748844%\\\"\\u003e\\n \\u003cp\\u003e280 (16.8%)\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd width=\\\"16.640986132511557%\\\"\\u003e\\n \\u003cp\\u003e40 (4.8%)\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd width=\\\"15.408320493066256%\\\"\\u003e\\n \\u003cp\\u003e320 (12.8%)\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003c/tr\\u003e\\n \\u003ctr\\u003e\\n \\u003ctd colspan=\\\"4\\\" width=\\\"100%\\\"\\u003e\\n \\u003cp\\u003ePsycho-social difficulties (PSD) at child age five\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003c/tr\\u003e\\n \\u003ctr\\u003e\\n \\u003ctd width=\\\"49.61479198767334%\\\"\\u003e\\n \\u003cp\\u003eAttention\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd width=\\\"18.335901386748844%\\\"\\u003e\\n \\u003cp\\u003e6.03 (2, 9)\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd width=\\\"16.640986132511557%\\\"\\u003e\\n \\u003cp\\u003e6.98 (2, 10)\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd width=\\\"15.408320493066256%\\\"\\u003e\\n \\u003cp\\u003e6.34 (2, 9)\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003c/tr\\u003e\\n \\u003ctr\\u003e\\n \\u003ctd width=\\\"49.61479198767334%\\\"\\u003e\\n \\u003cp\\u003eHyperactivity\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd width=\\\"18.335901386748844%\\\"\\u003e\\n \\u003cp\\u003e4.67 (3, 6)\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd width=\\\"16.640986132511557%\\\"\\u003e\\n \\u003cp\\u003e4.68 (3, 6)\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd width=\\\"15.408320493066256%\\\"\\u003e\\n \\u003cp\\u003e4.67 (3, 6)\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003c/tr\\u003e\\n \\u003ctr\\u003e\\n \\u003ctd width=\\\"49.61479198767334%\\\"\\u003e\\n \\u003cp\\u003eExternalizing (CBCL)\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd width=\\\"18.335901386748844%\\\"\\u003e\\n \\u003cp\\u003e3.98 (2, 6)\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd width=\\\"16.640986132511557%\\\"\\u003e\\n \\u003cp\\u003e3.73 (1, 6)\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd width=\\\"15.408320493066256%\\\"\\u003e\\n \\u003cp\\u003e3.9 (2, 6)\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003c/tr\\u003e\\n \\u003ctr\\u003e\\n \\u003ctd width=\\\"49.61479198767334%\\\"\\u003e\\n \\u003cp\\u003eInternalizing (CBCL)\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd width=\\\"18.335901386748844%\\\"\\u003e\\n \\u003cp\\u003e2.01 (0, 3)\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd width=\\\"16.640986132511557%\\\"\\u003e\\n \\u003cp\\u003e2.16 (0, 3)\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd width=\\\"15.408320493066256%\\\"\\u003e\\n \\u003cp\\u003e2.06 (0, 3)\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003c/tr\\u003e\\n \\u003ctr\\u003e\\n \\u003ctd width=\\\"49.61479198767334%\\\"\\u003e\\n \\u003cp\\u003eCommunication (CCC)\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd width=\\\"18.335901386748844%\\\"\\u003e\\n \\u003cp\\u003e3.93 (2, 6)\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd width=\\\"16.640986132511557%\\\"\\u003e\\n \\u003cp\\u003e4.76 (3, 7)\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd width=\\\"15.408320493066256%\\\"\\u003e\\n \\u003cp\\u003e4.21 (2, 6)\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003c/tr\\u003e\\n \\u003ctr\\u003e\\n \\u003ctd width=\\\"49.61479198767334%\\\"\\u003e\\n \\u003cp\\u003eDevelopment (ASQ)\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd width=\\\"18.335901386748844%\\\"\\u003e\\n \\u003cp\\u003e1.34 (0, 2)\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd width=\\\"16.640986132511557%\\\"\\u003e\\n \\u003cp\\u003e2.31 (1, 3)\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd width=\\\"15.408320493066256%\\\"\\u003e\\n \\u003cp\\u003e1.67 (0, 2)\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003c/tr\\u003e\\n \\u003ctr\\u003e\\n \\u003ctd colspan=\\\"4\\\" width=\\\"100%\\\"\\u003e\\n \\u003cp\\u003ePsycho-social difficulties (PSD) at child age eight\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003c/tr\\u003e\\n \\u003ctr\\u003e\\n \\u003ctd width=\\\"49.61479198767334%\\\"\\u003e\\n \\u003cp\\u003eAttention (ATT, RS-DBD)\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd width=\\\"18.335901386748844%\\\"\\u003e\\n \\u003cp\\u003e7.51 (4, 10)\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd width=\\\"16.640986132511557%\\\"\\u003e\\n \\u003cp\\u003e8.3 (4, 12)\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd width=\\\"15.408320493066256%\\\"\\u003e\\n \\u003cp\\u003e7.77 (4, 11)\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003c/tr\\u003e\\n \\u003ctr\\u003e\\n \\u003ctd width=\\\"49.61479198767334%\\\"\\u003e\\n \\u003cp\\u003eHyperactivity (HYP, RS-DBD)\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd width=\\\"18.335901386748844%\\\"\\u003e\\n \\u003cp\\u003e6.07 (2, 9)\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd width=\\\"16.640986132511557%\\\"\\u003e\\n \\u003cp\\u003e5.77 (1, 8)\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd width=\\\"15.408320493066256%\\\"\\u003e\\n \\u003cp\\u003e5.97 (2, 9)\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003c/tr\\u003e\\n \\u003ctr\\u003e\\n \\u003ctd width=\\\"49.61479198767334%\\\"\\u003e\\n \\u003cp\\u003eOppositional (OPP, RS-DBD)\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd width=\\\"18.335901386748844%\\\"\\u003e\\n \\u003cp\\u003e5.18 (2, 7)\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd width=\\\"16.640986132511557%\\\"\\u003e\\n \\u003cp\\u003e4.44 (1, 6)\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd width=\\\"15.408320493066256%\\\"\\u003e\\n \\u003cp\\u003e4.93 (2, 7)\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003c/tr\\u003e\\n \\u003ctr\\u003e\\n \\u003ctd width=\\\"49.61479198767334%\\\"\\u003e\\n \\u003cp\\u003eMood (MOOD, SMFQ)\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd width=\\\"18.335901386748844%\\\"\\u003e\\n \\u003cp\\u003e3.06 (1, 4)\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd width=\\\"16.640986132511557%\\\"\\u003e\\n \\u003cp\\u003e2.96 (1, 4.75)\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd width=\\\"15.408320493066256%\\\"\\u003e\\n \\u003cp\\u003e3.03 (1, 4)\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003c/tr\\u003e\\n \\u003ctr\\u003e\\n \\u003ctd width=\\\"49.61479198767334%\\\"\\u003e\\n \\u003cp\\u003eAnxiety (ANX, SCARED)\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd width=\\\"18.335901386748844%\\\"\\u003e\\n \\u003cp\\u003e1.21 (0, 2)\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd width=\\\"16.640986132511557%\\\"\\u003e\\n \\u003cp\\u003e1.22 (0, 2)\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd width=\\\"15.408320493066256%\\\"\\u003e\\n \\u003cp\\u003e1.21 (0, 2)\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003c/tr\\u003e\\n \\u003ctr\\u003e\\n \\u003ctd width=\\\"49.61479198767334%\\\"\\u003e\\n \\u003cp\\u003eCommunication (COMM, CCC)\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd width=\\\"18.335901386748844%\\\"\\u003e\\n \\u003cp\\u003e7.75 (4, 11)\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd width=\\\"16.640986132511557%\\\"\\u003e\\n \\u003cp\\u003e10.29 (5, 14)\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd width=\\\"15.408320493066256%\\\"\\u003e\\n \\u003cp\\u003e8.6 (4, 12)\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003c/tr\\u003e\\n \\u003ctr\\u003e\\n \\u003ctd colspan=\\\"4\\\" width=\\\"100%\\\"\\u003e\\n \\u003cp\\u003eMaternal characteristics\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003c/tr\\u003e\\n \\u003ctr\\u003e\\n \\u003ctd width=\\\"49.61479198767334%\\\"\\u003e\\n \\u003cp\\u003eEducation (years)\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd width=\\\"18.335901386748844%\\\"\\u003e\\n \\u003cp\\u003e14.01 (12, 15)\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd width=\\\"16.640986132511557%\\\"\\u003e\\n \\u003cp\\u003e13.98 (12, 16)\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd width=\\\"15.408320493066256%\\\"\\u003e\\n \\u003cp\\u003e14 (12, 15)\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003c/tr\\u003e\\n \\u003ctr\\u003e\\n \\u003ctd width=\\\"49.61479198767334%\\\"\\u003e\\n \\u003cp\\u003eAge (years)\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd width=\\\"18.335901386748844%\\\"\\u003e\\n \\u003cp\\u003e30.52 (27, 34)\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd width=\\\"16.640986132511557%\\\"\\u003e\\n \\u003cp\\u003e30.82 (28, 34)\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd width=\\\"15.408320493066256%\\\"\\u003e\\n \\u003cp\\u003e30.62 (28, 34)\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003c/tr\\u003e\\n \\u003ctr\\u003e\\n \\u003ctd width=\\\"49.61479198767334%\\\"\\u003e\\n \\u003cp\\u003eADHD (ADHD-RS)\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd width=\\\"18.335901386748844%\\\"\\u003e\\n \\u003cp\\u003e7.38 (5, 10)\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd width=\\\"16.640986132511557%\\\"\\u003e\\n \\u003cp\\u003e7.15 (5, 9)\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd width=\\\"15.408320493066256%\\\"\\u003e\\n \\u003cp\\u003e7.3 (5, 10)\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003c/tr\\u003e\\n \\u003ctr\\u003e\\n \\u003ctd width=\\\"49.61479198767334%\\\"\\u003e\\n \\u003cp\\u003eDepression (SCL-5)\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd width=\\\"18.335901386748844%\\\"\\u003e\\n \\u003cp\\u003e2.53 (0, 4)\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd width=\\\"16.640986132511557%\\\"\\u003e\\n \\u003cp\\u003e2.43 (0, 3)\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd width=\\\"15.408320493066256%\\\"\\u003e\\n \\u003cp\\u003e2.5 (0, 3)\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003c/tr\\u003e\\n \\u003c/tbody\\u003e\\n\\u003c/table\\u003e\\n\\u003cp\\u003eASD = Autisum spectrum disorder, LD = Learning difficulties, Lang = Language problems, Beh = behaviour problems, SEA = special educational assistance. Abbreviations and original scales for PSD are given in parentheses (see methods section for full names). Numbers in parentheses are percent or first and third quartiles\\u003c/p\\u003e\\n\\u003cp\\u003eInverse probability weights reduced the differences in mean values for covariates between participants followed up and those lost to follow up to less than 0.1 SMD (c.f. Figure S1; [47]). Cumulative distribution plots showed that weighting balanced the entire distributions of covariates (Figures S7 and S8).\\u003c/p\\u003e\\n\\u003ch2\\u003eEffects of special educational assistance\\u003c/h2\\u003e\\n\\u003cp\\u003eConsistent with the structural model shown in Figure 2, the analysis without adjustment showed that SEA at age five was associated with more psycho-social difficulties at age eight (c.f. Table S3 and Figure S7 ). Table S4 and Figures S9 and S10, S11, and S12 show coefficients of the adjusted regression model, which indicates that after adjustment for confounders SEA was associated with less psycho-social difficulties at age eight.\\u003c/p\\u003e\\n\\u003cp\\u003eOver all psycho-social outcomes and groups of developmental or behaviour problems the estimated average treatment effect (ATE) was a symptom reduction by 0.10 standardised mean deviations (SMD) (Credible Interval CI: 0.04, 0.16). Figure 3 shows that the 90% credible interval is for all groups above 0. The pairwise comparisons of all groups did not show clear differences in the estimated treatment effects between groups (c.f. Table S5 and Figure S14)\\u003c/p\\u003e\\n\\u003cp\\u003eFigure 3 and Table 2 also show estimated effect sizes stratified by outcomes and indicate that SEA had a positive effect on all measured psycho-social outcomes. While there were some differences in the effect size estimates for different outcomes, in particular smaller effects for anxiety and communication problems, pairwise comparisons did not show reliable differences between them (c.f. Table S6 and Figure S15). Effect size estimates did not vary substantially by the child sex (c.f. Figure S18).\\u003c/p\\u003e\\n\\u003cp\\u003eTable 2 Estimated average treatment effects (ATE) stratified by groups with different developmental and behavioural problems (rows) and psycho-social difficulties (columns)\\u003c/p\\u003e\\n\\u003cdiv align=\\\"center\\\"\\u003e\\n \\u003ctable border=\\\"0\\\" cellpadding=\\\"0\\\" cellspacing=\\\"0\\\" width=\\\"0\\\"\\u003e\\n \\u003cthead\\u003e\\n \\u003ctr\\u003e\\n \\u003ctd width=\\\"14.9581589958159%\\\"\\u003e\\n \\u003cp\\u003eGroup\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd width=\\\"11.820083682008368%\\\"\\u003e\\n \\u003cp\\u003eATT\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd width=\\\"11.820083682008368%\\\"\\u003e\\n \\u003cp\\u003eHYP\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd width=\\\"11.820083682008368%\\\"\\u003e\\n \\u003cp\\u003eOPP\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd width=\\\"11.820083682008368%\\\"\\u003e\\n \\u003cp\\u003eMOOD\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd width=\\\"12.866108786610878%\\\"\\u003e\\n \\u003cp\\u003eANX\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd width=\\\"12.656903765690377%\\\"\\u003e\\n \\u003cp\\u003eCOMM\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd width=\\\"12.238493723849372%\\\"\\u003e\\n \\u003cp\\u003eAverage\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003c/tr\\u003e\\n \\u003c/thead\\u003e\\n \\u003ctbody\\u003e\\n \\u003ctr\\u003e\\n \\u003ctd width=\\\"14.9581589958159%\\\"\\u003e\\n \\u003cp\\u003eASD\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd width=\\\"11.820083682008368%\\\"\\u003e\\n \\u003cp\\u003e0.08 (-0.06,0.21)\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd width=\\\"11.820083682008368%\\\"\\u003e\\n \\u003cp\\u003e0.11 (-0.02,0.25)\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd width=\\\"11.820083682008368%\\\"\\u003e\\n \\u003cp\\u003e0.11 (-0.02,0.25)\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd width=\\\"11.820083682008368%\\\"\\u003e\\n \\u003cp\\u003e0.1 (-0.03,0.24)\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd width=\\\"12.866108786610878%\\\"\\u003e\\n \\u003cp\\u003e0.08 (-0.06,0.21)\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd width=\\\"12.656903765690377%\\\"\\u003e\\n \\u003cp\\u003e0.07 (-0.08,0.2)\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd width=\\\"12.238493723849372%\\\"\\u003e\\n \\u003cp\\u003e0.09 (0, 0.18)\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003c/tr\\u003e\\n \\u003ctr\\u003e\\n \\u003ctd width=\\\"14.9581589958159%\\\"\\u003e\\n \\u003cp\\u003eLD\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd width=\\\"11.820083682008368%\\\"\\u003e\\n \\u003cp\\u003e0.09 (-0.02,0.21)\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd width=\\\"11.820083682008368%\\\"\\u003e\\n \\u003cp\\u003e0.11 (0,0.23)\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd width=\\\"11.820083682008368%\\\"\\u003e\\n \\u003cp\\u003e0.11 (0,0.23)\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd width=\\\"11.820083682008368%\\\"\\u003e\\n \\u003cp\\u003e0.11 (0,0.23)\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd width=\\\"12.866108786610878%\\\"\\u003e\\n \\u003cp\\u003e0.1 (-0.01,0.22)\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd width=\\\"12.656903765690377%\\\"\\u003e\\n \\u003cp\\u003e0.08 (-0.05,0.19)\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd width=\\\"12.238493723849372%\\\"\\u003e\\n \\u003cp\\u003e0.1 (0.03, 0.18)\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003c/tr\\u003e\\n \\u003ctr\\u003e\\n \\u003ctd width=\\\"14.9581589958159%\\\"\\u003e\\n \\u003cp\\u003eADHD \\u0026amp; Beh \\u0026amp; Lang\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd width=\\\"11.820083682008368%\\\"\\u003e\\n \\u003cp\\u003e0.1 (-0.04,0.24)\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd width=\\\"11.820083682008368%\\\"\\u003e\\n \\u003cp\\u003e0.11 (-0.03,0.26)\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd width=\\\"11.820083682008368%\\\"\\u003e\\n \\u003cp\\u003e0.09 (-0.05,0.23)\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd width=\\\"11.820083682008368%\\\"\\u003e\\n \\u003cp\\u003e0.11 (-0.03,0.25)\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd width=\\\"12.866108786610878%\\\"\\u003e\\n \\u003cp\\u003e0.1 (-0.04,0.25)\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd width=\\\"12.656903765690377%\\\"\\u003e\\n \\u003cp\\u003e0.08 (-0.07,0.22)\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd width=\\\"12.238493723849372%\\\"\\u003e\\n \\u003cp\\u003e0.1 (0, 0.19)\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003c/tr\\u003e\\n \\u003ctr\\u003e\\n \\u003ctd width=\\\"14.9581589958159%\\\"\\u003e\\n \\u003cp\\u003eADHD \\u0026amp; Lang\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd width=\\\"11.820083682008368%\\\"\\u003e\\n \\u003cp\\u003e0.07 (-0.05,0.18)\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd width=\\\"11.820083682008368%\\\"\\u003e\\n \\u003cp\\u003e0.11 (-0.01,0.22)\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd width=\\\"11.820083682008368%\\\"\\u003e\\n \\u003cp\\u003e0.13 (0.02,0.26)\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd width=\\\"11.820083682008368%\\\"\\u003e\\n \\u003cp\\u003e0.1 (-0.01,0.21)\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd width=\\\"12.866108786610878%\\\"\\u003e\\n \\u003cp\\u003e0.13 (0.02,0.26)\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd width=\\\"12.656903765690377%\\\"\\u003e\\n \\u003cp\\u003e0.1 (-0.02,0.21)\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd width=\\\"12.238493723849372%\\\"\\u003e\\n \\u003cp\\u003e0.11 (0.03, 0.18)\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003c/tr\\u003e\\n \\u003ctr\\u003e\\n \\u003ctd width=\\\"14.9581589958159%\\\"\\u003e\\n \\u003cp\\u003eADHD \\u0026amp; Beh\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd width=\\\"11.820083682008368%\\\"\\u003e\\n \\u003cp\\u003e0.15 (0.03,0.29)\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd width=\\\"11.820083682008368%\\\"\\u003e\\n \\u003cp\\u003e0.11 (-0.01,0.23)\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd width=\\\"11.820083682008368%\\\"\\u003e\\n \\u003cp\\u003e0.11 (-0.01,0.24)\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd width=\\\"11.820083682008368%\\\"\\u003e\\n \\u003cp\\u003e0.1 (-0.02,0.22)\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd width=\\\"12.866108786610878%\\\"\\u003e\\n \\u003cp\\u003e0.11 (-0.01,0.23)\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd width=\\\"12.656903765690377%\\\"\\u003e\\n \\u003cp\\u003e0.09 (-0.03,0.22)\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd width=\\\"12.238493723849372%\\\"\\u003e\\n \\u003cp\\u003e0.11 (0.04, 0.19)\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003c/tr\\u003e\\n \\u003ctr\\u003e\\n \\u003ctd width=\\\"14.9581589958159%\\\"\\u003e\\n \\u003cp\\u003eADHD\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd width=\\\"11.820083682008368%\\\"\\u003e\\n \\u003cp\\u003e0.09 (-0.02,0.2)\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd width=\\\"11.820083682008368%\\\"\\u003e\\n \\u003cp\\u003e0.12 (0.02,0.23)\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd width=\\\"11.820083682008368%\\\"\\u003e\\n \\u003cp\\u003e0.14 (0.03,0.26)\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd width=\\\"11.820083682008368%\\\"\\u003e\\n \\u003cp\\u003e0.09 (-0.03,0.19)\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd width=\\\"12.866108786610878%\\\"\\u003e\\n \\u003cp\\u003e0.11 (0,0.23)\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd width=\\\"12.656903765690377%\\\"\\u003e\\n \\u003cp\\u003e0.08 (-0.03,0.19)\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd width=\\\"12.238493723849372%\\\"\\u003e\\n \\u003cp\\u003e0.11 (0.03, 0.18)\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003c/tr\\u003e\\n \\u003ctr\\u003e\\n \\u003ctd width=\\\"14.9581589958159%\\\"\\u003e\\n \\u003cp\\u003eLang\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd width=\\\"11.820083682008368%\\\"\\u003e\\n \\u003cp\\u003e0.1 (0.01,0.18)\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd width=\\\"11.820083682008368%\\\"\\u003e\\n \\u003cp\\u003e0.15 (0.06,0.24)\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd width=\\\"11.820083682008368%\\\"\\u003e\\n \\u003cp\\u003e0.15 (0.07,0.24)\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd width=\\\"11.820083682008368%\\\"\\u003e\\n \\u003cp\\u003e0.1 (0.01,0.18)\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd width=\\\"12.866108786610878%\\\"\\u003e\\n \\u003cp\\u003e0.06 (-0.03,0.15)\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd width=\\\"12.656903765690377%\\\"\\u003e\\n \\u003cp\\u003e0.06 (-0.03,0.14)\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd width=\\\"12.238493723849372%\\\"\\u003e\\n \\u003cp\\u003e0.1 (0.04, 0.16)\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003c/tr\\u003e\\n \\u003ctr\\u003e\\n \\u003ctd width=\\\"14.9581589958159%\\\"\\u003e\\n \\u003cp\\u003eBeh\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd width=\\\"11.820083682008368%\\\"\\u003e\\n \\u003cp\\u003e0.09 (-0.03,0.2)\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd width=\\\"11.820083682008368%\\\"\\u003e\\n \\u003cp\\u003e0.07 (-0.06,0.18)\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd width=\\\"11.820083682008368%\\\"\\u003e\\n \\u003cp\\u003e0.11 (0,0.24)\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd width=\\\"11.820083682008368%\\\"\\u003e\\n \\u003cp\\u003e0.06 (-0.07,0.17)\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd width=\\\"12.866108786610878%\\\"\\u003e\\n \\u003cp\\u003e0.11 (0,0.23)\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd width=\\\"12.656903765690377%\\\"\\u003e\\n \\u003cp\\u003e0.1 (-0.02,0.21)\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd width=\\\"12.238493723849372%\\\"\\u003e\\n \\u003cp\\u003e0.09 (0.02, 0.16)\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003c/tr\\u003e\\n \\u003ctr\\u003e\\n \\u003ctd width=\\\"14.9581589958159%\\\"\\u003e\\n \\u003cp\\u003eAverage\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd width=\\\"11.820083682008368%\\\"\\u003e\\n \\u003cp\\u003e0.1 (0.01, 0.18)\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd width=\\\"11.820083682008368%\\\"\\u003e\\n \\u003cp\\u003e0.15 (0.06, 0.24)\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd width=\\\"11.820083682008368%\\\"\\u003e\\n \\u003cp\\u003e0.15 (0.07, 0.24)\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd width=\\\"11.820083682008368%\\\"\\u003e\\n \\u003cp\\u003e0.1 (0.01, 0.18)\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd width=\\\"12.866108786610878%\\\"\\u003e\\n \\u003cp\\u003e0.06 (-0.03, 0.15)\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd width=\\\"12.656903765690377%\\\"\\u003e\\n \\u003cp\\u003e0.06 (-0.03, 0.14)\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd width=\\\"12.238493723849372%\\\"\\u003e\\n \\u003cp\\u003e\\u0026nbsp;\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003c/tr\\u003e\\n \\u003ctr\\u003e\\n \\u003ctd colspan=\\\"8\\\" width=\\\"100%\\\"\\u003e\\n \\u003cp\\u003eATEs are reported as standardised mean differences (SMD). Numbers are means (90% credible intervals).\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003c/tr\\u003e\\n \\u003c/tbody\\u003e\\n \\u003c/table\\u003e\\n\\u003c/div\\u003e\"},{\"header\":\"Discussion\",\"content\":\"\\u003cp\\u003eThis research used observational data from a longitudinal population based cohort study to investigate the effect of special educational assistance (SEA) in ECEC on psycho-social difficulties of children with developmental or behaviour problems. We found that, after adjustment for treatment indicators, mothers of children who received SEA in kindergarten reported fewer psycho-social difficulties three years later, compared to mothers whose children did not receive SEA.\\u003c/p\\u003e \\u003cp\\u003eWhile there was some variation in the extent of the positive effect of SEA between groups and different psycho-social difficulties, these differences were not reliably different from zero (c.f. Figures S14 and S15). Because the credible intervals for these differences are large compared to the magnitude of the estimated overall effect and the random effects standard deviations are clearly non-zero (S4), these results do not exclude the possibility of group differences. Instead, they might reflect difficulties in reliably measuring exposure, covariates, and outcomes based on parent reports only. Still, the available data were sufficient to reveal an overall positive effect of SEA.\\u003c/p\\u003e \\u003cp\\u003eWhile the positive effect reported in this study is consistent with the results of randomized controlled trials [\\u003cspan citationid=\\\"CR12\\\" class=\\\"CitationRef\\\"\\u003e12\\u003c/span\\u003e, \\u003cspan citationid=\\\"CR13\\\" class=\\\"CitationRef\\\"\\u003e13\\u003c/span\\u003e] and with reports of the positive effects of preschool child care quality [\\u003cspan citationid=\\\"CR48\\\" class=\\\"CitationRef\\\"\\u003e48\\u003c/span\\u003e], it also stands in contrast to previous observational studies, which estimated no or a small negative \\u0026ldquo;effects\\u0026rdquo; of special education. This apparent contradiction can be due to a number of differences between the current and previous studies. We had estimates of pre-treatment difficulties, and could estimate effects of special education on the change of psycho-social difficulties. Moreover, we used adjustment for treatment predictors instead of propensity score weighting. Adjustment is the preferable approach if treatment-predictors are not colliders on a backdoor path from outcome to treatment and if the sample size is large enough to allow for inclusion of many of adjustment variables. Another important difference is that whereas previous studies focused on scholastic outcomes, we focused on the effect on psycho-social difficulties. This is a to date little examined but important outcome of SEA, because early psycho-social difficulties are associate with impaired functioning in adulthood [\\u003cspan citationid=\\\"CR3\\\" class=\\\"CitationRef\\\"\\u003e3\\u003c/span\\u003e]. Interestingly, the clear results of SEA on externalizing behaviour suggests that in addition to helping children with DBP, it can also benefit their families by reducing disruptive behaviour.\\u003c/p\\u003e \\u003cp\\u003eThe estimated effect size for the reduction of psycho-social difficulties is with on average 0.10 standardised mean difference small. In comparison, previous meta analysis about school\\u0026ndash; or ECEC\\u0026ndash;based interventions found effect sizes of between \\u0026minus;\\u0026thinsp;.3 and 1.3 SMD for children with or at risk for ADHD [\\u003cspan citationid=\\\"CR49\\\" class=\\\"CitationRef\\\"\\u003e49\\u003c/span\\u003e, \\u003cspan citationid=\\\"CR50\\\" class=\\\"CitationRef\\\"\\u003e50\\u003c/span\\u003e] or SMD between 0.3 and 1.1 for children with autism [\\u003cspan citationid=\\\"CR51\\\" class=\\\"CitationRef\\\"\\u003e51\\u003c/span\\u003e]. Randomized trials of classroom management training for kindergarten teachers showed effect sizes similar to our results [Cohen\\u0026rsquo;s d around 0.3 for high risk children at the nine-months follow up, 52]. A recent meta-analysis of reported effect sizes around 0.2\\u0026ndash;0.3 SMD from experimental manipulations of non-cognitive skill on psychosoial outcomes [\\u003cspan citationid=\\\"CR5\\\" class=\\\"CitationRef\\\"\\u003e5\\u003c/span\\u003e], and smaller effects around 0.1 SMD from non-experimental longitudinal studies. It is possible that the small effect sizes we estimated are, in addition to above mentioned measurement problems, due to the fact the SEA was often provided by personnel with limited training, especially for children with typically less severe problems (c.f. Figure S5).\\u003c/p\\u003e \\u003cp\\u003eMore generally, the decentralized organization of the Educational and Psychological Counselling Service is likely to lead to a large variation in the implementation of SEA [\\u003cspan citationid=\\\"CR53\\\" class=\\\"CitationRef\\\"\\u003e53\\u003c/span\\u003e]. MoBa did not collect more detailed data about SEA, which could help to elucidate when it is most effective. Another possible explanation is that the composition of the study sample, which over-represents well-educated families compared to the population [\\u003cspan citationid=\\\"CR39\\\" class=\\\"CitationRef\\\"\\u003e39\\u003c/span\\u003e], leads to an underestimation of the true effect size, because well-educated parents could reduce children\\u0026rsquo;s psycho-social difficulties even without SEA [\\u003cspan citationid=\\\"CR54\\\" class=\\\"CitationRef\\\"\\u003e54\\u003c/span\\u003e].\\u003c/p\\u003e \\u003cp\\u003eWhile the current study showed that mothers report fewer psycho-social difficulties in elementary school when their children received SEA in ECEC, a causal interpretation of this result as reflecting an effect of SEA rests on a number of assumptions encoded in Fig.\\u0026nbsp;\\u003cspan refid=\\\"Fig2\\\" class=\\\"InternalRef\\\"\\u003e2\\u003c/span\\u003e. One un-testable assumption is that there are no unmeasured confounders that predict both which children receive SEA and their developmental pathway. Even though the reported analysis includes obvious confounders, other unobserved confounders like e.g. parental engagement could still account for some of the positive association of SEA and psycho-social development. However, because RCTs of SEA and similar interventions typically report positive effects, and thus confirm a causal role of SEA, it appears unlikely that the effects estimated in this study are primarily due to confounding.\\u003c/p\\u003e \\u003cp\\u003eThe current study has a number of limitations that should be addressed in future studies. Outcomes should be assessed through blinded raters or objective instruments and the quality and quantity of the treatments need to be assessed in greater detail. Moreover, it is important that study samples include participants with a higher a priori prevalence of metnal health problems (i.e. no over-representation of highly educated parents which characteriizez MoBa) and that care is taken to avoid loss to follow up. Better measurements and more representative samples will be useful to investigate reasons for the relatively small effects observed in the current study, and to identify criteria for effective interventions in ECEC.\\u003c/p\\u003e\"},{\"header\":\"Conclusion\",\"content\":\"\\u003cp\\u003ePrevious RCTs about special educational assistance and teacher management programs showed that interventions in ECEC have a positive immediate impact for children with developmental or behavioural problems, but provide little guidance on long-term effects. The current study has due to its observational character a lower internal validity than RCTs, but complements them in terms of external validity and by examining long-term effects. It thus strengthens the view that interventions in ECEC are a useful approach to support pre-schoolers with developmental or behavioural problems.\\u003c/p\\u003e \\u003cp\\u003eIn sum, the current study suggests that the psycho-social development of children with developmental or behaviour problems can be modified in a positive way through interventions in ECEC, also when provided outside the structured context of randomized controlled trials. Future research with better measurements and more representative samples should investigate under which conditions such interventions are most effective.\\u003c/p\\u003e\"},{\"header\":\"Key Points And Relevance\",\"content\":\"\\u003cp\\u003e \\u003cul\\u003e \\u003cli\\u003e \\u003cp\\u003eParent training programs are considered a key component of early interventions against the development of developmental or mental health problems\\u003c/p\\u003e \\u003c/li\\u003e \\u003cli\\u003e \\u003cp\\u003eSpecial educational assistances in early childhood education and care (SEA in ECEC) showed positive effects on later outcomes in RCTs, but population based cohort studies reported no or even negative associations\\u003c/p\\u003e \\u003c/li\\u003e \\u003cli\\u003e \\u003cp\\u003eResults from our large, population based cohort study indicate that SEA in ECEC is associated with reduced psycho-social difficulties in elementary school\\u003c/p\\u003e \\u003c/li\\u003e \\u003cli\\u003e \\u003cp\\u003eSEA in ECEC may be effective also when implemented outside the structured context of RCTs and for children who do not come from disadvantaged backgrounds\\u003c/p\\u003e \\u003c/li\\u003e \\u003cli\\u003e \\u003cp\\u003eEasy access to SEA in ECEC may be a component of early intervention strategies to prevent or mitigate development of psycho-social difficulties in pre-schoolers at risk.\\u003c/p\\u003e \\u003c/li\\u003e \\u003c/ul\\u003e \\u003c/p\\u003e\"},{\"header\":\"Declarations\",\"content\":\"\\u003cp\\u003eAcknowledgements - The Norwegian Mother, Father and Child Cohort Study and the ADHD-Study is supported by the Norwegian Ministry of Health and Care Services and the Ministry of Education and Research. We are grateful to all the participating families in Norway who take part in this on-going cohort study.\\u0026nbsp;\\u003c/p\\u003e\\n\\u003cp\\u003eFunding: This research was supported by a grant of the ADHD Research Network in Norway.\\u003c/p\\u003e\\n\\u003cp\\u003eAvailability of data and materials: The dataset supporting the conclusions of this article is available upon application to Norwegian Mother, Father and Child Cohort Study (MoBa, \\u003ca href=\\\"https://www.fhi.no/en/studies/moba/\\\"\\u003ehttps://www.fhi.no/en/studies/moba/.\\u003c/a\\u003e\\u0026nbsp;\\u003c/p\\u003e\\n\\u003cp\\u003eEthics approval and consent to participate - The establishment and data collection in MoBa was previously based on a license from the Norwegian Data Protection Agency and approval from The Regional Committee for Medical Research Ethics, and it is now based on regulations related to the Norwegian Health Registry Act. All MoBa mothers initially signed an informed consent form to be able to participate in the study, and they can withdraw from the study at any time. MoBa participants are informed about new projects and project updates through the MoBa newsletter and MoBa homepage. The study was performed in accordance with the declaration of Helsinki. The study was approved by the Regional Committees for Medical Research Ethics - South East Norway (Application-ID 9775)\\u0026nbsp;\\u003c/p\\u003e\\n\\u003cp\\u003eConsent for publication - Not applicable.\\u0026nbsp;\\u003c/p\\u003e\\n\\u003cp\\u003eCompeting interests - The authors have no competing interests.\\u003c/p\\u003e\"},{\"header\":\"References\",\"content\":\"\\u003col\\u003e\\u003cli\\u003e\\u003cspan\\u003eWichstr\\u0026oslash;m L, Berg-Nielsen TS, Angold A, et al. Prevalence of psychiatric disorders in preschoolers. J Child Psychol Psychiatry Allied Discip. 2012;53:695\\u0026ndash;705.\\u003c/span\\u003e\\u003c/li\\u003e \\u003cli\\u003e\\u003cspan\\u003eGlobal Research on Developmental Disabilities Collaborators. Developmental disabilities among children younger than 5 years in 195 countries and territories, 1990\\u0026ndash;2016: a systematic analysis for the Global Burden of Disease Study 2016. The Lancet Global health. 2018;6:e1100\\u0026ndash;213.\\u003c/span\\u003e\\u003c/li\\u003e \\u003cli\\u003e\\u003cspan\\u003eCopeland WE, Wolke D, Shanahan L, Costello EJ. Adult Functional Outcomes of Common Childhood Psychiatric Problems: A Prospective, Longitudinal Study. JAMA psychiatry. 2015;72:892\\u0026ndash;9.\\u003c/span\\u003e\\u003c/li\\u003e \\u003cli\\u003e\\u003cspan\\u003eKnudsen EI, Heckman JJ, Cameron JL, Shonkoff JP. Economic, neurobiological, and behavioral perspectives on building America\\u0026rsquo;s future workforce. Proc Natl Acad Sci USA. 2006;103:10155\\u0026ndash;62.\\u003c/span\\u003e\\u003c/li\\u003e \\u003cli\\u003e\\u003cspan\\u003eSmithers LG, Sawyer ACP, Chittleborough CR, et al (2018) A systematic review and meta-analysis of effects of early life non-cognitive skills on academic, psychosocial, cognitive and health outcomes. Nature Human Behaviour 2:867\\u0026ndash;80. \\u003cspan class=\\\"ExternalRef\\\"\\u003e\\u003cspan class=\\\"RefSource\\\"\\u003ehttps://doi.org/ 10.1038/s41562-018-0461-x\\u003c/span\\u003e\\u003c/span\\u003e.\\u003c/span\\u003e\\u003c/li\\u003e \\u003cli\\u003e\\u003cspan\\u003eHeckman JJ. Skill formation and the economics of investing in disadvantaged children. Science. 2006;312:1900\\u0026ndash;2.\\u003c/span\\u003e\\u003c/li\\u003e \\u003cli\\u003e\\u003cspan\\u003eRea D, Burton T. New evidence on the Heckman curve. Journal of economic surveys. 2020;34:241\\u0026ndash;62. \\u003cspan class=\\\"ExternalRef\\\"\\u003e\\u003cspan class=\\\"RefSource\\\"\\u003ehttps://doi.org/10.1111/joes.12353\\u003c/span\\u003e\\u003c/span\\u003e.\\u003c/span\\u003e\\u003c/li\\u003e \\u003cli\\u003e\\u003cspan\\u003eReynolds AJ, Temple JA, Robertson DL, Mann EA. Long-term effects of an early childhood intervention on educational achievement and juvenile arrest: A 15-year follow-up of low-income children in public schools. JAMA: the journal of the American Medical Association. 2001;285:2339\\u0026ndash;46.\\u003c/span\\u003e\\u003c/li\\u003e \\u003cli\\u003e\\u003cspan\\u003ePerrin EC, Sheldrick RC, McMenamy JM, et al. Improving parenting skills for families of young children in pediatric settings: a randomized clinical trial. JAMA pediatrics. 2014;168:16\\u0026ndash;24.\\u003c/span\\u003e\\u003c/li\\u003e \\u003cli\\u003e\\u003cspan\\u003eOECD. Education at a Glance 2019: OECD Indicators. Paris: OECD Publishing; 2019.\\u003c/span\\u003e\\u003c/li\\u003e \\u003cli\\u003e\\u003cspan\\u003eHagen \\u0026Aring;M, Melby-Lerv\\u0026aring;g M, Lerv\\u0026aring;g A. Improving language comprehension in preschool children with language difficulties: a cluster randomized trial. J Child Psychol Psychiatry Allied Discip. 2017;58:1132\\u0026ndash;40.\\u003c/span\\u003e\\u003c/li\\u003e \\u003cli\\u003e\\u003cspan\\u003eZwaigenbaum L, Bauman ML, Choueiri R, et al. Early Intervention for Children With Autism Spectrum Disorder Under 3 Years of Age: Recommendations for Practice and Research. Pediatrics. 2015;136(Suppl 1):60\\u0026ndash;81.\\u003c/span\\u003e\\u003c/li\\u003e \\u003cli\\u003e\\u003cspan\\u003eReinke WM, Herman KC, Dong N. The Incredible Years Teacher Classroom Management Program: Outcomes from a Group Randomized Trial. Prevention science: the official journal of the Society for Prevention Research. 2018;19:1043\\u0026ndash;54.\\u003c/span\\u003e\\u003c/li\\u003e \\u003cli\\u003e\\u003cspan\\u003eBalzer LB. \\\"All Generalizations Are Dangerous, Even This One.\\\"-Alexandre Dumas. Epidemiology. 2017;28:562\\u0026ndash;6.\\u003c/span\\u003e\\u003c/li\\u003e \\u003cli\\u003e\\u003cspan\\u003eCole SR, Stuart EA. Generalizing evidence from randomized clinical trials to target populations: The ACTG 320 trial. Am J Epidemiol. 2010;172:107\\u0026ndash;15.\\u003c/span\\u003e\\u003c/li\\u003e \\u003cli\\u003e\\u003cspan\\u003eHuitfeldt A, Stensrud MJ. Re: Generalizing Study Results: A Potential Outcomes Perspective. Epidemiology. 2018;29:e13\\u0026ndash;4.\\u003c/span\\u003e\\u003c/li\\u003e \\u003cli\\u003e\\u003cspan\\u003eLesko CR, Buchanan AL, Westreich D, et al. Generalizing Study Results: A Potential Outcomes Perspective. Epidemiology. 2017;28:553\\u0026ndash;61.\\u003c/span\\u003e\\u003c/li\\u003e \\u003cli\\u003e\\u003cspan\\u003eSullivan AL, Field S. Do preschool special education services make a difference in kindergarten reading and mathematics skills?: A propensity score weighting analysis. Journal of school psychology. 2013;51:243\\u0026ndash;60.\\u003c/span\\u003e\\u003c/li\\u003e \\u003cli\\u003e\\u003cspan\\u003eDempsey I, Valentine M, Colyvas K. The Effects of Special Education Support on Young Australian School Students. International Journal of Disability Development Education. 2016;63:271\\u0026ndash;92.\\u003c/span\\u003e\\u003c/li\\u003e \\u003cli\\u003e\\u003cspan\\u003eWendelborg C, Caspersen J, Kittelsaa AM, et al. Barnehagetilbudet til barn med s\\u0026aelig;rlige behov. NTNU Samfunnsforskning; 2015.\\u003c/span\\u003e\\u003c/li\\u003e \\u003cli\\u003e\\u003cspan\\u003eLekhal R. Does special education predict students\\u0026rsquo; math and language skills? European journal of special needs education. 2018;33:525\\u0026ndash;40.\\u003c/span\\u003e\\u003c/li\\u003e \\u003cli\\u003e\\u003cspan\\u003eKvande MN, Bj\\u0026oslash;rklund O, Lydersen S, et al (2018) Effects of special education on academic achievement and task motivation: a propensity-score and fixed-effects approach. European journal of special needs education 1\\u0026ndash;15.\\u003c/span\\u003e\\u003c/li\\u003e \\u003cli\\u003e\\u003cspan\\u003eMorgan PL, Frisco M, Farkas G, Hibel J. A Propensity Score Matching Analysis of the Effects of Special Education Services. The Journal of special education. 2010;43:236\\u0026ndash;54.\\u003c/span\\u003e\\u003c/li\\u003e \\u003cli\\u003e\\u003cspan\\u003eMagnus P, Birke C, Vejrup K, et al (2016) Cohort profile update: The norwegian mother and child cohort study (MoBa). International journal of epidemiology.\\u003c/span\\u003e\\u003c/li\\u003e \\u003cli\\u003e\\u003cspan\\u003eMagnus P, Irgens LM, Haug K, et al. Cohort profile: The norwegian mother and child cohort study (MoBa). Int J Epidemiol. 2006;35:1146\\u0026ndash;50.\\u003c/span\\u003e\\u003c/li\\u003e \\u003cli\\u003e\\u003cspan\\u003eIrgens LM. The medical birth registry of norway. Epidemiological research and surveillance throughout 30 years. Acta obstetricia et gynecologica Scandinavica. 2000;79:435\\u0026ndash;9.\\u003c/span\\u003e\\u003c/li\\u003e \\u003cli\\u003e\\u003cspan\\u003eSilva RR, Alpert M, Pouget E, et al. A rating scale for disruptive behavior disorders, based on the DSM-IV item pool. Psychiatr Q. 2005;76:327\\u0026ndash;39.\\u003c/span\\u003e\\u003c/li\\u003e \\u003cli\\u003e\\u003cspan\\u003eSharp C, Goodyer IM, Croudace TJ. The Short Mood and Feelings Questionnaire (SMFQ): A Unidimensional Item Response Theory and Categorical Data Factor Analysis of Self-Report Ratings from a Community Sample of 7-through 11-Year-Old Children. J Abnorm Child Psychol. 2006;34:365\\u0026ndash;77.\\u003c/span\\u003e\\u003c/li\\u003e \\u003cli\\u003e\\u003cspan\\u003eBirmaher B, Brent DA, Chiappetta L, et al. Psychometric properties of the Screen for Child Anxiety Related Emotional Disorders (SCARED): a replication study. J Am Acad Child Adolesc Psychiatry. 1999;38:1230\\u0026ndash;6.\\u003c/span\\u003e\\u003c/li\\u003e \\u003cli\\u003e\\u003cspan\\u003eNorbury CF, Nash M, Baird G, Bishop D. Using a parental checklist to identify diagnostic groups in children with communication impairment: a validation of the Children\\u0026rsquo;s Communication Checklist\\u0026ndash;2. International journal of language \\u0026amp; communication disorders / Royal College of Speech Language Therapists. 2004;39:345\\u0026ndash;64 31.\\u003c/span\\u003e\\u003c/li\\u003e \\u003cli\\u003e\\u003cspan\\u003eConners CK, Sitarenios G, Parker JDA, Epstein JN. The Revised Conners\\u0026rsquo; Parent Rating Scale (CPRS-R): Factor Structure, Reliability, and Criterion Validity. J Abnorm Child Psychol. 1998;26:257\\u0026ndash;68.\\u003c/span\\u003e\\u003c/li\\u003e \\u003cli\\u003e\\u003cspan\\u003eN\\u0026oslash;vik TS. Validity of the child behaviour checklist in a norwegian sample. Eur Child Adolesc Psychiatry. 1999;8:247\\u0026ndash;54.\\u003c/span\\u003e\\u003c/li\\u003e \\u003cli\\u003e\\u003cspan\\u003eAchenbach TM, Ruffle TM. The Child Behavior Checklist and related forms for assessing behavioral/emotional problems and competencies. Pediatrics in review /American Academy of Pediatrics. 2000;21:265\\u0026ndash;71.\\u003c/span\\u003e\\u003c/li\\u003e \\u003cli\\u003e\\u003cspan\\u003eKessler RC, Adler L, Ames M, et al. The world health organization adult ADHD Self-Report scale (ASRS): A short screening scale for use in the general population. Psychological medicine. 2005;35:245\\u0026ndash;56.\\u003c/span\\u003e\\u003c/li\\u003e \\u003cli\\u003e\\u003cspan\\u003eStrand BH, Dalgard OS, Tambs K, Rognerud M. Measuring the mental health status of the norwegian population: A comparison of the instruments SCL-25, SCL-10, SCL-5 and MHI-5 (SF-36). Nord J Psychiatry. 2003;57:113\\u0026ndash;8.\\u003c/span\\u003e\\u003c/li\\u003e \\u003cli\\u003e\\u003cspan\\u003eR Core Team. R: A language and environment for statistical computing. Vienna: R Foundation for Statistical Computing; 2017.\\u003c/span\\u003e\\u003c/li\\u003e \\u003cli\\u003e\\u003cspan\\u003eB\\u0026uuml;rkner P-C. brms: An R package for Bayesian multilevel models using Stan. J Stat Softw. 2017;80:1\\u0026ndash;28. \\u003cspan class=\\\"ExternalRef\\\"\\u003e\\u003cspan class=\\\"RefSource\\\"\\u003ehttps://doi.org/10.18637/jss.v080.i01\\u003c/span\\u003e\\u003c/span\\u003e.\\u003c/span\\u003e\\u003c/li\\u003e \\u003cli\\u003e\\u003cspan\\u003eGreenland S, Pearl J, Robins JM. Causal diagrams for epidemiologic research. Epidemiology. 1999;10:37\\u0026ndash;48.\\u003c/span\\u003e\\u003c/li\\u003e \\u003cli\\u003e\\u003cspan\\u003eBiele G, Gustavson K, Czajkowski NO, et al. Bias from self selection and loss to follow-up in prospective cohort studies. Eur J Epidemiol. 2019;34:927\\u0026ndash;38.\\u003c/span\\u003e\\u003c/li\\u003e \\u003cli\\u003e\\u003cspan\\u003eStan Development Team. (2018) RStan: The R interface to Stan.\\u003c/span\\u003e\\u003c/li\\u003e \\u003cli\\u003e\\u003cspan\\u003eCarpenter B, Gelman A, Hoffman M, et al. Stan: A probabilistic programming language. Journal of statistical software. 2017;76:1\\u0026ndash;32.\\u003c/span\\u003e\\u003c/li\\u003e \\u003cli\\u003e\\u003cspan\\u003eGreenland S. Principles of multilevel modelling. Int J Epidemiol. 2000;29:158\\u0026ndash;67.\\u003c/span\\u003e\\u003c/li\\u003e \\u003cli\\u003e\\u003cspan\\u003eGelman A, Hill J, Yajima M. Why We (Usually) Don\\u0026rsquo;t Have to Worry About Multiple Comparisons. Journal of research on educational effectiveness. 2012;5:189\\u0026ndash;211.\\u003c/span\\u003e\\u003c/li\\u003e \\u003cli\\u003e\\u003cspan\\u003eBuuren S van, Groothuis-Oudshoorn K. Mice: Multivariate imputation by chained equations in r. J Stat Softw. 2011;45:1\\u0026ndash;67.\\u003c/span\\u003e\\u003c/li\\u003e \\u003cli\\u003e\\u003cspan\\u003eSullivan GM, Feinn R. Using Effect Size-or Why the P Value Is Not Enough. Journal of graduate medical education. 2012;4:279\\u0026ndash;82.\\u003c/span\\u003e\\u003c/li\\u003e \\u003cli\\u003e\\u003cspan\\u003eWasserstein RL, Schirm AL, Lazar NA. Moving to a World Beyond \\u0026ldquo;p \\u0026lt; 0.05\\u0026rdquo;. The American statistician. 2019;73:1\\u0026ndash;19.\\u003c/span\\u003e\\u003c/li\\u003e \\u003cli\\u003e\\u003cspan\\u003eAustin PC, Stuart EA. Moving towards best practice when using inverse probability of treatment weighting (IPTW) using the propensity score to estimate causal treatment effects in observational studies. Statistics in medicine. 2015;34:3661\\u0026ndash;79.\\u003c/span\\u003e\\u003c/li\\u003e \\u003cli\\u003e\\u003cspan\\u003eVandell DL, Belsky J, Burchinal M, et al. Do effects of early child care extend to age 15 years? Results from the NICHD study of early child care and youth development. Child development. 2010;81:737\\u0026ndash;56.\\u003c/span\\u003e\\u003c/li\\u003e \\u003cli\\u003e\\u003cspan\\u003eRichardson M, Moore DA, Gwernan-Jones R, et al. Non-pharmacological interventions for attention-deficit/hyperactivity disorder (ADHD) delivered in school settings: Systematic reviews of quantitative and qualitative research. Health technology assessment. 2015;19:1\\u0026ndash;470.\\u003c/span\\u003e\\u003c/li\\u003e \\u003cli\\u003e\\u003cspan\\u003eGaastra GF, Groen Y, Tucha L, Tucha O. The Effects of Classroom Interventions on Off-Task and Disruptive Classroom Behavior in Children with Symptoms of Attention-Deficit/Hyperactivity Disorder: A Meta-Analytic Review. PloS one. 2016;11:e0148841.\\u003c/span\\u003e\\u003c/li\\u003e \\u003cli\\u003e\\u003cspan\\u003eReichow B. Overview of meta-analyses on early intensive behavioral intervention for young children with autism spectrum disorders. J Autism Dev Disord. 2012;42:512\\u0026ndash;20.\\u003c/span\\u003e\\u003c/li\\u003e \\u003cli\\u003e\\u003cspan\\u003eFossum S, Handeg\\u0026aring;rd BH, Britt Drugli M. The Incredible Years Teacher Classroom Management Programme in Kindergartens: Effects of a Universal Preventive Effort. J Child Fam stud. 2017;26:2215\\u0026ndash;23.\\u003c/span\\u003e\\u003c/li\\u003e \\u003cli\\u003e\\u003cspan\\u003eNilsen S, Herlofsen C. National Regulations and Guidelines and the Local Follow-up in the Chain of Actions in Special Education. International journal of special education. 2012;27:136\\u0026ndash;47.\\u003c/span\\u003e\\u003c/li\\u003e \\u003cli\\u003e\\u003cspan\\u003eRussell AE, Ford T, Russell G. Socioeconomic Associations with ADHD: Findings from a Mediation Analysis. PloS one. 2015;10:e0128248.\\u003c/span\\u003e\\u003c/li\\u003e\\u003c/ol\\u003e\"}],\"fulltextSource\":\"\",\"fullText\":\"\",\"funders\":[],\"hasAdminPriorityOnWorkflow\":false,\"hasManuscriptDocX\":true,\"hasOptedInToPreprint\":true,\"hasPassedJournalQc\":\"\",\"hasAnyPriority\":false,\"hideJournal\":false,\"highlight\":\"\",\"institution\":\"\",\"isAcceptedByJournal\":true,\"isAuthorSuppliedPdf\":false,\"isDeskRejected\":\"\",\"isHiddenFromSearch\":false,\"isInQc\":false,\"isInWorkflow\":true,\"isPdf\":false,\"isPdfUpToDate\":true,\"isWithdrawnOrRetracted\":false,\"journal\":{\"display\":true,\"email\":\"info@researchsquare.com\",\"identity\":\"child-and-adolescent-psychiatry-and-mental-health\",\"isNatureJournal\":false,\"hasQc\":true,\"allowDirectSubmit\":false,\"externalIdentity\":\"caph\",\"sideBox\":\"Learn more about [Child and Adolescent Psychiatry and Mental Health](http://capmh.biomedcentral.com)\",\"snPcode\":\"13034\",\"submissionUrl\":\"https://submission.nature.com/new-submission/13034/3\",\"title\":\"Child and Adolescent Psychiatry and Mental Health\",\"twitterHandle\":\"@IACAPAP\",\"acdcEnabled\":true,\"dfaEnabled\":true,\"editorialSystem\":\"em\",\"reportingPortfolio\":\"BMC/SO AJ\",\"inReviewEnabled\":true,\"inReviewRevisionsEnabled\":true},\"keywords\":\"ADHD, ASD, Language difficulties, Behaviour problems, early childhood education and care, psycho-social intervention, special education, inattention, hyperactivity/impulsivity, oppositional behaviour, mood, anxiety, and communication, directed acyclic graph, hierarchical Bayesian modelling\",\"lastPublishedDoi\":\"10.21203/rs.3.rs-819337/v1\",\"lastPublishedDoiUrl\":\"https://doi.org/10.21203/rs.3.rs-819337/v1\",\"license\":{\"name\":\"CC BY 4.0\",\"url\":\"https://creativecommons.org/licenses/by/4.0/\"},\"manuscriptAbstract\":\"\\u003cp\\u003eBackground: Three to seven percent of pre-schoolers have developmental problems or child psychiatric disorders. Randomized controlled trials (RCTs) indicate that interventions in early childhood education and care improve long-term outcomes of children from disadvantaged backgrounds. It is unknown if effects generalize beyond the well-structured context of RCTs and to children who may not have a disadvantaged background but have developmental problems or psychiatric disorders.\\u0026nbsp;\\u003c/p\\u003e\\u003cp\\u003eMethods: We use data from the population-based Norwegian Mother, Father and Child Cohort Study, recruiting pregnant women from 1999 to 2009, with child follow-up from ages 6, 18, and 36 months to ages 5, 7, and 8 years. This sub-study included 2499 children with developmental problems or psychiatric disorders at age five. We investigate the effects of special educational assistance at age five on mother-reported internalizing, externalizing, and communication problems at age eight. We analyse bias due to treatment by indication with directed acyclic graphs, adjust for treatment predictors to reduce bias, and estimate effects in different patient groups and outcome domains with a hierarchical Bayesian model.\\u003c/p\\u003e\\u003cp\\u003eResults: In the adjusted analysis, pre-schoolers with special educational assistance had on average by 0.1 (0.04-0.16) standardised mean deviation fewer psycho-social difficulties in elementary school. Mean effect sizes varied between groups and outcomes.\\u003c/p\\u003e\\u003cp\\u003eConclusion: We estimate positive effects of educational assistance during the transition from preschool to the school years. It should therefore be considered as an intervention for pre-schoolers with developmental or behaviour problems. More research with improved measurements of treatment and outcomes is needed to identify success factors for their implementation.\\u003c/p\\u003e\",\"manuscriptTitle\":\"The Effect of Special Educational Assistance In Early Childhood Education And Care On Psycho-Social Difficulties In Elementary School Children\",\"msid\":\"\",\"msnumber\":\"\",\"nonDraftVersions\":[{\"code\":1,\"date\":\"2021-08-31 19:43:51\",\"doi\":\"10.21203/rs.3.rs-819337/v1\",\"editorialEvents\":[{\"type\":\"communityComments\",\"content\":0},{\"type\":\"decision\",\"content\":\"Major revision\",\"date\":\"2021-11-17T00:00:00+00:00\",\"index\":\"\",\"fulltext\":\"\"},{\"type\":\"editorInvitedReview\",\"content\":\"\",\"date\":\"2021-09-28T00:00:00+00:00\",\"index\":4,\"fulltext\":\"Recommendation: Reviewer's comments unavailable due to the journal's policy.\\n\"},{\"type\":\"editorInvitedReview\",\"content\":\"\",\"date\":\"2021-09-28T00:00:00+00:00\",\"index\":2,\"fulltext\":\"Recommendation: Reviewer's comments unavailable due to the journal's policy.\\n\"},{\"type\":\"editorInvitedReview\",\"content\":\"\",\"date\":\"2021-09-17T00:00:00+00:00\",\"index\":3,\"fulltext\":\"Recommendation: Reviewer's comments unavailable due to the journal's policy.\\n\"},{\"type\":\"editorInvitedReview\",\"content\":\"\",\"date\":\"2021-09-17T00:00:00+00:00\",\"index\":1,\"fulltext\":\"Recommendation: Reviewer's comments unavailable due to the journal's policy.\\n\"},{\"type\":\"reviewerAgreed\",\"content\":\"\",\"date\":\"2021-09-12T00:00:00+00:00\",\"index\":4,\"fulltext\":\"\"},{\"type\":\"reviewerAgreed\",\"content\":\"\",\"date\":\"2021-09-10T00:00:00+00:00\",\"index\":3,\"fulltext\":\"\"},{\"type\":\"reviewerAgreed\",\"content\":\"\",\"date\":\"2021-09-08T00:00:00+00:00\",\"index\":2,\"fulltext\":\"\"},{\"type\":\"editorInvitedReview\",\"content\":\"\",\"date\":\"2021-09-07T13:20:23+00:00\",\"index\":0,\"fulltext\":\"\"},{\"type\":\"reviewerAgreed\",\"content\":\"\",\"date\":\"2021-09-07T00:00:00+00:00\",\"index\":1,\"fulltext\":\"\"},{\"type\":\"reviewersInvited\",\"content\":\"\",\"date\":\"2021-09-06T02:26:53+00:00\",\"index\":\"\",\"fulltext\":\"\"},{\"type\":\"checksComplete\",\"content\":\"\",\"date\":\"2021-08-24T23:00:00+00:00\",\"index\":\"\",\"fulltext\":\"\"},{\"type\":\"editorInvited\",\"content\":\"\",\"date\":\"2021-08-24T23:00:00+00:00\",\"index\":\"\",\"fulltext\":\"\"},{\"type\":\"editorAssigned\",\"content\":\"\",\"date\":\"2021-08-19T14:42:04+00:00\",\"index\":\"\",\"fulltext\":\"\"},{\"type\":\"submitted\",\"content\":\"Child and Adolescent Psychiatry and Mental Health\",\"date\":\"2021-08-16T08:58:18+00:00\",\"index\":\"\",\"fulltext\":\"\"}],\"status\":\"published\",\"journal\":{\"display\":true,\"email\":\"info@researchsquare.com\",\"identity\":\"child-and-adolescent-psychiatry-and-mental-health\",\"isNatureJournal\":false,\"hasQc\":true,\"allowDirectSubmit\":false,\"externalIdentity\":\"caph\",\"sideBox\":\"Learn more about [Child and Adolescent Psychiatry and Mental Health](http://capmh.biomedcentral.com)\",\"snPcode\":\"13034\",\"submissionUrl\":\"https://submission.nature.com/new-submission/13034/3\",\"title\":\"Child and Adolescent Psychiatry and Mental Health\",\"twitterHandle\":\"@IACAPAP\",\"acdcEnabled\":true,\"dfaEnabled\":true,\"editorialSystem\":\"em\",\"reportingPortfolio\":\"BMC/SO AJ\",\"inReviewEnabled\":true,\"inReviewRevisionsEnabled\":true}}],\"origin\":\"\",\"ownerIdentity\":\"36b4d075-18c4-49d1-9c32-0c1d782cbbae\",\"owner\":[],\"postedDate\":\"August 31st, 2021\",\"published\":true,\"recentEditorialEvents\":[],\"rejectedJournal\":[],\"revision\":\"\",\"amendment\":\"\",\"status\":\"published-in-journal\",\"subjectAreas\":[{\"id\":6835569,\"name\":\"Pediatrics\"},{\"id\":6835570,\"name\":\"Psychiatry\"}],\"tags\":[],\"updatedAt\":\"2022-02-24T17:49:32+00:00\",\"versionOfRecord\":{\"articleIdentity\":\"rs-819337\",\"link\":\"https://doi.org/10.1186/s13034-022-00442-5\",\"journal\":{\"identity\":\"child-and-adolescent-psychiatry-and-mental-health\",\"isVorOnly\":false,\"title\":\"Child and Adolescent Psychiatry and Mental Health\"},\"publishedOn\":\"2022-02-24 17:49:32\",\"publishedOnDateReadable\":\"February 24th, 2022\"},\"versionCreatedAt\":\"2021-08-31 19:43:51\",\"video\":\"\",\"vorDoi\":\"10.1186/s13034-022-00442-5\",\"vorDoiUrl\":\"https://doi.org/10.1186/s13034-022-00442-5\",\"workflowStages\":[]},\"version\":\"v1\",\"identity\":\"rs-819337\",\"journalConfig\":\"researchsquare\"},\"__N_SSP\":true},\"page\":\"/article/[identity]/[[...version]]\",\"query\":{\"redirect\":\"/article/rs-819337\",\"identity\":\"rs-819337\",\"version\":[\"v1\"]},\"buildId\":\"_2-kVJe1T_tPrBINL-cwx\",\"isFallback\":false,\"isExperimentalCompile\":false,\"dynamicIds\":[84888],\"gssp\":true,\"scriptLoader\":[]}","source_license":"CC-BY-4.0","license_restricted":false}