Teacher-rated aggression and co-occurring behaviors and emotional problems among schoolchildren in four population-based European cohorts

This is a self-archived version of an original article. This version may differ from the original in pagination and typographic details. Author(s): Title: Year: Version: Copyright: Rights: Rights url: Please cite the original version: CC BY 4.0 https://creativecommons.org/licenses/by/4.0/ Teacher-rated aggression and co-occurring behaviors and emotional problems among schoolchildren in four population-based European cohorts © 2021 the Authors Published version Whipp, Alyce M.; Vuoksimaa, Eero; Bolhuis, Koen; de Zeeuw, Eveline L.; Korhonen, Tellervo; Mauri, Matteo; Pulkkinen, Lea; Rimfeld, Kaili; Rose, Richard J.; van Beijsterveldt, Catharina (Toos) E. M.; Bartels. Meike; Plomin. Robert; Tiemeier. Henning; Kaprio. Jaakko; Boomsma. Dorret, I. Whipp, Alyce M., Vuoksimaa, Eero, Bolhuis, Koen, de Zeeuw, Eveline L., Korhonen, Tellervo, Mauri, Matteo, Pulkkinen, Lea, Rimfeld, Kaili, Rose, Richard J., van Beijsterveldt, Catharina (Toos) E. M., Bartels. Meike, Plomin. Robert, Tiemeier. Henning, Kaprio. Jaakko, Boomsma. Dorret, I. (2021). Teacher-rated aggression and co-occurring behaviors and emotional problems among schoolchildren in four population-based European cohorts. PLoS ONE, 16(4), Article e0238667. https://doi.org/10.1371/journal.pone.0238667 2021 RESEARCH ARTICLE Teacher-rated aggression and co-occurring behaviors and emotional problems among schoolchildren in four population-based European cohorts Alyce M. Whipp 1 *, Eero Vuoksimaa 1 , Koen Bolhuis 2 , Eveline L. de Zeeuw 3 , Tellervo Korhonen 1 , Matteo Mauri 4 , Lea Pulkkinen 5 , Kaili Rimfeld 6 , Richard J. Rose 7 , Catharina (Toos) E. M. van Beijsterveldt 3 , Meike Bartels 3,8 , Robert Plomin 6 , Henning Tiemeier 9 , Jaakko Kaprio 1,10 , Dorret I. BoomsmaID 3,8 1Institute for Molecular Medicine Finland, HiLIFE, University of Helsinki, Helsinki, Finland, 2Department of Child and Adolescent Psychiatry, Erasmus Medical Center, Rotterdam, The Netherlands, 3Department of Biological Psychology, Faculty of Behavioural and Movement Sciences, Vrije Universiteit Amsterdam, Amsterdam, The Netherlands, 4University of Cagliari, Cagliari, Italy, 5Department of Psychology, University of Jyvaskyla, Jyvaskyla, Finland, 6Social, Genetic, and Developmental Psychiatry Centre, Institute of Psychiatry, Psychology, and Neuroscience, King’s College London, London, United Kingdom, 7Department of Psychological & Brain Sciences, Indiana University, Bloomington, Indiana, United States of America, 8Amsterdam Public Health Research Institute, Amsterdam, The Netherlands, 9Department of Social and Behavioral Science, Harvard TH Chan School of Public Health, Boston, Massachusetts, United States of America, 10 Department of Public Health, University of Helsinki, Helsinki, Finland *[email protected] Abstract Aggressive behavior in school is an ongoing concern. The current focus is on specific manifestations such as bullying, but the behavior is broad and heterogenous. Children spend a substantial amount of time in school, but their behaviors in the school setting tend to be less well characterized than at home. Because aggression may index multiple behavioral problems, we used three validated instruments to assess means, correlations and gender differences of teacher-rated aggressive behavior with co-occurring externalizing/internalizing problems and social behavior in 39,936 schoolchildren aged 7–14 from 4 population-based cohorts from Finland, the Netherlands, and the UK. Correlations of aggressive behavior were high with all other externalizing problems (r: 0.47–0.80) and lower with internalizing problems (r: 0.02–0.39). A negative association was observed with prosocial behavior (r: -0.33 to -0.54). Mean levels of aggressive behavior differed significantly by gender. Despite the higher mean levels of aggressive behavior in boys, the correlations were notably similar for boys and girls (e.g., aggressive-hyperactivity correlations: 0.51–0.75 boys, 0.47–0.70 girls) and did not vary greatly with respect to age, instrument or cohort. Thus, teacher-rated aggressive behavior rarely occurs in isolation; boys and girls with problems of aggressive behavior likely require help with other behavioral and emotional problems. Important to note, higher aggressive behavior is not only associated with higher amounts of other externalizing and internalizing problems but also with lower levels of prosocial behavior. PLOS ONE PLOS ONE | https://doi.org/10.1371/journal.pone.0238667 April 29, 2021 1 / 18 a1111111111 a1111111111 a1111111111 a1111111111 a1111111111 OPEN ACCESS Citation: Whipp AM, Vuoksimaa E, Bolhuis K, de Zeeuw EL, Korhonen T, Mauri M, et al. (2021) Teacher-rated aggression and co-occurring behaviors and emotional problems among schoolchildren in four population-based European cohorts. PLoS ONE 16(4): e0238667. https://doi. org/10.1371/journal.pone.0238667 Editor: Gerard Hutchinson, University of the West Indies at Saint Augustine, TRINIDAD AND TOBAGO Received: September 18, 2020 Accepted: March 31, 2021 Published: April 29, 2021 Peer Review History: PLOS recognizes the benefits of transparency in the peer review process; therefore, we enable the publication of all of the content of peer review and author responses alongside final, published articles. The editorial history of this article is available here: https://doi.org/10.1371/journal.pone.0238667 Copyright: ©2021 Whipp et al. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited. Data Availability Statement: The data that support the findings of this study are not publicly available due to privacy or ethical restrictions. FinnTwin12 Introduction Aggressive behavior in school is a persistent topic of concern, with bullying, genderand sexuality-based misconduct, and extreme violence (e.g., school fights, stabbings, shootings) currently garnering the most public attention [1,2]. While these specific manifestations of aggression are important to understand and manage for the safety of all in the school environment, broadly defined aggression may be an important marker for a wider set of behavioral problems that co-occur with it. Aggressive behavior itself is heterogenous in nature and can involve overt and covert as well as planned and unplanned actions and rarely occurs in isolation [3–5]. All children express such behaviors to varying degrees across development. Among school-aged children, aggressive behavior is associated with relationship quality among their peers, teachers, and families, as well as their eductional attainment, risk for substance abuse and other psychiatric disorders, and risk for partipation in criminal activities [6–8]. Aggressive behavior, in general, is often characterized and studied via parental or self ratings, with teacher ratings less often collected in epidemiologic or clinical research. Research from the past several decades has shown that an individual’s aggressive behavior is often situational (e.g., present at school, but not at home) and that assessments of behavioral and emotional problems do not correlate well between raters [9–12]. In the school setting, teacher, peer, and self ratings have been used to characterize behavioral problems; peer and teacher ratings are more strongly correlated compared to other observer correlations [9,13], and self ratings are commonly used in later adolescence. Teacher-rated measures of behavioral problems have also shown high reliability [13–15]. Furthermore, studies have shown that teacher ratings of problem behaviors have often been more useful than parent ratings in diagnostic and predictive outcomes, including psychiatric disorders and criminality [7,10,16,17]. Teachers’ ability to observe children in a structured setting and among peers of similar ages and abilities provides them with a valuable comparison-base, making their insight important. In investigating teacher-rated aggressive behavior, we also need to consider co-occuring behaviors and emotional problems. Aggressive behavior often co-occurs with other externalizing behaviors (e.g., hyperactivity) [5,18–20]. Internalizing problems, such as depression or anxiety, are also shown to moderately co-occur with aggressive behavior [5,21–24]. Furthermore, children with aggression and co-morbidities often have more than one co-morbidity, and, compared to aggressive children without co-morbidities, have poorer outcomes [8,18, 25,26]. Lastly, aggressive behavior has also been shown to be negatively associated with prosocial behavior [27,28]. Once thought to be opposite ends of the spectrum [27], prosocial behavior now appears to have a more complex relationship with aggressive behavior, with suggestions that prosocial behavior can be protective against future negative outcomes in aggressive children [29] and that there is possibly a goal-oriented prosocial behavior subtype positively associated with aggressive behavior [30]. In studying aggressive behavior, as well as related externalizing, internalizing and prosocial behavior, gender differences have played a large and complex role in our understanding. Early research on aggressive behavior focused only or mainly on boys, although studies in recent decades have greatly enriched our knowledge regarding both genders. Distinctions between direct aggression as being higher among boys and indirect aggression being higher among girls have generally given way to an understanding that both genders engage in both types of aggression, and that at least for indirect aggression the gender differences, if any, are small [31, 32]. Furthermore, a study by Nivette et al. [33] indicates that in societies that experience high gender inequality, differences in physical aggression by gender are minimal. In addition to mean differences, it is also important to investigate if behavioral problems and prosocial behavior are similarly or differently related to aggression in boys and girls. PLOS ONE Teacher-rated aggression and co-occurring behaviors and problems among schoolchildren PLOS ONE | https://doi.org/10.1371/journal.pone.0238667 April 29, 2021 2 / 18 data are available through the Institute for Molecular Medicine Finland (FIMM) Data Access Committee (DAC) for authorized researchers who have IRB/ethics approval and an institutionally approved study plan. For more details, please contact the FIMM DAC ([email protected]). The Generation R datasets analyzed during the current study are not publicly available due to the terms and conditions participants agree to when they participate in Generation R, but are available from data management on reasonable request ([email protected]). Applications for data and information on the access policy for the Netherlands Twin Register may be found at: https://tweelingenregister.vu.nl/ submitting-a-data-sharing-request. The Twins Early Development Study’s data access policy can be found at the following link https://www.teds.ac. uk/researchers/teds-data-access-policy. Funding: This work is part of the ACTION consortium which is supported by funding from the European Union Seventh Framework Programme (FP7/2007-2013) under grant agreement no. 602768. FT12: Data collection has been supported by the National Institute of Alcohol Abuse and Alcoholism (grants AA-12502, AA00145, and AA-09203 to RJR) and the Academy of Finland (grants 100499, 205585, 118555, 141054 and 264146 to JK). JK has been supported by the Academy of Finland (grants 308248, 312073). GENR: This work was supported by the Netherlands Organization for Scientific Research (NWO-grant 016.VICI.170.200) to HT, and the Sophia Children’s Hospital Research Foundation (research fellowship grant 921) to KB. Super computing resources were made possible through the NWO Physical Sciences Division (surfsara.nl). The first phase of the Generation R Study is made possible by financial support from the Erasmus Medical Centre, Rotterdam; the Erasmus University Rotterdam; The Netherlands Organization for Health Research and Development (ZonMw). NTR: Data collection in the NTR was funded by the Netherlands Organization for Science (NWO): Twin-family database for behavior genetics and genomics studies (NWO-480-04-004); Gravitation program of the Dutch Ministry of Education, Culture, and Science and the Netherlands Organization for Scientific Research (NWO024.001.003). ‘Longitudinal data collection from teachers of Dutch twins and their siblings’ (NWO481-08-011); ‘Twin-family study of individual differences in school achievement’ (NWO-056-32010); ZonMW “Genetic influences on stability and change in psychopathology from childhood to young adulthood” (NWO-912-10-020); “Netherlands Twin Registry Repository” (NWO- Regarding the school setting, research has often focused on bullying or psychiatric aggression diagnoses (e.g., conduct disorder, oppostional-defiant disorder) [19,22,34,35], with less attention on general, non-pathological levels of aggressive behavior and co-occuring behaviors. To shed light on the phenotype of aggressive behavior in schools and how common co-occuring behaviors generally are, we carried out a unique study in four large population-based cohorts that assembled teacher ratings of schoolchildren by using three validated teacher-rating instruments. This study’s overall objective was to characterize the levels and associations of teacher-rated aggressive behavior with co-occurring behaviors of children aged 7–14. Large datasets from collaborating population-based cohorts of children from Finland, the Netherlands, and the UK were analyzed. Specific aims were: 1) to report the mean levels of aggressive behavior and other behaviors as well as emotional problems as assessed by teachers, 2) to examine associations (co-occurrence) of aggressive behavior with other behaviors and emotional problems, and 3) to assess gender differences in the mean levels and associations of aggressive behavior and co-occurring behaviors and emotional problems. Materials and methods The datasets for this investigation were obtained through the collaboration of the ACTION (Aggression in Children: Unravelling gene-environment interplay to inform Treatment and InterventiON strategies; http://www.action-euproject.eu/) consortium [5]. Of the seven large child/adolescent cohorts brought together in ACTION, four had collected teacher rating data. In total, the data included 39,936 teacher ratings on children at ages 7, 9, 10, 12, and 14 (48.9% boys) from Finland, the Netherlands, and the UK, with some children observed at two or more ages. As in Bartels et al. [5], in the cohorts that included twin data one twin per family was randomly selected for analysis. Individuals were excluded if they had an illness or disability that interfered with their daily functioning (e.g., Down syndrome or severe neurodevelopmental disorder), and if they were missing substantial data from one of the examined subscales from cohort-respective behavioral and emotional problem questionnaires (see also: http://www. action-euproject.eu/content/data-protocols). Brief cohort and behavioral questionnaire descriptions are presented here (see S1 Text for further details on teacher rating collections and the school systems in Finland, the Netherlands, and the UK). Cohort descriptions The FinnTwin12 (FT12) dataset was established in Finland from the cohort of twins born 1983–87 [36]. It is a population-based twin study aimed at examining health-related behaviors and their precursors. Data were collected at ages 12, 14, 17, and 22. Teacher ratings on behavioral and emotional problems were collected at ages 12 and 14. Response rates were 93% and 94% for age 12 and 14 teacher ratings, respectively. The Generation R (GENR) study is a population-based birth cohort, established in the Netherlands from children born 2002–06 in the city of Rotterdam and surrounding areas [37], aimed at examining growth, development and health from fetal life to young adulthood. Data were collected during pregnancy, at birth, and frequently throughout childhood (currently up to age 13). Teacher ratings on behavioral and emotional problems were collected at child mean age 7 years; the response rate was 77%. The Netherlands Twin Register (NTR) was established in the Netherlands in 1987 and remains ongoing. The register includes adults and young twins who were registered by their parents shortly after birth and who are followed longitudinally to examine, in particular, behavioral development and psychopathology [38]. Data are collected at ages 1, 2, 3, 5, 7, 9, 10, 12, 14, 16, and 18 years (at which point twins move into the adult twin register). In school year PLOS ONE Teacher-rated aggression and co-occurring behaviors and problems among schoolchildren PLOS ONE | https://doi.org/10.1371/journal.pone.0238667 April 29, 2021 3 / 18 480-15-001/674). DIB would like to acknowledge the KNAW Academy Professor Award (PAH/6635). TEDS: TEDS is supported by a program grant to RP from the UK Medical Research Council (MR/ M021475/1). No funders had any involvement in the conduct of this research, including in the study design, data collection, analysis and interpretation of the data, the writing of the report, and the decision to submit to the article for publication. Competing interests: All authors declare no conflicts of interest. 1999–2000, the NTR began collecting teacher ratings for 7, 10 and 12 year old twins; the average response rate was ~60%. The Twins Early Development Study (TEDS) was established in the UK from the cohort of twins born 1994–96 [39]. It is a UK-representative longitudinal twin study aimed at examining language, cognitive, and behavioral development. Data were collected at ages 2, 3, 4, 7, 8, 9, 10, 12, 14, 16, 18, and 21. Teacher ratings on behavioral and emotional problems were collected at ages 7, 9, and 12; response rates were 85%, 76%, 78%, respectively. Ethical statement All data in the current investigation were collected under protocols that have been approved by the appropriate ethics committees, and studies were performed in accordance with the ethical standards established in the 1964 Declaration of Helsinki and its later amendments. For FT12, ethics approval was obtained from the Helsinki University Hospital Ethics Committee (HUS/845/2017) and the Indiana University Bloomington IRB (IRB-IUB, IRB00000222). For GENR, study protocols were approved by the Medical Ethics Committee of the Erasmus Medical Center (NL55105.078.15). For NTR, ethics approval came from the Central Ethics Committee on Research Involving Human Subjects of the VU University Medical Center, Amsterdam, an Institutional Review Board (IRB) certified by the U.S. Office of Human Research Protections (IRB00002991 under Federal-wide Assurance FWA00017598; IRB/institute codes, NTR 03–180). For TEDS, ethical approval was provided by the King’s College London ethics committee (reference number: PNM/09/10-104). All participants (or their guardians) provided written informed consent before participation in their respective cohorts. Study questionnaires The Multidimensional Peer Nomination Inventory (MPNI), used by the FT12 cohort, was originally developed as a tool for rating peers on childhood social behavior. However, it has been adapted and modified to collect ratings from other raters, including teachers [13]. It is a 37-item questionnaire with 6 of the subscales used here: aggression (6 items), depression (5 items), hyperactivity–impulsivity (7 items), inattention (4 items), prosocial behavior (12 items), and social anxiety (2 items). The aggression scale includes both direct (e.g., calls people names when angry at them) and indirect (e.g., spreads rumors) aggression items. Although further subscale scoring was not performed, the MPNI internal structure based on factor analysis indicates aggression, hyperactivity–impulsivity and inattention subscales as part of a behavioral problem/externalizing subscale, and depression and social anxiety subscales as part of an emotional problems/internalizing subscale. Each item on the teacher rating questionnaire has four response choices (from ‘not observed in child’ to ‘clearly observed’). Response choices are scored 0–3, and subscales are formed by taking the mean of all items in the subscale (no missing values were allowed). The internal consistency (Cronbach’s alpha) values of the MPNI teacher ratings range from 0.69 (social anxiety scale among girls) to 0.94 (hyperactivityimpulsivity and externalizing behavior for boys), indicating high reliability [13]. The Strengths and Difficulties Questionnaire (SDQ), used by the TEDS cohort, is a 25-item questionnaire that measures common childhood mental health problems [40]. The five subscales of the SDQ are conduct problems (5 items), emotional problems (5 items), hyperactivity (5 items), peer problems (5 items), and prosocial (5 items). The SDQ recognizes conduct problems and hyperactivity subscales as part of an externalizing subscale, and emotional and peer problems subscales as part of an internalizing subscale. For this study, we use ‘conduct problems’ as a proxy for aggressive behavior, and ‘emotional problems’ as a proxy for anxiety problems, as in Bartels et al. [5]. The conduct problems scale includes both aggression items (e.g., PLOS ONE Teacher-rated aggression and co-occurring behaviors and problems among schoolchildren PLOS ONE | https://doi.org/10.1371/journal.pone.0238667 April 29, 2021 4 / 18 often fights with other children) and rule-breaking type of items (e.g., often lies or cheats). Each item on the questionnaire has three response choices: ‘not true’, ‘somewhat true’, and ‘certainly true’. Response choices range from 0–2 and are coded so that higher scores represent greater risk for the behavior attribute, and subscale scores are derived as a scaled mean score when at least 3 of the 5 items in a subscale are non-missing. The internal consistency (Cronbach’s alpha) values of the SDQ teacher ratings range from 0.70 (peer problems) to 0.88 (hyperactivity-inattention), indicating high reliability [41]. The Teacher Report Form (TRF), part of the Achenbach System of Empirical-Based Assessment’s (ASEBA), was collected by the GENR and NTR cohorts and is a 112-item questionnaire that measures childhood behavioral and emotional problems [42]. The 8 syndrome subscales used here are aggressive behavior (20 items), anxious/depressed (16 items), attention problems (26 items), rule-breaking behavior (12 items), social problems (11 items), somatic complaints (9 items), thought problems (1 item), and withdrawn/depressed (8 items). The aggressive behavior scale includes, for example, both direct actions (e.g., physically attacks people) and broader behaviors (e.g., easily frustrated). The TRF recognizes aggressive behavior and rule-breaking behavior as externalizing problems, and anxious/depressed, withdrawn/depressed and somatic complaints as internalizing problems. In this study, the attention problems subscale will also be grouped under externalizing problems. Each item on the questionnaire has three response choices: ‘not true’, ‘somewhat or sometimes true’, and ‘very true or often true’. Response choices are scored 0–2, and items are summed to created sum scores of individual subscales. A small number of missing values per subscale (depending on the total number of items per subscale) was allowed by replacing the missing values with the mean item score of a subscale. The mean internal consistency (Cronbach’s alpha) values of the TRF teacher ratings used in 21 countries range from 0.65 (thought problems) to 0.93 (attention problems), indicating high reliability [43]. Analyses Data from the FT12, NTR, and TEDS cohorts were analyzed at one site (by AMW) in Stata version 15 (Stata Corporation, College Station, TX, USA), while data from GENR were analyzed locally (by KB) using R version 3.3.2. The analyses followed a standard operating procedure [5] to ensure uniform data handling and analysis. First, means, standard deviations (SD) and standard errors (SE) were obtained for all subscales for each age and cohort, separately by gender. T-tests were performed to determine if gender differences existed (p-value <0.05 was considered significant), and effect sizes were calculated as Cohen’s dvalues (with positive values indicating boys have larger mean levels than girls and vice versa). Effect sizes are emphasized over statistical significance since our sample sizes are large and thus significance is expected for many relationships. Next, Pearson correlations between the subscales were computed for each age and cohort, separately by gender. To formally test gender interactions, as well as to assess the effect size (betas) and amount of variance (R 2 values) in aggression explained by co-occurring behaviors, we ran linear regression models separately for each age and cohort. Before modeling, the subscale scores were standardized (mean = 0, SD = 1) to allow for comparability of the same questionnaire across different ages or cohorts where possible. Initial modeling included aggressive behavior as the dependent variable and one subscale score as the independent variable. There were three types of subscale scores in the initial models: 1) the externalizing problems subscale(s) with the highest correlation with aggressive behavior (e.g., hyperactivity); 2) the internalizing problems subscale(s) with the highest correlation with aggressive behavior (e.g., depression); and 3) the prosocial subscale (if available). For each model, data from boys and girls were modeled separately, after testing for gender interactions. Lastly, to examine multiple co-occuring behaviors with aggression, PLOS ONE Teacher-rated aggression and co-occurring behaviors and problems among schoolchildren PLOS ONE | https://doi.org/10.1371/journal.pone.0238667 April 29, 2021 5 / 18 regression modeling was performed with aggressive behavior as the dependent variable and the two (or three, if available) subscale measures from the initial models simultaneously modeled, modeled separately for gender after testing for gender interactions. Results We examined 39,936 teacher ratings on children: 3627 observations from FT12, 4512 observations from GENR, 18,569 observations from NTR, and 13,228 observations from TEDS. There were 17,267 observations of 7-year-olds (49.3% boys), 2762 of 9-year-olds (46.9% boys), 6582 of 10-year-olds (49.6% boys), 11,884 of 12-year-olds (48.4% boys), and 1441 of 14-year-olds (48.4% boys). An interactive summary of all results can be found at (http://www.actioneuproject.eu/TeacherRatingsChildAggression). Mean scores Across all cohorts, mean levels were higher for boys than girls in all externalizing subscale scores, with Cohen’s dvalues ranging 0.31–0.69 (Fig 1A–1C and S1 Table). Results regarding internalizing problems were somewhat cohort dependent, with smaller gender effect sizes than for externalizing problems and prosocial behaviors (Fig 1A–1C and S1 Table). In FT12, girls had slightly higher levels of social anxiety compared to boys (Cohen’s d ranged from -0.21 to -0.23), with boys and girls being more similar for depression (Cohen’s d ranged from -0.09 to -0.12). In GENR, NTR and TEDS, for all internalizing problems, boys and girls generally had similar levels (Cohen’s dranged from -0.09 to 0.12). For all cohorts, mean differences between boys and girls were found in all social behaviors, with girls having higher prosocial scores (Cohen’s dranged from -0.37 to -0.63), and boys having slightly more social/peer problems (Cohen’s drange: 0.10–0.24). Co-occurrence of aggression and other behaviors and problems In general, correlation patterns of aggressive behavior with other co-occurring behaviors were similar between genders and across cohorts and ages (Fig 2A–2C and S2 Table). The strength of the correlations of aggressive behavior with other externalizing problems was substantial (Fig 2A–2C and S2 Table). Correlations between aggressive behavior and hyperactivity/attention problems ranged 0.51–0.75 for boys and 0.47–0.70 for girls. Correlations of aggressive behavior and rule-breaking behavior (from GENR and NTR) ranged 0.71– 0.80 for boys and 0.63–0.74 for girls. Correlations of aggressive behavior and internalizing problems ranged from small to moderate (Fig 2A–2C and S2 Table). Regarding depressive symptoms, correlations with aggressive behavior ranged 0.16–0.27 for boys and 0.15–0.29 for girls. Correlations of general anxiety problems with aggressive behavior (from GENR, NTR, and TEDS) ranged 0.17–0.39 in boys and 0.10–0.33 in girls, whereas social anxiety and aggressive behavior (from FT12) correlations ranged from -0.02 to -0.10 for boys and girls. Correlations of aggressive behavior and social behaviors were moderate (Fig 2A–2C and S2 Table). Prosocial and aggressive behavior correlations (from FT12 and TEDS) ranged from -0.44 to -0.54 for boys and -0.33 to -0.44 for girls. Aggressive behavior and social/peer problems (from GENR, NTR, and TEDS) ranged 0.27–0.65 for boys and 0.26–0.65 for girls. Regression modeling In linear regression modeling (i.e., aggressive behavior as the dependent and one subscale as the independent variable), gender was significantly associated with aggression. Furthermore, PLOS ONE Teacher-rated aggression and co-occurring behaviors and problems among schoolchildren PLOS ONE | https://doi.org/10.1371/journal.pone.0238667 April 29, 2021 6 / 18 PLOS ONE Teacher-rated aggression and co-occurring behaviors and problems among schoolchildren PLOS ONE | https://doi.org/10.1371/journal.pone.0238667 April 29, 2021 7 / 18 all GENR and NTR and nearly all TEDS models indicated significant gender interaction terms (Table 1A–1C). In contrast, half of the FT12 models did not indicate significant gender interaction. Regarding model R 2 values (% of variance in dependent variable explained by independent variables), externalizing models were consistently largest (boy range: 0.26–0.63; girl range: 0.22–0.54). For internalizing models, R 2 values were small (boy range: 0.03–0.15; girl range: 0.01–0.11). For prosocial models, R 2 values ranged 0.11–0.29 (boy range: 0.19–0.29; girl range: 0.11–0.19). In further regression modeling (i.e., multiple subscales included simultaneously as independent variables), gender interactions were generally significant. R 2 values generally did not differ from those in externalizing-only models (S3 Table). However, independent variables in these analyses were generally all significant, though with smaller effect sizes compared to initial models. Discussion This study provides a summary of average levels and co-occurence of teacher-rated aggressive behavior and other behaviors and emotional problems for schoolchildren ages 7–14 in the European school setting. Although it is commonly assumed that aggressive behavior at school is associated with these other problems and behaviors, this is one of the few studies to look at large, population-based samples with teacher ratings of behaviors across multiple European countries. Results indicate that teacher-rated behavior patterns are quite similar across the different cohorts of Finland, the Netherlands, and the UK. We show that, as expected, the levels of aggressive behavior are statistically significantly different by gender, however, the effect sizes are only moderate. We also see that aggression often co-occurs with other behavioral and emotional difficulties, in both boys and girls, and that these correlations are quite similar between the genders. Regression modeling indicated that much of the variation (R 2 ) in aggressive behavior levels was explained by other co-occurring externalizing problems, though prosocial models also had rather large R 2 values in initial individual models. Modeling multiple co-occurring behaviors simultaneously indicated that children with aggressive behavior often have not only one co-occurring problem behavior, but multiple co-occurring problems (including low prosocial skills). Regarding co-occurence of teacher-rated aggressive behavior with other externalizing problems, we see consistent similarities in the gender patterns. Although boys had, as expected, higher levels and associations of aggression and other externalizing problems compared to girls, correlations between aggression and other externalizing behaviors were very similar (r differences �0.1 between boys and girls). In this respect, we can point to another NTR cohort study regarding gender differences in ADHD diagnosis and comorbidity using teacher ratings [20] in which boys and girls had similar comorbidity profiles and school impairment, however, girls were less likely than boys to be identified by teachers as disruptive and referred for treatment. Similarly, conduct disorder and oppositional defiant disorder have both been more likely to be attributed to boys than girls among teacher ratings, compared to parent ratings [44,45]. Previous studies have noted valid rater differences due to situational aggressive behavior [12], reflected in known low inter-rater agreement [9–11]. However, Stanger et al. [46] indicated that teacher ratings of externalizing problems alone were capable of predicting Fig 1. (a-c) Means and standard errors (SEs) of behavioral scales, separated by gender, age, cohort and behavioral questionnaire. a. MPNI questionnaire (FT12); Agg = aggression, Dep = depression, Hyp-Imp = hyperactivityimpulsivity, Inatt = inattention, Soc Anx = social anxiety. b. TRF questionnaire (GENR and NTR); AGG = aggression, ANX = anxious/depressed, AP = attention problems, RB = rule-breaking, SOC = social problems, SOM = somatic problems, TP = thought problems, WIT = withdrawn/depressed. c. SDQ questionnaire (TEDS). https://doi.org/10.1371/journal.pone.0238667.g001 PLOS ONE Teacher-rated aggression and co-occurring behaviors and problems among schoolchildren PLOS ONE | https://doi.org/10.1371/journal.pone.0238667 April 29, 2021 8 / 18 Data curation: Alyce M. Whipp, Koen Bolhuis, Eveline L. de Zeeuw, Richard J. Rose, Catharina (Toos) E. M. van Beijsterveldt, Robert Plomin, Henning Tiemeier. Formal analysis: Alyce M. Whipp, Koen Bolhuis. Investigation: Alyce M. Whipp, Eero Vuoksimaa, Dorret I. Boomsma. Methodology: Alyce M. Whipp, Eero Vuoksimaa, Tellervo Korhonen, Lea Pulkkinen, Kaili Rimfeld, Meike Bartels, Jaakko Kaprio, Dorret I. Boomsma. Resources: Eveline L. de Zeeuw, Matteo Mauri. Supervision: Eero Vuoksimaa, Tellervo Korhonen, Lea Pulkkinen, Jaakko Kaprio, Dorret I. Boomsma. Visualization: Matteo Mauri. Writing – original draft: Alyce M. Whipp, Eero Vuoksimaa. Writing – review & editing: Alyce M. Whipp, Eero Vuoksimaa, Koen Bolhuis, Eveline L. de Zeeuw, Tellervo Korhonen, Matteo Mauri, Lea Pulkkinen, Kaili Rimfeld, Richard J. Rose, Catharina (Toos) E. M. van Beijsterveldt, Meike Bartels, Robert Plomin, Henning Tiemeier, Jaakko Kaprio, Dorret I. Boomsma. References 1. United Nations Educational, S.a.C.O.U., Behind the numbers: Ending school violence and bullying. 2019, UNESCO Publishing: Paris. 2. OECD, PISA 2015 Results (Volume III): Students’ Well-Being, in PISA. 2017: Paris. 3. Pulkkinen, L., Longitudinal Study of Personality and Social Development: Insights about aggression after five decades, in The Cambridge Handbook of Violent Behavior and Aggression, 2nd Edition, D.J. F. A. T. Vazsonyi, & M. DeLisi, Editor. 2018, Cambridge University Press: Cambridge, UK. p. 31–51. 4. Vitaro F., Brendgen M., and Barker E.D., Subtypes of aggressive behaviors: a developmental perspective. Int J Behav Devel, 2006. 30(1): p. 1–19. 5. Bartels M., et al., Childhood aggression and the co-occurrence of behavioural and emotional problems: results across ages 3–16 years from multiple raters in six cohorts in the EU-ACTION project. Eur Child Adolesc Psychiatry, 2018. 27(9): p. 1105–1121. https://doi.org/10.1007/s00787-018-1169-1 PMID: 29845340 6. Farrington D.P., The development of offending and antisocial behaviour from childhood: key findings from the Cambridge Study in Delinquent Development. J Child Psychol Psychiatry, 1995. 36(6): p. 929–64. https://doi.org/10.1111/j.1469-7610.1995.tb01342.x PMID: 7593403 7. Whipp A.M., et al., Early adolescent aggression predicts antisocial personality disorder in young adults: a population-based study. Eur Child Adolesc Psychiatry, 2019. 28(3): p. 341–350. https://doi.org/10. 1007/s00787-018-1198-9 PMID: 30019148 8. Pulkkinen L., Human Development: From Middle Childhood to Middle Adulthood. 2017, New York: Routledge. 9. Achenbach T.M., McConaughy S.H., and Howell C.T., Child/adolescent behavioral and emotional problems: implications of cross-informant correlations for situational specificity. Psychol Bull, 1987. 101(2): p. 213–32. PMID: 3562706 10. Verhulst F.C., Koot H.M., and Van der Ende J., Differential predictive value of parents’ and teachers’ reports of children’s problem behaviors: a longitudinal study. J Abnorm Child Psychol, 1994. 22(5): p. 531–46. https://doi.org/10.1007/BF02168936 PMID: 7822627 11. De Los Reyes A. and Kazdin A.E., Informant discrepancies in the assessment of childhood psychopathology: a critical review, theoretical framework, and recommendations for further study. Psychol Bull, 2005. 131(4): p. 483–509. https://doi.org/10.1037/0033-2909.131.4.483 PMID: 16060799 12. Rettew D.C., et al., When parent and teacher ratings don’t agree: the Tracking Adolescents’ Individual Lives Survey (TRAILS). J Child Adolesc Psychopharmacol, 2011. 21(5): p. 389–97. https://doi.org/10. 1089/cap.2010.0153 PMID: 22040184 PLOS ONE Teacher-rated aggression and co-occurring behaviors and problems among schoolchildren PLOS ONE | https://doi.org/10.1371/journal.pone.0238667 April 29, 2021 15 / 18 13. Pulkkinen L., Kaprio J., and Rose R.J., Peers, teachers and parents as assessors of the behavioural and emotional problems of twins and their adjustment: the Multidimensional Peer Nomination Inventory. Twin Res, 1999. 2(4): p. 274–85. https://doi.org/10.1375/136905299320565762 PMID: 10723806 14. Polderman T.J., et al., Genetic analyses of teacher ratings of problem behavior in 5-year-old twins. Twin Res Hum Genet, 2006. 9(1): p. 122–30. https://doi.org/10.1375/183242706776402975 PMID: 16611477 15. Verhulst F.C., Dekker M.C., and van der Ende J., Parent, teacher and self-reports as predictors of signs of disturbance in adolescents: whose information carries the most weight? Acta Psychiatr Scand, 1997. 96(1): p. 75–81. https://doi.org/10.1111/j.1600-0447.1997.tb09909.x PMID: 9259229 16. Carbonneau R., et al., Can teachers’ behavior ratings be used to screen early adolescent boys for psychiatric diagnoses? Psychopathology, 2005. 38(3): p. 112–23. https://doi.org/10.1159/000085773 PMID: 15897681 17. Hodgins S., et al., Teachers’ ratings of childhood behaviours predict adolescent and adult crime among 3016 males and females. Can J Psychiatry, 2013. 58(3): p. 143–50. https://doi.org/10.1177/ 070674371305800304 PMID: 23461885 18. Verhulst F.C. and van der Ende J., "Comorbidity" in an epidemiological sample: a longitudinal perspective. J Child Psychol Psychiatry, 1993. 34(5): p. 767–83. https://doi.org/10.1111/j.1469-7610.1993. tb01070.x PMID: 8340444 19. August G.J., et al., Prevalence of ADHD and comorbid disorders among elementary school children screened for disruptive behavior. J Abnorm Child Psychol, 1996. 24(5): p. 571–95. https://doi.org/10. 1007/BF01670101 PMID: 8956085 20. Derks E.M., Hudziak J.J., and Boomsma D.I., Why more boys than girls with ADHD receive treatment: a study of Dutch twins. Twin Res Hum Genet, 2007. 10(5): p. 765–70. https://doi.org/10.1375/twin.10. 5.765 PMID: 17903118 21. van den Oord E.J., Verhulst F.C., and Boomsma D.I., A genetic study of maternal and paternal ratings of problem behaviors in 3-year-old twins. J Abnorm Psychol, 1996. 105(3): p. 349–57. https://doi.org/ 10.1037//0021-843x.105.3.349 PMID: 8772005 22. Yang H.J., Chen W.J., and Soong W.T., Rates and patterns of comorbidity of adolescent behavioral syndromes as reported by parents and teachers in a Taiwanese nonreferred sample. J Am Acad Child Adolesc Psychiatry, 2001. 40(9): p. 1045–52. https://doi.org/10.1097/00004583-200109000-00013 PMID: 11556628 23. Willner C.J., Gatzke-Kopp L.M., and Bray B.C., The dynamics of internalizing and externalizing comorbidity across the early school years. Dev Psychopathol, 2016. 28(4pt1): p. 1033–1052. https://doi.org/ 10.1017/S0954579416000687 PMID: 27739391 24. McConaughy S.H. and Skiba R.J., Comorbidity of Externalizing and Internalizing Problems. School Psychology Review, 1993. 22(3): p. 421–436. 25. Fontaine N., et al., Girls’ hyperactivity and physical aggression during childhood and adjustment problems in early adulthood: a 15-year longitudinal study. Arch Gen Psychiatry, 2008. 65(3): p. 320–8. https://doi.org/10.1001/archgenpsychiatry.2007.41 PMID: 18316678 26. Schaeffer C.M., et al., Modeling growth in boys’ aggressive behavior across elementary school: links to later criminal involvement, conduct disorder, and antisocial personality disorder. Dev Psychol, 2003. 39 (6): p. 1020–35. https://doi.org/10.1037/0012-1649.39.6.1020 PMID: 14584982 27. Eron L. and Huesmann L., The relation of prosocial behavior to the development of aggression and psychopathology. Aggress Behav, 1984. 10: p. 201–211. 28. Milledge S.V., et al., Peer relationships and prosocial behaviour differences across disruptive behaviours. Eur Child Adolesc Psychiatry, 2019. 28(6): p. 781–793. https://doi.org/10.1007/s00787-0181249-2 PMID: 30387006 29. Kokko K. and Pulkkinen L., Aggression in childhood and long-term unemployment in adulthood: a cycle of maladaptation and some protective factors. Dev Psychol, 2000. 36(4): p. 463–72. https://doi.org/10. 1037//0012-1649.36.4.463 PMID: 10902698 30. Boxer P., Tisak M.S., and Goldstein S.E., Is It Bad to Be Good? An Exploration of Aggressive and Prosocial Behavior Subtypes in Adolescence. Journal of Youth and Adolescence, 2004. 33: p. 91–100. 31. Card N.A., et al., Direct and indirect aggression during childhood and adolescence: a meta-analytic review of gender differences, intercorrelations, and relations to maladjustment. Child Dev, 2008. 79(5): p. 1185–229. https://doi.org/10.1111/j.1467-8624.2008.01184.x PMID: 18826521 32. Cleverley K., et al., Developmental trajectories of physical and indirect aggression from late childhood to adolescence: sex differences and outcomes in emerging adulthood. J Am Acad Child Adolesc Psychiatry, 2012. 51(10): p. 1037–51. https://doi.org/10.1016/j.jaac.2012.07.010 PMID: 23021479 33. Nivette A., et al., Sex differences in adolescent physical aggression: Evidence from sixty-three low-and middle-income countries. Aggress Behav, 2018. https://doi.org/10.1002/ab.21799 PMID: 30281153 PLOS ONE Teacher-rated aggression and co-occurring behaviors and problems among schoolchildren PLOS ONE | https://doi.org/10.1371/journal.pone.0238667 April 29, 2021 16 / 18 34. Verlinden M., et al., Preschool Attention-Deficit/Hyperactivity and Oppositional Defiant Problems as Antecedents of School Bullying. J Am Acad Child Adolesc Psychiatry, 2015. 54(7): p. 571–9. https:// doi.org/10.1016/j.jaac.2015.05.002 PMID: 26088662 35. Sourander A., et al., Childhood predictors of psychiatric disorders among boys: a prospective community-based follow-up study from age 8 years to early adulthood. J Am Acad Child Adolesc Psychiatry, 2005. 44(8): p. 756–67. https://doi.org/10.1097/01.chi.0000164878.79986.2f PMID: 16034277 36. Kaprio J., The Finnish Twin Cohort Study: an update. Twin Res Hum Genet, 2013. 16(1): p. 157–62. https://doi.org/10.1017/thg.2012.142 PMID: 23298696 37. Kooijman M.N., et al., The Generation R Study: design and cohort update 2017. Eur J Epidemiol, 2016. 31(12): p. 1243–1264. https://doi.org/10.1007/s10654-016-0224-9 PMID: 28070760 38. van Beijsterveldt C.E., et al., The Young Netherlands Twin Register (YNTR): longitudinal twin and family studies in over 70,000 children. Twin Res Hum Genet, 2013. 16(1): p. 252–67. https://doi.org/10.1017/ thg.2012.118 PMID: 23186620 39. Haworth C.M., Davis O.S., and Plomin R., Twins Early Development Study (TEDS): a genetically sensitive investigation of cognitive and behavioral development from childhood to young adulthood. Twin Res Hum Genet, 2013. 16(1): p. 117–25. https://doi.org/10.1017/thg.2012.91 PMID: 23110994 40. Goodman R., The Strengths and Difficulties Questionnaire: a research note. J Child Psychol Psychiatry, 1997. 38(5): p. 581–6. https://doi.org/10.1111/j.1469-7610.1997.tb01545.x PMID: 9255702 41. Goodman R., Psychometric properties of the strengths and difficulties questionnaire. J Am Acad Child Adolesc Psychiatry, 2001. 40(11): p. 1337–45. https://doi.org/10.1097/00004583-200111000-00015 PMID: 11699809 42. Achenbach, T.M., Manual for the child behavior checklist/4-18 and 1991 profile. 1991, Burlington, VT: Dept. of Psychiatry, University of Vermont. x, 288 p. 43. Rescorla L.A., et al., Consistency of Teacher-Reported Problems for Students in 21 Countries. School Psychology Review, 2007. 36(1): p. 91–110. 44. Offord D.R., et al., Integrating assessment data from multiple informants. J Am Acad Child Adolesc Psychiatry, 1996. 35(8): p. 1078–85. https://doi.org/10.1097/00004583-199608000-00019 PMID: 8755805 45. Maughan B., et al., Conduct disorder and oppositional defiant disorder in a national sample: developmental epidemiology. J Child Psychol Psychiatry, 2004. 45(3): p. 609–21. https://doi.org/10.1111/j. 1469-7610.2004.00250.x PMID: 15055379 46. Stanger C. and Lewis M., Agreement among Parents, Teachers, and Children on Internalizing and Externalizing Behavior Problems. Journal of Clinical Child Psychology, 1993. 22(1): p. 107–115. 47. Ha ¨ma ¨la ¨inen M. and Pulkkinen L., Problem behavior as a precursor of male criminality. Dev Psychopathol, 1996. 8: p. 443–455. 48. Wang M., et al., Why are empathic children more liked by peers? The mediating roles of prosocial and aggressive behaviors. Personality and Individual Differences, 2019. 144: p. 19–23. 49. White H.R., et al., Psychopathology as a predictor of adolescent drug use trajectories. Psychology of Addictive Behaviors, 2001. 15(3): p. 210–218. PMID: 11563798 50. Odgers C.L., et al., Female and male antisocial trajectories: from childhood origins to adult outcomes. Dev Psychopathol, 2008. 20(2): p. 673–716. https://doi.org/10.1017/S0954579408000333 PMID: 18423100 51. Hendriks A.M., et al., National Child and Adolescent Health Policies as Indicators of Adolescent Mental Health: A Multilevel Analysis of 30 European Countries. The Journal of Early Adolescence, 2019. 40 (4): p. 537–565. 52. Achenbach T.M., et al., Multicultural assessment of child and adolescent psychopathology with ASEBA and SDQ instruments: research findings, applications, and future directions. J Child Psychol Psychiatry, 2008. 49(3): p. 251–75. https://doi.org/10.1111/j.1469-7610.2007.01867.x PMID: 18333930 53. Hendriks A.M., et al., Content, diagnostic, correlational, and genetic similarities between common measures of childhood aggressive behaviors and related psychiatric traits. J Child Psychol Psychiatry, 2020. 54. Vuoksimaa E., et al., Higher aggression is related to poorer academic performance in compulsory education. J Child Psychol Psychiatry, 2020. https://doi.org/10.1111/jcpp.13273 PMID: 32474928 55. Pakaslahti L. and Keltikangas-Jarvinen L., Comparison of peer, teacher and self-assessments on adolescent direct and indirect aggression. Educ Psychol, 2000. 20: p. 177–190. 56. Collishaw S., et al., How far are associations between child, family and community factors and child psychopathology informant-specific and informant-general? J Child Psychol Psychiatry, 2009. 50(5): p. 571–80. https://doi.org/10.1111/j.1469-7610.2008.02026.x PMID: 19207620 57. de Zeeuw E.L., et al., Twin specific risk factors in primary school achievements. Twin Res Hum Genet, 2012. 15(1): p. 107–15. https://doi.org/10.1375/twin.15.1.107 PMID: 22784460 PLOS ONE Teacher-rated aggression and co-occurring behaviors and problems among schoolchildren PLOS ONE | https://doi.org/10.1371/journal.pone.0238667 April 29, 2021 17 / 18 58. Pulkkinen L., et al., Peer reports of adaptive behavior in twins and singletons: is twinship a risk or an advantage? Twin Res, 2003. 6(2): p. 106–18. https://doi.org/10.1375/136905203321536236 PMID: 12723997 59. Greenberg M.T., et al., The Effects of a Multiyear Universal Social-Emotional Learning Program: The Role of Student and School Characteristics. Journal of Consulting and Clinical Psychology, 2010. 78 (2): p. 156–168. https://doi.org/10.1037/a0018607 PMID: 20350027 PLOS ONE Teacher-rated aggression and co-occurring behaviors and problems among schoolchildren PLOS ONE | https://doi.org/10.1371/journal.pone.0238667 April 29, 2021 18 / 18