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Population Neuroscience

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Book cover Mental Health and Illness of Children and Adolescents

Part of the book series: Mental Health and Illness Worldwide ((MHIW))

Abstract

Population neuroscience is an emerging field of research defined by the intersection of neuroscience with epidemiology. In this chapter, we review large-scale developmental studies conducted in clinical, longitudinal high risk, and typically developing cohorts with neuroimaging. We point out the advantages offered by developmental and neuroimaging research when conducted in epidemiological settings such as better control for confounding and the possibility to enhance generalizability. We discuss the advances in the field that we attribute to population neuroscience approach, for example, the evidence for the maturational delay in ADHD and for the early onset of autistic brain changes preceding symptoms. Current population neuroimaging studies begin to explain the role of a more complex environment such as poverty and abuse, child behavior itself, genes, and their interplay in shaping the structure and function of the human brain. We conclude that the question of how different environmental and genetic factors shape the brain and how the brain predicts child psychiatric behavior can only be addressed in large population-based studies with repeated imaging and behavior assessments using a population neuroscience approach.

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References

  • Adams HH, Hibar DP, Chouraki V, Stein JL, Nyquist PA, Renteria ME, … Thompson PM (2016) Novel genetic loci underlying human intracranial volume identified through genome-wide association. Nat Neurosci 19(12):1569–1582. https://doi.org/10.1038/nn.4398

  • Alberton BAV, Nichols TE, Gamba HR, Winkler AM (2019) Multiple testing correction over contrasts for brain imaging. bioRxiv:775106

    Google Scholar 

  • Alemany S, Jansen P, Muetzel R, Marques N, El Marroun H, Jaddoe V, … White T (2019) Common polygenic variations for psychiatric disorders and cognition in relation to brain morphology in the general pediatric population. J Am Acad Child Adolesc Psychiatry 58:600–607

    Google Scholar 

  • Ambrosino S, De Zeeuw P, Wierenga LM, van Dijk S, Durston S (2017) What can cortical development in attention-deficit/hyperactivity disorder teach us about the early developmental mechanisms involved? Cereb Cortex 27(9):4624–4634

    Article  PubMed  Google Scholar 

  • American Psychiatric Association (2013) Diagnostic and statistical manual of mental disorders, 5th edn. APA, Arlington

    Book  Google Scholar 

  • Bale TL, Baram TZ, Brown AS, Goldstein JM, Insel TR, McCarthy MM, … Nestler EJ (2010) Early life programming and neurodevelopmental disorders. Biol Psychiatry 68(4):314–319. https://doi.org/10.1016/j.biopsych.2010.05.028

  • Bennett CM, Wolford GL, Miller MB (2009) The principled control of false positives in neuroimaging. Soc Cogn Affect Neurosci 4(4):417–422

    Article  PubMed  PubMed Central  Google Scholar 

  • Burton BK, Hjorthøj C, Jepsen JR, Thorup A, Nordentoft M, Plessen KJ (2016) Research review: do motor deficits during development represent an endophenotype for schizophrenia? A meta-analysis. J Child Psychol Psychiatry 57(4):446–456

    Article  PubMed  Google Scholar 

  • Carpenter WT, Strauss JS (2017) Developmental interactive framework for psychotic disorders. Oxford University Press, Oxford

    Google Scholar 

  • Clouston TS (1891) The neurosis of development. Oliver & Boyd, Edinburgh

    Google Scholar 

  • Constantino JN (2018) Deconstructing autism: from unitary syndrome to contributory developmental endophenotypes. Int Rev Psychiatry 30(1):18–24. https://doi.org/10.1080/09540261.2018.1433133

    Article  PubMed  PubMed Central  Google Scholar 

  • Desikan RS, Ségonne F, Fischl B, Quinn BT, Dickerson BC, Blacker D, … Hyman BT (2006) An automated labeling system for subdividing the human cerebral cortex on MRI scans into gyral based regions of interest. Neuroimage 31(3):968–980

    Google Scholar 

  • Dinga R, Schmaal L, Penninx B, van Tol MJ, Veltman DJ, van Velzen L, … Marquand AF (2019) Evaluating the evidence for biotypes of depression: methodological replication and extension of. Neuroimage Clin 22:101796. https://doi.org/10.1016/j.nicl.2019.101796

  • Donovan SJ, Susser E (2011) Commentary: advent of sibling designs. Int J Epidemiol 40(2):345–349. https://doi.org/10.1093/ije/dyr057

    Article  PubMed  PubMed Central  Google Scholar 

  • Drysdale AT, Grosenick L, Downar J, Dunlop K, Mansouri F, Meng Y, … Liston C (2017) Resting-state connectivity biomarkers define neurophysiological subtypes of depression. Nat Med 23(1):28–38. https://doi.org/10.1038/nm.4246

  • Ducharme S, Albaugh MD, Nguyen TV, Hudziak JJ, Mateos-Perez JM, Labbe A, … Brain Development Cooperative Group (2016) Trajectories of cortical thickness maturation in normal brain development – the importance of quality control procedures. Neuroimage 125:267–279. https://doi.org/10.1016/j.neuroimage.2015.10.010

  • Eklund A, Nichols TE, Knutsson H (2016) Cluster failure: why fMRI inferences for spatial extent have inflated false-positive rates. Proc Natl Acad Sci 113(28):7900–7905

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  • El Marroun H, Tiemeier H, Franken IH, Jaddoe VW, van der Lugt A, Verhulst FC, … White T (2016) Prenatal cannabis and tobacco exposure in relation to brain morphology: a prospective neuroimaging study in young children. Biol Psychiatry 79(12):971–979

    Google Scholar 

  • El Marroun H, Bolhuis K, Franken IH, Jaddoe VW, Hillegers MH, Lahey BB, Tiemeier H (2019) Preconception and prenatal cannabis use and the risk of behavioural and emotional problems in the offspring; a multi-informant prospective longitudinal study. Int J Epidemiol 48(1):287–296

    Article  PubMed  Google Scholar 

  • Elliott LT, Sharp K, Alfaro-Almagro F, Shi S, Miller KL, Douaud G, … Smith SM (2018) Genome-wide association studies of brain imaging phenotypes in UK Biobank. Nature 562(7726):210–216. https://doi.org/10.1038/s41586-018-0571-7

  • Emerson RW, Adams C, Nishino T, Hazlett HC, Wolff JJ, Zwaigenbaum L, … Elison JT (2017) Functional neuroimaging of high-risk 6-month-old infants predicts a diagnosis of autism at 24 months of age. Sci Transl Med 9(393):eaag2882

    Google Scholar 

  • Filatova S, Koivumaa-Honkanen H, Hirvonen N, Freeman A, Ivandic I, Hurtig T, … Miettunen J (2017) Early motor developmental milestones and schizophrenia: a systematic review and meta-analysis. Schizophr Res 188:13–20

    Google Scholar 

  • Fish B (1957) The detection of schizophrenia in infancy. J Nerv Ment Dis 125:1–24

    Google Scholar 

  • Franke B, Stein JL, Ripke S, Anttila V, Hibar DP, van Hulzen KJE, … Sullivan PF (2016) Genetic influences on schizophrenia and subcortical brain volumes: large-scale proof of concept. Nat Neurosci 19(3):420–431. https://doi.org/10.1038/nn.4228

  • Garavan H, Bartsch H, Conway K, Decastro A, Goldstein RZ, Heeringa S, … Zahs D (2018) Recruiting the ABCD sample: design considerations and procedures. Dev Cogn Neurosci 32:16–22. https://doi.org/10.1016/j.dcn.2018.04.004

  • Giedd JN, Rapoport JL (2010) Structural MRI of pediatric brain development: what have we learned and where are we going? Neuron 67(5):728–734

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  • Glasser MF, Coalson TS, Robinson EC, Hacker CD, Harwell J, Yacoub E, … Jenkinson M (2016) A multi-modal parcellation of human cerebral cortex. Nature 536(7615):171–178

    Google Scholar 

  • Greve D, Fischl B (2018) False positive rates in surface-based anatomical analysis. NeuroImage 171:6–14

    Article  PubMed  Google Scholar 

  • Guxens M, Lubczyńska MJ, Muetzel RL, Dalmau-Bueno A, Jaddoe VW, Hoek G, … Brunekreef B (2018) Air pollution exposure during fetal life, brain morphology, and cognitive function in school-age children. Biol Psychiatry 84(4):295–303

    Google Scholar 

  • Hazlett HC, Gu H, Munsell BC, Kim SH, Styner M, Wolff JJ, … Statistical Analysis (2017) Early brain development in infants at high risk for autism spectrum disorder. Nature 542(7641):348–351. https://doi.org/10.1038/nature21369

  • Hibar DP, Stein JL, Renteria ME, Arias-Vasquez A, Desrivieres S, Jahanshad N, … Medland SE (2015) Common genetic variants influence human subcortical brain structures. Nature 520(7546), 224–229. https://doi.org/10.1038/nature14101

  • Hirschhorn JN, Gajdos ZK (2011) Genome-wide association studies: results from the first few years and potential implications for clinical medicine. Annu Rev Med 62:11–24. https://doi.org/10.1146/annurev.med.091708.162036

    Article  CAS  PubMed  Google Scholar 

  • Hoogman M, Muetzel R, Guimaraes JP, Shumskaya E, Mennes M, Zwiers MP, … Franke B (2019) Brain imaging of the cortex in ADHD: a coordinated analysis of large-scale clinical and population-based samples. Am J Psychiatry 176(7):531–542. https://doi.org/10.1176/appi.ajp.2019.18091033

  • Ioannidis JPA (2019) What have we (not) learnt from millions of scientific papers with P values? Am Stat 73(sup1):20–25. https://doi.org/10.1080/00031305.2018.1447512

    Article  Google Scholar 

  • Jaddoe VW, Mackenbach JP, Moll HA., Steegers EA, Tiemeier H, Verhulst FC, … Hofman A (2006) The Generation R Study: design and cohort profile. Eur J Epidemiol 21(6):475

    Google Scholar 

  • Jansen AG, Dieleman GC, Jansen PR, Verhulst FC, Posthuma D, Polderman TJC (2019a) Psychiatric polygenic risk scores as predictor for attention deficit/hyperactivity disorder and autism spectrum disorder in a clinical child and adolescent sample. Behav Genet. https://doi.org/10.1007/s10519-019-09965-8

  • Jansen TA, Korevaar TI, Mulder TA, White T, Muetzel RL, Peeters RP, Tiemeier H (2019b) Maternal thyroid function during pregnancy and child brain morphology: a time window-specific analysis of a prospective cohort. Lancet Diabetes Endocrinol 7(8):629–637

    Article  CAS  PubMed  Google Scholar 

  • Jernigan TL, Brown TT, Hagler DJ, Jr, Akshoomoff N, Bartsch H, Newman E, … Genetics S (2016) The Pediatric Imaging, Neurocognition, and Genetics (PING) data repository. Neuroimage 124(Pt B):1149–1154. https://doi.org/10.1016/j.neuroimage.2015.04.057

  • Johnson D, Guthrie D, Smyke A, Koga S, Fox N, Zeanah C, Nelson C (2010) Growth and associations between auxology, caregiving environment, and cognition in socially deprived Romanian children randomized to foster vs ongoing institutional care. Arch Pediatr Adolesc Med 164(6):507–516

    Article  PubMed  PubMed Central  Google Scholar 

  • Jones W, Klin A (2013) Attention to eyes is present but in decline in 2-6-month-old infants later diagnosed with autism. Nature 504(7480):427–431. https://doi.org/10.1038/nature12715

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  • Kaczkurkin AN, Moore TM, Calkins ME, Ciric R, Detre JA, Elliott MA, … Satterthwaite TD (2018) Common and dissociable regional cerebral blood flow differences associate with dimensions of psychopathology across categorical diagnoses. Mol Psychiatry 23(10):1981–1989. https://doi.org/10.1038/mp.2017.174

  • Kern J, Geier D, Sykes L, Geier MR (2013) Evidence of neurodegeneration in autism spectrum disorder 2. Transl Neurodegen 2:17

    Article  Google Scholar 

  • Kolossa A, Kopp B (2018) Data quality over data quantity in computational cognitive neuroscience. NeuroImage 172:775–785

    Article  PubMed  Google Scholar 

  • Lenroot RK, Giedd JN (2006) Brain development in children and adolescents: insights from anatomical magnetic resonance imaging. Neurosci Biobehav Rev 30(6):718–729

    Article  PubMed  Google Scholar 

  • Leung L (2015) Validity, reliability, and generalizability in qualitative research. J Family Med Primary Care 4(3):324

    Article  Google Scholar 

  • LeWinn KZ, Sheridan MA, Keyes KM, Hamilton A, McLaughlin KA (2017) Sample composition alters associations between age and brain structure. Nat Commun 8(1):1–14

    Article  CAS  Google Scholar 

  • Lewis DA, Levitt P (2002) Schizophrenia as a disorder of neurodevelopment. Annu Rev Neurosci 25(1):409–32

    Google Scholar 

  • McIntosh AM, Owens DC, Moorhead WJ, Whalley HC, Stanfield AC, Hall J, … Lawrie SM (2011) Longitudinal volume reductions in people at high genetic risk of schizophrenia as they develop psychosis. Biol Psychiatry 69(10):953–958. https://doi.org/10.1016/j.biopsych.2010.11.003

  • Muetzel RL, Blanken LME, van der Ende J, El Marroun H, Shaw P, Sudre G, … White T (2018) Tracking brain development and dimensional psychiatric symptoms in children: a longitudinal population-based neuroimaging study. Am J Psychiatry 175(1):54–62. https://doi.org/10.1176/appi.ajp.2017.16070813

  • Murray RM, Bhavsar V, Tripoli G, Howes O (2017) 30 years on: how the neurodevelopmental hypothesis of schizophrenia morphed into the developmental risk factor model of psychosis. Schizophr Bull 43(6):1190–1196. https://doi.org/10.1093/schbul/sbx121

    Article  PubMed  PubMed Central  Google Scholar 

  • Neumann A, Muetzel RL, Lahey BB, Bakermans-Kranenburg MJ, van IJzendoorn MH, Jaddoe VW, Hillegers MH, White T, Tiemeier H (2020) White matter microstructure and the general psychopathology factor in children. J Am Acad Child Adolesc Psychiatry

    Google Scholar 

  • Noble KG, Houston SM, Brito NH, Bartsch H, Kan E, Kuperman JM, … Sowell ER (2015) Family income, parental education and brain structure in children and adolescents. Nat Neurosci 18(5):773–778. https://doi.org/10.1038/nn.3983

  • Obel C, Olsen J, Henriksen TB, Rodriguez A, Järvelin MR, Moilanen I, … Ebeling H (2011) Is maternal smoking during pregnancy a risk factor for hyperkinetic disorder?—Findings from a sibling design. Int J Epidemiol 40(2):338–345

    Google Scholar 

  • Paulus MP, Squeglia LM, Bagot K, Jacobus J, Kuplicki R, Breslin FJ, … Tapert SF (2019) Screen media activity and brain structure in youth: Evidence for diverse structural correlation networks from the ABCD study. Neuroimage 185:140–153. https://doi.org/10.1016/j.neuroimage.2018.10.040

  • Paus T (2010) Population neuroscience: why and how. Hum Brain Mapp 31:891–903

    Article  PubMed  PubMed Central  Google Scholar 

  • Pausova Z, Paus T, Abrahamowicz M, Bernard M, Gaudet D, Leonard G, … Veillette S (2017) Cohort profile: the Saguenay Youth Study (SYS). Int J Epidemiol 46(2):e19. https://doi.org/10.1093/ije/dyw023

  • Quinlan EB, Barker ED, Luo Q, Banaschewski T, Bokde ALW, Bromberg U, … IMAGEN Consortium (2018) Peer victimization and its impact on adolescent brain development and psychopathology. Mol Psychiatry. https://doi.org/10.1038/s41380-018-0297-9

  • Raznahan A, Wallace GL, Antezana L, Greenstein D, Lenroot R, Thurm A, … Giedd JN (2013) Compared to what? Early brain overgrowth in autism and the perils of population norms. Biol Psychiatry 74(8):563–575. https://doi.org/10.1016/j.biopsych.2013.03.022

  • Redcay E, Courchesne E (2005) When is the brain enlarged in autism? A meta-analysis of all brain size reports. Biol Psychiatry 58(1):1–9

    Article  PubMed  Google Scholar 

  • Richiardi L, Pizzi C, Pearce N (2013) Commentary: representativeness is usually not necessary and often should be avoided. Int J Epidemiol 42(4):1018–1022. https://doi.org/10.1093/ije/dyt103

    Article  PubMed  Google Scholar 

  • Rieder RO, Nichols PL (1979) Offspring of schizophrenics III: hyperactivity and neurological soft signs. Arch Gen Psychiatry 36(6):665–674

    Article  CAS  PubMed  Google Scholar 

  • Salinas YD, Wang Z, DeWan AT (2018) Statistical analysis of multiple phenotypes in genetic epidemiologic studies: from cross-phenotype associations to pleiotropy. Am J Epidemiol 187(4):855–863. https://doi.org/10.1093/aje/kwx296

    Article  PubMed  Google Scholar 

  • Samek DR, McGue M, Keyes M, Iacono WG (2015) Sibling facilitation mediates the association between older and younger sibling alcohol use in late adolescence. J Res Adolesc 25(4):638–651. https://doi.org/10.1111/jora.12154

    Article  PubMed  Google Scholar 

  • Savage JE, Jansen PR, Stringer S, Watanabe K, Bryois J, de Leeuw CA, … Posthuma D (2018) Genome-wide association meta-analysis in 269, 867 individuals identifies new genetic and functional links to intelligence. Nat Genet 50(7):912–919. https://doi.org/10.1038/s41588-018-0152-6

  • Schumann CM, Bloss CS, Barnes CC, Wideman GM, Carper RA, Akshoomoff N, … Courchesne E (2010) Longitudinal magnetic resonance imaging study of cortical development through early childhood in autism. J Neurosci 30(12):4419–4427. https://doi.org/10.1523/JNEUROSCI.5714-09.2010

  • Serdarevic F, Ghassabian A, van Batenburg-Eddes T, Tahirovic E, White T, Jaddoe VW, … Tiemeier H (2017) Infant neuromotor development and childhood problem behavior. Pediatrics 140(6):e20170884

    Google Scholar 

  • Serdarevic F, Jansen PR, Ghassabian A, White T, Jaddoe VW, Posthuma D, Tiemeier H (2018) Association of genetic risk for schizophrenia and bipolar disorder with infant neuromotor development. JAMA Psychiat 75(1):96–98

    Article  Google Scholar 

  • Shaw P, Greenstein D, Lerch J, Clasen L, Lenroot R, Gogtay N, … Giedd J (2006) Intellectual ability and cortical development in children and adolescents. Nature 440(7084):676–679. https://doi.org/10.1038/nature04513

  • Shaw P, Eckstrand K, Sharp W, Blumenthal J, Lerch JP, Greenstein D, … Rapoport JL (2007) Attention-deficit/hyperactivity disorder is characterized by a delay in cortical maturation. Proc Natl Acad Sci USA 104(49):19649–19654. https://doi.org/10.1073/pnas.0707741104

  • Shaw P, Malek M, Watson B, Greenstein D, De Rossi P, Sharp W (2013) Trajectories of cerebral cortical development in childhood and adolescence and adult attention-deficit/hyperactivity disorder. Biol Psychiatry 74(8):599–606

    Article  PubMed  PubMed Central  Google Scholar 

  • Sheridan MA, Fox NA, Zeanah CH, McLaughlin KA, Nelson CA (2012) Variation in neural development as a result of exposure to institutionalization early in childhood. Proc Natl Acad Sci 109(32):12927–12932

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  • Shrout P, Rodgers J (2018) Psychology, science, and knowledge construction: broadening perspectives from the replication crisis. Ann Rev Psychol 69:487–510

    Article  Google Scholar 

  • Smeland OB, Wang Y, Frei O, Li W, Hibar DP, Franke B, … Andreassen OA (2018) Genetic overlap between schizophrenia and volumes of hippocampus, putamen, and intracranial volume indicates shared molecular genetic mechanisms. Schizophr Bull 44(4), 854–864. https://doi.org/10.1093/schbul/sbx148

  • Smoller J, Andreassen O, Edenberg H, Faraone S, Glatt S, Kendler K (2019) Psychiatric genetics and the structure of psychopathology. Mol Psychiatry 24(3):409–420

    Article  PubMed  Google Scholar 

  • Sugranyes G, de la Serna E, Borras R, Sanchez-Gistau V, Pariente JC, Romero S, … Castro-Fornieles J (2017) Clinical, cognitive, and neuroimaging evidence of a neurodevelopmental continuum in offspring of probands with schizophrenia and bipolar disorder. Schizophr Bull 43(6):1208–1219. https://doi.org/10.1093/schbul/sbx002

  • Szucs D, Ioannidis JP (2017) Empirical assessment of published effect sizes and power in the recent cognitive neuroscience and psychology literature. PLoS Biol 15(3):e2000797. https://doi.org/10.1371/journal.pbio.2000797

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  • Thapar A, Rutter M (2015) Neurodevelopmental disorders. In: ThaparA, Pine DS, Leckman JF, Scott S, Snowling MJ, Taylor E (eds) Rutter’s child and adolescent psychiatry, 6th edn. Wiley, Chichester, pp 31–40

    Google Scholar 

  • Van IJzendoorn M, Bakermans-Kranenburg M, Juffer F (2007) Plasticity of growth in height, weight, and head circumference: meta-analytic evidence of massive catch-up after international adoption. J Dev Behav Pediatr 28(4):334–343

    Article  PubMed  Google Scholar 

  • van Os J, Jones P, Lewis G, Wadsworth M, Murray R (1997) Developmental precursors of affective illness in a general population birth cohort. Arch Gen Psychiatry 54(7):625–631

    Article  PubMed  Google Scholar 

  • Van 't Ent D, den Braber A, Baselmans BML, Brouwer RM, Dolan CV, Hulshoff Pol HE, … Bartels M (2017) Associations between subjective well-being and subcortical brain volumes. Sci Rep 7(1):6957. https://doi.org/10.1038/s41598-017-07120-z

  • Westerhausen R, Friesen CM, Rohani DA, Krogsrud SK, Tamnes CK, Skranes JS, … Walhovd KB (2018) The corpus callosum as anatomical marker of intelligence? A critical examination in a large-scale developmental study. Brain Struct Funct 223(1):285–296. https://doi.org/10.1007/s00429-017-1493-0

  • Whelan R, Watts R, Orr CA, Althoff RR, Artiges E, Banaschewski T, … IMAGEN Consortium (2014) Neuropsychosocial profiles of current and future adolescent alcohol misusers. Nature 512(7513):185–189. https://doi.org/10.1038/nature13402

  • White T (2015) Subclinical psychiatric symptoms and the brain: what can developmental population neuroimaging bring to the table? J Am Acad Child Adolesc Psychiatry 54(10):797–798. https://doi.org/10.1016/j.jaac.2015.07.011

    Article  PubMed  Google Scholar 

  • White T, El Marroun H, Nijs I, Schmidt M, van der Lugt A, Wielopolki PA, … Verhulst FC (2013) Pediatric population-based neuroimaging and the Generation R Study: the intersection of developmental neuroscience and epidemiology. Eur J Epidemiol 28(1):99–111. https://doi.org/10.1007/s10654-013-9768-0

  • Zhao B, Zhang J, Ibrahim JG, Luo T, Santelli RC, Li Y, … Zhu H (2019) Large-scale GWAS reveals genetic architecture of brain white matter microstructure and genetic overlap with cognitive and mental health traits (n = 17,706). Mol Psychiatry. https://doi.org/10.1038/s41380-019-0569-z

  • Zou R, Tiemeier H, Van Der Ende J, Verhulst FC, Muetzel RL, White T, … El Marroun H (2019) Exposure to maternal depressive symptoms in fetal life or childhood and offspring brain development: a population-based imaging study. Am J Psychiatry 176(9):702–710

    Google Scholar 

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Tiemeier, H., Muetzel, R. (2020). Population Neuroscience. In: Taylor, E., Verhulst, F., Wong, J., Yoshida, K., Nikapota, A. (eds) Mental Health and Illness of Children and Adolescents. Mental Health and Illness Worldwide. Springer, Singapore. https://doi.org/10.1007/978-981-10-0753-8_12-1

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