Abi-Dargham A et al (2023) Jun., Candidate biomarkers in psychiatric disorders: state of the field, World Psychiatry, vol. 22, no. 2, pp. 236–262, https://doi.org/10.1002/wps.21078

Garcia-Gutierrez MS, Manzanares J, Navarrete F (Jul. 2021) Editorial: the search for biomarkers in Psychiatry. Front Psychiatry 12:720411. https://doi.org/10.3389/fpsyt.2021.720411

Faraone SV et al (2021) Sep., The World Federation of ADHD International Consensus Statement: 208 Evidence-based conclusions about the disorder, Neurosci. Biobehav. Rev., vol. 128, pp. 789–818, https://doi.org/10.1016/j.neubiorev.2021.01.022

Faraone SV et al (Aug. 2015) Attention-deficit/hyperactivity disorder. Nat Rev Dis Primer 1:15020. https://doi.org/10.1038/nrdp.2015.20

Posner J, Polanczyk GV, Sonuga-Barke E (2020) Attention-deficit hyperactivity disorder, Lancet Lond. Engl., vol. 395, no. 10222, Art. no. 10222, Feb. https://doi.org/10.1016/S0140-6736(19)33004-1

Faraone SV et al (Feb. 2024) Attention-deficit/hyperactivity disorder. Nat Rev Dis Primer 10(1). https://doi.org/10.1038/s41572-024-00495-0

Hoogman M et al (Apr. 2017) Subcortical brain volume differences in participants with attention deficit hyperactivity disorder in children and adults: a cross-sectional mega-analysis. Lancet Psychiatry 4(4):310–319. https://doi.org/10.1016/S2215-0366(17)30049-4

Cortese S et al (2023) Feb., Candidate diagnostic biomarkers for neurodevelopmental disorders in children and adolescents: a systematic review, World Psychiatry, vol. 22, no. 1, pp. 129–149, https://doi.org/10.1002/wps.21037

Demontis D et al (Feb. 2023) Genome-wide analyses of ADHD identify 27 risk loci, refine the genetic architecture and implicate several cognitive domains. Nat Genet 55(2):198–208. https://doi.org/10.1038/s41588-022-01285-8

Hoogman M et al (Jan. 2022) Consortium neuroscience of attention deficit/hyperactivity disorder and autism spectrum disorder: the ENIGMA adventure. Hum Brain Mapp 43(1):37–55. https://doi.org/10.1002/hbm.25029

Pievsky MA, McGrath RE (Mar. 2018) The Neurocognitive Profile of Attention-Deficit/Hyperactivity disorder: a review of Meta-analyses. Arch Clin Neuropsychol 33(2):143–157. https://doi.org/10.1093/arclin/acx055

Tamm L, Loren REA, Peugh J, Ciesielski HA (2021) The Association of Executive Functioning With Academic, Behavior, and Social Performance Ratings in Children With ADHD, J Learn Disabil, vol. 54, no. 2, pp. 124–138, Mar. https://doi.org/10.1177/0022219420961338

Coghill D, Sonuga-Barke EJS (May 2012) Annual Research Review: categories versus dimensions in the classification and conceptualisation of child and adolescent mental disorders– implications of recent empirical study. J Child Psychol Psychiatry 53(5):469–489. https://doi.org/10.1111/j.1469-7610.2011.02511.x

Luo Y, Weibman D, Halperin JM, Li X (Feb. 2019) A review of heterogeneity in attention Deficit/Hyperactivity disorder (ADHD). Front Hum Neurosci 13:42. https://doi.org/10.3389/fnhum.2019.00042

Sibley MH et al (Feb. 2022) Variable patterns of Remission from ADHD in the Multimodal treatment study of ADHD. Am J Psychiatry 179(2):142–151. https://doi.org/10.1176/appi.ajp.2021.21010032

Caye A et al (Dec. 2016) Life span studies of ADHD—Conceptual challenges and predictors of Persistence and Outcome. Curr Psychiatry Rep 18(12):111. https://doi.org/10.1007/s11920-016-0750-x

Caye A et al (May 2019) A risk calculator to predict adult attention-deficit/hyperactivity disorder: generation and external validation in three birth cohorts and one clinical sample. Epidemiol Psychiatr Sci 29:e37. https://doi.org/10.1017/S2045796019000283

Lorenzi CH et al (2022) Aug., Replication of a predictive model for youth ADHD in an independent sample from a developing country, J Child Psychol Psychiatry, https://doi.org/10.1111/jcpp.13682

Meehan AJ et al (Jun. 2022) Clinical prediction models in psychiatry: a systematic review of two decades of progress and challenges. Mol Psychiatry 27(6):2700–2708. https://doi.org/10.1038/s41380-022-01528-4

Salum GA et al (2015) Mar., High risk cohort study for psychiatric disorders in childhood: rationale, design, methods and preliminary results, Int. J. Methods Psychiatr. Res., vol. 24, no. 1, Art. no. 1, https://doi.org/10.1002/mpr.1459

Aebi M, Kuhn C, Metzke CW, Stringaris A, Goodman R, Steinhausen H-C (Oct. 2012) The use of the development and well-being assessment (DAWBA) in clinical practice: a randomized trial. Eur Child Adolesc Psychiatry 21(10):559–567. https://doi.org/10.1007/s00787-012-0293-6

Foreman D, Morton S, Ford T (2009) Exploring the clinical utility of the Development And Well-Being Assessment (DAWBA) in the detection of hyperkinetic disorders and associated diagnoses in clinical practice, J. Child Psychol. Psychiatry, vol. 50, no. 4, pp. 460–470, Apr. https://doi.org/10.1111/j.1469-7610.2008.02017.x

Euesden J, Lewis CM, O’Reilly PF (May 2015) PRSice: polygenic risk score software. Bioinformatics 31(9):1466–1468. https://doi.org/10.1093/bioinformatics/btu848

Choi SW, O’Reilly PF (2019) PRSice–2: Polygenic Risk Score software for biobank-scale data, GigaScience, vol. 8, no. 7, p. giz082, Jul. https://doi.org/10.1093/gigascience/giz082

Dias-Viana JL, Gomes GVA (Aug. 2019) Escala Wechsler De Inteligência para Crianças (WISC): análise da produção de artigos científicos brasileiros. Psicol Rev 28(1):9–36. https://doi.org/10.23925/2594-3871.2019v28i1p

Vandierendonck A, Kemps E, Fastame MC, Szmalec A (Feb. 2004) Working memory components of the Corsi blocks task. Br J Psychol 95(1):57–79. https://doi.org/10.1348/000712604322779460

Bexkens A, Ruzzano L, d’ AMLC, Escury-Koenigs MW, Van der Molen, Huizenga HM (Jan. 2014) Inhibition deficits in individuals with intellectual disability: a meta-regression analysis. J Intellect Disabil Res 58(1):3–16. https://doi.org/10.1111/jir.12068

Toplak ME, Dockstader C, Tannock R (Feb. 2006) Temporal information processing in ADHD: findings to date and new methods. J Neurosci Methods 151(1):15–29. https://doi.org/10.1016/j.jneumeth.2005.09.018

Martel MM et al (Jan. 2017) A general psychopathology factor (P factor) in children: structural model analysis and external validation through familial risk and child global executive function. J Abnorm Psychol 126(1):137–148. https://doi.org/10.1037/abn0000205

Sjoberg D, Whiting DK, Curry M, Lavery J A., and, Larmarange J (2021) Reproducible Summary tables with the Gtsummary Package. R J 13(1):570. https://doi.org/10.32614/RJ-2021-053

Rosseel Y (2012) Lavaan: an R Package for Structural equation modeling. J Stat Softw 48(2). https://doi.org/10.18637/jss.v048.i02

Pastore M (Dec. 2018) Overlapping: a R package for estimating overlapping in empirical distributions. J Open Source Softw 3(32):1023. https://doi.org/10.21105/joss.01023

Bhullar A, Kumar K, Anand A (Jan. 2023) ADHD and neuropsychology: Developmental Perspective, Assessment, and interventions. Ann Neurosci 30(1):5–7. https://doi.org/10.1177/09727531231171765

Ungar M, Theron L Resilience and mental health: how multisystemic processes contribute to positive outcomes. Lancet Psychiatry, 7, 5, pp. 441–448, May 2020, doi: 10.1016/S2215–0366(19)30434–1.

Van Rooij D et al (2015) Jul., Distinguishing Adolescents With ADHD From Their Unaffected Siblings and Healthy Comparison Subjects by Neural Activation Patterns During Response Inhibition, Am. J. Psychiatry, vol. 172, no. 7, pp. 674–683, https://doi.org/10.1176/appi.ajp.2014.13121635

Wackerhagen C et al (2017) Jul., Influence of Familial Risk for Depression on Cortico-Limbic Connectivity During Implicit Emotional Processing, Neuropsychopharmacology, vol. 42, no. 8, pp. 1729–1738, https://doi.org/10.1038/npp.2017.59

Van Sprang ED et al (2022) Mar., Familial risk for depressive and anxiety disorders: associations with genetic, clinical, and psychosocial vulnerabilities, Psychol. Med., vol. 52, no. 4, pp. 696–706, https://doi.org/10.1017/S0033291720002299

Demro C, Lahud E, Burton PC, Purcell JR, Simon JJ, Sponheim SR (Jan. 2024) Reward anticipation-related neural activation following cued reinforcement in adults with psychotic psychopathology and biological relatives. Psychol Med 1–11. https://doi.org/10.1017/S0033291723003343

Toro VD et al (2024) Feb., The interaction between early life complications and a polygenic risk score for schizophrenia is associated with brain activity during emotion processing in healthy participants, Psychol. Med., pp. 1–10, https://doi.org/10.1017/S0033291724000011

Mooney MA et al (2021) Jun., Smaller total brain volume but not subcortical structure volume related to common genetic risk for ADHD, Psychol. Med., vol. 51, no. 8, pp. 1279–1288, https://doi.org/10.1017/S0033291719004148

Liu B et al (May 2016) Polygenic risk for Schizophrenia influences cortical gyrification in 2 Independent General populations. Schizophr Bull sbw051. https://doi.org/10.1093/schbul/sbw051

Kotov R et al (May 2017) The hierarchical taxonomy of psychopathology (HiTOP): a dimensional alternative to traditional nosologies. J Abnorm Psychol 126(4):454–477. https://doi.org/10.1037/abn0000258

Shaw P et al (Feb. 2011) Cortical development in typically developing children with symptoms of hyperactivity and impulsivity: support for a dimensional view of attention deficit hyperactivity disorder. Am J Psychiatry 168(2):143–151. https://doi.org/10.1176/appi.ajp.2010.10030385