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Bainter SA, McCauley TG, Fahmy MM, Goodman ZT, Kupis LB, Rao JS. Comparing Bayesian Variable Selection to Lasso Approaches for Applications in Psychology. PSYCHOMETRIKA 2023; 88:1032-1055. [PMID: 37217762 PMCID: PMC10202760 DOI: 10.1007/s11336-023-09914-9] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 06/20/2022] [Indexed: 05/24/2023]
Abstract
In the current paper, we review existing tools for solving variable selection problems in psychology. Modern regularization methods such as lasso regression have recently been introduced in the field and are incorporated into popular methodologies, such as network analysis. However, several recognized limitations of lasso regularization may limit its suitability for psychological research. In this paper, we compare the properties of lasso approaches used for variable selection to Bayesian variable selection approaches. In particular we highlight advantages of stochastic search variable selection (SSVS), that make it well suited for variable selection applications in psychology. We demonstrate these advantages and contrast SSVS with lasso type penalization in an application to predict depression symptoms in a large sample and an accompanying simulation study. We investigate the effects of sample size, effect size, and patterns of correlation among predictors on rates of correct and false inclusion and bias in the estimates. SSVS as investigated here is reasonably computationally efficient and powerful to detect moderate effects in small sample sizes (or small effects in moderate sample sizes), while protecting against false inclusion and without over-penalizing true effects. We recommend SSVS as a flexible framework that is well-suited for the field, discuss limitations, and suggest directions for future development.
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Affiliation(s)
- Sierra A Bainter
- Department of Psychology, University of Miami, 5665 Ponce de Leon Blvd, Coral Gables, FL, 33146, USA.
| | - Thomas G McCauley
- Department of Psychology, University of California San Diego, San Diego, USA
| | - Mahmoud M Fahmy
- Department of Industrial Engineering, University of Miami, Coral Gables, USA
| | - Zachary T Goodman
- Department of Psychology, University of Miami, 5665 Ponce de Leon Blvd, Coral Gables, FL, 33146, USA
| | - Lauren B Kupis
- Department of Psychiatry and Biobehavioral Sciences, University of California Los Angeles, Los Angeles, USA
| | - J Sunil Rao
- Division of Biostatistics, University of Miami, Coral Gables, USA
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Kohler CG, Wolf DH, Abi-Dargham A, Anticevic A, Cho YT, Fonteneau C, Gil R, Girgis RR, Gray DL, Grinband J, Javitch JA, Kantrowitz JT, Krystal JH, Lieberman JA, Murray JD, Ranganathan M, Santamauro N, Van Snellenberg JX, Tamayo Z, Gur RC, Gur RE, Calkins ME. Illness Phase as a Key Assessment and Intervention Window for Psychosis. BIOLOGICAL PSYCHIATRY GLOBAL OPEN SCIENCE 2023; 3:340-350. [PMID: 37519466 PMCID: PMC10382701 DOI: 10.1016/j.bpsgos.2022.05.009] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/28/2021] [Revised: 05/24/2022] [Accepted: 05/25/2022] [Indexed: 11/23/2022] Open
Abstract
The phenotype of schizophrenia, regardless of etiology, represents the most studied psychotic disorder with respect to neurobiology and distinct phases of illness. The early phase of illness represents a unique opportunity to provide effective and individualized interventions that can alter illness trajectories. Developmental age and illness stage, including temporal variation in neurobiology, can be targeted to develop phase-specific clinical assessment, biomarkers, and interventions. We review an earlier model whereby an initial glutamate signaling deficit progresses through different phases of allostatic adaptation, moving from potentially reversible functional abnormalities associated with early psychosis and working memory dysfunction, and ending with difficult-to-reverse structural changes after chronic illness. We integrate this model with evidence of dopaminergic abnormalities, including cortical D1 dysfunction, which develop during adolescence. We discuss how this model and a focus on a potential critical window of intervention in the early stages of schizophrenia impact the approach to research design and clinical care. This impact includes stage-specific considerations for symptom assessment as well as genetic, cognitive, and neurophysiological biomarkers. We examine how phase-specific biomarkers of illness phase and brain development can be incorporated into current strategies for large-scale research and clinical programs implementing coordinated specialty care. We highlight working memory and D1 dysfunction as early treatment targets that can substantially affect functional outcome.
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Affiliation(s)
- Christian G. Kohler
- Department of Psychiatry, Perelman School of Medicine, University of Pennsylvania, Philadelphia, Pennsylvania
| | - Daniel H. Wolf
- Department of Psychiatry, Perelman School of Medicine, University of Pennsylvania, Philadelphia, Pennsylvania
| | - Anissa Abi-Dargham
- Department of Psychiatry and Behavioral Health, Renaissance School of Medicine, Stony Brook University, Stony Brook
| | - Alan Anticevic
- Department of Psychiatry, Yale School of Medicine, New Haven, Connecticut
| | - Youngsun T. Cho
- Department of Psychiatry, Yale School of Medicine, New Haven, Connecticut
- Child Study Center, Yale School of Medicine, New Haven, Connecticut
| | - Clara Fonteneau
- Department of Psychiatry, Yale School of Medicine, New Haven, Connecticut
| | - Roberto Gil
- Department of Psychiatry and Behavioral Health, Renaissance School of Medicine, Stony Brook University, Stony Brook
| | - Ragy R. Girgis
- Departments of Psychiatry, Vagelos College of Physicians and Surgeons, Columbia University, New York
| | - David L. Gray
- Cerevel Therapeutics Research and Development, East Cambridge, Massachusetts
| | - Jack Grinband
- Departments of Psychiatry, Vagelos College of Physicians and Surgeons, Columbia University, New York
| | - Jonathan A. Javitch
- Departments of Psychiatry, Vagelos College of Physicians and Surgeons, Columbia University, New York
- Molecular Pharmacology and Therapeutics, Vagelos College of Physicians and Surgeons, Columbia University, New York
- Division of Molecular Therapeutics, New York State Psychiatric Institute, New York
| | - Joshua T. Kantrowitz
- Departments of Psychiatry, Vagelos College of Physicians and Surgeons, Columbia University, New York
- New York State Psychiatric Institute, New York
- Nathan Kline Institute, Orangeburg, New York
| | - John H. Krystal
- Department of Psychiatry, Yale School of Medicine, New Haven, Connecticut
| | - Jeffrey A. Lieberman
- Departments of Psychiatry, Vagelos College of Physicians and Surgeons, Columbia University, New York
| | - John D. Murray
- Department of Psychiatry, Yale School of Medicine, New Haven, Connecticut
| | - Mohini Ranganathan
- Department of Psychiatry, Yale School of Medicine, New Haven, Connecticut
| | - Nicole Santamauro
- Department of Psychiatry, Yale School of Medicine, New Haven, Connecticut
| | - Jared X. Van Snellenberg
- Department of Psychiatry and Behavioral Health, Renaissance School of Medicine, Stony Brook University, Stony Brook
| | - Zailyn Tamayo
- Department of Psychiatry, Yale School of Medicine, New Haven, Connecticut
| | - Ruben C. Gur
- Department of Psychiatry, Perelman School of Medicine, University of Pennsylvania, Philadelphia, Pennsylvania
| | - Raquel E. Gur
- Department of Psychiatry, Perelman School of Medicine, University of Pennsylvania, Philadelphia, Pennsylvania
| | - Monica E. Calkins
- Department of Psychiatry, Perelman School of Medicine, University of Pennsylvania, Philadelphia, Pennsylvania
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O'Hare K, Watkeys O, Whitten T, Dean K, Laurens KR, Harris F, Carr VJ, Green MJ. Cumulative environmental risk in early life is associated with mental disorders in childhood. Psychol Med 2023; 53:4762-4771. [PMID: 35866367 DOI: 10.1017/s0033291722001702] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 11/05/2022]
Abstract
BACKGROUND No single environmental factor is a necessary or sufficient cause of mental disorder; multifactorial and transdiagnostic approaches are needed to understand the impact of the environment on the development of mental disorders across the life course. METHOD Using linked multi-agency administrative data for 71 932 children from the New South Wales Child Developmental Study, using logistic regression, we examined associations between 16 environmental risk factors in early life (prenatal period to <6 years of age) and later diagnoses of mental disorder recorded in health service data (from age 6 to 13 years), both individually and summed as an environmental risk score (ERS). RESULTS The ERS was associated with all types of mental disorder diagnoses in a dose-response fashion, such that 2.8% of children with no exposure to any of the environmental factors (ERS = 0), compared to 18.3% of children with an ERS of 8 or more indicating exposure to 8 or more environmental factors (ERS ⩾ 8), had been diagnosed with any type of mental disorder up to age 13-14 years. Thirteen of the 16 environmental factors measured (including prenatal factors, neighbourhood characteristics and more proximal experiences of trauma or neglect) were positively associated with at least one category of mental disorder. CONCLUSION Exposure to cumulative environmental risk factors in early life is associated with an increased likelihood of presenting to health services in childhood for any kind of mental disorder. In many instances, these factors are preventable or capable of mitigation by appropriate public policy settings.
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Affiliation(s)
- Kirstie O'Hare
- Discipline of Psychiatry and Mental Health, University of New South Wales, Sydney, Australia
| | - Oliver Watkeys
- Discipline of Psychiatry and Mental Health, University of New South Wales, Sydney, Australia
| | - Tyson Whitten
- Discipline of Psychiatry and Mental Health, University of New South Wales, Sydney, Australia
- School of Social Sciences, University of Adelaide, Adelaide, South Australia, Australia
| | - Kimberlie Dean
- Discipline of Psychiatry and Mental Health, University of New South Wales, Sydney, Australia
- Justice Health and Forensic Mental Health Network, Sydney, New South Wales, Australia
| | - Kristin R Laurens
- Discipline of Psychiatry and Mental Health, University of New South Wales, Sydney, Australia
- School of Psychology and Counselling, Queensland University of Technology (QUT), Brisbane, Australia
| | - Felicity Harris
- Discipline of Psychiatry and Mental Health, University of New South Wales, Sydney, Australia
| | - Vaughan J Carr
- Discipline of Psychiatry and Mental Health, University of New South Wales, Sydney, Australia
- Neuroscience Research Australia, Sydney, Australia
- Department of Psychiatry, Monash University, Melbourne, Australia
| | - Melissa J Green
- Discipline of Psychiatry and Mental Health, University of New South Wales, Sydney, Australia
- Neuroscience Research Australia, Sydney, Australia
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O’Hare K, Watkeys O, Whitten T, Dean K, Laurens KR, Tzoumakis S, Harris F, Carr VJ, Green MJ. Cumulative Environmental Risk in Early Life: Associations With Schizotypy in Childhood. Schizophr Bull 2023; 49:244-254. [PMID: 36302227 PMCID: PMC10016419 DOI: 10.1093/schbul/sbac160] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 11/14/2022]
Abstract
BACKGROUND AND HYPOTHESIS Psychotic disorders are associated with a growing number of recognized environmental exposures. Cumulative exposure to multiple environmental risk factors in childhood may contribute to the development of different patterns of schizotypy evident in early life. Hypotheses were that distinct profiles of schizotypy would have differential associations with a cumulative score of environmental risk factors. STUDY DESIGN We prospectively examined the relationship between 19 environmental exposures (which had demonstrated replicated associations with psychosis) measured from the prenatal period through to age 11 years, and 3 profiles of schizotypy in children (mean age = 11.9 years, n = 20 599) that have been established in population data from the New South Wales-Child Development Study. Multinomial logistic regression was used to examine associations between membership in each of 3 schizotypy profiles (true schizotypy, introverted schizotypy, and affective schizotypy) and exposure to a range of 19 environmental risk factors for psychosis (both individually and summed as a cumulative environmental risk score [ERS]), relative to children showing no risk. RESULTS Almost all environmental factors were associated with at least 1 schizotypy profile. The cumulative ERS was most strongly associated with the true schizotypy profile (OR = 1.61, 95% CI = 1.52-1.70), followed by the affective (OR = 1.33, 95% CI = 1.28-1.38), and introverted (OR = 1.32, 95% CI = 1.28-1.37) schizotypy profiles. CONCLUSIONS Consistent with the cumulative risk hypothesis, results indicate that an increased number of risk exposures is associated with an increased likelihood of membership in the 3 schizotypy profiles identified in middle childhood, relative to children with no schizotypy profile.
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Affiliation(s)
- Kirstie O’Hare
- Discipline of Psychiatry and Mental Health, University of New South Wales, Sydney, Australia
| | - Oliver Watkeys
- Discipline of Psychiatry and Mental Health, University of New South Wales, Sydney, Australia
- Neuroscience Research Australia, Sydney, Australia
| | - Tyson Whitten
- Discipline of Psychiatry and Mental Health, University of New South Wales, Sydney, Australia
- School of Social Sciences, University of Adelaide, South Australia, Australia
| | - Kimberlie Dean
- Discipline of Psychiatry and Mental Health, University of New South Wales, Sydney, Australia
- Justice Health and Forensic Mental Health Network, Sydney, New South Wales, Australia
| | - Kristin R Laurens
- Discipline of Psychiatry and Mental Health, University of New South Wales, Sydney, Australia
- Queensland University of Technology (QUT), School of Psychology and Counselling, Brisbane, Australia
| | - Stacy Tzoumakis
- School of Criminology and Criminal Justice, Griffith University, Southport, Australia
- Griffith Criminology Institute, Griffith University, Southport, Australia
| | - Felicity Harris
- Discipline of Psychiatry and Mental Health, University of New South Wales, Sydney, Australia
| | - Vaughan J Carr
- Discipline of Psychiatry and Mental Health, University of New South Wales, Sydney, Australia
- Neuroscience Research Australia, Sydney, Australia
- Department of Psychiatry, Monash University, Melbourne, Australia
| | - Melissa J Green
- Discipline of Psychiatry and Mental Health, University of New South Wales, Sydney, Australia
- Neuroscience Research Australia, Sydney, Australia
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Kantor JR, Gur RC, Calkins ME, Moore TM, Port AM, Ruparel K, Scott JC, Troyan S, Gur RE, Roalf DR. Comparison of two cognitive screening measures in a longitudinal sample of youth at-risk for psychosis. Schizophr Res 2022; 246:216-224. [PMID: 35809354 PMCID: PMC10838490 DOI: 10.1016/j.schres.2022.06.017] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 12/16/2021] [Revised: 06/13/2022] [Accepted: 06/19/2022] [Indexed: 10/17/2022]
Abstract
BACKGROUND Validated screening tools are needed to detect subtle cognitive impairment in individuals at-risk for developing psychosis. Here, the utility of the Mini-Mental Status Examination (MMSE) and Penn Computerized Neurocognitive Battery (CNB) were evaluated for detecting cognitive impairment in individuals with psychosis spectrum (PS) symptoms. METHODS Participants (n = 229; 54 % female) completed the MMSE and CNB at baseline and two-year follow-up. PS (n = 91) and typically developing (TD; n = 138) participants were enrolled at baseline based on the presence or absence of PS symptoms. After two years, 65 participants remained PS, 104 participants remained TD, 23 participants had Emergent (EP) subthreshold PS symptoms, and 37 participants were experiencing Other Psychopathology (OP). RESULTS Generally, those with PS had lower scores than TD on both the MMSE (p < 0.0001) and CNB (p < 0.0001). Additionally, OP participants performed lower on the MMSE than TD (p = 0.02). Receiver operating characteristic (ROC) analyses indicated similar area under the curve (AUCs) for the two instruments (0.67); the MMSE showed higher specificity (0.71 vs. 0.62), while the CNB showed higher sensitivity (0.66 vs 0.52). Use of the MMSE and CNB in combination provided the highest diagnostic classification. CONCLUSION The MMSE and CNB can be used to screen for cognitive impairment in PS. The MMSE is better at ruling out PS-related cognitive impairment while the CNB is better at ruling in PS-related cognitive impairment. Overall, our results indicate that both tests are useful in screening for cognitive impairment, particularly in combination, in a PS population.
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Affiliation(s)
- Jenna R Kantor
- Brain Behavior Laboratory, Department of Psychiatry, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA; Lifespan Brain Institute, Department of Child and Adolescent Psychiatry and Behavioral Sciences, Children's Hospital of Philadelphia, USA
| | - Ruben C Gur
- Brain Behavior Laboratory, Department of Psychiatry, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA; Lifespan Brain Institute, Department of Child and Adolescent Psychiatry and Behavioral Sciences, Children's Hospital of Philadelphia, USA
| | - Monica E Calkins
- Brain Behavior Laboratory, Department of Psychiatry, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA; Lifespan Brain Institute, Department of Child and Adolescent Psychiatry and Behavioral Sciences, Children's Hospital of Philadelphia, USA
| | - Tyler M Moore
- Brain Behavior Laboratory, Department of Psychiatry, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA; Lifespan Brain Institute, Department of Child and Adolescent Psychiatry and Behavioral Sciences, Children's Hospital of Philadelphia, USA
| | - Allison M Port
- Brain Behavior Laboratory, Department of Psychiatry, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA; Lifespan Brain Institute, Department of Child and Adolescent Psychiatry and Behavioral Sciences, Children's Hospital of Philadelphia, USA
| | - Kosha Ruparel
- Brain Behavior Laboratory, Department of Psychiatry, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA; Lifespan Brain Institute, Department of Child and Adolescent Psychiatry and Behavioral Sciences, Children's Hospital of Philadelphia, USA
| | - J Cobb Scott
- Brain Behavior Laboratory, Department of Psychiatry, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA; VISN4 Mental Illness Research, Education, and Clinical Center at the Philadelphia VA Medical Center, Philadelphia, PA 19104, USA
| | - Scott Troyan
- Brain Behavior Laboratory, Department of Psychiatry, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA; Lifespan Brain Institute, Department of Child and Adolescent Psychiatry and Behavioral Sciences, Children's Hospital of Philadelphia, USA
| | - Raquel E Gur
- Brain Behavior Laboratory, Department of Psychiatry, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA; Lifespan Brain Institute, Department of Child and Adolescent Psychiatry and Behavioral Sciences, Children's Hospital of Philadelphia, USA
| | - David R Roalf
- Brain Behavior Laboratory, Department of Psychiatry, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA; Lifespan Brain Institute, Department of Child and Adolescent Psychiatry and Behavioral Sciences, Children's Hospital of Philadelphia, USA.
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Van Harten PN, Pieters LE. Clinical Consequences of Motor Behavior as Transdiagnostic Phenomenon. Schizophr Bull 2022; 48:749-751. [PMID: 35296900 PMCID: PMC9212087 DOI: 10.1093/schbul/sbac025] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 11/12/2022]
Affiliation(s)
- Peter N Van Harten
- Psychiatric Center GGz Centraal, Amersfoort, The Netherlands
- Department of Psychiatry, School for Mental Health and Neuroscience, Maastricht University Medical Center, Maastricht, The Netherlands
| | - Lydia E Pieters
- Psychiatric Center GGz Centraal, Amersfoort, The Netherlands
- Department of Psychiatry, School for Mental Health and Neuroscience, Maastricht University Medical Center, Maastricht, The Netherlands
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Moore TM, Lahey BB. Issues in Estimating Interpretable Lower Order Factors in Second-Order Hierarchical Models: Commentary on Clark et al. (2021). Clin Psychol Sci 2022; 10:593-598. [PMID: 35677113 PMCID: PMC9173570 DOI: 10.1177/21677026211035114] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 09/13/2023]
Abstract
Clark and colleagues asserted that lower-order factors in second-order models are comparable to specific factors in bifactor models when residualized on the general factor (Clark et al., 2021). Modeling simulated data demonstrated that residualized lower-order factors are correlated with bifactor specific factors only to the extent that factor loadings are proportional. Modeling actual data with violations of proportionality showed that specific and residualized lower-order factors are not always highly correlated and have differential correlations with criterion variables, even when both models fit acceptably. Because proportionality constraints limit only second-order models, bifactor models should be the first option for hierarchical modeling.
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Gur RE. Considering alternatives to the schizophrenia construct. Schizophr Res 2022; 242:49-51. [PMID: 35033392 DOI: 10.1016/j.schres.2021.12.027] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 09/26/2021] [Revised: 12/18/2021] [Accepted: 12/19/2021] [Indexed: 02/08/2023]
Affiliation(s)
- Raquel E Gur
- Department of Psychiatry, University of Pennsylvania, Perelman School of Medicine, United States of America.
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Schultze-Lutter F, Kindler J, Ambarini TK, Michel C. Positive psychotic symptoms in childhood and adolescence. Curr Opin Psychol 2021; 45:101287. [PMID: 35016089 DOI: 10.1016/j.copsyc.2021.11.007] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/31/2021] [Revised: 10/21/2021] [Accepted: 11/24/2021] [Indexed: 11/30/2022]
Abstract
Based on the assumption of a universal neurodevelopmental model of psychosis, especially of the schizophrenia spectrum, the diagnosis (and treatment) of psychosis in minors commonly follows those in adults. Yet, as our review demonstrates, recent years have seen an emergence of studies of minors indicating that developmental aspects may play a crucial role in the prevalence and appraisal of diagnostically relevant positive psychotic symptoms in their full-blown and subthreshold forms, including neurobiogenetic and other risk factors, such as migration. Thus, caution is advised to not overpathologize potentially transient and clinically irrelevant occurrence of (subthreshold) positive psychotic symptoms in the diagnosis and treatment of psychotic disorders and their clinical high-risk states in minors. More studies on developmental aspects are urgently needed.
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Affiliation(s)
- Frauke Schultze-Lutter
- Department of Psychiatry and Psychotherapy, Medical Faculty, Heinrich-Heine University Düsseldorf, Bergische Landstraße 2, 40470 Düsseldorf, Germany; University Hospital of Child and Adolescent Psychiatry and Psychotherapy, University of Bern, Bolligenstr, 111, 3000 Bern 60, Switzerland; Department of Psychology, Faculty of Psychology, Airlangga University, Airlangga 4-6, Surabaya 60286, Indonesia.
| | - Jochen Kindler
- University Hospital of Child and Adolescent Psychiatry and Psychotherapy, University of Bern, Bolligenstr, 111, 3000 Bern 60, Switzerland
| | - Tri Kurniati Ambarini
- Department of Psychology, Faculty of Psychology, Airlangga University, Airlangga 4-6, Surabaya 60286, Indonesia
| | - Chantal Michel
- University Hospital of Child and Adolescent Psychiatry and Psychotherapy, University of Bern, Bolligenstr, 111, 3000 Bern 60, Switzerland
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