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      Childhood generalized specific phobia as an early marker of internalizing psychopathology across the lifespan: results from the World Mental Health Surveys

      research-article
      1 , 2 , , 3 , 4 , 5 , 6 , 7 , 8 , 9 , 10 , 11 , 12 , 13 , 14 , 15 , 16 , 17 , 18 , 19 , 20 , 21 , 22 , 22 , 23 , 24 , 25 , 26 , 27 , 28 , 29 , 30 , 31 , 32 , 33 , 34 , 35 , 36 , 37 , 38 , 1 , 2 , on behalf of the WHO World Mental Health Survey Collaborators
      BMC Medicine
      BioMed Central
      Specific phobia, Internalizing disorders, Early markers, Comorbidity, Suicidality

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          Abstract

          Background

          Specific phobia (SP) is a relatively common disorder associated with high levels of psychiatric comorbidity. Because of its early onset, SP may be a useful early marker of internalizing psychopathology, especially if generalized to multiple situations. This study aimed to evaluate the association of childhood generalized SP with comorbid internalizing disorders.

          Methods

          We conducted retrospective analyses of the cross-sectional population-based World Mental Health Surveys using the Composite International Diagnostic Interview. Outcomes were lifetime prevalence, age of onset, and persistence of internalizing disorders; past-month disability; lifetime suicidality; and 12-month serious mental illness. Logistic and linear regressions were used to assess the association of these outcomes with the number of subtypes of childhood-onset (< 13 years) SP.

          Results

          Among 123,628 respondents from 25 countries, retrospectively reported prevalence of childhood SP was 5.9%, 56% of whom reported one, 25% two, 10% three, and 8% four or more subtypes. Lifetime prevalence of internalizing disorders increased from 18.2% among those without childhood SP to 46.3% among those with one and 75.6% those with 4+ subtypes (OR = 2.4, 95% CI 2.3–2.5, p < 0.001). Twelve-month persistence of lifetime internalizing comorbidity at interview increased from 47.9% among those without childhood SP to 59.0% and 79.1% among those with 1 and 4+ subtypes (OR = 1.4, 95% CI 1.4–1.5, p < 0.001). Respondents with 4+ subtypes also reported significantly more disability (3.5 days out of role in the past month) than those without childhood SP (1.1 days) or with only 1 subtype (1.8 days) ( B = 0.56, SE 0.06, p < 0.001) and a much higher rate of lifetime suicide attempts (16.8%) than those without childhood SP (2.0%) or with only 1 subtype (6.5%) (OR = 1.7, 95% CI 1.7–1.8, p < 0.001).

          Conclusions

          This large international study shows that childhood-onset generalized SP is related to adverse outcomes in the internalizing domain throughout the life course. Comorbidity, persistence, and severity of internalizing disorders all increased with the number of childhood SP subtypes. Although our study cannot establish whether SP is causally associated with these poor outcomes or whether other factors, such as a shared underlying vulnerability, explain the association, our findings clearly show that childhood generalized SP identifies an important target group for early intervention.

          Electronic supplementary material

          The online version of this article (10.1186/s12916-019-1328-3) contains supplementary material, which is available to authorized users.

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          Most cited references35

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          The World Mental Health (WMH) Survey Initiative version of the World Health Organization (WHO) Composite International Diagnostic Interview (CIDI)

          This paper presents an overview of the World Mental Health (WMH) Survey Initiative version of the World Health Organization (WHO) Composite International Diagnostic Interview (CIDI) and a discussion of the methodological research on which the development of the instrument was based. The WMH‐CIDI includes a screening module and 40 sections that focus on diagnoses (22 sections), functioning (four sections), treatment (two sections), risk factors (four sections), socio‐demographic correlates (seven sections), and methodological factors (two sections). Innovations compared to earlier versions of the CIDI include expansion of the diagnostic sections, a focus on 12‐month as well as lifetime disorders in the same interview, detailed assessment of clinical severity, and inclusion of information on treatment, risk factors, and consequences. A computer‐assisted version of the interview is available along with a direct data entry software system that can be used to keypunch responses to the paper‐and‐pencil version of the interview. Computer programs that generate diagnoses are also available based on both ICD‐10 and DSM‐IV criteria. Elaborate CD‐ROM‐based training materials are available to teach interviewers how to administer the interview as well as to teach supervisors how to monitor the quality of data collection. Copyright © 2004 Whurr Publishers Ltd.
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            Concordance of the Composite International Diagnostic Interview Version 3.0 (CIDI 3.0) with standardized clinical assessments in the WHO World Mental Health Surveys

            The DSM‐IV diagnoses generated by the fully structured lay‐administered Composite International Diagnostic Interview Version 3.0 (CIDI 3.0) in the WHO World Mental Health (WMH) surveys were compared to diagnoses based on follow‐up interviews with the clinician‐administered non‐patient edition of the Structured Clinical Interview for DSM‐IV (SCID) in probability subsamples of the WMH surveys in France, Italy, Spain, and the US. CIDI cases were oversampled. The clinical reappraisal samples were weighted to adjust for this oversampling. Separate samples were assessed for lifetime and 12‐month prevalence. Moderate to good individual‐level CIDI‐SCID concordance was found for lifetime prevalence estimates of most disorders. The area under the ROC curve (AUC, a measure of classification accuracy that is not influenced by disorder prevalence) was 0.76 for the dichotomous classification of having any of the lifetime DSM‐IV anxiety, mood and substance disorders assessed in the surveys and in the range 0.62–0.93 for individual disorders, with an inter‐quartile range (IQR) of 0.71–0.86. Concordance increased when CIDI symptom‐level data were added to predict SCID diagnoses in logistic regression equations. AUC for individual disorders in these equations was in the range 0.74–0.99, with an IQR of 0.87–0.96. CIDI lifetime prevalence estimates were generally conservative relative to SCID estimates. CIDI‐SCID concordance for 12‐month prevalence estimates could be studied powerfully only for two disorder classes, any anxiety disorder (AUC = 0.88) and any mood disorder (AUC = 0.83). As with lifetime prevalence, 12‐month concordance improved when CIDI symptom‐level data were added to predict SCID diagnoses. CIDI 12‐month prevalence estimates were unbiased relative to SCID estimates. The validity of the CIDI is likely to be under‐estimated in these comparisons due to the fact that the reliability of the SCID diagnoses, which is presumably less than perfect, sets a ceiling on maximum CIDI‐SCID concordance. Copyright © 2006 John Wiley & Sons, Ltd.
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              An invariant dimensional liability model of gender differences in mental disorder prevalence: evidence from a national sample.

              Epidemiological studies of categorical mental disorders consistently report that gender differences exist in many disorder prevalence rates and that disorders are often comorbid. Can a dimensional multivariate liability model be developed to clarify how gender impacts diverse, comorbid mental disorders? We pursued this possibility in the National Epidemiologic Survey on Alcohol and Related Conditions (NESARC; N = 43,093). Gender differences in prevalence were systematic such that women showed higher rates of mood and anxiety disorders, and men showed higher rates of antisocial personality and substance use disorders. We next investigated patterns of disorder comorbidity and found that a dimensional internalizing-externalizing liability model fit the data well, where internalizing is characterized by mood and anxiety disorders, and externalizing is characterized by antisocial personality and substance use disorders. This model was gender invariant, indicating that observed gender differences in prevalence rates originate from women and men's different average standings on latent internalizing and externalizing liability dimensions. As hypothesized, women showed a higher mean level of internalizing, while men showed a higher mean level of externalizing. We discuss implications of these findings for understanding gender differences in psychopathology and for classification and intervention. PsycINFO Database Record (c) 2012 APA, all rights reserved.
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                Author and article information

                Contributors
                +31 503633241 , y.a.de.vries@rug.nl
                ali_alhamzawi2000@yahoo.com
                jalonso@imim.es
                guilhermelgborges@gmail.com
                ronny.bruffaerts@uzleuven.be
                bp.bunting@ulster.ac.uk
                jcaldasalmeida@gmail.com
                alfredocia@gmail.com
                gdegirolamo@fatebenefratelli.it
                rdinolova@abv.bg
                oluyomie@yahoo.com
                florescu.silvia@gmail.com
                oye_gureje@yahoo.com
                jmharo@pssjd.org
                chiyihu@126.com
                eliegkaram@hotmail.com
                aimee.karam@idraac.org
                norito@m.u-tokyo.ac.jp
                andrzej.kiejna@umed.wroc.pl
                Viviane.Kovess@ehesp.fr
                singlee@cuhk.edu.hk
                zeinam@umich.edu
                fernando.navarro@carm.es
                marina.piazza@upch.pe
                Kate.scott@otago.ac.nz
                mhave@trimbos.nl
                ytorres@CES.EDU.CO
                mcviana6@gmail.com
                Kessler@hcp.med.harvard.edu
                peter.de.jonge@rug.nl
                Journal
                BMC Med
                BMC Med
                BMC Medicine
                BioMed Central (London )
                1741-7015
                24 May 2019
                24 May 2019
                2019
                : 17
                : 101
                Affiliations
                [1 ]ISNI 0000 0004 0407 1981, GRID grid.4830.f, Faculty of Behavioural and Social Sciences, Department of Developmental Psychology, , University of Groningen, ; Groningen, the Netherlands
                [2 ]Interdisciplinary Center Psychopathology and Emotion regulation, University Medical Center Groningen, University of Groningen, Groningen, the Netherlands
                [3 ]College of Medicine, Al-Qadisiya University, Diwaniya governorate, Iraq
                [4 ]ISNI 0000 0004 1767 9005, GRID grid.20522.37, Health Services Research Unit, , IMIM-Hospital del Mar Medical Research Institute, ; Barcelona, Spain
                [5 ]ISNI 0000 0000 9314 1427, GRID grid.413448.e, CIBER en Epidemiología y Salud Pública (CIBERESP), ; Barcelona, Spain
                [6 ]ISNI 0000 0001 2172 2676, GRID grid.5612.0, Pompeu Fabra University (UPF), ; Barcelona, Spain
                [7 ]ISNI 0000 0004 1776 9908, GRID grid.419154.c, National Institute of Psychiatry Ramón de la Fuente Muñiz, ; Mexico City, Mexico
                [8 ]ISNI 0000 0001 0668 7884, GRID grid.5596.f, Universitair Psychiatrisch Centrum - Katholieke Universiteit Leuven (UPC-KUL), Campus Gasthuisberg, ; Leuven, Belgium
                [9 ]ISNI 0000000105519715, GRID grid.12641.30, School of Psychology, , Ulster University, ; Londonderry, UK
                [10 ]ISNI 0000000121511713, GRID grid.10772.33, Lisbon Institute of Global Mental Health and Chronic Diseases Research Center (CEDOC), NOVA Medical School / Faculdade de Ciências Médicas, Universidade Nova de Lisboa, ; Lisbon, Portugal
                [11 ]Anxiety Clinic and Research Center, Buenos Aires, Argentina
                [12 ]GRID grid.419422.8, IRCCS Istituto Centro San Giovanni di Dio Fatebenefratelli, ; Brescia, Italy
                [13 ]GRID grid.416574.5, National Center of Public Health and Analyses, ; Sofia, Bulgaria
                [14 ]ISNI 0000 0004 1794 5983, GRID grid.9582.6, Department of Psychiatry, College of Medicine, , University of Ibadan, ; Ibadan, Nigeria
                [15 ]National School of Public Health, Management and Development, Bucharest, Romania
                [16 ]ISNI 0000 0004 1764 5403, GRID grid.412438.8, Department of Psychiatry, , University College Hospital, ; Ibadan, Nigeria
                [17 ]ISNI 0000 0004 1937 0247, GRID grid.5841.8, Parc Sanitari Sant Joan de Déu, CIBERSAM, , Universitat de Barcelona, ; Sant Boi de Llobregat, Barcelona, Spain
                [18 ]ISNI 0000 0004 1773 5396, GRID grid.56302.32, Department of Psychology, College of Education, , King Saud University, ; Riyadh, Saudi Arabia
                [19 ]GRID grid.452897.5, Shenzhen Institute of Mental Health and Shenzhen Kangning Hospital, ; Shenzhen, China
                [20 ]ISNI 0000 0001 2288 0342, GRID grid.33070.37, Department of Psychiatry and Clinical Psychology, Faculty of Medicine, , Balamand University, ; Beirut, Lebanon
                [21 ]ISNI 0000 0004 1773 3761, GRID grid.416659.9, Department of Psychiatry and Clinical Psychology, , St George Hospital University Medical Center, ; Beirut, Lebanon
                [22 ]GRID grid.429040.b, Institute for Development Research Advocacy and Applied Care (IDRAAC), ; Beirut, Lebanon
                [23 ]ISNI 0000 0000 9832 2227, GRID grid.416859.7, National Institute of Mental Health, National Center for Neurology and Psychiatry, ; Kodaira, Tokyo Japan
                [24 ]ISNI 0000 0001 1090 049X, GRID grid.4495.c, Wroclaw Medical University, ; Wrocław, Poland
                [25 ]ISNI 0000 0001 2296 1994, GRID grid.445638.8, University of Lower Silesia, ; Wroclaw, Poland
                [26 ]ISNI 0000 0001 2188 0914, GRID grid.10992.33, Ecole des Hautes Etudes en Santé Publique (EHESP), EA 4057, , Paris Descartes University, ; Paris, France
                [27 ]ISNI 0000 0004 1937 0482, GRID grid.10784.3a, Department of Psychiatry, , Chinese University of Hong Kong, ; Tai Po, Hong Kong
                [28 ]ISNI 0000000086837370, GRID grid.214458.e, Survey Research Center, Institute for Social Research, , University of Michigan, ; Ann Arbor, MI USA
                [29 ]ISNI 0000 0000 8745 438X, GRID grid.419058.1, UDIF-SM, Subdirección General de Planificación, Innovación y Cronicidad, Servicio Murciano de Salud, IMIB-Arrixaca, CIBERESP-Murcia, ; Murcia, Spain
                [30 ]GRID grid.452553.0, Instituto Murciano de Investigación Biosanitaria (IMIB) Virgen de la Arrixaca, ; Murcia, Spain
                [31 ]Centro de Investigación Biomédica en ERed en Epidemiología y Salud Pública (CIBERESP), Murcia, Spain
                [32 ]ISNI 0000 0004 0636 549X, GRID grid.419228.4, Instituto Nacional de Salud, ; Lima, Peru
                [33 ]Universidad Cayetano Heredia, Lima, Peru
                [34 ]ISNI 0000 0004 1936 7830, GRID grid.29980.3a, Department of Psychological Medicine, , University of Otago, ; Dunedin, Otago New Zealand
                [35 ]ISNI 0000 0001 0835 8259, GRID grid.416017.5, Trimbos Instituut, Netherlands Institute of Mental Health and Addiction, ; Utrecht, Netherlands
                [36 ]ISNI 0000 0001 0812 5789, GRID grid.411140.1, Center for Excellence on Research in Mental Health, , CES University, ; Medellin, Colombia
                [37 ]ISNI 0000 0001 2167 4168, GRID grid.412371.2, Department of Social Medicine, Postgraduate Program in Public Health, , Federal University of Espírito Santo, ; Vitoria, Brazil
                [38 ]ISNI 000000041936754X, GRID grid.38142.3c, Department of Health Care Policy, , Harvard Medical School, ; Boston, MA USA
                Article
                1328
                10.1186/s12916-019-1328-3
                6533738
                31122269
                0175c33e-afb1-4616-b62d-e3df22294dbf
                © The Author(s). 2019

                Open AccessThis article is distributed under the terms of the Creative Commons Attribution 4.0 International License ( http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The Creative Commons Public Domain Dedication waiver ( http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated.

                History
                : 23 January 2019
                : 17 April 2019
                Funding
                Funded by: FundRef http://dx.doi.org/10.13039/100000025, National Institute of Mental Health;
                Award ID: MH070884
                Award Recipient :
                Funded by: FundRef http://dx.doi.org/10.13039/100007197, U.S. Public Health Service;
                Award ID: R13-MH066849
                Award ID: R01-MH069864
                Award Recipient :
                Funded by: U.S. Public Health Service (US)
                Award ID: R01-DA016558
                Award Recipient :
                Funded by: FundRef http://dx.doi.org/10.13039/100000061, Fogarty International Center;
                Award ID: R03-TW006481
                Award Recipient :
                Categories
                Research Article
                Custom metadata
                © The Author(s) 2019

                Medicine
                specific phobia,internalizing disorders,early markers,comorbidity,suicidality
                Medicine
                specific phobia, internalizing disorders, early markers, comorbidity, suicidality

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