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Basterfield C, Fitzsimmons-Craft EE, Taylor CB, Eisenberg D, Wilfley DE, Newman MG. Internalizing psychopathology and its links to suicidal ideation, dysfunctional attitudes, and help-seeking readiness in a national sample of college students. J Affect Disord 2024; 350:255-263. [PMID: 38224742 PMCID: PMC11057016 DOI: 10.1016/j.jad.2024.01.058] [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] [Received: 09/20/2023] [Revised: 12/16/2023] [Accepted: 01/04/2024] [Indexed: 01/17/2024]
Abstract
BACKGROUND Recent evidence suggests that multiple emotional disorders may be better assessed using dimensional models of psychopathology. The current study utilized a cross-sectional population survey of college students (N = 8613 participants) to examine the extent to which broad psychopathology factors accounted for specific associations between emotional problems and clinical and behavioral validators: suicidality, dysfunctional attitudes, and treatment seeking. METHODS Confirmatory factor models were estimated to identify the best structure of psychopathology. Models were then estimated to examine the broad and specific associations between each psychopathology indicator and the clinical and behavioral validators. RESULTS The hierarchical model of psychopathology with internalizing problems at the top, fear, and distress at the second level, and five specific symptom dimensions at the third level evidenced the best fit. The associations between symptom indicators of psychopathology and clinical and behavioral validators were relatively small and inconsistent. Instead, much of the association between clinical and behavioral validators and emotional problems operated at a higher-order level. LIMITATIONS The cross-sectional nature of the survey precludes the ability to make conclusions regarding causality. CONCLUSIONS Researchers should focus on investigating the shared or common components across emotional disorders, particularly concerning individuals presenting with higher rates of suicidal ideation dysfunctional attitudes, and help-seeking behavior. Using higher-order dimensions of psychopathology could simplify the complex presentation of multiple co-occurring disorders and suggest valid constructs for future investigations.
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Aboul-Ata MA, Qonsua FT, Saadi IAA. Personality Pathology and Suicide Risk: Examining the Relationship Between DSM-5 Alternative Model Traits and Suicidal Ideation and Behavior in College-Aged Individuals. Psychol Rep 2023:332941231218940. [PMID: 38029776 DOI: 10.1177/00332941231218940] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/01/2023]
Abstract
BACKGROUND This study examines the link between personality pathology and suicide risk regarding the DSM-5 alternative model of personality disorders. METHOD The study investigates the facets, domains, internalizing, and externalizing of personality pathology and their correlation and predictive significance for suicidal ideation and behavior. This study examined a diverse and balanced sample of 1,398 college students aged between 18- and 29-year-olds from nine colleges in Kafrelshiekh University, with nearly equal representation of both genders (687 males, 711 females), a mix of rural and urban residents (807 rural, 591 urban), and a wide range of socioeconomic backgrounds (15 very low SES, 84 low SES, 878 moderate SES, 364 high SES, and 57 very high SES). The Personality Inventory for the DSM-5 (PID-5) was utilized to assess personality pathology. Columbia-Suicide Severity Rating Scale (C-SSRS) was used to evaluate suicidal ideation and behavior. RESULTS AND DISCUSSION Logistic regression reveals significant associations between personality traits and suicidal ideation (e.g., Anhedonia, Suspiciousness) and behavior (e.g., Risk Taking, Depressivity). Negative Affect and Detachment are significantly linked to suicidal ideation, while Detachment, Disinhibition, and Psychoticism are linked to suicidal behavior. Internalizing personality pathology predicts both ideation and behavior, indicating a contribution to suicidal thoughts and self-destructive acts. Externalizing is a significant predictor of suicidal behavior.
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Affiliation(s)
| | - Faten T Qonsua
- Department of Psychology, Kafrelsheikh University, Kafr el-Sheikh, Egypt
| | - Ibrahim A A Saadi
- Department of Psychology, University of Jeddah, Jeddah, Saudi Arabia
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Wang M, Richmond LL, Schleider JL, Nelson BD, Luhmann CC. Predicting internalizing symptoms with machine learning: identifying individuals that need care. JOURNAL OF AMERICAN COLLEGE HEALTH : J OF ACH 2023:1-10. [PMID: 37943500 DOI: 10.1080/07448481.2023.2277185] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 12/05/2022] [Accepted: 10/22/2023] [Indexed: 11/10/2023]
Abstract
Objective The current project aims to identify individuals in urgent need of mental health care, using a machine learning algorithm (random forest). Comparison/contrast with conventional regression analyses is discussed. Participants: A total of 2,409 participants were recruited from an anonymous university, including undergraduate and graduate students, faculty, and staff. Methods: Answers to a COVID-19 impact survey, the Patient Health Questionnaire-9 (PHQ-9), and the Generalized Anxiety Disorder-7 (GAD-7) were collected. The total scores of PHQ-9 and GAD-7 were regressed on six composites that were created from the questionnaire items, based on their topics. A random forest was trained and validated. Results: Results indicate that the random forest model was able to make accurate, prospective predictions (R2 = .429 on average) and we review variables that were deemed predictively relevant. Conclusions: Overall, the study suggests that predictive models can be clinically useful in identifying individuals with internalizing symptoms based on daily life disruption experiences.
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Affiliation(s)
- Mengxing Wang
- Department of Psychology, Stony Brook University, Stony Brook, New York, USA
| | - Lauren L Richmond
- Department of Psychology, Stony Brook University, Stony Brook, New York, USA
| | - Jessica L Schleider
- Department of Psychology, Stony Brook University, Stony Brook, New York, USA
| | - Brady D Nelson
- Department of Psychology, Stony Brook University, Stony Brook, New York, USA
| | - Christian C Luhmann
- Department of Psychology, Stony Brook University, Stony Brook, New York, USA
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Wang M, Eaton NR. Linking non-suicidal self-injury to psychopathology: The utility of transdiagnostic and DSM-based models. J Affect Disord 2023; 332:55-63. [PMID: 37004904 DOI: 10.1016/j.jad.2023.03.075] [Citation(s) in RCA: 3] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 10/31/2022] [Revised: 03/02/2023] [Accepted: 03/24/2023] [Indexed: 04/04/2023]
Abstract
Non-suicidal self-injury (NSSI) is a significant public health concern, and its primary formal link to the universe of psychopathology content in DSM diagnoses has been mostly through borderline personality disorder (BPD). Recent research has produced ample evidence of weaknesses of diagnoses relative to transdiagnostic psychopathology dimensions, and found that NSSI-related variables like suicidality are best predicted by transdiagnostic versus diagnosis-based variables. These findings suggest a need to characterize how NSSI may relate to different forms of psychopathology classification constructs. We examined how transdiagnostic dimensions of psychopathology relate to NSSI, focusing on how transdiagnostic (shared) variance of dimensional psychopathology spectra might differentially explained the variance in NSSI relative to traditional DSM diagnoses. In two nationally representative United States samples (Ns = 34,653 and 36,309), we modeled the common distress-fear-externalizing transdiagnostic comorbidity model and investigated questions of predictive utility of these dimensional and categorical psychopathology structures. Transdiagnostic dimensions were superior in predicting NSSI compared to common DSM-IV and DSM-5 diagnoses. These dimensions accounted for 33.6-38.7 % of NSSI variance across all analyses in both samples. DSM-IV/DSM-5 diagnoses, however, demonstrated only modest incremental prediction of NSSI over and above the transdiagnostic dimensions. These results support a transdiagnostic reconceptualization of NSSI's links with psychopathology and highlight the importance of transdiagnostic dimensions for predicting clinical outcomes relating to self-injurious behaviors. Implications for research and clinical practice are discussed.
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Affiliation(s)
- Mengxing Wang
- Department of Psychology, Stony Brook University, United States of America.
| | - Nicholas R Eaton
- Department of Psychology, Stony Brook University, United States of America
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5
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Pat N, Riglin L, Anney R, Wang Y, Barch DM, Thapar A, Stringaris A. Motivation and Cognitive Abilities as Mediators Between Polygenic Scores and Psychopathology in Children. J Am Acad Child Adolesc Psychiatry 2022; 61:782-795.e3. [PMID: 34506929 DOI: 10.1016/j.jaac.2021.08.019] [Citation(s) in RCA: 5] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 09/03/2020] [Revised: 07/23/2021] [Accepted: 08/31/2021] [Indexed: 12/14/2022]
Abstract
OBJECTIVE Fundamental questions in biological psychiatry concern the mechanisms that mediate between genetic liability and psychiatric symptoms. Genetic liability for many common psychiatric disorders often confers transdiagnostic risk to develop a wide variety of psychopathological symptoms through yet unknown pathways. This study examined the psychological and cognitive pathways that might mediate the relationship between genetic liability (indexed by polygenic scores; PS) and broad psychopathology (indexed by p factor and its underlying dimensions). METHOD First, which of the common psychiatric PSs (major depressive disorder [MDD], attention-deficit/hyperactivity disorder [ADHD], anxiety, bipolar disorder, schizophrenia, autism) that were associated with p factor were identified. Then focused was shifted to 3 pathways: punishment sensitivity (reflected by behavioral inhibition system), reward sensitivity (reflected by behavioral activation system), and cognitive abilities (reflected by g factor based on 10 neurocognitive tasks). We applied structural equation modeling on the Adolescent Brain Cognitive Development (ABCD) Study dataset (n = 4,814; 2,263 girls; 9-10 years old). RESULTS MDD and ADHD PSs were associated with p factor. The association between MDD PS and psychopathology was partially mediated by punishment sensitivity and cognitive abilities (proportion mediated = 22.35%). Conversely, the influence of ADHD PS on psychopathology was partially mediated by reward sensitivity and cognitive abilities (proportion mediated = 30.04%). The mediating role of punishment sensitivity was specific to emotional/internalizing. The mediating role of both reward sensitivity and cognitive abilities was specific to behavioral/externalizing and neurodevelopmental dimensions of psychopathology. CONCLUSION This study provides a better understanding of how genetic risks for MDD and ADHD confer risks for psychopathology and suggests potential prevention/intervention targets for children at risk.
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Affiliation(s)
- Narun Pat
- University of Otago, Dunedin, New Zealand.
| | | | | | - Yue Wang
- University of Otago, Dunedin, New Zealand
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6
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Kotov R, Krueger RF, Watson D, Cicero DC, Conway CC, DeYoung CG, Eaton NR, Forbes MK, Hallquist MN, Latzman RD, Mullins-Sweatt SN, Ruggero CJ, Simms LJ, Waldman ID, Waszczuk MA, Wright AGC. The Hierarchical Taxonomy of Psychopathology (HiTOP): A Quantitative Nosology Based on Consensus of Evidence. Annu Rev Clin Psychol 2021; 17:83-108. [PMID: 33577350 DOI: 10.1146/annurev-clinpsy-081219-093304] [Citation(s) in RCA: 182] [Impact Index Per Article: 60.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/09/2022]
Abstract
Traditional diagnostic systems went beyond empirical evidence on the structure of mental health. Consequently, these diagnoses do not depict psychopathology accurately, and their validity in research and utility in clinicalpractice are therefore limited. The Hierarchical Taxonomy of Psychopathology (HiTOP) consortium proposed a model based on structural evidence. It addresses problems of diagnostic heterogeneity, comorbidity, and unreliability. We review the HiTOP model, supporting evidence, and conceptualization of psychopathology in this hierarchical dimensional framework. The system is not yet comprehensive, and we describe the processes for improving and expanding it. We summarize data on the ability of HiTOP to predict and explain etiology (genetic, environmental, and neurobiological), risk factors, outcomes, and treatment response. We describe progress in the development of HiTOP-based measures and in clinical implementation of the system. Finally, we review outstanding challenges and the research agenda. HiTOP is of practical utility already, and its ongoing development will produce a transformative map of psychopathology.
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Affiliation(s)
- Roman Kotov
- Departments of Psychiatry and Psychology, Stony Brook University, Stony Brook, New York 11794, USA;
| | - Robert F Krueger
- Department of Psychology, University of Minnesota, Minneapolis, Minnesota 55455, USA
| | - David Watson
- Department of Psychology, University of Notre Dame, Notre Dame, Indiana 46556, USA
| | - David C Cicero
- Department of Psychology, University of North Texas, Denton, Texas 76203, USA
| | | | - Colin G DeYoung
- Department of Psychology, University of Minnesota, Minneapolis, Minnesota 55455, USA
| | - Nicholas R Eaton
- Departments of Psychiatry and Psychology, Stony Brook University, Stony Brook, New York 11794, USA;
| | - Miriam K Forbes
- Centre for Emotional Health, Department of Psychology, Macquarie University, Macquarie Park, New South Wales 2109, Australia
| | - Michael N Hallquist
- Department of Psychology and Neuroscience, University of North Carolina at Chapel Hill, Chapel Hill, North Carolina 27599, USA
| | - Robert D Latzman
- Department of Psychology, Georgia State University, Atlanta, Georgia 30303, USA
| | | | - Camilo J Ruggero
- Department of Psychology, University of North Texas, Denton, Texas 76203, USA
| | - Leonard J Simms
- Department of Psychology, University at Buffalo, State University of New York, Buffalo, New York 14260, USA
| | - Irwin D Waldman
- Department of Psychology, Emory University, Atlanta, Georgia 30322, USA
| | - Monika A Waszczuk
- Department of Psychology, Rosalind Franklin University, North Chicago, Illinois 60064, USA
| | - Aidan G C Wright
- Department of Psychology, University of Pittsburgh, Pittsburgh, Pennsylvania 15260, USA
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The structure of psychopathology and association with poor sleep, self-harm, suicidality, risky sexual behavior, and low self-esteem in a population sample of adolescents. Dev Psychopathol 2020; 33:1208-1219. [PMID: 32468983 DOI: 10.1017/s0954579420000437] [Citation(s) in RCA: 9] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/07/2023]
Abstract
There is a growing body of evidence highlighting the presence of a single general dimension of psychopathology that can account for multiple associations across mental and substance use disorders. However, relatively little evidence has emerged regarding the validity of this model with respect to a range of factors that have been previously implicated across multiple disorders. The current study utilized a cross-sectional population survey of adolescents (n = 2,003) to examine the extent to which broad psychopathology factors account for specific associations between psychopathology and key validators: poor sleep, self-harm, suicidality, risky sexual behavior, and low self-esteem. Confirmatory factor models, latent class models, and factor mixture models were estimated to identify the best structure of psychopathology. Structural equation models were then estimated to examine the broad and specific associations between each psychopathology indicator and the validators. A confirmatory factor model with three lower-order factors, representing internalizing, externalizing, and psychotic-like experiences, and a single higher-order factor evidenced the best fit. The associations between manifest indicators of psychopathology and validators were largely nonspecific. However, significant and large direct effects were found between several pairwise associations. These findings have implications for the identification of potential targets for intervention and/or tailoring of prevention programs.
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8
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Conway CC, Latzman RD, Krueger RF. A Meta-Structural Model of Common Clinical Disorder and Personality Disorder Symptoms. J Pers Disord 2020; 34:88-106. [PMID: 30650041 DOI: 10.1521/pedi_2019_33_383] [Citation(s) in RCA: 14] [Impact Index Per Article: 3.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 01/17/2023]
Abstract
A large and consistent research literature demonstrates the superiority of dimensional models of mental disorder. Factor analytic research has mapped the latent dimensions underlying separate sets of mental disorders (e.g., emotional disorders), but a common framework-unencumbered by arbitrary historical boundaries between disorder groups-requires additional research. Using empirically derived measures of three key domains of psychopathological variation, the overarching goal of the current study was to explicate dimensions connecting internalizing, externalizing, and personality disorders. Participants included 1,144 racially diverse undergraduates. Exploratory structural equation modeling analyses revealed seven latent dimensions: core internalizing, core externalizing, antagonism, impulsivity, dutifulness, detachment, and suspiciousness. This meta-structure reflects a more comprehensive model of the architecture of mental disorders than accounts derived from less inclusive assessment batteries. Future empirical work is needed to evaluate the utility of this structural model in etiological research, assessment, and treatment arenas.
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Affiliation(s)
- Christopher C Conway
- Department of Psychological Sciences, College of William & Mary, Williamsburg, Virginia
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9
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Hankin BL. A choose your own adventure story: Conceptualizing depression in children and adolescents from traditional DSM and alternative latent dimensional approaches. Behav Res Ther 2019; 118:94-100. [PMID: 31026717 PMCID: PMC6547377 DOI: 10.1016/j.brat.2019.04.006] [Citation(s) in RCA: 9] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/02/2018] [Revised: 04/09/2019] [Accepted: 04/17/2019] [Indexed: 01/15/2023]
Abstract
For the past several decades, the phenomenon of depression largely has been defined, classified, and thus assessed and analyzed, according to criteria based on the Diagnostic and Statistical Manual (now DSM5). A substantial body of knowledge on epidemiology, course, risk factors, correlates, consequences, assessment, and intervention for youth depression is based on this classical nosological approach to conceptualizing depression. Yet, recent structural and classification approaches, such as latent dimensional bifactor models (e.g., P factor model; Caspi et al., 2014) and hierarchical organizations (e.g., HiTOP; Kotov, Waszczuk, Krueger, Forbes, & Watson, 2017), have been proposed and supported as alternative options to characterize features of depression. This paper considers conceptualizations of depression among youth with a particular focus on validity: how important clinical outcomes and risks (genetic, neural, temperament, early pubertal timing, stress, and cognitive) relate to depression when ascertained via traditional DSM-defined depression versus more recent latent dimensional model approaches. The construct validity of depression, in terms of associations within respective nomological networks, varies by depression conceptualization. Clinical scientists and applied practitioners need to clearly think through the nature of what depression is and how the latent construct is conceptualized and measured. Conclusions reached for research, teaching, and evidence-based clinical work are affected and may not be the same across different conceptual and nosological organizational schemes.
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10
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Conway CC, Forbes MK, Forbush KT, Fried EI, Hallquist MN, Kotov R, Mullins-Sweatt SN, Shackman AJ, Skodol AE, South SC, Sunderland M, Waszczuk MA, Zald DH, Afzali MH, Bornovalova MA, Carragher N, Docherty AR, Jonas KG, Krueger RF, Patalay P, Pincus AL, Tackett JL, Reininghaus U, Waldman ID, Wright AG, Zimmermann J, Bach B, Bagby RM, Chmielewski M, Cicero DC, Clark LA, Dalgleish T, DeYoung CG, Hopwood CJ, Ivanova MY, Latzman RD, Patrick CJ, Ruggero CJ, Samuel DB, Watson D, Eaton NR. A Hierarchical Taxonomy of Psychopathology Can Transform Mental Health Research. PERSPECTIVES ON PSYCHOLOGICAL SCIENCE 2019; 14:419-436. [PMID: 30844330 PMCID: PMC6497550 DOI: 10.1177/1745691618810696] [Citation(s) in RCA: 190] [Impact Index Per Article: 38.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/18/2022]
Abstract
For more than a century, research on psychopathology has focused on categorical diagnoses. Although this work has produced major discoveries, growing evidence points to the superiority of a dimensional approach to the science of mental illness. Here we outline one such dimensional system-the Hierarchical Taxonomy of Psychopathology (HiTOP)-that is based on empirical patterns of co-occurrence among psychological symptoms. We highlight key ways in which this framework can advance mental-health research, and we provide some heuristics for using HiTOP to test theories of psychopathology. We then review emerging evidence that supports the value of a hierarchical, dimensional model of mental illness across diverse research areas in psychological science. These new data suggest that the HiTOP system has the potential to accelerate and improve research on mental-health problems as well as efforts to more effectively assess, prevent, and treat mental illness.
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Affiliation(s)
- Christopher C. Conway
- Department of Psychological Sciences, College of William & Mary, Williamsburg, VA, USA
| | - Miriam K. Forbes
- Centre for Emotional Health, Department of Psychology, Macquarie University, Sydney, Australia
| | | | - Eiko I. Fried
- Department of Psychology, University of Amsterdam, Amsterdam, Netherlands
| | - Michael N. Hallquist
- Department of Psychology, The Pennsylvania State University, State College, PA, USA
| | - Roman Kotov
- Department of Psychiatry, State University of New York, Stony Brook, NY, USA
| | | | - Alexander J. Shackman
- Department of Psychology and Neuroscience and Cognitive Science Program, University of Maryland, College Park, MD, USA
| | - Andrew E. Skodol
- Department of Psychiatry, University of Arizona, Tucson, AZ, USA
| | - Susan C. South
- Purdue University, Department of Psychological Sciences, West Lafayette, IN, USA
| | - Matthew Sunderland
- NHMRC Centre for Research Excellence in Mental Health and Substance Use, National Drug and Alcohol Research Centre, University of New South Wales, Sydney, Australia
| | - Monika A. Waszczuk
- Department of Psychiatry, State University of New York, Stony Brook, NY, USA
| | - David H. Zald
- Department of Psychology, Vanderbilt University, Nashville, TN, USA
| | | | | | - Natacha Carragher
- Medical Education and Student Office, Faculty of Medicine, University of New South Wales Australia, Sydney, New South Wales, Australia
| | - Anna R. Docherty
- Department of Psychiatry, University of Utah, Salt Lake City, UT, USA
| | - Katherine G. Jonas
- Department of Psychiatry, State University of New York, Stony Brook, NY, USA
| | - Robert F. Krueger
- Department of Psychology, University of Minnesota, Minneapolis, MN, USA
| | - Praveetha Patalay
- Institute of Psychology, Health and Society, University of Liverpool, Liverpool, UK
| | - Aaron L. Pincus
- Department of Psychology, The Pennsylvania State University, State College, PA, USA
| | | | - Ulrich Reininghaus
- Department of Psychiatry and Psychology, School for Mental Health and Neuroscience, Maastricht University, The Netherlands
- Centre for Epidemiology and Public Health, Health Service and Population Research Department, Institute of Psychiatry, Psychology & Neuroscience, King’s College London, London, UK
| | | | - Aidan G.C. Wright
- Department of Psychology, University of Pittsburgh, Pittsburgh, PA, USA
| | | | - Bo Bach
- Psychiatric Research Unit, Slagelse Psychiatric Hospital, Slagelse, Denmark
| | - R. Michael Bagby
- Departments of Psychology and Psychiatry, University of Toronto, Toronto, Canada
| | | | - David C. Cicero
- Department of Psychology, University of Hawaii at Manoa, HI, USA
| | - Lee Anna Clark
- Department of Psychology, University of Notre Dame, Notre Dame, IN, USA
| | - Tim Dalgleish
- Medical Research Council Cognition and Brain Sciences Unit, Cambridge, UK
| | - Colin G. DeYoung
- Department of Psychology, University of Minnesota, Minneapolis, MN, USA
| | | | - Masha Y. Ivanova
- Department of Psychiatry, University of Vermont, Burlington, VT, USA
| | - Robert D. Latzman
- Department of Psychology, Georgia State University, Atlanta, GA, USA
| | | | - Camilo J. Ruggero
- Department of Psychology, University of North Texas, Denton, TX, USA
| | - Douglas B. Samuel
- Purdue University, Department of Psychological Sciences, West Lafayette, IN, USA
| | - David Watson
- Department of Psychology, University of Notre Dame, Notre Dame, IN, USA
| | - Nicholas R. Eaton
- Department of Psychology, Stony Brook University, Stony Brook, NY, USA
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Mental disorder comorbidity and treatment utilization. Compr Psychiatry 2017; 79:89-97. [PMID: 28215792 PMCID: PMC5550376 DOI: 10.1016/j.comppsych.2017.02.003] [Citation(s) in RCA: 10] [Impact Index Per Article: 1.4] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 11/04/2016] [Revised: 01/31/2017] [Accepted: 02/04/2017] [Indexed: 01/10/2023] Open
Abstract
OBJECTIVE Effective interventions have been developed for myriad common psychological and substance use disorders, though they remain highly underutilized. Previous research has shown that the likelihood of treatment utilization varies across disorder diagnosis. However, studies that focus on individual disorders have resulted in a large, piecemeal literature that neglects the high rates of multivariate comorbidity. The current study investigated the association between treatment utilization and transdiagnostic comorbidity factors. METHODS In a nationally representative sample of the United States adult population (N=34,653), we applied the internalizing-externalizing latent comorbidity model to examine its association with lifetime utilization of various treatments for mood, anxiety, and substance use disorders. RESULTS Both internalizing and externalizing transdiagnostic factors were positively associated with all forms of treatment utilization. Stronger within-domain domain (e.g., internalizing's association with mood or anxiety treatment) than between-domain (e.g., internalizing's association with substance use disorder treatment) associations were found. Significant antagonistic internalizing-by-externalizing interactions were also observed. CONCLUSIONS These results underscore the importance of applying a nuanced approach to modeling comorbidity when predicting treatment utilization. Clinical implications are discussed.
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Dornbach-Bender A, Ruggero CJ, Waszczuk MA, Gamez W, Watson D, Kotov R. Mapping emotional disorders at the finest level: Convergent validity and joint structure based on alternative measures. Compr Psychiatry 2017; 79:31-39. [PMID: 28754505 DOI: 10.1016/j.comppsych.2017.06.011] [Citation(s) in RCA: 10] [Impact Index Per Article: 1.4] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 01/29/2017] [Revised: 05/15/2017] [Accepted: 06/22/2017] [Indexed: 11/29/2022] Open
Abstract
BACKGROUND Traditional categorization of emotional disorders suffers from within-disorder heterogeneity and excessive comorbidity. Quantitative nosology instead proposes grouping homogenous components of these disorders within a higher order internalizing dimension. However, the precise number, composition, and hierarchical structure of these components remains unclear and varies based on assessment tools. METHODS The present study jointly examined two assessment systems with the broadest coverage of homogeneous emotional disorder components-the revised Interview for Mood and Anxiety Symptoms (IMAS-R) and the self-report-based expanded version of the Inventory of Depression and Anxiety Symptoms (IDAS-II)-to map their convergent and discriminant validity and joint structure in outpatient (N=426) and treated student (N=306) samples. RESULTS Results identified 33 non-redundant components of emotional disorders. Most demonstrated strong convergent and discriminant validity between these two instruments. However, the IMAS-R provided more detailed and differentiated characterization of the content subsumed within three IDAS-II scales, and seven of the 33 components were unique to one measure or the other. Joint analysis of scales from both measures supported a four factor (i.e., distress, fear, OCD, mania) mid-level structure of emotional disorders. CONCLUSIONS Using multiple measures, methods, and samples, the present study provided evidence for the validity of core lower order components of the internalizing dimension and suggested they cluster into as many as four distinct factors reflecting distress, fear, OCD, and mania.
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Affiliation(s)
- Allison Dornbach-Bender
- Department of Psychology, University of North Texas, 1155 Union Circle #311280, Denton, TX 76203, United States.
| | - Camilo J Ruggero
- Department of Psychology, University of North Texas, 1155 Union Circle #311280, Denton, TX 76203, United States.
| | - Monika A Waszczuk
- Department of Psychiatry, Stony Brook University, HSC, Level T-10, Room 060F, Stony Brook, NY 11794-8101, United States.
| | - Wakiza Gamez
- Department of Psychology, University of Iowa, Iowa City, IA, USA.
| | - David Watson
- Department of Psychology, 118 Haggar Hall, University of Notre Dame, Notre Dame, IN 46556, United States.
| | - Roman Kotov
- Department of Psychiatry, Stony Brook University, HSC, Level T-10, Room 060H, Stony Brook, NY 11794-8101, United States.
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13
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Beyond comorbidity: Toward a dimensional and hierarchical approach to understanding psychopathology across the life span. Dev Psychopathol 2017; 28:971-986. [PMID: 27739384 DOI: 10.1017/s0954579416000651] [Citation(s) in RCA: 77] [Impact Index Per Article: 11.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/13/2022]
Abstract
We propose a novel developmentally informed framework to push research beyond a focus on comorbidity between discrete diagnostic categories and to move toward research based on the well-validated dimensional and hierarchical structure of psychopathology. For example, a large body of research speaks to the validity and utility of the internalizing and externalizing spectra as organizing constructs for research on common forms of psychopathology. The internalizing and externalizing spectra act as powerful explanatory variables that channel the psychopathological effects of genetic and environmental risk factors, predict adaptive functioning, and account for the likelihood of disorder-level manifestations of psychopathology. As such, our proposed theoretical framework uses the internalizing and externalizing spectra as central constructs to guide future psychopathology research across the life span. The framework is particularly flexible, because any of the facets or factors from the dimensional and hierarchical structure of psychopathology can form the focus of research. We describe the utility and strengths of this framework for developmental psychopathology in particular and explore avenues for future research.
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Sunderland M, Batterham P, Carragher N, Calear A, Slade T. Developing and Validating a Computerized Adaptive Test to Measure Broad and Specific Factors of Internalizing in a Community Sample. Assessment 2017; 26:1030-1045. [PMID: 28467115 DOI: 10.1177/1073191117707817] [Citation(s) in RCA: 11] [Impact Index Per Article: 1.6] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/21/2022]
Abstract
Highly efficient assessments that better account for comorbidity between mood and anxiety disorders (internalizing) are required to identify individuals who are most at risk of psychopathology in the community. The current study examined the efficiency and validity associated with a multidimensional computerized adaptive test (CAT) to measure broad and specific levels of internalizing psychopathology. The sample comprised 3,175 respondents to an online survey. Items from five banks (generalized anxiety, depression, obsessive-compulsive disorder, panic disorder, social anxiety disorder) were jointly calibrated using a bifactor item response theory model. Simulations indicated that an adaptive algorithm could accurately (rs ≥ 0.90) estimate general internalizing and specific disorder scores using on average 44 items in comparison with the full 133-item bank (67% reduction in items). Scores on the CAT demonstrate convergent and divergent validity with previously validated short severity scales and could significantly differentiate cases of DSM-5 disorder. As such, the CAT validly measures both broad and specific constructs of internalizing disorders in a manner similar to the full item bank and a static brief form but with greater gains in efficiency and, therefore, a reduced degree of respondent burden.
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Affiliation(s)
| | - Philip Batterham
- 2 Australian National University, Canberra, Australian Capital Territory, Australia
| | | | - Alison Calear
- 2 Australian National University, Canberra, Australian Capital Territory, Australia
| | - Tim Slade
- 1 University of New South Wales (UNSW) Australia, Sydney, Australia
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15
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Federici S, Bracalenti M, Meloni F, Luciano JV. World Health Organization disability assessment schedule 2.0: An international systematic review. Disabil Rehabil 2016; 39:2347-2380. [PMID: 27820966 DOI: 10.1080/09638288.2016.1223177] [Citation(s) in RCA: 221] [Impact Index Per Article: 27.6] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/08/2023]
Abstract
PURPOSE This systematic review examines research and practical applications of the World Health Organization Disability Assessment Schedule (WHODAS 2.0) as a basis for establishing specific criteria for evaluating relevant international scientific literature. The aims were to establish the extent of international dissemination and use of WHODAS 2.0 and analyze psychometric research on its various translations and adaptations. In particular, we wanted to highlight which psychometric features have been investigated, focusing on the factor structure, reliability, and validity of this instrument. METHOD Following Preferred Reporting Items for Systematic reviews and Meta-Analyses (PRISMA) methodology, we conducted a search for publications focused on "whodas" using the ProQuest, PubMed, and Google Scholar electronic databases. RESULTS We identified 810 studies from 94 countries published between 1999 and 2015. WHODAS 2.0 has been translated into 47 languages and dialects and used in 27 areas of research (40% in psychiatry). CONCLUSIONS The growing number of studies indicates increasing interest in the WHODAS 2.0 for assessing individual functioning and disability in different settings and individual health conditions. The WHODAS 2.0 shows strong correlations with several other measures of activity limitations; probably due to the fact that it shares the same disability latent variable with them. Implications for Rehabilitation WHODAS 2.0 seems to be a valid, reliable self-report instrument for the assessment of disability. The increasing interest in use of the WHODAS 2.0 extends to rehabilitation and life sciences rather than being limited to psychiatry. WHODAS 2.0 is suitable for assessing health status and disability in a variety of settings and populations. A critical issue for rehabilitation is that a single "minimal clinically important .difference" score for the WHODAS 2.0 has not yet been established.
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Affiliation(s)
- Stefano Federici
- a Department of Philosophy, Social & Human Sciences and Education , University of Perugia , Perugia , Italy
| | - Marco Bracalenti
- a Department of Philosophy, Social & Human Sciences and Education , University of Perugia , Perugia , Italy
| | - Fabio Meloni
- a Department of Philosophy, Social & Human Sciences and Education , University of Perugia , Perugia , Italy
| | - Juan V Luciano
- b Teaching, Research & Innovation Unit, Parc Sanitari Sant Joan De Déu , St. Boi De Llobregat , Spain.,c Primary Care Prevention and Health Promotion Research Network (RedIAPP) , Madrid , Spain
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16
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Anestis JC, Finn JA, Gottfried ED, Hames JL, Bodell LP, Hagan CR, Arnau RC, Anestis MD, Arbisi PA, Joiner TE. Burdensomeness, Belongingness, and Capability: Assessing the Interpersonal–Psychological Theory of Suicide With MMPI-2-RF Scales. Assessment 2016; 25:415-431. [DOI: 10.1177/1073191116652227] [Citation(s) in RCA: 12] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/16/2022]
Abstract
Given the emerging body of literature demonstrating the validity of the interpersonal–psychological theory of suicide (IPTS), and the importance of increasing our understanding of the development of risk factors associated with suicidal behavior, it seems worthwhile both to expand IPTS research via Minnesota Multiphasic Personality Inventory–2–Restructured Form (MMPI-2-RF) correlates and to expand the availability of methods by which to assess the constructs of the IPTS. The present study attempted to do so in a large adult outpatient mental health sample by (a) inspecting associations between the IPTS constructs and the substantive scales of the MMPI-2-RF and (b) exploring the utility of MMPI-2-RF scale–based algorithms of the IPTS constructs. Correlates between the IPTS constructs and the MMPI-2-RF scales scores largely followed a pattern consistent with theory-based predictions, and we provide preliminary evidence that the IPTS constructs can be reasonably approximated using theoretically based MMPI-2-RF substantive scales. Implications of these findings are discussed.
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Affiliation(s)
| | - Jacob A. Finn
- Minneapolis VA Health Care System, Minneapolis, MN, USA
| | | | - Jennifer L. Hames
- Minneapolis VA Health Care System, Minneapolis, MN, USA
- Florida State University, Tallahassee, FL, USA
| | | | | | | | | | - Paul A. Arbisi
- Minneapolis VA Health Care System, Minneapolis, MN, USA
- University of Minnesota, Minneapolis, MN, USA
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17
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Sadeh N, Wolf EJ, Logue MW, Hayes JP, Stone A, Griffin LM, Schichman SA, Miller MW. EPIGENETIC VARIATION AT SKA2 PREDICTS SUICIDE PHENOTYPES AND INTERNALIZING PSYCHOPATHOLOGY. Depress Anxiety 2016; 33:308-15. [PMID: 27038412 PMCID: PMC4825872 DOI: 10.1002/da.22480] [Citation(s) in RCA: 40] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 01/15/2016] [Revised: 01/27/2016] [Accepted: 01/29/2016] [Indexed: 11/12/2022] Open
Abstract
BACKGROUND DNA methylation of the SKA2 gene has recently been implicated as a biomarker of suicide risk and posttraumatic stress disorder (PTSD). To examine the specificity and reliability of these findings, we examined associations between SKA2 DNA methylation, broad dimensions of psychiatric symptoms, and suicide phenotypes in adults with high levels of trauma exposure. METHODS A total of 466 White, non-Hispanic veterans and their intimate partners (65% male) underwent clinical assessment and had blood drawn for genotyping and methylation analysis. DNA methylation of the CpG locus cg13989295 and genotype at the methylation-associated single-nucleotide polymorphism (SNP) rs7208505 were examined in relation to current and lifetime PTSD, internalizing and externalizing psychopathology, and suicide phenotypes (ideation, plans, and attempts). RESULTS DNA methylation at the previously implicated SKA2 CpG locus (cg13989295) was associated with current and lifetime symptoms of internalizing (but not externalizing) disorders. SKA2 methylation levels also predicted higher rates of current suicidal thoughts and behaviors, even after including well-established psychiatric risk factors for suicide in the model. Associations between PTSD and SKA2 were not significant, and genetic variation at the methylation-associated SNP (rs7208505) was not related to any of the phenotypes examined. CONCLUSIONS SKA2 methylation may index a general propensity to experience stress-related psychopathology, including internalizing disorders and suicidal thoughts and behaviors. This study demonstrates that SKA2 methylation levels explain unique variance in suicide risk not captured by clinical symptom interviews, providing further evidence of its potential utility as a biomarker of suicide risk and stress-related psychopathology.
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Affiliation(s)
- Naomi Sadeh
- National Center for PTSD, Behavioral Science Division, VA Boston Healthcare System, Boston, Massachusetts.,Department of Psychiatry, Boston University School of Medicine, Boston, Massachusetts
| | - Erika J Wolf
- National Center for PTSD, Behavioral Science Division, VA Boston Healthcare System, Boston, Massachusetts.,Department of Psychiatry, Boston University School of Medicine, Boston, Massachusetts
| | - Mark W Logue
- Research Service, VA Boston Healthcare System, Boston, Massachusetts.,Biomedical Genetics, Boston University School of Medicine, Boston, Massachusetts.,Department of Biostatistics, Boston University School of Public Health, Boston, Massachusetts
| | - Jasmeet P Hayes
- National Center for PTSD, Behavioral Science Division, VA Boston Healthcare System, Boston, Massachusetts.,Department of Psychiatry, Boston University School of Medicine, Boston, Massachusetts
| | - Annjanette Stone
- Pharmacogenomics Analysis Laboratory, Research Service, Central Arkansas Veterans Healthcare System, Arkansas
| | - L Michelle Griffin
- Pharmacogenomics Analysis Laboratory, Research Service, Central Arkansas Veterans Healthcare System, Arkansas
| | - Steven A Schichman
- Pharmacogenomics Analysis Laboratory, Research Service, Central Arkansas Veterans Healthcare System, Arkansas
| | - Mark W Miller
- National Center for PTSD, Behavioral Science Division, VA Boston Healthcare System, Boston, Massachusetts.,Department of Psychiatry, Boston University School of Medicine, Boston, Massachusetts
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