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Tyrer P. Threading a pathway through the forest of mood and personality disorders. BJPSYCH ADVANCES 2020. [DOI: 10.1192/bja.2019.63] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/23/2022]
Abstract
SUMMARYThe classification of mood and personality disorders has become unnecessarily complicated. It has become bogged down by well-meaning but unhelpful subcategories that puzzle the will of clinicians to make useful judgements. The answer is to think of bipolar, depressive and personality disorders as each constituting a spectrum of severity and not to be too preoccupied with individual labels. It would also be useful to avoid the diagnostic chimera of borderline personality disorder, a condition that defies proper classification.
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Widiger TA, McCabe GA. The Alternative Model of Personality Disorders (AMPD) from the Perspective of the Five-Factor Model. Psychopathology 2020; 53:149-156. [PMID: 32526758 DOI: 10.1159/000507378] [Citation(s) in RCA: 19] [Impact Index Per Article: 4.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 12/02/2019] [Accepted: 03/19/2020] [Indexed: 11/19/2022]
Abstract
The fifth edition of the American Psychiatric Association's (APA) Diagnostic and Statistical Manual of Mental Disorders(DSM-5; American Psychiatric Association. Diagnostic and Statistical Manual of Mental Disorders. 5th ed. Washington: American Psychiatric Association; 2013) includes an Alternative Model of Personality Disorders (AMPD). The AMPD includes two components: the Criterion A level of personality functioning (i.e., impairments or deficits in the sense of self and interpersonal relatedness) and the Criterion B five-domain maladaptive trait model. The purpose of the current paper is to discuss the AMPD from the perspective of the Five-Factor Model (FFM) of general personality structure. The conclusion of this review is that both the Criterion A self-other deficits and the Criterion B traits can be understood as maladaptive variants of the FFM.
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Affiliation(s)
- Thomas A Widiger
- Department of Psychology, University of Kentucky, Lexington, Kentucky, USA,
| | - Gillian A McCabe
- Department of Psychology, University of Kentucky, Lexington, Kentucky, USA
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Stulp HP, Koelen J, Glas GG, Eurelings-Bontekoe L. Validation of the apperception test God representations, an implicit measure to assess God representations. Part 3: associations between implicit and explicit measures of God representations and self-reported level of personality functioning. JOURNAL OF SPIRITUALITY IN MENTAL HEALTH 2019. [DOI: 10.1080/19349637.2019.1700475] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.4] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/25/2022]
Affiliation(s)
| | - Jurrijn Koelen
- GGZ Centraal De Meregaard, The Netherlands
- University of Amsterdam, Amsterdam, The Netherlands
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Stulp HP, Koelen J, Schep-Akkerman A, Glas GG, Eurelings-Bontekoe L. God representations and aspects of psychological functioning: A meta-analysis. COGENT PSYCHOLOGY 2019. [DOI: 10.1080/23311908.2019.1647926] [Citation(s) in RCA: 10] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/26/2022] Open
Affiliation(s)
- Henk P. Stulp
- Lectorate Health Care and Spirituality, Viaa University of Applied Sciences, Zwolle, The Netherlands
| | - Jurrijn Koelen
- Lectorate Health Care and Spirituality, University of Amsterdam, Amsterdam, The Netherlands
| | - Annemiek Schep-Akkerman
- Lectorate Health Care and Spirituality, Viaa University of Applied Sciences, Zwolle, The Netherlands
- Lectorate Health Care and Spirituality, Dutch College of General Practitioners, Utrecht, Amsterdam, The Netherlands
| | - Gerrit G. Glas
- Lectorate Health Care and Spirituality, Dimence Groep and VUmc Amsterdam, Amsterdam
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Affiliation(s)
- Joshua D. Miller
- Department of Psychology, University of Georgia, Athens, Georgia 30602–3013
| | - Donald R. Lynam
- Department of Psychological Sciences, Purdue University, West Lafayette, Indiana 47907
| | - Courtland S. Hyatt
- Department of Psychology, University of Georgia, Athens, Georgia 30602–3013
| | - W. Keith Campbell
- Department of Psychology, University of Georgia, Athens, Georgia 30602–3013
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Kim YR, Tyrer P, Lee HS, Kim SG, Hwang ST, Lee GY, Mulder R. Preliminary field trial of a putative research algorithm for diagnosing ICD-11 personality disorders in psychiatric patients: 2. Proposed trait domains. Personal Ment Health 2015; 9:298-307. [PMID: 26472077 DOI: 10.1002/pmh.1305] [Citation(s) in RCA: 20] [Impact Index Per Article: 2.2] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 04/01/2015] [Revised: 06/17/2015] [Accepted: 07/19/2015] [Indexed: 11/06/2022]
Abstract
This field trial examines the discriminant validity of five trait domains of the originally proposed research algorithm for diagnosing International Classification of Diseases (ICD)-11 personality disorders. This trial was carried out in South Korea where a total of 124 patients with personality disorder participated in the study. Participants were assessed using originally proposed monothetic trait domains of asocial-schizoid, antisocial-dissocial, anxious-dependent, emotionally unstable and anankastic-obsessional groups of the research algorithm in ICD-11. Their assessments were compared to those from the Personality Assessment Schedule interview, and the five-factor model (FFM). A total of 48.4% of patients were found to have pathology in two or more domains. In the discriminant analysis, 64.2% of the grouped cases of the originally proposed ICD-11 domains were correctly classified by the five domain categories using the Personality Assessment Schedule, with the highest accuracy in the anankastic-obsessional domain and the lowest accuracy in the emotionally unstable domain. In comparison, the asocial-schizoid, anxious-dependent and the emotionally unstable domains were moderately correlated with the FFM, whereas the anankastic-obsessional or antisocial-dissocial domains were not significantly correlated with the FFM. In this field trial, we demonstrated the limited discriminant and the convergent validities of the originally proposed trait domains of the research algorithm for diagnosing ICD-11 personality disorder. The results suggest that the anankastic, asocial and dissocial domains show good discrimination, whereas the anxious-dependent and emotionally unstable ones overlap too much and have been subsequently revised.
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Affiliation(s)
- Youl-Ri Kim
- Department of Psychiatry, Seoul Paik Hospital, Inje University, Seoul, South Korea.,Institute of Eating Disorders and Mental Health, Inje University, Seoul, South Korea
| | - Peter Tyrer
- Centre for Mental Health, Department of Medicine, Imperial College, London, UK
| | - Hong-Seock Lee
- Department of Psychiatry, Kangnam Sacred Hospital, Hallym University, Seoul, South Korea
| | - Sung-Gon Kim
- Department of Psychiatry, Pusan National University Yangsan Hospital, Pusan National University School of Medicine, Yangsan, South Korea
| | - Soon-Taek Hwang
- Department of Psychology, Chungbuk National University, Cheongju, South Korea
| | - Gi Young Lee
- Department of Psychological & Brain Sciences, Johns Hopkins University, Baltimore, USA
| | - Roger Mulder
- Department of Psychological Medicine, University of Otago, Dunedin, New Zealand
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Zimmermann J, Brakemeier EL, Benecke C. Alternatives DSM-5-Modell zur Klassifikation von Persönlichkeitsstörungen. PSYCHOTHERAPEUT 2015. [DOI: 10.1007/s00278-015-0033-8] [Citation(s) in RCA: 9] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 10/23/2022]
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DSM-5 reviewed from different angles: goal attainment, rationality, use of evidence, consequences—part 2: bipolar disorders, schizophrenia spectrum disorders, anxiety disorders, obsessive-compulsive disorders, trauma- and stressor-related disorders, personality disorders, substance-related and addictive disorders, neurocognitive disorders. Eur Arch Psychiatry Clin Neurosci 2015; 265:87-106. [PMID: 25155875 DOI: 10.1007/s00406-014-0521-9] [Citation(s) in RCA: 22] [Impact Index Per Article: 2.4] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 05/08/2014] [Accepted: 08/01/2014] [Indexed: 12/16/2022]
Abstract
Part 1 of this paper discussed several more general aspects of Diagnostic and Statistical Manual of Mental Disorders (DSM-5) and offered a detailed, paradigmatic analysis of changes made to the chapter on depressive disorders. This second part focusses on several other disorders, including bipolar and schizophrenia spectrum disorders. The respective changes and their possible consequences are discussed under consideration of traditional psychiatric classification, particularly from the perspective of European traditions and on the basis of a PubMed search and review papers. The general conclusion is that even seemingly small changes such as the introduction of the mixed feature specifier can have far-reaching consequences. Contrary to the original plans, DSM-5 has not radically changed to become a primarily dimensional diagnostic system but has preserved the categorical system for most disorders. The ambivalence of the respective decision-making becomes apparent from the last minute decision to change the classification of personality disorders from dimensional back to categorical. The advantages and disadvantages of the different approaches are discussed in this context. In DSM-5, only the chapter on addictive disorders has a somewhat dimensional structure. Also in contrast to the original intentions, DSM-5 has not used a more neurobiological approach to disorders by including biological markers to increase the objectivity of psychiatric diagnoses. Even in the most advanced field in terms of biomarkers, the neurocognitive disorders, the primarily symptom-based, descriptive approach has been preserved and the well-known amyloid-related and other biomarkers are not included. This is because, even after so many years of biomarker research, the results are still not considered to be robust enough to use in clinical practice.
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Furnham A, Bates S, Ladha R, Lee ZY, Lousley C, Sigl-Gloecker J. The recognition of the personality disorders among young people. Int J Soc Psychiatry 2014; 60:681-6. [PMID: 24327186 DOI: 10.1177/0020764013511958] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.1] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 11/17/2022]
Abstract
BACKGROUND Previous research suggests that mental health literacy regarding the personality disorders is low, with few disorders being recognised. AIMS The current study aimed to examine the effect of a background in psychology as a predictor of knowledge of the personality disorders. METHODS An opportunistic sample of 165 participants (mean age = 30.12 years, standard deviation (SD) = 15.27 years) took part in the study. Participants were instructed to read 10 personality disorder vignettes and other 'filler' items and rate each person in terms of how happy, successful at work and good at personal relationships they are, as well as whether they have a psychological problem. RESULTS Results showed, as predicted, that those with a background in psychology were more accurate at labelling disorders. In addition, laypeople's mental health literacy was good for identifying the presence of personality disorders, but was considerably poorer when naming them. CONCLUSION Recognising that people may have a disorder and having a 'correct' or recognised label are not the same thing.
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Affiliation(s)
- Adrian Furnham
- Research Department of Clinical, Educational and Health Psychology, University College London, London, UK
| | - Sophie Bates
- Research Department of Clinical, Educational and Health Psychology, University College London, London, UK
| | - Ruhina Ladha
- Research Department of Clinical, Educational and Health Psychology, University College London, London, UK
| | - Zhen Yi Lee
- Research Department of Clinical, Educational and Health Psychology, University College London, London, UK
| | - Chiara Lousley
- Research Department of Clinical, Educational and Health Psychology, University College London, London, UK
| | - Joanna Sigl-Gloecker
- Research Department of Clinical, Educational and Health Psychology, University College London, London, UK
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Tyrer P, Crawford M, Sanatinia R, Tyrer H, Cooper S, Muller-Pollard C, Christodoulou P, Zauter-Tutt M, Miloseska-Reid K, Loebenberg G, Guo B, Yang M, Wang D, Weich S. Preliminary studies of the ICD-11 classification of personality disorder in practice. Personal Ment Health 2014; 8:254-63. [PMID: 25200623 DOI: 10.1002/pmh.1275] [Citation(s) in RCA: 42] [Impact Index Per Article: 4.2] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 05/12/2014] [Revised: 08/17/2014] [Accepted: 08/21/2014] [Indexed: 11/07/2022]
Abstract
OBJECTIVE This study aims to compare ICD-10 and putative ICD-11 classifications of personality disorder in different clinical populations. DESIGN Prospective recording of ICD-10 and ICD-11 personality disorder classifications was carried out in (1) an anxious medical population, (2) an acute psychiatric in-patient population and (3) a retrospective recording of a mixed anxiety depression cohort in which all baseline data were scored from baseline information using the ICD-11 classification and compared with the original ICD-10 assessments. METHOD Comparison of ICD-10 and ICD-11 prevalence of personality disorder in each population was carried out. RESULTS Data from 722 patients were recorded. Using the ICD-10 criteria, the prevalence of generic personality disorder was 33.8% compared with 40.4% using the ICD-11 ones (χ2 = 6.7; P < 0.01), with 103 (14.3%) discordant assessments. Using the severity definitions in ICD-11, 34.3% of patients had personality difficulty. Severity level varied greatly by population; severe personality disorder was five times more common in the inpatient group. The four domain traits originally denoted as qualifying severity in ICD-11, negative affective, dissocial, anankastic and detached, were linked to anxious, borderline, dissocial, anankastic and schizoid personality disorders in ICD-10. Many patients had pathology in two or more domains. CONCLUSIONS The ICD-11 classification of personality disorder yields somewhat higher levels of personality dysfunction than ICD-10, possibly because the age range for the onset of diagnosis is now flexible. The range of severity levels make the classification more useful than ICD-10 in clinical practice as it identifies the greater pathology necessary for intervention.
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Affiliation(s)
- Peter Tyrer
- Centre for Mental Health, Imperial College, London, W6 8RP, UK
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Kirmayer LJ, Crafa D. What kind of science for psychiatry? Front Hum Neurosci 2014; 8:435. [PMID: 25071499 PMCID: PMC4092362 DOI: 10.3389/fnhum.2014.00435] [Citation(s) in RCA: 67] [Impact Index Per Article: 6.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/11/2014] [Accepted: 05/29/2014] [Indexed: 12/20/2022] Open
Abstract
Psychiatry has invested its hopes in neuroscience as a path to understanding mental disorders and developing more effective treatments and ultimately cures. Recently, the U.S. NIMH has elaborated this vision through a new framework for mental health research, the Research Domain Criteria (RDoC). This framework aims to orient mental health research toward the discovery of underlying neurobiological and biobehavioral mechanisms of mental disorders that will eventually lead to definitive treatments. In this article we consider the rationale of the RDoC and what it reveals about implicit models of mental disorders. As an overall framework for understanding mental disorders, RDoC is impoverished and conceptually flawed. These limitations are not accidental but stem from disciplinary commitments and interests that are at odds with the larger concerns of psychiatry. A multilevel, ecosocial approach to biobehavioral systems is needed both to guide relevant neuroscience research and insure the inclusion of social processes that may be fundamental contributors to psychopathology and recovery.
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Affiliation(s)
- Laurence J. Kirmayer
- Division of Social and Transcultural Psychiatry, McGill University & Institute of Community and Family Psychiatry, Jewish General HospitalMontreal, QC, Canada
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