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Cognitive diagnosis models (CDMs) have been used as psychometric tools in educational assessments to estimate students' proficiency profiles. However, most CDMs assume that all students adopt the same strategy when approaching problems in an assessment, which may not be the case in practice. This study develops a generalized multiple‐strategy CDM for dichotomous response data. The proposed model provides a unified framework to accommodate various condensation rules (e.g., conjunctive, disjunctive, and additive) and different strategy selection approaches (i.e., probability‐matching, over‐matching, and maximizing). Model parameters are estimated using the marginal maximum likelihood estimation via expectation‐maximization algorithm. Simulation studies showed that the parameters of the proposed model can be adequately recovered and that the proposed model was relatively robust to some types of model misspecifications. A set of real data was analysed as well to illustrate the use of the proposed model in practice. [ABSTRACT FROM AUTHOR]

Highlights • Body image concerns are a prominent feature in AN and BDD. • Other similarities include perfectionism and deficits in body size estimation. • Differences include predominant physical concerns with their appearance. • AN and BDD may be more appropriately classified as 'body image disorders'. • More studies with larger sample sizes are needed. Abstract Anorexia nervosa (AN) and body dysmorphic disorder (BDD) are serious psychiatric conditions, both of which are associated with a disturbance of body image. The aim of this paper was to review those studies that have directly compared groups of individuals with AN and BDD, to determine similarities and differences in presentation between the two conditions. The literature was searched to September 2018, and studies were included if they were English language, empirical research papers published in peer-reviewed journals, specifically comparing AN and BDD patients. Fifteen relevant studies were identified. The results suggested that individuals with AN and BDD share a number of similarities, including their degree of body dissatisfaction. Differences between the conditions included primary concerns with body shape and weight in AN, and much more diffuse concerns (but predominantly the face) in BDD. The small number of studies, along with the limited replication of results emphasises the need for greater research in this area. However, the studies undertaken to date highlight the high degree of overlap between AN and BDD and suggests that the conditions may represent similar body image disorders. This has implications for the nosological status of AN and BDD. [ABSTRACT FROM AUTHOR]

Copyright of Journal of Craniomandibular Function is the property of Quintessence Publishing Company Inc. and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Abstract Introduction We established a method for diagnostic harmonization across multiple studies of preclinical Alzheimer's disease and validated the method by examining its relationship with clinical status and cognition. Methods Cognitive and clinical data were used from five studies (N = 1746). Consensus diagnoses established in each study used criteria to identify progressors from normal cognition to mild cognitive impairment. Correspondence was evaluated between these consensus diagnoses and three algorithmic classifications based on (1) objective cognitive impairment in 2+ tests only; (2) a Clinical Dementia Rating (CDR) of ≥0.5 only; and (3) both. Associations between baseline cognitive performance and cognitive change were each tested in relation to progression to algorithm‐based classifications. Results In each study, an algorithmic classification based on both cognitive testing cutoff scores and a CDR ≥0.5 provided optimal balance of sensitivity and specificity (areas under the curve: 0.85–0.95). Over an average 6.6 years of follow‐up (up to 28 years), N = 186 initially cognitively normal participants aged on average 64 years at baseline progressed (incidence rate: 15.3 people/1000 person‐years). Baseline cognitive scores and cognitive change were associated with future diagnostic status using this algorithmic classification. Discussion Both cognitive tests and CDR ratings can be combined across multiple studies to obtain a reliable algorithmic classification with high specificity and sensitivity. This approach may be applicable to large cohort studies and to clinical trials focused on preclinical Alzheimer's disease because it provides an alternative to implementation of a time‐consuming adjudication panel.

The Diagnostic and Statistical Manual of Mental Disorders ( DSM ) has provided a standard language that physicians, scientists, and public health specialists use to communicate about mental disorders. This guideline was revised for the first time in 1986 and its last edition (fifth edition) was published in 2013. The most important modifications in the DSM-5 include the change in font, reexamination of the definition of psychological disorder, the order of categories, considerations for lifetime growth and developmental issues, categorization of disorders with greater emphasis on neuroscience and less emphasis on symptom emergence, differentiation between main diagnosis and the reason for referral, determination of temporary or absolute diagnosis, new categories of other specified and unspecified disorders, tendency toward dimensional evaluation, decrease in diagnosis-centered system, emphasis on cultural issues, emphasis on gender issues, and reexamination of diagnosis criteria. The aim of the present article was a critical, applied, and integrated investigation into these modifications. The new version received the most criticisms regarding extreme medicalization of normal issues. The main controversies regarding this version are related to the definition of some disorders, diagnostic inflation, and inappropriate impact of drug companies. In the final section of the article, the future perspectives of psychological disorder categories are explored. It seems that the Research Domain Criteria (RDoC) Project will play an important role in psychological disorder categorization in the future.

Objective: The Hierarchical Taxonomy of Psychopathology (HiTOP) posits that psychopathology is hierarchically structured. For personality disorder (PD) traits, there are five spectra: internalizing, thought disorder, disinhibited externalizing, antagonistic externalizing, and detachment. Empirical findings suggest a sixth group, compulsivity. In this research, we tried to recover the five HiTOP spectra, plus compulsivity, specifically for PD traits. Methods: The sample was composed of 4,868 Brazilians (54.9% women, age ranging from 18 to 70; mean = 25.7; SD = 9.64). All participants answered the Dimensional Clinical Personality Inventory 2 (IDCP-2), a self-report inventory for adults, developed in Brazil, for assessment of pathological personality traits. Results: Parallel analysis yielded up to nine factors. On exploratory structural equation modeling (E-SEM), the balance between interpretability and fit index suggested the six-factor solution as the best solution. The fit indexes for the confirmatory factor analysis were slightly less adjusted in comparison to the empirical model. Conclusion: The hypothesis was confirmed, as we did find the groups proposed at the spectrum level of the HiTOP. We also found a compulsivity factor, encompassing the main traits from the conscientiousness dimension of IDCP-2, which is related to obsessive-compulsive PD. Finding the six groupings of traits in the HiTOP model contributes to the validity of this model, and confirms the existence of proposed spectra.

Frontal-subcortical circuit dysfunction is commonly associated with apathy, a neuropsychiatric sequelae of human immunodeficiency virus type-1 (HIV-1). Behavioral and neurochemical indices of apathy in the nucleus accumbens (NAc), a key brain region involved in frontal-subcortical circuitry, are influenced by the factor of biological sex. Despite evidence of sex differences in HIV-1, the effect of biological sex on medium spiny neurons (MSNs), which are central integrators of frontal-subcortical input, has not been systematically evaluated. In the present study, a DiOlistic labeling technique was used to investigate the role of long-term HIV-1 viral protein exposure, the factor of biological sex, and their possible interaction, on synaptic dysfunction in MSNs of the NAc in the HIV-1 transgenic (Tg) rat. HIV-1 Tg rats, independent of biological sex, displayed profound alterations in synaptic connectivity, evidenced by a prominent shift in the distribution of dendritic spines. Female HIV-1 Tg rats, but not male HIV-1 Tg rats, exhibited alterations in dendritic branching and neuronal arbor complexity relative to control animals, supporting an alteration in glutamate neurotransmission. Morphologically, HIV-1 Tg male, but not female HIV-1 Tg rats, displayed a population shift towards decreased dendritic spine volume, suggesting decreased synaptic area, relative to control animals. Synaptic dysfunction accurately identified presence of the HIV-1 transgene, dependent upon biological sex, with at least 80% accuracy (i.e., Male: 80%; Female: 90%). Collectively, these results support a primary alteration in circuit connectivity, the mechanism of which is dependent upon biological sex. Understanding the effect of biological sex on the underlying neural mechanism for HIV-1 associated apathy is vital for the development of sex-based therapeutics and cure strategies.

Internet gaming disorder (IGD) is often diagnosed on the basis of nine underlying criteria from the latest version of the Diagnostic and Statistical Manual of Mental Disorders (DSM-5). Here, we examined whether such symptom-based categorization could be translated into computation-based classification. Structural MRI (sMRI) and diffusion-weighted MRI (dMRI) data were acquired in 38 gamers diagnosed with IGD, 68 normal gamers diagnosed as not having IGD, and 37 healthy non-gamers. We generated 108 features of gray matter (GM) and white matter (WM) structure from the MRI data. When regularized logistic regression was applied to the 108 neuroanatomical features to select important ones for the distinction between the groups, the disordered and normal gamers were represented in terms of 43 and 21 features, respectively, in relation to the healthy non-gamers, whereas the disordered gamers were represented in terms of 11 features in relation to the normal gamers. In support vector machines (SVM) using the sparse neuroanatomical features as predictors, the disordered and normal gamers were discriminated successfully, with accuracy exceeding 98%, from the healthy non-gamers, but the classification between the disordered and normal gamers was relatively challenging. These findings suggest that pathological and non-pathological gamers as categorized with the criteria from the DSM-5 could be represented by sparse neuroanatomical features, especially in the context of discriminating those from non-gaming healthy individuals.

This article examines the history of the conceptualization of dissociative, conversion, and somatoform syndromes in relation to one another, chronicles efforts to classify these and other phenomenologically-related psychopathology in the American diagnostic system for mental disorders, and traces the subsequent divergence in opinions of dissenting sectors on classification of these disorders. This article then considers the extensive phenomenological overlap across these disorders in empirical research, and from this foundation presents a new model for the conceptualization of these disorders. The classification of disorders formerly known as hysteria and phenomenologically-related syndromes has long been contentious and unsettled. Examination of the long history of the conceptual difficulties, which remain inherent in existing classification schemes for these disorders, can help to address the continuing controversy. This review clarifies the need for a major conceptual revision of the current classification of these disorders. A new phenomenologically-based classification scheme for these disorders is proposed that is more compatible with the agnostic and atheoretical approach to diagnosis of mental disorders used by the current classification system.

Frontal-subcortical circuit dysfunction is commonly associated with apathy, a neuropsychiatric sequelae of human immunodeficiency virus type-1 (HIV-1). Behavioral and neurochemical indices of apathy in the nucleus accumbens (NAc), a key brain region involved in frontal-subcortical circuitry, are influenced by the factor of biological sex. Despite evidence of sex differences in HIV-1, the effect of biological sex on medium spiny neurons (MSNs), which are central integrators of frontal-subcortical input, has not been systematically evaluated. In the present study, a DiOlistic labeling technique was used to investigate the role of long-term HIV-1 viral protein exposure, the factor of biological sex, and their possible interaction, on synaptic dysfunction in MSNs of the NAc in the HIV-1 transgenic (Tg) rat. HIV-1 Tg rats, independent of biological sex, displayed profound alterations in synaptic connectivity, evidenced by a prominent shift in the distribution of dendritic spines. Female HIV-1 Tg rats, but not male HIV-1 Tg rats, exhibited alterations in dendritic branching and neuronal arbor complexity relative to control animals, supporting an alteration in glutamate neurotransmission. Morphologically, HIV-1 Tg male, but not female HIV-1 Tg rats, displayed a population shift towards decreased dendritic spine volume, suggesting decreased synaptic area, relative to control animals. Synaptic dysfunction accurately identified presence of the HIV-1 transgene, dependent upon biological sex, with at least 80% accuracy (i.e., Male: 80%; Female: 90%). Collectively, these results support a primary alteration in circuit connectivity, the mechanism of which is dependent upon biological sex. Understanding the effect of biological sex on the underlying neural mechanism for HIV-1 associated apathy is vital for the development of sex-based therapeutics and cure strategies. [ABSTRACT FROM AUTHOR]

Copyright of International Journal of Computerized Dentistry is the property of Quintessence Publishing Company Inc. and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

BackgroundThe approach to apply multivariate pattern analyses based on neuro imaging data for outcome prediction holds out the prospect to improve therapeutic decisions in mental disorders. Patients suffering from panic disorder with agoraphobia (PD/AG) often exhibit an increased perception of bodily sensations. The purpose of this investigation was to assess whether multivariate classification applied to a functional magnetic resonance imaging (fMRI) interoception paradigm can predict individual responses to cognitive behavioral therapy (CBT) in PD/AG.MethodsThis analysis is based on pretreatment fMRI data during an interoceptive challenge from a multicenter trial of the German PANIC-NET. Patients with DSM-IV PD/AG were dichotomized as responders (n = 30) or non-responders (n = 29) based on the primary outcome (Hamilton Anxiety Scale Reduction ≥50%) after 6 weeks of CBT (2 h/week). fMRI parametric maps were used as features for response classification with linear support vector machines (SVM) with or without automated feature selection. Predictive accuracies were assessed using cross validation and permutation testing. The influence of methodological parameters and the predictive ability for specific interoception-related symptom reduction were further evaluated.ResultsSVM did not reach sufficient overall predictive accuracies (38.0–54.2%) for anxiety reduction in the primary outcome. In the exploratory analyses, better accuracies (66.7%) were achieved for predicting interoception-specific symptom relief as an alternative outcome domain. Subtle information regarding this alternative response criterion but not the primary outcome was revealed by post hoc univariate comparisons.ConclusionIn contrast to reports on other neurofunctional probes, SVM based on an interoception paradigm was not able to reliably predict individual response to CBT. Results speak against the clinical applicability of this technique.

Hepatitis E virus (HEV) is one of the major pathogens that cause acute viral hepatitis. The human (genotypes 1 and 2) and zoonotic (genotypes 3 and 4) groups of HEV present different epidemiology and clinical features. In this study, we developed a classification method for rapidly classifying HEV into human or zoonotic groups that combines a general antigen test with a zoonotic group-specific antigen test. Evaluation of serial samples from HEV-infected rhesus monkeys indicated that HEV antigen-positive samples can be classified using the antigen-based classification method. The antigen-based classification method was evaluated further on 55 genotyped samples from acute hepatitis E patients, including 9 human and 46 zoonotic groups. The novel method was completely consistent with the sequencing results: 9/9 for the human groups (100%, 95% confidence interval [CI] 66.4-100%) and 46/46 for the zoonotic groups (100%, 95% CI 92.3-100%). This method was also successfully used for the clustering of some samples that could not be clustered by sequencing. Compared with the sequencing-based method, this method is less time-consuming, less expensive, and less technically complex and is therefore ideal for large numbers of samples. In conclusion, this study provides a convenient and sensitive method for classifying different groups of HEV, and it has potentially important public health applications, especially in underdeveloped areas that cannot afford the high cost of nucleic acid testing. [ABSTRACT FROM AUTHOR]

Objectives: Combinations of resting-state fMRI and machine-learning techniques are increasingly employed to develop diagnostic models for mental disorders. However, little is known about the neurobiological heterogeneity of depression and diagnostic machine learning has mainly been tested in homogeneous samples. Our main objective was to explore the inherent structure of a diverse unipolar depression sample. The secondary objective was to assess, if such information can improve diagnostic classification.Materials and Methods: We analyzed data from 360 patients with unipolar depression and 360 non-depressed population controls, who were subdivided into two independent subsets. Cluster analyses (unsupervised learning) of functional connectivity were used to generate hypotheses about potential patient subgroups from the first subset. The relationship of clusters with demographical and clinical measures was assessed. Subsequently, diagnostic classifiers (supervised learning), which incorporated information about these putative depression subgroups, were trained.Results: Exploratory cluster analyses revealed two weakly separable subgroups of depressed patients. These subgroups differed in the average duration of depression and in the proportion of patients with concurrently severe depression and anxiety symptoms. The diagnostic classification models performed at chance level.Limitations: It remains unresolved, if subgroups represent distinct biological subtypes, variability of continuous clinical variables or in part an overfitting of sparsely structured data.Conclusions: Functional connectivity in unipolar depression is associated with general disease effects. Cluster analyses provide hypotheses about potential depression subtypes. Diagnostic models did not benefit from this additional information regarding heterogeneity. [ABSTRACT FROM AUTHOR]

Focusing on the case of medically unexplained symptoms ( MUS), this article explores diagnostic classification in the absence of biomedical evidence or other strong medical warrants for diagnosis. The data are from three focus group interviews with Norwegian general practitioners ( GPs) conducted in 2015, that centred on the issue of what diagnoses to use (or not) for MUS. The qualitative analysis reconstructs the logic underlying GPs' diagnostic accounts, which centred on the meaning of diagnostic categories and on anticipating how 'generalised others' would respond to those meanings (called 'diagnosing by anticipation'). The analysis suggests that GPs confer diagnoses by balancing unwarranted medical accuracy and anticipated harmful diagnostic consequences; the goal of diagnosis was finding categories in the International Classification of Primary Care that would yield acceptable results, without making a liar of the GP in the process. Drawing on the distinction between diagnosis as colligation and classification, the findings and their relevance for medical sociology are discussed. Counter to frequent descriptions as 'illness that cannot be diagnosed', the analysis shows how GPs can diagnose MUS in the bureaucratic sense of diagnosis as classification - a sense that has been missing from sociological view. [ABSTRACT FROM AUTHOR]

Diagnostic criteria for complex medical conditions caused by a multitude of both genetic and environmental factors should be descriptive and avoid any attribution of causality. Furthermore, the wording used to describe a disorder should be evidence-based and avoid stigmatization of the affected individuals. Both terminology and categorizations should be readily comprehensible for healthcare professionals and guide clinical decision making. Uncertainties with respect to diagnostic issues and their implications may be addressed to direct future clinical research. In this context, the European Association of the Study of Obesity (EASO) considers it an important endeavor to review the current ICD-11 Beta Draft for the definition of overweight and obesity and to propose a substantial revision. We aim to provide an overview of the key issues that we deem relevant for the discussion of the diagnostic criteria. We first discuss the current ICD-10 criteria and those proposed in the ICD 11 Beta Draft. We conclude with our own proposal for diagnostic criteria, which we believe will improve the assessment of patients with obesity in a clinically meaningful way. [ABSTRACT FROM AUTHOR]

Background: The approach to apply multivariate pattern analyses based on neuro imaging data for outcome prediction holds out the prospect to improve therapeutic decisions in mental disorders. Patients suffering from panic disorder with agoraphobia (PD/AG) often exhibit an increased perception of bodily sensations. The purpose of this investigation was to assess whether multivariate classification applied to a functional magnetic resonance imaging (fMRI) interoception paradigm can predict individual responses to cognitive behavioral therapy (CBT) in PD/AG. Methods: This analysis is based on pretreatment fMRI data during an interoceptive challenge from a multicenter trial of the German PANIC-NET. Patients with DSM-IV PD/AG were dichotomized as responders (n = 30) or non-responders (n = 29) based on the primary outcome (Hamilton Anxiety Scale Reduction ≥50%) after 6 weeks of CBT (2 h/week). fMRI parametric maps were used as features for response classification with linear support vector machines (SVM) with or without automated feature selection. Predictive accuracies were assessed using cross validation and permutation testing. The influence of methodological parameters and the predictive ability for specific interoception-related symptom reduction were further evaluated. Results: SVM did not reach sufficient overall predictive accuracies (38.0-54.2%) for anxiety reduction in the primary outcome. In the exploratory analyses, better accuracies (66.7%) were achieved for predicting interoception-specific symptom relief as an alternative outcome domain. Subtle information regarding this alternative response criterion but not the primary outcome was revealed by post hoc univariate comparisons. Conclusion: In contrast to reports on other neurofunctional probes, SVM based on an interoception paradigm was not able to reliably predict individual response to CBT. Results speak against the clinical applicability of this technique. [ABSTRACT FROM AUTHOR]

The underlying structure of problematic gambling behaviors, such as those assessed by the South Oaks Gambling Screen ( SOGS), remain unknown: Can problem gambling be assessed unidimensionally or should multiple qualitatively different dimensions be taken into account, and if so, what do these qualitative dimensions indicate? How significant are the deviations from unidimensionality in practice? A cross-sectional random sample of Finns aged 15-74 (n = 4,484) was drawn from the Population Information Registry and surveyed in 2011-2012. Analyses were conducted using descriptive statistics, Confirmatory factor analysis ( CFA) and multidimensional item response theory ( MIRT) models. Altogether, 14.9% of the population endorsed at least one of the 20 SOGS items, but nine items had low endorsement rates (≤ 0.2%). CFA and MIRT techniques suggested that individuals differed from each other in two positively correlated ( r = 0.70) underlying dimensions: 'impact on self primarily' and 'impact on others also'. This two-factor correlated-factors model can be reinterpreted as a bifactor model with one general gambling-problem factor and two specific factors with similar interpretation as in the correlated-factors model but with non-overlapping items. The two specific factors may provide clinically useful information without extra costs of assessment. [ABSTRACT FROM AUTHOR]

Study Design: A cross-sectional survey with a longitudinal follow-up.Objectives: The aim of this study was to test the hypothesis that pain, which is localized to the low back, differs epidemiologically from that which occurs simultaneously or close in time to pain at other anatomical sites SUMMARY OF BACKGROUND DATA.: Low back pain (LBP) often occurs in combination with other regional pain, with which it shares similar psychological and psychosocial risk factors. However, few previous epidemiological studies of LBP have distinguished pain that is confined to the low back from that which occurs as part of a wider distribution of pain.Methods: We analyzed data from CUPID, a cohort study that used baseline and follow-up questionnaires to collect information about musculoskeletal pain, associated disability, and potential risk factors, in 47 occupational groups (office workers, nurses, and others) from 18 countries.Results: Among 12,197 subjects at baseline, 609 (4.9%) reported localized LBP in the past month, and 3820 (31.3%) nonlocalized LBP. Nonlocalized LBP was more frequently associated with sciatica in the past month (48.1% vs. 30.0% of cases), occurred on more days in the past month and past year, was more often disabling for everyday activities (64.1% vs. 47.3% of cases), and had more frequently led to medical consultation and sickness absence from work. It was also more often persistent when participants were followed up after a mean of 14 months (65.6% vs. 54.1% of cases). In adjusted Poisson regression analyses, nonlocalized LBP was differentially associated with risk factors, particularly female sex, older age, and somatizing tendency. There were also marked differences in the relative prevalence of localized and nonlocalized LBP by occupational group.Conclusion: Future epidemiological studies should distinguish where possible between pain that is limited to the low back and LBP that occurs in association with pain at other anatomical locations.Level Of Evidence: 2. [ABSTRACT FROM AUTHOR]

The myriad controversies embroiling the mental health field-heightened in the lead-up to the release of DSM-5 (2013)-merit a close analysis of the field and its epistemological underpinnings. By using DSM as a starting point, this paper develops to overview the entire mental health field. Beginning with a history of the field and its recent crises, the troubles of the past 'external crisis' are compared to the contemporary 'internal crisis.' In an effort to examine why crises have recurred, the internal dynamics of the field are assessed: applying Kuhn's paradigmatic framework, crises are appraised to situate the differences between the natural sciences and the mental health field. Next, a Foucauldian analysis examines the functioning of the field's power over the body, which is disproportionate in comparison to its scientific grounding. This is followed by investigating the field's combination of contested scientific grounding and significant power, through a Latourian consideration of the assumptions and meaning behind the mental health field's deployment of science. This includes scrutinizing the history of the classification of Post-Traumatic Stress Disorder (PTSD). The paper closes by assessing the field's potential to address these issues effectively. [ABSTRACT FROM AUTHOR]