Racial and Ethnic Bias in the Diagnosis of Alcohol Use Disorder in Veterans.

OBJECTIVE: Studies show that racially and ethnically minoritized veterans have a higher prevalence of alcohol use disorder (AUD) than White veterans. The investigators examined whether the relationship between self-reported race and ethnicity and AUD diagnosis remains after adjusting for alcohol consumption, and if so, whether it varies by self-reported alcohol consumption. METHODS: The sample included 700,012 Black, White, and Hispanic veterans enrolled in the Million Veteran Program. Alcohol consumption was defined as an individual's maximum score on the consumption subscale of the Alcohol Use Disorders Identification Test (AUDIT-C), a screen for unhealthy alcohol use. A diagnosis of AUD, the primary outcome, was defined by the presence of relevant ICD-9 or ICD-10 codes in electronic health records. Logistic regression with interactions was used to assess the association between race and ethnicity and AUD as a function of maximum AUDIT-C score. RESULTS: Black and Hispanic veterans were more likely than White veterans to have an AUD diagnosis despite similar levels of alcohol consumption. The difference was greatest between Black and White men; at all but the lowest and highest levels of alcohol consumption, Black men had 23%-109% greater odds of an AUD diagnosis. The findings were unchanged after adjustment for alcohol consumption, alcohol-related disorders, and other potential confounders. CONCLUSIONS: The large discrepancy in the prevalence of AUD across groups despite a similar distribution of alcohol consumption levels suggests that there is racial and ethnic bias, with Black and Hispanic veterans more likely than White veterans to receive an AUD diagnosis. Efforts are needed to reduce bias in the diagnostic process to address racialized differences in AUD diagnosis.

Reproducibility of Glycemic Measures Among Dysglycemic Youth and Adults in the RISE Study.

AIMS: Previous work found poor reproducibility for measures of glycemia in individuals at risk for dysglycemia. Differences between youth and adults have not been assessed. Using youth and adults in the Restoring Insulin Secretion Study, we tested variability and classification concordance for hemoglobin A1C (HbA1c), fasting and 2-hour glucose from oral glucose tolerance tests (OGTTs). METHODS: HbA1c and glucose on repeated samples obtained ∼6 weeks apart were compared in 66 youth (mean age 14.2 years) and 354 adults (52.7 years). Changes, coefficient of variation (CV), and concordance of diagnostic categories between the 2 visits were compared. RESULTS: Mean difference between the 2 visits in HbA1c was higher in youth than adults (P < .001), while fasting glucose was similar and 2-hour glucose was lower in youth (P = .051). CV was smallest for HbA1c compared to fasting and 2-hour glucose. For HbA1c, youth had higher CV (P < .001); whereas CV for 2-hour glucose was lower for youth (P = .041). Classification concordance by HbA1c was lower in youth (P = .004). Using OGTT or HbA1c for classification, intervisit variability produced discordant classification in 20% of youth and 28% of adults. Using both fasting glucose and HbA1c, intervisit variability reduced discordant classification to 16% of adults while not improving classification in youth. CONCLUSIONS: Poor reproducibility and lack of classification concordance highlight the limitations of one-time testing, with important implications for assessing eligibility in clinical trials. Consideration should be given to using more than a single parameter for screening and diagnosis, especially when classification category is important.

Classification statistics of the Montreal Cognitive Assessment (MoCA): Are we interpreting the MoCA correctly?

OBJECTIVE: The Montreal Cognitive Assessment (MoCA) is a common cognitive screener for detecting mild cognitive impairment (MCI). However, previously suggested cutoff scores of 26/30 and above is often criticized and lacks racial diversity. The purpose of this study is to investigate the potential influence of race on MoCA classification cutoff score accuracy. METHOD: Data were obtained from the National Alzheimer's Coordinating Center (NACC) Uniform Data Set and yielded 4,758 total participants. Participants were predominately White (82.8%) and female (61.7%) with a mean age of 69.3 years (SD = 10.3) and education level of 16.3 years (SD = 2.6). Based on NACC's classification, participants were either cognitively normal (n = 3,650) or MCI (n = 1,108). RESULTS: Sensitivity and specificity analyses revealed that when using the cutoff score of ≤26/30, the MoCA correctly classified 73.2% of White cognitively normal participants and 83.1% of White MCI participants. In contrast, this criterion correctly classified 40.5% of Black cognitively normal participants and 90.8% of Black MCI participants. Our sample was highly educated; therefore, we did not observe significant differences in scores when accounting for education across race. Classification statistics are presented. CONCLUSIONS: Black participants were misclassified at a higher rate than White participants when applying the ≤26/30 cutoff score. We suggest cutoff scores of ≤25/30 be applied to White persons and ≤22/30 for Black persons. These findings highlight the need for racially stratified population-based norms given the high misclassification of Black participants without such adjustment.

Mapping Research Domain Criteria using a transdiagnostic mini-RDoC assessment in mental disorders: a confirmatory factor analysis.

This study aimed to build on the relationship of well-established self-report and behavioral assessments to the latent constructs positive (PVS) and negative valence systems (NVS), cognitive systems (CS), and social processes (SP) of the Research Domain Criteria (RDoC) framework in a large transnosological population which cuts across DSM/ICD-10 disorder criteria categories. One thousand four hundred and thirty one participants (42.1% suffering from anxiety/fear-related, 18.2% from depressive, 7.9% from schizophrenia spectrum, 7.5% from bipolar, 3.4% from autism spectrum, 2.2% from other disorders, 18.4% healthy controls, and 0.2% with no diagnosis specified) recruited in studies within the German research network for mental disorders for the Phenotypic, Diagnostic and Clinical Domain Assessment Network Germany (PD-CAN) were examined with a Mini-RDoC-Assessment including behavioral and self-report measures. The respective data was analyzed with confirmatory factor analysis (CFA) to delineate the underlying latent RDoC-structure. A revised four-factor model reflecting the core domains positive and negative valence systems as well as cognitive systems and social processes showed a good fit across this sample and showed significantly better fit compared to a one factor solution. The connections between the domains PVS, NVS and SP could be substantiated, indicating a universal latent structure spanning across known nosological entities. This study is the first to give an impression on the latent structure and intercorrelations between four core Research Domain Criteria in a transnosological sample. We emphasize the possibility of using already existing and well validated self-report and behavioral measurements to capture aspects of the latent structure informed by the RDoC matrix.

DSM-5-TR: Rationale, Process, and Overview of Changes.

The DSM-5 text revision (DSM-5-TR) is the first published revision of the DSM-5 since its publication in 2013. Like the previous text revision (DSM-IV-TR), the main goal of the DSM-5-TR is to comprehensively update the descriptive text accompanying each DSM disorder on the basis of reviews of the literature over the past 10 years. In contrast to the DSM-IV-TR, in which updates were confined almost exclusively to the text, the DSM-5-TR includes many other changes and enhancements of interest to practicing clinicians, such as the addition of diagnostic categories (prolonged grief disorder, stimulant-induced mild neurocognitive disorder, unspecified mood disorder, and a category to indicate the absence of a diagnosis); the provision of ICD-10-CM symptom codes for reporting suicidal and nonsuicidal self-injurious behavior; modifications, mostly for clarity, of the diagnostic criteria for more than 70 disorders; and updates in terminology (e.g., replacing "neuroleptic medications" with "antipsychotic medications or other dopamine receptor blocking agents" throughout the text and replacing "desired gender" with "experienced gender" in the text for gender dysphoria). Finally, the entire text was reviewed by an Ethnoracial Equity and Inclusion Work Group to ensure appropriate attention to risk factors such as the experience of racism and discrimination, as well as the use of nonstigmatizing language.

Nature and Assessment of Personality Pathology and Diagnosis.

This article demonstrates the contribution of Otto Kernberg's object relations theory of personality pathology to the current understanding of the nature and assessment of personality pathology and diagnosis. The article introduces recent advances in psychiatric nosology and presents differing views on the meaning of the general severity criterion common to all personality pathology (i.e., level of personality functioning as described in criterion A of the Alternative DSM-5 Model for Personality Disorders). Next, the significance of Kernberg's theory to recent nosological advances is discussed, with a focus on two important features: first, a definition of personality that goes beyond signs and symptoms to include structural motivational components, in the domains of self- and interpersonal functioning, that are common to all personality manifestations and that fulfill an intrapsychic, organizing function; second, identity formation and consolidation as the ultimate end point of healthy personality functioning. That these cornerstone features of Kernberg's theory, articulated more than 50 years ago, align with the most up-to-date conceptualization of personality pathology confirms that Kernberg's theory represents an idea whose time has finally come.

Object Relations Theory Model of Personality Disorders.

Contemporary models of the diagnosis and classification of personality disorders have diverged from the categorical diagnostic framework of the DSM system. One response to this movement can be found in the Alternative DSM-5 Model for Personality Disorders (AMPD), which uses dimensions of personality functioning, coupled with identification of dominant pathological traits, to define and classify personality disorders. By applying psychodynamic object relations theory to the AMPD, therapists can enrich the understanding and assessment of personality functioning and pathology as described in the AMPD.

Preclinical and clinical evidence on the approach-avoidance conflict evaluation as an integrative tool for psychopathology.

The approach-avoidance conflict (AAC), i.e. the competing tendencies to undertake goal-directed actions or to withdraw from everyday life challenges, stands at the basis of humans' existence defining behavioural and personality domains. Gray's Reinforcement Sensitivity Theory posits that a stable bias toward approach or avoidance represents a psychopathological trait associated with excessive sensitivity to reward or punishment. Optogenetic studies in rodents and imaging studies in humans associated with cross-species AAC paradigms granted new emphasis to the hippocampus as a hub of behavioural inhibition. For instance, recent functional neuroimaging studies show that functional brain activity in the human hippocampus correlates with threat perception and seems to underlie passive avoidance. Therefore, our commentary aims to (i) discuss the inhibitory role of the hippocampus in approach-related behaviours and (ii) promote the integration of functional neuroimaging with cross-species AAC paradigms as a means of diagnostic, therapeutic, follow up and prognosis refinement in psychiatric populations.

Diagnostic terms psychiatrists prefer to use for common psychotic and personality disorders.

OBJECTIVE: There are ongoing discussions on updating various standard psychiatric terms, including schizophrenia, which can be confusing, and personality disorders, which can be pejorative. To contribute to this process, suggestions and recommendations on terminology were sought from academic psychiatrists with substantial clinical experience. METHODS: In an online survey, 263 psychiatrists were asked how often they used alternative instead of standard terms for the diagnosis or symptom description of psychotic disorders and DSM Cluster B personality disorders. They were also asked what specific terms they preferred to use. Reasons for their views and choices were obtained. RESULTS: 125 clinicians (48%) responded. Only a minority of clinicians (31%) tended to use the term schizophrenia often, preferring to say psychosis or to refer to thinking and perceptual problems. Even lower proportions of clinicians (7-14%) often use the terms for Cluster B personality disorder subtypes: antisocial, narcissistic, histrionic, and borderline. Alternatives suggested for these disorders included discussing emotional dysregulation, traits of sensitivity and reactivity, and relational difficulties. Reasons cited for choosing alternative terms were to avoid miscommunication (71% of responders) and to avoid offending the patient (78% of responders). CONCLUSIONS: There are practical alternatives to standard psychiatric terminology that may improve communication with patients and be more respectful choices, as well. The suggestions of the psychiatrists responding to this survey might be of immediate value to others in their practices and might be worthy of consideration by those writing the next versions of the standard manuals, both the DSM and the ICD.

Genes To Mental Health (G2MH): A Framework to Map the Combined Effects of Rare and Common Variants on Dimensions of Cognition and Psychopathology.

Rare genomic disorders (RGDs) confer elevated risk for neurodevelopmental psychiatric disorders. In this era of intense genomics discoveries, the landscape of RGDs is rapidly evolving. However, there has not been comparable progress to date in scalable, harmonized phenotyping methods. As a result, beyond associations with categorical diagnoses, the effects on dimensional traits remain unclear for many RGDs. The nature and specificity of RGD effects on cognitive and behavioral traits is an area of intense investigation: RGDs are frequently associated with more than one psychiatric condition, and those studied to date affect, to varying degrees, a broad range of developmental and cognitive functions. Although many RGDs have large effects, phenotypic expression is typically influenced by additional genomic and environmental factors. There is emerging evidence that using polygenic risk scores in individuals with RGDs offers opportunities to refine prediction, thus allowing for the identification of those at greatest risk of psychiatric illness. However, translation into the clinic is hindered by roadblocks, which include limited genetic testing in clinical psychiatry, and the lack of guidelines for following individuals with RGDs, who are at high risk of developing psychiatric symptoms. The Genes to Mental Health Network (G2MH) is a newly funded National Institute of Mental Health initiative that will collect, share, and analyze large-scale data sets combining genomics and dimensional measures of psychopathology spanning diverse populations and geography. The authors present here the most recent understanding of the effects of RGDs on dimensional behavioral traits and risk for psychiatric conditions and discuss strategies that will be pursued within the G2MH network, as well as how expected results can be translated into clinical practice to improve patient outcomes.

An Answer to "So What?" Implications of Network Theory for Research and Practice.

Research and practice in psychiatry and clinical psychology have been guided by differing schools of thought over the years. Recently, the network theory of psychopathology has arisen as a framework for thinking about mental health. Network theory challenges three common assumptions: psychological problems are caused by disease entities that exist independently of their signs and symptoms, classification and diagnosis of psychological problems should follow a medical model, and psychological problems are caused by diseases or aberrations in the brain. Conversely, network theory embraces other assumptions that are well accepted in clinical practice (e.g., the interaction of thoughts, behaviors, and emotions, as posited in cognitive-behavioral therapies) and integrates those assumptions into a coherent framework for research and practice. In this article, the authors review developments in network theory by focusing on anxiety-related conditions, discuss future areas for change, and outline implications of network theory for research and clinical practice.

Obsessive-Compulsive (Anankastic) Personality Disorder in the ICD-11: A Scoping Review.

Introduction: With the shift from a categorical to a dimensional model, ICD-11 has made substantial changes to the diagnosis of personality disorders (PDs), including obsessive-compulsive (anankastic) personality disorder (OCPD). The ICD-11 PD model proposes a single diagnosis of PD with specifications regarding severity and domains. However, a systematic overview of ICD-11 anankastia is lacking. In this review we address the reformulation of the OCPD diagnosis in the ICD-11, and draw comparisons with the DSM-5, with a particular focus on diagnostic validity and clinical utility. We hypothesized that the ICD-11 PD model provides a diagnostically valid and clinically useful approach to OCPD, with specific emphasis on the anankastia domain as the primary trait qualifier. Methods: Literature published from 2010 to 2020 was systematically searched using the PubMed/MEDLINE, PsychInfo, Cochrane, and Web of Sciences search engines, in order to find all articles that addressed ICD-11 anankastia. Relevant articles were collated, and themes of these articles subsequently extracted. Results: Out of the 264 publications identified, 19 articles were included in this review. Four themes were identified, namely (a) overlap of DSM-5 OCPD with the ICD-11 PD model, (b) the factorial structure of the ICD-11 PD model with respect to the anankastia domain, (c) the clinical utility of the ICD-11 PD model, and (d) comparison of the ICD-11 PD model of anankastia with the DSM-5 alternative model for OCPD. Conclusions: The ICD-11 anankastia domain overlaps with DSM-5 OCPD traits, and the factor analyses of the ICD-11 PD model further support the diagnostic validity of this domain. There is some support for the clinical utility of the ICD-11 PD model of anankastia but further studies are needed, including of its relationship to obsessive-compulsive and related disorders.

A Bayesian approach to estimating the population prevalence of mood and anxiety disorders using multiple measures.

AIMS: There is currently no universally accepted measure for population-based surveillance of mood and anxiety disorders. As such, the use of multiple linked measures could provide a more accurate estimate of population prevalence. Our primary objective was to apply Bayesian methods to two commonly employed population measures of mood and anxiety disorders to make inferences regarding the population prevalence and measurement properties of a combined measure. METHODS: We used data from the 2012 Canadian Community Health Survey - Mental Health linked to health administrative databases in Ontario, Canada. Structured interview diagnoses were obtained from the survey, and health administrative diagnoses were identified using a standardised algorithm. These two prevalence estimates, in addition to data on the concordance between these measures and prior estimates of their psychometric properties, were used to inform our combined estimate. The marginal posterior densities of all parameters were estimated using Hamiltonian Monte Carlo (HMC), a Markov Chain Monte Carlo technique. Summaries of posterior distributions, including the means and 95% equally tailed posterior credible intervals, were used for interpretation of the results. RESULTS: The combined prevalence mean was 8.6%, with a credible interval of 6.8-10.6%. This combined estimate sits between Bayesian-derived prevalence estimates from administrative data-derived diagnoses (mean = 7.4%) and the survey-derived diagnoses (mean = 13.9%). The results of our sensitivity analysis suggest that varying the specificity of the survey-derived measure has an appreciable impact on the combined posterior prevalence estimate. Our combined posterior prevalence estimate remained stable when varying other prior information. We detected no problematic HMC behaviour, and our posterior predictive checks suggest that our model can reliably recreate our data. CONCLUSIONS: Accurate population-based estimates of disease are the cornerstone of health service planning and resource allocation. As a greater number of linked population data sources become available, so too does the opportunity for researchers to fully capitalise on the data. The true population prevalence of mood and anxiety disorders may reside between estimates obtained from survey data and health administrative data. We have demonstrated how the use of Bayesian approaches may provide a more informed and accurate estimate of mood and anxiety disorders in the population. This work provides a blueprint for future population-based estimates of disease using linked health data.

Patient descriptions of loss of control and eating episode size interact to influence expert diagnosis of ICD-11 binge-eating disorder.

BACKGROUND: Although data suggest that the sense of "loss of control" (LOC) is the most salient aspect of binge eating, the definition of LOC varies widely across eating disorder assessments. The WHO ICD-11 diagnostic guidelines for binge eating do not require an objectively large amount of food, which makes accurate LOC diagnosis even more critical. However, it can be especially challenging to assess LOC in the context of elevated weight status and in the absence of compensatory behaviors. This ICD-11 field sub-study examined how descriptions of subjective experience during distressing eating episodes, in combination with different eating episode sizes, influence diagnoses of binge-eating disorder (BED). METHOD: Mental health professionals with eating disorder expertise from WHO's Global Clinical Practice Network (N = 192) participated in English, Japanese, and Spanish. Participants were asked to select the correct diagnosis for two randomly assigned case vignettes and to rate the clinical importance and ease of use of each BED diagnostic guideline. RESULTS: The presence of LOC interacted with episode size to predict whether a correct diagnostic conclusion was reached. If the amount consumed during a typical distressing eating episode was only subjectively large compared to objectively large, clinicians were 23.1 times more likely to miss BED than to correctly diagnose it, and they were 9.7 times more likely to incorrectly diagnose something else than to correctly diagnose BED. In addition, clinicians were 10.8 times more likely to make a false positive diagnosis of BED when no LOC was described if the episode was objectively large. Descriptions of LOC that were reliably associated with correct diagnoses across episodes sizes included two that are similar to those already included in proposed ICD-11 guidelines and a third that is not. This third description of LOC focuses on giving up attempts to control eating because perceived overeating feels inevitable. CONCLUSIONS: Results highlight the importance of detailed clarification of the LOC construct in future guidelines. Explicitly distinguishing LOC from distressing and mindless overeating could help promote consistent and accurate diagnosis of BED versus another or no eating disorder.

[Diagnosis and treatment of ankyloglossia in newborns and infants].

Ankyloglossia is a congenital condition characterized by a short lingual frenulum, which may result in the restriction of tongue movement and function. Considerable controversy regarding the diagnosis, clinical significance, and management of the condition remains, and great variations in practice have been recorded. Indeed, attitudes toward ankyloglossia differ among professional groups, and opinions may vary remarkably even among those within the same specialty. This article reviews the embryology, genetics, diagnosis, clinical presentation, and treatment of ankyloglossia to help physicians better understand and treat the condition.

Disruptive Behavior Disorders: The Challenge of Delineating Mechanisms in the Face of Heterogeneity.

Causal pathways to disruptive behavior disorders, even within the same diagnostic category, are varied. Both equifinality and multifinality pose considerable challenges to uncovering underlying mechanisms and understanding varied developmental trajectories associated with disruptive behavior disorders. Uncovering genetic causes requires improved granularity in how we operationalize presentation and developmental trajectories associated with disruptive behavior disorders. If we want to integrate the study of genetic, environmental, and neurocognitive factors within a longitudinal framework, we need to improve measurement. Furthermore, brain changes associated with disruptive behavior disorders should not simply be understood as outcomes of genetic and environmental influences, but also as factors that reciprocally influence future social environments over time in ways that are important in contributing to risk and resilience. Advancing the field with regard to these challenges will result in more truly integrated investigation of disruptive behavior disorders, which holds the promise of improving our ability to develop more effective preventive and intervention approaches.