Deconstructing negative symptoms of schizophrenia: avolition-apathy and diminished expression clusters predict clinical presentation and functional outcome.
TL;DR: It is suggested that distinct subgroups of patients with elevated AA or DE can be identified within the broader diagnosis of schizophrenia and that these subgroups show clinically meaningful differences in presentation.
About: This article is published in Journal of Psychiatric Research.The article was published on 2013-06-01 and is currently open access. It has received 343 citations till now. The article focuses on the topics: Avolition & Apathy.
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Stony Brook University1, University of Minnesota2, University of Notre Dame3, University of Vermont4, University of Toronto5, Boston University6, University of Maryland, Baltimore7, Duke University8, University of Kansas9, King's College London10, Columbia University11, Broad Institute12, Purdue University13, University of Iowa14, University of Georgia15, Texas A&M University16, Oklahoma State University–Stillwater17, University of Groningen18, Florida State University19, Uniformed Services University of the Health Sciences20, Bryn Mawr College21, University of North Texas22, University of Otago23, University at Buffalo24, University of Arizona25, University of New South Wales26, Northwestern University27, Emory University28, University of Kentucky29, University of Pittsburgh30, Brown University31
TL;DR: The HiTOP promises to improve research and clinical practice by addressing the aforementioned shortcomings of traditional nosologies and provides an effective way to summarize and convey information on risk factors, etiology, pathophysiology, phenomenology, illness course, and treatment response.
Abstract: The reliability and validity of traditional taxonomies are limited by arbitrary boundaries between psychopathology and normality, often unclear boundaries between disorders, frequent disorder co-occurrence, heterogeneity within disorders, and diagnostic instability. These taxonomies went beyond evidence available on the structure of psychopathology and were shaped by a variety of other considerations, which may explain the aforementioned shortcomings. The Hierarchical Taxonomy Of Psychopathology (HiTOP) model has emerged as a research effort to address these problems. It constructs psychopathological syndromes and their components/subtypes based on the observed covariation of symptoms, grouping related symptoms together and thus reducing heterogeneity. It also combines co-occurring syndromes into spectra, thereby mapping out comorbidity. Moreover, it characterizes these phenomena dimensionally, which addresses boundary problems and diagnostic instability. Here, we review the development of the HiTOP and the relevant evidence. The new classification already covers most forms of psychopathology. Dimensional measures have been developed to assess many of the identified components, syndromes, and spectra. Several domains of this model are ready for clinical and research applications. The HiTOP promises to improve research and clinical practice by addressing the aforementioned shortcomings of traditional nosologies. It also provides an effective way to summarize and convey information on risk factors, etiology, pathophysiology, phenomenology, illness course, and treatment response. This can greatly improve the utility of the diagnosis of mental disorders. The new classification remains a work in progress. However, it is developing rapidly and is poised to advance mental health research and care significantly as the relevant science matures. (PsycINFO Database Record
1,635 citations
Cites background from "Deconstructing negative symptoms of..."
...New research indicates that it is informative to subdivide negative symptoms into inexpressivity and avolitionapathy (Kotov et al., 2016; Kring, Gur, Blanchard, Horan, & Reise, 2013; Strauss et al., 2012, 2013), resulting in four homogenous components overall....
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University of Florida1, University of Düsseldorf2, Washington University in St. Louis3, University of New Mexico4, University of Pennsylvania5, Vanderbilt University6, New York University7, Creedmoor Psychiatric Center8, Cardiff University9, University of Iowa10, Harvard University11, Veterans Health Administration12, University of California, San Diego13, King's College London14, Maastricht University Medical Centre15, University of Maryland, Baltimore16
TL;DR: The essence of the broad DSM-IV definition of schizophrenia is retained and changes in its definition should improve diagnosis and characterization of individuals with schizophrenia and facilitate measurement-based treatment and concurrently provide a more useful platform for research that will elucidate its nature.
520 citations
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TL;DR: Research on reward processing in schizophrenia has begun to provide important insights into the cognitive and neural mechanisms associated with motivational impairments, and suggestions for novel behavioral intervention strategies that make use of external cues, reinforcers, and mobile technology are discussed.
Abstract: This article reviews and synthesizes research on reward processing in schizophrenia, which has begun to provide important insights into the cognitive and neural mechanisms associated with motivational impairments. Aberrant cortical-striatal interactions may be involved with multiple reward processing abnormalities, including: (1) dopamine-mediated basal ganglia systems that support reinforcement learning and the ability to predict cues that lead to rewarding outcomes; (2) orbitofrontal cortex-driven deficits in generating, updating, and maintaining value representations; (3) aberrant effort-value computations, which may be mediated by disrupted anterior cingulate cortex and midbrain dopamine functioning; and (4) altered activation of the prefrontal cortex, which is important for generating exploratory behaviors in environments where reward outcomes are uncertain. It will be important for psychosocial interventions targeting negative symptoms to account for abnormalities in each of these reward processes, which may also have important interactions; suggestions for novel behavioral intervention strategies that make use of external cues, reinforcers, and mobile technology are discussed.
353 citations
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University of Naples Federico II1, University of L'Aquila2, University of Turin3, University of Bari4, University of Bologna5, University of Catania6, University of Genoa7, University of Foggia8, Sapienza University of Rome9, University of Pisa10, University of Chieti-Pescara11, University of Siena12, University of Parma13, University of Salerno14, University of Milan15, University of Cagliari16, University of Brescia17, University of Padua18, University of Rome Tor Vergata19, University of Eastern Piedmont20
TL;DR: The observed complex associations among investigated predictors, mediators and real‐life functioning strongly suggest that integrated and personalized programs should be provided as standard treatment to people with schizophrenia.
344 citations
Cites result from "Deconstructing negative symptoms of..."
...A significant relationship between avolition and poor social outcome has been reported in previous studies (93-95)....
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TL;DR: The assessment of the negative symptom dimension has recently improved, but even current expert consensus‐based instruments diverge on several aspects and the use of objective measures might contribute to overcome uncertainties about the reliability of rating scales, but these measures require further investigation and validation.
314 citations
References
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TL;DR: The Brief Psychiatric Rating Scale (BRS) as mentioned in this paper was developed to provide a rapid assessment technique particularly suited to the evaluation of patient change, and it is recommended for use where efficiency, speed, and economy are important considerations.
Abstract: The Brief Psychiatric Rating Scale was developed to provide a rapid assessment technique particularly suited to the evaluation of patient change. Sixteen symptom constructs which have resulted from factor analyses of several larger sets of items, principally Lorr's Multidimensional Scale for Rating Psychiatric Patients (MSRPP) (1953) and Inpatient Multidimensional Psychiatric Scale (IMPS) (1960), have been included for rating on 7-point ordered category rating scales. The attempt has been to include a single scale to record degree of symptomacology in each of the relatively independent symptom areas which have been identified. Some of the preliminary work which has led to the identification of primary symptom constructs has been published (Gorham & Overall, 1960, 1961, Overall, Gorharn, & Shawver, 1961). While other reports are in preparation, applications of the Brief Scale in both pure and applied research suggest the importance of presenting the basic instrument to the wider scientific audience at this time, together with recommendations for its standard use. The primary purpose in developing the Brief Scale has been the development of a highly efficient, rapid evaluation procedure for use in assessing treatment change in psychiatric patients while at the same time yielding a rather comprehensive description of major symptom characteristics. It is recommended for use where efficiency, speed, and economy are important considerations, while more detailed evaluation procedures, such as those developed by Lorr (1953, 1961) should perhaps be wed in other cases. In order to achieve the maximum effectiveness in use of the Brief Scale, a standard interview procedure and more detailed description of rating concepts are included in this report. In addition, each symptom concept is defined briefly in the rating scale statements themselves. Raters using the scale should become thoroughly familiar with the scale definitions presented herein, after which the rating scale statements should be sufficient to provide recall of the nature and delineation of each symptom area. , To increase the reliability of ratings, it is recommended that patients be interviewed jointly by a team of two clinicians, with the two raters making independent ratings at the completion of the interview. An alternative procedure which has been recommended by some is to have raters discuss and arrive at a
10,457 citations
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01 Jan 1974
TL;DR: This fourth edition of the highly successful Cluster Analysis represents a thorough revision of the third edition and covers new and developing areas such as classification likelihood and neural networks for clustering.
Abstract: Cluster analysis comprises a range of methods for classifying multivariate data into subgroups. By organising multivariate data into such subgroups, clustering can help reveal the characteristics of any structure or patterns present. These techniques are applicable in a wide range of areas such as medicine, psychology and market research. This fourth edition of the highly successful Cluster Analysis represents a thorough revision of the third edition and covers new and developing areas such as classification likelihood and neural networks for clustering. Real life examples are used throughout to demonstrate the application of the theory, and figures are used extensively to illustrate graphical techniques. The book is comprehensive yet relatively non-mathematical, focusing on the practical aspects of cluster analysis.
9,857 citations
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01 Jan 1984
TL;DR: Cluster analysis is a multivariate procedure for detecting natural groupings in data that resembles discriminant analysis in one respect—the researcher seeks to classify a set of objects into subgroups although neither the number nor members of the subgroups are known.
Abstract: SYSTAT provides a variety of cluster analysis methods on rectangular or symmetric data matrices. Cluster analysis is a multivariate procedure for detecting natural groupings in data. It resembles discriminant analysis in one respect—the researcher seeks to classify a set of objects into subgroups although neither the number nor members of the subgroups are known. CLUSTER provides three procedures for clustering: Hierarchical Clustering, K-Clustering, and Additive Trees. The Hierarchical Clustering procedure comprises hierarchical linkage methods. The K-Clustering procedure splits a set of objects into a selected number of groups by maximizing between-cluster variation and minimizing within-cluster variation. The Additive Trees Clustering procedure produces a Sattath-Tversky additive tree clustering. Hierarchical Clustering clusters cases, variables, or both cases and variables simultaneously; K-Clustering clusters cases only; and Additive Trees clusters a similarity or dissimilarity matrix. Several distance metrics are available with Hierarchical Clustering and K-Clustering including metrics for binary, quantitative and frequency count data. Hierarchical Clustering has ten methods for linking clusters and displays the results as a tree (dendrogram) or a polar dendrogram. When the MATRIX option is used to cluster cases and variables, SYSTAT uses a gray-scale or color spectrum to represent the values. SYSTAT further provides five indices, viz., statistical criteria by which an appropriate number of clusters can be chosen from the Hierarchical Tree. Options for cutting (or pruning) and coloring the hierarchical tree are also provided. In the K-Clustering procedure SYSTAT offers two algorithms, KMEANS and KMEDIANS, for partitioning. Further, SYSTAT provides nine methods for selecting initial seeds for both KMEANS and KMEDIANS. Cluster analysis is a multivariate procedure for detecting groupings in data. The objects in these groups may be: Cases (observations or rows of a rectangular data file). For example, suppose health indicators (numbers of doctors, nurses, hospital beds, life expectancy, etc.) are recorded for countries (cases), then developed nations may form a subgroup or cluster separate from developing countries. Variables (characteristics or columns of the data). For example, suppose causes of death (cancer, cardiovascular, lung disease, diabetes, accidents, etc.) are recorded for each U.S. state (case); the results show that accidents are relatively independent of the illnesses. Cases and variables (individual entries in the data matrix). For example, certain wines are associated with good years of production. Other wines have other years that are better. Clusters may be of two sorts: overlapping or exclusive. Overlapping clusters allow the same object to appear in more than one …
2,533 citations
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TL;DR: The developed Scale for the Assessment of Negative Symptoms has excellent interrater reliability and the five symptom complexes defined by the scale have good internal consistency, which indicates that the conceptual organization of the scale is also cohesive.
Abstract: • Recently, a renaissance of interest in "negative symptoms," eg, affective flattening or impoverishment of speech and language, has occurred. Although some investigators believe that these symptoms are important indicators of outcome, of response to treatment, and perhaps of a distinct, underlying pathologic process, research on the negative-symptom syndrome in schizophrenia has been handicapped because no standard instrument existed to assess it. This investigation reports on the developed Scale for the Assessment of Negative Symptoms. When symptoms are defined by objective behavioral indices, they have excellent interrater reliability. Furthermore, the five symptom complexes defined by the scale (affective flattening, alogia, avolition, anhedonia, and attentional impairment) have good internal consistency, which indicates that the conceptual organization of the scale is also cohesive.
2,136 citations