End-stage renal disease (ESRD) is associated with significantly increased morbidity and mortality resulting from cardiovascular disease (CVD) and infections, accounting for 50% and 20%, respectively, of the total mortality in ESRD patients. It is possible that these two complications are linked to alterations in the immune system in ESRD, as uremia is associated with a state of immune dysfunction characterized by immunodepression that contributes to the high prevalence of infections among these patients, as well as by immunoactivation resulting in inflammation that may contribute to CVD. This review describes disorders of the innate and adaptive immune systems in ESRD, underlining the specific role of ESRD-associated disturbances of Toll-like receptors. Finally, based on the emerging links between the alterations of immune system, CVD, and infections in ESRD patients, it emphasizes the potential role of the immune dysfunction in ESRD as an underlying cause for the high mortality in this patient population and the need for more studies in this area.

We describe a new self-report instrument, the Inventory of Depression and Anxiety Symptoms (IDAS), which was designed to assess specific symptom dimensions related to major depression and related anxiety disorders. We created the IDAS by conducting principal factor analyses in three large samples (college students, psychiatric patients, community adults); we also examined the robustness of its psychometric properties in five additional samples (high school students, college students, young adults, postpartum women, psychiatric patients) that were not involved in the scale development process. The IDAS contains 10 specific symptom scales: Suicidality, Lassitude, Insomnia, Appetite Loss, Appetite Gain, Ill Temper, Well-Being, Panic, Social Anxiety, and Traumatic Intrusions. It also includes two broader scales: General Depression (which contains items overlapping with several other IDAS scales) and Dysphoria (which does not). The scales (a) are internally consistent, (b) capture the target dimensions well, and (c) define a single underlying factor. They show strong short-term stability, and display excellent convergent validity and good discriminant validity in relation to other self-report and interviewbased measures of depression and anxiety.

The original Inventory of Depression and Anxiety Symptoms (IDAS) contains 11 nonoverlapping scales assessing specific depression and anxiety symptoms. In creating the expanded version of the IDAS (the IDAS-II), our goal was to create new scales assessing other important aspects of the anxiety disorders as well as key symptoms of bipolar disorder. Factor analyses of the IDAS-II item pool led to the creation of seven new scales (Traumatic Avoidance, Checking, Ordering, Cleaning, Claustrophobia, Mania, Euphoria) plus an expanded version of Social Anxiety. These scales are internally consistent and show strong convergent and significant discriminant validity in relation to other self-report and interview-based measures of anxiety, depression, and mania. Furthermore, the scales demonstrate substantial criterion and incremental validity in relation to interview-based measures of DSM-IV (Diagnostic and Statistical Manual of Mental Disorders, fourth edition) symptoms and disorders. Thus, the expanded IDAS-II now assesses a broad range of depression, anxiety, and bipolar symptoms.

Amazon’s Mechanical Turk (MTurk) is arguably one of the most important research tools of the past decade. The ability to rapidly collect large amounts of high-quality human subjects data has advanced multiple fields, including personality and social psychology. Beginning in summer 2018, concerns arose regarding MTurk data quality leading to questions about the utility of MTurk for psychological research. We present empirical evidence of a substantial decrease in data quality using a four-wave naturalistic experimental design: pre-, during, and post-summer 2018. During and to some extent post-summer 2018, we find significant increases in participants failing response validity indicators, decreases in reliability and validity of a widely used personality measure, and failures to replicate well-established findings. However, these detrimental effects can be mitigated by using response validity indicators and screening the data. We discuss implications and offer suggestions to ensure data quality.

In 2 meta-analyses involving 58 studies and 59,575 participants, we quantitatively summarized the relative reliability and validity of continuous (i.e., dimensional) and discrete (i.e., categorical) measures of psychopathology. Overall, results suggest an expected 15% increase in reliability and 37% increase in validity through adoption of a continuous over discrete measure of psychopathology alone. This increase occurs across all types of samples and forms of psychopathology, with little evidence for exceptions. For typical observed effect sizes, the increase in validity is sufficient to almost halve sample sizes necessary to achieve standard power levels. With important caveats, the current results, considered with previous research, provide sufficient empirical and theoretical basis to assume a priori that continuous measurement of psychopathology is more reliable and valid. Use of continuous measures in psychopathology assessment has widespread theoretical and practical benefits in research and clinical settings.

Shortcomings of approaches to classifying psychopathology based on expert consensus have given rise to contemporary efforts to classify psychopathology quantitatively. In this paper, we review progress in achieving a quantitative and empirical classification of psychopathology. A substantial empirical literature indicates that psychopathology is generally more dimensional than categorical. When the discreteness versus continuity of psychopathology is treated as a research question, as opposed to being decided as a matter of tradition, the evidence clearly supports the hypothesis of continuity. In addition, a related body of literature shows how psychopathology dimensions can be arranged in a hierarchy, ranging from very broad "spectrum level" dimensions, to specific and narrow clusters of symptoms. In this way, a quantitative approach solves the "problem of comorbidity" by explicitly modeling patterns of co-occurrence among signs and symptoms within a detailed and variegated hierarchy of dimensional concepts with direct clinical utility. Indeed, extensive evidence pertaining to the dimensional and hierarchical structure of psychopathology has led to the formation of the Hierarchical Taxonomy of Psychopathology (HiTOP) Consortium. This is a group of 70 investigators working together to study empirical classification of psychopathology. In this paper, we describe the aims and current foci of the HiTOP Consortium. These aims pertain to continued research on the empirical organization of psychopathology; the connection between personality and psychopathology; the utility of empirically based psychopathology constructs in both research and the clinic; and the development of novel and comprehensive models and corresponding assessment instruments for psychopathology constructs derived from an empirical approach.

We describe a new self-report instrument, the Inventory of Depression and Anxiety Symptoms (IDAS), which was designed to assess specific symptom dimensions related to major depression and related anxiety disorders. We created the IDAS by conducting principal factor analyses in three large samples (college students, psychiatric patients, community adults); we also examined the robustness of its psychometric properties in five additional samples (high school students, college students, young adults, postpartum women, psychiatric patients) that were not involved in the scale development process. The IDAS contains 10 specific symptom scales: Suicidality, Lassitude, Insomnia, Appetite Loss, Appetite Gain, Ill Temper, Well-Being, Panic, Social Anxiety, and Traumatic Intrusions. It also includes two broader scales: General Depression (which contains items overlapping with several other IDAS scales) and Dysphoria (which does not). The scales (a) are internally consistent, (b) capture the target dimensions well, and (c) define a single underlying factor. They show strong short-term stability, and display excellent convergent validity and good discriminant validity in relation to other self-report and interview-based measures of depression and anxiety.

Experiential avoidance (EA) has been conceptualized as the tendency to avoid negative internal experiences and is an important concept in numerous conceptualizations of psychopathology as well as theories of psychotherapy. Existing measures of EA have either been narrowly defined or demonstrated unsatisfactory internal consistency and/or evidence of poor discriminant validity vis-à-vis neuroticism. To help address these problems, we developed a reliable self-report questionnaire assessing a broad range of EA content that was distinguishable from higher order personality traits. An initial pool of 170 items was administered to a sample of undergraduates (N = 312) to help evaluate individual items and establish a structure via exploratory factor analyses. A revised set of items was then administered to another sample of undergraduates (N = 314) and a sample of psychiatric outpatients (N = 201). A 2nd round of item evaluation was performed, resulting in a final 62-item measure consisting of 6 subscales. Cross-validation data were gathered in 3 new, independent samples (students, N = 363; patients, N = 265; community adults, N = 215). The resulting measure (the Multidimensional Experiential Avoidance Questionnaire, or MEAQ) exhibited good internal consistency, was substantially associated with other measures of avoidance, and demonstrated greater discrimination vis-à-vis neuroticism relative to preexisting measures of EA. Furthermore, the MEAQ was broadly associated with psychopathology and quality of life, even after controlling for the effects of neuroticism.