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. (Contains 3 footnotes, 9 tables, and 6 figures.)
The authors describe a new self-report instrument, the Inventory of Depression and Anxiety Symptoms (IDAS), which was designed to assess specific symptom dimensions of major depression and related ...anxiety disorders. They created the IDAS by conducting principal factor analyses in 3 large samples (college students, psychiatric patients, community adults); the authors also examined the robustness of its psychometric properties in 5 additional samples (high school students, college students, young adults, postpartum women, psychiatric patients) who 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 2 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.
Suppressor effects are operating when the addition of a predictor increases the predictive power of another variable. We argue that suppressor effects can play a valuable role in explicating the ...construct validity of symptom measures by bringing into clearer focus opposing elements that are inherent-but largely hidden-in the measure's overall score. We illustrate this point using theoretically grounded, replicated suppressor effects that have emerged in analyses of the original Inventory of Depression and Anxiety Symptoms (IDAS; Watson et al., 2007) and its expanded 2nd version (IDAS-II; Watson et al., 2012). In Study 1, we demonstrate that the IDAS-II Appetite Gain and Appetite Loss scales contain both (a) a shared distress component that creates a positive correlation between them and (b) a specific symptom component that produces a natural negative association between them (i.e., people who recently have experienced decreased interest in food/loss of appetite are less likely to report a concomitant increase in appetite/weight). In Study 2, we establish that mania scales also contain 2 distinct elements-namely, high energy/positive emotionality and general distress/dysfunction-that oppose each another in many instances. In both studies, we obtained evidence of suppression effects that were highly robust across different types of respondents (e.g., clinical outpatients, community adults, college students) and using both self-report and interview-based measures. These replicable suppressor effects establish that many homogeneous, unidimensional symptom scales actually contain distinguishable components with distinct-at times, even antagonistic-properties.
For more than a century, research on psychopathology has focused on categorical diagnoses. Although this work has produced major discoveries, growing evidence points to the superiority of a ...dimensional approach to the science of mental illness. Here we outline one such dimensional system—the Hierarchical Taxonomy of Psychopathology (HiTOP)—that is based on empirical patterns of co-occurrence among psychological symptoms. We highlight key ways in which this framework can advance mental-health research, and we provide some heuristics for using HiTOP to test theories of psychopathology. We then review emerging evidence that supports the value of a hierarchical, dimensional model of mental illness across diverse research areas in psychological science. These new data suggest that the HiTOP system has the potential to accelerate and improve research on mental-health problems as well as efforts to more effectively assess, prevent, and treat mental illness.
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.
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.
Pediatric asthma is a common, relapsing-remitting, chronic inflammatory airway disease that when uncontrolled often leads to substantial patient and health care system burden. Improving management of ...asthma in primary care can help patients stay well controlled.
The Vermont Child Health Improvement Program (VCHIP) developed a quality improvement (QI) learning collaborative with a primary objective to improve clinical asthma management measures through improvement in primary care office systems to support asthma care. Seven months of medical record review data were evaluated for improvements on eight clinical asthma management measures. Pre and post office systems inventory (OSI) self-assessments detailing adherence to improvement strategies were analyzed for improvement. Logistic regressions were used to test for associations between OSI strategy post scores and the corresponding clinical asthma management measures by month seven.
This study found significant improvement from baseline to month seven on seven of the eight clinical asthma management measures and between pre and post OSI for seven of the nine strategies assessed (N = 19 practices). Additionally, one point higher average OSI scores on the assessment and monitoring of asthma severity, asthma control, asthma action plans, and asthma education strategies were associated with significantly greater odds of improvement in their respective clinical asthma management measures.
A QI learning collaborative approach in primary care can improve office systems and corresponding clinical management measures for pediatric patients with asthma. This suggests that linking specific office systems strategies to clinical measures may be a helpful tactic within the learning collaborative model.
Further Validation of the IDAS Watson, David; O'Hara, Michael W; Chmielewski, Michael ...
Psychological assessment,
09/2008, Letnik:
20, Številka:
3
Journal Article
Recenzirano
The authors explicated the validity of the Inventory of Depression and Anxiety Symptoms (IDAS;
D. Watson et al., 2007
) in 2 samples (306 college students and 605 psychiatric patients). The IDAS ...scales showed strong convergent validity in relation to parallel interview-based scores on the Clinician Rating version of the IDAS; the mean convergent correlations were .51 and .62 in the student and patient samples, respectively. With the exception of the Well-Being Scale, the scales also consistently demonstrated significant discriminant validity. Furthermore, the scales displayed substantial criterion validity in relation to
Diagnostic and Statistical Manual of Mental Disorders
(4th ed.;
DSM-IV
;
American Psychiatric Association, 1994
) mood and anxiety disorder diagnoses in the patient sample. The authors identified particularly clear and strong associations between (a) major depression and the IDAS General Depression, Dysphoria and Well-Being scales, (b) panic disorder and IDAS Panic, (c) posttraumatic stress disorder and IDAS Traumatic Intrusions, and (d) social phobia and IDAS Social Anxiety. Finally, in logistic regression analyses, the IDAS scales showed significant incremental validity in predicting several
DSM-IV
diagnoses when compared against the Beck Depression Inventory-II (
A. T. Beck, R. A. Steer, & G. K. Brown, 1996
) and the Beck Anxiety Inventory (
A. T. Beck & R. A. Steer, 1990
).
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.
What Is Being Assessed and Why It Matters Chmielewski, Michael; Watson, David
Journal of personality and social psychology,
07/2009, Letnik:
97, Številka:
1
Journal Article
Recenzirano
Temporal instability can reflect either true psychological change or transient measurement error, and it is important that trait psychologists be able to distinguish one from the other. The authors ...report results from large retest studies of Big Five, trait affectivity, and personality disorder measures across time frames (2 months and 2 weeks) over which these constructs should show little or no true change. On average, nearly 25% of the variance in the measures was a product of transient error rather than true change; however, the proportion of error varied widely-but consistently-across measures. In addition, a reexamination of long-term longitudinal data demonstrated that ignoring transient error can lead to inaccurate conclusions. Most notably, a substantial portion of the observed instability in the Big Five and trait affectivity is due to transient error; thus, these traits are even more stable than commonly thought. The present data further suggest that previous reports of differential stability between the Big Five and trait affectivity are due, in part, to differential levels of transient error in measures of these constructs.
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