Content Validity of the Psychiatric Symptom Index Ces-Depression Scale, and State-Trait Anxiety Inventory from the Perspective of DSM-IV (original) (raw)
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2015
I express my deepest appreciation to my advisor, Dr. John Young for guiding, shaping, and supporting my academic pursuits throughout my graduate education at the University of Mississippi. I am also indebted to Dr. Danielle J. Maack who generously shared her laboratory equipment and research space for various parts of my dissertation project. In addition, I thank Dr. Alan M. Gross for giving invaluable advice and feedback and encouraging me to think critically about ways to advance the psychology field. Lastly, I also thank Dr. John P. Bentley for inspiring me to learn about the fascinating world of statistics. vii
2008
Abstract 1. 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.
Distinguishing symptom dimensions of depression and anxiety: An integrative approach
Journal of Affective Disorders, 2012
Background: Clark and Watson developed the tripartite model in which a symptom dimension of 'negative affect' covers common psychological distress that is typically seen in anxious and depressed patients. The 'positive affect' and 'somatic arousal' dimensions cover more specific symptoms. Although the model has met much support, it does not cover all relevant anxiety symptoms and its negative affect dimension is rather unspecific. Therefore, we aimed to extend the tripartite model in order to describe more specific symptom patterns with unidimensional measurement scales. Method: 1333 outpatients provided self report data. To develop an extended factor model, exploratory factor analysis (EFA) was conducted in one part of the data (n = 578). Confirmatory factor analysis (CFA) was conducted in the second part (n = 755), to assess model-fit and comparison with other models. Rasch analyses were done to investigate the unidimensionality of the factors. Results: EFA resulted in a 6-factor model: feelings of worthlessness, fatigue, somatic arousal, anxious apprehension, phobic fear and tension. CFA in the second sample showed that a 6factor model with a hierarchical common severity factor fits the data better than alternative 1-and 3-factor models. Rasch analyses showed that each of the factors and the total of factors can be regarded as unidimensional measurement scales. Limitations: The model is based on a restricted symptom-pool: more dimensions are likely to exist. Conclusion: The extended tripartite model describes the clinical state of patients more specifically. This is relevant for both clinical practice and research.
Psychometric considerations of depression symptom rating scales
Neuropsychiatry, 2011
Psychometric considerations of depression symptom rating scales Practice points Depression is a condition that is inferred from its symptoms and signs rather than a condition that can be observed directly such as a fracture, elevated body temperature or blood pressure. As such, depression can be viewed as a latent variable, inferred variable or construct rather than an observable variable. Latent variables have been commonly studied in psychometrics using what is known as classical test theory. More recently, various forms of modern test theory, in particular item response theory (IRT), have proven particularly useful in articulating features of tests used to infer depression. An IRT model developed by Samejima is particularly useful with polytomous (multipoint) scales, such as Likert scales, as opposed to scales that use binary responses. One of the several useful aspects of IRT is that it can be used to equate scales (i.e., provide a formal basis for saying that a score of X on test A corresponds to a score of Y on test B). This paper contrasts various scales used to infer depression with regard to their internal properties such as reliability and dimensionality. A key point is that reliability and related statistics are a function of the sample in which they are inferred (i.e., there is no such thing as 'the reliability of test X'). Although it is important to ensure that the various scales measure depression in a meaningful sense, their results are more similar than different because of their similar item content. Because of this and space limitations, we will not be concerned with this issue of validity.