Nicholas R. Eaton and Robert F. Krueger
Assessment is at the very core of clinical and research endeavors to understand and ameliorate depressive disorders. In the current chapter, we discuss pressing issues in assessment of depressive disorders beginning with the definitional: how these disorders are conceptualized and classified. We highlight the DSM-IV-TR nosological organization of depressive disorders, and those disorders that are closely related (e.g., anxiety and adjustment disorders), as well as current depressive disorder proposals for the upcoming DSM-5. The high rates of comorbidity among the depressive and related disorders are discussed as an assessment challenge, and we propose a unified latent structure framework to supplement clinical assessment that involves characterizing individuals’ levels of underlying internalizing disorder liability. We discuss how disorders, and the latent internalizing liability, may manifest differently across subpopulations, such as age and ethnicity/culture. Finally, we discuss psychometric issues and conclude with a list of critical unanswered questions in depressive disorder assessment.
Thomas A. Widiger and Whitney L. Gore
This chapter provides a discussion of the American Psychiatric Association’s classification of mental disorders (DSM-I through DSM-5), with a particular emphasis on mood disorders and their classification and diagnosis. It begins with the rationale for having an official, authoritative diagnostic manual and then traces the history of the development of the first edition through the fourth edition (DSM-IV-TR, 2000). The authors then discuss fundamental issues concerning the fifth edition (DSM-5, 2013), including the definition of mental disorder, the empirical support for proposed revisions, the shift toward a dimensional model of classification, and the shift toward a neurobiologically-based classification.
Mark D. Litt, Howard Tennen, and Glenn Affleck
The idea of coping has been central to our understanding of adaptation to stressors for more than 30 years. Models of coping have included factors such as traits or other dispositions, appraisals, expectancies, moods, characteristics of the situation, and health outcomes themselves. Despite the fact that coping theory was initially construed as dynamic and transactional in nature, most models of coping have been unidirectional, and have treated coping as a static outcome of the constituent factors. In this chapter we argue that unidirectional models of coping and adaptation have come about as a result of our difficulty in measuring coping as a dynamic process that unfolds over time, and that coping changes moment to moment or day to day depending on the situational determinants and the coping processes that have occurred before. Daily process and momentary assessment technologies, allied with multi-level statistical techniques, are now allowing a more detailed understanding of coping and its complexities. In this chapter we review the development of new coping models and how intensive measurement is enhancing our view of how coping works.
Phillip D. Ruppert and Deborah K. Attix
Older adults will account for a growing proportion of the global population. There will be an increased need for clinicians who are competent in evaluating and/or treating geriatric disorders. The ability to differentiate between normal and pathological conditions of aging will be essential to the clinical practice of geropsychologists and general clinicians. Clinicians specializing in care of geriatric populations will be well served by knowledge of how to identify and manage the emotional and functional impact of both normal cognitive change and the neurological disorders of ageing. This chapter provides an overview of some of the most common causes of cognitive impairment in later life. We then discuss options for assessing for cognitive impairment in older adults and best practices for providing feedback of cognitive testing to geriatric patients and their care-givers. Next, we introduce the topic of neuropsychological interventions as a non-pharmacological tool that clinicians may use to help older adults and care-givers compensate for cognitive impairments in their daily lives. Finally, a model for treatment planning in neuropsychological interventions is discussed, and case examples are provided to illustrate use of this model.
Suzanne C. Segerstrom and Gregory T. Smith
Every researcher deals with error at some level. In psychoneuroimmunology (PNI) research, there may be error due to substantive fluctuations in immune parameters (e.g., as related to stress, time of day, or activity). This error is significant for some parameters, but it can and should be minimized by taking multiple measurements or converted into “good,” substantive variance by measuring variables that can predict the fluctuations. Type I and Type II “bad” errors are of more concern; many PNI studies have far too few subjects for the number of effects they test. Of studies included in a recent meta-analysis of stress and human immunity, several studies actually had fewer subjects than they had statistical tests. Finally, variance due to assay or supply variability contributes to “ugly” error, and it should be addressed by analysis of covariance or partial variance. However, too often, important variance due to factors such as age is designated as “ugly” rather than incorporated into the model. We suggest solutions for addressing “good,” “bad,” and “ugly” error and look into the future of physiometrics.
Screening, Assessment, and Diagnosis of Mood and Anxiety Disorders During Pregnancy and the Postpartum Period
Kimberly J. Hart and Heather A. Flynn
Mood and anxiety disorders are highly prevalent in perinatal samples, affecting as many as 20% of childbearing women (Gavin et al., 2005). In an effort to prevent adverse outcomes associated with perinatal mood and anxiety disorders, researchers and clinicians have advocated routine screening during the perinatal period (NRC, 2009). Although, there are several screening measures for depression, many of which have been used or validated in perinatal populations, few screening tools have been developed specifically for or validated in perinatal samples for bipolar disorder or anxiety disorders. Despite the ongoing need for brief, accurate, and easily administered screening measures, it seems clear that perinatal mood and anxiety screening is associated with substantial improvement in rate of detection (Georgiopoulous et al., 1999; Georgiopoulos, Bryan, Wollan, and Yawn, 2001; Gilbody, Sheldon, and House, 2008). However, in the absence of systematic protocols to ensure further assessment, treatment, and follow-up, screening is unlikely to have a positive impact on depression-associated morbidity (Gjerdingen, Katon, and Rich, 2008; Gilbody et al., 2008; Miller et al., 2012; NRC, 2009). Preliminary evidence suggests that screening for perinatal mood and anxiety disorders, when embedded within larger systems to ensure comprehensive assessment, connection to treatment, and regular monitoring, has the potential to improve outcomes for women and their families. The question of whether screening programs can ultimately decrease depression-associated morbidity and prevent adverse outcomes cannot be answered given the existing research base (Myers et al., 2013). Although much is left to be understood about perinatal screening for mood and anxiety disorders, the impact of this research lies in potential for reducing negative maternal outcomes as well as for prevention of the negative impact of perinatal depression on the health and well-being of babies born to depressed or anxious mothers.