Randall T. Salekin, Matthew A. Jarrett, and Elizabeth W. Adams
This chapter focuses on a range of measurement issues including traditional test development procedures and model testing. Themes of the chapter include the importance of integrating research disciplines and nosologies with regard to test development, the need for test development and measurement in the context of idiographic and nomothetic treatment designs, the need for change sensitive measures, and the possible integration of both idiographic and nomothetic treatment designs. Finally, the chapter emphasizes the importance of exploring novel areas of measurement (e.g., biological functioning, contextual factors) using emerging technologies. It is thought that innovative test development and use will lead to improved intervention model testing.
Frederick T. L. Leong and Zornitsa Kalibatseva
The increasing population of racial and ethnic minorities calls for more attention to cultural diversity in clinical research. This chapter starts with a definition of culture and a brief discussion of the two parallel approaches to culture within psychology, cross-cultural psychology and racial and ethnic minority psychology. Subsequently, the chapter reviews cross-cultural issues in clinical research along two dimensions, namely the methodological strategies used to undertake clinical research and the methodological challenges encountered in clinical research. The reviewed methodological strategies include clinical case studies, analogue and simulation studies, randomized clinical trials, archival research and secondary data analysis, culture-specific approaches to treatment research, and meta-analysis. Lastly, the chapter discusses five methodological challenges for clinical research with culturally diverse populations, such as sample selection, measurement equivalence, race and ethnicity as demographic versus psychological variables, confounds and intersectionality, and differential research infrastructure.
Jill A. Stoddard, Christopher Barmann, Eric Lenze, and Julie L. Wetherell
By the year 2050, the number of adults over the age of 60 will reach an estimated two billion, representing the fastest-growing segment of the population. Although anxiety and mood disorders are common among older adults, consensus is lacking as to the most appropriate treatments. In an effort to optimize treatment strategies for older adults, this chapter focuses on a thorough review of outcome literature investigating the use of pharmacotherapy and psychotherapy within three treatment domains: combination, sequential, and augmentation. The preponderance of evidence has lent support to the notion that combining psychosocial and medical treatments results in better outcomes for older adults with anxiety and mood disorders. However, there is a clear need for additional randomized, controlled trials further investigating optimal treatment strategies addressing mental health in late life.
Colleen Jacobson and Kristen Batejan
During the past several years, interest in nonsuicidal self-injury (NSSI) has grown considerably, thus sparking increased theorizing and research into the etiological roots of this perplexing yet relatively common behavior. The current chapter provides an overview of the main theoretical explanations for NSSI, with a more detailed description of those with an adequate amount of empirical support. While the majority of the theories (e.g., psychodynamic, interpersonal, affect regulation, cognitive, biological) have received at least some empirical support, the affect regulation and interpersonally based theories seem to have the largest amount of empirical grounding. Specifically, research indicates that the majority of people who self-injure do so to relieve unwanted negative feelings, while a large minority also engages in NSSI in order to elicit an interpersonal response. Highlighting the need for a comprehensive model of NSSI, this chapter concludes with the presentation of an integrated theory of the etiology of NSSI, which incorporates various distal and proximal risk factors.
Philip C. Kendall and Jonathan S. Comer
Acknowledging the nascent stage of the collaboration between science and clinical psychology, this chapter discusses features of the preferred approach to guide the accumulation of knowledge through careful implementation and evaluation. The collaboration of science and practice in clinical psychology has produced meaningful, reliable, and replicated findings, and illustrations (e.g., exposure for anxiety, cognitive-behavioral therapy for depression and panic) are identified. Speculations regarding the future of our field and a model for optimal science—practice collaborations in clinical psychology are offered.
Bryce D. McLeod, Nadia Islam, and Emily Wheat
Therapy process research investigates what happens in therapy sessions and how these interactions influence outcomes. Therapy process research employs an array of methodologies but has recently used clinical trials as a platform for investigating process—outcome relations. This chapter serves as a resource for performing and interpreting therapy process research conducted within clinical trials. Issues related to designing, conducting, and evaluating therapy process research are reviewed, with examples drawn from the child therapy literature to illustrate key concepts. The chapter concludes with suggested future research directions.
Rinad S. Beidas, Tara G. Mehta, Marc Atkins, Bonnie Solomon, and Jenna Merz
Dissemination and implementation (DI) science has grown exponentially in the past decade. This chapter reviews and discusses the research methodology pertinent to empirical DI inquiry within mental health services research. This chapter (a) reviews models of DI science, (b) presents and discusses design, variables, and measures relevant to DI processes, and (c) offers recommendations for future research.
Gerald P. Koocher
Clinical research requires careful attention to ethical principles from the design of the project, through data collection, and extending on to the data analysis and publication of results. Each of these stages requires attention to different issues in order to fully inform, respect, and protect research participants. In addition, special attention must focus on the integrity of the research enterprise and our relationships with co-investigators, assistants, and students. New technologies and new professional skills will offer increased opportunity, but will also require that we confront new challenges
David P. MacKinnon, Ginger Lockhart, Amanda N. Baraldi, and Lois A. Gelfand
This chapter outlines methods for identifying the mediating mechanisms by which treatments achieve effects and moderators of these effects. Mediating variables are variables that transmit a treatment effect to an outcome variable. Moderating variables are variables that identify the subgroups, conditions, or factors for which the treatment effect on the outcome differs. Reasons for conducting mediation and moderation analyses in treatment research are provided along with simple examples of mediation and moderation models. More detailed mediation models are described that incorporate multiple mediators, longitudinal measurement, experimental designs, and alternative approaches to causal inference for mediation. A research design for an exemplar treatment study that includes investigation of mediating and moderating processes is described. However, we acknowledge that the search for mediating and moderating variables in treatment research must be a multifaceted approach that includes information from a variety of sources in addition to ideal experimental design and careful measurement of constructs. The chapter concludes with future directions in mediation and moderation methodology in treatment research.
John Hunsley and Eric J. Mash
Evidence-based assessment relies on research and theory to inform the selection of constructs to be assessed for a specific assessment purpose, the methods and measures to be used in the assessment, and the manner in which the assessment process unfolds. An evidence-based approach to clinical assessment necessitates the recognition that, even when evidence-based instruments are used, the assessment process is a decision-making task in which hypotheses must be iteratively formulated and tested. In this chapter, we review (a) the progress that has been made in developing an evidence-based approach to clinical assessment in the past decade and (b) the many challenges that lie ahead if clinical assessment is to be truly evidence-based.
Philip S. Santangelo, Ulrich W. Ebner-Priemer, and Timothy J. Trull
The Experience Sampling Method (ESM) can improve our understanding of how psychopathological symptoms unfold over time in everyday life. We discuss major benefits of ESM by presenting selected studies involving (a) real-time assessment (i.e., assessments focusing on individuals' momentary states, experiences, or behaviors); (b) real-world assessments enhancing laboratory-to-life generalizability; (c) multiple assessments over time allowing the study of dynamic processes; (d) multimodal assessment integrating psychological, physiological, and behavioral data; (e) assessment of setting or context specificities allowing for context-sensitive analyses; and (f) the provision of immediate interactive feedback. Furthermore, we offer recommendations concerning design issues for ESM studies, namely with regard to (a) choosing a sampling strategy, (b) participants' burden, compliance, and reactivity, (c) hardware and software solutions, (d) mathematical procedures when analyzing ESM data, and (e) visualization of ESM data. Regardless of remaining challenges, ESM offers great potential in clinical psychology with its possible application as a therapeutic tool and by revealing a comprehensive and generalizable picture of patients' and research participants' symptomatology.
M. Robin DiMatteo, Tricia A. Miller, and Leslie R. Martin
This essay examines issues relevant to the accurate assessment of patient adherence to recommendations for health behavior change and/or the management of medical conditions, including long-term chronic diseases. Both conceptual and methodological issues are discussed. The importance of accurate assessment in both clinical practice and research is examined, as well as the consequences of conceptual and measurement biases. The role of assessments of current adherence in predicting future behavior is examined, as is the essential distinction between assessing adherence as a behavior and assessing the predictors and consequences of adherence. The potential challenges of various approaches to assessing adherence accurately are examined, focusing particularly on self-report; measurement scales for adherence are presented; and innovative techniques are discussed for assessing adherence using technologically based formats. Effective communication is emphasized as the most important and salient element relevant to adherence assessment, linking patient adherence assessment with effective communication in the clinical setting.
Naomi Koerner, Heather K. Hood, and Martin M. Antony
The main objective of this chapter is to provide an overview of clinical interviewing. Although clinical interviewing is often referred to as an art (Shea, 2007), the information in this chapter highlights the science of clinical interviewing as well. The chapter opens with a discussion of the general structure and content of clinical interviews that are typically conducted in mental health contexts. The reader is introduced to a variety of interviews that are used in the assessment of Axis I and Axis II conditions, including their psychometric properties; guidelines for the assessment of suicidality are also presented. This is followed by an overview of interviewing skills. Specifically discussed are ways in which information processing limitations, verbal and nonverbal cues, and style of questions can influence the clinical interview. We then turn to a discussion of case formulation, a core component of the clinical interview. Empirical research on the impact of training on quality of case conceptualization and on the association between case formulation and treatment outcome is summarized. The chapter closes with a brief overview of issues that may arise when interviewing certain populations, in particular, couples, individuals from diverse populations, and young individuals.
Multivariate multilevel survival analysis is introduced for studying hazard rates of observed emotional behavior relevant for coercion theory. Finite time sampling reliability (FTSR) and short-term retest reliability (STRR) across two occasions (sessions) of observation during structured problem-solving tasks several weeks apart were determined for hazard rates of emotional behaviors for parent–child dyads. While FTSR was high (.80–.96), STRR was low (.16–.65), suggesting that emotional behaviors in the context of parent–child social interaction are not very stable over a period of several weeks. Using latent variable structural equation models that corrected for the low STRR, two hazard rates were predictive of change in child antisocial behavior over a 3-year period (kindergarten to third grade) net of initial child antisocial behavior. Low levels of parent positive emotion and increases from session 1 to 2 of child neutral behavior both accounted for unique variance in third grade antisocial behavior.
Lynne Steinberg and David Thissen
Item response theory (IRT) comprises a collection of mathematical and statistical models and methods that are used in the assembly and scoring of psychological questionnaires and scales. IRT is used to investigate the statistical properties of categorical responses to questions, or other observations that may be indicators on a test or scale. IRT models are used for item analysis and scoring for items with dichotomous or polytomous responses. Statistical analysis using IRT summarizes the degree of endorsement or severity of each response, the strength of the relation between the item response and the underlying construct, and the degree to which a collection of questions or other indicators measure one coherent construct, or more than one. IRT is also used to investigate the degree to which item responses exhibit differential item functioning, or a lack of desired invariance, over groups. Finally, IRT is used to compute scale scores that are comparable across alternate forms of a questionnaire, and that may have better statistical properties than more traditional summed scores. This chapter illustrates these ideas with empirical examples.
Michael J. Zvolensky, John P. Forsyth, and Kirsten Johnson
Experimental psychopathology represents a subfield of psychological science aimed at elucidating the processes underlying abnormal behavior. The present chapter provides a synopsis of key elements of experimental psychopathology research and its methods. In the first section, we define experimental psychopathology research and briefly articulate its origins. Second, we present the methodological approaches employed in experimental psychopathology research. Third, we present some of the molar conceptual considerations for the assessment approaches in experimental psychopathology research. In the final section, we describe some key challenges to experimental psychopathology research as well as potentially useful strategies recommended for overcoming such challenges.
Andy P. Field
Meta-analysis is now the method of choice for assimilating research investigating the same question. This chapter is a nontechnical overview of the process of conducting meta-analysis in the context of clinical psychology. We begin with an overview of what meta-analysis aims to achieve. The process of conducting a meta-analysis is then described in six stages: (1) how to do a literature search; (2) how to decide which studies to include in the analysis (inclusion criteria); (3) how to calculate effect sizes for each study; (4) running a basic meta-analysis using the metaphor package for the free software R; (5) how to look for publication bias and moderators of effect sizes; and (6) how to write up the results for publication.
Patrick E. McKnight and Katherine M. McKnight
The inevitability and importance of missing data ought to move researchers to prevent, treat, and report the condition. Unfortunately, despite great advances in the field, researchers tend to ignore missing data. We hypothesize that ignoring missing data stems from low interest, unavailable solutions, and higher priorities by most social scientists. Thus, we aimed to remedy those potential mechanisms by providing a clear demonstration of missing-data handling in three distinct data analysis scenarios (psychometric, longitudinal, and covariance models) using R. Each of these exemplar procedures comes with code and data allowing readers to replicate and extend our examples to their own data. By demonstrating the use of missing-data—handling techniques in a freely available statistical package (R), we hope to increase available options and reduce the researcher's burden for handling missing data in common social science data analytic scenarios.
Stephen G. West, Leona S. Aiken, Heining Cham, and Yu Liu
This chapter presents a broad overview of multiple regression (MR), psychology's data analytic workhorse. MR is a statistical method for investigating the relationship between categorical, quantitative, or both types of independent variables and a single dependent variable. An initial literature review documents the broad use of MR in leading journals in clinical psychology. The chapter then provides an understanding of the fundamentals of simple linear regression models, followed by more complex models involving nonlinear effects and interactions. The chapter presents solutions to several potential problems that arise in MR, including missing data, data collected from groups (multilevel modeling), data collected from individuals over time (growth curve models, generalized estimating equations), and noncontinuous dependent variables including binary outcomes, unordered or ordered categories, and counts (generalized linear model). Throughout, the chapter offers advice for clinical researchers on problems that commonly arise in conducting and interpreting MR analyses.
Music therapy is an evidence-based profession. Music therapy research aims to provide information about outcomes that support music therapy practice including contributing to theoretical perspectives that can explain why changes occur during treatment. Music therapy research has been conducted in a range of health, education, and community contexts throughout the world. Initially many music therapy developments in the university sector occurred through the establishment of training programmes that were developed and delivered by music therapists with professional experience in leading services in education and health care. Now many music therapy training programmes are led by people with practice experience along with research qualifications, and some universities offer music therapy doctoral pathways. Music therapy research capacity has expanded through a notable increase in PhD graduates as well as an increase in funded research in music therapy. This chapter covers: (1) traditions, (2) trends, and (3) contexts for music therapy research.