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- Volume 14, 2018
Annual Review of Clinical Psychology - Volume 14, 2018
Volume 14, 2018
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Risk Factors for Depression: An Autobiographical Review
Vol. 14 (2018), pp. 1–28More LessI have been given a priceless opportunity to reflect on my career in the remarkably productive field of risk factors for depression. Psychological research on depression exploded in the early years of my work. I try to give an account of the choices and challenges, and reflect on the influences, some calculated and some serendipitous, that determined the paths I have followed. I focus mostly on the robust depression risk factors that have influenced my research, including dysfunctional cognitions, stressful life events and circumstances, parental depression, interpersonal dysfunction, and being female, and I cover some of what I did but also the influential work of others. This is a selective review of depression research in the past 40 or so years, noting some of the big developments that set the stage for the remarkable activity that continues today. In the conclusion, there is a brief statement of aspirations for future developments in our field.
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History of the Treatment of Female Sexual Dysfunction(s)
Vol. 14 (2018), pp. 29–54More LessThis article reviews the history of the treatment of women's sexual problems from the Victorian era to the twenty-first century. The contextual nature of determining what constitutes female sexual psychopathology is highlighted. Conceptions of normal sexuality are subject to cultural vagaries, making it difficult to identify female sexual dysfunctions. A survey of the inclusion, removal, and collapsing of women's sexual diagnoses in the Diagnostic and Statistical Manual of Mental Disorders from 1952 to 2013 illuminates the biases in the various editions. Masters and Johnson's models of sexual response and dysfunction paved the way for the diagnosis and treatment of women's sexual dysfunctions. Their sex therapy paradigm is described. Conceptions of and treatments for anorgasmia, arousal difficulties, vaginismus, dyspareunia, and low desire are reviewed. The medicalization of human sexuality and the splintering of sex therapy are discussed, along with current trends and new directions in sexual health care for women.
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Latent Growth and Dynamic Structural Equation Models
Kevin J. Grimm, and Nilam RamVol. 14 (2018), pp. 55–89More LessLatent growth models make up a class of methods to study within-person change—how it progresses, how it differs across individuals, what are its determinants, and what are its consequences. Latent growth methods have been applied in many domains to examine average and differential responses to interventions and treatments. In this review, we introduce the growth modeling approach to studying change by presenting different models of change and interpretations of their model parameters. We then apply these methods to examining sex differences in the development of binge drinking behavior through adolescence and into adulthood. Advances in growth modeling methods are then discussed and include inherently nonlinear growth models, derivative specification of growth models, and latent change score models to study stochastic change processes. We conclude with relevant design issues of longitudinal studies and considerations for the analysis of longitudinal data.
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Machine Learning Approaches for Clinical Psychology and Psychiatry
Vol. 14 (2018), pp. 91–118More LessMachine learning approaches for clinical psychology and psychiatry explicitly focus on learning statistical functions from multidimensional data sets to make generalizable predictions about individuals. The goal of this review is to provide an accessible understanding of why this approach is important for future practice given its potential to augment decisions associated with the diagnosis, prognosis, and treatment of people suffering from mental illness using clinical and biological data. To this end, the limitations of current statistical paradigms in mental health research are critiqued, and an introduction is provided to critical machine learning methods used in clinical studies. A selective literature review is then presented aiming to reinforce the usefulness of machine learning methods and provide evidence of their potential. In the context of promising initial results, the current limitations of machine learning approaches are addressed, and considerations for future clinical translation are outlined.
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Polygenic Risk Scores in Clinical Psychology: Bridging Genomic Risk to Individual Differences
Vol. 14 (2018), pp. 119–157More LessGenomewide association studies (GWASs) across psychiatric phenotypes have shown that common genetic variants generally confer risk with small effect sizes (odds ratio < 1.1) that additively contribute to polygenic risk. Summary statistics derived from large discovery GWASs can be used to generate polygenic risk scores (PRS) in independent, target data sets to examine correlates of polygenic disorder liability (e.g., does genetic liability to schizophrenia predict cognition?). The intuitive appeal and generalizability of PRS have led to their widespread use and new insights into mechanisms of polygenic liability. However, when currently applied across traits they account for small amounts of variance (<3%), are relatively uninformative for clinical treatment, and, in isolation, provide no insight into molecular mechanisms. Larger GWASs are needed to increase the precision of PRS, and novel approaches integrating various data sources (e.g., multitrait analysis of GWASs) may improve the utility of current PRS.
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Realizing the Mass Public Benefit of Evidence-Based Psychological Therapies: The IAPT Program
Vol. 14 (2018), pp. 159–183More LessEmpirically supported psychological therapies have been developed for many mental health conditions. However, in most countries only a small proportion of the public benefit from these advances. The English Improving Access to Psychological Therapies (IAPT) program aims to bridge the gap between research and practice by training over 10,500 new psychological therapists in empirically supported treatments and deploying them in new services for the treatment of depression and anxiety disorders. Currently IAPT treats over 560,000 patients per year, obtains clinical outcome data on 98.5% of these individuals, and places this information in the public domain. Around 50% of patients treated in IAPT services recover, and two-thirds show worthwhile benefits. The clinical and economic arguments on which IAPT is based are presented, along with details of the service model, how the program was implemented, and recent findings about service organization. Limitations and future directions are outlined.
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Lay Health Worker Involvement in Evidence-Based Treatment Delivery: A Conceptual Model to Address Disparities in Care
Vol. 14 (2018), pp. 185–208More LessMobilizing lay health workers (LHWs) to deliver evidence-based treatments (EBTs) is a workforce strategy to address mental health disparities in underserved communities. LHWs can be leveraged to support access to EBTs in a variety of ways, from conducting outreach for EBTs delivered by professional providers to serving as the primary treatment providers. This critical review provides an overview of how LHW-supported or -delivered EBTs have been leveraged in low-, middle-, and high-income countries (HICs). We propose a conceptual model for LHWs to address drivers of service disparities, which relate to the overall supply of the EBTs provided and the demand for these treatments. The review provides illustrative case examples that demonstrate how LHWs have been leveraged globally and domestically to increase access to mental health services. It also discusses challenges and recommendations regarding implementing LHW-supported or -delivered EBTs.
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Treatment Selection in Depression
Vol. 14 (2018), pp. 209–236More LessMental health researchers and clinicians have long sought answers to the question “What works for whom?” The goal of precision medicine is to provide evidence-based answers to this question. Treatment selection in depression aims to help each individual receive the treatment, among the available options, that is most likely to lead to a positive outcome for them. Although patient variables that are predictive of response to treatment have been identified, this knowledge has not yet translated into real-world treatment recommendations. The Personalized Advantage Index (PAI) and related approaches combine information obtained prior to the initiation of treatment into multivariable prediction models that can generate individualized predictions to help clinicians and patients select the right treatment. With increasing availability of advanced statistical modeling approaches, as well as novel predictive variables and big data, treatment selection models promise to contribute to improved outcomes in depression.
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Transforming the Treatment of Schizophrenia in the United States: The RAISE Initiative
Vol. 14 (2018), pp. 237–258More LessThe schizophrenia spectrum disorders are neurodevelopmental illnesses with a lifetime prevalence near 1%, producing extensive functional impairment and low expectations for recovery. Until recently, treatment in the United States has largely attempted to stabilize individuals with chronic schizophrenia. The identification and promotion of evidence-based practices for schizophrenia via the Patient Outcomes Research Team, combined with international studies supporting the value of early intervention, provided the foundation for the Recovery After an Initial Schizophrenia Episode (RAISE) project. The RAISE studies further supported the value of reducing the duration of untreated psychosis and providing a multi-element treatment called coordinated specialty care (CSC) to improve outcomes for patients in usual treatment settings. Although CSC programs have proliferated rapidly in the United States, many challenges remain in the treatment and recovery of individuals with schizophrenia in the aftermath of RAISE.
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Antisocial Personality as a Neurodevelopmental Disorder
Vol. 14 (2018), pp. 259–289More LessAlthough antisocial personality disorder (APD) is one of the most researched personality disorders, it is still surprisingly resistant to treatment. This lack of clinical progress may be partly due to the failure to view APD as a neurodevelopmental disorder and to consider early interventions. After first defining what constitutes a neurodevelopmental disorder, this review evaluates the extent to which APD meets neurodevelopmental criteria, covering structural and functional brain imaging, neurocognition, genetics and epigenetics, neurochemistry, and early health risk factors. Prevention and intervention strategies for APD are then outlined, focusing on addressing early biological and health systems, followed by forensic and clinical implications. It is argued both that APD meets criteria for consideration as a neurodevelopmental disorder and that consideration should be given both to the possibility that early onset conduct disorder is neurodevelopmental in nature, and also to the inclusion of psychopathy as a specifier in future Diagnostic and Statistical Manual revisions of APD.
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Attention Deficit Hyperactivity Disorder (ADHD): Controversy, Developmental Mechanisms, and Multiple Levels of Analysis
Vol. 14 (2018), pp. 291–316More LessControversy abounds regarding the symptom dimensions of attention problems, impulsivity, and hyperactivity, developmentally extreme and impairing levels of which compose the diagnostic category of attention deficit hyperactivity disorder (ADHD). I highlight causal factors, underlying mechanisms, developmental trajectories, and female manifestations of ADHD, integrating the psychobiological underpinnings of this syndrome with contextual factors related to its clinical presentation, impairments, and soaring increases in diagnosed prevalence. Indeed, despite strong heritability, ADHD is expressed via transactional patterns of influence linked to family-, school-, peer-, neighborhood-, and policy-related factors. Moreover, intervention strategies must take into account both pharmacologic and behavioral modalities if the goal is to enhance competencies, rather than symptom reduction per se. A comprehensive understanding of ADHD mandates multiple levels of analysis—spanning genes, neurotransmission, brain pathways, individual skill levels, family socialization, peer relationships, and educational and cultural forces—which must be integrated and synthesized to surpass reductionist accounts, reduce stigma, and maximize the impact of prevention- and intervention-related efforts.
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Conduct Disorder and Neighborhood Effects
Vol. 14 (2018), pp. 317–341More LessThere has been a considerable amount of scholarly attention to the relationship between neighborhood effects and conduct disorder, particularly in recent years. Having said this, it has been nearly two decades since a comprehensive synthesis of this literature has been conducted. Relying on a detailed and comprehensive search strategy and inclusion criteria, this article offers a systematic and interdisciplinary review of 47 empirical studies that have examined neighborhood effects and conduct disorder. Described results suggest that there are generally robust linkages between adverse neighborhood factors and conduct disorder and externalizing behavior problems, as 67 of the 93 (72.04%) effect sizes derived from these studies yielded statistically significant neighborhood effects. The review also identifies salient mediating and moderating influences. It discusses study limitations and directions for future research as well.
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Culture's Influence on Stressors, Parental Socialization, and Developmental Processes in the Mental Health of Children of Immigrants
Vol. 14 (2018), pp. 343–370More LessChildren of immigrants represent one in four children in the United States and will represent one in three children by 2050. Children of Asian and Latino immigrants together represent the majority of children of immigrants in the United States. Children of immigrants may be immigrants themselves, or they may have been born in the United States to foreign-born parents; their status may be legal or undocumented. We review transcultural and culture-specific factors that influence the various ways in which stressors are experienced; we also discuss the ways in which parental socialization and developmental processes function as risk factors or protective factors in their influence on the mental health of children of immigrants. Children of immigrants with elevated risk for mental health problems are more likely to be undocumented immigrants, refugees, or unaccompanied minors. We describe interventions and policies that show promise for reducing mental health problems among children of immigrants in the United States.
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Stress, Telomeres, and Psychopathology: Toward a Deeper Understanding of a Triad of Early Aging
Vol. 14 (2018), pp. 371–397More LessTelomeres play an important part in aging and show relationships to lifetime adversity, particularly childhood adversity. Meta-analyses demonstrate reliable associations between psychopathology (primarily depression) and shorter telomere length, but the nature of this relationship has not been fully understood. Here, we review and evaluate the evidence for impaired telomere biology as a consequence of psychopathology or as a contributing factor, and the important mediating roles of chronic psychological stress and impaired allostasis. There is evidence for a triadic relationship among stress, telomere shortening, and psychiatric disorders that is positively reinforcing and unfolds across the life course and, possibly, across generations. We review the role of genetics and biobehavioral responses that may contribute to shorter telomere length, as well as the neurobiological impact of impaired levels of telomerase. These complex interrelationships are important to elucidate because they have implications for mental and physical comorbidity and, potentially, for the prevention and treatment of depression.
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Behavioral Addictions as Mental Disorders: To Be or Not To Be?
Vol. 14 (2018), pp. 399–423More LessShould excessive and problematic engagement in nonsubstance use behaviors be mental disorders? The fifth edition of the Diagnostic and Statistical Manual of Mental Disorders (DSM-5) repositioned gambling disorder in the substance use disorders section and introduced Internet gaming disorder in the research appendix; the International Classification of Diseases (ICD-11) is also considering it. This article outlines pros and cons of considering behavioral addictions as mental disorders and also reviews the DSM-5 decision-making processes. It focuses on three conditions: gambling disorder, Internet gaming disorder (IGD), and Internet addiction (IA). We detail assessment methods and prevalence rates for these conditions and outline psychiatric comorbidities, demographic and biological risk factors, and promising treatment approaches. We also briefly discuss other putative behavioral addictions: eating/food, sex, exercise, shopping, and tanning “addictions.” Overall, data are inconclusive, and consistent terminology and methodology are needed to define and evaluate these conditions more fully prior to considering them mental disorders.
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Cognitive Effects of Cancer and Cancer Treatments
Vol. 14 (2018), pp. 425–451More LessAs the population of cancer survivors has grown into the millions, there has been increasing emphasis on understanding how the late effects of treatment affect survivors’ ability to return to work/school, their capacity to function and live independently, and their overall quality of life. This review focuses on cognitive change associated with cancer and cancer treatments. Research in this area has progressed from a pharmacotoxicology perspective to a view of the cognitive change as a complex interaction of aspects of the treatment, vulnerability factors that increase risk for posttreatment cognitive decline, cancer biology, and the biology of aging. Methodological advances include the development of (a) measurement approaches that assess more fine-grained subcomponents of cognition based on cognitive neuroscience and (b) advanced statistical approaches. Conceptual issues that arise from this multidimensional perspective are described in relation to future directions, understanding of mechanisms, and development of innovative interventions.
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Social Security and Disability Due to Mental Impairment in Adults
Vol. 14 (2018), pp. 453–469More LessThe Social Security Administration (SSA) oversees two disability programs, Social Security Disability Insurance (SSDI) and Supplemental Security Income (SSI). Adults with mental impairments represent a very large component of the programs. Policy makers and SSA are concerned about the accuracy of disability determination and also about low levels of labor force participation among individuals with disabilities. Adults with mental impairments are challenging to assess for work-related functional limitations. They are also a challenge to return to labor force participation. SSA has sponsored several demonstration research programs focusing on improving the accuracy of disability determination and on interventions in supported employment to return individuals with mental impairments to competitive employment. This article reviews the demonstration research focused on both entry into the disability system (at the “front door”) and potential exit from it (through the “back door”). All of the research holds promise to “right-size” the SSA disability program.
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Evolutionary Perspectives on Genetic and Environmental Risk Factors for Psychiatric Disorders
Vol. 14 (2018), pp. 471–493More LessEvolutionary medicine uses evolutionary theory to help elucidate why humans are vulnerable to disease and disorders. I discuss two different types of evolutionary explanations that have been used to help understand human psychiatric disorders. First, a consistent finding is that psychiatric disorders are moderately to highly heritable, and many, such as schizophrenia, are also highly disabling and appear to decrease Darwinian fitness. Models used in evolutionary genetics to understand why genetic variation exists in fitness-related traits can be used to understand why risk alleles for psychiatric disorders persist in the population. The usual explanation for species-typical adaptations—natural selection—is less useful for understanding individual differences in genetic risk to disorders. Rather, two other types of models, mutation-selection-drift and balancing selection, offer frameworks for understanding why genetic variation in risk to psychiatric (and other) disorders exists, and each makes predictions that are now testable using whole-genome data. Second, species-typical capacities to mount reactions to negative events are likely to have been crafted by natural selection to minimize fitness loss. The pain reaction to tissue damage is almost certainly such an example, but it has been argued that the capacity to experience depressive symptoms such as sadness, anhedonia, crying, and fatigue in the face of adverse life situations may have been crafted by natural selection as well. I review the rationale and strength of evidence for this hypothesis. Evolutionary hypotheses of psychiatric disorders are important not only for offering explanations for why psychiatric disorders exist, but also for generating new, testable hypotheses and understanding how best to design studies and analyze data.
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Previous Volumes
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Volume 19 (2023)
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Volume 18 (2022)
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Volume 17 (2021)
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Volume 16 (2020)
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Volume 15 (2019)
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Volume 14 (2018)
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Volume 13 (2017)
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Volume 12 (2016)
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Volume 11 (2015)
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Volume 10 (2014)
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Volume 9 (2013)
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Volume 8 (2012)
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Volume 7 (2011)
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Volume 6 (2010)
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Volume 5 (2009)
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Volume 4 (2008)
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Volume 3 (2007)
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Volume 2 (2006)
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Volume 1 (2005)
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Volume 0 (1932)