Annual Review of Clinical Psychology

Neuropsychiatric disorders are associated with abnormal function of the default mode network (DMN), a distributed network of brain regions more active during rest than during performance of many attention-demanding tasks and characterized by a high degree of functional connectivity (i.e., temporal correlations between brain regions). Functional magnetic resonance imaging studies have revealed that the DMN in the healthy brain is associated with stimulus-independent thought and self-reflection and that greater suppression of the DMN is associated with better performance on attention-demanding tasks. In schizophrenia and depression, the DMN is often found to be hyperactivated and hyperconnected. In schizophrenia this may relate to overly intensive self-reference and impairments in attention and working memory. In depression, DMN hyperactivity may be related to negative rumination. These findings are considered in terms of what is known about psychological functions supported by the DMN, and alteration of the DMN in other neuropsychiatric disorders.

Humans have an intrinsic need for social connection; thus, it is crucial to understand depression in an interpersonal context. Interpersonal theories of depression posit that depressed individuals tend to interact with others in a way that elicits rejection, which increases their risk for future depression. In this review, we summarize the interpersonal characteristics, risk factors, and consequences of depression in the context of the relevant theories that address the role of interpersonal processes in the onset, maintenance, and chronicity of depression. Topics reviewed include social skills, behavioral features, communication behaviors, interpersonal feedback seeking, and interpersonal styles as they relate to depression. Treatment implications are discussed in light of the current research on interpersonal processes in depression, and the following future directions are discussed: developing integrative models of depression, improving measurement of interpersonal constructs, examining the association between interpersonal processes in depression and suicide, and tailoring interventions to target interpersonal processes in depression.

Trong các phương pháp tiếp cận mạng về tâm thần học, các rối loạn phát sinh từ sự tương tác nguyên nhân giữa các triệu chứng (ví dụ, lo âu → mất ngủ → mệt mỏi), có thể liên quan đến các vòng phản hồi (ví dụ, một người có thể lạm dụng chất kích thích để quên đi những vấn đề phát sinh do lạm dụng chất này). Bài đánh giá hiện tại xem xét các phương pháp phù hợp để xác định các mạng triệu chứng và thảo luận về các kỹ thuật phân tích mạng có thể được sử dụng để trích xuất thông tin có giá trị lâm sàng và khoa học từ các mạng đó (ví dụ, triệu chứng nào là trung tâm nhất trong mạng lưới của một người). Các tác giả cũng chỉ ra cách các kỹ thuật phân tích mạng có thể được sử dụng để xây dựng các mô hình mô phỏng bắt chước động lực triệu chứng. Các phương pháp tiếp cận mạng giải thích một cách tự nhiên sự thành công hạn chế của các chiến lược nghiên cứu truyền thống, vốn thường dựa trên ý tưởng rằng các triệu chứng là biểu hiện của một yếu tố chung tiềm ẩn nào đó, đồng thời cung cấp các phương pháp thay thế hứa hẹn. Thêm vào đó, các kỹ thuật này có thể mở ra khả năng hướng dẫn và đánh giá các can thiệp điều trị.

This article reviews the interactions of estrogen changes and psychosocial stress in contributing to vulnerability to major depressive disorder (MDD) in women. Estrogen modulates brain networks and processes related to changes in stress response, cognition, and emotional dysregulation that are core characteristics of MDD. Synergistic effects of estrogen on cognitive and emotional function, particularly during psychosocial stress, may underlie the association of ovarian hormone fluctuation and depression in women. We propose a model of estrogen effects on multiple brain systems that interface with stress-related emotional and cognitive processes implicated in MDD and discuss possible mechanisms through which reproductive events and changes in estrogen may contribute to MDD risk in women with other concurrent risk factors.

Crowdsourcing has had a dramatic impact on the speed and scale at which scientific research can be conducted. Clinical scientists have particularly benefited from readily available research study participants and streamlined recruiting and payment systems afforded by Amazon Mechanical Turk (MTurk), a popular labor market for crowdsourcing workers. MTurk has been used in this capacity for more than five years. The popularity and novelty of the platform have spurred numerous methodological investigations, making it the most studied nonprobability sample available to researchers. This article summarizes what is known about MTurk sample composition and data quality with an emphasis on findings relevant to clinical psychological research. It then addresses methodological issues with using MTurk—many of which are common to other nonprobability samples but unfamiliar to clinical science researchers—and suggests concrete steps to avoid these issues or minimize their impact.

Today's lesbian, gay, bisexual, and transgender (LGBT) youth come out at younger ages, and public support for LGBT issues has dramatically increased, so why do LGBT youth continue to be at high risk for compromised mental health? We provide an overview of the contemporary context for LGBT youth, followed by a review of current science on LGBT youth mental health. Research in the past decade has identified risk and protective factors for mental health, which point to promising directions for prevention, intervention, and treatment. Legal and policy successes have set the stage for advances in programs and practices that may foster LGBT youth mental health. Implications for clinical care are discussed, and important areas for new research and practice are identified.

The fifth revision of the Diagnostic and Statistical Manual of Mental Disorders (DSM-5) was the most controversial in the manual's history. This review selectively surveys some of the most important changes in DSM-5, including structural/organizational changes, modifications of diagnostic criteria, and newly introduced categories. It analyzes why these changes led to such heated controversies, which included objections to the revision's process, its goals, and the content of altered criteria and new categories. The central focus is on disputes concerning the false positives problem of setting a valid boundary between disorder and normal variation. Finally, this review highlights key problems and issues that currently remain unresolved and need to be addressed in the future, including systematically identifying false positive weaknesses in criteria, distinguishing risk from disorder, including context in diagnostic criteria, clarifying how to handle fuzzy boundaries, and improving the guidelines for “other specified” diagnosis.

Schizophrenia is often referred to as one of the most severe mental disorders, primarily because of the very high mortality rates of those with the disorder. This article reviews the literature on excess early mortality in persons with schizophrenia and suggests reasons for the high mortality as well as possible ways to reduce it. Persons with schizophrenia have an exceptionally short life expectancy. High mortality is found in all age groups, resulting in a life expectancy of approximately 20 years below that of the general population. Evidence suggests that persons with schizophrenia may not have seen the same improvement in life expectancy as the general population during the past decades. Thus, the mortality gap not only persists but may actually have increased. The most urgent research agenda concerns primary candidates for modifiable risk factors contributing to this excess mortality, i.e., side effects of treatment and lifestyle factors, as well as sufficient prevention and treatment of physical comorbidity.

The use of repeated, momentary, real-world assessment methods known as the Experience Sampling Method and Ecological Momentary Assessment (EMA) has been broadly embraced over the last few decades. These methods have extended our assessment reach beyond lengthy retrospective self-reports as they can capture everyday experiences in their immediate context, including affect, behavior, symptoms, and cognitions. In this review we evaluate nine conceptual, methodological, and psychometric issues about EMA with the goal of stimulating conversation and guiding future research on these matters: the extent to which participants are actually reporting momentary experiences, respondents’ interpretation of momentary questions, the use of comparison standards in responding, efforts to increase the EMA reporting period beyond the moment to longer periods within a day, training of EMA study participants, concerns about selection bias of respondents, the impact of missing EMA assessments, the reliability of momentary data, and for which purposes EMA might be considered a gold standard for assessment. Resolution of these issues should have far-reaching implications for advancing the field.

Group-based trajectory models are increasingly being applied in clinical research to map the developmental course of symptoms and assess heterogeneity in response to clinical interventions. In this review, we provide a nontechnical overview of group-based trajectory and growth mixture modeling alongside a sampling of how these models have been applied in clinical research. We discuss the challenges associated with the application of both types of group-based models and propose a set of preliminary guidelines for applied researchers to follow when reporting model results. Future directions in group-based modeling applications are discussed, including the use of trajectory models to facilitate causal inference when random assignment to treatment condition is not possible.