Clinical Psychological Science最新文献

The ability to make valid conclusions in psychological science rests upon rigorous measure development. People with lived experience of psychological disorders can make invaluable contributions to the measure development process, but they are often excluded from this process by researchers. When people with lived experience are included, their contributions are limited to consultation early in the process. This review advocates for shared decision-making with people with lived experience throughout the measure development process. We provide an overview of the phases and steps involved in the development of self-report measures, highlighting the critical contributions of people with lived experience at each step. Next, guided by the continuum of community engagement in research, we review studies from the psychological science literature that embrace community-engaged measure development approaches inclusive of people with lived experience of psychological disorders. We conclude with a discussion of opportunities and challenges to community-engaged measure development in psychological science.

Since 2022, following the Dobbs decision by the United States Supreme Court, abortion restrictions have increased throughout the country. This represents the most recent phase of decades of political and legal restrictions on abortion access, including the 1976 Hyde Amendment restricting federal funds for abortion services. Limiting access to legal abortion and safe reproductive healthcare has serious implications for the mental health of people who can become pregnant, and thus for clinical psychology. However, there are gaps in competence around sexual and reproductive health (SRH) for clinical psychologists in research and practice. In this paper, we 1) review empirical evidence regarding abortion and mental health, 2) discuss barriers to SRH competence for clinical psychology, and 3) present guiding principles for psychologists and institutions/training programs to address these competence gaps across research, clinical practice, and advocacy. We focus on clinical psychology, but the content is applicable to behavioral health disciplines broadly.

Patterns of alcohol consumption can spread from one person to the next in social networks. Yet the necessary conditions required for this social influence to occur are not clearly defined. Here we leverage the sudden and seismic shift in social life following COVID-19, a natural phenomenon that divorced social relationships from the contexts those relationships typically inhabit. Using a social network-based clustered longitudinal design, we examined alcohol use patterns among cohorts of heavy drinking friendship dyads and triads (N=314) traced longitudinally pre- and post-pandemic. In line with hypotheses, results indicated a disruptive effect of COVID-era on social influence effects-while friendships endured, longitudinal links between friends' and participants' problem drinking diminished significantly with COVID-19. In contrast to these inter-individual effects, intra-individual (i.e., autoregressive) links between participants' past and present drinking remained intact. Results inform the understanding of mechanisms undergirding social influence effects, pointing to a potential role for context.

Negative cognitive style and rumination are prominent cognitive vulnerabilities (CVs) that contribute to development of psychopathology, especially internalizing problems. Yet, little is known about trajectories of CVs across development (age) and gender and what predicts CVs. This study characterized CV trajectories from ages 9-18 and investigated predictors of CV trajectories. Community youth (N=607; M _age=12.37; 55% girls) completed repeated assessments of CVs across three years; youth and parents were assessed for many CV predictors at baseline. Measurement invariance supported partial scalar for CVs across age and scalar invariance by gender. Quadratic age characterized rumination trajectories (decrease ages 9-12; increase ages 13-18); girls ruminated more than boys. Negative cognitive style showed no significant gender or age effects. Most baseline predictors (observed parental positive affect; youth temperament, personality disorder traits, coping, emotion regulation, internalizing symptoms, MDD history, and negative environmental contexts) predicted CV trajectories. Implications for theory and clinical application are discussed.

Young adults typically drink socially, yet most lab studies testing alcohol responses have administered alcohol in isolation. This is the first study to examine alcohol responses and social reward in a group setting among a young adult at-risk sample. Heavy drinking young adults (N=393; 50% female) were grouped in threes and drank a moderate dose of alcohol or a placebo. These social interactions were recorded, and the duration and sequence of facial expressions, speech, and laughter were coded. Results revealed a comprehensive, multimodal, positive effect of alcohol on socioemotional experiences across self-report (e.g., increased positive affect and social bonding, greater relief of unpleasant feelings) and behavioral outcomes at both the individual- (e.g., more rapid increases in Duchenne smiling) and group-levels (e.g., more three-way conversations). Findings underscore the potential for group-formation paradigms to yield valuable data regarding etiological mechanisms underlying alcohol use disorder. All data and code are available (https://osf.io/3q42z/).

In this article, we assessed the performance of several predictive modeling algorithms of suicide attempt resulting in inpatient hospitalization or suicide among youths ages 9 to 18 (N = 34,528) after contact (6-12 months) with a mental-health specialist in Stockholm, Sweden, from 2006 to 2012. Using 209 predictors across domains (e.g., clinical, demographic, family, neighborhood, social) identified from national registers, we applied standard logistic regression, regularized logistic regression, and machine-learning algorithms (i.e., random forests, gradient boosting, support vector machines). Standard logistic regression (area under the receiver operating characteristic curve [AUC] = 0.77, 95% confidence interval [CI] = [0.72, 0.82]) and random-forest models (AUC = 0.80, 95% CI = [0.74, 0.86]) demonstrated the highest AUCs. Sensitivities ranged from 0.33 (support vector machines) to 0.91 (standard logistic regression). Although the study was underpowered to detect a difference between logistic regression and machinelearning algorithms (outcome prevalence = 0.7%), performance metrics were similar across models. Logistic regression is not clearly worse than machine-learning approaches. Ongoing research is needed to examine how prediction models can augment clinical decision-making.

In this study, we investigate using passive data, specifically, heart rate and actigraphy, for individuals with binge-type eating disorders such as bulimia nervosa (BN) and binge-eating disorder (BED). By applying dynamical-system theory and incorporating advancements in technology-based health care, we explored the relationship between passive data patterns as potential indicators of binge-eating episodes. Over 30 days, 1,019 participants with BN or BED symptoms used the Recovery Record app on iPhone and Apple Watches for real-time eating-behavior logging. Apple Watches simultaneously recorded heart rate and actigraphy. Results show no marked difference in heart and step averages 2 hr before a binge versus a control period. However, significant momentum and stability differences emerged when examining the changing dynamics leading up to a binge event. These findings suggest that the stability of step, rather than their average value, may serve as a detectable indicator of approaching binge events.

Although obsessive-compulsive disorder (OCD) features maladaptive decision making, previous research examining economic decision making in OCD has yielded inconsistent results. Here we examined whether unmedicated adults with OCD (n = 268) differ from healthy controls (HC; n = 256) on two measures of decision making about potential rewards: 1) delay discounting, the tendency to prefer rewards sooner rather than later, even if the delayed reward is larger, and 2) risk tolerance, the willingness to gamble for uncertain rewards when the risk is known. Data were collected in Brazil, India, the Netherlands, South Africa, and the USA as part of the Global OCD study. After controlling for age, sex, education, socioeconomic status, IQ, and site, individuals with OCD did not differ from HC in either delay discounting or risk tolerance. However, patients with OCD who reported more anxiety and depression showed higher delay discounting, or a relative preference for immediate rewards.

The pathoplasty model posits that personality influences the manifestation of psychopathology, but has rarely tested the influence on the symptomatic expression of depression. We tested pathoplastic effects of personality on depressive symptoms in five cross-sectional samples varying in age, specific measures of personality, and specific measures of depression. Tests of pathoplastic effects were conducted using moderated non-linear factor analysis. Across samples, we found little evidence for pathoplastic effects of personality on depressive symptoms. We found minimal evidence that personality is associated with the structure of the depression construct (i.e., loadings to indicators). Lower levels of positive emotionality were associated with greater likelihood of endorsing sleep problems, beyond the influence of overall depression severity, but was inconsistent across sleep items. Although we found minimal influence of personality on depression symptom manifestation, longitudinal work can examine similar issues in younger and older samples, as well as examining more dimensions of personality.

This research examined whether non-suicide-specific treatments effectively reduced suicidal ideation (SI) among a clinical sample of eating disorder (ED) patients (N=3,447 of whom 50.9% presented with SI). All participants met criteria for a current DSM-5 ED and were administered a combination of evidence-based treatments in inpatient, residential, partial hospitalization, and intensive outpatient ED treatment facilities. Mediation analyses tested whether SI at discharge decreased specifically through standardized residual change scores in ED symptoms. Both SI and ED symptoms decreased over the course of treatment without clinically meaningful differences by ED diagnosis. ED symptom improvement partially mediated the relationship between SI at admission and discharge, suggesting that treating ED symptoms with evidence-based treatments can be an effective way to reduce SI, at least partially, for many patients. These findings demonstrate the importance of facilitating evidence-based treatment referrals for specific disorders as a component of broad-based suicide outreach and prevention strategies.