Journal of psychopathology and clinical science最新文献

This viewpoint article discusses the utility of high-dosage experiments (HDEs) in everyday life to test theories in clinical science. HDEs involve experimental manipulations and assessments that occur over much longer periods of time than traditional experiments-generally days or even weeks. By nature, they also occur outside the lab, in the everyday environments of participants. Additionally, as with other experiments, the purpose of the study is concealed from participants. Experimental design is one of the most distinguishable characteristics of psychology that separates it from other behavioral sciences. Studies that rely on experiments are essential for theory testing and establishing the potential causal role of mechanisms that underlie psychopathology. Yet despite the value of experimental research, experimental studies are not currently given special prominence in clinical psychological science. For example, in the Journal of Psychopathology and Clinical Science, of all the empirical studies in the most recent year (2023), only three of 77 incorporated an experimental manipulation. Experimental research appears to be less popular in clinical psychology than in other fields, such as social psychology. What might account for this discrepancy? First, clinical samples are more difficult to recruit. This is important because experimental manipulations may produce small effects that require large samples for detection. Additionally, mechanisms hypothesized to underlie psychopathology are often chronic and intransigent. For example, cognitive factors (e.g., perfectionistic beliefs) could require an especially strong manipulation to modify in isolation. Researchers have argued that psychology has been experiencing a crisis in theory development. Eronen and Bringmann (2021) stated that one major reason for this crisis is the difficulty in establishing causal relationships between psychological constructs. The replication crisis has garnered even more attention (Open Science Collaboration, 2015). HDEs would help address these two crises and provide stronger and more replicable tests of theory. This could allow us to more precisely identify important mechanisms underlying psychopathology, potentially enhancing treatment efficacy, and enabling us to move the field forward. (PsycInfo Database Record (c) 2024 APA, all rights reserved).

This article presents an ecologically valid transdiagnostic framework regarding narrative identity disturbances in psychopathology. Problems with self and identity are distressing, disruptive to everyday functioning, and central to theoretical models of recovery. Yet these problems are sorely understudied, in part due to differences in concepts, theories, and measurement models across disorder-specific literatures. Disorder-specific theories are useful for understanding the etiology of disturbances to self and identity. However, while root causes may vary across disorders, their effects on explicit, conscious, reflective experience share important transdiagnostic parallels. These problems affect the extended sense of self as an individual with memories, a present identity, and future expectancies. By extension, these problems are developmental, reflecting an ever-evolving conception of oneself across the life course. Finally, these problems are contextual and intersubjective, constructed over time through interactions with others in the family, community, and society. A unified transdiagnostic model for reflective self-disturbances should therefore be idiographic and grounded in developmental and personality theory, with a strong emphasis on ecological validity. Narrative identity is emerging as a coherent, cross-cutting framework for understanding problems with self and identity across diagnostic boundaries. Important current research directions include transdiagnostic samples and clinical control groups; more diverse samples; expanding on the latent structure of narrative identity in clinical populations, and developing new assessment techniques to supplement trained raters. These directions will further enhance narrative identity's utility for idiographic, developmental, and ecologically valid clinical research. (PsycInfo Database Record (c) 2024 APA, all rights reserved).

We developed three machine learning models that predict hour-by-hour probabilities of a future lapse back to alcohol use with increasing temporal precision (i.e., lapses in the next week, next day, and next hour). Model features were based on raw scores and longitudinal change in theoretically implicated risk factors collected through ecological momentary assessment. Participants (N = 151, 51% male, M_age = 41, 87% White, 97% non-Hispanic) in early recovery (1-8 weeks of abstinence) from alcohol use disorder provided 4 × daily ecological momentary assessment for up to 3 months. We used grouped, nested cross-validation to select the best models and evaluate the performance of those best models. Models yielded median areas under the receiver operating curves of 0.89, 0.90, and 0.93 in the 30 held-out test sets for week-, day-, and hour-level models, respectively. Some feature categories consistently emerged as being globally important to lapse prediction across our week-, day-, and hour-level models (i.e., past use, future self-efficacy). However, most of the more punctate, time-varying constructs (e.g., craving, past stressful events, arousal) appear to have a greater impact within the next-hour prediction model. This research represents an important step toward the development of a smart (machine learning guided) sensing system that can both identify periods of peak lapse risk and recommend specific supports to address factors contributing to this risk. (PsycInfo Database Record (c) 2024 APA, all rights reserved).

Adverse childhood experiences (ACEs) confer risk to the mental health of Black youth, but few studies have examined how youth gender, family, and neighborhood factors jointly influence the psychological impact of adversity. This study investigates if family resilience and neighborhood cohesion jointly moderate the link between latent ACE profiles and mental health among Black girls and boys. This study uses data from the National Survey of Children's Health, combined across the years 2016 through 2021, and includes a nationally representative sample of 5,493 Black youth (48% female) between the ages of 12 and 17. Two patterns of ACEs were identified using latent class analysis characterized by no-to-minimal ACE exposure and moderate-to-high ACE exposure. Membership in the high-ACEs class increased the risk for internalizing problems among Black boys (b = 0.56, p < .001) and girls (b = 0.42, p < .01). Only boys in the high-ACEs class who also reported low levels of family resilience and low neighborhood cohesion evidenced an increased risk for externalizing concerns (b = 0.70, p < .001). Conversely, only girls in the high-ACEs class who reported high levels of family resilience and low levels of neighborhood cohesion evidenced an increased risk for externalizing problems (b = 0.69, p < .01). Findings suggest that the impact of ACEs on mental health is not uniform across Black boys and girls, and that family and neighborhood-level factors may collectively shape the impact of ACEs on the mental health among Black youth in unique ways. (PsycInfo Database Record (c) 2024 APA, all rights reserved).

Current assessment protocols for attention-deficit/hyperactivity disorder (ADHD) focus heavily on a set of highly overlapping symptoms, with well-validated factors like cognitive disengagement syndrome (CDS), executive function (EF), age, sex, and race and ethnicity generally being ignored. Using machine learning techniques, the current study aimed to validate recent findings proposing a subset of ADHD symptoms that, together, predict ADHD diagnosis, severity, and impairment level better than the full symptom list, while also testing whether the inclusion of the factors listed above could further increase accuracy. Parents of 1,922 children (50.1% male) aged 6-17 years completed rating scales of ADHD, CDS, EF, and impairment. Results suggested nine symptoms as most important in predicting outcomes: (a) has difficulty sustaining attention in tasks or play activities; (b) does not follow through on instructions and fails to finish work; (c) avoids tasks (e.g., schoolwork, homework) that require sustained mental effort; (d) is often easily distracted; (e) has difficulty organizing tasks and activities; (f) is often forgetful in daily activities; (g) fidgets with hands or feet or squirms in seat; (h) interrupts/intrudes on others; and (i) shifts around excessively or feels restless or hemmed in. The abbreviated algorithm achieved accuracy rates that did not significantly differ compared to an algorithm comprising all 18 symptoms in predicting impairment, while also demonstrating excellent discriminative ability in predicting ADHD diagnosis. Adding CDS and EF to the abbreviated algorithm further improved the prediction of global impairment. Continued refinement of screening tools will be key to ensuring access to clinical services for youth at risk for ADHD. (PsycInfo Database Record (c) 2024 APA, all rights reserved).

Emotion-related impulsivity-the engagement in impulsive reactions specifically in response to emotions-is considered a transdiagnostic factor underlying psychopathology. The reflexive responding to emotion (RRE) model of emotion-related impulsivity (Carver et al., 2008) suggests that sensitivities to reward and threat in combination with control over emotion are factors that result in internalizing and externalizing psychopathology. In the current study, we adapt the trait-based RRE model to momentary states by evaluating how within-person fluctuations in affect combine with perceptions of momentary emotional control to predict impulsive, rash action and inaction in daily life. Participants (college students and adults recruited from the community: N = 197) completed 8 days of ecological momentary assessment, where we assessed current affect, perceptions of momentary emotional control (via distress intolerance and willpower), and urges for rash action and inaction (5,353 momentary prompts completed). We also assessed subsequent engagement in rash action and inaction. Using multilevel modeling, we found that when people feel greater positive affect and lower negative affect, they also report greater subjective willpower and lower distress intolerance, replicating past ecological momentary assessment findings. Furthermore, we found that momentary perceptions of momentary emotional control moderated the relationship between (a) affect and urges for rash action and (b) affect and engagement in rash action at follow-up. Findings support a dynamic model of the RRE model, confirming that perceptions of momentary emotional control are relevant for both rash action and inaction, particularly when occurring alongside shifts in affect. (PsycInfo Database Record (c) 2024 APA, all rights reserved).

Intensive longitudinal research-including experience sampling and smartphone sensor monitoring-has potential for identifying proximal risk factors for psychopathology, including suicidal thoughts and behaviors (STB). Yet, missing data can complicate analysis and interpretation. This study aimed to address whether clinical and study design factors are associated with missing data and whether missingness predicts changes in symptom severity or STB. Adolescents ages 13- to 18 years old (N = 179) reporting depressive, anxiety, and/or substance use disorders were enrolled; 65% reported current suicidal ideation and 29% indicated a past-year attempt. Passively acquired smartphone sensor data (e.g., global positioning system, accelerometer, and keyboard inputs), daily mood surveys, and weekly suicidal ideation surveys were collected during the 6-month study period using the effortless assessment research system smartphone app. First, acquisition of passive smartphone sensor data (with data on ∼80% of days across the whole sample) was strongly associated with survey data acquisition on the same day (∼44% of days). Second, STB and psychiatric symptoms were largely not associated with missing data. Rather, temporal features (e.g., length of time in study, weekends, and summer) explained more missingness of survey and passive smartphone sensor data. Last, within-participant changes in missing data over time neither followed nor predicted subsequent change in suicidal ideation and psychiatric symptoms. Findings indicate that considering technical and study design factors impacting missingness is critical and highlight several factors that should be addressed to maximize the validity of clinical interpretations in intensive longitudinal research. (PsycInfo Database Record (c) 2024 APA, all rights reserved).