Journal of psychopathology and clinical science最新文献

Ketamine has shown promise in rapidly improving symptoms of depression and most notably treatment-resistant depression (TRD). However, given the heterogeneity of TRD, biobehavioral markers of treatment response are necessary for the personalized prescription of intravenous ketamine. Heterogeneity in depression can be manifested in discrete patterns of functional connectivity (FC) in default mode, ventral affective, and cognitive control networks. This study employed a data-driven approach to parse FC during positive mood processing to characterize subgroups of patients with TRD prior to infusion and determine whether these connectivity-based subgroups could predict subsequent antidepressant response to ketamine compared to saline infusion. 152 adult patients with TRD completed a baseline assessment of FC during positive mood processing and were randomly assigned to either ketamine or saline infusion. The assessment utilized Subgroup-Group Iterative Multiple Model Estimation to recover directed connectivity maps and applied Walktrap algorithm to determine data-driven subgroups. Depression severity was assessed pre- and 24-hr postinfusion. Two connectivity-based subgroups were identified: Subgroup A (n = 110) and Subgroup B (n = 42). We observed that treatment response was moderated by an infusion type by subgroup interaction (p = .040). For patients receiving ketamine, subgroup did not predict treatment response (β = -.326, p = .499). However, subgroup predicted response for saline patients. Subgroup B individuals, relative to A, were more likely to be saline responders at 24-hr postinfusion (β = -2.146, p = .007). Thus, while ketamine improved depressive symptoms uniformly across both subgroups, this heterogeneity was a predictor of placebo response. (PsycInfo Database Record (c) 2024 APA, all rights reserved).

Most studies aimed at understanding suicidal behavior have focused on quantifying the associations between putative risk factors and suicidal behavior in comparative studies of cases and controls. The current study, in comparison, exclusively focused on cases-89 Army soldiers presenting for hospital care following a suicide attempt-and attempted to reveal the antecedents of, reasons for, and consequences of suicide attempts. This mixed-methods study using qualitative interviews and self-report surveys/interviews revealed that in most cases, the most recent onset of suicidal thoughts began shortly before the suicide attempt and were not disclosed to others, limiting opportunities for intervention via traditional approaches. The primary reason given for attempting suicide was to escape from psychologically aversive conditions after concluding that no other effective strategies or options were available. Participants reported both negative (e.g., self-view, guilt) and positive (e.g., learning new skills, receiving support) consequences of their suicide attempt-and described things they believe would have prevented them from making the attempt. These findings provide new insights into the motivational and contextual factors for suicidal behavior and highlight several novel directions for prevention and intervention efforts. (PsycInfo Database Record (c) 2024 APA, all rights reserved).

This article discusses the concept of "experience" in experience sampling. A central challenge of clinical science is understanding psychopathological constructs and their manifestations. In conventional definitions and measures of psychopathology, subjective experience of mental disorder is often lost. The authors argue for an integration of phenomenology-or prioritization of subjectivity-in psychopathological construct definition and measurement, particularly through experience sampling methods (ESMs). ESMs capture idiographic, contextual, and longitudinal elements of lived experience that can expand our current conceptualizations and classifications of psychopathology. The authors propose three novel applications and extensions: (a) leveraging ESM for subjective construct definition (i.e., phenomena detection), (b) mixed-methods approaches, like cognitive interviewing, to improve the validity of ESM measures and (c) incorporation of novel ESM approaches (e.g., audiovisual data capturing) to expand understanding of subjective, daily experience of psychopathology. Merging phenomenological tradition with ESM serves to expand our understanding of psychopathology and bring "experience" back into experience sampling. (PsycInfo Database Record (c) 2024 APA, all rights reserved).

Problematic pornography use (PPU) is the most common manifestation of the newly introduced compulsive sexual behavior disorder diagnosis in the 11th revision of the International Classification of Diseases. Research related to PPU has proliferated in the past two decades, but most prior studies were characterized by several shortcomings (e.g., using homogenous, small samples), resulting in crucial knowledge gaps and a limited understanding concerning empirically based risk factors for PPU. This study aimed to identify the most robust risk factors for PPU using a preregistered study design. Independent laboratories' 74 preexisting self-report data sets (N_participants = 112,397; N_countries = 16) were combined to identify which factors can best predict PPU using an artificial intelligence-based method (i.e., machine learning). We conducted random forest models on each data set to examine how different sociodemographic, psychological, and other characteristics predict PPU, and combined the results of all data sets using random-effects meta-analysis with meta-analytic moderators (e.g., community vs. treatment-seeking samples). Predictors explained 45.84% of the variance in PPU scores. Out of the 700+ potential predictors, 17 variables emerged as significant predictors across data sets, with the top five being (a) pornography use frequency, (b) emotional avoidance pornography use motivation, (c) stress reduction pornography use motivation, (d) moral incongruence toward pornography use, and (e) sexual shame. This study is the largest and most integrative data analytic effort in the field to date. Findings contribute to a better understanding of PPU's etiology and may provide deeper insights for developing more efficient, cost-effective, empirically based directions for future research as well as prevention and intervention programs targeting PPU. (PsycInfo Database Record (c) 2024 APA, all rights reserved).

Bipolar disorder (BD) is a chronic psychiatric condition characterized by large episodic changes in mood and energy. Recently, BD has been proposed to be conceptualized as chronic cyclical mood instability, as opposed to the traditional view of alternating discrete episodes with stable periods in-between. Recognizing this mood instability may improve care and call for high-frequency measures coupled with advanced statistical models. To uncover empirically derived mood states, a multilevel hidden Markov model (HMM) was applied to 4-month ecological momentary assessment data in 20 patients with BD, yielding ∼9,820 assessments in total. Ecological momentary assessment data comprised self-report questionnaires (5 × daily) measuring manic and depressive constructs. Manic and depressive symptoms were also assessed weekly using the Altman Self-Rating Mania Scale and the Quick Inventory for Depressive Symptomatology Self-Report. Alignment between HMM-uncovered momentary mood states and weekly questionnaires was assessed with a multilevel linear model. HMM uncovered four mood states: neutral, elevated, mixed, and lowered, which aligned with weekly symptom scores. On average, patients remained < 25 hr in one state. In almost half of the patients, mood instability was observed. Switching between mood states, three patterns were identified: patients switching predominantly between (a) neutral and lowered states, (b) neutral and elevated states, and (c) mixed, elevated, and lowered states. In all, elevated and lowered mood states were interspersed by mixed states. The results indicate that chronic mood instability is a key feature of BD, even in "relatively" euthymic periods. This should be considered in theoretical and clinical conceptualizations of the disorder. (PsycInfo Database Record (c) 2024 APA, all rights reserved).

Landmark studies have shown decreased coherence between different emotion response systems (e.g., physiology and facial expressions) in people with psychosis. However, while there is good evidence to suggest broad signs of affective dysfunction (e.g., blunting of facial expression) in the critical clinical high-risk (CHR) state, it is not clear whether these signs fit into a broader pattern of decoupling. This is in part due to there being no studies to date with this population that include a dyadic interaction. The current laboratory-based dyadic interaction study examined whether there is decreased coherence in CHR between autonomic physiology, as indexed by heart rate, and facial expressions of emotion, assessed by automated facial expressions analysis. The study included 145 individuals consisting of 34 CHR-partner and 41 control-partner pairs who completed clinical interviews and engaged in three naturalistic 10-min conversations while their physiology and expressions were continuously monitored. Compared to controls, CHR youth showed decreased coherence between heart rate and positive (t = 4.09) and negative (t = -7.90) facial expressions. Across CHR and control youth, greater severity of psychosis risk symptoms was related to lower coherence between heart rate and positive (t = 3.97-11.69) and neutral expressions (t = 0.06-4.98), and a change in the direction of the relationship between heart rate and negative expression intensity (t = 7.88-10.60). These findings provide the first evidence for changes in coherence between physiology and facial expressions of emotion in CHR individuals, with larger changes in coherence relating to greater general psychotic-like symptom severity. This evidence may be leveraged to identify targets for early diagnosis and intervention. (PsycInfo Database Record (c) 2024 APA, all rights reserved).

The diagnosis of personality disorder (PD) is undergoing a transition from a categorical model that distinguishes types from one another to a model that characterizes patients with dimensional profiles. The DSM-5 (Diagnostic and Statistical Manual of Mental Disorders, 5th ed.) alternative model of personality disorder (AMPD) and the International Statistical Classification of Diseases and Related Health Problems (11th ed.) have two primary criteria: the first is a dimension that differentiates PD from both normal personality and other kinds of disorder, can be used to indicate the overall level of severity of a patient's functional difficulties, and is the basis for PD diagnosis. The second is a set of traits with structural connections to normal-range personality variables that characterize the type of problems the patient is likely to have. (PsycInfo Database Record (c) 2024 APA, all rights reserved).

The perinatal period is marked by a higher risk of experiencing depressive, anxiety, and/or trauma-related symptoms, a phenomenon that affects millions of individuals each year. Obsessive-compulsive disorder (OCD) and posttraumatic stress disorder (PTSD) symptoms commonly co-occur but have rarely been examined together beyond prevalence estimates in the perinatal period. Our study aimed to explore patterns of associations among OCD and PTSD symptoms to elucidate within- and between-person effects and how these effects may change over time. Participants (N = 270) were recruited during pregnancy from an academic medical center affiliated with a midwestern university. PTSD, OCD, and depressive symptoms were assessed at pregnancy, 4, 8, and 12 weeks postpartum. A panel graphical vector autoregression model was used to estimate networks. The temporal network provided information regarding directed predictive effects between symptoms, and hyperarousal, neutralizing, and ordering were the most stable and predictive symptoms across time. The contemporaneous network, which yields undirected partial correlations between symptoms at a given moment, indicated that there were positive associations between intrusions and avoidance, hyperarousal and negative alterations in cognitions and mood, as well as between hyperarousal and dysphoria. This study identified hyperarousal and neutralizing as the PTSD and OCD symptoms with the strongest stability, predictive power, and association with other symptoms. Clinically, this indicates that screening for hyperarousal and neutralizing symptoms may identify individuals who could maximally benefit from treatment in the perinatal period. (PsycInfo Database Record (c) 2024 APA, all rights reserved).