Association of Positive, Negative, and Disorganized Schizotypy With the Temporal Dynamics of Schizotypic Experiences in Daily Life.

BACKGROUND AND HYPOTHESIS: Schizotypy is a useful and unifying construct for examining the etiology, development, and expression of schizophrenia-spectrum psychopathology. The positive, negative, and disorganized schizotypy dimensions are associated with distinct patterns of schizophrenia-spectrum symptoms and impairment. Furthermore, they are differentiated by mean levels of psychotic-like, suspicious, negative, and disorganized schizotypic experiences in daily life, and by temporal dynamics of affect. The schizotypy dimensions were thus hypothesized to be differentiated by the temporal dynamics of schizotypic experiences in daily life. STUDY DESIGN: The present study employed experience sampling methodology in a large nonclinically ascertained sample (n = 693) to examine the associations of multidimensional schizotypy with psychotic-like, suspicious, negative, and disorganized schizotypic experiences in daily life, as well as with their temporal dynamics (variability, reactivity, inertia, and instability). STUDY RESULTS: We replicated the mean-level associations between multidimensional schizotypy and schizotypic experiences in daily life. Furthermore, positive, negative, and disorganized schizotypy demonstrated hypothesized, differential patterns of temporal dynamics of schizotypic experiences. Disorganized schizotypy demonstrated the most robust associations, including intensity, variability, and inertia of disorganized schizotypic experiences. Disorganized schizotypy also moderated reactivity of psychotic-like and disorganized schizotypic experiences following previously reported stress. Positive schizotypy was associated with intensity and variability of psychotic-like experiences. Negative schizotypy was associated with intensity and variability of negative schizotypic experiences. CONCLUSIONS: The findings indicate that schizotypy dimensions can be differentiated by both mean levels and temporal patterns of psychotic-like, suspicious, negative, and disorganized schizotypic experiences in daily life, with disorganized schizotypy uniquely characterized by stress reactivity.

Longitudinal Interplay Between Alcohol Use, Mood, and Functioning in Bipolar Spectrum Disorders.

Importance: Alcohol use disorder (AUD) is present in nearly half of individuals with bipolar disorder (BD) and is associated with markedly worsening outcomes. Yet, the concurrent treatment of BD and AUD remains neglected in both research and clinical care; characterizing their dynamic interplay is crucial in improving outcomes. Objective: To characterize the longitudinal alcohol use patterns in BD and examine the temporal associations among alcohol use, mood, anxiety, and functioning over time. Design, Setting, and Participants: This cohort study selected participants and analyzed data from the Prechter Longitudinal Study of Bipolar Disorder (PLS-BD), an ongoing cohort study that recruits through psychiatric clinics, mental health centers, and community outreach events across Michigan and collects repeated phenotypic data. Participants selected for the present study were those with a diagnosis of BD type I (BDI) or type II (BDII) who had been in the study for at least 5 years. Data used were extracted from February 2006 to April 2022, and follow-up ranged from 5 to 16 years. Main Outcomes and Measures: Alcohol use was measured using the Alcohol Use Disorders Identification Test. Depression, mania or hypomania, anxiety, and functioning were measured using the 9-Item Patient Health Questionnaire, the Altman Self-Rating Mania Scale, the 7-item Generalized Anxiety Disorder assessment scale, and the Life Functioning Questionnaire, respectively. Results: A total of 584 individuals (386 females (66.1%); mean [SD] age, 40 [13.6] years) were included. These participants had a BDI (445 [76.2%]) or BDII (139 [23.8%]) diagnosis, with or without a lifetime diagnosis of AUD, and a median (IQR) follow-up of 9 (0-16) years. More problematic alcohol use was associated with worse depressive (ß = 0.04; 95% credibility interval [CrI], 0.01-0.07) and manic or hypomanic symptoms (ß = 0.04; 95% CrI, 0.01-0.07) as well as lower workplace functioning (ß = 0.03; 95% CrI, 0.00-0.06) over the next 6 months, but increased depressive and manic or hypomanic symptoms were not associated with greater subsequent alcohol use. These latter 2 associations were more pronounced in BDII than BDI (mania or hypomania: ß = 0.16 [95% CrI, 0.02-0.30]; workplace functioning: ß = 0.26 [95% CrI, 0.06-0.45]). Alcohol use was not associated with anxiety over time. Conclusions and Relevance: This study found that alcohol use, regardless of diagnostic status, was associated with mood instability and poorer work functioning in BD, but increased mood symptoms were not associated with subsequent alcohol use. Given its prevalence and repercussions, dimensional and longitudinal assessment and management of alcohol use are necessary and should be integrated into research and standard treatment of BD.

An initial test of the contrast avoidance model in bipolar spectrum disorders.

The Contrast Avoidance Model suggests that individuals sensitive to negative emotional shifts use prior increases in negative affect to prevent further escalation in response to adverse situations, while the heightened negative affect amplifies positive emotional contrasts when encountering unexpected positive events. Individuals with bipolar spectrum disorders (BSDs), characterized by shifts between (hypo)manic and depressive episodes, may undergo more salient emotional contrasts. Drawing from the Contrast Avoidance Model, the shifts from depression to (hypo)mania can be conceptualized as positive emotional contrasts, potentially heightening the perceived pleasure during (hypo)manic episodes. On the other hand, the shifts from (hypo)manic to depressive episodes can be viewed as negative emotional contrasts, contributing to the challenges associated with depressive states. Despite the intriguing potential of this interplay, the link between the Contrast Avoidance Model and BSDs has never been empirically tested. Our study addressed this gap by examining group differences in contrast avoidance traits between individuals with BSDs, unipolar depression, and healthy controls in a large cohort study (N = 536). Results indicated that individuals with BSDs exhibited significantly higher scores in the total, and Discomfort with Negative Emotional Shifts and Avoidance of Negative Emotional Contrasts/Enhancement of Positive Emotional Contrasts factors, as well as separate item scores on the Contrast Avoidance Questionnaire-General Emotion (CAQ-GE), compared to those with unipolar depression and healthy controls. Although marginal, the BD II subtype demonstrated a stronger inclination to avoid negative emotional contrasts compared to BD I. These findings suggest that contrast avoidance may be a psychological mechanism implicated in BSDs.

Longitudinal dynamics between anxiety and depression in bipolar spectrum disorders.

Anxiety and depression are common among individuals with bipolar spectrum disorders (BSDs), with anxiety being a risk factor for depression and vice versa. While the harmful effects of these symptoms are well recognized, their temporal dynamics have not been fully tested. To address this gap, our study investigated bidirectional relationships between anxiety and depression in individuals with BSDs using data from the Prechter Longitudinal Study of Bipolar Disorder, collected over an average of 11 years. We included 651 participants with various BSD subtypes (BD I, BD II, BD not otherwise specified, and schizoaffective bipolar type), with at least 5 years' data for adequate statistical power in detecting temporal dynamics. Bimonthly measurements of anxiety and depression were analyzed using dynamic structural equation modeling. Beyond assessing autoregressive and cross-lagged effects, this study also investigated whether temporal dynamics differed based on demographic characteristics and the use of psychiatric medication. Our findings revealed that individuals with BSDs experienced significant fluctuations in anxiety and depression over time. In addition, we found significant autoregressive and cross-lagged effects of anxiety and depression. Comparison of the cross-lagged effects demonstrated that anxiety had a greater effect on subsequent depression than vice versa. Age and marital status impacted cross-lagged and autoregressive effects. Specifically, older participants had stronger temporal associations between depression and subsequent anxiety, while widowed participants exhibited a heightened impact of depression on subsequent depression. These results underscore the importance of early identification and integrative interventions aimed at addressing both anxiety and depression to mitigate subsequent symptoms in BSDs. (PsycInfo Database Record (c) 2024 APA, all rights reserved).

Patterns of pharmacotherapy for bipolar disorder: A GBC survey.

OBJECTIVES: To understand treatment practices for bipolar disorders (BD), this study leveraged the Global Bipolar Cohort collaborative network to investigate pharmacotherapeutic treatment patterns in multiple cohorts of well-characterized individuals with BD in North America, Europe, and Australia. METHODS: Data on pharmacotherapy, demographics, diagnostic subtypes, and comorbidities were provided from each participating cohort. Individual site and regional pooled proportional meta-analyses with generalized linear mixed methods were conducted to identify prescription patterns. RESULTS: This study included 10,351 individuals from North America (n = 3985), Europe (n = 3822), and Australia (n = 2544). Overall, participants were predominantly female (60%) with BD-I (60%; vs. BD-II = 33%). Cross-sectionally, mood-stabilizing anticonvulsants (44%), second-generation antipsychotics (42%), and antidepressants (38%) were the most prescribed medications. Lithium was prescribed in 29% of patients, primarily in the Australian (31%) and European (36%) cohorts. First-generation antipsychotics were prescribed in 24% of the European versus 1% in the North American cohort. Antidepressant prescription rates were higher in BD-II (47%) compared to BD-I (35%). Major limitations were significant differences among cohorts based on inclusion/exclusion criteria, data source, and time/year of enrollment into cohort. CONCLUSIONS: Mood-stabilizing anticonvulsants, second-generation antipsychotics, and antidepressants were the most prescribed medications suggesting prescription patterns that are not necessarily guideline concordant. Significant differences exist in the prescription practices across different geographic regions, especially the underutilization of lithium in the North American cohorts and the higher utilization of first-generation antipsychotics in the European cohorts. There is a need to conduct future longitudinal studies to further explore these differences and their impact on outcomes, and to inform and implement evidence-based guidelines to help improve treatment practices in BD.

Alcohol use disorder conceptualizations and diagnoses reflect their sociopolitical context.

The present paper highlights how alcohol use disorder (AUD) conceptualizations and resulting diagnostic criteria have evolved over time in correspondence with interconnected sociopolitical influences in the United States. We highlight four illustrative examples of how DSM-defined alcoholism, abuse/dependence, and AUD have been influenced by sociopolitical factors. In doing so, we emphasize the importance of recognizing and understanding such sociopolitical factors in the application of AUD diagnoses. Last, we offer a roadmap to direct the process of future efforts toward the improved diagnosis of AUD, with an emphasis on pursuing falsifiability, acknowledging researchers' assumptions about human behavior, and collaborating across subfields. Such efforts that center the numerous mechanisms and functions of behavior, rather than signs or symptoms, have the potential to minimize sociopolitical influences in the development of diagnostic criteria and maximize the treatment utility of diagnoses.

Barriers to and facilitators of success for early and Mid-Career professionals focused on bipolar disorder: A global needs survey by the International Society for Bipolar Disorders.

INTRODUCTION: The International Society for Bipolar Disorders created the Early Mid-Career Committee (EMCC) to support career development of the next generation of researchers and clinicians specializing in bipolar disorder (BD). To develop new infrastructure and initiatives, the EMCC completed a Needs Survey of the current limitations and gaps that restrict recruitment and retention of researchers and clinicians focused on BD. METHODS: The EMCC Needs Survey was developed through an iterative process, relying on literature and content expertise of workgroup members. The survey included 8 domains: navigating transitional career stages, creating and fostering mentorship, research activities, raising academic profile, clinical-research balance, networking and collaboration, community engagement, work-life balance. The final survey was deployed from May to August 2022 and was available in English, Spanish, Portuguese, Italian, and Chinese. RESULTS: Three hundred participants across six continents completed the Needs Survey. Half of the participants self-identified as belonging to an underrepresented group in health-related sciences (i.e., from certain gender, racial, ethnic, cultural, or disadvantaged backgrounds including individuals with disabilities). Quantitative results and qualitative content analysis revealed key barriers to pursuing a research career focused on BD with unique challenges specific to scientific writing and grant funding. Participants highlighted mentorship as a key facilitator of success in research and clinical work. CONCLUSION: The results of the Needs Survey are a call to action to support early- and midcareer professionals pursuing a career in BD. Interventions required to address the identified barriers will take coordination, creativity, and resources to develop, implement, and encourage uptake but will have long-lasting benefits for research, clinical practice, and ultimately those affected by BD.

Affective dynamics in daily life are differentially expressed in positive, negative, and disorganized schizotypy.

Schizotypy and schizophrenia are associated with disruptions in the experience of affect. Temporal patterns of affect, or affective dynamics, offer unique information about the expression of multidimensional schizophrenia-spectrum psychopathology. The present study employed experience sampling methodology to examine affective intensity, inertia, variability, reactivity, and instability in positive, negative, and disorganized schizotypy in nonclinically ascertained young adults (n = 275). As hypothesized, disorganized schizotypy demonstrated the most robust associations with affective dynamics and was characterized by elevated intensity, reactivity, and variability of negative affect. Disorganized schizotypy was also associated with instability of negative affect, but this relation was better accounted for by mean negative affect, which was elevated in disorganized schizotypy. Negative schizotypy was characterized by diminished intensity and variability of positive affect as expected, but was unassociated with affective inertia. Finally, as hypothesized, positive schizotypy was associated with elevated intensity and variability of negative affect at the bivariate level, but was unassociated with affective dynamics when including disorganized schizotypy in the model. These findings indicate that the schizotypy dimensions are differentiated by both mean levels and dynamics of affect, and that affective dynamics convey unique information about multidimensional schizotypy beyond mean levels of affect. The findings provide further support for the multidimensional model of schizotypy. (PsycInfo Database Record (c) 2023 APA, all rights reserved).

Integration of Face-to-Face Screening With Real-time Machine Learning to Predict Risk of Suicide Among Adults.

Importance: Understanding the differences and potential synergies between traditional clinician assessment and automated machine learning might enable more accurate and useful suicide risk detection. Objective: To evaluate the respective and combined abilities of a real-time machine learning model and the Columbia Suicide Severity Rating Scale (C-SSRS) to predict suicide attempt (SA) and suicidal ideation (SI). Design, Setting, and Participants: This cohort study included encounters with adult patients (aged ≥18 years) at a major academic medical center. The C-SSRS was administered during routine care, and a Vanderbilt Suicide Attempt and Ideation Likelihood (VSAIL) prediction was generated in the electronic health record. Encounters took place in the inpatient, ambulatory surgical, and emergency department settings. Data were collected from June 2019 to September 2020. Main Outcomes and Measures: Primary outcomes were the incidence of SA and SI, encoded as International Classification of Diseases codes, occurring within various time periods after an index visit. We evaluated the retrospective validity of the C-SSRS, VSAIL, and ensemble models combining both. Discrimination metrics included area under the receiver operating curve (AUROC), area under the precision-recall curve (AUPR), sensitivity, specificity, positive predictive value (PPV), and negative predictive value (NPV). Results: The cohort included 120 398 unique index visits for 83 394 patients (mean [SD] age, 51.2 [20.6] years; 38 107 [46%] men; 45 273 [54%] women; 13 644 [16%] Black; 63 869 [77%] White). Within 30 days of an index visit, the combined models had higher AUROC (SA: 0.874-0.887; SI: 0.869-0.879) than both the VSAIL (SA: 0.729; SI: 0.773) and C-SSRS (SA: 0.823; SI: 0.777) models. In the highest risk-decile, ensemble methods had PPV of 1.3% to 1.4% for SA and 8.3% to 8.7% for SI and sensitivity of 77.6% to 79.5% for SA and 67.4% to 70.1% for SI, outperforming VSAIL (PPV for SA: 0.4%; PPV for SI: 3.9%; sensitivity for SA: 28.8%; sensitivity for SI: 35.1%) and C-SSRS (PPV for SA: 0.5%; PPV for SI: 3.5%; sensitivity for SA: 76.6%; sensitivity for SI: 68.8%). Conclusions and Relevance: In this study, suicide risk prediction was optimal when leveraging both in-person screening (for acute measures of risk in patient-reported suicidality) and historical EHR data (for underlying clinical factors that can quantify a patient's passive risk level). To improve suicide risk classification, prediction systems could combine pretrained machine learning with structured clinician assessment without needing to retrain the original model.

A critical examination of multidimensionality within the Hypomanic Personality Scale.

BACKGROUND: The Hypomanic Personality Scale (HPS) assesses bipolar spectrum psychopathology and risk for bipolar disorders. Despite the developers' intent to create a scale that provides a unitary score, several studies have examined whether the HPS has a multidimensional structure. These models have been unable to identify a replicable multidimensional structure, with models varying from fairly similar to entirely dissimilar, and have suffered from theoretical and methodological concerns. PROCEDURES: We therefore examined the multidimensional structure of the HPS in a large undergraduate and adult sample (n = 5002). MAIN FINDINGS: We failed to reproduce factors with equal congruence to those of previously published models. PRINCIPLE CONCLUSIONS: We concluded that the HPS lacks factorial validity in previous research as a multidimensional measure of bipolar spectrum psychopathology. We further recommend the creation of a novel multidimensional assessment of bipolar spectrum psychopathology developed from a theoretically driven, comprehensive model, rather than examining a multidimensional model of a pre-existing measure, such as the HPS.

Empathy, Emotion Recognition, and Paranoia in the General Population.

Background: Paranoia is associated with a multitude of social cognitive deficits, observed in both clinical and subclinical populations. Empathy is significantly and broadly impaired in schizophrenia, yet its relationship with subclinical paranoia is poorly understood. Furthermore, deficits in emotion recognition - a very early component of empathic processing - are present in both clinical and subclinical paranoia. Deficits in emotion recognition may therefore underlie relationships between paranoia and empathic processing. The current investigation aims to add to the literature on social cognition and paranoia by: (1) characterizing the relationship between paranoia and empathy, and (2) testing whether there is an indirect effect of emotion recognition on the relationship between empathy and paranoia. Methods: Paranoia, empathy, and emotion recognition were assessed in a non-clinical sample of adults (n = 226) from the Nathan Kline Institute-Rockland (NKI-Rockland) dataset. Paranoia was measured using the Peters Delusions Inventory-21 (PDI-21). Empathy was measured using the Interpersonal Reactivity Index (IRI), a self-report instrument designed to assess empathy using four subscales: Personal Distress, Empathic Concern, Perspective Taking, and Fantasy. Emotion recognition was assessed using the Penn Emotion Recognition Test (ER-40). Structural equation modeling (SEM) was used to estimate relationships between paranoia, the four measures of empathy and emotion recognition. Results: Paranoia was associated with the Fantasy subscale of the IRI, such that higher Fantasy was associated with more severe paranoia (p < 0.001). No other empathy subscales were associated with paranoia. Fantasy was also associated with the emotion recognition of fear, such that higher Fantasy was correlated with better recognition of fear (p = 0.008). Paranoia and emotion recognition were not significantly associated. The Empathic Concern subscale was negatively associated with emotion recognition, with higher empathic concern related to worse overall emotion recognition (p = 0.002). All indirect paths through emotion recognition were non-significant. Discussion: These results suggest that imaginative perspective-taking contributes to paranoia in the general population. These data do not, however, point to robust global relationships between empathy and paranoia or to emotion recognition as an underlying mechanism. Deficits in empathy and emotion recognition observed in schizophrenia may be associated with the broader pathology of schizophrenia, and therefore not detectable with subclinical populations.

Variability in Sleep Is Associated with Trait-Based and Daily Measures of Bipolar Spectrum Psychopathology.

INTRODUCTION: Although sleep disturbances are well documented in bipolar spectrum disorders (BSDs), significantly less research has examined whether these disturbances are present in those at risk for developing BSDs or with subsyndromal symptoms. The present study examined associations between risk for BSDs, as measured by the Hypomanic Personality Scale (HPS), and sleep assessed using experience sampling. We assessed whether intraindividual variability in sleep was associated with affect, cognition, and behavior in daily life and potential directionality of these relationships. METHODS: 233 young adults oversampled for high scores on the HPS completed 14 days of experience sampling assessing total sleep time (TST), bed/rise time, sleep quality, affect (negative and positive affect), cognition (difficulty concentrating, racing thoughts), and behavior (impulsivity) in daily life. We used Dynamic Structural Equation Modeling (DSEM) to assess within-person links between sleep and bipolar spectrum psychopathology. RESULTS: HPS scores were associated with less TST, later bedtime, and more variable TST and bedtime. Variability in TST was associated with negative affect, difficulty concentrating/racing thoughts, and impulsivity. Within-person decreases in sleep were associated with next day increases in negative affect, stress, difficulty concentrating, and racing thoughts. LIMITATIONS: Measurement of sleep was limited. Future studies should examine both objective measures of sleep (e.g., actigraphy) and fragmentation in sleep. CONCLUSIONS: Risk for BSD was associated with similar patterns of sleep disruptions as seen in BSDs. Important dynamic links between sleep and bipolar spectrum psychopathology emerged indicating that sleep is an important target for improving symptoms of BSDs in daily life.

Bipolar spectrum psychopathology is associated with altered emotion dynamics across multiple timescales.

Emotion dysregulation is a core feature of bipolar spectrum psychopathology and may confer risk for poor outcomes or progression along the bipolar spectrum. However, previous research on bipolar psychopathology has primarily concentrated on characterizing distinct mood episodes and failed to characterize microlevel dynamics of the experience of emotion. This is the first study to our knowledge to comprehensively examine the extent to which bipolar spectrum psychopathology, as measured by the Hypomanic Personality Scale (HPS), is associated with altered dynamics of positive (PA) and negative affect (NA) across multiple timescales. Young adults (n = 233) oversampled for high HPS scores (>1.5 SD) completed self-report questionnaires and 14 days of experience sampling questionnaires assessing high- and low-arousal NA and PA. Four emotion dynamics (reactivity, variability, instability, inertia) were computed from each participant's time series. As predicted, HPS scores were positively associated with variability and instability of high-arousal NA and PA both within and between days (over and above mean levels of emotions, depression, and neuroticism). Further, HPS scores were associated with large fluctuations in low- but not high-arousal NA and moderated stress reactivity. Specifically, high scorers on the HPS were more likely to report feeling like their emotions were out of control (but not high-intensity NA) when experiencing stress. Contrary to expectation, HPS scores were unassociated with inertia of high-arousal PA. Findings indicated that microlevel emotion dynamics are disrupted across multiple timescales in those high in bipolar spectrum psychopathology. Examining emotion dynamics should enhance understanding of risk for bipolar disorders and facilitate development of mood-monitoring interventions. (PsycInfo Database Record (c) 2022 APA, all rights reserved).

Intensity, frequency, and differentiation of discrete emotion categories in daily life and their associations with depression, worry, and rumination.

Previous research examining links between psychopathology and emotions in daily life have largely focused on disorder-specific patterns of mean-level positive and negative affect. In this study, we examined three transdiagnostic dimensions of psychopathology, namely depression, worry, and rumination, and their association with the intensity, frequency, and differentiation of discrete emotion categories endorsed in daily life. Three independent samples of young adults (total n = 614) completed baseline measures assessing depression, worry, and rumination followed by a 1-week daily diary procedure. Daily diaries assessed the following emotion categories: "tranquility," "contentment," "happiness," "excitement," "pride," "sadness," "boredom," "guilt," "fear," and "anger." Intensity, frequency, and differentiation were all calculated from daily emotion ratings. Psychopathology was associated with intensity and frequency of pleasant emotion, with intensity showing stronger associations. Intensity of contentment and happiness were most strongly associated with all three forms of psychopathology, whereas pride had the weakest associations. Psychopathology was associated with intensity and frequency of unpleasant emotions, with frequency tending to show stronger associations. Frequency of sadness and boredom were most strongly associated with depression, whereas the frequency and intensity of fear were similarly associated with depression and worry. Although psychopathology was associated with pleasant and unpleasant emotion differentiation, to our surprise, effect sizes were negligible to small. Clinical implications and recommendations for future research are discussed. (PsycInfo Database Record (c) 2022 APA, all rights reserved).