Examining contemporaneous and temporal associations of real-time suicidal ideation using network analysis.

BACKGROUND: Suicidal ideation arises from a complex interplay of multiple interacting risk factors over time. Recently, ecological momentary assessment (EMA) has increased our understanding of factors associated with real-time suicidal ideation, as well as those predicting ideation at the level of hours and days. Here we used statistical network methods to investigate which cognitive-affective risk and protective factors are associated with the temporal dynamics of suicidal ideation. METHODS: The SAFE study is a longitudinal cohort study of 82 participants with current suicidal ideation who completed 4×/day EMA over 21 days. We modeled contemporaneous (t) and temporal (t + 1) associations of three suicidal ideation components (passive ideation, active ideation, and acquired capability) and their predictors (positive and negative affect, anxiety, hopelessness, loneliness, burdensomeness, and optimism) using multilevel vector auto-regression models. RESULTS: Contemporaneously, passive suicidal ideation was positively associated with sadness, hopelessness, loneliness, and burdensomeness, and negatively with happiness, calmness, and optimism; active suicidal ideation was positively associated with passive suicidal ideation, sadness, and shame; and acquired capability only with passive and active suicidal ideation. Acquired capability and hopelessness positively predicted passive ideation at t + 1, which in turn predicted active ideation; acquired capability was positively predicted at t + 1 by shame, and negatively by burdensomeness. CONCLUSIONS: Our findings show that systematic real-time associations exist between suicidal ideation and its predictors, and that different factors may uniquely influence distinct components of ideation. These factors may represent important targets for safety planning and risk detection.

Intolerance of uncertainty as a predictor of anxiety severity and trajectory during the COVID-19 pandemic.

BACKGROUND: Efforts to identify risk and resilience factors for anxiety severity and course during the COVID-19 pandemic have focused primarily on demographic rather than psychological variables. Intolerance of uncertainty (IU), a transdiagnostic risk factor for anxiety, may be a particularly relevant vulnerability factor. METHOD: N = 641 adults with pre-pandemic anxiety data reported their anxiety, IU, and other pandemic and mental health-related variables at least once and up to four times during the COVID-19 pandemic, with assessments beginning in May 2020 through March 2021. RESULTS: In preregistered analyses using latent growth models, higher IU at the first pandemic timepoint predicted more severe anxiety, but also a sharper decline in anxiety, across timepoints. This finding was robust to the addition of pre-pandemic anxiety and demographic predictors as covariates (in the full sample) as well as pre-pandemic depression severity (in participants for whom pre-pandemic depression data were available). Younger age, lower self/parent education, and self-reported history of COVID-19 illness at the first pandemic timepoint predicted more severe anxiety across timepoints with strong model fit, but did not predict anxiety trajectory. CONCLUSIONS: IU prospectively predicted more severe anxiety but a sharper decrease in anxiety over time during the pandemic, including after adjustment for covariates. IU therefore appears to have unique and specific predictive utility with respect to anxiety in the context of the COVID-19 pandemic.

Subjective evidence evaluation survey for many-analysts studies.

Many-analysts studies explore how well an empirical claim withstands plausible alternative analyses of the same dataset by multiple, independent analysis teams. Conclusions from these studies typically rely on a single outcome metric (e.g. effect size) provided by each analysis team. Although informative about the range of plausible effects in a dataset, a single effect size from each team does not provide a complete, nuanced understanding of how analysis choices are related to the outcome. We used the Delphi consensus technique with input from 37 experts to develop an 18-item subjective evidence evaluation survey (SEES) to evaluate how each analysis team views the methodological appropriateness of the research design and the strength of evidence for the hypothesis. We illustrate the usefulness of the SEES in providing richer evidence assessment with pilot data from a previous many-analysts study.

Developing a transdiagnostic Ecological Momentary Assessment protocol for psychopathology.

OBJECTIVES: The network approach to psychopathology posits that mental disorders emerge from dynamic interactions among psychopathology-relevant variables. Ecological Momentary Assessment (EMA) is frequently used to assess these variables in daily life. Considering the transdiagnostic nature of the network approach to psychopathology, this study describes the development of a transdiagnostic EMA protocol for psychopathology. METHODS: First, 96 clinicians completed an online survey, providing three EMA constructs for up to three disorders they specialize in, and three EMA constructs relevant across disorders (transdiagnostic constructs). Second, 12 focus groups were conducted with clinical experts for specific types of diagnoses (e.g., mood disorders, anxiety disorders). Finally, a selection of items was reached by consensus. Two raters independently coded the online survey responses with an inter-rater agreement of 87.3%. RESULTS: Jaccard indices showed up to 52.6% overlap in EMA items across types of diagnoses. The most frequently reported transdiagnostic constructs were mood, sleep quality, and stress. A final set of EMA items is created based on items' frequency and informativeness, ensuring completeness across diagnoses and minimizing burden. CONCLUSIONS: The described procedure resulted in a feasible EMA protocol to examine psychopathology transdiagnostically. Feasibility was helped by the overlap in mentioned symptoms across disorders. Such overlap raises questions about the validity of DSM categories.

Polygenic Scores and Networks of Psychopathology Symptoms.

Importance: Studies on polygenic risk for psychiatric traits commonly use a disorder-level approach to phenotyping, implicitly considering disorders as homogeneous constructs; however, symptom heterogeneity is ubiquitous, with many possible combinations of symptoms falling under the same disorder umbrella. Focusing on individual symptoms may shed light on the role of polygenic risk in psychopathology. Objective: To determine whether polygenic scores are associated with all symptoms of psychiatric disorders or with a subset of indicators and whether polygenic scores are associated with comorbid phenotypes via specific sets of relevant symptoms. Design, Setting, and Participants: Data from 2 population-based cohort studies were used in this cross-sectional study. Data from children in the Avon Longitudinal Study of Parents and Children (ALSPAC) were included in the primary analysis, and data from children in the Twins Early Development Study (TEDS) were included in confirmatory analyses. Data analysis was conducted from October 2021 to January 2024. Pregnant women based in the Southwest of England due to deliver in 1991 to 1992 were recruited in ALSPAC. Twins born in 1994 to 1996 were recruited in TEDS from population-based records. Participants with available genetic data and whose mothers completed the Short Mood and Feelings Questionnaire and the Strength and Difficulties Questionnaire when children were 11 years of age were included. Main Outcomes and Measures: Psychopathology relevant symptoms, such as hyperactivity, prosociality, depression, anxiety, and peer and conduct problems at age 11 years. Psychological networks were constructed including individual symptoms and polygenic scores for depression, anxiety, attention-deficit/hyperactivity disorder (ADHD), body mass index (BMI), and educational attainment in ALSPAC. Following a preregistered confirmatory analysis, network models were cross-validated in TEDS. Results: Included were 5521 participants from ALSPAC (mean [SD] age, 11.8 [0.14] years; 2777 [50.3%] female) and 4625 participants from TEDS (mean [SD] age, 11.27 [0.69] years; 2460 [53.2%] female). Polygenic scores were preferentially associated with restricted subsets of core symptoms and indirectly associated with other, more distal symptoms of psychopathology (network edges ranged between r = -0.074 and r = 0.073). Psychiatric polygenic scores were associated with specific cross-disorder symptoms, and nonpsychiatric polygenic scores were associated with a variety of indicators across disorders, suggesting a potential contribution of nonpsychiatric traits to comorbidity. For example, the polygenic score for ADHD was associated with a core ADHD symptom, being easily distracted (r = 0.07), and the polygenic score for BMI was associated with symptoms across disorders, including being bullied (r = 0.053) and not thinking things out (r = 0.041). Conclusions and Relevance: Genetic associations observed at the disorder level may hide symptom-level heterogeneity. A symptom-level approach may enable a better understanding of the role of polygenic risk in shaping psychopathology and comorbidity.

Common Cause Versus Dynamic Mutualism: An Empirical Comparison of Two Theories of Psychopathology in Two Large Longitudinal Cohorts.

Mental disorders are among the leading causes of global disease burden. To respond effectively, a strong understanding of the structure of psychopathology is critical. We empirically compared two competing frameworks, dynamic-mutualism theory and common-cause theory, that vie to explain the development of psychopathology. We formalized these theories in statistical models and applied them to explain change in the general factor of psychopathology (p factor) from early to late adolescence (N = 1,482) and major depression in middle adulthood and old age (N = 6,443). Change in the p factor was better explained by mutualism according to model-fit indices. However, a core prediction of mutualism was not supported (i.e., predominantly positive causal interactions among distinct domains). The evidence for change in depression was more ambiguous. Our results support a multicausal approach to understanding psychopathology and showcase the value of translating theories into testable statistical models for understanding developmental processes in clinical sciences.

The LEADING Guideline: Reporting Standards for Expert Panel, Best-Estimate Diagnosis, and Longitudinal Expert All Data (LEAD) Studies.

Background: Accurate assessments of symptoms and illnesses are essential for health research and clinical practice but face many challenges. The absence of a single error-free measure is currently addressed by assessment methods involving experts reviewing several sources of information to achieve a more accurate or best-estimate assessment. Three bodies of work spanning medicine, psychiatry, and psychology propose similar assessment methods: The Expert Panel, the Best-Estimate Diagnosis, and the Longitudinal Expert All Data (LEAD) method. However, the quality of such best-estimate assessments is typically very difficult to evaluate due to poor reporting of the assessment methods and when they are reported, the reporting quality varies substantially. Here, we tackle this gap by developing reporting guidelines for such best-estimate assessment studies. Methods: The development of the reporting guidelines followed a four-stage approach: 1) drafting reporting standards accompanied by rationales and empirical evidence, which were further developed with a patient organization for depression, 2) incorporating expert feedback through a two-round Delphi procedure, 3) refining the guideline based on an expert consensus meeting, and 4) testing the guideline by i) having two researchers test it and ii) using it to examine the extent previously published studies report the standards. The last step also provides evidence for the need for the guideline: 10 to 63% (Mean = 33%) of the standards were not reported across thirty randomly selected studies. Results: The LEADING guideline comprises 20 reporting standards related to four groups: The Longitudinal design (four standards); the Appropriate data (four standards); the Evaluation - experts, materials, and procedures (ten standards); and the Validity group (two standards). Conclusions: We hope that the LEADING guideline will be useful in assisting researchers in planning, conducting, reporting, and evaluating research aiming to achieve best-estimate assessments.

Heterogeneity of outcome measures in depression trials and the relevance of the content of outcome measures to patients: a systematic review.

Research waste occurs when randomised controlled trial (RCT) outcomes are heterogeneous or overlook domains that matter to patients (eg, relating to symptoms or functions). In this systematic review, we reviewed the outcome measures used in 450 RCTs of adult unipolar and bipolar depression registered between 2018 and 2022 and identified 388 different measures. 40% of the RCTs used the same measure (Hamilton Depression Rating Scale [HAMD]). Patients and clinicians matched each item within the 25 most frequently used measures with 80 previously identified domains of depression that matter to patients. Seven (9%) domains were not covered by the 25 most frequently used outcome measures (eg, mental pain and irritability). The HAMD covered a maximum of 47 (59%) of the 80 domains that matter to patients. An interim solution to facilitate evidence synthesis before a core outcome set is developed would be to use the most common measures and choose complementary scales to optimise domain coverage. TRANSLATIONS: For the French and Dutch translations of the abstract see Supplementary Materials section.

A Network Study of Family Affect Systems in Daily Life.

Adolescence is a time period characterized by extremes in affect and increasing prevalence of mental health problems. Prior studies have illustrated how affect states of adolescents are related to interactions with parents. However, it remains unclear how affect states among family triads, that is adolescents and their parents, are related in daily life. This study investigated affect state dynamics (happy, sad, relaxed, and irritated) of 60 family triads, including 60 adolescents (Mage = 15.92, 63.3% females), fathers and mothers (Mage = 49.16). The families participated in the RE-PAIR study, where they reported their affect states in four ecological momentary assessments per day for 14 days. First, we used multilevel vector-autoregressive network models to estimate affect dynamics across all families, and for each family individually. Resulting models elucidated how family affect states were related at the same moment, and over time. We identified relations from parents to adolescents and vice versa, while considering family variation in these relations. Second, we evaluated the statistical performance of the network model via a simulation study, varying the percentage missing data, the number of families, and the number of time points. We conclude with substantive and statistical recommendations for future research on family affect dynamics.

Introducing FRED: Software for Generating Feedback Reports for Ecological Momentary Assessment Data.

Ecological Momentary Assessment (EMA) is a data collection approach utilizing smartphone applications or wearable devices to gather insights into daily life. EMA has advantages over traditional surveys, such as increasing ecological validity. However, especially prolonged data collection can burden participants by disrupting their everyday activities. Consequently, EMA studies can have comparably high rates of missing data and face problems of compliance. Giving participants access to their data via accessible feedback reports, as seen in citizen science initiatives, may increase participant motivation. Existing frameworks to generate such reports focus on single individuals in clinical settings and do not scale well to large datasets. Here, we introduce FRED (Feedback Reports on EMA Data) to tackle the challenge of providing personalized reports to many participants. FRED is an interactive online tool in which participants can explore their own personalized data reports. We showcase FRED using data from the WARN-D study, where 867 participants were queried for 85 consecutive days with four daily and one weekly survey, resulting in up to 352 observations per participant. FRED includes descriptive statistics, time-series visualizations, and network analyses on selected EMA variables. Participants can access the reports online as part of a Shiny app, developed via the R programming language. We make the code and infrastructure of FRED available in the hope that it will be useful for both research and clinical settings, given that it can be flexibly adapted to the needs of other projects with the goal of generating personalized data reports.

Elemental psychopathology: distilling constituent symptoms and patterns of repetition in the diagnostic criteria of the DSM-5.

BACKGROUND: The DSM-5 features hundreds of diagnoses comprising a multitude of symptoms, and there is considerable repetition in the symptoms among diagnoses. This repetition undermines what we can learn from studying individual diagnostic constructs because it can obscure both disorder- and symptom-specific signals. However, these lost opportunities are currently veiled because symptom repetition in the DSM-5 has not been quantified. METHOD: This descriptive study mapped the repetition among the 1419 symptoms described in 202 diagnoses of adult psychopathology in section II of the DSM-5. Over a million possible symptom comparisons needed to be conducted, for which we used both qualitative content coding and natural language processing. RESULTS: In total, we identified 628 distinct symptoms: 397 symptoms (63.2%) were unique to a single diagnosis, whereas 231 symptoms (36.8%) repeated across multiple diagnoses a total of 1022 times (median 3 times per symptom; range 2-22). Some chapters had more repetition than others: For example, every symptom of every diagnosis in the bipolar and related disorders chapter was repeated in other chapters, but there was no repetition for any symptoms of any diagnoses in the elimination disorders, gender dysphoria or paraphilic disorders. The most frequently repeated symptoms included insomnia, difficulty concentrating, and irritability - listed in 22, 17 and 16 diagnoses, respectively. Notably, the top 15 most frequently repeating diagnostic criteria were dominated by symptoms of major depressive disorder. CONCLUSION: Overall, our findings lay the foundation for a better understanding of the extent and potential consequences of symptom overlap.

A narrative systematic review of changes in mental health symptoms from before to during the COVID-19 pandemic.

The onset of the COVID-19 pandemic raised concerns regarding population-wide impacts on mental health. Existing work on the psychological impacts of disaster has identified the potential for multiple response trajectories, with resilience as likely as the development of chronic psychopathology. Early reviews of mental health during the pandemic suggested elevated prevalence rates of multiple forms of psychopathology, but were limited by largely cross-sectional approaches. We conducted a systematic review of studies that prospectively assessed pre- to peri-pandemic changes in symptoms of psychopathology to investigate potential mental health changes associated with the onset of the pandemic (PROSPERO #CRD42021255042). A total of 97 studies were included, covering symptom clusters including obsessive-compulsive disorder (OCD), post-traumatic stress disorder (PTSD), fear, anxiety, depression, and general distress. Changes in psychopathology symptoms varied by symptom dimension and sample characteristics. OCD, anxiety, depression, and general distress symptoms tended to increase from pre- to peri-pandemic. An increase in fear was limited to medically vulnerable participants, and findings for PTSD were mixed. Pre-existing mental health diagnoses unexpectedly were not associated with symptom exacerbation, except in the case of OCD. Young people generally showed the most marked symptom increases, although this pattern was reversed in some samples. Women in middle adulthood in particular demonstrated a considerable increase in anxiety and depression. We conclude that mental health responding during the pandemic varied as a function of both symptom cluster and sample characteristics. Variability in responding should therefore be a key consideration guiding future research and intervention.

Principles and procedures for revising the hierarchical taxonomy of psychopathology.

Quantitative, empirical approaches to establishing the structure of psychopathology hold promise to improve on traditional psychiatric classification systems. The Hierarchical Taxonomy of Psychopathology (HiTOP) is a framework that summarizes the substantial and growing body of quantitative evidence on the structure of psychopathology. To achieve its aims, HiTOP must incorporate emerging research in a systematic, ongoing fashion. In this article, we describe the historical context and grounding of the principles and procedures for revising the HiTOP framework. Informed by strengths and shortcomings of previous classification systems, the proposed revisions protocol is a formalized system focused around three pillars: (a) prioritizing systematic evaluation of quantitative evidence by a set of transparent criteria and processes, (b) balancing stability with flexibility, and (c) promoting inclusion over gatekeeping in all aspects of the process. We detail how the revisions protocol will be applied in practice, including the scientific and administrative aspects of the process. Additionally, we describe areas of the HiTOP structure that will be a focus of early revisions and outline challenges for the revisions protocol moving forward. The proposed revisions protocol is designed to ensure that the HiTOP framework reflects the current state of scientific knowledge on the structure of psychopathology and fulfils its potential to advance clinical research and practice. (PsycInfo Database Record (c) 2023 APA, all rights reserved).

Suicidal ideation across depressive episodes: 9-year longitudinal cohort study.

BACKGROUND: Depression is a highly recurrent disorder, with more than 50% of those affected experiencing a subsequent episode. Although there is relatively little stability in symptoms across episodes, some evidence indicates that suicidal ideation may be an exception. However, these findings warrant replication, especially over longer periods and across multiple episodes. AIMS: To assess the relative stability of suicidal ideation in comparison with other non-core depressive symptoms across episodes. METHOD: We examined 490 individuals with current major depressive disorder (MDD) at baseline and at least one subsequent episode during 9-year follow-up within the Netherlands Study of Depression and Anxiety (NESDA). The Inventory of Depressive Symptomatology (IDS) was used to assess DSM-5 non-core MDD symptoms (fatigue, appetite/weight change, sleep disturbance, psychomotor disturbance, concentration difficulties, worthlessness/guilt, suicidal ideation) at baseline and 2-, 4-, 6- and 9-year follow-up. We examined consistency in symptom presentation (i.e. whether the symptom met the diagnostic threshold, based on a binary categorisation of the IDS) using kappa (κ) and percentage agreement, and stability in symptom severity using Spearman correlation, based on the continuous IDS scores. RESULTS: Out of all non-core depressive symptoms, insomnia appeared the most stable across episodes (r = 0.55-0.69, κ = 0.31-0.47) and weight decrease the least stable (r = 0.03-0.33, κ = 0.06-0.19). For suicidal ideation, correlations across episodes ranged from r = 0.36 to r = 0.55 and consistency ranged from κ = 0.28 to κ = 0.49. CONCLUSIONS: Suicidal ideation is moderately stable in recurrent depression over 9 years. Contrary to prior reports, however, it does not exhibit substantially more stability than most other non-core symptoms of depression.

Studying fine-grained elements of psychopathology to advance mental health science.

Given the now well-recognized limitations of traditional classification systems for research, this editorial proposes to advance mental health science by focusing research efforts on studying fine-grained elements of mental health and illness such as symptoms, mechanisms, and processes. Our own perspectives are informed by three approaches in particular that have gained traction over the last decade: the Hierarchical Taxonomy of Psychopathology, the network or systems approach, and the National Institute of Mental Health Research Domain Criteria. Drawing on these and other perspectives as well as the diverse views of the author teams that contributed to this Special Section, we summarize the state of the field and propose an ambitious plan for the way ahead. Specifically, we propose that embracing pluralistic, multimethod, and multisystem approaches offers a way forward. This will require strategies to reduce research waste and much stronger channels for communication to identify confluence, discoveries, and dead ends within and between disciplines. We are optimistic this will lead to a better understanding of the mechanisms underpinning psychopathology and ultimately to more effective interventions. (PsycInfo Database Record (c) 2023 APA, all rights reserved).

History repeating: guidelines to address common problems in psychedelic science.

Research in the last decade has expressed considerable optimism about the clinical potential of psychedelics for the treatment of mental disorders. This optimism is reflected in an increase in research papers, investments by pharmaceutical companies, patents, media coverage, as well as political and legislative changes. However, psychedelic science is facing serious challenges that threaten the validity of core findings and raise doubt regarding clinical efficacy and safety. In this paper, we introduce the 10 most pressing challenges, grouped into easy, moderate, and hard problems. We show how these problems threaten internal validity (treatment effects are due to factors unrelated to the treatment), external validity (lack of generalizability), construct validity (unclear working mechanism), or statistical conclusion validity (conclusions do not follow from the data and methods). These problems tend to co-occur in psychedelic studies, limiting conclusions that can be drawn about the safety and efficacy of psychedelic therapy. We provide a roadmap for tackling these challenges and share a checklist that researchers, journalists, funders, policymakers, and other stakeholders can use to assess the quality of psychedelic science. Addressing today's problems is necessary to find out whether the optimism regarding the therapeutic potential of psychedelics has been warranted and to avoid history repeating itself.

Using network models to explore the associations between posttraumatic stress disorder symptoms and subjective cognitive functioning.

Several studies have identified relationships between posttraumatic stress disorder (PTSD) and cognitive functioning. Here, we aimed to elucidate the nature of this relationship by investigating cross-sectional associations between subjective cognitive functioning (SCF) and 1) the PTSD sum score, 2) symptom domains, and 3) individual symptoms. We also investigated temporal stability by testing whether results replicated over a 3-year period. We estimated partial correlation networks of DSM-5 PTSD symptoms (at baseline) and SCF (at baseline and follow-up, respectively), using data from the National Health and Resilience in Veterans Study (NHRVS; N = 1484; Mdn = 65 years). The PTSD sum score was negatively associated with SCF. SCF was consistently negatively associated with the PTSD symptom domains 'marked alterations in arousal and reactivity' and 'negative alterations in cognitions and mood', and showed robust relations with the specific symptoms 'having difficulty concentrating' and 'trouble experiencing positive feelings'. Results largely replicated at the 3-year follow-up, suggesting that some PTSD symptoms both temporally precede and are statistically associated with the development or maintenance of reduced SCF. We discuss the importance of examining links between specific PTSD domains and symptoms with SCF-relations obfuscated by focusing on PTSD diagnoses or sum scores-as well as investigating mechanisms underlying these relations. Registration Number: 37069 (https://aspredicted.org/n5sw7.pdf).