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BackgroundAccumulating evidence suggests the COVID-19 pandemic has negative effects on public mental health. Digital interventions that have been developed and evaluated in recent years may be used to mitigate the negative consequences of the pandemic. However, evidence-based recommendations on the use of existing telemedicine and internet-based (eHealth) and app-based mobile health (mHealth) interventions are lacking. ObjectiveThe aim of this study was to investigate the theoretical and empirical base, user perspective, safety, effectiveness, and cost-effectiveness of digital interventions related to public mental health provision (ie, mental health promotion, prevention, and treatment of mental disorders) that may help to reduce the consequences of the COVID-19 pandemic. MethodsA rapid meta-review was conducted. The MEDLINE, PsycINFO, and CENTRAL databases were searched on May 11, 2020. Study inclusion criteria were broad and considered systematic reviews and meta-analyses that investigated digital tools for health promotion, prevention, or treatment of mental health conditions and determinants likely affected by the COVID-19 pandemic. ResultsOverall, 815 peer-reviewed systematic reviews and meta-analyses were identified, of which 83 met the inclusion criteria. Our findings suggest that there is good evidence on the usability, safety, acceptance/satisfaction, and effectiveness of eHealth interventions. Evidence on mHealth apps is promising, especially if social components (eg, blended care) and strategies to promote adherence are incorporated. Although most digital interventions focus on the prevention or treatment of mental disorders, there is some evidence on mental health promotion. However, evidence on process quality, cost-effectiveness, and long-term effects is very limited. ConclusionsThere is evidence that digital interventions are particularly suited to mitigating psychosocial consequences at the population level. In times of physical distancing, quarantine, and restrictions on social contacts, decision makers should develop digital strategies for continued mental health care and invest time and efforts in the development and implementation of mental health promotion and prevention programs.

The Hierarchical Taxonomy of Psychopathology consortium aims to develop a comprehensive self-report measure to assess psychopathology dimensionally. The current research describes the initial conceptualization, development, and item selection for the thought disorder spectrum and related constructs from other spectra. The thought disorder spectrum is defined primarily by the positive and disorganized traits and symptoms of schizophrenia-spectrum disorders. The Thought Disorder Sub-Workgroup identified and defined 16 relevant constructs and wrote 10 to 15 items per each construct. These items were administered, along with detachment and mania items, to undergraduates and people with serious mental illness. Three hundred and sixty-five items across 25 scales were administered. An exploratory factor analysis of the scale scores suggested a two-factor structure corresponding to positive and negative symptoms for two samples. The mania scales loaded with the positive factor, while the detachment scales loaded with the negative factor. Item-level analyses resulted in 19 preliminary scales, including 215 items that cover the range of thought disorder pathology, and will be carried forward for the next phase of data collection/analysis.

The Hierarchical Taxonomy of Psychopathology (HiTOP) is an empirical structural model of psychological symptoms formulated to improve the reliability and validity of clinical assessment. Neurobiology can inform assessments of early risk and intervention strategies, and the HiTOP model has greater potential to interface with neurobiological measures than traditional categorical diagnoses given its enhanced reliability. However, one complication is that observed biological correlates of clinical symptoms can reflect various factors, ranging from dispositional risk to consequences of psychopathology. In this paper, we argue that the HiTOP model provides an optimized framework for conducting research on the biological correlates of psychopathology from an ontogenetic perspective that distinguishes among indicators of liability, current symptoms, and consequences of illness. Through this approach, neurobiological research can contribute more effectively to identifying individuals at high dispositional risk, indexing treatment-related gains, and monitoring the consequences of mental illness, consistent with the aims of the HiTOP framework.
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Genetic discovery in psychiatry and clinical psychology is hindered by suboptimal phenotypic definitions. We argue that the hierarchical, dimensional, and data-driven classification system proposed by the Hierarchical Taxonomy of Psychopathology (HiTOP) consortium provides a more effective approach to identifying genes that underlie mental disorders, and to studying psychiatric etiology, than current diagnostic categories. Specifically, genes are expected to operate at different levels of the HiTOP hierarchy, with some highly pleiotropic genes influencing higher order psychopathology (e.g., the general factor), whereas other genes conferring more specific risk for individual spectra (e.g., internalizing), subfactors (e.g., fear disorders), or narrow symptoms (e.g., mood instability). We propose that the HiTOP model aligns well with the current understanding of the higher order genetic structure of psychopathology that has emerged from a large body of family and twin studies. We also discuss the convergence between the HiTOP model and findings from recent molecular studies of psychopathology indicating broad genetic pleiotropy, such as cross-disorder SNP-based shared genetic covariance and polygenic risk scores, and we highlight molecular genetic studies that have successfully redefined phenotypes to enhance precision and statistical power. Finally, we suggest how to integrate a HiTOP approach into future molecular genetic research, including quantitative and hierarchical assessment tools for future data-collection and recommendations concerning phenotypic analyses. (PsycINFO Database Record (c) 2020 APA, all rights reserved).

ObjectiveDiagnosis is a cornerstone of clinical practice for mental health care providers, yet traditional diagnostic systems have well-known shortcomings, including inadequate reliability, high comorbidity, and marked within-diagnosis heterogeneity. The Hierarchical Taxonomy of Psychopathology (HiTOP) is a data-driven, hierarchically based alternative to traditional classifications that conceptualizes psychopathology as a set of dimensions organized into increasingly broad, transdiagnostic spectra. Prior work has shown that using a dimensional approach improves reliability and validity, but translating a model like HiTOP into a workable system that is useful for health care providers remains a major challenge.MethodThe present work outlines the HiTOP model and describes the core principles to guide its integration into clinical practice.ResultsPotential advantages and limitations of the HiTOP model for clinical utility are reviewed, including with respect to case conceptualization and treatment planning. A HiTOP approach to practice is illustrated and contrasted with an approach based on traditional nosology. Common barriers to using HiTOP in real-world health care settings and solutions to these barriers are discussed.ConclusionsHiTOP represents a viable alternative to classifying mental illness that can be integrated into practice today, although research is needed to further establish its utility. (PsycINFO Database Record (c) 2019 APA, all rights reserved).

The categorical model of personality disorder classification in the American Psychiatric Association's Diagnostic and Statistical Manual of Mental Disorders (5th ed. [DSM-5]; American Psychiatric Association, 2013 ) is highly and fundamentally problematic. Proposed for DSM-5 and provided within Section III (for Emerging Measures and Models) was the Alternative Model of Personality Disorder (AMPD) classification, consisting of Criterion A (self-interpersonal deficits) and Criterion B (maladaptive personality traits). A proposed alternative to the DSM-5 more generally is an empirically based dimensional organization of psychopathology identified as the Hierarchical Taxonomy of Psychopathology (HiTOP; Kotov et al., 2017 ). HiTOP currently includes, at the highest level, a general factor of psychopathology. Further down are the five domains of detachment, antagonistic externalizing, disinhibited externalizing, thought disorder, and internalizing (along with a provisional sixth somatoform dimension) that align with Criterion B. The purpose of this article is to discuss the potential inclusion and placement of the self-interpersonal deficits of the DSM-5 Section III Criterion A within HiTOP.

For more than a century, research on psychopathology has focused on categorical diagnoses. Although this work has produced major discoveries, growing evidence points to the superiority of a dimensional approach to the science of mental illness. Here we outline one such dimensional system-the Hierarchical Taxonomy of Psychopathology (HiTOP)-that is based on empirical patterns of co-occurrence among psychological symptoms. We highlight key ways in which this framework can advance mental-health research, and we provide some heuristics for using HiTOP to test theories of psychopathology. We then review emerging evidence that supports the value of a hierarchical, dimensional model of mental illness across diverse research areas in psychological science. These new data suggest that the HiTOP system has the potential to accelerate and improve research on mental-health problems as well as efforts to more effectively assess, prevent, and treat mental illness.

Background and Hypotheses Affective recovery, operationalized as the time needed for affect to return to baseline levels after daily stressors, may be a putative momentary representation of resilience. This study aimed to investigate affective recovery in positive and negative affect across subclinical and clinical stages of psychosis and whether this is associated with exposure to childhood trauma (sexual, physical, and emotional abuse). Study Design We used survival analysis to predict the time-to-recovery from a daily event-related stressor in a pooled sample of 3 previously conducted experience sampling studies including 113 individuals with first-episode psychosis, 162 at-risk individuals, and 94 controls. Study Results Negative affective recovery (ie, return to baseline following an increase in negative affect) was longer in individuals with first-episode psychosis compared with controls (hazard ratio [HR] = 1.71, 95% confidence interval [CI; 1.03, 2.61], P  = .04) and in at-risk individuals exposed to high vs low levels of emotional abuse (HR = 1.31, 95% CI [1.06, 1.62], P  = .01). Positive affective recovery (ie, return to baseline following a decrease in positive affect) did not differ between groups and was not associated with childhood trauma. Conclusions Our results give first indications that negative affective recovery may be a putative momentary representation of resilience across stages of psychosis and may be amplified in at-risk individuals with prior experiences of emotional abuse. Understanding how affective recovery contributes to the development of psychosis may help identify new targets for prevention and intervention to buffer risk or foster resilience in daily life. [ABSTRACT FROM AUTHOR]

This randomized clinical trial investigates the efficacy of a transdiagnostic ecological momentary intervention for improving self-esteem in youth with low self-esteem and exposure to childhood adversity. Key Points: Question: Can a transdiagnostic, blended ecological momentary intervention improve self-esteem in youth with low self-esteem and prior exposure to childhood adversity? Findings: This randomized clinical trial of 174 youth with low self-esteem and exposure to childhood adversity demonstrated that a novel transdiagnostic ecological momentary intervention improved the primary outcome of self-esteem at postintervention and 6-month follow-up. Small to moderate effect sizes signaled beneficial effects on general psychopathology, quality of life, and other secondary outcomes. Meaning: This trial demonstrated efficacy of a novel transdiagnostic ecological momentary intervention on self-esteem and signaled beneficial effects on secondary outcomes, which needs to be followed by investigating implementation in routine public mental health provision. Importance: Targeting low self-esteem in youth exposed to childhood adversity is a promising strategy for preventing adult mental disorders. Ecological momentary interventions (EMIs) allow for the delivery of youth-friendly, adaptive interventions for improving self-esteem, but robust trial-based evidence is pending. Objective: To examine the efficacy of SELFIE, a novel transdiagnostic, blended EMI for improving self-esteem plus care as usual (CAU) compared with CAU only. Design, Setting, and Participants: This was a 2-arm, parallel-group, assessor-blinded, randomized clinical trial conducted from December 2018 to December 2022. The study took place at Dutch secondary mental health services and within the general population and included youth (aged 12-26 years) with low self-esteem (Rosenberg Self-Esteem Scale [RSES] <26) exposed to childhood adversity. Interventions: A novel blended EMI (3 face-to-face sessions, email contacts, app-based, adaptive EMI) plus CAU or CAU only. Main Outcomes and Measures: The primary outcome was RSES self-esteem at postintervention and 6-month follow-up. Secondary outcomes included positive and negative self-esteem, schematic self-beliefs, momentary self-esteem and affect, general psychopathology, quality of life, observer-rated symptoms, and functioning. Results: A total of 174 participants (mean [SD] age, 20.7 [3.1] years; 154 female [89%]) were included in the intention-to-treat sample, who were primarily exposed to childhood emotional abuse or neglect, verbal or indirect bullying, and/or parental conflict. At postintervention, 153 participants (87.9%) and, at follow-up, 140 participants (80.5%), provided primary outcome data. RSES self-esteem was, on average, higher in the experimental condition (blended EMI + CAU) than in the control condition (CAU) across both postintervention and follow-up as a primary outcome (B = 2.32; 95% CI, 1.14-3.50; P <.001; Cohen d-type effect size [hereafter, Cohen d] = 0.54). Small to moderate effect sizes were observed suggestive of beneficial effects on positive (B = 3.85; 95% CI, 1.83-5.88; P <.001; Cohen d = 0.53) and negative (B = −3.78; 95% CI, −6.59 to −0.98; P =.008; Cohen d = −0.38) self-esteem, positive (B = 1.58; 95% CI, 0.41-2.75; P =.008; Cohen d = 0.38) and negative (B = −1.71; 95% CI, −2.93 to −0.48; P =.006; Cohen d = −0.39) schematic self-beliefs, momentary self-esteem (B = 0.29; 95% CI, 0.01-0.57; P =.04; Cohen d = 0.24), momentary positive affect (B = 0.23; 95% CI, 0.01-0.45; P =.04; Cohen d = 0.20), momentary negative affect (B = −0.33; 95% CI, −0.59 to −0.03, P =.01, Cohen d = −0.27), general psychopathology (B = −17.62; 95% CI, −33.03 to −2.21; P =.03; Cohen d = −0.34), and quality of life (B = 1.16; 95% CI, 0.18-2.13; P =.02; Cohen d = 0.33) across postintervention and follow-up. No beneficial effects on symptoms and functioning were observed. Conclusions and Relevance: A transdiagnostic, blended EMI demonstrated efficacy on the primary outcome of self-esteem and signaled beneficial effects on several secondary outcomes. Further work should focus on implementing this novel EMI in routine public mental health provision. Trial Registration: Dutch Trial Register Identifier:NL7129(NTR7475) [ABSTRACT FROM AUTHOR]