The “at risk mental state” for psychosis approach has been a catalytic, highly productive research paradigm over the last 25 years. In this paper we review that paradigm and summarize its key ...lessons, which include the valence of this phenotype for future psychosis outcomes, but also for comorbid, persistent or incident non‐psychotic disorders; and the evidence that onset of psychotic disorder can at least be delayed in ultra high risk (UHR) patients, and that some full‐threshold psychotic disorder may emerge from risk states not captured by UHR criteria. The paradigm has also illuminated risk factors and mechanisms involved in psychosis onset. However, findings from this and related paradigms indicate the need to develop new identification and diagnostic strategies. These findings include the high prevalence and impact of mental disorders in young people, the limitations of current diagnostic systems and risk identification approaches, the diffuse and unstable symptom patterns in early stages, and their pluripotent, transdiagnostic trajectories. The approach we have recently adopted has been guided by the clinical staging model and adapts the original “at risk mental state” approach to encompass a broader range of inputs and output target syndromes. This approach is supported by a number of novel modelling and prediction strategies that acknowledge and reflect the dynamic nature of psychopathology, such as dynamical systems theory, network theory, and joint modelling. Importantly, a broader transdiagnostic approach and enhancing specific prediction (profiling or increasing precision) can be achieved concurrently. A holistic strategy can be developed that applies these new prediction approaches, as well as machine learning and iterative probabilistic multimodal models, to a blend of subjective psychological data, physical disturbances (e.g., EEG measures) and biomarkers (e.g., neuroinflammation, neural network abnormalities) acquired through fine‐grained sequential or longitudinal assessments. This strategy could ultimately enhance our understanding and ability to predict the onset, early course and evolution of mental ill health, further opening pathways for preventive interventions.
In recent years, there has been increased focus on subthreshold stages of mental disorders, with attempts to model and predict which individuals will progress to full-threshold disorder. Given this ...research attention and the clinical significance of the issue, this article analyzes the assumptions of the theoretical models in the field.
Psychiatric research into predicting the onset of mental disorder has shown an overreliance on one-off sampling of cross-sectional data (ie, a snapshot of clinical state and other risk markers) and may benefit from taking dynamic changes into account in predictive modeling. Cross-disciplinary approaches to complex system structures and changes, such as dynamical systems theory, network theory, instability mechanisms, chaos theory, and catastrophe theory, offer potent models that can be applied to the emergence (or decline) of psychopathology, including psychosis prediction, as well as to transdiagnostic emergence of symptoms.
Psychiatric research may benefit from approaching psychopathology as a system rather than as a category, identifying dynamics of system change (eg, abrupt vs gradual psychosis onset), and determining the factors to which these systems are most sensitive (eg, interpersonal dynamics and neurochemical change) and the individual variability in system architecture and change. These goals can be advanced by testing hypotheses that emerge from cross-disciplinary models of complex systems. Future studies require repeated longitudinal assessment of relevant variables through either (or a combination of) micro-level (momentary and day-to-day) and macro-level (month and year) assessments. Ecological momentary assessment is a data collection technique appropriate for micro-level assessment. Relevant statistical approaches are joint modeling and time series analysis, including metric-based and model-based methods that draw on the mathematical principles of dynamical systems. This next generation of prediction studies may more accurately model the dynamic nature of psychopathology and system change as well as have treatment implications, such as introducing a means of identifying critical periods of risk for mental state deterioration.
Identifying young people at risk of developing serious mental illness and identifying predictors of onset of illness has been a focus of psychiatric prediction research, particularly in the field of ...psychosis. Work in this area has facilitated the adoption of the clinical staging model of early clinical phenotypes, ranging from at-risk mental states to chronic and severe mental illness. It has been a topic of debate if these staging models should be conceptualised as disorder-specific or transdiagnostic. In order to inform this debate and facilitate cross-diagnostic discourse, the present scoping review provides a broad overview of the body of literature of (a) longitudinal at-risk approaches and (b) identified antecedents of (homotypic) illness progression across three major mental disorders psychosis, bipolar disorder (BD) and depression, and places these in the context of clinical staging. Stage 0 at-risk conceptualisations (i.e. familial high-risk approaches) were identified in all three disorders. However, formalised stage 1b conceptualisations (i.e. ultra-high-risk approaches) were only present in psychosis and marginally in BD. The presence of non-specific and overlapping antecedents in the three disorders may support a general staging model, at least in the early stages of severe psychotic or mood disorders.
Abstract During recent years, a decrease has been noted in the rate of transition of ultra-high risk (UHR) clients to a psychotic disorder. Although important to the concept of the at-risk mental ...state, the reasons for this decline remain largely unknown. We investigated the possibility of a ‘dilution effect’ in contributing to the decline, i.e. if later UHR cohorts present with less severe clinical intake characteristics than earlier cohorts. Firstly, clinical intake characteristics of a large UHR sample (n = 397) were compared across baseline year epochs (1995–2006). Characteristics showing significant differences were included in a Cox-regression to examine if they could explain the decline in transition rates. Secondly, because later cohorts show lower transition rates, ‘more stringent’ UHR-criteria were retrospectively applied to these cohorts (post-2000, n = 219), investigating if this resulted in a higher transition rate. Results indicated that earlier cohorts presented with (1) a larger array of attenuated psychotic symptoms, (2) higher ratings on conceptual disorganization (formal thought disorder) and (3) a higher proportion of individuals with trait risk factor (all P < .001). However, these factors could not fully account for the decline in transition rates. Applying more stringent UHR-criteria to the post-2000-subsample did not substantially change the rate of transition. Our study suggests that later UHR cohorts presented with different clinical intake characteristics than earlier cohorts. While this may have contributed to the observed decrease in transition rates to psychosis, it does not appear to fully account for this decline, suggesting other factors have also impacted on transition rates over time.
Temporal genomic data hold great potential for studying evolutionary processes such as speciation. However, sampling across speciation events would, in many cases, require genomic time series that ...stretch well back into the Early Pleistocene subepoch. Although theoretical models suggest that DNA should survive on this timescale
, the oldest genomic data recovered so far are from a horse specimen dated to 780-560 thousand years ago
. Here we report the recovery of genome-wide data from three mammoth specimens dating to the Early and Middle Pleistocene subepochs, two of which are more than one million years old. We find that two distinct mammoth lineages were present in eastern Siberia during the Early Pleistocene. One of these lineages gave rise to the woolly mammoth and the other represents a previously unrecognized lineage that was ancestral to the first mammoths to colonize North America. Our analyses reveal that the Columbian mammoth of North America traces its ancestry to a Middle Pleistocene hybridization between these two lineages, with roughly equal admixture proportions. Finally, we show that the majority of protein-coding changes associated with cold adaptation in woolly mammoths were already present one million years ago. These findings highlight the potential of deep-time palaeogenomics to expand our understanding of speciation and long-term adaptive evolution.
Most psychiatric disorders develop during adolescence and young adulthood and are preceded by a phase during which attenuated or episodic symptoms and functional decline are apparent. The ...introduction of the ultra-high risk (UHR) criteria two decades ago created a new framework for identification of risk and for pre-emptive psychiatry, focusing on first episode psychosis as an outcome. Research in this paradigm demonstrated the comorbid, diffuse nature of emerging psychopathology and a high degree of developmental heterotopy, suggesting the need to adopt a broader, more agnostic approach to risk identification. Guided by the principles of clinical staging, we introduce the concept of a pluripotent at-risk mental state. The clinical high at risk mental state (CHARMS) approach broadens identification of risk beyond psychosis, encompassing multiple exit syndromes such as mania, severe depression, and personality disorder. It does not diagnostically differentiate the early stages of psychopathology, but adopts a "pluripotent" approach, allowing for overlapping and heterotypic trajectories and enabling the identification of both transdiagnostic and specific risk factors. As CHARMS is developed within the framework of clinical staging, clinical utility is maximized by acknowledging the dimensional nature of clinical phenotypes, while retaining thresholds for introducing specific interventions. Preliminary data from our ongoing CHARMS cohort study (
= 114) show that 34% of young people who completed the 12-month follow-up assessment (
= 78) transitioned from Stage 1b (attenuated syndrome) to Stage 2 (full disorder). While not without limitations, this broader risk identification approach might ultimately allow reliable, transdiagnostic identification of young people in the early stages of severe mental illness, presenting further opportunities for targeted early intervention and prevention strategies.
Positive affect (PA) plays a crucial role in the development, course, and recovery of depression. Recently, we showed that a therapeutic application of the experience sampling method (ESM), ...consisting of feedback focusing on PA in daily life, was associated with a decrease in depressive symptoms. The present study investigated whether the experience of PA increased during the course of this intervention.
Multicentre parallel randomized controlled trial. An electronic random sequence generator was used to allocate treatments.
University, two local mental health care institutions, one local hospital.
102 pharmacologically treated outpatients with a DSM-IV diagnosis of major depressive disorder, randomized over three treatment arms.
Six weeks of ESM self-monitoring combined with weekly PA-focused feedback sessions (experimental group); six weeks of ESM self-monitoring combined with six weekly sessions without feedback (pseudo-experimental group); or treatment as usual (control group).
The interaction between treatment allocation and time in predicting positive and negative affect (NA) was investigated in multilevel regression models.
102 patients were randomized (mean age 48.0, SD 10.2) of which 81 finished the entire study protocol. All 102 patients were included in the analyses. The experimental group did not show a significant larger increase in momentary PA during or shortly after the intervention compared to the pseudo-experimental or control groups (χ2(2) = 0.33, p = .846). The pseudo-experimental group showed a larger decrease in NA compared to the control group (χ2(1) = 6.29, p =.012).
PA-focused feedback did not significantly impact daily life PA during or shortly after the intervention. As the previously reported reduction in depressive symptoms associated with the feedback unveiled itself only after weeks, it is conceivable that the effects on daily life PA also evolve slowly and therefore were not captured by the experience sampling procedure immediately after treatment.
Trialregister.nl/trialreg/index.asp. NTR1974.
•Self-monitoring of emotions improved negative emotion differentiation in depression.•Improvement of positive emotion differentiation was not statistically significant.•Emotion differentiation ...changes were not proportional to the number of self-reports.
Major depressive disorder has been linked to an inability to differentiate between negative emotions. The current study investigates whether emotion differentiation improves when individuals with major depressive disorder are required to report on specific emotions multiple times a day through the experience sampling method (ESM) – a structured self-report diary technique.
Seventy-nine patients diagnosed with major depressive disorder participated in this study, of whom 55 used ESM for 6 weeks (3 days a week, 10 times a day). Changes from baseline to post assessment in positive and negative emotion differentiation were compared between the participants who did and those who did not use ESM.
Engaging in ESM related to an improvement in both positive and negative emotion differentiation, but only the latter reached statistical significance. The relationship between the number of ESM measurements (dose) and emotion differentiation change (response) was not significant.
The sample size for the dose-response analysis was relatively small (N = 55). It is unknown whether emotion differentiation improvements generalize beyond the emotions (N = 12) we probed in this study. Other factors could also have contributed to the change (e.g., meetings with the researchers).
The present study suggests that patients with depression using ESM for 3 days a week for 6 weeks can improve their negative emotion differentiation. Future studies should assess after what period of ESM changes in emotion differentiation become apparent, and whether these changes are persistent and relate to actual improvement in depressive symptoms.
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