On the transience or stability of subthreshold psychopathology

The Identification and Management of Subthreshold Depression and Anxiety in Primary Care for People With Long-Term Conditions

Background: Subthreshold depression (sDep) and anxiety (sAnx) are common conditions and are associated with significant suffering, impaired functioning, increased healthcare utilisation and economic costs. Furthermore, they are risk factors for crossing the clinical threshold and developing mental health disorders. Subthreshold conditions are associated with long-term conditions (LTCs). This scoping review aimed to explore the identification and management of sDep and sAnx in primary care for patients with LTCs. Methods: We conducted a scoping review, following the Joanna Briggs Institute (JBI) Manual for Evidence Synthesis. Medline, PsycInfo, CINAHL and International Pharmaceutical Abstracts were searched for articles prior to September 2023. We included studies written in English that were conducted among the adult population. All studies that aimed to identify and manage sDep and anxiety in patients with LTC in primary care have been included. Results: Thirty-three articles were included in this scoping review, of which seven studies incorporated an intervention component for sDep and sAnx in patients with LTCs. A variety of definitions and screening tools were used to identify sDep and sAnx. Problem-solving therapy (PST) and behavioural activation (BA) were the most common intervention components and showed promising results. Limitations: We excluded studies that did not explicitly state the terms 'subthreshold', 'subclinical' or 'subsyndromal' depression or anxiety which may be relevant. Conclusion: There is currently limited evidence regarding the identification and management of sDep and sAnx in patients with LTCs, warranting further research.

Prevalence and risk of subthreshold anxiety developing into threshold anxiety disorder in the general population

BACKGROUND

Subthreshold anxiety may act as a critical precursor and risk factor for the onset of threshold anxiety. However, accurate prevalence rates of subthreshold anxiety and its role in leading to threshold anxiety require further elucidation.

METHODS

We conducted a search on PubMed and Web of Science using predefined criteria and identified 45 articles with a total of 278,971 individuals to estimate the prevalence rates using a random effects model. The incidence risk ratio (IRR) was estimated by comparing the proportion of individuals with subthreshold anxiety who developed threshold anxiety to those without subthreshold anxiety in seven articles involving 18,693 individuals.

RESULTS

Our analysis revealed an overall prevalence of subthreshold anxiety of 6.19%. Specifically, among individuals with subthreshold generalized anxiety disorders, adolescents show the highest prevalence (9.47%), outpacing adults (4.69%) and the elderly (3.49%). Further analysis of seven studies showed an increased risk of developing threshold anxiety in individuals with subthreshold anxiety (IRR = 2.63), with a higher transition rate (9.59%) compared to those without subthreshold anxiety (3.65%).

CONCLUSIONS

Anxiety disorders may be conceptualized as a spectrum, with subthreshold anxiety serving as a significant prodromal state and risk factor for the development of threshold anxiety. Proactive management of subthreshold anxiety represents an effective approach for the prevention of its progression to threshold anxiety. Future research should investigate the risk of progression from subthreshold to threshold anxiety across various types, and explore how factors, such as social support and personality traits facilitate this progression.

Understanding the transdiagnostic mechanisms underlying emerging psychopathology in adolescence: study protocol of a 1-year prospective epidemiological (EMERGE) study

INTRODUCTION

Adolescent mental health is a global public health challenge as most cases remain undetected and untreated, and consequently, have a high likelihood of persistence or recurrence. It is critical to improve early detection of mental disorders and to target individuals experiencing subclinical symptoms. However, most indicated prevention approaches have been developed for risk syndromes of specific mental disorders. This contradicts the increasing recognition of emerging psychopathology as a complex system characterised by rapid shifts in subclinical symptoms, cutting across diagnostic categories and interacting with each other over time. Therefore, this study aims to examine the dynamic course, pattern and network of subclinical symptoms and transdiagnostic mechanisms over time.

METHOD AND ANALYSIS

The EMERGE-study is a prospective, naturalistic, 1-year follow-up study. A general population sample of 1196 adolescents will be recruited. Inclusion criteria are age between 11 and 17 years, German language skills, main residency in Switzerland and access to internet. Individuals will be excluded if they have a current or lifetime axis I mental disorder. Assessments of subclinical symptoms of several mental disorders and potential transdiagnostic mechanisms will be conducted at baseline and at 3-month, 6-month, 9-month and 12-month follow-up. Structural equation modelling will be used to estimate the homotypic and heterotypic patterns of subclinical symptoms and the associations with transdiagnostic mechanisms. Latent growth mixture modelling and growth mixture survival analysis will be carried out to identify subclasses of individuals with different trajectories of subclinical symptoms that may be predictive of an onset of a mental disorder. Network analysis will be applied to assess the centrality of subclinical symptoms and how networks of emerging psychopathology change over time.

ETHICS AND DISSEMINATION

Ethical approval was obtained from the Bern Cantonal Ethics Committee (ID 2020-02108). All findings will be disseminated by publication in peer-reviewed scientific journals and by presentation of the results to conferences and stakeholder organisation events.

A longitudinal study of the impact of childhood adversity dimensions on social and psychological factors and symptoms of psychosis, depression, and anxiety

The present study examined three empirically-derived childhood adversity dimensions as predictors of social, psychological, and symptom outcomes across three prospective assessments of a young adult sample. Participants were assessed five times over eight years with semi-structured interviews and questionnaires. The analyses used the dimensions underlying multiple subscales from well-established childhood adversity measures administered at the first two assessment waves (described in a previous report). Outcome data pertain to the last three assessment waves, with sample sizes ranging from 89 to 169. As hypothesized, the childhood adversity dimensions demonstrated overlapping and differential longitudinal associations with the outcomes. Deprivation predicted the negative (deficit-like) dimension of psychosis, while Threat and Intrafamilial Adversity predicted the positive (psychotic-like) dimension. Depression and anxiety symptoms were predicted by different childhood adversity dimensions over time. Furthermore, Threat predicted a smaller and less diverse social network, Intrafamilial Adversity predicted anxious attachment, and Deprivation predicted a smaller social network, anxious and avoidant attachment, perceived social support, and loneliness. The three adversity dimensions combined accounted for moderate to large proportions of variance in several outcomes. These results extend prior work by identifying associations of three meaningful dimensions of childhood adversity with different risk profiles across psychological, social, and psychopathological domains. The findings enhance our understanding of the impact of childhood adversity across young adulthood.

Using unsupervised clustering approaches to identify common mental health profiles and associated mental health-care service-use patterns in Ontario, Canada

Mental health is a complex, multidimensional concept that goes beyond clinical diagnoses, including psychological distress, life stress, and well-being. In this study, we aimed to use unsupervised clustering approaches to identify multidimensional mental health profiles that exist in the population, and their associated service-use patterns. The data source was the 2012 Canadian Community Health Survey-Mental Health, linked to administrative health-care data; all Ontario, Canada, adult respondents were included. We used a partitioning around medoids clustering algorithm with Gower's proximity to identify groups with distinct combinations of mental health indicators and described them according to their sociodemographic and service-use characteristics. We identified 4 groups with distinct mental health profiles, including 1 group that met the clinical threshold for a depressive diagnosis, with the remaining 3 groups expressing differences in positive mental health, life stress, and self-rated mental health. The 4 groups had different age, employment, and income profiles and exhibited differential access to mental health-care services. This study represents the first step in identifying complex profiles of mental health at the population level in Ontario. Further research is required to better understand the potential causes and consequences of belonging to each of the mental health profiles identified. This article is part of a Special Collection on Mental Health.

Transdiagnostic symptom networks in relation to mental health service use in community youth

OBJECTIVE

The objective of this study is to scrutinize whether psychopathology symptom networks differ between those with and without lifetime: treatment seeking, treatment and treatment of longer duration.

METHODS

We created non-exclusive groups of subjects with versus without lifetime treatment seeking, treatment and treatment of mid-long-term duration. We estimated Ising models and carried out network comparison tests (NCTs) to compare (a) overall connectivity and (b) network structure. Furthermore, we examined node strength. We used propensity score matching (PSM) to minimize potential confounding by indication for service use.

RESULTS

Based on data from 9,172 participants, there were no statistically significant differences in overall connectivity and network structure in those with versus without lifetime: treatment seeking (p = .75 and p = .82, respectively), treatment (p = .63 and p = .49, respectively) and treatment of mid-longterm duration (p = .15 and p = .62, respectively). Notably, comparing networks with versus without service use consistently revealed higher node strength in 'obsessions' and 'aggression' and lower node strength in 'elevated mood' in all networks with service use.

CONCLUSIONS

Findings suggest that after adjusting for potential confounding by indication for service use, there was no indication of an association in overall connectivity or network structure for lifetime treatment seeking, treatment and treatment of longer duration. However, selected structurally important symptoms differed consistently in all three comparisons. Our findings highlight the potential of network analysis methods to examine treatment mechanisms and outcomes. Specifically, more granular network characteristics on the node level may complement and enrich traditional outcomes in clinical research.