Dimensional and discrete variations on the psychosis continuum in a Dutch crowd-sourcing population sample.

BACKGROUND: Mild psychotic experiences are common in the general population. Although transient and benign in most cases, these experiences are predictive of later mental health problems for a significant minority. The goal of the present study was to perform examinations of the dimensional and discrete variations in individuals' reporting of subclinical positive and negative psychotic experiences in a unique Dutch internet-based sample from the general population. METHODS: Positive and negative subclinical psychotic experiences were measured with the Community Assessment of Psychic Experiences in 2870 individuals. First, the prevalence of these experiences and their associations with demographics, affect, psychopathology and quality of life were investigated. Next, latent class analysis was used to identify data-driven subgroups with different symptom patterns, which were subsequently compared on aforementioned variables. RESULTS: Subclinical psychotic experiences were commonly reported. Both positive and negative psychotic experiences were associated with younger age, more negative affect, anxiety and depression as well as less positive affect and poorer quality of life. Seven latent classes ('Low psychotic experiences', 'Lethargic', 'Blunted', 'Distressed', 'Paranormal', 'Distressed/grandiose' and 'Distressed/positive psychotic experiences') were identified that demonstrated both dimensional differences in the number/severity of psychotic experiences and discrete differences in the patterns of reported experiences. CONCLUSION: Subclinical psychotic experiences show both dimensional severity variations and discrete symptom-pattern variations across individuals. To understand and capture all interindividual variations in subclinical psychotic experiences, their number, nature and context (co-occurrence patterns) should be considered at the same time. Only some psychotic experiences may lay on a true psychopathological psychosis continuum.

Casting wider nets for anxiety and depression: disability-driven cross-diagnostic subtypes in a large cohort.

BACKGROUND: In search of empirical classifications of depression and anxiety, most subtyping studies focus solely on symptoms and do so within a single disorder. This study aimed to identify and validate cross-diagnostic subtypes by simultaneously considering symptoms of depression and anxiety, and disability measures. METHOD: A large cohort of adults (Lifelines, n = 73 403) had a full assessment of 16 symptoms of mood and anxiety disorders, and measurement of physical, social and occupational disability. The best-fitting subtyping model was identified by comparing different hybrid mixture models with and without disability covariates on fit criteria in an independent test sample. The best model's classes were compared across a range of external variables. RESULTS: The best-fitting Mixed Measurement Item Response Theory model with disability covariates identified five classes. Accounting for disability improved differentiation between people reporting isolated non-specific symptoms ['Somatic' (13.0%), and 'Worried' (14.0%)] and psychopathological symptoms ['Subclinical' (8.8%), and 'Clinical' (3.3%)]. Classes showed distinct associations with clinically relevant external variables [e.g. somatization: odds ratio (OR) 8.1-12.3, and chronic stress: OR 3.7-4.4]. The Subclinical class reported symptomatology at subthreshold levels while experiencing disability. No pure depression or anxiety, but only mixed classes were found. CONCLUSIONS: An empirical classification model, incorporating both symptoms and disability identified clearly distinct cross-diagnostic subtypes, indicating that diagnostic nets should be cast wider than current phenomenology-based categorical systems.