The associations between daily reports of loneliness and psychotic experiences in the early risk stages for psychosis.

AIM: Bi-directional associations between loneliness and psychotic experiences (PEs) have been reported, but the mechanisms underlying these associations are unknown. This study aims to explore associations between daily reports of loneliness and PEs, and test differences in this association across young adult individuals at different levels of risk for psychosis. METHODS: We analysed 90-day diary data on loneliness and PEs from N = 96 participants (mean age 24.7, range 18-35, 77% female) divided into 4 subgroups, each indexing increased levels of risk for psychosis according to the clinical staging model: 'psychometric' (n = 25), 'low' (n = 27), 'mild' (n = 24), and 'ultra-high'(n = 20) risk. Multilevel vector autoregressive models examined within-day (contemporaneous) and between-day (temporal) associations between loneliness and PEs for the total sample. Next, these associations were compared across subgroups. RESULTS: Loneliness and PEs were significantly associated contemporaneously (partial correlation B = 0.14) but not temporally. Subgroup membership moderated both contemporaneous and temporal associations. The contemporaneous association between loneliness and PEs was stronger in the low-risk subgroup compared to the mild-risk (B = -0.35, p < .01) and ultra-high-risk (B = -0.36, p < .01) subgroups. The temporal association between loneliness on the previous day and PEs on the current day was stronger in mild-risk subgroup compared to the ultra-high-risk subgroup (B = -0.03, p = .03). After adjusting for multiple testing, only the contemporaneous-but not the temporal-associations remained statistically significant. CONCLUSIONS: Loneliness is associated with PEs in individuals at risk for psychosis, particularly in those with low to mild symptoms. Our findings tentatively suggest that especially individuals with low expressions of PEs may be more sensitive to social context, but future studies are needed to replicate and further unravel the potentially stage-specific interplay between social context and PEs.

Relating stability of individual dynamical networks to change in psychopathology.

One hypothesis flowing from the network theory of psychopathology is that symptom network structure is associated with psychopathology severity and in turn, one may expect that individual network structure changes with the level of psychopathology severity. However, this expectation has rarely been addressed directly. This study aims to examine (1) the stability of individual contemporaneous symptom networks over a one-year period and (2) whether network stability is associated with a change in psychopathology. We used daily diary data of n = 66 individuals, located along the psychosis severity continuum, from two separate 90-day periods, one year apart (t = 180). Based on the newly developed Individual Network Invariance Test (INIT) to assess symptom-network stability, participants were divided into two groups with stable and unstable networks and we tested whether these groups differed in their absolute change in psychopathology severity. The majority of the sample (n = 51, 77.3%) showed a stable network over time while most individuals showed a decrease in psychopathological severity. We found no significant association between a change in psychopathology severity and individual network stability. Our results call for further critical evaluation of the association between networks and psychopathology to optimize the implementation of clinical applications based on current methods.

Mental health, risk and protective factors at micro- and macro-levels across early at-risk stages for psychosis: The Mirorr study.

BACKGROUND: The clinical staging model states that psychosis develops through subsequent stages of illness severity. To better understand what drives illness progression, more extensive comparison across clinical stages is needed. The current paper presents an in-depth characterization of individuals with different levels of risk for psychosis (i.e., different early clinical stages), using a multimethod approach of cross-sectional assessments and daily diary reports. METHODS: Data came from the Mirorr study that includes N = 96 individuals, divided across four subgroups (n1  = 25, n2  = 27, n3  = 24, and n4  = 20). These subgroups, each with an increasing risk for psychosis, represent clinical stages 0-1b. Cross-sectional data and 90-day daily diary data on psychopathology, well-being, psychosocial functioning, risk and protective factors were statistically compared across subgroups (stages) and descriptively compared across domains and assessment methods. RESULTS: Psychopathology increased across subgroups, although not always linearly and nuanced differences were seen between assessment methods. Well-being and functioning differed mostly between subgroup 1 and the other subgroups, suggesting differences between non-clinical and clinical populations. Risk and protective factors differed mostly between the two highest and lowest subgroups, especially regarding need of social support and coping, suggesting differences between those with and without substantial psychotic experiences. Subgroup 4 (stage 1b) reported especially high levels of daily positive and negative psychotic experiences. CONCLUSIONS: Risk for psychosis exists in larger contexts of mental health and factors of risk and protection that differ across stages and assessment methods. Taking a broad, multi-method approach is an important next step to understand the complex development of youth mental health problems.

Dynamic symptom networks across different at-risk stages for psychosis: An individual and transdiagnostic perspective.

The clinical staging model distinguishes different stages of mental illness. Early stages, are suggested to be more mild, diffuse and volatile in terms of expression of psychopathology than later stages. This study aimed to compare individual transdiagnostic symptom networks based on intensive longitudinal data between individuals in different early clinical stages for psychosis. It was hypothesized that with increasing clinical stage (i) density of symptom networks would increase and (ii) psychotic experiences would be more central in the symptom networks. Data came from a 90-day diary study, resulting in 8640 observations within N = 96 individuals, divided over four subgroups representing different early clinical stages (n1 = 25, n2 = 27, n3 = 24, n4 = 20). Sparse Time Series Chain Graphical Models were used to create individual contemporaneous and temporal symptom networks based on 10 items concerning symptoms of depression, anxiety, psychosis, non-specific and vulnerability domains. Network density and symptom centrality (strength) were calculated individually and compared between and within the four subgroups. Level of psychopathology increased with clinical stage. The symptom networks showed large between-individual variation, but neither network density not psychotic symptom strength differed between the subgroups in the contemporaneous (pdensity = 0.59, pstrength > 0.51) and temporal (pdensity = 0.75, pstrength > 0.35) networks. No support was found for our hypothesis that higher clinical stage comes with higher symptom network density or a more central role for psychotic symptoms. Based on the high inter-individual variability, our results highlight the importance of individualized assessment of symptom networks.