Early Warning Signals Based on Momentary Affect Dynamics can Expose Nearby Transitions in Depression:A Confirmatory Single-Subject Time-Series Study

Background: In complex systems early warning signals such as rising autocorrelation, variance and network connectivity are hypothesized to anticipate relevant shifts in a system. For direct evidence hereof in depression, designs are needed in which early warning signals and symptom transitions are prospectively assessed within an individual. Therefore, this study aimed to detect personalized early warning signals preceding the occurrence of a major symptom transition. Methods: Six single-subject time-series studies were conducted, collecting frequent observations of momentary affective states during a time-period when participants were at increased risk of a symptom transition. Momentary affect states were reported three times a day over three to six months (95-183 days). Depressive symptoms were measured weekly using the Symptom CheckList-90. Presence of sudden symptom transitions was assessed using change point analysis. Early warning signals were analysed using moving window techniques. Results: As change point analysis revealed a significant and sudden symptom transition in one participant in the studied period, early warning signals were examined in this person. Autocorrelation (r=0·51; p<2.2e-16), and variance (r=0·53; p<2.2e-16) in 'feeling down', and network connectivity (r=0·42; p<2.2e-16) significantly increased a month before this transition occurred. These early warnings also preceded the rise in absolute levels of 'feeling down' and the participant's personal indication of risk for transition. Conclusions: This study replicated the findings of a previous study and confirmed the presence of rising early warning signals a month before the symptom transition occurred. Results show the potential of early warning signals to improve personalized risk assessment in the field of psychiatry

On the transience of stability of subthreshold psychopathology

Symptoms of psychopathology lie on a continuum ranging from mental health to psychiatric disorders. Although much research has focused on progression along this continuum, for most individuals, subthreshold symptoms do not escalate into full-blown disorders. This study investigated how the stability of psychopathological symptoms (attractor strength) varies across severity levels (homebase). Data were retrieved from the TRAILS TRANS-ID study, where 122 at-risk young adults (mean age 23.6 years old, 57% males) monitored their mental states daily for a period of six months (± 183 observations per participant). We estimated each individual’s homebase and attractor strength using generalized additive mixed models. Regression analyses showed no association between homebases and attractor strengths (linear model: B = 0.02, p = 0.47, R(2) < 0.01; polynomial model: B < 0.01, p = 0.61, R(2) < 0.01). Sensitivity analyses where we (1) weighed estimates according to their uncertainty and (2) removed individuals with a DSM-5 diagnosis from the analyses did not change this finding. This suggests that stability is similar across severity levels, implying that subthreshold psychopathology may resemble a stable state rather than a transient intermediate between mental health and psychiatric disorder. Our study thus provides additional support for a dimensional view on psychopathology, which implies that symptoms differ in degree rather than kind

Individual-specific and subgroup level associations between stress and psychopathology in daily life:A temporal network investigation

INTRODUCTION: Stress is a risk factor for developing psychopathology. Emerging evidence suggests that daily experiences of stress may also predict symptoms during the day. It is unclear to what extent the influence of stress on psychopathology during the day is the same across individuals (including across diagnostic boundaries), and which effects are individual-specific OBJECTIVES: This study aims to reveal how stress and symptoms are interrelated in a cross-diagnostic context by modeling individual level temporal networks, and examining subgroups with similar dynamics. METHODS: Hundred twenty two young adults (43.4% women) with a wide range of psychopathology in terms of severity and type of problems completed a six-month daily diary study. We used a temporal network approach (i.e., group iterative multiple model estimation) to model how stress and ten specific symptoms (e.g., feeling down, paranoia, restlessness) were related across time at the individual-specific, subgroup, and group level. RESULTS: After controlling for the lagged influence of stress on itself, stress level predicted the level of restlessness, worrying, nervousness, and feeling down during the same day for >70% of individuals. We observed three larger subgroups with each over 20 individuals, whose temporal networks showed different dynamic patterns involving specific symptoms. Effects of stress on other specific symptoms differed across individuals, and these were not subgroup-specific. CONCLUSIONS: This study showed important overlap between individuals in terms of impact of stress on psychopathology in daily life. Subtle differences between individuals were also observed. Possibly, such differences are relevant for examining individual-specific vulnerability for future psychopathology. This requires further investigation. DISCLOSURE: No significant relationships

Early warning signals and critical transitions in psychopathology:challenges and recommendations

Empirical evidence is mounting that monitoring momentary experiences for the presence of early warning signals (EWS) may allow for personalized predictions of meaningful symptom shifts in psychopathology. Studies aiming to detect EWS require intensive longitudinal measurement designs that center on individuals undergoing change. We recommend that researchers: (a) define criteria for relevant symptom shifts a priori to allow specific hypothesis testing; (b) balance the observation period length and high-frequency measurements with participant burden by testing ambitious designs with pilot studies; (c) choose variables that are meaningful to their patient group and facilitate replication by others. Thoroughly considered designs are necessary to assess the promise of EWS as a clinical tool to detect, prevent or encourage impending symptom changes in psychopathology