Evidence for mood instability in patients with bipolar disorder: Applying multilevel hidden Markov modeling to intensive longitudinal ecological momentary assessment data.

Bipolar disorder (BD) is a chronic psychiatric condition characterized by large episodic changes in mood and energy. Recently, BD has been proposed to be conceptualized as chronic cyclical mood instability, as opposed to the traditional view of alternating discrete episodes with stable periods in-between. Recognizing this mood instability may improve care and call for high-frequency measures coupled with advanced statistical models.

The temporal order of emotional, cognitive, and behavioral gains in daily life during treatment of depression.

Objective: Despite the importance for understanding mechanisms of change, little is known about the order of change in daily life emotions, cognitions, and behaviors during treatment of depression. This study examined the within-person temporal order of emotional, cognitive, and behavioral improvements using ecological momentary assessment data.

Method: Thirty-two individuals with diagnosed depression completed ecological momentary assessment questions on emotions (sad mood, happy mood), behaviors (social interaction, number of activities), and cognitive variables (worrying, negative self-thoughts) 5 times a day during a 4-month period in which they underwent psychotherapy for depression.

Monitoring emotional intensity and variability to forecast depression recurrence in real time in remitted adults.

Objective: Recurrent depressive episodes are preceded by changing mean levels of repeatedly assessed emotions (e.g., feeling restless), which can be detected in real time using statistical process control (SPC).

Predicting recurrence of depression using cardiac complexity in individuals tapering antidepressants.

It is currently unknown whether the complexity and variability of cardiac dynamics predicts future depression and whether within-subject change herein precedes the recurrence of depression. We tested this in an innovative repeated single-subject study in individuals who had a history of depression and were tapering their antidepressants. In 50 individuals, electrocardiogram (ECG) derived Interbeat-interval (IBI) time-series data were collected for 5 min every morning and evening, for 4 months.

Recurrence of depression can be foreseen by monitoring mental states with statistical process control.

Detecting early signs of recurrence of psychopathology is key for prevention and treatment. Personalized risk assessment is especially relevant for formerly depressed patients, for whom recurrence is common. We aimed to examine whether recurrence of depression can be accurately foreseen by applying Exponentially Weighted Moving Average (EWMA) statistical process control charts to Ecological Momentary Assessment (EMA) data.

[Ecological momentary assessment as a clinical tool in psychiatry: promises, pitfalls, and possibilities].

Background: Ecological momentary assessment (EMA) is a promising method to gain insight into the daily lives of people with mental disorders. EMA can be used to monitor mood, symptoms, and experiences multiple times per day. Using advanced statistical methods, such as network analysis, as EMA feedback might result in novel insights that are relevant to psychiatric care.

Transitions in depression: if, how, and when depressive symptoms return during and after discontinuing antidepressants.

Purpose: The aim of the current study is to provide insight into if, how, and when meaningful changes occur in individual patients who discontinue antidepressant medication. Agreement between macro-level quantitative symptom data, qualitative ratings, and micro-level Ecological Momentary Assessments is examined.

Methods: During and shortly after antidepressant discontinuation, depressive symptoms and 'feeling down' were measured in 56 participants, using the SCL-90 depression subscale weekly (macro-level) for 6 months, and 5 Ecological Momentary Assessments daily (micro-level) for 4 months (30.

Daily dynamics of negative affect: indicators of rate of response to treatment and remission from depression?

More instability (MSSD) and variability (SD) of negative affect (NA) have been related to current and future depressive symptoms. We investigated whether NA instability and variability were predictive of the rate of symptom improvement during treatment and of reaching remission status. Forty-six individuals with major depressive disorder completed six days of ecological momentary assessments (10 beeps/day) before starting a combination of pharmacotherapy and supportive therapy.

A Web-Based Application for Personalized Ecological Momentary Assessment in Psychiatric Care: User-Centered Development of the PETRA Application.

Background: Smartphone self-monitoring of mood, symptoms, and contextual factors through ecological momentary assessment (EMA) provides insights into the daily lives of people undergoing psychiatric treatment. Therefore, EMA has the potential to improve their care. To integrate EMA into treatment, a clinical tool that helps clients and clinicians create personalized EMA diaries and interpret the gathered data is needed.

Feasibility, usability and clinical value of intensive longitudinal diary assessments in older persons with cognitive impairment and depressive symptoms.

Objectives: To evaluate the feasibility, usability and clinical value of daily diary assessments combined with actigraphy in older persons with cognitive impairment.

Methods: For 63 days, patients ≥60 years with cognitive impairments filled out a daily diary (including standardized questionnaires and cognitive test battery), and wore an actiwatch (sleep). After the study, participants and clinicians received personal feedback about patterns and daily triggers of depressive symptoms, sleep and cognitive performance.

Real-time monitoring of increases in restlessness to assess idiographic risk of recurrence of depressive symptoms.

Background: This confirmatory study aimed to examine whether we can foresee recurrence of depressive symptoms using personalized modeling of rises in restlessness.

Methods: Participants were formerly depressed patients ( = 41) in remission who (gradually) discontinued antidepressants. Participants completed five smartphone-based Ecological Momentary Assessments (EMA) a day, for a period of 4 months, yielding a total of 21 180 observations.

Anticipating manic and depressive transitions in patients with bipolar disorder using early warning signals.

Background: In bipolar disorder treatment, accurate episode prediction is paramount but remains difficult. A novel idiographic approach to prediction is to monitor generic early warning signals (EWS), which may manifest in symptom dynamics. EWS could thus form personalized alerts in clinical care.

A Narrative Review of Network Studies in Depression: What Different Methodological Approaches Tell Us About Depression.

The network theory of psychopathology proposes that mental disorders arise from direct interactions between symptoms. This theory provides a promising framework to understand the development and maintenance of mental disorders such as depression. In this narrative review, we summarize the literature on network studies in the field of depression.

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.

Single-Subject Research in Psychiatry: Facts and Fictions.

Scientific evidence in the field of psychiatry is mainly derived from group-based ("nomothetic") studies that yield group-aggregated results, while often the need is to answer questions that apply to individuals. Particularly in the presence of great inter-individual differences and temporal complexities, information at the individual-person level may be valuable for personalized treatment decisions, individual predictions and diagnostics. The single-subject study design can be used to make inferences about individual persons.

Recommendations for the use of long-term experience sampling in bipolar disorder care: a qualitative study of patient and clinician experiences.

Background: Self-monitoring has been shown to improve the self-management and treatment of patients with bipolar disorder. However, current self-monitoring methods are limited to once-daily retrospectively assessed mood, which may not suit the rapid mood fluctuations in bipolar disorder. The experience sampling method (ESM), which assesses mood in real-time several times a day, may overcome these limitations.

Correction to: Feasibility and predictors of change of narrative exposure therapy for displaced populations: a repeated measures design.

[This corrects the article DOI: 10.1186/s40814-020-00613-1.].

Virtual reality based cognitive behavioral therapy for paranoia: Effects on mental states and the dynamics among them.

Background: Negative affective processes may contribute to maintenance of paranoia in patients with psychosis, and vice versa. Successful treatment may break these pathological symptom networks. This study examined whether treatment with virtual reality based cognitive behavioral therapy (VR-CBT) for paranoia influences momentary affective states, and whether VR-CBT changes the adverse interplay between affective states and paranoia.

Feasibility and predictors of change of narrative exposure therapy for displaced populations: a repeated measures design.

Background: Displaced victims of interpersonal violence, such as refugees, asylum seekers, and victims of sexual exploitation, are growing in numbers and are often suffering from a post-traumatic stress disorder (PTSD). At the same time, these victims are known to benefit less from trauma-focused therapy (TFT) and to be less compliant to treatment. The objective of this paper is to describe the rationale and research protocol of an ongoing trial that aims to evaluate different variables that might influence the feasibility of TFT for the study population.

Sudden gains in day-to-day change: Revealing nonlinear patterns of individual improvement in depression.

Objective: We examined individual overall trajectories of change and the occurrence of sudden gains in daily self-rated problem severity and the relation of these patterns to treatment response.

Method: Mood disorder patients ( = 329, mean age = 44, 55% women) completed daily self-ratings about the severity of their complaints as a standard part of treatment, using the Therapy Process Questionnaire (TPQ). Per individual, the best-fitting defined (linear, log-linear, 1-step) trajectory was tested for significance: for change over time, and for specificity of the best-fitting trajectory.

Insights of Patients and Clinicians on the Promise of the Experience Sampling Method for Psychiatric Care.

Objective: This qualitative study aimed to map the relevance of the experience sampling method (ESM) for psychiatric practice and identify barriers and facilitators for implementation, as perceived by patients and clinicians.

Methods: Participants were 22 patients with various diagnoses and 21 clinicians (e.g.

What do centrality measures measure in psychological networks?

Centrality indices are a popular tool to analyze structural aspects of psychological networks. As centrality indices were originally developed in the context of social networks, it is unclear to what extent these indices are suitable in a psychological network context. In this article we critically examine several issues with the use of the most popular centrality indices in psychological networks: degree, betweenness, and closeness centrality.