Emotion dynamics concurrently and prospectively predict mood psychopathology

Emotion Dynamics among Late Adolescents and Emerging Adults: The Role of Maternal Privacy Invasion Perceptions

Prior research suggests that youth experience immediate emotional distress following privacy invasion, but it is unclear whether and how persistent privacy invasion over longer periods destabilizes the intrapersonal emotional regulatory functions that privacy serves. This study investigated whether late adolescents and emerging adults who reported different patterns of maternal privacy invasion over a full academic year showed differences in emotion regulation, as reflected by the frequency and lability of negative and positive emotional experiences. Participants were first-year university students (n = 349; 60.2% female) in Hong Kong, aged 17 to 24 (MT1 = 18.20, SDT1 = 1.10). They self-reported maternal privacy invasion perceptions and negative and positive emotions 16 times, at bi-weekly intervals. Latent class growth analyses divided participants into a Higher Invasion Perceptions group (24.9%), a Moderate Invasion Perceptions group (46.4%), and a Lower Invasion Perceptions group (28.7%). A one-way MANCOVA examined potential differences in negative and positive emotion dynamics across groups, indexed by frequency (means) and instability (mean square of successive differences and probability of acute change). In line with predictions, both the Higher Invasion and Moderate Invasion groups reported higher negative emotion frequency and instability, compared to the Lower Invasion group. However, groups showed no significant differences regarding positive emotion frequency and instability. The findings indicate that perceptions of maternal privacy invasion predict youth's negative emotion regulation processes over their first collegiate year. Prolonged, higher levels of maternal privacy invasion may disrupt the intrapersonal regulatory functions that privacy serves over time.

Affective Instability: Impact of Fluctuating Emotions on Regulation and Psychological Well-Being

Previous research has focused on understanding the occurrence of intense and fluctuating emotions and the ability to manage these emotions and affective states. These phenomena have been, respectively, labeled as affective instability and emotion regulation and have been studied among individuals diagnosed with borderline personality disorder (BPD), attention-deficit/hyperactivity disorder (ADHD), bipolar disorder (BD), and post-traumatic stress disorder (PTSD). Previous findings suggest that affective instability may be associated with poorer psychological well-being. The present study aims to investigate the general tendency of affective instability and capacity for emotional regulation among college students, regardless of a previous psychological diagnosis, and to understand the relationship between these processes and psychological well-being. Three questionnaires were administered to measure levels of affective instability, the ability to manage fluctuating affective states, and overall psychological well-being. The findings suggest that (1) individuals with diagnoses experience affective lability and difficulty regulating emotions at a greater rate than those without, (2) higher affective lability scores are consistent with more significant emotion dysregulation and lower overall psychological well-being, and (3) scores on the Affective lability Scale (ALS) and the Difficulties in Emotional Regulation Scale (DERS) are reliable predictors of one's estimated Global Assessment of Functioning (GAF) scores. Although causation has not been established, the evidence suggests that individuals with diagnoses experience greater difficulty in regulating their emotions, have greater affective lability, and experience diminished psychological well-being and day-to-day functionality. Certain anecdotal evidence suggests that emotional lability can be endogenous and affect multiple aspects of an individual's social, occupational, and personal life. By revising the existing literature and the present findings, the authors provide insights into the significance of endogenous factors in the context of affective lability and offer suggestions for future research.

Characterizing the dynamics, reactivity and controllability of moods in depression with a Kalman filter

BACKGROUND

Mood disorders involve a complex interplay between multifaceted internal emotional states, and complex external inputs. Dynamical systems theory suggests that this interplay between aspects of moods and environmental stimuli may hence determine key psychopathological features of mood disorders, including the stability of mood states, the response to external inputs, how controllable mood states are, and what interventions are most likely to be effective. However, a comprehensive computational approach to all these aspects has not yet been undertaken.

METHODS

Here, we argue that the combination of ecological momentary assessments (EMA) with a well-established dynamical systems framework-the humble Kalman filter-enables a comprehensive account of all these aspects. We first introduce the key features of the Kalman filter and optimal control theory and their relationship to aspects of psychopathology. We then examine the psychometric and inferential properties of combining EMA data with Kalman filtering across realistic scenarios. Finally, we apply the Kalman filter to a series of EMA datasets comprising over 700 participants with and without symptoms of depression.

RESULTS

The results show a naive Kalman filter approach performs favourably compared to the standard vector autoregressive approach frequently employed, capturing key aspects of the data better. Furthermore, it suggests that the depressed state involves alterations to interactions between moods; alterations to how moods responds to external inputs; and as a result an alteration in how controllable mood states are. We replicate these findings qualitatively across datasets and explore an extension to optimal control theory to guide therapeutic interventions.

CONCLUSIONS

Mood dynamics are richly and profoundly altered in depressed states. The humble Kalman filter is a well-established, rich framework to characterise mood dynamics. Its application to EMA data is valid; straightforward; and likely to result in substantial novel insights both into mechanisms and treatments.

Sleep and circadian disruption in bipolar disorders: From psychopathology to digital phenotyping in clinical practice

Sleep and biological rhythms are integral to mood regulation across the lifespan, particularly in bipolar disorder (BD), where alterations in sleep phase, structure, and duration occur in all mood states. These disruptions are linked to poorer quality of life, heightened suicide risk, impaired cognitive function, and increased relapse rates. This review highlights the pathophysiology of sleep disturbances in BD and aims to consolidate understanding and clinical applications of these phenomena. It also summarizes the evolution of sleep and biological rhythms assessment methods, including ecological momentary assessment (EMA) and digital phenotyping. It underscores the importance of recognizing circadian rhythm involvement in mood regulation, suggesting potential therapeutic targets. Future research directions include elucidating circadian clock gene mechanisms, understanding environmental impacts on circadian rhythms, and investigating the bidirectional relationship between sleep disturbances and mood regulation in BD. Standardizing assessment methods and addressing privacy concerns related to EMA technology and digital phenotyping are essential for advancing research. Collaborative efforts are crucial for enhancing clinical applicability and understanding the broader implications of biological rhythms in BD diagnosis and treatment. Overall, recognizing the significance of sleep and biological rhythms in BD offers promise for improved outcomes through targeted interventions and a deeper understanding of the disorder's underlying mechanisms.

Network analyses of ecological momentary emotion and avoidance assessments before and after cognitive behavioral therapy for anxiety disorders

Negative emotions and associated avoidance behaviors are core symptoms of anxiety. Current treatments aim to resolve dysfunctional coupling between them. However, precise interactions between emotions and avoidance in patients' everyday lives and changes from pre- to post-treatment remain unclear. We analyzed data from a randomized controlled trial where patients with anxiety disorders underwent 16 sessions of cognitive behavioral therapy (CBT). Fifty-six patients (68 % female, age: M = 33.31, SD = 12.45) completed ecological momentary assessments five times a day on 14 consecutive days before and after treatment, rating negative emotions and avoidance behaviors experienced within the past 30 min. We computed multilevel vector autoregressive models to investigate contemporaneous and time-lagged associations between anxiety, depression, anger, and avoidance behaviors within patients, separately at pre- and post-treatment. We examined pre-post changes in network density and avoidance centrality, and related these metrics to changes in symptom severity. Network density significantly decreased from pre- to post-treatment, indicating that after therapy, mutual interactions between negative emotions and avoidance were attenuated. Specifically, contemporaneous associations between anxiety and avoidance observed before CBT were no longer significant at post-treatment. Effects of negative emotions on avoidance assessed at a later time point (avoidance instrength) decreased, but not significantly. Reduction in avoidance instrength positively correlated with reduction in depressive symptom severity, meaning that as patients improved, they were less likely to avoid situations after experiencing negative emotions. Our results elucidate mechanisms of successful CBT observed in patients' daily lives and may help improve and personalize CBT to increase its effectiveness.

Association of Positive, Negative, and Disorganized Schizotypy With the Temporal Dynamics of Schizotypic Experiences in Daily Life

BACKGROUND AND HYPOTHESIS

Schizotypy is a useful and unifying construct for examining the etiology, development, and expression of schizophrenia-spectrum psychopathology. The positive, negative, and disorganized schizotypy dimensions are associated with distinct patterns of schizophrenia-spectrum symptoms and impairment. Furthermore, they are differentiated by mean levels of psychotic-like, suspicious, negative, and disorganized schizotypic experiences in daily life, and by temporal dynamics of affect. The schizotypy dimensions were thus hypothesized to be differentiated by the temporal dynamics of schizotypic experiences in daily life.

STUDY DESIGN

The present study employed experience sampling methodology in a large nonclinically ascertained sample (n = 693) to examine the associations of multidimensional schizotypy with psychotic-like, suspicious, negative, and disorganized schizotypic experiences in daily life, as well as with their temporal dynamics (variability, reactivity, inertia, and instability).

STUDY RESULTS

We replicated the mean-level associations between multidimensional schizotypy and schizotypic experiences in daily life. Furthermore, positive, negative, and disorganized schizotypy demonstrated hypothesized, differential patterns of temporal dynamics of schizotypic experiences. Disorganized schizotypy demonstrated the most robust associations, including intensity, variability, and inertia of disorganized schizotypic experiences. Disorganized schizotypy also moderated reactivity of psychotic-like and disorganized schizotypic experiences following previously reported stress. Positive schizotypy was associated with intensity and variability of psychotic-like experiences. Negative schizotypy was associated with intensity and variability of negative schizotypic experiences.

CONCLUSIONS

The findings indicate that schizotypy dimensions can be differentiated by both mean levels and temporal patterns of psychotic-like, suspicious, negative, and disorganized schizotypic experiences in daily life, with disorganized schizotypy uniquely characterized by stress reactivity.

RSA instability in mothers of preschoolers and adolescents is related to observations of supportive parenting behaviors

Respiratory sinus arrhythmia (RSA; a measure of respiratory modulation of vagal control of heart rate) is a dynamic process. For mothers, RSA functioning has been associated with depressive symptoms and coincides with supportive parenting. However, research has largely focused on RSA suppression (i.e., difference score from rest to stress task). The present study examined depressive symptoms and supportive parenting with RSA instability-a dynamic measure of the magnitude of RSA change across a task. In two samples of mothers (N = 210), one with preschoolers (Study 1: n = 108, Mage = 30.68 years, SD = 6.06, 47.0% Black, 43.0% White) and one with adolescents (Study 2: n = 102, Mage = 35.51, SD = 6.51, 75.2% Black), RSA instability was calculated during an interaction task. In both studies, instrumental supportive parenting behaviors were negatively related to RSA instability. Findings provide preliminary support for RSA instability as an indicator of physiological dysregulation for mothers.

Insomnia symptom severity and dynamics of arousal-related symptoms across the day

Arousal is a central component of many emotional symptoms and can contribute to insomnia. Here we assessed how the timing and fluctuating nature of arousal-related symptoms over the course of the day relate to insomnia symptom severity. In this study, 361 participants (M age = 31.9 years, 282 women, 77 men, 2 non-binary individuals) completed the Insomnia Severity Index to assess severity of insomnia symptoms, followed by repeated ratings of anxiety or nervousness, stress, sleepiness, and feeling down via their mobile phone between ~08:00 hours and 00:00 hours across 1 day. Measures of dynamics included: mean levels across the day; variation (standard deviation); instability (mean squared successive differences); and resistance to change/inertia (first-order autocorrelation). Time-of-day patterns were modelled using generalized additive mixed effects models. Insomnia symptom severity (mean Insomnia Severity Index = 9.1, SD = 5.2, range 0-25) was associated with higher mean levels of all arousal-related symptoms, and increased instability and variation throughout the day in anxiety or nervousness, stress, and feeling down. Resistance to change (inertia) was not associated with insomnia symptom severity. Generalized additive mixed effects analyses showed that while individuals with more severe insomnia symptoms had elevated symptoms across the entire day, they were especially more anxious or nervous and sleepy in the early morning (~08:00 hours), anxious or nervous, stressed and sleepy in the late afternoon/early evening (~16:00 hours-21:00 hours), and anxious or nervous and stressed in the late evening (~22:00 hours). Remarkably, higher arousal occurred in the presence of high subjective sleepiness. Together these results indicate that insomnia symptom severity is associated with problems with daytime and evening arousal regulation.

Limited evidence of autocorrelation signaling upcoming affective episodes: a 12-month e-diary study in patients with bipolar disorder

BACKGROUND

Increased autocorrelation (AR) of system-specific measures has been suggested as a predictor for critical transitions in complex systems. Increased AR of mood scores has been reported to anticipate depressive episodes in major depressive disorder, while other studies found AR increases to be associated with depressive episodes themselves. Data on AR in patients with bipolar disorders (BD) is limited and inconclusive.

METHODS

Patients with BD reported their current mood via daily e-diaries for 12 months. Current affective status (euthymic, prodromal, depressed, (hypo)manic) was assessed in 26 bi-weekly expert interviews. Exploratory analyses tested whether self-reported current mood and AR of the same item could differentiate between prodromal phases or affective episodes and euthymia.

RESULTS

A total of 29 depressive and 20 (hypo)manic episodes were observed in 29 participants with BD. Self-reported current mood was significantly decreased during the two weeks prior to a depressive episode (early prodromal, late prodromal), but not changed prior to manic episodes. The AR was neither a significant predictor for the early or late prodromal phase of depression nor for the early prodromal phase of (hypo)mania. Decreased AR was found in the late prodromal phase of (hypo)mania. Increased AR was mainly found during depressive episodes.

CONCLUSIONS

AR changes might not be better at predicting depressive episodes than simple self-report measures on current mood in patients with BD. Increased AR was mostly found during depressive episodes. Potentially, changes in AR might anticipate (hypo)manic episodes.

Daily stigma and daily emotional well-being among people living with HIV: Testing a buffering hypothesis of social support during the COVID-19 pandemic

This study examined the relationship between daily perceived stigma and daily emotional well-being among people living with HIV/AIDS during the COVID-19 pandemic. Additionally, a buffering effect of perceived emotional support on this relationship was verified. The participants were 133 patients with a medically confirmed diagnosis of HIV infection. Data were collected using online diaries completed every evening for five consecutive weekdays in three bursts separated by 6 months. Dynamic multilevel analyses showed a significant positive autoregressive effect for daily stigma in each burst. Additionally, increased stigma predicts increased negative affect and decreased positive affect the next day. However, these effects differed across bursts. Thus, to some extent, daily HIV/AIDS stigma was found to predict a decrease in affective well-being the next day. The buffering effect of perceived emotional support reduced this decline but was also time-limited, probably because of the later established direction in these relationships at the individual level and/or because of changes in the course of the pandemic. The results provide insights on the role of daily stigma in shaping affective well-being, suggesting that it may be a significant source of short-term negative emotional consequences for PWLH.

An initial test of the contrast avoidance model in bipolar spectrum disorders

The Contrast Avoidance Model suggests that individuals sensitive to negative emotional shifts use prior increases in negative affect to prevent further escalation in response to adverse situations, while the heightened negative affect amplifies positive emotional contrasts when encountering unexpected positive events. Individuals with bipolar spectrum disorders (BSDs), characterized by shifts between (hypo)manic and depressive episodes, may undergo more salient emotional contrasts. Drawing from the Contrast Avoidance Model, the shifts from depression to (hypo)mania can be conceptualized as positive emotional contrasts, potentially heightening the perceived pleasure during (hypo)manic episodes. On the other hand, the shifts from (hypo)manic to depressive episodes can be viewed as negative emotional contrasts, contributing to the challenges associated with depressive states. Despite the intriguing potential of this interplay, the link between the Contrast Avoidance Model and BSDs has never been empirically tested. Our study addressed this gap by examining group differences in contrast avoidance traits between individuals with BSDs, unipolar depression, and healthy controls in a large cohort study (N = 536). Results indicated that individuals with BSDs exhibited significantly higher scores in the total, and Discomfort with Negative Emotional Shifts and Avoidance of Negative Emotional Contrasts/Enhancement of Positive Emotional Contrasts factors, as well as separate item scores on the Contrast Avoidance Questionnaire-General Emotion (CAQ-GE), compared to those with unipolar depression and healthy controls. Although marginal, the BD II subtype demonstrated a stronger inclination to avoid negative emotional contrasts compared to BD I. These findings suggest that contrast avoidance may be a psychological mechanism implicated in BSDs.

Neurophysiological responses to emotional faces predict dynamic fluctuations in affect in adolescents

The ability to accurately identify and interpret others' emotions is critical for social and emotional functioning during adolescence. Indeed, previous research has identified that laboratory-based indices of facial emotion recognition and engagement with emotional faces predict adolescent mood states. Whether socioemotional information processing relates to real-world affective dynamics using an ecologically sensitive approach, however, has rarely been assessed. In the present study, adolescents (N = 62; ages 13-18) completed a Facial Recognition Task, including happy, angry, and sad stimuli, while EEG data were acquired. Participants also provided ecological momentary assessment (EMA) data probing their current level of happiness, anger, and sadness for 1-week, resulting in indices of emotion (mean-level, inertia, instability). Analyses focused on relations between (1) accuracy for and (2) prolonged engagement with (LPP) emotional faces and EMA-reported emotions. Greater prolonged engagement with happy faces was related to less resistance to changes in happiness (i.e., less happiness inertia), whereas greater prolonged engagement with angry faces associated with more resistance to changes in anger (i.e., greater anger inertia). Results suggest that socioemotional processes captured by laboratory measures have real-world implications for adolescent affective states and highlight potentially actionable targets for novel treatment approaches (e.g., just-in-time interventions). Future studies should continue to assess relations among socioemotional informational processes and dynamic fluctuations in adolescent affective states.

A cognitive-computational account of mood swings in adolescence

Teenagers have a reputation for being fickle, in both their choices and their moods. This variability may help adolescents as they begin to independently navigate novel environments. Recently, however, adolescent moodiness has also been linked to psychopathology. Here, we consider adolescents' mood swings from a novel computational perspective, grounded in reinforcement learning (RL). This model proposes that mood is determined by surprises about outcomes in the environment, and how much we learn from these surprises. It additionally suggests that mood biases learning and choice in a bidirectional manner. Integrating independent lines of research, we sketch a cognitive-computational account of how adolescents' mood, learning, and choice dynamics influence each other, with implications for normative and psychopathological development.

Beyond traditional metrics: A novel method for measuring mood instability in bipolar disorder

Background

Clinical care for bipolar disorder (BD) has a narrow focus on prevention and remission of episodes with pre/post treatment reductions in symptom severity as the 'gold standard' for outcomes in clinical trials and measurement-based care strategies. The study aim was to provide a novel method for measuring outcomes in BD that has clinical utility and can stratify individuals with BD based on mood instability.

Methods

Participants were 603 with a BD (n=385), other or non-affective disorder (n=71), or no psychiatric history (n=147) enrolled in an intensive longitudinal cohort for at least 10 years that collects patient reported outcomes measures (PROMs) assessing depression, (hypo)mania, anxiety, and functioning every two months. Mood instability was calculated as the within-person variance of PROMs and stratified into low, moderate, and high thresholds, respectively.

Outcomes

Individuals with BD had significantly higher mood instability index's for depression, (hypo)mania, and anxiety compared to psychiatric comparisons (moderate effects, p's<.001) and healthy controls (large effects, p's<.001). A significantly greater proportion of individuals with BD fell into the moderate (depression: 52·8%; anxiety: 51·4%; (hypo)mania: 48·3%) and high instability thresholds (depression: 11·5%; anxiety: 9·1%; (hypo)mania: 10·8%) compared to psychiatric comparisons (moderate: 25·5 - 26·6%; high: 0% - 4·7%) and healthy controls (moderate: 2·9% - 17·1%; high: 0% - 1·4%). Being in the high or moderate instability threshold predicted worse health functioning (p's < .00, small to large effects).

Interpretation

Mood instability, as measured in commonly used PROMs, characterized the course of illness over time, correlated with functional outcomes, and significantly differentiated those with BD from healthy controls and psychiatric comparisons. Results suggest a paradigm shift in monitoring outcomes in BD, by measuring mood instability as a primary outcome index.

Childhood abuse and neglect and profiles of adult emotion dynamics

Childhood maltreatment (CM) is experienced by ∼40% of all children at major personal and societal costs. The divergent associations between emotional, physical, and sexual abuse or neglect in childhood and differences in adult emotional functioning and regulation were examined in terms of daily emotion intensity, variability, instability, inertia, and diversity, reported over 30 days by 290 Dutch aged 19-73. Participants described their abuse/neglect experiences retrospectively using the Childhood Trauma Questionnaire (CTQ). Dissecting CM effects on adult emotion dynamics may inform theories on the ontogenesis and functioning of emotions, on effects of abuse and neglect, to better understand (dys)functional emotional development, and to prevent their adverse sequelae. Structural equation models (SEM) showed that most types of CM were associated with specific patterns of emotion dynamics, and only emotional abuse had no unique effects on the emotional dynamic indices. Emotional neglect was associated with most measures of emotion dynamics (i.e., less intense, variable, unstable, and diverse emotions). Sexual abuse associated with increases and physical neglect decreases in negative affect variability and instability. Physical abuse was associated with inertia but with a small effect size. Social contact frequency did not mediate much of the relationship between CM types and emotion dynamics.

Respiratory sinus arrhythmia (RSA) dynamics matter for children's emotion regulation: RSA inertia and instability within a stress task

The present study employed two key dynamic indicators (i.e., inertia and instability) to the psychophysiological research of child emotion regulation (ER) and examined whether respiratory sinus arrhythmia (RSA) dynamics were associated with child ER during a stress task. Eighty-nine Chinese school-age children (Mage  = 8.77 years, SD = 1.80 years; 46.1% girls) and their primary caregivers participated in the study. After controlling for RSA static reactivity, multiple regression analyses indicated that lower RSA inertia was related to fewer in-task negative emotions rated by children and their caregivers, and higher RSA instability was associated with better child trait ER. This study introduces physiological indicators of the dynamic aspects of parasympathetic activity to the study of child ER.

Social jetlag and trajectories of mood symptoms and reward responsiveness in individuals at low-risk, high-risk, and with bipolar spectrum disorders: An ecological momentary assessment study

A specific type of sleep disruption, social jetlag, involves an incongruence of sleep time between weekends and weekdays. This study investigated relationships between social jetlag and mood symptom lability and trajectories of daily reward responsiveness and mood symptoms. Participants (N = 130) from three groups (moderate reward sensitivity, high reward sensitivity, and high reward sensitivity with a diagnosed bipolar spectrum disorder [BSD]) were recruited from an ongoing longitudinal study based on their self-reported reward sensitivity and a diagnostic interview. For this study, they completed 20 days of ecological momentary assessment (EMA) of reward responsiveness and mood symptoms and a daily sleep diary. Social jetlag was significantly associated with differences in trajectories of depressive symptoms between groups. Specifically, greater social jetlag was associated with a greater increase in depressive symptoms over the 20 days for participants in the high reward sensitivity and BSD groups compared to the moderate reward sensitivity group. Social jetlag also was significantly associated with depressive symptom lability during the EMA period, but this finding was reduced to a trend toward significance when controlling for self-reported sleep duration. The study adds to the literature with methodological strengths including the EMA design and assessment of symptom and reward responsiveness trajectories.

The added value of daily diary data in 1- and 3-year prediction of psychopathology and psychotic experiences in individuals at risk for psychosis

This study aimed to assess whether adding information on psychological experiences derived from a daily diary to baseline cross-sectional data could improve short- (1-year) and long-term (3-years) prediction of psychopathology and positive psychotic experiences (PEs). We used 90-day daily diary data from 96 individuals in early subclinical risk stages for psychosis. Stepwise linear regression models were built for psychopathology and PEs at 1- and 3-years follow-up, adding: (1) baseline questionnaires, (2) the mean and variance of daily psychological experiences, and (3) individual symptom network density. We assessed whether similar results could be achieved with a subset of the data (7-14- and 30-days). The mean and variance of the diary improved model prediction of short- and long-term psychopathology and PEs, compared to prediction based on baseline questionnaires solely. Similar results were achieved with 7-14- and 30-day subsets. Symptom network density did not improve model prediction except for short-term prediction of PEs. Simple metrics, i.e., the mean and variance from 7 to 14 days of daily psychological experiences assessments, can improve short- and long-term prediction of both psychopathology and PEs in individuals in early subclinical stages for psychosis. Diary data could be a valuable addition to clinical risk prediction models for psychopathology development.

A Person-Centered Approach to Emotional Security: Latent Profile Analysis of the Dark Triad and Psychological Symptoms

Few studies have examined emotional security utilizing a person-centered approach. Therefore, in the present study, we conceptualized a multidimensional construct that includes psychological symptoms (i.e., depression, anxiety, and stress) and the dark triad traits (i.e., Machiavellianism, narcissism, and psychopathy). Applying latent profile analysis (LPA) allows the exploration of the interaction of emotional security with the dark triad traits and psychological symptoms in the sample at the level of sub-classes. Depression, stress, anxiety, Machiavellianism, narcissism, and psychopathy were determined as profile indicators. Moreover, satisfaction with life and the psychological well-being of the sub-classes were predicted. Data were gathered from 558 participants (418 females, %74.9) with an average age of 22.44 years). LPA indicated four distinct profiles: 'High emotional security and low psychological symptoms, and dark triad traits' (22%), 'Low emotional security and high psychological symptoms, dark triad traits' (5%), 'Low emotional security and moderate dark triad traits' (28%), 'Moderate emotional security, psychological symptoms, and dark triad traits' (45%). Mixture modeling approach-based research provides a complementary view of the previous psychopathology literature. The findings could help practitioners target at-risk university students with low emotional security, low psychological well-being, and low life satisfaction and design programs to aid them in alleviating the psychological symptoms and the dark triad traits.

Specificity of affective dynamics of bipolar and major depressive disorder

OBJECTIVE

Here, we examine whether the dynamics of the four dimensions of the circumplex model of affect assessed by ecological momentary assessment (EMA) differ among those with bipolar disorder (BD) and major depressive disorder (MDD).

METHODS

Participants aged 11-85 years (n = 362) reported momentary sad, anxious, active, and energetic dimensional states four times per day for 2 weeks. Individuals with lifetime mood disorder subtypes of bipolar-I, bipolar-II, and MDD derived from a semistructured clinical interview were compared to each other and to controls without a lifetime history of psychiatric disorders. Random effects from individual means, inertias, innovation (residual) variances, and cross-lags across the four affective dimensions simultaneously were derived from multivariate dynamic structural equation models.

RESULTS

All mood disorder subtypes were associated with higher levels of sad and anxious mood and lower energy than controls. Those with bipolar-I had lower average activation, and lower energy that was independent of activation, compared to MDD or controls. However, increases in activation were more likely to perpetuate in those with bipolar-I. Bipolar-II was characterized by higher lability of sad and anxious mood compared to bipolar-I and controls but not MDD. Compared to BD and controls, those with MDD exhibited cross-augmentation of sadness and anxiety, and sadness blunted energy.

CONCLUSION

Bipolar-I is more strongly characterized by activation and energy than sad and anxious mood. This distinction has potential implications for both specificity of intervention targets and differential pathways underlying these dynamic affective systems. Confirmation of the longer term stability and generalizability of these findings in future studies is necessary.

A randomized trial on differential changes in thought and affect after mindfulness versus dyadic practice indicates phenomenological fingerprints of app-based interventions

Contemplative practice has demonstrated benefits for mental health and well-being. Most previous studies, however, implemented in-person trainings containing a mix of different, mostly solitary, practices and focused on pre- to post-training outcomes. In this randomized trial, we explore the immediate differential efficacy of two daily app-delivered practices in shifting emotional (valence, arousal) and thinking patterns (thought content on future-past, self-other, positive-negative dimensions). For 10 weeks of daily training, 212 participants (18-65 years) performed either a novel 12-min partner-based socio-emotional practice (Affect Dyad) or a 12-min attention-focused solitary mindfulness-based practice. Using ordinal Bayesian multilevel modeling, we found that both practice types led to more positive affect and higher arousal. However, whereas mindfulness-based practice partly led to a decrease in active thoughts, particularly in future-, other-related and negative thoughts, the Dyad in contrast led to increases in other-related, and positive thoughts. This shift towards more social and positive thoughts may specifically support overcoming ruminative thinking patterns associated with self-related and negative thought content. Overall, these differential findings may help inform the adaptation of scalable app-based mental trainings in different segments of the population with the goal to improve mental health and well-being.

Moment-to-moment affective dynamics in schizophrenia and bipolar disorder

BACKGROUND

Affective disturbances in schizophrenia and bipolar disorder may represent a transdiagnostic etiological process as well as a target of intervention. Hypotheses on similarities and differences in various parameters of affective dynamics (intensity, successive/acute changes, variability, and reactivity to stress) between the two disorders were tested.

METHODS

Experience sampling method was used to assess dynamics of positive and negative affect, 10 times a day over 6 consecutive days. Patients with schizophrenia (n = 46) and patients with bipolar disorder (n = 46) were compared against age-matched healthy controls (n = 46).

RESULTS

Compared to controls, the schizophrenia group had significantly more intense momentary negative affect, a lower likelihood of acute changes in positive affect, and reduced within-person variability of positive affect. The bipolar disorder group was not significantly different from either the schizophrenia group or the healthy control group on any affect indexes. Within the schizophrenia group, level of depression was associated with weaker reactivity to stress for negative affect. Within the bipolar disorder group, level of depression was associated with lower positive affect.

CONCLUSIONS

Patients with schizophrenia endured a more stable and negative affective state than healthy individuals, and were less likely to be uplifted in response to happenings in daily life. There is little evidence that these affective constructs characterize the psychopathology of bipolar disorder; such investigation may have been limited by the heterogeneity within group. Our findings supported the clinical importance of assessing multiple facets of affective dynamics beyond the mean levels of intensity.

The future is dynamic: A call for intensive longitudinal data in immunopsychiatry

The long-term value of immunopsychiatry will be based on its ability to translate basic science into effective clinical interventions. In this article, we discuss a key obstacle to achieving this important translational goal-namely, the preponderance of studies that are cross-sectional, or that have months-to-years long follow-up periods. Immunopsychiatric processes such as stress, inflammation, and depression symptoms are inherently dynamic and fluctuate over hours, days, and weeks. This fact suggests that higher-density data collection with only days between measurements is necessary to capture-with adequate resolution-the actual dynamics of these systems, determine optimal time lags with which to observe associations between variables of interest, and maximize the translational potential of these data. To illustrate these points, we use pilot data from our own intensive longitudinal immunopsychiatric study. We then conclude by making several recommendations for future research. By learning how to better use existing data for dynamically informative studies as well as collecting intensive longitudinal data, we believe immunopsychiatry will be much better positioned to advance our causal understanding of the interplay between the immune system and health.

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. During and after treatment, the Hamilton Depression Rating Scale (HDRS) diagnostic interview was performed monthly for 18 months. The rate of change in HDRS scores over five months (during treatment) and remission status (HDRS ≤ 7) over eighteen months were predicted by the SD, MSSD and Mean of NA, and relevant baseline predictors. Higher Mean NA and baseline symptom severity, but not NA variability or instability, predicted stronger depressive symptom reduction during treatment. Higher odds of remitting were only associated with lower Mean NA. Higher mean NA may indicate more room for improvement and thus for a steeper rate of symptom change, while lower mean NA levels may imply that remission status is more readily reached. To resolve the inconclusive findings for instability and variability as predictors of symptom improvement replication in larger samples is required.

A dual-system, machine-learning approach reveals how daily pubertal hormones relate to psychological well-being in everyday life

The two studies presented in this paper seek to resolve mixed findings in research linking activity of pubertal hormones to daily adolescent outcomes. In study 1 we used a series of Confirmatory Factor Analyses to compare the fit of one and two-factor models of seven steroid hormones (n = 994 participants, 8084 samples) of the HPA and HPG axes, using data from a field study (https://www.icpsr.umich.edu/web/ICPSR/studies/38180) collected over ten consecutive weekdays in a representative sample of teens starting high school. In study 2, we fit a Bayesian model to our large dataset to explore how hormone activity was related to outcomes that have been demonstrated to be linked to mental health and wellbeing (self-reports of daily affect and stress coping). Results reveal, first that a two-factor solution of adolescent hormones showed good fit to our data, and second, that HPG activity, rather than the more often examined HPA activity, was associated with improved daily affect ratios and stress coping. These findings suggest that field research, when it is combined with powerful statistical techniques, may help to improve our understanding of the relationship between adolescent hormones and daily measures of well-being.

Identifying latent profiles of emotion dysregulation in a sample of primarily Black women with trauma exposure

BACKGROUND

Emotion dysregulation (ED) is a heterogenous, multi-dimensional transdiagnostic risk factor relevant to the development and maintenance of both internalizing and externalizing psychopathology, especially for those who have experienced trauma. The goals of the current study were to use person-centered analyses to identify distinct profiles of individuals characterized by unique patterns of ED dimensions, and to examine differences in internalizing and externalizing symptoms in a community sample.

METHODS

Participants (n = 783, 97% Black, 93% women) were recruited from an urban safety net hospital with high rates of trauma exposure. Latent profile analysis was used to uncover unique patterns of ED and multinomial logistic regression to evaluate the conditional distribution of our correlates across profiles.

RESULTS

The best-fitting model uncovered four classes: Low ED (42%), Low Awareness/Clarity (34%), Low Impulse Control (17%), and High ED (6%). All classes differed in terms of internalizing symptoms (anxiety sensitivity, depression, PTSD), with classes characterized by higher ED reporting more severe symptoms. For externalizing symptoms (food addiction behaviors, alcohol and drug abuse, aggressive behavior), the Low ED class reported fewer symptoms than all other profiles, while Low Awareness/Clarity, Low Impulse Control, and High ED did not differ from each other.

CONCLUSIONS

Patterns of emotion dysregulation ought to be assessed and considered as treatment targets for those experiencing both internalizing and externalizing psychopathology symptoms.

Stimulus-Driven Affective Change: Evaluating Computational Models of Affect Dynamics in Conjunction with Input

The way in which emotional experiences change over time can be studied through the use of computational models. An important question with regard to such models is which characteristics of the data a model should account for in order to adequately describe these data. Recently, attention has been drawn on the potential importance of nonlinearity as a characteristic of affect dynamics. However, this conclusion was reached through the use of experience sampling data in which no information was available about the context in which affect was measured. However, affective stimuli may induce some or all of the observed nonlinearity. This raises the question of whether computational models of affect dynamics should account for nonlinearity, or whether they just need to account for the affective stimuli a person encounters. To investigate this question, we used a probabilistic reward task in which participants either won or lost money at each trial. A number of plausible ways in which the experimental stimuli played a role were considered and applied to the nonlinear Affective Ising Model (AIM) and the linear Bounded Ornstein-Uhlenbeck (BOU) model. In order to reach a conclusion, the relative and absolute performance of these models were assessed. Results suggest that some of the observed nonlinearity could indeed be attributed to the experimental stimuli. However, not all nonlinearity was accounted for by these stimuli, suggesting that nonlinearity may present an inherent feature of affect dynamics. As such, nonlinearity should ideally be accounted for in the computational models of affect dynamics.

Supplementary Information

The online version contains supplementary material available at 10.1007/s42761-022-00118-5.

How Stable, Really? Traditional and Nonlinear Dynamics Approaches to Studying Temporal Fluctuations in Personality and Affect

A pair of quantitative case studies is presented to demonstrate how different approaches to quantifying temporal variability in ratings of traits and affect can provide rich information for personality researchers. Data are presented and analyzed from two college students who completed an Ecological Momentary Assessment protocol sampling ratings of affect and traits up to 24 times daily for one week. Both classical and nonlinear data analytic techniques were applied to the data to summarize and examine the temporal dynamics of both traits and affect. For the purposes of exposition, one Big Five trait rating, extraversion, and the PANAS positive and negative affects, are discussed. The results support previous research demonstrating a high degree of variability in ratings of both traits and affect over time. Analyses using nonlinear and complexity expand on these findings and suggest temporal patterning as well as disorder; implications of phase portraits for understanding variability are discussed. The findings are discussed in light of a processing dynamics approach to resolving the role of variability in understanding personality.

Affective Dynamics and Mean Levels of Preschool Irritability and Sadness: Predictors of Children's Psychological Functioning Two Years Later

Although irritability and sadness are cardinal symptoms of depression, they are also common in preschoolers. The daily experiences of these emotions are not well-understood during early childhood, yet may provide insight into identification of early depressive symptoms. The current longitudinal study examined daily mean levels and emotion dynamics of preschool-aged children's irritability and sadness and psychiatric outcomes in early school-age. Parents (n = 291) completed 14 consecutive daily diaries about their preschoolers' emotions. Two years later, parents (n = 164) completed a semi-structured clinical interview and questionnaires about their children's psychological functioning. Strong correlations between mean and dynamic measures (rs = 0.65-0.91) were identified. Preschoolers' mean daily levels and dynamics of irritability (variability, instability, inertia) and sadness (instability, inertia) predicted symptoms and impairment 2 years later. Sadness instability and inertia continued to predict difficulties after adjusting for mean daily sadness. Fine-grained daily measures of preschoolers' affect may be help identify children at-risk for psychological problems.

Acceptance Mindfulness-Trait as a Protective Factor for Post-Natal Depression: A Preliminary Research

(1) Background: the prevalence of postnatal depression (PND) reaches up to 20%. PND could be based on the interaction between a psychological vulnerability and chronic stress that pregnancy would activate. Vulnerability factors reflect a psychological profile mirroring mindfulness-trait (MT). A high level of MT is associated with an efficient regulation of both physiological and psychological stress, especially negative moods. Interestingly, mindfulness level can be improved by program based on mindfulness meditation. We hypothesize that MT is a protective factor for PND. We also postulate that negative moods increase during the pregnancy for women who develop a PND after delivery (2) Methods: we conducted a multicentric prospective longitudinal study including 85 women during their first trimester of their pregnancy and 72 from the childbirth to the baby's first birthday". At the inclusion, presence and acceptance of MT and various variables of personality and of psychological functioning were assessed. Mood evolution was monitored each month during the pregnancy and a delivery trauma risk was evaluated after delivery. PND detection was carried out at 48 h, 2, 6 and 12 months after the delivery with the Edinburgh Postnatal Depression Scale with a screening cut-off >11. (3) Results: high-acceptance MT is a protective factor for PND (OR: 0.79). Women without PND displayed less negative mood during pregnancy (p < 0.05 for Anxiety, Confusion and Anger). (4) Conclusions: these results suggest the value of deploying programs to enhance the level of mindfulness, especially in its acceptance dimension, before, during and after pregnancy, to reduce the risk of PND.

On the transience or 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, R2 < 0.01; polynomial model: B < 0.01, p = 0.61, R2 < 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.

A digital self-report survey of mood for bipolar disorder

OBJECTIVES

Bipolar disorder (BP) is commonly researched in digital settings. As a result, standardized digital tools are needed to measure mood. We sought to validate a new survey that is brief, validated in digital form, and able to separately measure manic and depressive severity.

METHODS

We introduce a 6-item digital survey, called digiBP, for measuring mood in BP. It has three depressive items (depressed mood, fidgeting, fatigue), two manic items (increased energy, rapid speech), and one mixed item (irritability); and recovers two scores (m and d) to measure manic and depressive severity. In a secondary analysis of individuals with BP who monitored their symptoms over 6 weeks (n = 43), we perform a series of analyses to validate the digiBP survey internally, externally, and as a longitudinal measure.

RESULTS

We first verify a conceptual model for the survey in which items load onto two factors ("manic" and "depressive"). We then show weekly averages of m and d scores from digiBP can explain significant variation in weekly scores from the Young Mania Rating Scale (R²  = 0.47) and SIGH-D (R²  = 0.58). Lastly, we examine the utility of the survey as a longitudinal measure by predicting an individual's future m and d scores from their past m and d scores.

CONCLUSIONS

While further validation is warranted in larger, diverse populations, these validation analyses should encourage researchers to consider digiBP for their next digital study of BP.

Affective lability as a prospective predictor of subsequent bipolar disorder diagnosis: a systematic review

Objectives

The early pathogenesis and precursors of Bipolar Disorder (BD) are poorly understood. There is some cross-sectional and retrospective evidence of affective lability as a predictor of BD, but this is subject to recall biases. The present review synthesises the prospective evidence examining affective lability and the subsequent development of BD at follow-up.

Methods

The authors performed a systematic search of PubMed, PsycInfo and Embase (1960–June 2020) and conducted hand searches to identify studies assessing affective lability (according to a conceptually-inclusive definition) at baseline assessment in individuals without a BD diagnosis, and a longitudinal follow-up assessment of bipolar (spectrum) disorders. Results are reported according to the PRISMA guidelines, and the synthesis without meta-analysis (SWiM) reporting guidelines were used to strengthen the narrative synthesis. The Newcastle–Ottawa Scale was used to assess risk of bias (ROB).

Results

11 articles describing 10 studies were included. Being identified as having affective lability at baseline was associated with an increased rate of bipolar diagnoses at follow-up; this association was statistically significant in six of eight studies assessing BD type I/II at follow-up and in all four studies assessing for bipolar spectrum disorder (BSD) criteria. Most studies received a ‘fair’ or ‘poor’ ROB grade.

Conclusions

Despite a paucity of studies, an overall association between prospectively-identified affective lability and a later diagnosis of BD or BSD is apparent with relative consistency between studies. This association and further longitudinal studies could inform future clinical screening of those who may be at risk of BD, with the potential to improve diagnostic accuracy and facilitate early intervention.

Supplementary Information

The online version contains supplementary material available at 10.1186/s40345-021-00237-1.

Emotion networks across self-reported depression levels during the COVID-19 pandemic

ABSTRACTDuring stressful circumstances, such as the COVID-19 pandemic, disturbances in emotional experiences can occur. These emotional disturbances, if not relieved or regulated, can be associated with feelings of depression. Currently, little is known about which emotional experiences (positive and negative) are associated with feelings of depression during COVID-19. This study aimed to estimate and compare mixed, positive and negative valence emotion networks during COVID-19 for low, moderate and high levels of self-reported depression. Across 26,034 participants, central emotional experiences included gratitude, sadness, fear, anxiety, compassion, and being moved for all self-reported depression levels; love for low levels of depression, and confusion for high levels of depression. The strongest edges included fear-anxiety, loneliness-boredom, anger-disgust, determination-hope, and compassion-being moved for all self-reported depression levels; calm-relief, and sadness-frustration for high levels of self-reported depression; and admiration-being moved for low and moderate self-reported depression levels. Network comparison tests showed mixed, positive and negative emotion networks significantly differed in structure across all self-reported depression levels. Network connectivity was also significantly stronger for low self-reported depression within positive and negative emotion networks. These networks provide key information on emotional experiences associated with depression during COVID-19.

Daily emotional inertia and long-term subjective well-being among people living with HIV

OBJECTIVE

The aim of this study was to verify if subjective well-being (SWB) modifies the autoregressive effect of daily emotions and if this emotional inertia predicts long-term changes in SWB among people living with HIV (PLWH).

METHODS

The 131 participants had medically confirmed diagnoses of HIV and were undergoing antiretroviral therapy. They assessed their SWB (satisfaction with life, negative affect, positive affect) twice with an interval of one year. They also took part in a five-day online diary study six months from their baseline SWB assessment and reported their daily negative and positive emotions.

RESULTS

Results showed that baseline SWB did not modify the emotional carryover effect from one to another. Additionally, after control for baseline SWB, emotional inertia did not predict SWB one year later. However, such an effect was noted for the mean values of daily reported emotions, indicating their unique predictive power over SWB itself.

CONCLUSIONS

This may suggest that emotional inertia does not necessarily provide better information than more straightforward measures of affective functioning.

Depression risk factors and affect dynamics: An experience sampling study

Affect dynamics reflect individual differences in how emotional information is processed, and may provide insights into how depressive episodes develop. To extend prior studies that examined affect dynamics in currently depressed individuals, the present study tested in 68 non-depressed young adults whether three well-established risk factors for major depressive disorder (MDD) - (a) past episodes of MDD, (b) family history of MDD, and (c) reduced neurophysiological responses to reward - predicted mean levels, instability, or inertia (i.e., inflexibility) of positive affect (PA) and/or negative affect (NA). Momentary PA and NA were assessed up to 6 times per day for 14 days (mean number of surveys completed = 45.89). MDD history and family history of MDD were assessed via semi-structured interview, and neurophysiological responses to reward were indexed using the Reward Positivity, an event-related potential related to depression. After adjusting for current depressive symptoms, results indicated that (a) past episodes of MDD predicted higher mean levels of NA, (b) family history of MDD predicted greater PA inertia, and (c) blunted reactivity to reward predicted greater NA inertia. Collectively, these results suggest that elevated mean levels of NA and inflexibility of PA and NA may be potential mechanisms that confer risk for depression.

Emotional awareness, affective dysregulation, and bipolar spectrum psychopathology: A path analysis

Affective dysregulation is present in those with subsyndromal symptoms of hypomania and mania and prospectively predicts the development of bipolar spectrum disorders. A crucial, understudied area related to the experience and regulation of emotion in this population is emotional awareness - emotional clarity (Clarity) and attention to emotion (Attention). We examined whether scores on the Hypomanic Personality Scale (HPS) were associated with deficits in emotional awareness and whether these deficits were associated with heightened intensity and instability of negative (NA) and positive affect (PA). Young adults (n=233), oversampled for high HPS scores completed self-reports and 14 days of experience sampling assessing high and low arousal NA and PA. HPS scores were associated with low Clarity and unassociated with Attention. High HPS scores were associated with greater high and low arousal NA intensity and instability only for those at low and mean levels of Attention. In contrast, there was a significant indirect association between HPS scores and intensity of high and low arousal NA and PA, as well as instability of high arousal NA, through low Clarity. Results highlighted that individual differences exist in the extent to which facets of emotional awareness differentially link scores on the HPS to emotional outcomes.

Digital health data-driven approaches to understand human behavior

Advances in digital technologies and data analytics have created unparalleled opportunities to assess and modify health behavior and thus accelerate the ability of science to understand and contribute to improved health behavior and health outcomes. Digital health data capture the richness and granularity of individuals' behavior, the confluence of factors that impact behavior in the moment, and the within-individual evolution of behavior over time. These data may contribute to discovery science by revealing digital markers of health/risk behavior as well as translational science by informing personalized and timely models of intervention delivery. And they may help inform diagnostic classification of clinically problematic behavior and the clinical trajectories of diagnosable disorders over time. This manuscript provides a review of the state of the science of digital health data-driven approaches to understanding human behavior. It reviews methods of digital health assessment and sources of digital health data. It provides a synthesis of the scientific literature evaluating how digitally derived empirical data can inform our understanding of health behavior, with a particular focus on understanding the assessment, diagnosis and clinical trajectories of psychiatric disorders. And, it concludes with a discussion of future directions and timely opportunities in this line of research and its clinical application.

Emotion Network Analysis During COVID-19 Quarantine - A Longitudinal Study

Introduction: The coronavirus disease 2019 (COVID-19) emergency has imposed important challenges in the lives of individuals, particularly since the restriction of free movement. In Spain, this mandatory home confinement started on March 14, 2020. In this scenario, some calls have been made to better understand the exact impact of the quarantine on the emotional status of individuals across time. Materials and Methods: On the first day that the Spanish government imposed the quarantine, our team launched an online longitudinal study to monitor emotional responses to the COVID-19 emergency over time. For 2 weeks, 187 people have responded to a daily diary on emotion functioning. An emotion network analysis was performed to study the network structure of 30 mood states and its changes during the first 2 weeks of the quarantine. Results: The emotional network showed critical changes in the interactions of emotions over time. An analysis of mean emotional levels did not show statistically significant changes in mood over time. Interestingly, two different network patterns were found when the sample was divided between those with favorable responses and those with unfavorable responses. Discussion: This new approach to the study of longitudinal changes of the mood state network of the population reveals different adaptation strategies reflected on the sample's emotional network. This network approach can help identify most fragile individuals (more vulnerable to external stressors) before they develop clear and identifiable psychopathology and also help identify anti-fragile individuals (those who improve their functioning in the face of external stressors). This is one of the first studies to apply an emotional network approach to study the psychological effects of pandemics and might offer some clues to psychologists and health administrators to help people cope with and adjust to this critical situation.

Rationale and Design of the Women's Health And Daily Experiences Project: Protocol for an Ecological Momentary Assessment Study to Identify Real-Time Predictors of Midlife Women's Physical Activity

BACKGROUND

Midlife women are at an elevated risk for cardiovascular disease (CVD) and associated mortality. Those who have additional risk conditions such as obesity or hypertension report specific barriers to engaging in cardioprotective behaviors such as physical activity (PA). Considerable effort has been devoted to understanding PA determinants and designing interventions for midlife women, although with suboptimal success, as increasing PA could meaningfully attenuate CVD risk. An updated approach to understanding PA among midlife women could improve upon existing resources by focusing on novel psychosocial influences on PA in this population (ie, body satisfaction, social interactions, social comparisons, mood state) and within-person relations between these influences and PA in the natural environment.

OBJECTIVE

The overarching goal of Project WHADE (Women's Health And Daily Experiences) is to use an ecological momentary assessment (EMA) approach to capture ecologically valid relations between midlife women's psychosocial experiences and PA as they engage in their normal daily activities. The primary aim of the study is to identify within-person psychosocial predictors of variability in PA (ie, experiences associated with higher vs lower PA for a given individual).

METHODS

Midlife women (aged 40-60 years) with one or more additional risk markers for CVD (eg, hypertension) will be recruited from primary care clinics and the general community (target n=100). Eligible women will complete an initial survey and a face-to-face baseline session before engaging in a 10-day EMA protocol. Psychosocial experiences will be assessed using a brief self-report via a smartphone 5 times per day, and PA will be assessed throughout waking hours using a research-grade monitor. Participants will return for a brief exit interview at the end of 10 days. Multilevel models that address the nested structure of EMA data will be used to evaluate the study aims.

RESULTS

Recruitment and enrollment are ongoing, and a total of 75 women have completed the protocol to date. Data collection is expected to be completed in Fall 2020.

CONCLUSIONS

Project WHADE is designed to identify naturally occurring psychosocial experiences that predict short-term variability in midlife women's PA. As such, the results of this study should advance the current understanding of PA among midlife women by providing further insight into within-person psychosocial influences on PA in this group. In the future, this information could help inform the design of interventions for this population.

INTERNATIONAL REGISTERED REPORT IDENTIFIER (IRRID)

DERR1-10.2196/19044.

Early warning signals in psychopathology: what do they tell?

BACKGROUND

Despite the increasing understanding of factors that might underlie psychiatric disorders, prospectively detecting shifts from a healthy towards a symptomatic state has remained unattainable. A complex systems perspective on psychopathology implies that such symptom shifts may be foreseen by generic indicators of instability, or early warning signals (EWS). EWS include, for instance, increasing variability, covariance, and autocorrelation in momentary affective states-of which the latter was studied. The present study investigated if EWS predict (i) future worsening of symptoms as well as (ii) the type of symptoms that will develop, meaning that the association between EWS and future symptom shifts would be most pronounced for congruent affective states and psychopathological domains (e.g., feeling down and depression).

METHODS

A registered general population cohort of adolescents (mean age 18 years, 36% male) provided ten daily ratings of their affective states for 6 consecutive days. The resulting time series were used to compute EWS in feeling down, listless, anxious, not relaxed, insecure, suspicious, and unwell. At baseline and 1-year follow-up, symptom severity was assessed by the Symptom Checklist-90 (SCL-90). We selected four subsamples of participants who reported an increase in one of the following SCL-90 domains: depression (N = 180), anxiety (N = 192), interpersonal sensitivity (N = 184), or somatic complaints (N = 166).

RESULTS

Multilevel models showed that EWS in feeling suspicious anticipated increases in interpersonal sensitivity, as hypothesized. EWS were absent for other domains. While the association between EWS and symptom increases was restricted to the interpersonal sensitivity domain, post hoc analyses showed that symptom severity at baseline was related to heightened autocorrelations in congruent affective states for interpersonal sensitivity, depression, and anxiety. This pattern replicated in a second, independent dataset.

CONCLUSIONS

The presence of EWS prior to symptom shifts may depend on the dynamics of the psychopathological domain under consideration: for depression, EWS may manifest only several weeks prior to a shift, while for interpersonal sensitivity, EWS may already occur 1 year in advance. Intensive longitudinal designs where EWS and symptoms are assessed in real-time are required in order to determine at what timescale and for what type of domain EWS are most informative of future psychopathology.

Digital solutions for shaping mood and behavior among individuals with mood disorders

Mood disorders present on-going challenges to the medical field, with difficulties ranging from establishing effective treatments to understanding complexities of one's mood. One solution is the use of mobile apps and wearables for measuring physiological symptoms and real-time mood in order to shape mood and behavior. Current digital research is focused on increasing engagement in monitoring mood, uncovering mood dynamics, predicting mood, and providing digital microinterventions. This review discusses the importance and risks of user engagement, as well as barriers to improving it. Research on mood dynamics highlights the possibility to reveal data-driven computational phenotypes that could guide treatment. Mobile apps are being used to track voice patterns, GPS, and phone usage for predicting mood and treatment response. Future directions include utilizing mobile apps to deliver and evaluate microinterventions. To continue these advances, standardized reporting and study designs should be considered to improve digital solutions for mood disorders.