Emotion elicitation and capture among real couples in the lab

Couples’ relationships affect partners’ mental and physical well-being. Automatic recognition of couples’ emotions will not only help to better understand the interplay of emotions, intimate relationships, and health and well-being, but also provide crucial clinical insights into protective and risk factors of relationships, and can ultimately guide interventions. However, several works developing emotion recognition algorithms use data from actors in artificial dyadic interactions and the algorithms are likely not to perform well on real couples. We are developing emotion recognition methods using data from real couples and, in this paper, we describe two studies we ran in which we collected emotion data from real couples — Dutch-speaking couples in Belgium and German-speaking couples in Switzerland. We discuss our approach to eliciting and capturing emotions and make five recommendations based on their relevance for developing well-performing emotion recognition systems for couples

Siblings dealing with pediatric cancer : a family- and context-oriented approach

Background: Pediatric cancer is a severe life-threatening disease that poses significant challenges to the life of the siblings. Based on the social ecology model, the current study is aimed at exploring the association between intrafamilial (family functioning, family support) and contextual (network support) resources, and the individual adjustment of siblings facing cancer in their brother/sister. Methods: Participants were 81 siblings of children with leukemia or non-Hodgkin lymphoma. The mean siblings' age was 10.32 years. Siblings completed the Family Environment Scale, the Social Support Questionnaire for Children, the Situation-Specific Emotional Reactions Questionnaire, and the Pediatric Quality of Life Inventory. Data were analyzed using a multi-level approach. Results: Family functioning, family support, and network support proved to be related to siblings' cancer-related emotional reactions post-diagnosis. In addition, the present study suggests taking into account the gender of the ill child and the age of the siblings. Discussion: Our findings led to the conclusion that resources at both the intrafamilial level and the contextual level are important for explaining sibling adjustment post-diagnosis. Interventions targeting the sibling, the family, and the external network are warranted to enhance sibling adjustment

Relational needs frustration: an observational study on the role of negative (dis)engaging emotions

The present study aimed to explore the role of partners’ negative engaging and disengaging emotions in dealing with the frustration of autonomy and relatedness needs during conflict. In an observational study, partners from 141 heterosexual couples participated in a conflict interaction task followed by a video-mediated recall procedure during which they reported their level of relational need frustration and their emotions experienced at different moments during the interaction. Results showed that in partners, more autonomy frustration, experienced at the beginning of the conflict, was accompanied by more concurrent negative disengaging emotions (anger, irritation), whereas more relatedness frustration was accompanied by more negative engaging emotions (hurt, sadness, disappointment). Additionally, the concurrent association between partners’ relatedness frustration and their experience of negative engaging emotions was negatively moderated by their own relatedness relationship beliefs (as assessed by background questionnaires), indicating that for individuals who considered relatedness to be less important, relatedness frustration and negative engaging emotions were more strongly linked than for people with high relatedness beliefs. Finally, negative engaging emotions – assessed at the beginning of the conflict – were associated with more relatedness frustration at a subsequent time point in the interaction in men, but not in women. This study contributes to our understanding of how partners’ negative emotions and the frustration of important relational needs are intertwined

SIMON: A Digital Protocol to Monitor and Predict Suicidal Ideation

Each year, more than 800,000 persons die by suicide, making it a leading cause of death worldwide. Recent innovations in information and communication technology may offer new opportunities in suicide prevention in individuals, hereby potentially reducing this number. In our project, we design digital indices based on both self-reports and passive mobile sensing and test their ability to predict suicidal ideation, a major predictor for suicide, and psychiatric hospital readmission in high-risk individuals: psychiatric patients after discharge who were admitted in the context of suicidal ideation or a suicidal attempt, or expressed suicidal ideations during their intake. Specifically, two smartphone applications -one for self-reports (SIMON-SELF) and one for passive mobile sensing (SIMON-SENSE)- are installed on participants' smartphones. SIMON-SELF uses a text-based chatbot, called Simon, to guide participants along the study protocol and to ask participants questions about suicidal ideation and relevant other psychological variables five times a day. These self-report data are collected for four consecutive weeks after study participants are discharged from the hospital. SIMON-SENSE collects behavioral variables -such as physical activity, location, and social connectedness- parallel to the first application. We aim to include 100 patients over 12 months to test whether (1) implementation of the digital protocol in such a high-risk population is feasible, and (2) if suicidal ideation and psychiatric hospital readmission can be predicted using a combination of psychological indices and passive sensor information. To this end, a predictive algorithm for suicidal ideation and psychiatric hospital readmission using various learning algorithms (e.g., random forest and support vector machines) and multilevel models will be constructed. Data collected on the basis of psychological theory and digital phenotyping may, in the future and based on our results, help reach vulnerable individuals early and provide links to just-in-time and cost-effective interventions or establish prompt mental health service contact. The current effort may thus lead to saving lives and significantly reduce economic impact by decreasing inpatient treatment and days lost to inability

Validation of Visual and Auditory Digital Markers of Suicidality in Acutely Suicidal Psychiatric Inpatients: Proof-of-Concept Study

BACKGROUND Multiple symptoms of suicide risk have been assessed based on visual and auditory information, including flattened affect, reduced movement, and slowed speech. Objective quantification of such symptomatology from novel data sources can increase the sensitivity, scalability, and timeliness of suicide risk assessment. OBJECTIVE We aimed to examine measurements extracted from video interviews using open-source deep learning algorithms to quantify facial, vocal, and movement behaviors in relation to suicide risk severity in recently admitted patients following a suicide attempt. METHODS We utilized video to quantify facial, vocal, and movement markers associated with mood, emotion, and motor functioning from a structured clinical conversation in 20 patients admitted to a psychiatric hospital following a suicide risk attempt. Measures were calculated using open-source deep learning algorithms for processing facial expressivity, head movement, and vocal characteristics. Derived digital measures of flattened affect, reduced movement, and slowed speech were compared to suicide risk with the Beck Scale for Suicide Ideation controlling for age and sex, using multiple linear regression. RESULTS Suicide severity was associated with multiple visual and auditory markers, including speech prevalence (β=-0.68, P=.02, r$^{2}$=0.40), overall expressivity (β=-0.46, P=.10, r$^{2}$=0.27), and head movement measured as head pitch variability (β=-1.24, P=.006, r$^{2}$=0.48) and head yaw variability (β=-0.54, P=.06, r$^{2}$=0.32). CONCLUSIONS Digital measurements of facial affect, movement, and speech prevalence demonstrated strong effect sizes and linear associations with the severity of suicidal ideation

Design and baseline characteristics of the finerenone in reducing cardiovascular mortality and morbidity in diabetic kidney disease trial

Background: Among people with diabetes, those with kidney disease have exceptionally high rates of cardiovascular (CV) morbidity and mortality and progression of their underlying kidney disease. Finerenone is a novel, nonsteroidal, selective mineralocorticoid receptor antagonist that has shown to reduce albuminuria in type 2 diabetes (T2D) patients with chronic kidney disease (CKD) while revealing only a low risk of hyperkalemia. However, the effect of finerenone on CV and renal outcomes has not yet been investigated in long-term trials. Patients and Methods: The Finerenone in Reducing CV Mortality and Morbidity in Diabetic Kidney Disease (FIGARO-DKD) trial aims to assess the efficacy and safety of finerenone compared to placebo at reducing clinically important CV and renal outcomes in T2D patients with CKD. FIGARO-DKD is a randomized, double-blind, placebo-controlled, parallel-group, event-driven trial running in 47 countries with an expected duration of approximately 6 years. FIGARO-DKD randomized 7,437 patients with an estimated glomerular filtration rate >= 25 mL/min/1.73 m(2) and albuminuria (urinary albumin-to-creatinine ratio >= 30 to <= 5,000 mg/g). The study has at least 90% power to detect a 20% reduction in the risk of the primary outcome (overall two-sided significance level alpha = 0.05), the composite of time to first occurrence of CV death, nonfatal myocardial infarction, nonfatal stroke, or hospitalization for heart failure. Conclusions: FIGARO-DKD will determine whether an optimally treated cohort of T2D patients with CKD at high risk of CV and renal events will experience cardiorenal benefits with the addition of finerenone to their treatment regimen. Trial Registration: EudraCT number: 2015-000950-39; ClinicalTrials.gov identifier: NCT02545049

Partner-expected affect : how you feel now is predicted by how your partner thought you felt before

Romantic partners can modulate each other's emotions in many ways, resulting in interwoven emotional lives. Here, building on findings from basic psychological research, we propose a novel way of such interconnectedness, termed partner-expected affect, in which perceptions of a partner's feelings may positively predict how this partner will actually feel at a later moment in time. We evaluated this hypothesis by means of an experience sampling study in which 100 romantic partners (50 couples) reported on the level of valence and arousal of their own feelings and of the perceived feelings of their partners 10 times a day throughout a week. In line with expectations, we found that how individuals were feeling at a particular moment was positively predicted by how their partner thought they felt at the previous moment (on top of how they felt at the previous moment and how their partner felt at the previous moment), at least when they had interacted with each other in between. This finding identifies a novel potential way in which people may shape each other's feelings and paves the way to further examine the nature and boundary conditions of such partner-expected affect

All's well that ends well? A test of the peak-end rule in couples' conflict discussions

Despite its importance for well-being, surprisingly little is known about what determines how couples feel after a conflict. Using the peak-end rule, we examined whether partners' post-conflict affect was mainly predicted by their most aversive or pleasant emotional experience (peaks) during the conflict, or by the emotional tone at the end of the interaction. One hundred and one couples engaged in a conflict interaction and afterwards evaluated their momentary affect during the interaction. Post-conflict affect (in terms of positive and negative feelings, and perceived partner responsiveness) was assessed immediately after the conflict, after a subsequent positive discussion, and upon returning to daily life (here, rumination about the relationship was assessed as well). Our results showed that the negative and positive peaks, but not the end emotion, predicted immediate and partly extended post-conflict affect in individuals. This finding has clinical implications for the mediation of couple conflict