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. Nonparametric change-point analyses were used to determine the timing of gains (i.e., improvements in the mean of each variable) for each individual. We then established whether the first (i.e., earliest) gains in emotions preceded, followed, or occurred in the same week as cognitive and behavioral gains for each individual. RESULTS: Contrary to our hypotheses, first gains in behaviors did not precede first emotional gains (3 times, 8%) more often than they followed them (26 times, 70%). Cognitive gains often occurred in the same week as first emotional gains (43 times, 58%) and less often preceded (13 times, 18%) or followed emotional gains (18 times, 24%). CONCLUSION: The first improvements in behaviors did not tend to precede the first improvements in emotions likely because fewer behavioral gains were found. The finding that cognitive variables tend to improve around the same time as sad mood may explain why many studies failed to find that cognitive change predicts later change in depressive symptoms. (PsycInfo Database Record (c) 2024 APA, all rights reserved).

Considering the 'With Whom': Differences Between Event- and Signal-Contingent ESM Data of Person-Specific Social Interactions.

Experience sampling studies often aim to capture social interactions. A central methodological question in such studies is whether to use event- or signal-contingent sampling. The little existing research on this issue has not taken into account that social interactions occur with unique interaction partners (e.g., Anna or Tom). We analyze one week of social interaction data of 286 students from the University of Pittsburgh (60.8% male, mean age 19.2 years), taking into account the unique interaction partners of each student. Specifically, we investigate the differences between event- and signal contingent sampling in (1) the total number of unique interaction partners captured, as well as (2) the kinds of relationships, and (3) the quality of social interactions with these captured interaction partners. Apart from a larger quantity of interactions and unique interaction partners in the event-contingent sampling design, our analyses indicate subtle differences between the two designs when aiming to assess social interactions with more distant interaction partners, such as coworkers or strangers. Most importantly, in our analyses, specific interaction partners and social roles explained a considerable amount of variance in the quality of social interactions (up to 20.5%), suggesting that future research would benefit greatly from considering "with whom" individuals interact.

Subjective long-term emotional and social effects of recreational MDMA use: the role of setting and intentions.

MDMA is a recreational drug commonly used to enhance euphoria, but it is also used in non-party settings with self-insight or social connection intentions. Yet, little is known about whether distinct consumer groups are formed based on consumption setting and intention. We aimed to characterize different types of recreational MDMA users based on consumption setting and intentions, and to examine their differences in perceptions of long-term social-emotional effects of MDMA use. We analyzed self-reports of 766 individuals (ages 18-61, mostly from Western countries), reporting on their MDMA consumption habits and perceived effects. We used a K-medoids clustering algorithm to identify distinct types of consumption settings and intentions. We identified three setting types - party settings with friends (N = 388), private home settings (N = 132), mixed settings (N = 246) - and three intention types - euphoria and energy (N = 302), self-insight (N = 219), mixed intentions (N = 245). Members of the self-insight and mixed intentions clusters reported considerably more long-term socio-emotional benefits than members of the euphoria and energy cluster. No differences were observed between the setting clusters. In this particular sample, more long-term benefits than harms were reported. Our findings suggest that the long-term social-emotional benefits of MDMA are associated with whether users seek self-insight or have mixed intentions.

Studying Daily Social Interaction Quantity and Quality in Relation to Depression Change: A Multi-Phase Experience Sampling Study.

Day-to-day social life and mental health are intertwined. Yet, no study to date has assessed how the quantity and quality of social interactions in daily life are associated with changes in depressive symptoms. This study examines these links using multiple-timescale data (iSHAIB data set; N = 133), where the level of depressive symptoms was measured before and after three 21-day periods of event-contingent experience sampling of individuals' interpersonal interactions (T = 64,112). We find weak between-person effects for interaction quantity and perceiving interpersonal warmth of others on changes in depressive symptoms over the 21-day period, but strong and robust evidence for overwarming-a novel construct representing the self-perceived difference between one's own and interaction partner's level of interpersonal warmth. The findings highlight the important role qualitative aspects of social interactions may play in the progression of individuals' depressive symptoms.

Computational social science is growing up: why puberty consists of embracing measurement validation, theory development, and open science practices.

Puberty is a phase in which individuals often test the boundaries of themselves and surrounding others and further define their identity - and thus their uniqueness compared to other individuals. Similarly, as Computational Social Science (CSS) grows up, it must strike a balance between its own practices and those of neighboring disciplines to achieve scientific rigor and refine its identity. However, there are certain areas within CSS that are reluctant to adopt rigorous scientific practices from other fields, which can be observed through an overreliance on passively collected data (e.g., through digital traces, wearables) without questioning the validity of such data. This paper argues that CSS should embrace the potential of combining both passive and active measurement practices to capitalize on the strengths of each approach, including objectivity and psychological quality. Additionally, the paper suggests that CSS would benefit from integrating practices and knowledge from other established disciplines, such as measurement validation, theoretical embedding, and open science practices. Based on this argument, the paper provides ten recommendations for CSS to mature as an interdisciplinary field of research.

Modeling categorical time-to-event data: The example of social interaction dynamics captured with event-contingent experience sampling methods.

The depth of information collected in participants' daily lives with active (e.g., experience sampling surveys) and passive (e.g., smartphone sensors) ambulatory measurement methods is immense. When measuring participants' behaviors in daily life, the timing of particular events-such as social interactions-is often recorded. These data facilitate the investigation of new types of research questions about the timing of those events, including whether individuals' affective state is associated with the rate of social interactions (binary event occurrence) and what types of social interactions are likely to occur (multicategory event occurrences, e.g., interactions with friends or family). Although survival analysis methods have been used to analyze time-to-event data in longitudinal settings for several decades, these methods have not yet been incorporated into ambulatory assessment research. This article illustrates how multilevel and multistate survival analysis methods can be used to model the social interaction dynamics captured in intensive longitudinal data, specifically when individuals exhibit particular categories of behavior. We provide an introduction to these models and a tutorial on how the timing and type of social interactions can be modeled using the R statistical programming language. Using event-contingent reports (N = 150, Nevents = 64,112) obtained in an ambulatory study of interpersonal interactions, we further exemplify an empirical application case. In sum, this article demonstrates how survival models can advance the understanding of (social interaction) dynamics that unfold in daily life. (PsycInfo Database Record (c) 2023 APA, all rights reserved).

Feedback About a Person's Social Context - Personal Networks and Daily Social Interactions.

The social context of a person, meaning their social relationships and daily social interactions, is an important factor for understanding their mental health. However, personalised feedback approaches to psychotherapy do not consider this factor sufficiently yet. Therefore, we developed an interactive feedback prototype focusing specifically on a person's social relationships as captured with personal social networks (PSN) and daily social interactions as captured with experience sampling methodology (ESM). We describe the development of the prototype as well as two evaluation studies: Semi-structured interviews with students (N = 23) and a focus group discussion with five psychotherapy patients. Participants from both studies considered the prototype useful. The students considered participation in our study, which included social context assessment via PSN and ESM as well as a feedback session, insightful. However, it remains unclear how much insight the feedback procedure generated for the students beyond the insights they already gained from the assessments. The focus group patients indicated that in a clinical context, (social context) feedback may be especially useful to generate insight for the clinician and facilitate collaboration between patient and clinician. Furthermore, it became clear that the current feedback prototype requires explanations by a researcher or trained clinician and cannot function as a stand-alone intervention. As such, we discuss our feedback prototype as a starting point for future research and clinical implementation.

Modeling social interaction dynamics measured with smartphone sensors: An ambulatory assessment study on social interactions and loneliness.

More and more data are being collected using combined active (e.g., surveys) and passive (e.g., smartphone sensors) ambulatory assessment methods. Fine-grained temporal data, such as smartphone sensor data, allow gaining new insights into the dynamics of social interactions in day-to-day life and how these are associated with psychosocial phenomena - such as loneliness. So far, however, smartphone sensor data have often been aggregated over time, thus, not doing justice to the fine-grained temporality of these data. In this article, we demonstrate how time-stamped sensor data of social interactions can be modeled with multistate survival models. We examine how loneliness is associated with (a) the time between social interaction (i.e., interaction rate) and (b) the duration of social interactions in a student population (Nparticipants = 45, Nobservations = 74,645). Before a 10-week ambulatory assessment phase, participants completed the UCLA loneliness scale, covering subscales on intimate, relational, and collective loneliness. Results from the multistate survival models indicated that loneliness subscales were not significantly associated with differences in social interaction rate and duration - only relational loneliness predicted shorter social interaction encounters. These findings illustrate how the combination of new measurement and modeling methods can advance knowledge on social interaction dynamics in daily life settings and how they relate to psychosocial phenomena such as loneliness.

Social integration of adolescents with chronic pain: a social network analysis.

ABSTRACT: Adolescents with chronic pain (ACP) often experience impairments in their social functioning. Little is known about the consequences of these impairments on peer relationships of ACP. This study applied social network analysis to examine whether adolescents with more pain problems are less popular (RQ1), adolescents with similar pain problems name each other more often as being part of the same peer group (RQ2), dyads with an adolescent experiencing more pain problems report less positive (eg, support) and more negative (eg, conflict) friendship qualities (RQ3), and positive and negative friendship qualities moderate the relationship between pain and emotional distress (RQ4). This study used data from the first wave of a longitudinal study (N = 2767) which followed up Swedish adolescents from 19 public schools. For RQ1-3, Multiple Regression Quadratic Assignment Procedure was applied. For RQ4, standard multilevel models with observations of adolescents nested within schools were estimated. Results showed that ACP were not less popular than adolescents without chronic pain. Second, ACP nominated each other more often as being part of the same peer group. Third, results regarding friendship quality showed that adolescents with more pain problems perceived the relationship with their friends as less positive (eg, support) and more negative (eg, conflict) than adolescents with less pain problems. Finally, positive and negative friendship qualities moderated the relationship between pain and emotional distress. This study contributes to the literature on the importance of peer relationships of ACP. Clinical implications and directions for future research are discussed.

Psychometric evaluation of the German version of the Opening Minds Stigma Scale for Health Care Providers (OMS-HC).

BACKGROUND: Healthcare professionals can be a source of stigma and discrimination for people with mental illness, and anti-stigma programs are needed for this target group. However, there is no validated German language scale to assess attitudes of healthcare professionals towards people with mental illness. This study had the aim to validate the German language version of the Opening Minds Stigma Scale for Health Care Providers (OMS-HC), a self-report measure of stigmatizing attitudes. METHODS: Staff (n = 392) on general psychiatric inpatient wards (excluding child, forensic and geriatric psychiatry) at five psychiatric hospitals in Switzerland (n = 3) and Germany (n = 2) participated in the study. The internal consistency of the OMS-HC was examined as well as its factor structure using exploratory and confirmatory factor analyses. To assess the scale's concurrent validity, we used the Social Distance Scale. RESULTS: Internal consistency for the OMS-HC total score was good (α = 0.74), acceptable for the subscales Attitudes (α = 0.62) and Social Distance (α = 0.69), and poor for the Disclosure subscale (α = 0.55). The original three-factor structure fit our data well. The OMS-HC total score and the Social Distance subscale score were significantly correlated with the Social Distance Scale, supporting concurrent validity. CONCLUSION: The German version of the OMS-HC demonstrated satisfactory psychometric properties and can be recommended for future research and intervention evaluation.

Getting stuck in social isolation: Solitude inertia and depressive symptoms.

Social isolation and depression are tightly linked and can reinforce each other in a vicious cycle. Yet, the antecedents of this complex cycle are not well understood. To date, little is known about how the dynamics of social isolation in daily life (i.e., solitude) play a role in this cycle. To investigate these complex dynamics, we introduce the concept of solitude inertia, which captures individuals' tendencies to remain in social states of solitude. We argue that, although short-term solitude can have both positive and negative effects on individuals' depressive symptoms, prolonged states of solitude (i.e., high solitude inertia) are detrimental. At the same time, individuals with depression might be more vulnerable to "get stuck" in solitude. In this study, we tease apart the bidirectional relationship between solitude inertia and depressive symptoms. We use data from the MindMaastricht study in which 129 individuals with residual depressive symptoms participated in two experience sampling assessments phases (T1 and T2) that were 8 weeks apart (Nobs = 11,558). Using logistic multilevel models, we find that higher levels of depressive symptoms are related to higher solitude inertia. We further show that depressive symptoms at T1 are not predictive of solitude inertia at T2. However, solitude inertia at T1 was predictive of depressive symptoms eight weeks later (T2) in a linear regression analysis. This study introduces and highlights the role of solitude inertia as a potential intervention target in social isolation and depression dynamics. (PsycInfo Database Record (c) 2020 APA, all rights reserved).

Students under lockdown: Comparisons of students' social networks and mental health before and during the COVID-19 crisis in Switzerland.

This study investigates students' social networks and mental health before and at the time of the COVID-19 pandemic in April 2020, using longitudinal data collected since 2018. We analyze change on multiple dimensions of social networks (interaction, friendship, social support, co-studying) and mental health indicators (depression, anxiety, stress, loneliness) within two cohorts of Swiss undergraduate students experiencing the crisis (N = 212), and make additional comparisons to an earlier cohort which did not experience the crisis (N = 54). In within-person comparisons we find that interaction and co-studying networks had become sparser, and more students were studying alone. Furthermore, students' levels of stress, anxiety, loneliness, and depressive symptoms got worse, compared to measures before the crisis. Stressors shifted from fears of missing out on social life to worries about health, family, friends, and their future. Exploratory analyses suggest that COVID-19 specific worries, isolation in social networks, lack of interaction and emotional support, and physical isolation were associated with negative mental health trajectories. Female students appeared to have worse mental health trajectories when controlling for different levels of social integration and COVID-19 related stressors. As universities and researchers discuss future strategies on how to combine on-site teaching with online courses, our results indicate the importance of considering social contacts in students' mental health and offer starting points to identify and support students at higher risk of social isolation and negative psychological effects during the COVID-19 pandemic.

Short-term and long-term effects of a social network intervention on friendships among university students.

Informal social relations, such as friendships, are crucial for the well-being and success of students at all levels of education. Network interventions can aim at providing contact opportunities in school settings to prevent the social isolation of individuals and facilitate integration between otherwise segregated social groups. We investigate the short-term and long-term effects of one specific network intervention in an undergraduate cohort freshly admitted to an engineering department ([Formula: see text]). In this intervention, we randomly assigned students into small groups at an introduction event two months prior to their first day at university. The groups were designed to increase mixed-gender contact opportunities. Two months after the intervention, we find a higher rate of friendships, common friends, and mixed-gender friendships in pairs of students who were assigned to the same group than in pairs from different groups (short-term effects). These effects gradually diminish over the first academic year (long-term effects). Using stochastic actor-oriented models, we investigate the long-term trajectory of the intervention effects, while considering alternative network processes, such as reciprocity, transitivity, homophily, and popularity. The results suggest that even though the induced friendship ties are less stable than other friendships, they may serve as early seeds for complex social network processes. Our study shows that simple network interventions can have a pronounced short-term effect and indirect long-term effects on the evolution and structure of student communities.

Depressive symptoms are associated with social isolation in face-to-face interaction networks.

Individuals with depressive symptoms are more likely to be isolated in their social networks, which can further increase their symptoms. Although social interactions are an important aspect of individuals' social lives, little is known about how depressive symptoms affect behavioral patterns in social interaction networks. This article analyzes the effect of depressive symptoms on social interactions in two empirical settings (Ntotal = 123, Ndyadic relations = 2,454) of students spending a weekend together in a remote camp house. We measured social interactions between participants with Radio Frequency Identification (RFID) nametags. Prior to the weekend, participants were surveyed on their depressive symptoms and friendship ties. Using state-of-the-art social network analysis methods, we test four preregistered hypotheses. Our results indicate that depressive symptoms are associated with (1) spending less time in social interaction, (2) spending time with similarly depressed others, (3) spending time in pair-wise interactions rather than group interactions but not with (4) spending relatively less time with friends. By "zooming in" on face-to-face social interaction networks, these findings offer new insights into the social consequences of depressive symptoms.

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. We show that problems with centrality indices discussed in the social network literature also apply to the psychological networks. Assumptions underlying centrality indices, such as presence of a flow and shortest paths, may not correspond with a general theory of how psychological variables relate to one another. Furthermore, the assumptions of node distinctiveness and node exchangeability may not hold in psychological networks. We conclude that, for psychological networks, betweenness and closeness centrality seem especially unsuitable as measures of node importance. We therefore suggest three ways forward: (a) using centrality measures that are tailored to the psychological network context, (b) reconsidering existing measures of importance used in statistical models underlying psychological networks, and (c) discarding the concept of node centrality entirely. Foremost, we argue that one has to make explicit what one means when one states that a node is central, and what assumptions the centrality measure of choice entails, to make sure that there is a match between the process under study and the centrality measure that is used. (PsycINFO Database Record (c) 2019 APA, all rights reserved).

The validity of RFID badges measuring face-to-face interactions.

Face-to-face interactions are important for a variety of individual behaviors and outcomes. In recent years, a number of human sensor technologies have been proposed to incorporate direct observations in behavioral studies of face-to-face interactions. One of the most promising emerging technologies is the application of active Radio Frequency Identification (RFID) badges. They are increasingly applied in behavioral studies because of their low costs, straightforward applicability, and moderate ethical concerns. However, despite the attention that RFID badges have recently received, there is a lack of systematic tests on how valid RFID badges are in measuring face-to-face interactions. With two studies, we aim to fill this gap. Study 1 (N = 11) compares how data assessed with RFID badges correspond with video data of the same interactions (construct validity) and how this fit can be improved using straightforward data processing strategies. The analyses show that the RFID badges have a sensitivity of 50%, which can be enhanced to 65% when flickering signals with gaps of less than 75 s are interpolated. The specificity is relatively less affected by this interpolation process (before interpolation 97%, after interpolation 94.7%)-resulting in an improved accuracy of the measurement. In Study 2 (N = 73) we show that self-report data of social interactions correspond highly with data gathered with the RFID badges (criterion validity).

Integration in emerging social networks explains academic failure and success.

Academic success of students has been explained with a variety of individual and socioeconomic factors. Social networks that informally emerge within student communities can have an additional effect on their achievement. However, this effect of social ties is difficult to measure and quantify, because social networks are multidimensional and dynamically evolving within the educational context. We repeatedly surveyed a cohort of 226 engineering undergraduates between their first day at university and a crucial examination at the end of the academic year. We investigate how social networks emerge between previously unacquainted students and how integration in these networks explains academic success. Our study measures multiple important dimensions of social ties between students: their positive interactions, friendships, and studying relations. By using statistical models for dynamic network data, we are able to investigate the processes of social network formation in the cohort. We find that friendship ties informally evolve into studying relationships over the academic year. This process is crucial, as studying together with others, in turn, has a strong impact on students' success at the examination. The results are robust to individual differences in socioeconomic background factors and to various indirect measures of cognitive abilities, such as prior academic achievement and being perceived as smart by other students. The findings underline the importance of understanding social network dynamics in educational settings. They call for the creation of university environments promoting the development of positive relationships in pursuit of academic success.

Knowledge on types of treatment pressure. A cross-sectional study among mental health professionals.

Treatment pressure restricts patients' voluntary and autonomous decisions. Yet interventions involving treatment pressure are widely used in mental health and psychosocial services. This cross-sectional study explored whether mental health professionals' knowledge on five types of treatment pressure (no coercion, persuasion or conviction, leverage, threat, and formal coercion) was associated with sociodemographic, professional and contextual factors. A more positive attitude towards interventions involving treatment pressure was associated with underrating the level of those interventions compared with a predefined default value. The treatment setting and professional group played a minor role in 'leverage' and 'formal coercion' types of treatment pressure, respectively.

Informal coercion as a neglected form of communication in psychiatric settings in Germany and Switzerland.

AIMS: Informal coercion is a frequently used form of communication among mental health professionals to influence treatment outcomes. This study investigates the recognition, attitude, and application of different forms of informal coercion by mental health professionals. METHODS: Mental health professionals of five psychiatric institutions in Germany and Switzerland (n = 424) took part in an online survey assessing the recognition of, attitudes towards, and application of different forms of informal coercion. RESULTS: Mental health professionals did not recognize the extent of informal coercion adequately; especially stronger forms were underestimated. Recognition and application of informal coercion was predicted by attitudes towards coercion. Furthermore, there were differences between profession of participants regarding the recognition and application of informal coercion. CONCLUSIONS: It is important to realize that the extent of applied informal coercion in therapeutic communication is often not recognized by practitioners, although it might interfere with a sound therapeutic relationship.