How are Conversations via an On-Demand Peer-To-Peer Emotional Well-Being App Associated with Emotional Improvement?

Non-clinical, on-demand peer-to-peer (PtP) support apps have become increasingly popular over the past several years. Although not as pervasive as general self-help apps, these PtP support apps are usually free and instantly connect individuals through live texting with a non-clinical volunteer who has been minimally trained to listen and offer support. To date, there is little empirical work that examines whether and how using an on-demand PtP support app improves emotional well-being. Applying regression and multilevel models to N = 1000+ PtP conversations, this study examined whether individuals experience emotional improvement following a conversation on a PtP support app (HearMe) and whether dyadic characteristics of the conversation - specifically, verbal and emotional synchrony - are associated with individuals' emotional improvement. We found that individuals reported emotional improvement following a conversation on the PtP support app and that verbal (but not emotional) synchrony was associated with the extent of individuals' emotional improvement. Our results suggest that online PtP support apps are a viable source of help. We discuss cautions and considerations when applying our findings to enhance the delivery of support provision on PtP apps.

A Screenshot Vignette Study of Caregiver Perceptions of Adolescent Digital Dating Abuse.

Recent national data show that approximately three-quarters of adolescents experience digital dating abuse (DDA). Caregivers' perceptions and knowledge of online risk behaviors are important points of prevention and intervention, yet little is known about how caregivers view adolescent DDA and whether they can recognize DDA in complex interactions (e.g., DDA behaviors interwoven with positive relational behaviors). An ethnic/racial and gender-diverse sample of 289 caregivers of at least one adolescent reported on their risk perceptions of DDA, level of comfort discussing DDA with their adolescent, and whether they could identify DDA in hypothetical vignettes of online interactions between adolescent romantic partners. We found that caregivers' risk perceptions of adolescent DDA were consistent with rates of adolescent-reported DDA in the literature and that caregivers reported being comfortable discussing DDA with their adolescent. Furthermore, we found that caregivers' ability to identify DDA behaviors (or its absence) correctly in the vignettes depended on the interaction context. Specifically, it was more difficult for caregivers to identify DDA when the interaction included positive emotions. Our findings suggest that there is promise for prevention and intervention given caregivers' acknowledgment of DDA and their willingness to discuss it.

Examining individual differences in how interaction behaviors change over time: A dyadic multinomial logistic growth modeling approach.

Several theoretical perspectives suggest that dyadic experiences are distinguished by patterns of behavioral change that emerge during interactions. Methods for examining change in behavior over time are well elaborated for the study of change along continuous dimensions. Extensions for charting increases and decreases in individuals' use of specific, categorically defined behaviors, however, are rarely invoked. Greater accessibility of Bayesian frameworks that facilitate formulation and estimation of the requisite models is opening new possibilities. This article provides a primer on how multinomial logistic growth models can be used to examine between-dyad differences in within-dyad behavioral change over the course of an interaction. We describe and illustrate how these models are implemented in the Bayesian framework using data from support conversations between strangers (N = 118 dyads) to examine (RQ1) how six types of listeners' and disclosers' behaviors change as support conversations unfold and (RQ2) how the disclosers' preconversation distress moderates the change in conversation behaviors. The primer concludes with a series of notes on (a) implications of modeling choices, (b) flexibility in modeling nonlinear change, (c) necessity for theory that specifies how and why change trajectories differ, and (d) how multinomial logistic growth models can help refine current theory about dyadic interaction. (PsycInfo Database Record (c) 2023 APA, all rights reserved).

Conceptualizing and Examining Change in Communication Research.

Communication research often focuses on processes of communication, such as how messages impact individuals over time or how interpersonal relationships develop and change. Despite their importance, these change processes are often implicit in much theoretical and empirical work in communication. Intensive longitudinal data are becoming increasingly feasible to collect and, when coupled with appropriate analytic frameworks, enable researchers to better explore and articulate the types of change underlying communication processes. To facilitate the study of change processes, we (a) describe advances in data collection and analytic methods that allow researchers to articulate complex change processes of phenomena in communication research, (b) provide an overview of change processes and how they may be captured with intensive longitudinal methods, and (c) discuss considerations of capturing change when designing and implementing studies. We are excited about the future of studying processes of change in communication research, and we look forward to the iterations between empirical tests and theory revision that will occur as researchers delve into studying change within communication processes.

Dyadic analysis and the reciprocal one-with-many model: Extending the study of interpersonal processes with intensive longitudinal data.

Newly available data streams from experience sampling studies and social media are providing new opportunities to study individuals' dyadic relations. The "one-with-many" (OWM) model (Kenny et al., 2006; Kenny & Winquist, 2001) was specifically constructed for and is used to examine features of multiple dyadic relationships that one set of focal persons (e.g., therapists, physicians) has with others (e.g., multiple clients, multiple patients). Originally, the OWM model was constructed for and applied to cross-sectional data. However, the model can be extended to accommodate and may be particularly useful for the analysis of intensive repeated measures data now being obtained through experience sampling and social media. This article (a) provides a practical tutorial on fitting the OWM model, (b) describes how the OWM model is extended for analysis of repeated measures data, and (c) illustrates application of the OWM model using reports about interpersonal behavior and benefits individuals experienced in 64,111 social interactions during 9 weeks of study (N = 150). Our presentation highlights the utility of the OWM model for examining interpersonal processes in everyday life. (PsycInfo Database Record (c) 2022 APA, all rights reserved).

Do New Romantic Couples Use More Similar Language Over Time? Evidence from Intensive Longitudinal Text Messages.

The digital text traces left by computer-mediated communication (CMC) provide a new opportunity to test theories of relational processes that were originally developed through observation of face-to-face interactions. Communication accommodation theory, for example, suggests that conversation partners' verbal (and non-verbal) behaviors become more similar as relationships develop. Using a corpus of 1+ million text messages that 41 college-age romantic couples sent to each other during their first year of dating, this study examines how linguistic alignment of new romantic couples' CMC changes during relationship formation. Results from nonlinear growth models indicate that three aspects of daily linguistic alignment (syntactic-language style matching, semantic-latent semantic analysis, overall-cosine similarity) all exhibit exponential growth to an asymptote as romantic relationships form. Beyond providing empirical support that communication accommodation theory also applies in romantic partners' CMC, this study demonstrates how relational processes can be examined using digital trace data.

Monte Carlo simulations using extant data to mimic populations: Applications to the modified linear probability model and logistic regression.

Monte Carlo simulations are widely used in the social sciences to explore the viability of analytic methods in the face of assumption violations. Simulation results, however, may not be applicable to substantive research applications because they often are conducted under idealized rather than realistic conditions. Shortcomings of simulation design are discussed using linear equations as a case study, focusing on (a) variable distributions, (b) population level specification error, (c) population level measurement precision, and (d) predictor variable relationships. A new strategy is presented, called extant data simulation, which can be used to supplement traditional simulation designs to provide perspectives on Monte Carlo study conclusion generalizability to realistic research scenarios. The approach is illustrated for a binary regression simulation comparing a modified linear probability model to logistic regression. The demonstration results affirm the potential use of a modified linear probability model in a range of analytic contexts, contrary to common recommendations. It also establishes the simplicity and utility of extant data simulation designs for addressing generalizability of traditional Monte Carlo based conclusions. (PsycInfo Database Record (c) 2021 APA, all rights reserved).

Screenomics: A Framework to Capture and Analyze Personal Life Experiences and the Ways that Technology Shapes Them.

Digital experiences capture an increasingly large part of life, making them a preferred, if not required, method to describe and theorize about human behavior. Digital media also shape behavior by enabling people to switch between different content easily, and create unique threads of experiences that pass quickly through numerous information categories. Current methods of recording digital experiences provide only partial reconstructions of digital lives that weave - often within seconds - among multiple applications, locations, functions and media. We describe an end-to-end system for capturing and analyzing the "screenome" of life in media, i.e., the record of individual experiences represented as a sequence of screens that people view and interact with over time. The system includes software that collects screenshots, extracts text and images, and allows searching of a screenshot database. We discuss how the system can be used to elaborate current theories about psychological processing of technology, and suggest new theoretical questions that are enabled by multiple time scale analyses. Capabilities of the system are highlighted with eight research examples that analyze screens from adults who have generated data within the system. We end with a discussion of future uses, limitations, theory and privacy.

The Idiosyncrasies of Everyday Digital Lives: Using the Human Screenome Project to Study User Behavior on Smartphones.

Most methods used to make theory-relevant observations of technology use rely on self-report or application logging data where individuals' digital experiences are purposively summarized into aggregates meant to describe how the average individual engages with broadly defined segments of content. This aggregation and averaging masks heterogeneity in how and when individuals actually engage with their technology. In this study, we use screenshots (N > 6 million) collected every five seconds that were sequenced and processed using text and image extraction tools into content-, context-, and temporally-informative "screenomes" from 132 smartphone users over several weeks to examine individuals' digital experiences. Analyses of screenomes highlight extreme between-person and within-person heterogeneity in how individuals switch among and titrate their engagement with different content. Our simple quantifications of textual and graphical content and flow throughout the day illustrate the value screenomes have for the study of individuals' smartphone use and the cognitive and psychological processes that drive use. We demonstrate how temporal, textual, graphical, and topical features of people's smartphone screens can lay the foundation for expanding the Human Screenome Project with full-scale mining that will inform researchers' knowledge of digital life.

Screenomics: A New Approach for Observing and Studying Individuals' Digital Lives.

AIMS: This study describes when and how adolescents engage with their fast-moving and dynamic digital environment as they go about their daily lives. We illustrate a new approach - screenomics - for capturing, visualizing, and analyzing screenomes, the record of individuals' day-to-day digital experiences. SAMPLE: Over 500,000 smartphone screenshots provided by four Latino/Hispanic youth, age 14-15 years, from low-income, racial/ethnic minority neighborhoods. METHOD: Screenomes collected from smartphones for one to three months, as sequences of smartphone screenshots obtained every five seconds that the device is activated, are analyzed using computational machinery for processing images and text, machine learning algorithms, human-labeling, and qualitative inquiry. FINDINGS: Adolescents' digital lives differ substantially across persons, days, hours, and minutes. Screenomes highlight the extent of switching among multiple applications, and how each adolescent is exposed to different content at different times for different durations - with apps, food-related content, and sentiment as illustrative examples. IMPLICATIONS: We propose that the screenome provides the fine granularity of data needed to study individuals' digital lives, for testing existing theories about media use, and for generation of new theory about the interplay between digital media and development.

Emotion socialization as a dynamic process across emotion contexts.

Emotion-related socialization behaviors that occur during parent-child interactions are dynamic. According to Eisenberg, Cumberland, and Spinrad's (1998) model, ongoing parental reactions to emotions and discussions of emotion indirectly shape children's socioemotional competence throughout childhood and adolescence. Typically developing adolescents-girls especially-are at increased risk for developing internalizing symptoms. We examined if and how emotion dynamics of mother-daughter interactions contribute to adolescent girls' internalizing symptoms. We applied grid-sequence analysis (Brinberg, Fosco, & Ram, 2017) to observational data obtained while N = 96 typically developing adolescent girls (Mage = 13.99 years) and their mothers engaged in 5 different emotionally-laden discussions. We identified patterns of expressed emotions that unfolded during each discussion and examined how interdyad differences in those patterns were associated with mothers' and daughters' internalizing symptoms. Dyads differed with respect to whether mothers or daughters tended to regulate positive emotion expressions. Interdyad differences in moment-to-moment dynamics of happy/excited and worried/sad discussions were associated with adolescent girls' social anxiety symptoms, although differences in emotion dynamics of proud, frustrated/annoyed, and grateful discussions were not. Taken together, results illustrate how methodological innovations are enabling new examination and detailed description of parent-child emotion socialization dynamics. (PsycINFO Database Record (c) 2020 APA, all rights reserved).

Exploring Processes in Day-to-Day Parent-Adolescent Conflict and Angry Mood: Evidence for Circular Causality.

Parent-adolescent conflict has been studied both as a precursor of long-term macrolevel developmental risks and as an outcome of microlevel, moment-to-moment interaction patterns. However, the family-level processes underlying the maintenance or regulation of conflict in daily life are largely overlooked. A meso-level understanding of parent-adolescent conflict offers important practical insights that have direct implications for interventions. The present study explores day-to-day reciprocal processes and carryover in parents' and adolescents' experiences of anger and conflict. Daily diary data provided by parent-adolescent dyads (N = 151) from two-caregiver households (adolescents: 61.59% female, mean age = 14.60 years) over 21 days were examined using a multivariate Poisson multilevel model to evaluate the circular causality principle in parents' and adolescents' daily conflict and anger. Findings offer empirical support for the theory, suggesting that parents' and adolescents' anger and conflict exist together in a feedback loop wherein conflict is both a consequence of past anger and also an antecedent of future anger, both within and across persons. Increased understanding of the daily interaction patterns and maintenance of parent-adolescent conflict can guide more informed, targeted, and well-timed interventions intended to ameliorate the consequences of problematic parent-adolescent conflict sequences.

El conflicto entre padres y adolescentes se ha estudiado como precursor de riesgos del desarrollo a nivel macro y a largo plazo y como resultado de los patrones de interacción a cada momento y a nivel micro. Sin embargo, los procesos a nivel familiar que subyacen al mantenimiento o a la regulación del conflicto en la vida diaria se pasan por alto en gran medida. Una comprensión a nivel meso del conflicto entre padres y adolescentes ofrece importantes conocimientos prácticos que tienen consecuencias directas para las intervenciones. El presente estudio analiza los procesos recíprocos diarios y residuales en las experiencias de enfado y conflicto de los padres y los adolescentes. Se analizaron los datos de los registros diarios proporcionados por las díadas padre-adolescente (N= 151) de dos hogares de cuidadores (adolescentes: 61.59 % sexo femenino, edad promedio= 14.60 años) durante 21 días utilizando un modelo multivariado y multinivel de Poisson para evaluar el principio de causalidad circular en el conflicto y el enfado diarios de los padres y los adolescentes. Los resultados ofrecen respaldo empírico para la teoría, ya que sugieren que el enfado y el conflicto de los padres y los adolescentes existen juntos en un círculo vicioso en el cual el conflicto es tanto una consecuencia del enfado anterior como un antecedente del enfado futuro, tanto dentro como entre las personas. Una mayor comprensión de los patrones de interacción diaria y del mantenimiento del conflicto entre padres y adolescentes puede guiar intervenciones más informadas, orientadas y oportunas destinadas a mejorar las consecuencias de las secuencias problemáticas de conflicto entre padres y adolescentes.

Examining inter-family differences in intra-family (parent-adolescent) dynamics using grid-sequence analysis.

Family systems theorists have forwarded a set of theoretical principles meant to guide family scientists and practitioners in their conceptualization of patterns of family interaction-intra-family dynamics-that, over time, give rise to family and individual dysfunction and/or adaptation. In this article, we present an analytic approach that merges state space grid methods adapted from the dynamic systems literature with sequence analysis methods adapted from molecular biology into a "grid-sequence" method for studying inter-family differences in intra-family dynamics. Using dyadic data from 86 parent-adolescent dyads who provided up to 21 daily reports about connectedness, we illustrate how grid-sequence analysis can be used to identify a typology of intrafamily dynamics and to inform theory about how specific types of intrafamily dynamics contribute to adolescent behavior problems and family members' mental health. Methodologically, grid-sequence analysis extends the toolbox of techniques for analysis of family experience sampling and daily diary data. Substantively, we identify patterns of family level microdynamics that may serve as new markers of risk/protective factors and potential points for intervention in families. (PsycINFO Database Record

The Questionable Ecological Validity of Ecological Momentary Assessment: Considerations for Design and Analysis.

Experience sampling (ESM), diary, ecological momentary assessment (EMA), ambulatory monitoring, and related methods are part of a research tradition aimed at capturing the ongoing stream of individuals' behavior in real-world situations. By design, these approaches prioritize ecological validity. In this paper, we examine how the purported ecological validity these study designs provide may be compromised during data analysis. After briefly outlining the benefits of EMA-type designs, we highlight some of the design issues that threaten ecological validity, illustrate how the typical multilevel analysis of EMA-type data can compromise generalizability to "real-life", and consider how unobtrusive monitoring and person-specific analysis may provide for more precise descriptions of individuals' actual human ecology.

Analyzing Dyadic Data Using Grid-Sequence Analysis: Interdyad Differences in Intradyad Dynamics.

Objectives: Spouses are proximal contexts for and influence each other's behaviors, particularly in old age. In this article, we forward an integrated approach that merges state space grid methods adapted from the dynamic systems literature with sequence analysis methods adapted from molecular biology into a "grid-sequence" method for studying interdyad differences in intradyad dynamics. Method: Using dyadic data from 108 older couples (MAge = 75.18 years) with six within-day emotion and activity reports over 7 days, we illustrate how grid-sequence analysis can be used to identify a taxonomy of dyads with different emotion dynamics. Results: Results provide a basis for measuring a set of dyad-level variables that capture dynamic equilibrium, daily routines, and interdyad differences. Specifically, we identified four groups of dyads who differed in how their moment-to-moment happiness was organized, with some evidence that these patterns were related to dyad-level differences in agreement on amount of time spent with partner and in subjective health. Discussion: Methodologically, grid-sequence analysis extends the toolbox of techniques for analysis of dyadic experience sampling data. Substantively, we identify patterns of dyad-level microdynamics that may serve as new markers of risk/protective factors and potential points for intervention in older adults' proximal context.