@article{TeerlingBernholtAsseburgetal.2019, author = {Teerling, Annika and Bernholt, Andrea and Asseburg, Regine and Hasl, Andrea and Igler, Jennifer and Schlitter, Theresa and Ohle-Peters, Annika and McElvany, Nele and K{\"o}ller, Olaf}, title = {Affektiv-kognitive Auseinandersetzung mit einer Innovation im Implementationsprozess}, series = {Psychologie in Erziehung und Unterricht : Zeitschrift f{\"u}r Forschung und Praxis}, volume = {66}, journal = {Psychologie in Erziehung und Unterricht : Zeitschrift f{\"u}r Forschung und Praxis}, number = {1}, publisher = {Reinhardt}, address = {M{\"u}nchen}, issn = {0342-183X}, doi = {10.2378/peu2018.art21d}, pages = {33 -- 50}, year = {2019}, abstract = {Schulische und vor allem unterrichtliche Implementationsprozesse zielen zumeist auf die Professionalisierung der Lehrkr{\"a}fte ab. Die intendierte Ver{\"a}nderung des Unterrichts beginnt dabei mit einer gew{\"u}nschten Ver{\"a}nderung von Einstellungen und Verhaltensweisen der Lehrkr{\"a}fte, welche erst zu einer ver{\"a}nderten Handlungsroutine in der Arbeitspraxis f{\"u}hren kann. Das Modell der Stages of Concern von Hall und Hord (2006) stellt eine der wenigen M{\"o}glichkeiten dar, die individuelle Perspektive der Lehrkr{\"a}fte im Implementationsprozess modellbasiert und standardisiert zu untersuchen. Der vorliegende Beitrag betrachtet anhand dieses Modells die affektiv-kognitive Auseinandersetzung der Beteiligten im Implementationsprozess sowie deren Zusammenh{\"a}nge mit verschiedenen Aspekten der Kommunikation und der wahrgenommenen Entwicklung. Auf Basis einer Stichprobe von N = 66 Lehrkr{\"a}ften kann dabei gezeigt werden, dass insbesondere die Aspekte H{\"a}ufigkeit der Kooperation, Kommunikation im Kollegium und Erfahrungen im Team die affektiv-kognitive Auseinandersetzung vorhersagen. Diese Auseinandersetzung - insbesondere mit den Konsequenzen der Neuerung - bedingt wiederum die wahrgenommene Entwicklung im Implementationsprozess.}, language = {de} } @article{SchachnerGrossHasletal.2021, author = {Schachner, Theresa and Gross, Christoph and Hasl, Andrea and Wangenheim, Florian von and Kowatsch, Tobias}, title = {Deliberative and paternalistic interaction styles for conversational agents in digital health}, series = {Journal of medical internet research : international scientific journal for medical research, information and communication on the internet ; JMIR}, volume = {23}, journal = {Journal of medical internet research : international scientific journal for medical research, information and communication on the internet ; JMIR}, number = {1}, publisher = {Healthcare World}, address = {Richmond, Va.}, issn = {1438-8871}, doi = {10.2196/22919}, pages = {13}, year = {2021}, abstract = {Background: Recent years have witnessed a constant increase in the number of people with chronic conditions requiring ongoing medical support in their everyday lives. However, global health systems are not adequately equipped for this extraordinarily time-consuming and cost-intensive development. Here, conversational agents (CAs) can offer easily scalable and ubiquitous support. Moreover, different aspects of CAs have not yet been sufficiently investigated to fully exploit their potential. One such trait is the interaction style between patients and CAs. In human-to-human settings, the interaction style is an imperative part of the interaction between patients and physicians. Patient-physician interaction is recognized as a critical success factor for patient satisfaction, treatment adherence, and subsequent treatment outcomes. However, so far, it remains effectively unknown how different interaction styles can be implemented into CA interactions and whether these styles are recognizable by users. Objective: The objective of this study was to develop an approach to reproducibly induce 2 specific interaction styles into CA-patient dialogs and subsequently test and validate them in a chronic health care context. Methods: On the basis of the Roter Interaction Analysis System and iterative evaluations by scientific experts and medical health care professionals, we identified 10 communication components that characterize the 2 developed interaction styles: deliberative and paternalistic interaction styles. These communication components were used to develop 2 CA variations, each representing one of the 2 interaction styles. We assessed them in a web-based between-subject experiment. The participants were asked to put themselves in the position of a patient with chronic obstructive pulmonary disease. These participants were randomly assigned to interact with one of the 2 CAs and subsequently asked to identify the respective interaction style. Chi-square test was used to assess the correct identification of the CA-patient interaction style. Results: A total of 88 individuals (42/88, 48\% female; mean age 31.5 years, SD 10.1 years) fulfilled the inclusion criteria and participated in the web-based experiment. The participants in both the paternalistic and deliberative conditions correctly identified the underlying interaction styles of the CAs in more than 80\% of the assessments (X-1(,8)8(2)=38.2; P<.001; phi coefficient r(phi)=0.68). The validation of the procedure was hence successful. Conclusions: We developed an approach that is tailored for a medical context to induce a paternalistic and deliberative interaction style into a written interaction between a patient and a CA. We successfully tested and validated the procedure in a web-based experiment involving 88 participants. Future research should implement and test this approach among actual patients with chronic diseases and compare the results in different medical conditions. This approach can further be used as a starting point to develop dynamic CAs that adapt their interaction styles to their users.}, language = {en} } @article{HaslVoelkleKretschmannetal.2022, author = {Hasl, Andrea and Voelkle, Manuel and Kretschmann, Julia and Richter, Dirk and Brunner, Martin}, title = {A dynamic structural equation approach to modeling wage dynamics and cumulative advantage across the lifespan}, series = {Multivariate Behavioral Research}, volume = {58}, journal = {Multivariate Behavioral Research}, number = {3}, publisher = {Routledge, Taylor \& Francis Group}, address = {Abingdon}, issn = {0027-3171}, doi = {10.1080/00273171.2022.2029339}, pages = {504 -- 525}, year = {2022}, abstract = {Wages and wage dynamics directly affect individuals' and families' daily lives. In this article, we show how major theoretical branches of research on wages and inequality-that is, cumulative advantage (CA), human capital theory, and the lifespan perspective-can be integrated into a coherent statistical framework and analyzed with multilevel dynamic structural equation modeling (DSEM). This opens up a new way to empirically investigate the mechanisms that drive growing inequality over time. We demonstrate the new approach by making use of longitudinal, representative U.S. data (NLSY-79). Analyses revealed fundamental between-person differences in both initial wages and autoregressive wage growth rates across the lifespan. Only 0.5\% of the sample experienced a "strict" CA and unbounded wage growth, whereas most individuals revealed logarithmic wage growth over time. Adolescent intelligence and adult educational levels explained substantial heterogeneity in both parameters. We discuss how DSEM may help researchers study CA processes and related developmental dynamics, and we highlight the extensions and limitations of the DSEM framework.}, language = {en} } @article{HaslKretschmannRichteretal.2019, author = {Hasl, Andrea and Kretschmann, Julia and Richter, Dirk and Voelkle, Manuel and Brunner, Martin}, title = {Investigating Core Assumptions of the "American Dream": Historical Related to Key Life Outcomes in Adulthood}, series = {Psychology and aging}, volume = {34}, journal = {Psychology and aging}, number = {8}, publisher = {American Psychological Association}, address = {Washington}, issn = {0882-7974}, doi = {10.1037/pag0000392}, pages = {1055 -- 1076}, year = {2019}, abstract = {The present study examines how historical changes in the U.S. socioeconomic environment in the 20th century may have affected core assumptions of the "American Dream." Specifically, the authors examined whether such changes modulated the extent to which adolescents' intelligence (IQ), their grade point average (GPA), and their parents' socioeconomic status (SES) could predict key life outcomes in adulthood about 20 years later. The data stemmed from two representative U.S. birth cohorts of 15- and 16-year-olds who were born in the early 1960s (N = 3,040) and 1980s (N = 3,524) and who participated in the National Longitudinal Surveys of Youth (NLSY). Cohort differences were analyzed with respect to differences in average relations by means of multiple and logistic regression and for specific points in each outcome distribution by means of quantile regressions. In both cohorts, IQ, GPA, and parental SES predicted important educational, occupational, and health-related life-outcomes about 20 years later. Across historical time, the predictive utility of adolescent IQ and parental SES remained stable for the most part. Yet, the combined effects of social-ecological and socioeconomic changes may have increased the predictive utility (that is, the regression weights) of adolescent GPA for educational, occupational, and health outcomes over time for individuals who were born in the 1980s. Theoretical implications concerning adult development, aging, and late life inequality are discussed. (PsycINFO Database Record.}, language = {en} } @phdthesis{Hasl2023, author = {Hasl, Andrea}, title = {Time matters: Adopting a lifespan developmental perspective on individual differences in skills, cumulative advantages, and the role of dynamic modeling approaches}, doi = {10.25932/publishup-59511}, url = {http://nbn-resolving.de/urn:nbn:de:kobv:517-opus4-595112}, school = {Universit{\"a}t Potsdam}, pages = {274}, year = {2023}, abstract = {The impact of individual differences in cognitive skills and socioeconomic background on key educational, occupational, and health outcomes, as well as the mechanisms underlying inequalities in these outcomes across the lifespan, are two central questions in lifespan psychology. The contextual embeddedness of such questions in ontogenetic (i.e., individual, age-related) and historical time is a key element of lifespan psychological theoretical frameworks such as the HIstorical changes in DEvelopmental COntexts (HIDECO) framework (Drewelies et al., 2019). Because the dimension of time is also a crucial part of empirical research designs examining developmental change, a third central question in research on lifespan development is how the timing and spacing of observations in longitudinal studies might affect parameter estimates of substantive phenomena. To address these questions in the present doctoral thesis, I applied innovative state-of-the-art methodology including static and dynamic longitudinal modeling approaches, used data from multiple international panel studies, and systematically simulated data based on empirical panel characteristics, in three empirical studies. The first study of this dissertation, Study I, examined the importance of adolescent intelligence (IQ), grade point average (GPA), and parental socioeconomic status (pSES) for adult educational, occupational, and health outcomes over ontogenetic and historical time. To examine the possible impact of historical changes in the 20th century on the relationships between adolescent characteristics and key adult life outcomes, the study capitalized on data from two representative US cohort studies, the National Longitudinal Surveys of Youth 1979 and 1997, whose participants were born in the late 1960s and 1980s, respectively. Adolescent IQ, GPA, and pSES were positively associated with adult educational attainment, wage levels, and mental and physical health. Across historical time, the influence of IQ and pSES for educational, occupational, and health outcomes remained approximately the same, whereas GPA gained in importance over time for individuals born in the 1980s. The second study of this dissertation, Study II, aimed to examine strict cumulative advantage (CA) processes as possible mechanisms underlying individual differences and inequality in wage development across the lifespan. It proposed dynamic structural equation models (DSEM) as a versatile statistical framework for operationalizing and empirically testing strict CA processes in research on wages and wage dynamics (i.e., wage levels and growth rates). Drawing on longitudinal representative data from the US National Longitudinal Survey of Youth 1979, the study modeled wage levels and growth rates across 38 years. Only 0.5 \% of the sample revealed strict CA processes and explosive wage growth (autoregressive coefficients AR > 1), with the majority of individuals following logarithmic wage trajectories across the lifespan. Adolescent intelligence (IQ) and adult highest educational level explained substantial heterogeneity in initial wage levels and long-term wage growth rates over time. The third study of this dissertation, Study III, investigated the role of observation timing variability in the estimation of non-experimental intervention effects in panel data. Although longitudinal studies often aim at equally spaced intervals between their measurement occasions, this goal is hardly ever met. Drawing on continuous time dynamic structural equation models, the study examines the -seemingly counterintuitive - potential benefits of measurement intervals that vary both within and between participants (often called individually varying time intervals, IVTs) in a panel study. It illustrates the method by modeling the effect of the transition from primary to secondary school on students' academic motivation using empirical data from the German National Educational Panel Study (NEPS). Results of a simulation study based on this real-life example reveal that individual variation in time intervals can indeed benefit the estimation precision and recovery of the true intervention effect parameters.}, language = {en} } @article{BrunnerKellerStallaschetal.2022, author = {Brunner, Martin and Keller, Lena and Stallasch, Sophie E. and Kretschmann, Julia and Hasl, Andrea and Preckel, Franzis and Luedtke, Oliver and Hedges, Larry}, title = {Meta-analyzing individual participant data from studies with complex survey designs}, series = {Research synthesis methods}, volume = {14}, journal = {Research synthesis methods}, number = {1}, publisher = {Wiley}, address = {Hoboken}, issn = {1759-2879}, doi = {10.1002/jrsm.1584}, pages = {5 -- 35}, year = {2022}, abstract = {Descriptive analyses of socially important or theoretically interesting phenomena and trends are a vital component of research in the behavioral, social, economic, and health sciences. Such analyses yield reliable results when using representative individual participant data (IPD) from studies with complex survey designs, including educational large-scale assessments (ELSAs) or social, health, and economic survey and panel studies. The meta-analytic integration of these results offers unique and novel research opportunities to provide strong empirical evidence of the consistency and generalizability of important phenomena and trends. Using ELSAs as an example, this tutorial offers methodological guidance on how to use the two-stage approach to IPD meta-analysis to account for the statistical challenges of complex survey designs (e.g., sampling weights, clustered and missing IPD), first, to conduct descriptive analyses (Stage 1), and second, to integrate results with three-level meta-analytic and meta-regression models to take into account dependencies among effect sizes (Stage 2). The two-stage approach is illustrated with IPD on reading achievement from the Programme for International Student Assessment (PISA). We demonstrate how to analyze and integrate standardized mean differences (e.g., gender differences), correlations (e.g., with students' socioeconomic status [SES]), and interactions between individual characteristics at the participant level (e.g., the interaction between gender and SES) across several PISA cycles. All the datafiles and R scripts we used are available online. Because complex social, health, or economic survey and panel studies share many methodological features with ELSAs, the guidance offered in this tutorial is also helpful for synthesizing research evidence from these studies.}, language = {en} }