Transference of relationship qualities to a virtual world

This dissertation investigates to which extent internal working models of relationships and personality characteristics of participants are transferred to computer-generated agents in a virtual social environment (VSE). For this purpose a VSE was created that was populated with several autonomous agents which interacted with each other. Participants can control one of the the agents (the "protagonist"); one of the other agents is the spouse of the protagonist. Using this setup, a potential projection screen for the dynamics of the real-life relationship, as well as for generalized internal working models was created. Chapter 1 summarizes the research question, gives an overview of the development of the VSE called "Simoland", and provides a general summary and conclusion about the dissertation. Chapters 2 - 4 each are self-contained manuscripts. Chapter 2 („The challenge of constructing psychologically believable agents“) is a theoretical article which describes challenges and new possibilities in the implementation of psychological models into autonomous agents. Chapter 3 („Virtual social environments as a tool for psychological assessment: Dynamics of interaction with a virtual spouse“) describes the first empirical study conducted in Simoland. This study demonstrates how intrapersonal changes in interaction behavior can be investigated in VSEs. With a sample of 236 participants I could show that both the relationship satisfaction with the real life partner, and the intimacy motive of the participant had an influence on the behavior towards the virtual spouse. Hence, it could be shown that virtual behavior indeed is connected to conditions of the real world. While the first study investigated unrestricted behavior in an open world, in Chapter 4 („Transference of adult attachment dynamics to a virtual spouse“) specific, theoretically derived scenes were created which were supposed to activate the attachment system. With a sample of 422 participants we could demonstrate interindividual differences in attachment behavior as a reaction to one of three scenes: a separation, a conflict with the virtual spouse, and a threatening situation. Both attachment anxiety and attachment avoidance significantly and meaningfully correlated with the behavior in the VSE, the physical distance between protagonist and virtual spouse, and emotional ratings. To summarize, this dissertation for the first time shows that qualities of real-life relationships, as well as internal working models of attachment, are transferred to virtual agents. Thereby new ways are opened to investigate behavior in close relationships and representations of significant others through virtual scenarios.Diese Dissertation untersucht, inwieweit Beziehungsrepräsentationen und Persönlichkeitsmerkmale von Personen auf computergenerierte Agenten in einer virtuellen sozialen Umgebung (VSU) übertragen werden. Dazu wurde eine VSU erstellt, in der Teilnehmer eine virtuelle Figur (den „Protagonisten“) steuern können, welche wiederum mit anderen autonomen Agenten interagiert. Einer dieser anderen Agenten ist der virtuelle Partner/ die virtuelle Partnerin des Protagonisten, womit eine mögliche Projektionsfläche für die Beziehungsdynamik der realen Partnerschaft sowie für generalisierte interne Arbeitsmodelle von Beziehungen hergestellt wurde. Kapitel 1 fasst die Forschungsfrage zusammen und beschreibt den Entstehungsprozess der VSU namens „Simoland“, und gibt eine kurze Zusammenfassung der Gesamtergebnisse. Kapitel 2 – 4 stellen jeweils eigenständige Manuskripte dar. Kapitel 2 („The challenge of constructing psychologically believable agents“) ist ein theoretischer Artikel, der Herausforderungen und neue Wege beschreibt wie psychologische Modelle in autonome Agent implementiert werden können. Kapitel 3 („Virtual social environments as a tool for psychological assessment: Dynamics of interaction with a virtual spouse“) beschreibt die erste psychologische Untersuchung in Simoland, welche demonstriert wie intraindividuelle Entwicklung im Interaktionsverhalten untersucht werden kann. An einer Stichprobe von 236 Teilnehmern konnte gezeigt werden, dass sowohl die Beziehungszufriedenheit zum realen Partner, als auch das Intimitätsmotiv der Teilnehmer einen Einfluss auf das Verhalten in der VSU hatten, und somit das virtuelle Verhalten tatsächlich verknüpft ist mit der realen Welt. Während die erste Studie freies Verhalten untersucht hat, wurden in der zweiten Studie theoriegeleitet verschiedene Szenarien hergestellt, welche das Bindungssystem aktivieren sollen. (Kapitel 4: „Transference of adult attachment dynamics to a virtual spouse“). Dadurch konnten an 422 Teilnehmern interindividuelle Unterschiede im Bindungsverhalten als Reaktion auf folgende Szenen gezeigt werden: eine Trennungssituation, eine Konfliktsituation, sowie eine Bedrohungssituation. Die dimensionalen Bindungsstile (Bindungsvermeidung und Bindungsängstlichkeit) korrelierten sinnvoll und signifikant mit dem Verhalten in der VSU, der physikalischen Distanz zwischen Protagonist und Partner/in, sowie Emotionseinschätzungen. Zusammenfasst zeigt diese Dissertation zum ersten Mal, dass Qualitäten der realen Partnerschaft, sowie interne Arbeitsmodelle der Bindung auf virtuelle Agenten übertragen werden. Somit werden neue Wege eröffnet, Beziehungsverhalten und -repräsentationen in virtuellen Szenarien zu untersuchen

Strange Carers

The present comment focuses on the distinction between attachment as bond formation and expectations of availability and responsiveness (security) within attachment relationships. We enumerate key components of bonding and functions of carer secure base support. Our analysis has implications for design and suggests that robots are unlikely to serve effectively as sole carers. Even with robots as part-time carers, attachment-like bonds would likely focus on human carers. Similarly, although infants and children would certainly build expectations regarding the availability and responsiveness of robot carers, the quality of human care would probably be the determining influence on later development and competence. Notwithstanding their limitations of robots as attachment figures they have considerable potential to extend parental care and enrich infant exploration. The Sharkey’s paper and further consideration of robots as carers for infants, children, older adults, an

At what sample size do correlations stabilize?

Sample correlations converge to the population value with increasing sample size, but the estimates are often inaccurate in small samples. In this report we use Monte-Carlo simulations to determine the critical sample size from which on the magnitude of a correlation can be expected to be stable. The necessary sample size to achieve stable estimates for correlations depends on the effect size, the width of the corridor of stability (i.e., a corridor around the true value where deviations are tolerated), and the requested confidence that the trajectory does not leave this corridor any more. Results indicate that in typical scenarios the sample size should approach 250 for stable estimates

Getting the most out of your family data with the R-package fSRM

Introduction Family research aims to explore family dynamics but is often limited to the examination of unidirectional processes (e.g. parenting, child effects). As the behavior of one person has consequences that go beyond that one individual, the family functioning should be investigated in its full complexity. The Social Relations Model (SRM; Kenny & La Voie, 1984) is a conceptual and analytical model which can disentangle family dynamics at three different levels: the individual level (actor and partner effect), the dyadic level (relationship effects) and the family level (family effect). Nonetheless, its statistical complexity may be a hurdle for family researchers. The user-friendly R-package fSRM that we developed performs almost automatically those rather complex SRM analyses. Using real data the different features of the package are presented. Methods When a round robin design is used (i.e. every family member rates every other member on the same items), the etiology of the obtained dyadic scores can be unraveled using the SRM. In particular, the estimation of the SRM parameters can be based on a confirmatory factor analysis. Therefor fSRM builds on lavaan (Rosseel, 2012), a popular R-package developed for structural equation modeling. With fSRM, one simple line of R-code suffices to perform the required analysis. Results and discussion The fSRM-output provides easy-to-interpret summary tables of SRM variances, variance decompositions, individual and dyadic reciprocities. SRM means, which may be very informative - but infrequently reported - are straightforwardly obtained and can easily be compared between roles. Moreover, the package is suitable for both single and multigroup studies. Additional options (e.g. intragenerational similarities) are discussed. In sum, fSRM enables family researchers to get easily the most out of their data

Getting the most out of your family data with fSRM

Introduction Family research aims to explore family dynamics but is often limited to the examination of unidirectional processes (e.g. parenting, child effects). As the behavior of one person has consequences that go beyond that one individual, the family functioning should be investigated in its full complexity. The Social Relations Model (SRM; Kenny & La Voie, 1984) is a conceptual and analytical model which can disentangle family dynamics at three different levels: the individual level (actor and partner effect), the dyadic level (relationship effects) and the family level (family effect). Nonetheless, its statistical complexity may be a hurdle for family researchers. The user-friendly R-package fSRM (Stas, Schönbrodt & Loeys, in prep.), performs almost automatically those rather complex SRM analyses. Using real data the different features of the package are presented. Aim and methods When a round robin design is used (i.e. every family member rates every other member on the same items), the etiology of the obtained dyadic scores can be unraveled using the SRM. With fSRM, one simple line of R-code suffices to perform the required analysis. Results and discussion The fSRM-output provides easy-to-interpret summary tables of SRM variances, variance decompositions, individual and dyadic reciprocities. SRM means, which may be very informative - but infrequently reported - are straightforwardly obtained and can easily be compared between roles. Moreover, the package is suitable for both single and multigroup studies. Additional options (e.g. intragenerational similarities) are discussed. In sum, fSRM enables family researchers to get easily the most out of their data

Testing Similarity Effects with Dyadic Response Surface Analysis

Dyadic similarity effect hypotheses state that the (dis)similarity between dyad members (e.g. the similarity on a personality dimension) is related to a dyadic outcome variable (e.g. the relationship satisfaction of both partners). Typically, these hypotheses have been investigated by using difference scores or other profile similarity indices as predictors of the outcome variables. These approaches, however, have been vigorously criticized for their conceptual and statistical shortcomings. Here, we introduce a statistical method that is based on polynomial regression and addresses most of these shortcomings: dyadic response surface analysis. This model is tailored for similarity effect hypotheses and fully accounts for the dyadic nature of relationship data. Furthermore, we provide a tutorial with an illustrative example and reproducible R and Mplus scripts that should assist substantive researchers in precisely formulating, testing, and interpreting their dyadic similarity effect hypotheses