Enhancing Student Gerocompetencies: Evaluation of an Intergenerational Service Learning Course

This article describes the development and evaluation of an intergenerational service-learning course designed to promote social work gerocompetencies. Service-learning opportunities were structured into the course, including an optional evidence-based falls prevention program, for older adults, entitled A Matter of Balance (MOB). Significant differences between pre- and posttest scores on the Geriatric Social Work Competency Scale (GSWCS) were noted for students in the service learning course (n = 13). Once MOB was introduced as an independent variable, the MOB participants scored the highest mean posttest scores for 2 GSWCS domains: values, ethics, and theoretical perspectives; and intervention. The benefits of utilizing social work gerocompetencies to guide course objectives, content, and student outcomes are discussed.     

Why the Infinite Decision Puzzle is Puzzling

Pulier (2000, Theory and Decision 49: 291) and Machina (2000, Theory and Decision 49: 293) seek to dissolve the Barrett–Arntzenius infinite decision puzzle (1999, Theory and Decision 46: 101). The proposed dissolutions, however, are based on misunderstandings concerning how the puzzle works and the nature of supertasks more generally. We will describe the puzzle in a simplified form, address the recent misunderstandings, and describe possible morals for decision theory.     

VOLUNTARY DISCLOSURE AND EARNINGS EXPECTATIONS IN MULTI-LEVEL MARKETING

Multi-level marketing (MLM) firms recruit individuals into a business opportunity but are not required to disclose the earnings of past participants. Some MLMs voluntarily create income disclosures, which may serve both marketing and risk-management functions. We create an economic experiment to explore the impact of MLM income disclosure on consumer interest and expectations. Results suggest that disclosure does not significantly alter interest in the business opportunity but does reduce expectations, on average, when subjects are asked to estimate annual income in a lab environment. We discuss findings in the context of current regulatory policy. (JEL D18, D82, M38)     

SOCIAL HIERARCHIES: A LABORATORY STUDY ON PUNISHMENT PATTERNS ACROSS NETWORKS

We experimentally study punishment patterns across network structures, and their effect on cooperation. In a repeated public goods setting, subjects can only observe and punish their neighbors. Centralized structures (like the star network) outperform other incomplete networks and reach contribution levels like the ones observed in a complete network. Our results suggest that hierarchical network structures with a commonly observed player benefit more from sanctions not because central players punish more, but because they follow, and promote, different punishment patterns. While quasi-central players in other incomplete architectures (like the line network) retaliate, and get trapped in the vicious circle of antisocial punishment, central players in the star network do not punish back, increase their contributions when sanctioned by peripheral players, and sanction other participants in a prosocial manner. Our results illustrate recent field studies on the evolutionary prevalence of hierarchical networks. We document a network-based rationale for this positive effect in an identity-free, fully anonymous environment. (JEL C72, C91, C92, D90, H41)     

Life on File: Archival Epistemology and Theory

Qualitative Sociology - History’s epistemological dilemma equally applies to sociology: how can we make claims about persons, events, and processes on the basis of archival records? This...     

Pressure to Attend Therapy,Dyadic Adjustment,and Adverse Childhood Experiences: Direct and Indirect Effects on the Therapeutic Alliance in Couples Therapy

In this study we examine the role that pressure to attend therapy, dyadic adjustment, and adverse childhood experiences (ACEs) play in developing the therapeutic alliance. A total of 351 couples received treatment as usual at three family therapy training clinics. Participants rated predictor variables at intake and alliance at the fourth session. Results of a path analysis indicate that each partner's dyadic adjustment is directly associated with the quality of her or his own alliance. In addition, when male partners report more ACEs and pressure to attend treatment, their own alliance scores decrease. Additionally, when one partner reports feeling pressure to attend therapy, the other partner's alliance decreases. Finally, for males, there is an indirect effect of dyadic adjustment on alliance through pressure to attend therapy. These results suggest that clinicians should routinely assess relationship adjustment, how pressured each partner is feeling to attend treatment, and ACEs; as these may impact alliance quality.     

An Introduction and Illustration of Bayesian Modeling in Couple and Family Therapy Research

Bayesian modeling is becoming increasing popular as a method for data analyses in the social sciences and can move couple, marriage, and family therapy (C/MFT) research forward. Bayesian modeling helps researchers better understand the uncertainty of findings and incorporate previous research into analyses. Other benefits of Bayesian modeling are the straightforward interpretation of findings, high-quality inferences even with small samples (in combination with an informative prior), and the ability to work with complex data structures (observations nested in relationships and time points) which are common in C/MFT research. This article introduces the benefits of Bayesian modeling and provides an example of an Actor–Partner Interdependence Model using R. Information on how to conduct the same analyses using Stata and MPlus is provided in the Supplemental Information.