The “Ought-Is” Problem: An Implementation Science Framework for Translating Ethical Norms Into Practice

Abstract

We argue that once a normative claim is developed, there is an imperative to effect changes based on this norm. As such, ethicists should adopt an “implementation mindset” when formulating norms, and collaborate with others who have the expertise needed to implement policies and practices. To guide this translation of norms into practice, we propose a framework that incorporates implementation science into ethics. Implementation science is a discipline dedicated to supporting the sustained enactment of interventions. We further argue that implementation principles should be integrated into the development of specific normative claims as well as the enactment of these norms. Ethicists formulating a specific norm should consider whether that norm can feasibly be enacted because the resultant specific norm will directly affect the types of interventions subsequently developed. To inform this argument, we will describe the fundamental principles of implementation science, using informed consent to research participation as an illustration.     

Playing the long game: A multivariate multilevel non-linear growth curve model of long-term effects in a randomized trial of the Good Behavior Game

This cluster randomized controlled trial (RCT) examined the impact of the Good Behavior Game (GBG) on children's developmental trajectories of disruptive behavior, concentration problems, and prosocial behavior from middle childhood (ages 6–7 years) to early adolescence (ages 10–11 years). Seventy-seven schools in England were randomly assigned to intervention and control groups. Allocation was balanced by school size and the proportion of children eligible for free school meals. Children (N = 3084) ages 6–7 years at baseline were the target cohort. Outcome measures, assessed via the Teacher Observation of Child Adaptation Checklist, were taken prior to randomization (baseline – Time 1) and annually for the next 4 years (Time 2 to Time 5). During the 2-year main trial period (Time 1 to Time 3), teachers of this cohort in intervention schools implemented the GBG, whereas their counterparts in the control group continued their usual practice. A multivariate multilevel non-linear growth curve model indicated that the GBG reduced concentration problems over time. In addition, the model also revealed that the intervention improved prosocial behavior among at-risk children (e.g., those with elevated symptoms of conduct problems at Time 1, n = 485). No intervention effects were unequivocally found in relation to disruptive behavior. These findings are discussed in relation to the extant literature, strengths and limitations are noted, and practical and methodological implications are highlighted.     

Empirical Bayes Derivative Estimates

Abstract

A dynamic system is a set of interacting elements characterized by changes occurring over time. The estimation of derivatives is a mainstay for exploring dynamics of constructs, particularly when the dynamics are complicated or unknown. The presence of measurement error in many social science constructs frequently results in poor estimates of derivatives, as even modest proportions of measurement error can compound when estimating derivatives. Given the overlap in the specification of latent differential equation models and latent growth curve models, and the equivalence of latent growth curve models and mixed models under some conditions, derivatives could be estimated from estimates of random effects. This article proposes a new method for estimating derivatives based on calculating the Empirical Bayes estimates of derivatives from a mixed model. Two simulations compare four derivative estimation methods: Generalized Local Linear Approximation, Generalized Orthogonal Derivative Estimates, Functional Data Analysis, and the proposed Empirical Bayes Derivative Estimates. The simulations consider two data collection scenarios: short time series (≤10 observations) from many individuals or occasions, and long individual time series (25–500 observations). A substantive example visualizing the dynamics of intraindividual positive affect time series is also presented.     

Signaling trustworthiness: The effect of leader humor on feedback-seeking behavior

ABSTRACT

Given its capacity to cultivate a range of positive outcomes in the workplace, humor has been recognized as a valuable tool for leadership purposes. However, the theoretical understanding of leader humor remains relatively limited and the mechanism through which it influences follower outcomes has not been clearly identified. Drawing on signaling theory, we developed and empirically tested a model which delineates the relationship between leader humor and a specific follower behavior – proactive feedback seeking. We collected data from 304 employees and their respective leaders working in a large Canadian retail organization. Results of our analyses indicate that leader humor can impact subordinate feedback-seeking behavior via its influence on subordinates’ affect-based and cognition-based trust in the leader.