Buscador de artigos científicos

Howard Rachlin and his contemporaries pioneered basic behavioral science innovations that have been usefully applied to advance understanding of human substance use disorder and related health behaviors. We briefly summarize the innovations of molar behaviorism (the matching law), behavioral economics, and teleological behaviorism. Behavioral economics and teleological behaviorism's focus on final causes are especially illuminating for these applied fields. Translational and applied research are summarized for laboratory studies of temporal discounting and economic demand, cohort studies of alcohol and other drug use in the natural environment, and experimental behavioral economic modeling of health behavior‐related public health policies. We argue that the teleological behavioral perspective on health behavior is conducive to and merges seamlessly with the contemporary socioecological model of health behavior, which broadens the contextual influences (e.g., community, economic, infrastructure, health care access and policy) of individuals’ substance use and other health risk behaviors. Basic‐to‐applied translations to date have been successful and bode well for continued applications of basic science areas pioneered by Howard Rachlin and his contemporaries.

Perhaps the most popular definition of psychology is the science of mind and behavior. However, the interrelation between mind and behavior is one of continuing controversy. The present paper examines this enduring issue from the perspectives of George J. Romanes, an early comparative psychologist, Edwin G. Boring, an influential experimental psychologist, and Howard Rachlin, an estimable recent behaviorist. Their respective positions shed considerable light on both the theory and practice of behavioral psychology.

Abstract We present the mathematical description of feedback functions of variable interval and variable differential reinforcement of low rates as functions of schedule size only. These results were obtained using an R script named Beak, which was built to simulate rates of behavior interacting with simple schedules of reinforcement. Using Beak, we have simulated data that allow an assessment of different reinforcement feedback functions. This was made with unparalleled precision, as simulations provide huge samples of data and, more importantly, simulated behavior is not changed by the reinforcement it produces. Therefore, we can vary response rates systematically. We've compared different reinforcement feedback functions for random interval schedules, using the following criteria: meaning, precision, parsimony, and generality. Our results indicate that the best feedback function for the random interval schedule was published by Baum (1981). We also propose that the model used by Killeen (1975) is a viable feedback function for the random differential reinforcement of low rates schedule. We argue that Beak paves the way for greater understanding of schedules of reinforcement, addressing still open questions about quantitative features of simple schedules. Also, Beak could guide future experiments that use schedules as theoretical and methodological tools.

Abstract Incidental bidirectional naming (Inc‐BiN) has been defined as a verbal developmental cusp whereby children demonstrate learning the names of things as listener and speaker as a function of observation alone. Stimulus characteristics have been found to affect performance in tests for Inc‐BiN. To further explore this effect, Experiment 1 compared untaught listener and speaker responses for novel familiar‐type versus novel nonfamiliar‐type stimuli with 20 first‐grade students following naming experiences in which the participants observed each visual stimulus five times while hearing its name. Participants performed significantly better with familiar‐type than with nonfamiliar‐type stimuli. Experiment 2 examined the effects of a repeated‐probe intervention to induce Inc‐BiN with nonfamiliar‐type stimuli. Participants were six first‐grade students who demonstrated incidental unidirectional naming (i.e., acquired names as listener from exposure alone). Implementation of the intervention was staggered across dyads of participants in a multiple‐probe, simultaneous‐treatments design. One participant in each dyad received the intervention with nonfamiliar‐type stimuli only and the other with both nonfamiliar‐ and familiar‐type stimuli. Pre‐ and postintervention Inc‐BiN probes with stimuli not included in the intervention suggested both conditions were effective in establishing Inc‐BiN for nonfamiliar‐type stimuli. These findings have implications for understanding the mechanisms underlying Inc‐BiN.

Abstract While trying to infer laws of behavior, accounting for both within‐subjects and between‐subjects variance is often overlooked. It has been advocated recently to use multilevel modeling to analyze matching behavior. Using multilevel modeling within behavior analysis has its own challenges though. Adequate sample sizes are required (at both levels) for unbiased parameter estimates. The purpose of the current study is to compare parameter recovery and hypothesis rejection rates of maximum likelihood (ML) estimation and Bayesian estimation (BE) of multilevel models for matching behavior studies. Four factors were investigated through simulations: number of subjects, number of measurements by subject, sensitivity (slope), and variance of the random effect. Results showed that both ML estimation and BE with flat priors yielded acceptable statistical properties for intercept and slope fixed effects. The ML estimation procedure generally had less bias, lower RMSE, more power, and false‐positive rates closer to the nominal rate. Thus, we recommend ML estimation over BE with uninformative priors, considering our results. The BE procedure requires more informative priors to be used in multilevel modeling of matching behavior, which will require further studies.

Abstract Procedural fidelity is the extent to which independent variables are implemented as designed. Despite 40 years of discussion about the importance of procedural fidelity for behavioral research, reporting of fidelity data remains an uncommon practice in behavior‐analytic journals. Researchers have speculated about reasons for underreporting, but the perspectives of scholars about when reporting is warranted or necessary have not yet been explored. Thus, the purpose of this study was to evaluate possible reasons for infrequent reporting of fidelity data in behavior‐analytic studies. To address this purpose, we conducted focus groups with scholars in applied behavior analysis. Five themes emerged regarding why procedural fidelity data are not typically reported. We provide a discussion about how these themes are interrelated and offer suggestions and recommendations to assist with the collection and reporting of fidelity data.

Abstract Renewal is a type of relapse that occurs due to a change in context. Previous research has demonstrated that renewal of target responding may occur despite the availability of differential reinforcement for an alternative response (DRA). Nevertheless, the current literature on renewal presents mixed findings regarding the effects of dense and lean schedules of DRA on the magnitude of renewal. We used a translational approach with undergraduate college students and a task on a touchscreen tablet device to study the effects of dense and lean schedules of DRA during repeated renewal tests. All participants experienced two, three‐phase ABA renewal arrangements. In the dense and lean renewal arrangements, we differentially reinforced alternative behavior in Context B and the renewal test in Context A on a VI 3‐s or a VI 12‐s schedule, respectively. Overall, we observed renewal in 31/36 (86%) renewal tests regardless of the density of reinforcement for the alternative response. Furthermore, the results showed that although renewal occurred in both arrangements, we found slightly higher magnitudes of renewal during DRA with lean schedules of reinforcement relative to dense schedules. We discuss the implications of these findings as they relate to the treatment of problem behavior.

Howard Rachlin's widely influential behavioral economic approach to self‐control and related issues provides the model for this submission. The topic is overconsumption. Current human consumption levels are unsustainable. Explanations typically focus on societal factors, such as the seductive power of advertising and/or misguided tax policies. However, the effectiveness of these factors depends on the degree to which individuals are susceptible to the message: “consume more.” Humans are not blank slates. This paper argues that how individuals frame their choices establishes the susceptibility to overconsume. According to economic theory, consumers frame their options as bundles, composed of different combinations of the available items and activities. This leads to maximizing. In experiments, participants tend to frame their options as “either‐or” choices. This leads to the matching law. Mathematical models of concurrent schedule choice procedures show that (1) the matching law implies overconsumption of the most preferred option and (2) that individuals will persist in preferring their favorite option even when doing so reduces overall reward rates. Given that the matching law better describes how individuals choose than does maximizing, the mathematical models of widely used choice procedures help explain why efforts to increase consumption have been more influential than efforts to control consumption.