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Dive into the research topics where Derek D. Reed is active.

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Featured researches published by Derek D. Reed.


Appetite | 2014

Robust relation between temporal discounting rates and body mass

David P. Jarmolowicz; J. Bradley C. Cherry; Derek D. Reed; Jared M. Bruce; John M. Crespi; Jayson L. Lusk; Amanda S. Bruce

When given the choice between


Journal of Applied Behavior Analysis | 2010

BEHAVIORAL COACHING TO IMPROVE OFFENSIVE LINE PASS- BLOCKING SKILLS OF HIGH SCHOOL FOOTBALL ATHLETES

John V. Stokes; James K. Luiselli; Derek D. Reed; Richard K. Fleming

100 today and


Journal of Applied Behavior Analysis | 2011

A PARAMETRIC ANALYSIS OF ERRORS OF COMMISSION DURING DISCRETE-TRIAL TRAINING

Florence D. DiGennaro Reed; Derek D. Reed; Cynthia N. Baez; Helena Maguire

110 in 1 week, certain people are more likely to choose the immediate, yet smaller reward. The present study examined the relations between temporal discounting rate and body mass while accounting for important demographic variables, depressive symptoms, and behavioral inhibition and approach. After having their heights and weights measured, 100 healthy adults completed the Monetary Choice Questionnaire, the Beck Depression Inventory-II, and the Behavioral Inhibition Scale/Behavioral Approach Scale. Overweight and obese participants exhibited higher temporal discounting rates than underweight and healthy weight participants. Temporal discounting rates decreased as the magnitude of the delayed reward increased, even when other variables known to impact temporal discounting rate (i.e., age, education level, and annual household income) were used as covariates. A higher body mass was strongly related to choosing a more immediate monetary reward. Additional research is needed to determine whether consideration-of-future-consequences interventions, or perhaps cognitive control interventions, could be effective in obesity intervention or prevention programs.


Journal of Applied Behavior Analysis | 2012

A TUTORIAL ON THE USE OF EXCEL 2010 AND EXCEL FOR MAC 2011 FOR CONDUCTING DELAY-DISCOUNTING ANALYSES

Derek D. Reed; Brent A. Kaplan; Adam T. Brewer

We evaluated several behavioral coaching procedures for improving offensive line pass-blocking skills with 5 high school varsity football players. Pass blocking was measured during practice drills and games, and our intervention included descriptive feedback with and without video feedback and teaching with acoustical guidance (TAG). Intervention components and pass blocking were evaluated in a multiple baseline design, which showed that video feedback and TAG were the most effective procedures. For all players, improved pass blocking matched a standard derived by observing more experienced linemen and was evident in games. Additional intervention was required to maintain pass-blocking proficiency. Issues pertinent to behavioral coaching and sport psychology research are discussed.


Journal of Applied Behavior Analysis | 2011

Temporal Discounting Predicts Student Responsiveness to Exchange Delays in a Classroom Token System.

Derek D. Reed; Brian K. Martens

We investigated the effects of systematic changes in levels of treatment integrity by altering errors of commission during error-correction procedures as part of discrete-trial training. We taught 3 students with autism receptive nonsense shapes under 3 treatment integrity conditions (0%, 50%, or 100% errors of commission). Participants exhibited higher levels of performance during perfect implementation (0% errors). For 2 of the 3 participants, performance was low and showed no differentiation in the remaining conditions. Findings suggest that 50% commission errors may be as detrimental as 100% commission errors on teaching outcomes.


Journal of Applied Behavior Analysis | 2010

A behavioral intervention for teaching tackling skills to high school football athletes

John V. Stokes; James K. Luiselli; Derek D. Reed

In recent years, researchers and practitioners in the behavioral sciences have profited from a growing literature on delay discounting. The purpose of this article is to provide readers with a brief tutorial on how to use Microsoft Office Excel 2010 and Excel for Mac 2011 to analyze discounting data to yield parameters for both the hyperbolic discounting model and area under the curve. This tutorial is intended to encourage the quantitative analysis of behavior in both research and applied settings by readers with relatively little formal training in nonlinear regression.


Behavior Analyst | 2009

What Are We Doing When We Translate from Quantitative Models

Thomas S. Critchfield; Derek D. Reed

Typical assessments of temporal discounting involve presenting choices between hypothetical monetary outcomes. Participants choose between smaller immediate rewards and larger delayed rewards to determine how the passage of time affects the subjective value of reinforcement. Few studies, however, have compared such discounting to actual manipulations of reward delay. The present study examined the predictive validity of a temporal discounting procedure developed for use with children. Forty-six sixth-grade students completed a brief discounting assessment and were then exposed to a classwide intervention that involved both immediate and delayed reinforcement in a multiple baseline design across classrooms. The parameters derived from two hyperbolic models of discounting correlated significantly with actual on-task behavior under conditions of immediate and delayed exchange. Implications of temporal discounting assessments for behavioral assessment and treatment are discussed.


Psychological Record | 2011

The “Tyranny of Choice”: Choice Overload as a Possible Instance of Effort Discounting

Derek D. Reed; Florence D. DiGennaro Reed; James T. Chok; Gary A. Brozyna

We evaluated an intervention that combined task analysis and differential reinforcement for teaching tackling skills to 2 high school football athletes. As a result of intervention, both players tackled more proficiently in practice drills and maintained proficient tackling during games.


Journal of Applied Behavior Analysis | 2009

Using Microsoft Office Excel 2007 to conduct generalized matching analyses.

Derek D. Reed

Although quantitative analysis (in which behavior principles are defined in terms of equations) has become common in basic behavior analysis, translational efforts often examine everyday events through the lens of narrative versions of laboratory-derived principles. This approach to translation, although useful, is incomplete because equations may convey concepts that are difficult to capture in words. To support this point, we provide a nontechnical introduction to selected aspects of quantitative analysis; consider some issues that translational investigators (and, potentially, practitioners) confront when attempting to translate from quantitative models; and discuss examples of relevant translational studies. We conclude that, where behavior-science translation is concerned, the quantitative features of quantitative models cannot be ignored without sacrificing conceptual precision, scientific and practical insights, and the capacity of the basic and applied wings of behavior analysis to communicate effectively.


Behavior analysis in practice | 2013

Behavioral Economics: A Tutorial for Behavior Analysts in Practice

Derek D. Reed; Christopher R. Niileksela; Brent A. Kaplan

When making a choice, people like to have options, but an emerging literature on “choice overload” suggests that the provision of too many options results in adverse experiences, including a depletion of cognitive resources and postdecision feelings of regret. A strong implication is that individuals should shy away from situations involving too many options. The present study examined whether this expression of choice overload would emerge when human services workers confronted hypothetical scenarios involving choices of treatment strategies. On different trials, the participants indicated preference for single-option, limited-options, and extensive-options scenarios, wherein the number of extensive-options alternatives geometrically increased across successive trials. In general, preference for extensive-options scenarios decreased with the number of options that they incorporated. Preference for extensive options was well described by a negatively decelerating, hyperbolic-like function that typically is employed in studies of discounting. Moreover, as expected based on the choice overload framework, participants who were categorized as “maximizers” using the Maximization and Regret Scales demonstrated lower discounting (i.e., lower k value) than those categorized as “satisficers.” We discuss how a quantitative discounting framework may be fruitfully applied to advance the study of choice overload.

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Jared M. Bruce

University of Missouri–Kansas City

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