Empirical Matching, Matching Theory, and an Evolutionary Theory of Behavior Dynamics in Clinical Application

McDowell, J. J.

doi:10.1007/s40614-021-00296-w

Cited by 7 publications

(13 citation statements)

References 92 publications

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“…However, a comprehensive review of the details of the ETBD is beyond the scope of this article. Readers interested in greater depth and details are referred to recent, instructive reviews (McDowell, 2019(McDowell, , 2021. The ETBD generates artificial organism behavior and arranges experimental environments computationally, meaning that the behavior of artificial organisms does not occur or interact with the environment (e.g., produce reinforcement) in the same way a rat presses a lever and receives food in an operant chamber or a child raises their hand and receives attention in a classroom.…”

Section: General Methodsmentioning

confidence: 99%

“…The similarity between the behavior of artificial organisms animated by the ETBD and that of live organisms has been observed with steady-state (e.g., slight undermatching; McDowell et al, 2008) and dynamic (e.g., momentary effect of successive reinforcers; Kulubekova & McDowell, 2013) phenomena. Moreover, the ETBD has proven useful in modeling other applied phenomena such as resurgence , attention deficit hyperactivity disorder (Popa, 2013), and deviant verbal behavior (McDowell & Caron, 2010;McDowell, 2021). Morris and McDowell (2021) applied the ETBD to develop and evaluate models of the subtypes of automatically reinforced SIB.…”

mentioning

confidence: 99%

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Applying the evolutionary theory of behavior dynamics to model the subtypes of automatically reinforced self‐injurious behavior

Morris

Lucia

2023

J of App Behav Analysis

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The delineation of the subtypes of automatically reinforced self‐injurious behavior improved the utility of functional analysis results in predicting treatment efficacy. However, the mechanisms underlying subtype differences remain unclear and difficult to study in clinical populations. Morris and McDowell (2021) attempted to elucidate subtype differences by developing and evaluating models of the subtypes within the evolutionary theory of behavior dynamics. In the current study, we applied techniques from precision medicine to further evaluate the models developed by Morris and McDowell. This evaluation highlighted shortcomings of the existing models and suggested ways they could be improved. Thus, we conducted more extended modeling within the framework of precision medicine to identify models that were more quantitatively similar to available clinical data. Improved models that more closely approximate clinical data were identified. The implications of these models for research, practice, and further applications of the evolutionary theory of behavior dynamics are discussed.

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Section: General Methodsmentioning

confidence: 99%

mentioning

confidence: 99%

Applying the evolutionary theory of behavior dynamics to model the subtypes of automatically reinforced self‐injurious behavior

Morris

Lucia

2023

J of App Behav Analysis

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“…It can also be used to describe decisions made in playing baseball and basketball (Alferink et al, 2009;Cox et al, 2021). The matching law is also helping us understand a variety of clinical problems, including antisocial and delinquent behavior, attention-deficit/hyperactivity disorder, chronic pain syndrome, and self-injurious behavior (McDowell, 2021).…”

Section: Concurrent Schedulesmentioning

confidence: 99%

Schedules of reinforcement.

Domjan¹,

Delamater²

2023

The Essentials of Conditioning and Learning (5th Ed.).

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D id you know that• schedules of reinforcement determine rates and patterns of responding?• ratio schedules produce higher rates of responding than interval schedules?• interval schedules do not provide the reinforcer automatically after the passage of a particular time interval?• schedule effects are related to the feedback function that characterizes each schedule of reinforcement?• some schedules of reinforcement focus on choice and provide reinforcement for two (or more) response alternatives?• the generalized matching law describes choice behavior in a wide range of situations? According to the matching law, relative rates of responding equal relative rates of reinforcement.• self-control is investigated using concurrent-chain schedules of rein forcement?• the value of a reward declines as a function of how long you have to wait for it, but individuals differ in how rapidly reward value declines, and this psychological variable predicts measures of health and success in various aspects of life?

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“…There is compelling support for the ETBD in the basic literature (e.g., McDowell, 2004McDowell, , 2019McDowell, , 2021McDowell & Klapes, 2020;McDowell & Popa, 2010), and readers are referred to McDowell (2023) for additional summaries of the ETBD. Research shows emergent outcomes produced by the ETBD mirror steady-state choice of live organisms in matching arrangements (see McDowell, 2021 for an extensive summary). That is, AOs animated by the ETBD respond comparably to live animals on (a) single-alternative arrangements using random-interval (RI) schedules (e.g., McDowell & Arashanapalli, 2021;McDowell & Klapes, 2020;Morris & McDowell, 2021), (b) concurrent RI RI schedules (e.g., McDowell & Calvin, 2015;McDowell & Klapes, 2019), and (c) concurrent random-ratio (RR) schedules (McDowell & Klapes, 2018).…”

Section: Application Of the Etbd To Model Behavior In The Laboratorymentioning

confidence: 99%

Application of the evolutionary theory of behavior dynamics to severe challenging behavior

Hagopian,

Falligant

2023

J of App Behav Analysis

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The evolutionary theory of behavior dynamics (ETBD) is a genetic algorithm that applies the Darwinian principles of evolutionary biology to model how behavior changes dynamically via selection by contingencies of reinforcement. The ETBD is a complexity theory where low‐level rules of selection, reproduction, and mutation operate iteratively to animate “artificial organisms” that generate emergent outcomes. Numerous studies have demonstrated the ETBD can accurately model behavior of live animals in the laboratory, and it has been applied recently to model automatically maintained self‐injury. The purpose of the current series of studies was to further extend the application of the ETBD to model additional functional classes of challenging behavior and clinical procedures. Outcomes obtained with artificial organisms generally corresponded well with outcomes observed with clinical cases sourced from consecutive controlled case series studies. Conceptual and methodological considerations on the application of the ETBD to model challenging behavior are discussed.

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Empirical Matching, Matching Theory, and an Evolutionary Theory of Behavior Dynamics in Clinical Application

Cited by 7 publications

References 92 publications

Applying the evolutionary theory of behavior dynamics to model the subtypes of automatically reinforced self‐injurious behavior

Applying the evolutionary theory of behavior dynamics to model the subtypes of automatically reinforced self‐injurious behavior

Schedules of reinforcement.

Application of the evolutionary theory of behavior dynamics to severe challenging behavior

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