Relational frame theory 20 years on: The Odysseus voyage and beyond

Verification report: A critical reanalysis of Vahey et al. (2015) "A meta-analysis of criterion effects for the Implicit Relational Assessment Procedure (IRAP) in the clinical domain"

The meta-analysis reported in Vahey et al. (2015) concluded that the Implicit Relational Assessment Procedure (IRAP) has high clinical criterion validity (meta-analytic r‾ = .45) and therefore "the potential of the IRAP as a tool for clinical assessment" (p. 64). Vahey et al. (2015) also reported power analyses, and the article is frequently cited for sample size determination in IRAP studies, especially their heuristic of N > 37. This article attempts to verify those results. Results were found to have very poor reproducibility at almost every stage of the data extraction and analysis with errors generally biased towards inflating the effect size. The reported meta-analysis results were found to be mathematically implausible and could not be reproduced despite numerous attempts. Multiple internal discrepancies were found in the effect sizes such as between the forest plot and funnel plot, and between the forest plot and the supplementary data. 23 of the 56 (41.1%) individual effect sizes were not actually criterion effects and did not meet the original inclusion criteria. The original results were also undermined by combining effect sizes with different estimands. Reextraction of effect sizes from the original articles revealed 360 additional effect sizes that met inclusion criteria that should have been included in the original analysis. Examples of selection bias in the inclusion of larger effect sizes were observed. A new meta-analysis was calculated to understand the compound impact of these errors (i.e., without endorsing its results as a valid estimate of the IRAP's criterion validity). The effect size was half the size of the original (r‾ = .22), and the power analyses recommended sample sizes nearly 10 times larger than the original (N > 346), which no published original study using the IRAP has met. In aggregate, this seriously undermines the credibility and utility of the original article's conclusions and recommendations. Vahey et al. (2015) appears to need substantial correction at minimum. In particular, researchers should not rely on its results for sample size justification. A list of suggestions for error detection in meta-analyses is provided.

Further N-Frame networking dynamics of conscious observer-self agents via a functional contextual interface: predictive coding, double-slit quantum mechanical experiment, and decision-making fallacy modeling as applied to the measurement problem in humans and AI

Artificial intelligence (AI) has made some remarkable advances in recent years, particularly within the area of large language models (LLMs) that produce human-like conversational abilities via utilizing transformer-based architecture. These advancements have sparked growing calls to develop tests not only for intelligence but also for consciousness. However, existing benchmarks assess reasoning abilities across various domains but fail to directly address consciousness. To bridge this gap, this paper introduces the functional contextual N-Frame model, a novel framework integrating predictive coding, quantum Bayesian (QBism), and evolutionary dynamics. This comprehensive model explicates how conscious observers, whether human or artificial, should update beliefs and interact within a quantum cognitive system. It provides a dynamic account of belief evolution through the interplay of internal observer states and external stimuli. By modeling decision-making fallacies such as the conjunction fallacy and conscious intent collapse experiments within this quantum probabilistic framework, the N-Frame model establishes structural and functional equivalence between cognitive processes identified within these experiments and traditional quantum mechanics (QM). It is hypothesized that consciousness serves as an active participant in wavefunction collapse (or actualization of the physical definite states we see), bridging quantum potentiality and classical outcomes via internal observer states and contextual interactions via a self-referential loop. This framework formalizes decision-making processes within a Hilbert space, mapping cognitive states to quantum operators and contextual dependencies, and demonstrates structural and functional equivalence between cognitive and quantum systems in order to address the measurement problem. Furthermore, the model extends to testable predictions about AI consciousness by specifying informational boundaries, contextual parameters, and a conscious-time dimension derived from Anti-de Sitter/Conformal Field Theory correspondence (AdS/CFT). This paper theorizes that human cognitive biases reflect adaptive, evolutionarily stable strategies that optimize predictive accuracy (i.e., evolved quantum heuristic strategies rather than errors relative to classical rationality) under uncertainty within a quantum framework, challenging the classical interpretation of irrationality. The N-Frame model offers a unified account of consciousness, decision-making, behavior, and quantum mechanics, incorporating the idea of finding truth without proof (thus overcoming Gödelian uncertainty), insights from quantum probability theory (such as the Linda cognitive bias findings), and the possibility that consciousness can cause waveform collapse (or perturbation) accounting for the measurement problem. It proposes a process for conscious time and branching worldlines to explain subjective experiences of time flow and conscious free will. These theoretical advancements provide a foundation for interdisciplinary exploration into consciousness, cognition, and quantum systems, offering a path toward developing tests for AI consciousness and addressing the limitations of classical computation in representing conscious agency.

On the Disruptive Effects of Behavior Analysis on Behavior Analysis: The High Cost of Keeping Out Acceptance and Commitment Therapy and Training

ACT is entering its 40th year of development. Despite its undeniable historical origins in behavior analysis, extensive basis in behavior analytic research, and now enormous body of empirical research supporting its basic claims, some are still arguing that ACT is not legitimately part of behavior analysis. We agree with the target article that it is. We argue, however, that critics are right to feel that ACT will disrupt the field. It will do so not because of ACT per se, but because it brings relational frame theory (RFT) in with it and vice versa, and relational operants operate on other behavioral processes. This empirically established effect means that the vast literature on direct contingency control will need to be reexamined piece by piece while considering relational learning abilities. Such an agenda is exciting, but it is also daunting and disorienting. For behavior analysis to reject either ACT or RFT, both must be rejected. That appears to be the only way to avoid the coming disruption, but the cost would be in the distortion of the field itself that would result. Sometime the products of a scientific field require a fundamental rethinking of that field. In our view, that is the situation behavior analysis now faces. It is a kind of test, and we do not yet know if behavior analysis will pass it.

Naming, Stimulus Equivalence and Relational Frame Theory: Stronger Together than Apart

Research on human language started to change when Murray Sidman and colleagues demonstrated that a participant was able to derive unreinforced stimulus relations after conditional discrimination training. This work provided the basis for a novel approach to research on symbolic behavior and fostered the development of three main theoretical accounts: stimulus equivalence (SE), relational frame theory (RFT), and naming theory (NT). These accounts unfolded in the last decades of the twentieth century, promoting intense debate and discussion within behavior analysis. Although experimental research emerging from these three accounts is still highly active today, the theoretical discussions have, to a large extent, faded. Considering the importance of rekindling a dialogue, this article aims to describe the differences among the three accounts, but focus on their common points. We conclude by arguing that developing a more complete behavior-analytic account of human language would be served best by considering both research and theoretical analyses of SE, RFT and NT. Finally, we provide examples of two successful research groups that adopted this approach and in doing so have advanced our understanding of language within behavior analysis.

Acceptance and commitment therapy reduces perceived ostracism in suicidal patients

INTRODUCTION

Ostracism increases the risk of depression and suicidal behaviors. Mindfulness training, which is at the core of third-wave behavioral therapies such as acceptance and commitment therapy (ACT), might reduce social distress and inhibit negative affect.

METHODS

This randomized controlled trial included 32 patients with a history of suicide attempt in the past year who followed seven weekly sessions of ACT or progressive relaxation therapy (PRT). To assess and compare the effects of ACT and PRT on social distress, patients performed a validated paradigm of social exclusion (the Cyberball Game) followed by completion of the Need Threat Scale (NTS) at inclusion (baseline) and within two weeks after the intervention ended (posttherapy).

RESULTS

The included patients were mainly women (N = 28; 87.5%), and their mean age was 40 years (SD: 12 years). Twenty-six patients (81%) experienced current depression. The postintervention NTS score was greater (lower social distress) in the ACT group than in the PRT group (group × time interaction; β = 0.47, p < 0.05), even after controlling for depressive symptoms (β = 0.27, p < 0.05). The NTS score change (between baseline and posttherapy) was correlated with changes in dispositional mindfulness (r = 0.46, p = 0.03), cognitive fusion (r = - 0.61, p < 10-3) and acceptance (r = 0.57, p < 10-2).

CONCLUSION

ACT decreased social pain independently of its effect on depression. Reduced social pain was correlated with improved therapeutic processes and decreased suicidal ideation, highlighting the therapeutic potential of ACT for managing ostracism and suicide risk.

A Modern Collaborative Behavior Analytic Approach to Incidental Naming

An important distinction has been drawn within the behavior-analytic literature between two types of naming. Naming that is reinforced is referred to as bidirectional naming, and naming that is not reinforced is referred to as incidental bidirectional naming. According to verbal behavior development theory children who demonstrate incidental naming have developed a verbal behavioral cusp, and often learn new language more rapidly as a result. A growing body of research has assessed incidental naming using what is described as an incidental naming experience, in which novel stimuli are presented and named by a researcher but with no direct differential reinforcement for subsequent naming responses by the participant. According to relational frame theory, such studies on incidental naming have typically involved presenting contextual cues that likely serve to establish the name relations between an object and its name. As such, contextual cues may play a critical role in the emergence of incidental naming responses, but there are no published studies that have systematically tested the potential role of contextual cues in relation to incidental naming. The current article provides a narrative review of the incidental naming literature, highlighting variables that remain to be explored in future research.

Recent Developments in RFT Encourage Interbehavioral Field-Based Views of Human Language and Cognition: A Preliminary Analysis

Relational frame theory (RFT) as a behavior-analytic approach to understanding human language and cognition is now over 40 years old. However, the last 8 years have seen a relatively intense period of empirical and conceptual developments within the theory. Some of this work has begun to draw on early and much underplayed features of RFT, including field-theoretical analyses and concepts. These analyses are relatively nascent and thus the current article aims to provide a relatively detailed example of a field-theoretical analysis of a specific RFT research program. We begin with a brief overview of the "traditional" RFT approach to human language and cognition, followed by a summary of recent research involving the implicit relational assessment procedure (IRAP) and the differential arbitrarily applicable relational responding effects (DAARRE) model. We then go on to consider the DAARRE model in the context of J. R. Kantor's interbehavioral formula for the psychological event. Having done so, we conclude that the challenge involved in analyzing increasingly complex forms of human language and cognition appears to call for more field-based theorizing in some form or another.

Relating in the Wild: Toward an Analysis of Equivalence Relations Under More Naturalistic Conditions

Since the first proposal 50 years ago, numerous experiments have documented how arbitrarily related stimuli can become functionally interchangeable. These studies have sought to understand how different variables can moderate the probability of equivalence class formation. However, the well-established evidence regarding this phenomenon in experimental settings does not necessarily guarantee an understanding about how equivalence relations are produced in natural settings. In typical experiments, experimenters control critical variables to produce equivalence relations, such as, the requirement of proficiency with baseline relations, the number of opportunities to relate two or more stimuli, the efforts to promote stimulus control topography coherent with the experimenter-defined relations, etc. All these variables, however, are not controlled in our daily lives. The present article elucidates how some differences between experimental and natural settings can likely affect how the phenomenon of equivalence relations can occur in noncontrolled, naturalistic environments. Furthermore, we suggest new areas of research to promote the generalization of basic experimental data to contingencies in our daily lives.

A functional contextual, observer-centric, quantum mechanical, and neuro-symbolic approach to solving the alignment problem of artificial general intelligence: safe AI through intersecting computational psychological neuroscience and LLM architecture for emergent theory of mind

There have been impressive advancements in the field of natural language processing (NLP) in recent years, largely driven by innovations in the development of transformer-based large language models (LLM) that utilize "attention." This approach employs masked self-attention to establish (via similarly) different positions of tokens (words) within an inputted sequence of tokens to compute the most appropriate response based on its training corpus. However, there is speculation as to whether this approach alone can be scaled up to develop emergent artificial general intelligence (AGI), and whether it can address the alignment of AGI values with human values (called the alignment problem). Some researchers exploring the alignment problem highlight three aspects that AGI (or AI) requires to help resolve this problem: (1) an interpretable values specification; (2) a utility function; and (3) a dynamic contextual account of behavior. Here, a neurosymbolic model is proposed to help resolve these issues of human value alignment in AI, which expands on the transformer-based model for NLP to incorporate symbolic reasoning that may allow AGI to incorporate perspective-taking reasoning (i.e., resolving the need for a dynamic contextual account of behavior through deictics) as defined by a multilevel evolutionary and neurobiological framework into a functional contextual post-Skinnerian model of human language called "Neurobiological and Natural Selection Relational Frame Theory" (N-Frame). It is argued that this approach may also help establish a comprehensible value scheme, a utility function by expanding the expected utility equation of behavioral economics to consider functional contextualism, and even an observer (or witness) centric model for consciousness. Evolution theory, subjective quantum mechanics, and neuroscience are further aimed to help explain consciousness, and possible implementation within an LLM through correspondence to an interface as suggested by N-Frame. This argument is supported by the computational level of hypergraphs, relational density clusters, a conscious quantum level defined by QBism, and real-world applied level (human user feedback). It is argued that this approach could enable AI to achieve consciousness and develop deictic perspective-taking abilities, thereby attaining human-level self-awareness, empathy, and compassion toward others. Importantly, this consciousness hypothesis can be directly tested with a significance of approximately 5-sigma significance (with a 1 in 3.5 million probability that any identified AI-conscious observations in the form of a collapsed wave form are due to chance factors) through double-slit intent-type experimentation and visualization procedures for derived perspective-taking relational frames. Ultimately, this could provide a solution to the alignment problem and contribute to the emergence of a theory of mind (ToM) within AI.

Merging meaningful classes and abstract equivalence classes by exclusion

The current experiment assessed whether relating abstract stimuli with familiar pictures by exclusion would produce the formation of a meaningful equivalence class. Ten participants learned conditional discrimination relations with abstract stimuli and established equivalence classes (ABC classes). They then learned DA (D1A1, D2A2, and D3A3) conditional discriminations with written words as D stimuli; two words (D1 and D2) were meaningful stimuli in the participants verbal community ("Dentist" and "Baker"), whereas the third (D3) was a pseudoword ("Tabilu"). In testing trials, participants evidenced derived relations between pictures related preexperimentally to D1 and D2 with the experimental equivalence classes related to D1 and D2. For some participants, the decontextualized stimuli were a set of boat pictures (Condition 1), whereas for others they were a set of miscellaneous pictures (Condition 2). Participants in both conditions successfully matched decontextualized pictures (unrelated to dentist and baker contexts) to all abstract stimuli in the class related to D3 (exclusion responding). In Condition 1 the meaning reported to the word Tabilu was similar across participants, but in Condition 2 participants showed more variations to answer to the meaning of Tabilu. These results suggest that exclusion learning can occur under different stimulus control topographies.

Behavior Analysts' Relationship to Relating Relations: A Survey on Perceptions, Acceptability, Knowledge, and Capacity for Derived Stimulus Relations Research and Practice

The study and application of procedures that result in stimulus relations via relational frame theory (RFT) and stimulus equivalence (applied as equivalence-based instruction; EBI), have made tremendous strides in contemporary behavior analysis. However, applications at scale lag basic and translational research. We turn our attention inward to investigate potential causes. We replicated and extended Enoch and Nicholson (Behavior Analysis in Practice, 13(3), 609-617, 2020) by conducting a survey of behavior analysts (n = 129) to determine their perceptions, experiences, and barriers in carrying out research and practice based on RFT and EBI. Participants indicated an interest in RFT and EBI, and mostly perceive both within the scope of behavior analysis. A majority of behavior analysts reported formal education in EBI (78.3%), in contrast to a minority in RFT (15.5%). Adoption of procedures derived from RFT and EBI may be in proportion to formal education. Compounded with a lack of accuracy on basic knowledge questions, there is a potential gap in capacity in the field in addressing behavior related to complex verbal behavior.

Deictic Relational Responding and Perspective-Taking in Autistic Individuals: A Scoping Review

Perspective-taking skills are crucial for successful social interactions and some autistic individuals seem to demonstrate great difficulty in this area. The concept continues to generate clinical and research interest across mainstream psychology and within behavior analysis. Within behavior analysis, relational frame theorists have argued that deictic relational responding is critically involved in perspective-taking. We conducted a systematic search of the behavior analytic studies on deictic relational responding and perspective-taking in autistic individuals to highlight methods used to test perspective-taking and deictic relations, methods to train these if deficits were observed, and evidence for a relationship between deictic relational responding and perspective-taking. Seven studies met inclusion criteria and we conducted a descriptive analysis of these studies. We found some variation in the methods used to test and train perspective-taking through deictic relations. Only three of the studies attempted to demonstrate a link between deictic relational responding and perspective-taking. Overall, our review highlighted a need for more research into deictic relational responding and perspective-taking in autistic individuals, and we discussed specific areas for future research.

Relating different perspectives on how outcomes of behavior influence behavior

Many researchers have tackled the question of how behavior is influenced by its outcomes. Some have adopted a nonmechanistic (functional) perspective that attempts to describe the influence of outcomes on behavior. Others have adopted a mechanistic (cognitive) perspective that attempts to explain the influence of outcomes on behavior. Orthogonal to this distinction, some have focused on the influence of outcomes that a behavior had in the past, whereas others also consider the influence of outcomes that a behavior might have in the future. In this article, we relate these different perspectives with the goal of reducing misunderstandings and fostering collaborations between researchers who adopt different perspectives on the common question of how behavior is influenced by its outcomes.

Explaining First Language Acquisition in Terms of Basic Behavioral Processes: Introduction to the Special Section

This special section of Perspectives on Behavior Science follows up on a virtual panel discussion on the role of operant and Pavlovian processes in children's language learning. We present four articles, including two contributed by panelists, that illustrate the explanatory power of operant conditioning processes in the study of language.

Relating relational networks: An initial experimental analysis

Studying relating of relational networks is a complex and challenging task. The main objective of the present study was to demonstrate relating within and across relational networks based on same/opposite and bigger/smaller contextual cues and establish antecedent control. After nonarbitrary pretraining of the contextual cues, two nonsense stimulus classes were established based on comparative relations. Participants were trained to select stimuli from an array of options based on a symbolic rule that established a relation between two stimuli: one of Network 1 and one of Network 2. Training involved relating Network 1 to Network 2, and testing assessed relating Network 2 to Network 1. Seven of eight participants reached the mastery criterion in training and responded accordingly in test. In a final stage, reinforcing and punishing consequences were varied systematically in the presence of two novel stimuli and antecedent control was observed for all 7 participants. Experiment 2 replicated the results of Experiment 1 but using contextual cues taken from natural language, and Experiment 3 sought to understand the effects of pretraining relational responding using natural language. The mastery criteria were reached by four of seven participants in Experiment 2 and by all eight participants in Experiment 3. Future studies could develop and refine the methods employed here in analyzing the relating of relational networks, thus allowing for an increasingly sophisticated behavior-analytic account of human language and cognition.

Thinking of learning phenomena as instances of relational behavior

We explore the idea that some learning phenomena can be thought of as instances of relational behavior-more specifically, arbitrarily applicable relational responding (AARR). After explaining the nature of AARR, we discuss what it means to say that learning phenomena such as evaluative and fear conditioning are instances of AARR. We then list several implications of this perspective for empirical and theoretical research on learning, as well as for how learning phenomena relate to other psychological phenomena in human and nonhuman animals.

Computational models of stimulus equivalence: An intersection for the study of symbolic behavior

Stimulus equivalence is a central paradigm in the analysis of symbolic behavior, language, and cognition. It describes emergent relations between stimuli that were not explicitly trained and cannot be explained by primary stimulus generalization. In recent years, researchers have developed computational models to simulate the learning of equivalence relations. These models have been used to address primary theoretical and methodological issues in this field, such as exploring the underlying mechanisms that explain emergent equivalence relations and analyzing the effects of training and testing protocols on equivalence outcomes. Nonetheless, although these models build upon general learning principles, their operation is usually obscure for nonmodelers, and in the field of stimulus equivalence computational models have been developed with a variety of approaches, architectures, and algorithms that make it difficult to understand the scope and contributions of these tools. In this paper, we present the state of the art in computational modeling of stimulus equivalence. We seek to provide concise and accessible descriptions of the models' functioning and operation, highlight their main theoretical and methodological contributions, identify the existing software available for researchers to run experiments, and suggest future directions in the emergent field of computational modeling of stimulus equivalence.

Grappling with the Complexity of Behavioral Processes in Human Psychological Suffering: Some Potential Insights from Relational Frame Theory

Relational frame theory (RFT) has historically been considered the basic explanatory science behind acceptance and commitment therapy (ACT). However, some have argued that there has been an increasing separation between the two in recent years. The primary aim of the current article is to explore the extent to which RFT concepts, particularly those that have been proposed recently in the context of "up-dating" the theory, may be used to build stronger links between basic and applied behavior analyses in which there is a shared language of relatively precise technical terms. As an example of this strategy, we outline RFT process-based experimental and conceptual analyses of the impact of one of the most widely used sets of interventions employed in the ACT literature, defusion. In addition, we suggest a potential experimental methodology for analyzing the basic behavioral processes involved. Overall, the current article should be seen as part of a broader research agenda that aims to explore how RFT may be used to provide a functional-analytic abstractive treatment of the behavioral processes involved in human psychological suffering.

The Complexity of Racial Prejudice: The Importance of a Broader Perspective

Critic review of the article: Beck, C., Garcia, Y., & Catagnus, R. (2022). Effects of Perspective Taking and Values Consistency in Reducing Implicit Racial Bias. Universitas Psychologica, 21, 1-17. https://doi.org/10.11144/Javeriana.upsy21.eptv

The IRAP as a Measure of Implicit Cognition: A Case of Frankenstein’s Monster

The implicit relational assessment procedure (IRAP) was initially developed as a way to assess the strength and probability of natural verbal relations, as defined within relational frame theory (RFT), and was conceptually rooted within the behavior-analytic tradition. However, the IRAP quickly became employed primarily as a measure of implicit cognition, more in line with mainstream psychology than behavior analysis. In doing so, research using the IRAP increasingly employed ill-defined mainstream psychological terms, focused on correlational analyses with traditional psychometry, and thus emphasized prediction over the prediction-and-influence of behavior. Although perhaps beneficial to the study of implicit cognition, this approach could be argued to have limited the IRAP's utility in behavior analyses of human language and cognition. In the current article we will reflect on this suggestion, on the IRAPs place and current use in the field of behavior analysis, and on its potential future within behavioral psychology in light of recent conceptual and empirical advances in RFT. In doing so, it is hoped that the measure may be refined into a better understood, more precise, functional-analytic tool.

Derived Relations and Meaning in Responding to Art

The Argentine poet Jorge Luis Borges may have come closer than anyone else to envisioning a radical behavioristic aesthetics. What he said about poetry can be generalized to other art forms: that poetry happens when someone reads a poem. Art, therefore, is the behavioral episode in which someone responds to the stimuli arranged by the artist. Because each person that comes into contact with a work of art has a different history with the work and its elements, responding will vary widely for persons and for the same person at different times. An essential feature of this history is the network of derived relations involving the elements of the artwork, and the transfer and transformation of behavioral functions across this network.