Exposure-based cognitive behavioral therapy for irritable bowel syndrome. A single-case experimental design across 13 subjects

Irritable bowel syndrome (IBS) is a highly prevalent disorder with a significant impact on quality of life. The presence of psychological symptoms in IBS patients such as catastrophic worry and behavioral avoidance suggests the possible efficacy of cognitive behavioral interventions. Exposure-based cognitive behavioral therapy (CBT) has proven to be a promising approach but has only been investigated in a few studies and mainly via the Internet. Therefore, the aims of this study were to extend and replicate previous findings and to evaluate whether an individual, face-to-face, exposure-based CBT leads to improvement in gastrointestinal symptoms, pain catastrophizing, avoidance behavior and quality of life in IBS patients. Thirteen patients with IBS according to Rome III criteria participated in a single-case experimental study using a five-week baseline and a subsequent twelve-session intervention phase focusing on psycho-education, mindfulness and in vivo exposure. Standardized measurement of gastrointestinal symptoms, pain catastrophizing, avoidance behavior and quality of life was conducted weekly during baseline as well as intervention phase and at six-month follow-up. Results showed that over 70% of patients improved significantly on gastrointestinal symptoms, pain catastrophizing, and quality of life. Effects on avoidance behavior were modest. These results strengthen and extend earlier findings and provide further support for the efficacy of exposure-based strategies for IBS.     

Single-case experimental designs: Characteristics,changes, and challenges

Tactics of Scientific Research (Sidman, 1960) provides a visionary treatise on single-case designs, their scientific underpinnings, and their critical role in understanding behavior. Since the foundational base was provided, single-case designs have proliferated especially in areas of application where they have been used to evaluate interventions with an extraordinary range of clients, settings, and target foci. This article highlights core features of single-case experimental designs, how key and ancillary features of the designs have evolved, the special strengths of the designs, and challenges that have impeded their integration in many areas where their contributions are sorely needed. The article ends by placing the methodological approach in the context of other research traditions. In this way, the discussion moves from the specific designs toward foundations and philosophy of science issues in keeping with the strengths of the person and book we are honoring.     

The relations between neuroscience and human behavioral science.

Neuroscience seeks to understand how the human brain, perhaps the most complex electrochemical machine in the universe, works, in terms of molecules, membranes, cells and cell assemblies, development, plasticity, learning, memory, cognition, and behavior. The human behavioral sciences, in particular psychiatry and clinical psychology, deal with disorders of human behavior and mentation. The gap between neuroscience and the human behavioral sciences is still large. However, some major advances in neuroscience over the last two decades have diminished the span. This article reviews the major advances of neuroscience in six areas with relevance to the behavioral sciences: (a) evolution of the nervous system; (b) visualizing activity in the human brain; (c) plasticity of the cerebral cortex; (d) receptors, ion channels, and second/third messengers; (e) molecular genetic approaches; and (f) understanding integrative systems with networks and circadian clocks as examples.     

The effectiveness of psychological skills training and behavioral interventions in sport using single-case designs: A meta regression analysis of the peer-reviewed studies

We used a novel meta regression analysis approach to examine the effectiveness of psychological skills training and behavioral interventions in sport assessed using single-case experimental designs (SCEDs). One hundred and twenty-one papers met the inclusion criteria applied to eight database searches and key sport psychology journals. Seventy-one studies reported sufficient detail for effect sizes to be calculated for the effects of psychological skills training on psychological, behavioral, and performance variables. The unconditional mean effect size for weighted (Δ = 2.40) and unweighted (Δ = 2.83) models suggested large improvements in psychological, behavioral, and performance outcomes associated with implementing cognitive-behavioral psychological skills training and behavioral interventions with a SCED. However, meta-regression analysis revealed important heterogeneities and sources of bias within this literature. First, studies using a group-based approach reported lower effect sizes compared to studies using single-case approaches. Second, the single-case studies, (over 90 per cent the effect sizes), revealed upwardly biased effect sizes arising from: (i) positive publication bias such that studies using lower numbers of baseline observations reported larger effects, while studies using larger numbers of baseline observations reported smaller – but still substantial – effects; (ii) not adopting a multiple baseline design; and (iii) not establishing procedural reliability. We recommend that future researchers using SCED’s should consider these methodological issues.     

Social neuroscience evidence for dehumanised perception

Dehumanisation describes perceiving a person as nonhuman in some ways, such as lacking a mind. Social psychology is beginning to understand cognitive and affective causes and mechanisms—the psychological how and why of dehumanisation. Social neuroscience research also can inform these questions. After background on social neural networks and on past dehumanisation research, the article contrasts (a) research on fully humanised person perception, reviewing studies on affective and cognitive factors, specifically mentalising (considering another's mind), with (b) dehumanised perception, proposing neural systems potentially involved. Finally, the conclusion suggests limitations of social neuroscience, future research directions, and real-world consequences of this all-too-human phenomenon.     

From a single-level analysis to a multilevel analysis of single-case experimental designs

Multilevel modeling provides one approach to synthesizing single-case experimental design data. In this study, we present the multilevel model (the two-level and the three-level models) for summarizing single-case results over cases, over studies, or both. In addition to the basic multilevel models, we elaborate on several plausible alternative models. We apply the proposed models to real datasets and investigate to what extent the estimated treatment effect is dependent on the modeling specifications and the underlying assumptions. By considering a range of plausible models and assumptions, researchers can determine the degree to which the effect estimates and conclusions are sensitive to the specific assumptions made. If the same conclusions are reached across a range of plausible assumptions, confidence in the conclusions can be enhanced. We advise researchers not to focus on one model but conduct multiple plausible multilevel analyses and investigate whether the results depend on the modeling options.     

Minimax d-optimal designs for item response theory models

Various different item response theory (IRT) models can be used in educational and psychological measurement to analyze test data. One of the major drawbacks of these models is that efficient parameter estimation can only be achieved with very large data sets. Therefore, it is often worthwhile to search for designs of the test data that in some way will optimize the parameter estimates. The results from the statistical theory on optimal design can be applied for efficient estimation of the parameters.A major problem in finding an optimal design for IRT models is that the designs are only optimal for a given set of parameters, that is, they are locally optimal. Locally optimal designs can be constructed with a sequential design procedure. In this paper minimax designs are proposed for IRT models to overcome the problem of local optimality. Minimax designs are compared to sequentially constructed designs for the two parameter logistic model and the results show that minimax design can be nearly as efficient as sequentially constructed designs.     

Notes for a dialogue between psychoanalysis and neuroscience1

The author postulates that the dialogue between psychoanalysis and neuroscience is based on the assumption that both deal with virtual structures. They are two facets of the same noumenal reality, but with different phenomenal realities, and it is possible to use metapsychology as a lingua franca to develop communication between the two fi elds. In the second part of the paper, the author refl ects on the results of recent neurophysiological research which seem to offer to psychoanalysis possibilities for fi nding an anatomical‐physiological correlate of some well‐known psychic phenomena and mechanisms, such as imitation, introjection, identifi cation, empathy, identity, mother‐child communication, learning, social communication and the analyst‐patient relationship. Particular neurons, called mirror neurons, have been located in the F5 area of baboons' brains. They are also present in man's brain within Broca's area. These neurons activate our motor system during both the performance of actions and the observation of actions performed by others giving rise to an automatic response, a sort of simulation or, rather, imitation, as the process is not intentional, but automatic and unaware, that is, unconscious.     

A primer for using multilevel models to meta-analyze single case design data with AB phases

Meta-analytic methods provide a way to synthesize data across treatment evaluation studies. However, these well-accepted methods are infrequent with behavior analytic studies. Multilevel models may be a promising method to meta-analyze single-case data. This technical article provides a primer for how to conduct a multilevel model with single-case designs with AB phases using data from the differential-reinforcement-of-low-rate behavior literature. We provide details, recommendations, and considerations for searching for appropriate studies, organizing the data, and conducting the analyses. All data sets are available to allow the reader to follow along with this primer. The purpose of this technical article is to minimally equip behavior analysts to complete a meta-analysis that will summarize a current state of affairs as it relates to the science of behavior analysis and its practice. Moreover, we aim to demonstrate the value of analyses of this sort for behavior analysis.     

Cognitive behavioral therapy for compulsive buying disorder

To our knowledge, no psychotherapy treatment studies for compulsive buying have been published. The authors conducted a pilot trial comparing the efficacy of a group cognitive behavioral intervention designed for the treatment of compulsive buying to a waiting list control. Twenty-eight subjects were assigned to receive active treatment and 11 to the waiting list control group. The results at the end of treatment showed significant advantages for cognitive behavioral therapy (CBT) over the waiting list in reductions in the number of compulsive buying episodes and time spent buying, as well as scores on the Yale–Brown Obsessive Compulsive Scale—Shopping Version and the Compulsive Buying Scale. Improvement was well-maintained at 6-month follow-up. The pilot data suggests that a cognitive behavioral intervention can be quite effective in the treatment of compulsive buying disorder. This model requires further testing.     

14 challenges and their solutions for conducting social neuroscience and longitudinal EEG research with infants

The use of electroencephalography (EEG) to study infant brain development is a growing trend. In addition to classical longitudinal designs that study the development of neural, cognitive and behavioural functions, new areas of EEG application are emerging, such as novel social neuroscience paradigms using dual infant-adult EEG recordings. However, most of the experimental designs, analysis methods, as well as EEG hardware were originally developed for single-person adult research. When applied to study infant development, adult-based solutions often pose unique problems that may go unrecognised. Here, we identify 14 challenges that infant EEG researchers may encounter when designing new experiments, collecting data, and conducting data analysis. Challenges related to the experimental design are: (1) small sample size and data attrition, and (2) varying arousal in younger infants. Challenges related to data acquisition are: (3) determining the optimal location for reference and ground electrodes, (4) control of impedance when testing with the high-density sponge electrode nets, (5) poor fit of standard EEG caps to the varying infant head shapes, and (6) ensuring a high degree of temporal synchronisation between amplifiers and recording devices during dual-EEG acquisition. Challenges related to the analysis of longitudinal and social neuroscience datasets are: (7) developmental changes in head anatomy, (8) prevalence and diversity of infant myogenic artefacts, (9) a lack of stereotypical topography of eye movements needed for the ICA-based data cleaning, (10) and relatively high inter-individual variability of EEG responses in younger cohorts. Additional challenges for the analysis of dual EEG data are: (11) developmental shifts in canonical EEG rhythms and difficulties in differentiating true inter-personal synchrony from spurious synchrony due to (12) common intrinsic properties of the signal and (13) shared external perturbation. Finally, (14) there is a lack of test-retest reliability studies of infant EEG. We describe each of these challenges and suggest possible solutions. While we focus specifically on the social neuroscience and longitudinal research, many of the issues we raise are relevant for all fields of infant EEG research.     

Some promising dimensions for behavioral community technology

In recent years, the search for effective and replicable approaches to planned change in communities has escalated. Applied behavior analysts have participated in these efforts to remedy existing community problems and to increase the capacities of community residents to meet their goals. Examples of behavioral technologies for community settings are described and their advantages are noted. Criteria for more contextually appropriate community technologies are suggested and strategies for developing behavioral methods according to these criteria are described. This paper outlines some promising dimensions for behavioral community technology and discusses several possible limitations to a behavioral approach to addressing societal problems.     

Rank‐based permutation approaches for non‐parametric factorial designs

Inference methods for null hypotheses formulated in terms of distribution functions in general non‐parametric factorial designs are studied. The methods can be applied to continuous, ordinal or even ordered categorical data in a unified way, and are based only on ranks. In this set‐up Wald‐type statistics and ANOVA‐type statistics are the current state of the art. The first method is asymptotically exact but a rather liberal statistical testing procedure for small to moderate sample size, while the latter is only an approximation which does not possess the correct asymptotic α level under the null. To bridge these gaps, a novel permutation approach is proposed which can be seen as a flexible generalization of the Kruskal–Wallis test to all kinds of factorial designs with independent observations. It is proven that the permutation principle is asymptotically correct while keeping its finite exactness property when data are exchangeable. The results of extensive simulation studies foster these theoretical findings. A real data set exemplifies its applicability.     

Working memory and behavioral inhibition in boys with ADHD: An experimental examination of competing models

Working memory (WM) and behavioral inhibition impairments have garnered significant attention as candidate core features, endophenotypes, and/or associated neurocognitive deficits of attention-deficit/hyperactivity disorder (ADHD). The relationship between ADHD-related WM and inhibition deficits remains relatively unclear, however, with inferences about the constructs’ directional relationship stemming predominantly from correlational research. The current study utilized a dual-task paradigm to experimentally examine the relationship between ADHD-related WM and behavioral inhibition deficits. A total of 31 boys (15 ADHD and 16 typically developing [TD]) aged 8–12 years completed WM (1-back and 2-back), behavioral inhibition (stop-signal task [SST]), and dual-condition (1-back/SST and 2-back/SST) experimental tasks. Children with ADHD exhibited significant, large-magnitude WM deficits for the 1-back condition but were not significantly different from children in the TD group for the 2-back, 1-back/SST, and 2-back/SST conditions. Children with ADHD also exhibited significant inhibition deficits for the SST, 1-back/SST, and 2-back/SST conditions, but the within-group effect was not significant. The findings suggest that ADHD-related stop-signal demands are upstream, or compete for, resources involved in controlled-focused attention and/or other central executive (CE), WM processes.     

The behavioral activation for depression scale-short form: development and validation

Following a landmark component analysis of cognitive therapy by Jacobson and colleagues (1996), there has been renewed interest in behavioral activation (BA) treatments for depression. The Behavioral Activation for Depression Scale (BADS) was developed to measure when and how clients become activated over the course of BA treatment. Multiple studies have provided initial support for the BADS but have also identified several potential problems. Four studies were conducted in order to develop and provide initial evaluation of a short form of the BADS that addresses these concerns. In Study 1, an exploratory factor analysis was conducted on existing data using the original BADS in order to identify items to retain for the short form. In Study 2, these items were administered to a new sample of college students with elevated depressive symptoms and were analyzed with exploratory and confirmatory factor analyses. Study 3 examined the predictive validity of the BADS-SF by examining the BADS-SF and depression scores in relation to activity tracking and reward-value ratings over the course of 1 week. Study 4 examined BADS-SF data over the course of BA treatment for two clients using cross-lagged panel correlations. With one client, changes in BADS-SF scores led changes in depression scores by 1 week, whereas with the other client changes in BADS-SF and depression scores occurred concurrently. These studies resulted in a nine-item scale that demonstrated good item characteristics as well as acceptable internal consistency reliability, construct validity, and predictive validity.     

Sequential evaluation of behavioral treatments and methylphenidate dosage for children with attention deficit hyperactivity disorder

We used a sequential approach to evaluate the relative and combined effects of different types of behavioral treatments, as well as dosage of methylphenidate (MPH), on the disruptive behavior of 3 students who had been diagnosed with attention deficit hyperactivity disorder. Results showed that individualized behavioral treatments produced decreases in disruptive behavior equivalent to MPH for all 3 participants and demonstrated the need to evaluate behavioral treatments and medication dosage on an individual basis.     

Gratitude for small and large favors: A behavioral test

The effect of large and small favors on gratitude was tested using a behavioral measure. Participants were 149 undergraduates (120 female, 29 male). Half received raffle tickets for a US$100 prize, and half received tickets for a US$10 prize. Some received tickets from another (fictitious) student, and others received tickets by chance. Participants receiving a favor subsequently distributed more tickets to the other student; participants receiving a more valuable favor also distributed more (ps?<?0.05). Self-reported grateful motivation predicted distribution better than did indebtedness. Grateful motivation mediated the relationship between favor and distribution (p?<?0.05). Results provide validity for a behavioral measure of gratitude, tentatively support favor value as a determinant of gratitude, and further differentiate between gratitude and indebtedness.     

No sex differences in spatial location memory for abstract designs

Previous research has demonstrated a female advantage, albeit imperfectly, on tests of object location memory where object identity information is readily available. However, spatial and visual elements are often confounded in the experimental tasks used. Here spatial and visual memory performance was compared in 30 men and 30 women by presenting 12 abstract designs in a spatial array for recall and recognition (visual memory) and spatial location ("object" location memory). Object location memory was measured via a sensitive absolute displacement score defined as the distance in mms between the position assigned to the object during recall and the actual position it originally occupied. There were no sex differences in either the visual or spatial location tests. Controlling for age and estimated IQ scores made no impact on the results. These data suggest an absence of a sex difference in purely visual and spatial aspects of object location memory.     

An equation for behavioral contrast.

Pigeons were trained on a three-component multiple schedule in which the rates of reinforcement in the various components were systematically varied. Response rates were described by an equation that posits that the response-strengthening effects of reinforcement are inversely related to the context of reinforcement in which it occurs, and that the context is calculated as the weighted average of the various sources of reinforcement in the situation. The quality of fits was comparable to that found with previous quantitative analyses of concurrent schedules, especially for relative response rates, with over 90% of the variance accounted for in every case. As with previous research, reinforcements in the component that was to follow received greater weights in determining the context than did reinforcements in the preceding component.