Electrical muscle stimulation improves vastus medialis quality: A single-case experimental design

Limited research has directly addressed the challenges of higher education for students with autism, who face additional difficulties in navigating social, personal and academic obstacles. With more students experiencing mental health difficulties whilst at university, therapeutic interventions on offer need to be suitable for those accessing support. Cognitive behavioural therapy (CBT) is widely used to support university students, as it is firmly established as an effective treatment for a range of issues, including social and generalised anxiety in typically developing populations (NICE, 2013; NICE, 2019). However, the efficacy of CBT for individuals with autistic spectrum condition (ASC) is less well known, despite the high prevalence rates of anxiety in this population. This paper seeks to address a gap in the literature and uses a single-case (A-B) experimental design over 16 sessions to reduce co-morbid social and generalised anxiety in a university student with high-functioning ASC. Clark’s (2001) cognitive model of social anxiety and Wells’ (1997) cognitive model of generalised anxiety were employed to formulate anxiety experienced in this case. Standardised outcome measures were used for social anxiety, i.e. the Social Phobia Inventory (SPIN), and generalised anxiety, i.e. the Generalised Anxiety Disorder-7 (GAD-7), in conjunction with idiographic ratings to assess the impact of therapy. Findings indicate that CBT was an acceptable and useful intervention with mixed results; discrepancies were found between clinical change recorded on standardised measures compared with idiographic ratings. This paper discusses the use of standardised measures of anxiety for individuals with ASC and identifies directions for further research. Key learning aims (1) To appreciate the unique mental health challenges of university students with ASC. (2) To identify psychological interventions that are suitable for individuals with ASC. (3) To consider the value in employing more than one evidence-based cognitive model of anxiety when clients present with co-morbid mental health issues. (4) To question the utility of using standardised outcome measures compared with idiographic measures in therapy.

This paper introduces the Special Issue of Neuropsychological Rehabilitation on Single Case Experimental Design (SCED) methodology. SCED studies have a long history of use in evaluating behavioural and psychological interventions, but in recent years there has been a resurgence of interest in SCED methodology, driven in part by the development of standards for conducting and reporting SCED studies. Although there is consensus on some aspects of SCED methodology, the question of how SCED data should be analysed remains unresolved. This Special Issues includes two papers discussing aspects of conducting SCED studies, five papers illustrating use of SCED methodology in clinical practice, and nine papers that present different methods of SCED data analysis. A final Discussion paper summarises points of agreement, highlights areas where further clarity is needed, and ends with a set of resources that will assist researchers conduct and analyse SCED studies.

Difficulties in emotion regulation are a significant contributing factor to delinquent behavior in adolescence. These adolescents struggle with recognizing, comprehending, and controlling emotions, which impedes the effectiveness of current forensic treatments. In addition, forensic care often faces challenges regarding treatment engagement due to a lack of motivation and difficulties building an alliance between clients and caregivers. The use of Feelee, an app that collects and displays active and passive data, is promising to support adolescents in obtaining more insight into their emotion regulation abilities. Furthermore, the integration of smartphone apps, like Feelee, offers new perspectives to increase adolescents' engagement and adherence to treatment. This study presents the research protocol for evaluating the initial effects of the Feelee app on emotion regulation among adolescents in the forensic outpatient setting. The Feelee app integrates with treatment as usual, and the multiple single-case experimental design methodology is discussed in detail. A multiple single-case experimental ABA design was applied to examine the initial effectiveness of Feelee. A total of 24 participants from 2 forensic outpatient care centers completed a 2-week baseline (phase A1), 4-week intervention (phase B), and a 2-week follow-up (phase A2). The primary outcome, emotional regulation, is measured daily using self-reports via the smartphone. Secondary outcomes, including emotional differentiation, insight and self-reflection, emotional awareness, and treatment-related factors such as motivation and therapeutic alliance, are assessed through questionnaires administered at preintervention, postintervention, and follow-up points. Quantitative analyses follow single-case experimental design methods, including visual analysis of individual trajectories, standardized mean difference permutation distance tests, and Cohen d at the group level. A 95% CI is calculated per participant to assess change reliability. Secondary outcomes are analyzed using the Reliable Change Index. Qualitative follow-up interviews are analyzed using thematic analysis at both the individual and group levels. Data collection started in June 2023 and was completed in January 2025. By the time of final manuscript submission, 89 participants had been recruited and 24 had enrolled in the study. Study results will be published in peer-reviewed journals and presented at national and international conferences throughout 2025. This study aims to evaluate the effectiveness of the Feelee app in enhancing emotion regulation skills. By using a multiple single-case experimental ABA design, we will get a first insight into the addition of Feelee to treatment as usual in the forensic outpatient setting. Study strengths include the low-threshold addition, ecological validity, and the use of both quantitative and qualitative research methods. Further implications for clinical practice are discussed. Central Committee on Research Involving Human Subjects NL-OMON54390; https://onderzoekmetmensen.nl/en/trial/54390 and ClinicalTrials.gov NCT06509360; https://clinicaltrials.gov/study/NCT06509360. DERR1-10.2196/64756.

This paper presents an argument for more extensive use of single-case experimental research designs in medical education research. Single-case experimental designs consist of a group of experimental techniques that are widely used in the social sciences but are just beginning to be utilized by medical researchers. The method emphasizes reliable observations of behavior, repeated measurements of outcome, and individualized tailoring of objectives for each subject; all of these occur within a system that allows an experimental analysis to be conducted. Single-case designs are particularly useful when only small numbers of participants are available for a relatively long period of time. Trends in medical education toward individualized instruction, adult-centered learning, and fine-grained analyses of medical skills and knowledge make this field especially amenable to single-case experimental designs. Issues of internal and external validity, generality, practicality, and ethics are discussed, and several typical designs are illustrated. While the emergence of qualitative research methods in medical education may prove useful, single-case designs can maintain experimental science's emphasis on methodologic rigor, while allowing the flexibility often needed to conduct research in applied settings.

Single-case experimental designs (SCEDs) have grown in popularity in the fields such as education, psychology, medicine, and rehabilitation. Although SCEDs are valid experimental designs for determining evidence-based practices, they encounter some challenges in analyses of data. One of these challenges, missing data, is likely to be occurred frequently in SCEDs research due to repeated measurements over time. Since missing data is a critical factor that can weaken the validity and generalizability of a study, it is important to determine the characteristics of missing data in SCEDs, which are especially conducted with a small number of participants. In this regard, this study aimed to describe missing data features in SCEDs studies in detail. To accomplish this goal, 465 published SCEDs studies within the recent 5 years in six journals were included in the investigation. The overall results showed that the prevalence of missing data among SCEDs articles in at least one phase, as at least one data point, was approximately 30%. In addition, the results indicated that the missing data rates were above 10% within most studies where missing data occurred. Although missing data is so common in SCEDs research, only a handful of studies (5%) have handled missing data; however, their methods are traditional. In analyzing SCEDs data, several methods are proposed considering missing data ratios in the literature. Therefore, missing data rates determined in this study results can shed light on the analyses of SCEDs data with proper methods by improving the validity and generalizability of study results.

This paper compares two methods, inferential statistics and Systems Dynamics, to study the individual happiness evolution after a single dose of drug consumption. In an application case, the effect of alcohol and caffeine on happiness is analyzed through a single case experimental design with replication with two participants. Both inferential statistical analysis and Systems Dynamics methods have been used to analyze the results. Two scales were used to measure happiness: the Euphoria Scale (ES) and the Smiling Face Scale (SFS), in trait and state format. A single-case experimental ABC design was used. Phase A with no treatment, and Phases B and C with both subjects receiving 26.51 ml of alcohol and 330 mg of caffeine, respectively. The participants filled in a form with both scales in state-format every 10 minutes over a 3-hour period, in each one of the three phases A, B and C. The main conclusion of the performed analysis is that both methods provide similar results about the evolution of individual happiness after single dose consumption. Therefore, the article provides that inferential statistics and the stimulus-response model derived from the Systems Dynamics approach can be used in a complementary and enriching way to obtain prediction results.

Recently the N of 1, or single case experimental trial design, has increased in popularity among physicians and therapists interested in assessing the usefulness of a therapeutic modality within a single subject [1, 2]. The techniques are not considered new; single case experimental designs have found acceptance and widespread use for many years in the behavioral sciences [3]. Additionally, experimental physiology and medicine have employed these methods extensively over the last few decades, although there is a relative paucity of articles in the clinical literature that report the results of N of 1 trials. There is a variety of design options possible for N of 1 studies, and the interested reader is referred to Reference 3 for a more comprehensive review of the topic. This paper will review a few of the major design options, with particular attention given to the alternating treatment design (ATD). The advantages and drawbacks of the N of 1 technique, with specific reference to the field of rheumatology, will be the main emphasis.

BackgroundAlthough Cognitive Behavioural Therapy (CBT) is effective for 60% of adolescents with anxiety disorders, only 36% are in remission post‐intervention. This indicates that more effective treatments are needed which should be reflected in the NICE guidelines. We hypothesised that Single‐case experimental designs (SCEDs) may provide a framework for accelerating the development of novel interventions. The primary purpose of this review was to investigate whether SCEDs are currently followed by randomised controlled trials (RCTs) of CBT intervention for adolescent anxiety disorders named in the NICE guidelines. The secondary objective was to investigate whether using SCEDs prior to RCTs could be a helpful approach.MethodFor the primary search of SCEDs five databases were used (PsycINFO, PubMed, PsycArticles, Web of Science and ProQuest). Nineteen articles met eligibility criteria including a total of 107 participants. For the secondary search of RCTs named in the NICE guidelines for adolescent anxiety disorders 53 articles met inclusion criteria and were included in the systematic review.ResultsThe 19 SCED studies included in the review were conducted with participants with a diverse range of anxiety disorders and across a range of CBT formats. Two of the SCEDs were followed by RCTs, but neither of these were named in the NICE guidelines for anxiety disorders. All of the SCEDs identified were rated as low quality with none meeting the criteria for the highest or second highest quality rating. From the secondary searches, none of the RCTs named in the NICE guide were preceded by SCEDs.ConclusionsIt was concluded that currently SCEDs were not followed by RCTs of CBT interventions named in the NICE guidelines for adolescent anxiety disorders. However, it was suggested that SCEDs may provide an important framework for the development of more effective interventions for adolescents with anxiety.

Single-case experimental design is a family of experimental methods that can be used to examine the efficacy of interventions by testing a small number of patients or cases. This article provides an overview of single-case experimental design research for use in rehabilitation as another option along with traditional group-based research when studying rare cases and rehabilitation interventions of unknown efficacy. Basic concepts related to single-case experimental design and the characteristics of common subtypes ( N-of-1 randomized controlled trial, withdrawal design, multiple-baseline design, multiple-treatment design, changing criterion/intensity design, and alternating treatment design) are introduced. The advantages and disadvantages of each subtype are discussed along with challenges in data analysis and interpretation. Criteria and caveats for interpreting single-case experimental design results and their use in evidence-based practice decisions are discussed. Recommendations are provided for appraising single-case experimental design articles as well as using single-case experimental design principles to improve real-world clinical evaluation.

This paper compares two methods, inferential statistics and Systems Dynamics, to study the evolution of individual happiness after a single dose of drug consumption. In an application case, the effect of alcohol and caffeine on happiness is analyzed through a single-case experimental design, with replication, involving two participants. Both inferential statistical analysis and Systems Dynamics methods have been used to analyze the results. Two scales were used to measure happiness—the Euphoria Scale (ES) and the Smiling Face Scale (SFS)—in trait and state format. A single-case experimental ABC design was used. Phase A had no treatment, and Phases B and C saw both subjects receiving 26.51 mL of alcohol and 330 mg of caffeine, respectively. The participants filled in a form with both scales in a state format every 10 min over a 3 h period, operating in each one of the three phases A, B and C. The main conclusion of the analysis performed is that both methods provide similar results about the evolution of individual happiness after single dose consumption. Therefore, the article shows that inferential statistics and the stimulus response model derived from the Systems Dynamics approach can be used in a complementary and enriching way to obtain prediction results.

We explored the effectiveness of a sensory-based, family-centered coaching approach to changing problematic routines for young children with autism. Three mothers of young children with autism, atypical sensory processing, and global developmental delay each participated in a single-case experimental ABA design study. Mothers selected a problematic daily routine linked to sensory challenges as the focus of four intervention sessions provided in the home. Changes in mothers' perceptions of the children's behavior were the primary outcome, measured daily on a visual analog scale. Visual and descriptive analyses were undertaken. The sensory-based, family-centered coaching approach showed promise for changing sensory-related problem behaviors of young children with autism, but the degree and maintenance of the intervention effect varied among participants.

Single-Case Experimental Designs (SCEDs) are increasingly recognized as a valuable alternative to group designs. Mediation analysis is useful in SCEDs contexts because it informs researchers about the underlying mechanism through which an intervention influences the outcome. However, methods for conducting mediation analysis in SCEDs have only recently been proposed. Furthermore, repeated measures of a target behavior present the challenges of autocorrelation and missing data. This paper aims to extend methods for estimating indirect effects in piecewise regression analysis in SCEDs by (1) evaluating three methods for modeling autocorrelation, namely, Newey-West (NW) estimation, feasible generalized least squares (FGLS) estimation, and explicit modeling of an autoregressive structure of order one (AR(1)) in the error terms and (2) evaluating multiple imputation in the presence of data that are missing completely at random. FGLS and AR(1) outperformed NW and OLS estimation in terms of efficiency, Type I error rates, and coverage, while OLS was superior to the methods in terms of power for larger samples. The performance of all methods is consistent across 0% and 20% missing data conditions. 50% missing data led to unsatisfactory power and biased estimates. In light of these findings, we provide recommendations for applied researchers.

Missing data is inevitable in single-case experimental designs (SCEDs) studies due to repeated measures over a period of time. Despite this fact, SCEDs implementers such as researchers, teachers, clinicians, and school psychologists usually ignore missing data in their studies. Performing analyses without considering missing data in an intervention study using SCEDs or a meta-analysis study including SCEDs studies in a topic can lead to biased results and affect the validity of individual or overall results. In addition, missingness can undermine the generalizability of SCEDs studies. Considering these drawbacks, this study aims to give descriptive and advisory information to SCEDs practitioners and researchers about missing data in single-case data. To accomplish this task, the study presents information about missing data mechanisms, item level and unit level missing data, planned missing data designs, drawbacks of ignoring missing data in SCEDs, and missing data handling methods. Since single imputation methods among missing data handling methods do not require complicated statistical knowledge, are easy to use, and hence are more likely to be used by practitioners and researchers, the present study evaluates single imputation methods in terms of intervention effect sizes and missing data rates by using a real and hypothetical data sample. This study encourages SCEDs implementers, and also meta-analysts to use some of the single imputation methods to increase the generalizability and validity of the study results in case they encounter missing data in their studies.

Single-Case Experimental Designs (SCEDs) have lately been recognized as a valuable alternative to large-group studies. SCEDs form a great tool for the evaluation of treatment effectiveness in heterogeneous and low-incidence conditions, which are common in the field of communication disorders. Mediation analysis is indispensable in treatment research because it informs researchers about the mechanism through which the intervention leads to changes (e.g., communication skills) in the outcome of interest (e.g., developmental outcomes). Despite the increasing popularity of both SCEDs and mediation analysis, there are currently no methods for estimating mediated effects for a single individual. This paper describes how Bayesian piecewise regression analysis can be used for mediation analysis in SCEDs. A Playskin LiftTM dataset from one infant born preterm who is at risk for cognitive developmental delays is used to illustrate two approaches to mediation analysis in SCEDs: Bayesian computation of the mediated effect and Bayesian informative hypothesis testing. Annotated R code is provided so researchers can easily fit the proposed models to their own SCED data set. Advantages and limitations of the method are discussed.

The use of single-case experimental design (SCED) methodology is growing across all domains of rehabilitation. SCED methodology may be used for several different purposes, which creates confusion about its ethical, legal and regulatory status. We will argue that aspects of SCED methodology can be helpful in clinical practice to determine the optimal treatment for a given person. Given the use of SCED methods in research, clinicians may assume that ethics committee approval is required, though this is not necessarily the case given that SCED methods may, under certain circumstances, be considered as evidence-based clinical practice, rather than generalizable research. In this paper, we aim to raise awareness of the principles and legal/ethical framework of SCEDs, and we propose a series of position points that could help researchers/ethics review boards to determine whether a SCED is “research” or “evidence-based person-specific clinical practice”, based on its design and purpose. We aim to clarify how the features of SCED methodology - baseline length and content, repeated measurement, randomization, and blinding - impact SCED categorization. A secondary objective is to provide recommendations for universities and training institutes to help trainees undertaking SCED studies to use appropriate methodologies that comply with the proposed regulatory framework.