Evaluating the Effectiveness of Take it Personal!+ in People With Mild Intellectual Disability or Borderline Intellectual Functioning and Substance Use Disorder: A Multiple Baseline Single-Case Experimental Study.

Individuals with mild intellectual disabilities or borderline intellectual functioning are at increased risk to develop a substance use disorder-however, effective treatment programs adapted to this target group are scarce. This study evaluated the effectiveness of Take it Personal!+ in individuals with mild intellectual disabilities or borderline intellectual functioning and substance use disorder. Take it Personal!+ is a personalized treatment based on motivational interviewing and cognitive-behavioral therapy supported by an mHealth application. Data were collected in a nonconcurrent multiple baseline single-case experimental design across individuals with four phases (i.e., baseline, treatment, posttreatment, and follow-up). Twelve participants were randomly allocated to baseline lengths varying between 7 and 11 days. Substance use quantity was assessed during baseline, treatment, and posttreatment with a daily survey using a mobile application. Visual analysis was supported with statistical analysis of the daily surveys by calculating three effect size measures in 10 participants (two participants were excluded from this analysis due to a compliance rate below 50%). Secondary, substance use severity was assessed with standardized questionnaires at baseline, posttreatment, and follow-up and analyzed by calculating the Reliable Change Index. Based on visual analysis of the daily surveys, 10 out of 12 participants showed a decrease in mean substance use quantity from baseline to treatment and, if posttreatment data were available, to posttreatment. Statistical analysis showed an effect of Take it Personal!+ in terms of a decrease in daily substance use in 8 of 10 participants from baseline to treatment and if posttreatment data were available, also to posttreatment. In addition, data of the standardized questionnaires showed a decrease in substance use severity in 8 of 12 participants. These results support the effectiveness of Take it Personal!+ in decreasing substance use in individuals with mild intellectual disabilities or borderline intellectual functioning.

The Permutation Distancing Test for dependent single-case observational AB-phase design data: A Monte Carlo simulation study.

The Permutation Distancing Test (PDT) is a nonparametric test for evaluating treatment effects in dependent single-case observational design (SCOD) AB-phase data without linear trends. Monte Carlo methods were used to estimate the PDT power and type I error rate, and to compare them to those of the Single-Case Randomization Test (SCRT) assuming a randomly determined intervention point and the traditional permutation test assuming full exchangeability. Data were simulated without linear trends for five treatment effect levels (- 2, - 1, 0, 1, 2), five autocorrelation levels (0, .15, .30, .45, .60), and four observation number levels (30, 60, 90, 120). The power was calculated multiple times for all combinations of factor levels each generating 1000 replications. With 30 observations, the PDT showed sufficient power (≥ 80%) to detect medium treatment effects up to autocorrelation ≤ .45. Using 60 observations, the PDT showed sufficient power to detect medium treatment effects regardless of autocorrelation. With ≥ 90 observations, the PDT could also detect small treatment effects up to autocorrelation ≤ .30. With 30 observations, the type I error rate was 5-7%. With 60 observations and more, the type I error rate was ≤ 5% with autocorrelation < .60. The PDT outperformed the SCRT regarding power, particularly with a small number of observations. The PDT outperformed the traditional permutation test regarding type I error rate control, especially when autocorrelation increased. In conclusion, the PDT is a useful and promising nonparametric test to evaluate treatment effects in dependent SCOD AB-phase data without linear trends.

Internet-Delivered Therapy for Parents With Health Anxiety by Proxy: Protocol for a Single-Case Experimental Design Study.

BACKGROUND: Health anxiety (HA) by proxy is described as parents' obsessive worries that their child is severely ill although this is not medically confirmed. Research on HA by proxy suggests that it is highly distressing for the parent and that the child may be at risk of developing maladaptive symptom coping strategies. No targeted treatment for this group exists. We developed PROXY, an 8-week psychological internet-delivered treatment for parents with HA by proxy. The treatment components of PROXY are informed by cognitive behavioral therapy as well as acceptance and commitment therapy, and it was developed in collaboration with parents experiencing HA by proxy and clinical experts. OBJECTIVE: This paper describes the protocol for a study investigating the potential effects of PROXY on parents' worries about their children's health using a single-case experimental design (SCED). METHODS: Five parents clinically evaluated as experiencing HA by proxy will be included. A replicated randomized SCED study will be conducted in which each participant will be randomized to receive treatment after a baseline period of between 7 and 26 days (phase A). The treatment phase duration is 8 weeks for all participants (phase B), followed by a follow-up phase lasting between 14 and 33 days (phase C), ensuring that all participants remain in the study for 96 days. Participants will report daily anxiety level by SMS text message throughout the study. They will also answer self-report questionnaires, including questions on HA by proxy and own HA, 4 times during the study. Data will be submitted to structured visual analysis to inspect anxiety level, the variability of anxiety, trends, the overlap of data points among phases, when effects occur, and the consistency of data patterns across participants. Furthermore, randomization tests will be conducted for each participant to test the null hypothesis that PROXY will have no effect on participants' anxiety. RESULTS: The recruitment of parents began in June 2022. As of March 2, 2023, a total of 4 parents have been included in the study. Data collection was expected to cease in April 2023. CONCLUSIONS: To the best of our knowledge, this protocol describes the only study of treatment for HA by proxy. As the prevalence of this condition is still unknown, a SCED was chosen because this method allows the inclusion of very few participants while still providing information on effects and treatment courses. Conducting the study with a replicated randomized phase design enables methodologically sound testing despite the inclusion of very few participants. The results will inform researchers on individual treatment courses and effects, which may direct future research in terms of the possible mechanisms of change, ideas for how to refine the treatment content, and how the treatment may be offered to patients in the future. TRIAL REGISTRATION: ClinicalTrials.gov NCT04830605; https://clinicaltrials.gov/study/NCT04830605. INTERNATIONAL REGISTERED REPORT IDENTIFIER (IRRID): DERR1-10.2196/46927.

Testing delayed, gradual, and temporary treatment effects in randomized single-case experiments: A general response function framework.

Randomization tests represent a class of significance tests to assess the statistical significance of treatment effects in randomized single-case experiments. Most applications of single-case randomization tests concern simple treatment effects: immediate, abrupt, and permanent changes in the level of the outcome variable. However, researchers are confronted with delayed, gradual, and temporary treatment effects; in general, with "response functions" that are markedly different from single-step functions. We here introduce a general framework that allows specifying a test statistic for a randomization test based on predicted response functions that is sensitive to a wide variety of data patterns beyond immediate and sustained changes in level: different latencies (degrees of delay) of effect, abrupt versus gradual effects, and different durations of the effect (permanent or temporary). There may be reasonable expectations regarding the kind of effect (abrupt or gradual), entailing a different focal data feature (e.g., level or slope). However, the exact amount of latency and the exact duration of a temporary effect may not be known a priori, justifying an exploratory approach studying the effect of specifying different latencies or delayed effects and different durations for temporary effects. We provide illustrations of the proposal with real data, and we present a user-friendly freely available web application implementing it.

Out of proportion or out of context? Comparing 8- to 9-year-olds' proportional reasoning abilities across fair-sharing, mixtures, and probability contexts.

Findings on children's proportional reasoning abilities strongly vary across studies. This might be due to the different contexts that can be used in proportional problems: fair-sharing, mixtures, and probability. A review of the scientific literature suggests that the context of proportional problems may not only impact the difficulty of the problem, but that it also plays an important role in how children approach the problems. In other words, different contexts might elicit different (erroneous) thinking strategies. The aim of the present study was to investigate the role of context in third graders' (n = 305) proportional reasoning abilities. Results showed that children performed significantly better in a fair-sharing context compared to a mixture and a probability context. No evidence was found for a difference in performance on the mixture and the probability context. However, the kind of erroneous answers that were given in the mixture and probability context differed slightly, with more additive answers in the mixture context and more one-dimensional answers in the probability context. These findings suggest that the type of answers elicited by proportional problems might depend on the specific context in which the problem is presented.

Components of Behavioral Parent Training for Children With Attention-Deficit/Hyperactivity Disorder: A Series of Replicated Single-Case Experiments.

Behavioral parent training (BPT) is an evidence-based treatment for children with attention-deficit/hyperactivity disorder (ADHD). Stimulus control techniques (antecedent-based techniques, e.g., clear rules, instructions) and contingency management techniques (consequent-based techniques, e.g., praise, ignore) are the most common ones that are being taught to parents in BPT. However, research into the additive effects of these techniques is scarce. In this replicated single-case experimental ABC phase design, including six children on stable medication for ADHD (8-11 years) and their parents, the added efficacy of consequent-based techniques on top of antecedent-based techniques was evaluated. After a baseline period (phase A), we randomized the commencement time of two sessions parent training in antecedent-based techniques and two sessions parent training in consequent-based techniques for each child. Children's behaviors were assessed by daily parent ratings of selected problem behaviors and an overall behavior rating. Although visual inspection showed that behavior improved for most children in both phases, randomization tests did not demonstrate the added efficacy of the consequent-based techniques on top of the antecedent-based techniques. Limitations of the study and recommendations for future single-case experiments in this population are discussed.

Consistency in Single-Case ABAB Phase Designs: A Systematic Review.

The current article presents a systematic review of consistency in single-case ABAB phase designs. We applied the CONsistency of DAta Patterns (CONDAP) measure to a sample of 460 data sets retrieved from 119 applied studies published over the past 50 years. The main purpose was to (a) identify typical CONDAP values found in published ABAB designs and (b) develop interpretational guidelines for CONDAP to be used for future studies to assess the consistency of data patterns from similar phases. The overall distribution of CONDAP values is right-skewed with several extreme values to the right of the center of the distribution. The B-phase CONDAP values fall within a narrower range than the A-phase CONDAP values. Based on the cumulative distribution of CONDAP values, we offer the following interpretational guidelines in terms of consistency: very high, 0 ≤ CONDAP ≤ 0.5; high, 0.5 < CONDAP ≤ 1; medium, 1 < CONDAP < 1.5; low, 1.5 < CONDAP ≤ 2; very low, CONDAP > 2. We give examples of combining CONDAP benchmarks with visual analysis of single-case ABAB phase designs and conclude that the majority of data patterns (41.2%) in published ABAB phase designs is medium consistent.

It is probably a pattern: does spontaneous focusing on regularities in preschool predict reasoning about randomness four years later?

The many studies with coin-tossing tasks in literature show that the concept of randomness is challenging for adults as well as children. Systematic errors observed in coin-tossing tasks are often related to the representativeness heuristic, which refers to a mental shortcut that is used to judge randomness by evaluating how well a set of random events represents the typical example for random events we hold in our mind. Representative thinking is explained by our tendency to seek for patterns in our surroundings. In the present study, predictions of coin-tosses of 302 third-graders were explored. Findings suggest that in third grade of elementary school, children make correct as well as different types of erroneous predictions and individual differences exist. Moreover, erroneous predictions that were in line with representative thinking were positively associated with an early spontaneous focus on regularities, which was assessed when they were in second year of preschool. We concluded that previous studies might have underestimated children's reasoning about randomness in coin-tossing contexts and that representative thinking is indeed associated with pattern-based thinking tendencies.

The effectiveness of aerobic versus strengthening exercise therapy in individuals with chronic whiplash-associated disorder: a randomised single case experimental design study.

PURPOSE: Recent RCTs and meta-analyses compare the effectiveness of different types of exercise for chronic whiplash associated disorder (WAD). This study aimed to verify whether the results of these studies translate to statistically significant and clinically meaningful effects in individual participants. MATERIALS AND METHODS: A series of replicated randomised single case experimental design studies (SCEDs) with A-B design (A: baseline, B: intervention). Eight participants with chronic WAD (8 female, mean [SD] age 47 [10] years) were randomised into one of four baseline durations (5, 8, 11, and 14 days) and to one of two eight-week exercise interventions (aerobic or strengthening). Daily measures of pain intensity, bothersomeness, and interference were collected during the baseline phase and the intervention phase. RESULTS: Visual analyses indicated that three participants in the aerobic exercise group meaningfully improved. No improvements were found in the strengthening group. Effect sizes favoured the aerobic exercise group, yet randomisation tests of pooled effects did not show a difference in between-intervention effectiveness. CONCLUSION: Contrary to our expectations, three out of four participants were nearly pain-free at the end of the aerobic exercise intervention, whereas none of the participants in the strengthening group improved meaningfully. This suggests that aerobic exercise may be favourable for WAD.Implications for RehabilitationOur results suggest that aerobic exercises are favourable over strengthening exercises and may be the preferred option for patients with chronic WAD.We found substantial variability in self-reported outcomes within participants, clinicians should be aware of this in the judgement of treatment effectiveness.

Defining and assessing immediacy in single-case experimental designs.

Immediacy is one of six data aspects (alongside level, trend, variability, overlap, and consistency) that has to be accounted for when visually analyzing single-case data. Given that it is one of the aspects that has received considerably less attention than other data aspects, the current text offers a review of the proposed conceptual definitions of immediacy (i.e., what it refers to) and also of the suggested operational definitions (i.e., how exactly is it assessed and/or quantified). Provided that a variety of conceptual and operational definitions is identified, we propose following a sensitivity analysis using a randomization test for assessing immediate effects in single-case experimental designs, by identifying when changes were most clear. In such a sensitivity analysis, the immediate effects are tested for multiple possible intervention points and for different possible operational definitions. Robust immediate effects can be detected if the results for the different operational definitions converge.

Development, evaluation and implementation of a digital behavioural health treatment for chronic pain: study protocol of the multiphase DAHLIA project.

INTRODUCTION: Chronic pain affects about 20%-40% of the population and is linked to mental health outcomes and impaired daily functioning. Pharmacological interventions are commonly insufficient for producing relief and recovery of functioning. Behavioural health treatment is key to generate lasting benefits across outcome domains. However, most people with chronic pain cannot easily access evidence-based behavioural interventions. The overall aim of the DAHLIA project is to develop, evaluate and implement a widely accessible digital behavioural health treatment to improve well-being in individuals with chronic pain. METHODS AND ANALYSIS: The project follows the four phases of the mHealth Agile Development and Evaluation Lifecycle: (1) development and pre-implementation surveillance using focus groups, stakeholder interviews and a business model; (2) iterative optimisation studies applying single case experimental design (SCED) method in 4-6 iterations with n=10 patients and their healthcare professionals per iteration; (3) a two-armed clinical randomised controlled trial enhanced with SCED (n=180 patients per arm) and (4) interview-based post-market surveillance. Data analyses include multilevel modelling, cost-utility and indicative analyses.In October 2021, inter-sectorial partners are engaged and funding is secured for four years. The treatment content is compiled and the first treatment prototype is in preparation. Clinical sites in three Swedish regions are informed and recruitment for phase 1 will start in autumn 2021. To facilitate long-term impact and accessibility, the treatment will be integrated into a Swedish health platform (www.1177.se), which is used on a national level as a hub for advice, information, guidance and e-services for health and healthcare. ETHICS AND DISSEMINATION: The study plan has been reviewed and approved by Swedish ethical review authorities. Findings will be actively disseminated through peer-reviewed journals, conference presentations, social media and outreach activities for the wider public. TRIAL REGISTRATION NUMBER: NCT05066087.

Estimating and Testing Causal Mediation Effects in Single-Case Experimental Designs Using State-Space Modeling.

In this article, we present single-case causal mediation analysis as the application of causal mediation analysis to data collected within a single-case experiment. This method combines the focus on the individual with the focus on mechanisms of change, rendering it a promising approach for both mediation and single-case researchers. For this purpose, we propose a new method based on time-discrete state-space modeling to estimate the direct and indirect treatment effects. We demonstrate how to estimate the model for a single-case experiment on stress and craving in a routine alcohol consumer before and after an imposed period of abstinence. Furthermore, we present a simulation study that examines the estimation and testing of the standardized indirect effect. All parameters used to generate the data were recovered with acceptable precision. We use maximum likelihood and permutation procedures to calculate p-values and standard errors of the parameters estimates. The new method is promising for testing mediated effects in single-case experimental designs. We further discuss limitations of the new method with respect to causal inference, as well as more technical concerns, such as the choice of the time lags between the measurements.

Quantitative Techniques and Graphical Representations for Interpreting Results from Alternating Treatment Design.

Multiple quantitative methods for single-case experimental design data have been applied to multiple-baseline, withdrawal, and reversal designs. The advanced data analytic techniques historically applied to single-case design data are primarily applicable to designs that involve clear sequential phases such as repeated measurement during baseline and treatment phases, but these techniques may not be valid for alternating treatment design (ATD) data where two or more treatments are rapidly alternated. Some recently proposed data analytic techniques applicable to ATD are reviewed. For ATDs with random assignment of condition ordering, the Edgington's randomization test is one type of inferential statistical technique that can complement descriptive data analytic techniques for comparing data paths and for assessing the consistency of effects across blocks in which different conditions are being compared. In addition, several recently developed graphical representations are presented, alongside the commonly used time series line graph. The quantitative and graphical data analytic techniques are illustrated with two previously published data sets. Apart from discussing the potential advantages provided by each of these data analytic techniques, barriers to applying them are reduced by disseminating open access software to quantify or graph data from ATDs.

The randomized marker method for single-case randomization tests: Handling data missing at random and data missing not at random.

Single-case experiments are frequently plagued by missing data problems. In a recent study, the randomized marker method was found to be valid and powerful for single-case randomization tests when the missing data were missing completely at random. However, in real-life experiments, it is difficult for researchers to ascertain the missing data mechanism. For analyzing such experiments, it is essential that the missing data handling method is valid and powerful for various missing data mechanisms. Hence, we examined the performance of the randomized marker method for data that are missing at random and data that are missing not at random. In addition, we compared the randomized marker method with multiple imputation, because the latter is often considered the gold standard among imputation techniques. To compare and evaluate these two methods under various simulation conditions, we calculated the type I error rate and statistical power in single-case randomization tests using these two methods of handling missing data and compared them to the type I error rate and statistical power using complete datasets. The results indicate that while multiple imputation presents an advantage in the presence of strongly correlated covariate data, the randomized marker method remains valid and results in sufficient statistical power for most of the missing data conditions simulated in this study.

The Additive Effect of CBT Elements on the Video Game 'Mindlight' in Decreasing Anxiety Symptoms of Children with Autism Spectrum Disorder.

The aim of the present study was to examine the additive effect of elements of cognitive behavioral therapy (CBT) on the video game Mindlight in decreasing anxiety of children with an autism spectrum disorder (ASD). A non-concurrent multiple baseline design with 8 children with ASD in the age of 8-12 was used. CBT did not have the hypothesized additive effect on Mindlight in decreasing anxiety of children with ASD. Instead, multiple participants already experienced a decrease in anxiety during the Mindlight sessions. Yet, several participants did experience a stabilization in anxiety at a low level during the CBT sessions. For now, it can be concluded that CBT does not have an additive effect on Mindlight.

Establishment of an International Collaborative Network for N-of-1 Trials and Single-Case Designs.

In this article we briefly examine the unique features of Single-Case Designs (SCDs) (studies in a single participant), their history and current trends, and real-world clinical applications. The International Collaborative Network for N-of-1 Trials and Single-Case Designs (ICN) is a formal collaborative network for individuals with an interest in SCDs. The ICN was established in 2017 to support the SCD scientific community and provide opportunities for collaboration, a global communication channel, resource sharing and knowledge exchange. In May 2021, there were more than 420 members in 31 countries. A member survey was undertaken in 2019 to identify priorities for the ICN for the following few years. This article outlines the key priorities identified and the ICN's progress to date in these key areas including network activities (developing a communications strategy to increase awareness, collecting/sharing a comprehensive set of resources, guidelines and tips, and incorporating the consumer perspective) and scientific activities (writing position papers and guest editing special journal issues, exploring key stakeholder perspectives about SCDs, and working to streamline ethical approval processes for SCDs). The ICN provides a practical means to engage with this methodology through membership. We encourage clinicians, researchers, industry, and healthcare consumers to learn more about and conduct SCDs, and to join us in our mission of using SCDs to improve health outcomes for individuals and populations.

Assessing Consistency in Single-Case Alternation Designs.

Consistency is one of the crucial single-case data aspects that are expected to be assessed visually, when evaluating the presence of an intervention effect. Complementarily to visual inspection, there have been recent proposals for quantifying the consistency of data patterns in similar phases and the consistency of effects for reversal, multiple-baseline, and changing criterion designs. The current text continues this line of research by focusing on alternation designs using block randomization. Specifically, three types of consistency are discussed: consistency of superiority of one condition over another, consistency of the average level across blocks, and consistency in the magnitude of the effect across blocks. The focus is put especially on the latter type of consistency, which is quantified on the basis of partitioning the variance, as attributed to the intervention, to the blocking factor or remaining as residual (including the interaction between the intervention and the blocks). Several illustrations with real and fictitious data are provided in order to make clear the meaning of the quantification proposed. Moreover, specific graphical representations are recommend for complementing the numerical assessment of consistency. A freely available user-friendly webpage is developed for implementing the proposal.

The Assessment of Consistency in Single-Case Experiments: Beyond A-B-A-B Designs.

Quality standards for single-case experimental designs (SCEDs) recommend inspecting six data aspects: level, trend, variability, overlap, immediacy, and consistency of data patterns. The data aspect consistency has long been neglected by visual and statistical analysts of SCEDs despite its importance for inferring a causal relationship. However, recently a first quantification has been proposed in the context of A-B-A-B designs, called CONsistency of DAta Patterns (CONDAP). In the current paper, we extend the existing CONDAP measure for assessing consistency in designs with more than two successive A-B elements (e.g., A-B-A-B-A-B), multiple baseline designs, and changing criterion designs. We illustrate each quantification with published research.

Family-centered practices in home-based support for families with children with an intellectual disability: Judgments of parents and professionals.

BACKGROUND: The realization of the family-centered approach (FCA) in home-based support (HBS) for families with children with an intellectual disability (ID) in Flanders was investigated, and parents' and family workers' perspectives were compared. The relation between parents' educational level, the family worker's education, and his/her experience in HBS; and parents' and family workers' judgments on the realization of the FCA was considered. METHOD: Parents (N = 58 families) and family workers (N = 46) completed the helpgiving practices scale and the enabling practices scale. RESULTS: The FCA was largely present, parents rated its realization higher than family workers. Considering family workers' answers, parents' educational level appeared an important factor for parental autonomy. CONCLUSIONS: The study confirms recent research on the realization of the FCA. Including different perspectives, a nuanced view on the realization of the FCA was obtained. Further research on the concrete meaning, interpretation, and elaboration of the FCA is needed.

A systematic review of applied single-case research published between 2016 and 2018: Study designs, randomization, data aspects, and data analysis.

Single-case experimental designs (SCEDs) have become a popular research methodology in educational science, psychology, and beyond. The growing popularity has been accompanied by the development of specific guidelines for the conduct and analysis of SCEDs. In this paper, we examine recent practices in the conduct and analysis of SCEDs by systematically reviewing applied SCEDs published over a period of three years (2016-2018). Specifically, we were interested in which designs are most frequently used and how common randomization in the study design is, which data aspects applied single-case researchers analyze, and which analytical methods are used. The systematic review of 423 studies suggests that the multiple baseline design continues to be the most widely used design and that the difference in central tendency level is by far most popular in SCED effect evaluation. Visual analysis paired with descriptive statistics is the most frequently used method of data analysis. However, inferential statistical methods and the inclusion of randomization in the study design are not uncommon. We discuss these results in light of the findings of earlier systematic reviews and suggest future directions for the development of SCED methodology.