Behavior Modification最新文献

Direct observation is a process central to behavior science, but its implementation may be challenging in some contexts (e.g., classrooms, homes). One potential solution to improve the feasibility of conducting behavioral observation and measurement involves machine learning. Using previously published data, we developed and tested novel models to automatically measure the duration of vocal stereotypy in eight children with autism. In addition to accuracy and the kappa statistic, we examined session-by-session correlations between values measured by machine learning and those recorded by a human observer. Nearly all our models produced high correlations (i.e., .90 or more) and resulted in better metrics than those reported by the original study. The next step is for researchers to test the models on novel datasets to examine the generalizability of our findings.

The present single-case quasi-experimental study monitored changes in target behavior and experiential avoidance (EA) in an individually delivered, 10-session weekly acceptance and commitment therapy intervention. Participants were three university students with elevated EA who endorsed varying mental health concerns. Primary outcome and process variables were daily measures of clinically relevant behavioral excesses (CRB-E) and daily participant-rated EA, respectively. Additionally, we collected weekly measures of EA, along with pre-, mid-, post-treatment, and 3-month follow-up clinical outcome measures. Overall, synchrony across daily, weekly, and pre/post nomothetic measures was largely observed across participants, and findings suggested improvement in clinical outcomes for two of three participants. Daily measurements of CRB-E and EA fluctuated considerably within both baseline and intervention phases. Cross-lagged correlation analyses revealed no evidence of temporal precedence of change in daily measured EA over change in daily measured CRB-E (or vice versa). Implications of these findings and directions for future research are discussed.

Visual analysis is the primary method to detect functional relations in single-case experimental design (SCED) research. Meta-Visual-Analysis (MVA) is a novel approach used to synthesize SCED data where the estimated effect size measures are principally anchored to primary aspects of visual analysis: change in the magnitude of level, trend, variability, and trend-adjusted level of projected trends. For each of these aspects, percentage point differences between baseline and intervention conditions are estimated and quantified for every participant across studies. MVA effect sizes are standardized, and their aggregates are graphically displayed in a manner similar to individual SCED graphs. MVA graphs are compared and visually analyzed with the aim of better understanding the effectiveness and generality of interventions across SCED studies. In this discussion paper we provide general steps to conduct an MVA and describe MVA's utility in reviewing, organizing, and directing future SCED research syntheses.

Sleep deprivation is a common health condition among people with intellectual disabilities. Studies have linked sleep problems with challenging behaviors. However, it is unclear if there is a consistent effect on challenging behavior and what reinforcement mechanism(s) might be involved. A systematic review of PsychINFO, PubMed, and Scopus identified seven studies meeting the inclusion criteria that had been published over the past 50 years. Data were extracted regarding participant characteristics, specific aim, sleep deprivation, functional behavioral assessments, results, and key findings. Studies consistently reported increased rates of challenging behavior following bouts of sleep deprivation. Five of the seven studies demonstrated negative reinforcement as the mechanism associated with increased challenging behavior. Results were unclear or lacking for other reinforcer mechanisms. Current evidence shows that sleep deprivation can increase negatively reinforced challenging behavior, but automatic and positive reinforcement mechanisms may be unaffected. Theoretical and practice implications are discussed.

In vivo therapeutic coaching of parent-child interactions is the primary mechanism of change in behavioral parent training programs such as parent-child interaction therapy (PCIT), yet relatively little research has examined the coaching process. The primary aim of this study was to explore the bidirectional interaction between therapist-parent dyads to better understand how therapists influence parent behavior and vice versa. Observational data from two research projects were analyzed separately and together using lag sequential analysis (LSA). Results demonstrate that therapist responsive coaching (e.g., praising parent behavior) led parents to use more child-centered skills. Responsive coaching techniques led to immediate increases in parents' use of the targeted positive parenting skill (10%-25% re-use). Responsive strategies followed targeted parent verbalizations more often than directive strategies, suggesting that therapists reinforce positive parenting skills as soon as parents use them. When directive coaching techniques were used, there was a 18% to 32% chance that parents followed through with a child-centered skill as coached. This study is the first to explore the influence of in vivo coaching on parent skill acquisition on a micro-level and has implications for the therapist training.

The psychometric properties of the Reward Probability Index (RPI), which assesses environmental reward as an indirect measure of response-contingent positive reinforcement (RCPR), were estimated in a Mexican population. With the voluntary participation of 1297 adults, reliability was assessed, and evidence was collected regarding the internal structure and its relationship with emotional symptomatology and other variables. Good internal consistency indices (ω and α) were found for both the total scale and its dimensions. A two-dimensional structure, comprising Reward Probability and Environmental Suppressors, and a second-order factor consistent with RCPR theory, was confirmed. This model demonstrated measurement invariance across sex, mental health treatment status, and the presence or absence of emotional symptomatology. Consistent relationships were observed between RPI scores and emotional symptomatology, psychological inflexibility, and life satisfaction. Additionally, evidence was found supporting the criterion validity of the RPI in relation to depression. RPI is a psychometrically solid instrument, and its use is recommended in the Mexican population to account for environmental reward, utilizing a total score and by dimensions.

A reversal design (i.e., ABAB) was used to examine whether increasing steps correlate with higher levels of student interactions. Furthermore, does allowing educators to monitor their steps and set step goals enhance the potential for intervention adoption and lead to lasting teacher behavior change? Each pre-service inclusive early childhood special education teachers were in the final year of their preparation program, during their student teaching practicum. The study took place in two public k-5 elementary schools situated in a mid-size city (approximately 52K in population) in the Southern United States. In addition to visual analysis procedures, nonoverlap of all pairs was used to assess overlap, and Tau-U were used to calculate effect size. The research questions were: (1) Does goal setting and step counting increase the physical steps taken by educators during instruction?; 2) Is there a functional relation between steps taken and teacher-student interactions?; and (3) Are step increases a socially valid approach for increasing teacher-student engagement? Although the results point to minor (positive) effects on teacher steps, the data's variability prevents us from drawing conclusions about the relationship between independent and dependent variables. Nonetheless, when comparing baseline levels to MSI behaviors, we can observe meaningful shifts in a therapeutic direction in the MSI data.. Implications for research and practices are also presented.

Persistent inappropriate self-feeding (e.g., finger-feeding food typically consumed using a utensil after 14-24 months of age) is common for children with neurodevelopmental disorders and other delays and can result in energy and nutrient deficiencies. Although interventions for problematic feeding behavior are common, there is limited information for children without a pediatric feeding disorder who self-feed but exclusively do so inappropriately. We used a proactive approach, with a foundation in the skill-acquisition literature, to address the inappropriate self-feeding of seven children with neurodevelopmental disorders or other delays but without a feeding-related diagnosis. We first evaluated response blocking as an assessment to identify motivation and skill deficits. The assessment identified a skill deficit, a motivation deficit, and a combined deficit for four, two, and one participant, respectively. These results informed treatment for six of the seven participants. Treatment for a motivation deficit included response blocking with and without programmed differential reinforcement. Treatment for a skill deficit included backward chaining with response blocking and programmed differential reinforcement. Treatments were generally successful for all six participants. We discuss the usefulness and implications of response blocking as a brief assessment for inappropriate self-feeding.

The identification of behavioral markers that predict the trajectory of behavior could guide the allocation of limited clinical resources to improve efficacy, efficiency, and safety. As a preliminary exploration of this possibility, we conducted a retrospective records review of incident reports for aggression displayed by residents at a secure juvenile detention center. Our purpose was to evaluate latency to first aggression as a candidate behavioral marker for predicting subsequent high-rate aggression. Our results indicate that latency to first aggression may be a high-quality predictor of subsequent high-rate aggression, and we identified specific cutoff scores that added high levels of predictive value. We use these data to demonstrate a process by which clinicians and researchers can identify predictor variables and use them to guide subsequent allocation of clinical resources. Practical, conceptual, and ethical considerations related to applications of this process as well as potential directions for future research in this area are discussed.