Individuals with intellectual and developmental disabilities who exhibit problem behavior often receive behavioral assessment and treatment in specialized inpatient and outpatient clinics. However, problem behavior sometimes reemerges as a function of changes in contexts and stimulus conditions, such as returning to the home environment. This reemergence is called renewal. Recently, Muething et al. (2020) found that renewal occurred in over half (67%) of cases from an outpatient clinic. Their sample was obtained exclusively from an outpatient setting and despite the applied relevance of renewal, its clinical prevalence in other populations is unknown. Accordingly, we replicated Muething et al.’s procedures and analyzed renewal in 37 inpatient treatment applications across 34 cases via consecutive‐controlled case series. Renewal was present in 59% of cases; however, we found that renewal occurred in only 24% of context changes compared to 42% reported by Muething et al. Various factors related to the prevalence of renewal were evaluated.

The dual‐criteria and conservative dual‐criteria methods effectively supplement visual analysis with both simulated and published datasets. However, extant research evaluating the probability of observing false positive outcomes with published data may be affected by case selection bias and publication bias. Thus, the probability of obtaining false positive outcomes using these methods with data collected in the course of clinical care is unknown. We extracted baseline data from clinical datasets using a consecutive controlled case‐series design and calculated the proportion of false positive outcomes for baseline phases of various lengths. Results replicated previous findings from Lanovaz, Huxley, and Dufour (2017), as the proportion of false positive outcomes generally decreased as the number of points in Phase B (but not Phase A) increased using both methods. Extending these findings, results also revealed differences in the rate of false positive outcomes across different types of baselines.

Scheithauer et al. (2020) recently demonstrated that differences in the source of baseline data extracted from a functional analysis (FA) may not affect subsequent clinical decision-making in comparison to a standard baseline. These outcomes warrant additional quantitative examination, as correspondence of visual analysis has sometimes been reported to be unreliable. In the current study, we quantified the occurrence of false positives within a dataset of FA and baseline data using the dual-criteria (DC) and conservative dual-criteria (CDC) methods. Results of this quantitative analysis suggest that false positives were more likely when using FA data (rather than original baseline data) as the initial treatment baseline. However, both sources of baseline data may have acceptably low levels of false positives for practical use. Overall, the findings provide preliminary quantitative support for the conclusion that determinations of effective treatment may be easily obtained using different sources of baseline data.