In 1974, Rekers and Lovaas published an article in the Journal of Applied Behavior Analysis (JABA) wherein the authors coached a child’s parents to ignore and physically abuse that child when he engaged in gender-non-conforming behaviors. In October 2020, the Society for the Experimental Analysis of Behavior (SEAB) and JABA’s editor-in-chief Dr. Linda LeBlanc published a Statement of Concern regarding Rekers and Lovaas (1974), which described concerns regarding the paper and then provided justification for the journal’s decision to not retract this paper. In this current response, I articulate criticisms of JABA’s rationale for not retracting this paper. I acknowledge the ambiguity in the evidence available regarding a determination of ethical conduct, and end with an argument that Rekers and Lovaas (1974) should be retracted.

To draw informed conclusions from research studies, research consumers need full and accurate descriptions of study methods and procedures. Preregistration has been proposed as a means to clarify reporting of research methods and procedures, with the goal of reducing bias in research. However, preregistration has been applied primarily to research studies utilizing group designs. In this article, we discuss general issues in preregistration and consider the use of preregistration in single-case design research, particularly as it relates to differing applications of this methodology. We then provide a rationale and make specific recommendations for preregistering single-case design research, including guidelines for preregistering basic descriptive information, research questions, participant characteristics, baseline conditions, independent and dependent variables, hypotheses, and phase-change decisions.

Reliable and valid data form the foundation for evidence-based practices, yet surprisingly few studies on school-based behavioral assessments have been conducted which implemented one of the most fundamental approaches to construct validation, the multitrait-multimethod matrix (MTMM). To this end, the current study examined the reliability and validity of data derived from three commonly utilized school-based behavioral assessment methods: Direct Behavior Rating – Single Item Scales, systematic direct observations, and behavior rating scales on three common constructs of interest: academically engaged, disruptive, and respectful behavior. Further, this study included data from different sources including student self-report, teacher report, and external observers. A total of 831 students in grades 3–8 and 129 teachers served as participants. Data were analyzed using bivariate correlations of the MTMM, as well as single and multi-level structural equation modeling. Results suggested the presence of strong methods effects for all the assessment methods utilized, as well as significant relations between constructs of interest. Implications for practice and future research are discussed.

In this study, generalizability theory was used to examine the extent to which (a) time-sampling methodology, (b) number of simultaneous behavior targets, and (c) individual raters influenced variance in ratings of academic engagement for an elementary-aged student. Ten graduate-student raters, with an average of 7.20 hr of previous training in systematic direct observation and 58.20 hr of previous direct observation experience, scored 6 videos of student behavior using 12 different time-sampling protocols. Five videos were submitted for analysis, and results for observations using momentary time-sampling and whole-interval recording suggested that the majority of variance was attributable to the rating occasion, although results for partial-interval recording generally demonstrated large residual components comparable with those seen in prior research. Dependability coefficients were above .80 when averaging across 1 to 2 raters using momentary time-sampling, and 2 to 3 raters using whole-interval recording. Ratings derived from partial-interval recording needed to be averaged over 3 to 7 raters to demonstrate dependability coefficients above .80.

The implementation of multi-tiered systems in schools necessitates the use of screening assessments which produce valid and reliable data to identify students in need of tiered supports. Data derived from these screening assessments may be evaluated according to their classification accuracy, or the degree to which cut scores correctly identify individuals as at-risk or not-at-risk. The current study examined the performance of mean scores derived from over 1700 students in Grades 1, 2, 4, 5, 7, and 8 using Direct Behavior Rating—Single Item Scales. Students were rated across three time points (Fall, Winter, Spring) by their teachers in three areas: (a) academically engaged behavior, (b) disruptive behavior, and (c) respectful behavior. Classification accuracy indices and comparisons among behaviors were derived using Receiver Operating Characteristic (ROC) curve analyses, partial area under the curve (pAUC) tests, and bootstrapping methods to evaluate the degree to which mean behavior ratings accurately identified students who demonstrated elevated behavioral symptomology on the Behavioral and Emotional Screening System. Results indicated that optimal cut-scores for mean behavior ratings and a composite rating demonstrated high levels of specificity, sensitivity, and negative predictive value, with sensitivity point estimates for optimal cut-scores exceeding .70 for individual behaviors and .75 for composite scores across grade groups and time points.