Association for Behavior Analysis International

This symposium will describe new methods that can be used across educational, medical, and psychiatric settings to improve the quality of data collection and increase the social validity of behavioral interventions. In the first study, the authors developed a data collection tool to evaluate the quality of behavior support plans developed for children with severe problem behavior in a community school. The authors demonstrated that by using the tool, they were able to determine the strengths and weakness of current behavior plans to obtain a measure of quality. The second presentation focuses on a treatment package for improving staff’s data collection. The treatment package included simplified data sheets, behavior clickers, and prompts. Results demonstrate that these strategies can improve the quality of data collection on an inpatient psychiatric unit. The final presentation focuses on increasing the amount of behavior data collected by nurses on an inpatient medical rehabilitation unit. This study expands on the findings from the second presentation by systematically evaluating the effects of prompts via an established medical records system. Results support the use of prompts as demonstrated by a significant increase in the amount of data collected by nurses in prompt conditions as compared to baseline conditions.

The target audience of this talk is any behavior analysist or supervisor who is responsible for monitoring and improving staff performance within a clinical setting.

Data collection is a hallmark of effective behavior-analytic therapy. Collecting accurate data permits a behavior analyst to evaluate the effectiveness of behavioral treatment. The current study evaluated the use of a clicker, simplified observation, and timer to improve accuracy of data collection on a psychiatric unit for children diagnosed with intellectual and developmental disabilities. Experiment 1, conducted within a combined multiple baseline across participants and reversal design, was an evaluation to identify an intervention package for four participants employed by the psychiatric unit. Interventions yielding the highest interobserver agreement (IOA) were highly individualized. Thus, we selected the most comprehensive intervention and exposed four additional participants to this intervention during Experiment 2. Results showed that this intervention improved IOA for these additional participants as evaluated within a multiple baseline across participants design. Results of the current study will be discussed to assist other behavior analysts improve data collection practices in hospital or school settings.

Patient’s behavior in the medical setting often interrupts medical care (e.g., refusal of care, removal of medical equipment, self-injurious, and aggressive behaviors). Direct behavioral measurements are essential to adequately design and evaluate the efficacy of behavioral interventions in an effort to provide appropriate medical care and ensure safety. Nurses have the most frequent contact with patients and are responsible for evaluating and documenting patients’ medical and behavioral information; however, nurses typically collect indirect measurements of behavior and psychological wellbeing rather than direct behavioral observations. The present study evaluated effectiveness of computerized prompts to increase nurses’ data recording behaviors in a subacute pediatric inpatient medical rehabilitation unit. Initial baseline data demonstrated that only 28.17% of intervals of behavior data were collected by nursing staff. Computerized prompts within the hospital’s electronic medical records system (Meditech) were implemented across five sets of nurses using an A-B-A-B reversals with one set, A-C-B-A-B-D-B reversal design with a second set, an A-B design with two sets, and intervention only condition with the final set. Percent of data collected was calculated using permanent products of weekly behavior data sheets. Results of the present study demonstrate that computerized prompts resulted in a clinically significant increase in the percent of data that were collected.