Association for Behavior Analysis International

The Association for Behavior Analysis International® (ABAI) is a nonprofit membership organization with the mission to contribute to the well-being of society by developing, enhancing, and supporting the growth and vitality of the science of behavior analysis through research, education, and practice.


35th Annual Convention; Phoenix, AZ; 2009

Event Details

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Symposium #434
CE Offered: PSY/BACB
Further Analyses of the Sensitivity of Partial Interval Recording and Momentary Time Sampling for Detecting Behavior Changes
Monday, May 25, 2009
1:30 PM–2:50 PM
North 129 A
Area: DDA/AUT; Domain: Applied Behavior Analysis
Chair: John T. Rapp (St. Cloud State University)
Abstract: This symposium includes four presentations on the sensitivity of partial interval recording (PIR) and momentary time sampling (MTS) for detecting changes in actual or simulated behavioral events. In the first study, Devine and Rapp generated simulated data to target sessions with various percentages (e.g., 25%, 50%, 75%) of an event and subsequently evaluated the extent to which each interval size of PIR and MTS detected small, moderate, or large behavior changes. In addition, Devine and Rapp evaluated whether 10-min, 30-min, or 60-min sessions increased the sensitivity of each interval size of PIR or MTS for detecting small or moderate behavior changes. Finally, Devine and Rapp also evaluated the extent to which PIR and MTS produced false positives when evaluating changes in duration events and whether interval methods generated trends that did not exist in the respective CDR data paths. Testa and Rapp conducted a study that was similar the Devine and Rapp study; however, they focused on evaluating changes in frequency (discrete) events with PIR and MTS. In the third study, Carrol and Rapp evaluated whether the sensitivity of MTS for detecting small or moderate behavior changes could be enhanced using (a) combinations of MTS and PIR, (b) combinations of MTS and whole interval recording, and (c) variable intervals sizes of MTS. In the final presentation, Delmolino et al. evaluated the extent to which various interval sizes of PIR and MTS detected the same behavior function as continuous measures based on the results from functional assessments for several individuals.
Evaluating the Accuracy of Interval Recording Methods in Estimating Duration Events: Assessing the Effect of Session Length
SHERISE L. DEVINE (St. Cloud State University and St. Amant), John T. Rapp (St. Cloud State University)
Abstract: This study extends upon the body of research that exists in assessing the accuracy of partial-interval recording (PIR) and momentary time sampling (MTS) in estimating duration events. Simulated data were generated to produce various absolute durations of behavior (25%, 33%, 50%, 66% and 75%) for various session lengths (10 min, 30 min, and 60 min). Inter-response times (IRT) were simulated for low, medium, or high ratios for each percentage of behavior. The generated data were scored using continuous duration recording (CDR) and graphed into ABAB reversal designs. Subsequently, the generated data were re-scored using PIR and MTS with interval sizes set at 10 s, 20 s, 30 s, 1 min, and 2 min. Results were graphed accordingly into ABAB reversal designs and visually inspected for functional control otherwise depicted in the CDR measures. Overall, increased session length yielded increased sensitivity for most interval recording methods examined, with exception to PIR interval sizes set at 30-s or higher. Increased session length allowed MTS with interval sizes up to 30-s to detect a slightly higher proportion of small behavior changes than 10-s MTS when using shorter sessions.
Evaluating the Sensitivity of Interval Recording Methods for Detecting Changes in Frequency Events: The Effect of Session Length
JENNIFER TESTA (St Cloud State University), John T. Rapp (St. Cloud State University)
Abstract: This study extends the findings on the accuracy of using partial interval recording (PIR) and momentary time sampling (MTS) to estimate frequency events by investigating the effects of session length. Using simulated data, continuous frequency records (CFR) were generated for events at different rates (approximately 0.75, 2.0, 3.0, 4.0, 5.0, 6.0, 8.0, 13.0, and 20.0 rpm) and session lengths (10, 30, and 60 min). Thereafter, CFR were converted into PIR and MTS records with 10-s, 20-s, 30-s, 1-min, and 2-min intervals. Data were depicted on line graphs and analyzed within ABAB reversal design. The results indicated that the sensitivity of various interval sizes of MTS increased as the session length increase and that some interval methods generate trends that do not appear in the CFR data paths.
Detecting Changes in Simulated Events: Using Variations of Momentary Time-Sampling to Measure Changes in Duration Events
REGINA A CARROLL (Saint Cloud State University), John T. Rapp (St. Cloud State University)
Abstract: The extent to which a greater proportion of small behavior changes could be detected with momentary time-sampling (MTS) was evaluated by (a) combining various interval sizes of partial-interval recording (PIR) with specific interval sizes of MTS and (b) using variable interval sizes of MTS that were based on means of 20 s and 1 min. For each targeted percentage, low, moderate, and high interresponse times to event-run ratios were compared with reversal designs to determine whether sensitivity increased with either variation of MTS. The results showed that (a) combinations of MTS and PIR and MTS and WIR yielded increased sensitivity over MTS alone; however, the increased sensitivity was offset by an increased probability of generating false positives and (b) variable-interval MTS produced comparable sensitivity to fixed-interval MTS. Thus, none of the three variations of MTS yielded increased detection of small behavior changes.
Comparison of data obtained via continuous and interval recording methods during functional behavior assessment and treatment evaluation for stereotyped behavior.
SUZANNAH J. FERRAIOLI (Douglass Developmental Disabilities Center, Rutger), Lara M. Delmolino (Douglass Developmental Disabilities Center, Rutger), Robert LaRue (Douglass Developmental Disabilities Center, Rutger), Kate E. Fiske (Kennedy Krieger Institute), Meredith Bamond (Douglass Developmental Disabilities Center, Rutger), Kimberly Sloman (Douglass Developmental Disabilities Center, Rutger)
Abstract: A number of studies have demonstrated that the use of partial interval recording (PIR) overestimates the occurrence of stereotyped behavior in clinical settings, whereas momentary time-sampling (MTS) more closely matches the relative duration of the behavior as measured by continuous observation and recording. (Delmolino, Fiske & Dackis, 2008; Gardenier, MacDonald, & Green, 2004). Further, it has been demonstrated that the selection of interval length and rate of the behavior impact the accuracy of both PIR and MTS (Fiske, Delmolino & Ferraioli, 2008; Gardenier et al., 2004 . Despite these findings, PIR data is often utilized for measurement of stereotyped behavior. In related research, Meany-Daboul, Roscoe, Bourret and Ahearn (2007) compared continuous frequency and duration data with PIR and MTS data within a treatment analysis and found that methods generated similar conclusions regarding data trends and response to treatment, although frequency data more closely matched PIR and duration data more closely matched MTS. The current study extends this line of research by comparing the data produced by continuous duration recording with PIR and MTS at various interval lengths for stereotypy exhibited by children with autism across functional behavior assessment sessions. Visual analysis will examine whether the same behavioral function is identified using each data method during functional assessment within a multi-element design. Subsequent data produced in treatment evaluation sessions with each observation method will also be compared to evaluate whether interpretations regarding response to treatment are influenced by data type. This line of research helps to highlight the need for calibration of data collection methods to ensure the most accurate data to guide data-based clinical decisions, particularly in relation to stereotyped behavior.



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