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ERIC EJ889223: The Effects of Self-Monitoring on the Procedural Integrity of a Behavioral Intervention for Young Children with Developmental Disabilities PDF

2010·0.41 MB·English
by  ERIC
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JOURNALOFAPPLIEDBEHAVIORANALYSIS 2010, 43, 315–320 NUMBER2 (SUMMER2010) THE EFFECTS OF SELF-MONITORING ON THE PROCEDURAL INTEGRITY OF A BEHAVIORAL INTERVENTION FOR YOUNG CHILDREN WITH DEVELOPMENTAL DISABILITIES JOSHUA B. PLAVNICK, SUMMER J. FERRERI, AND ANGELA N. MAUPIN MICHIGANSTATEUNIVERSITY Theeffectsofself-monitoringontheproceduralintegrityoftokeneconomyimplementationby 3 staff in a special education classroom were evaluated. The subsequent changes in academic readiness behaviors of 2 students with low-incidence disabilities were measured. Multiple baselines across staff and students showed that procedural integrity increased when staff used monitoring checklists, and students’ academic readiness behavior also increased. Results are discussedwithrespecttotheuseofself-monitoringandtheimportanceofproceduralintegrityin publicschoolsettings. Keywords: autism,developmentaldisabilities,earlychildhoodspecialeducation,procedural integrity,self-monitoring, token economy _______________________________________________________________________________ Proceduralintegrityisthedegreetowhichan elementary school teachers. Improved integrity intervention is implemented as intended (e.g., was correlated negatively with student problem Najdowski et al., 2008). Accurate implementa- behavior.Thesestudiesareunique,becausethey tion of evidence-based interventions allows report educator and student data for an data-based decision making regarding the intervention in a public school setting. Howev- effectiveness of an intervention and increases er, an external researcher was needed to provide the likelihood of improving student outcomes thefeedbacknecessaryforchangestoprocedural (for a review, see Hagermoser-Sanetti & integrity; ongoing external support may not be Kratochwill, 2008). Effective training practices, feasible in many school settings. such as didactic instruction, behavioral rehears- Self-monitoring is a procedure that has been al, and brief coaching, must be combined with shown to increase the accuracy with which contingencies following training to ensure direct service providers implement a variety of accurate implementation of behavioral inter- protocols in human service organizations (Allen ventions (DiGennaro, Martens, & Kleinman, & Blackston, 2003; Richman, Riordan, Reiss, 2007; DiGennaro, Martens, & McIntyre, Pyles, & Bailey, 1988). Seligson-Petscher and 2005). In these two studies, performance Bailey (2006) examined the effects of self- feedback and negative reinforcement were monitoringontheaccurateimplementationofa combined to increase the procedural integrity behavior intervention plan by public school of a behavioral intervention implemented by personnel. Despite increases in procedural integrity, experimenters provided performance feedback throughout all conditions, making it This investigation was funded by the Office of Special Education and Rehabilitative Services of the U.S. impossible to isolate the effects of self-monitor- Department of Education (Grant H325D030060). We ingonproceduralintegrity.Thepurposesofthe thankMary Mariagefor her collaboration andsupport. currentstudywere(a)toidentifytheeffectsofa Address correspondence to Joshua Plavnick, c/o Sum- mer Ferreri, Counseling Educational Psychology and self-monitoring checklist on the procedural Special Education, College of Education, 340 Erickson, integrity of token economy implementation by MichiganStateUniversity,EastLansing,Michigan48824 early childhood special education (ECSE) (e-mail: [email protected]). doi:10.1901/jaba.2010.43-315 classroom staff and (b) to identify any changes 315 316 JOSHUA B. PLAVNICK et al. in academic readiness behaviors of ECSE a 30-s whole-interval procedure and MotivAi- studentswhenexperimentalmanipulationswere der vibrating timers to signal the end of an applied to token economy implementation. interval. Engagement in academic readiness behavior was scored when a student demon- strated both target behaviors for an entire METHOD interval. Staff participants delivered token Participants, Setting, and Materials reinforcers to students for engaging in these Three Caucasian staff members and 2 behaviors following a pretraining baseline. Hispanic students participated in this research Observations were 10 to 15 min in length and study. Ingrid (teacher), Teri, and Rita (para- occurred during small- and large-group activi- professionals) were educators in a 10-hr per ties 2 or 3 days each week. week ECSE program. Ingrid requested experi- Two independent observers scored 28% of menter support for 2 students in the ECSE staff and 38% of student observations to program who often required one-to-one adult evaluate interobserver agreement. Agreements support to participate in group activities. Toby were identified when both observers scored the (4 years old) had been diagnosed with autism same response for a component (staff partici- and Kendra (3 years old) with Williams pants) or interval (student participants). Dis- syndrome and specific language impairment. agreements were identified when interobserver responses varied for a component or interval. Measurement and Interobserver Agreement Total agreements were divided by the sum of Staff. Experimenters used a discrete categori- agreementsplusdisagreementsandconvertedto zation procedure (Kazdin, 1982) to score the a percentage. Mean agreement for procedural percentage of token economy components integrity was 84% (range, 64% to 100%), 84% implemented correctly. A component was (range, 64% to 91%), and 95% (range, 82% to scored correct if it occurred in the correct order 100%) for Rita, Teri, and Ingrid, respectively. and as written on a token economy procedural Mean agreement for academic readiness behav- checklist (available from the first author). An ior was 83% (range, 60% to 100%) and 94% item was scored incorrect if it was not (range, 70% to 100%) for Toby and Kendra, implemented as written or was implemented respectively. Low agreement scores occurred in the wrong order, or if another response was during initial observations and were corrected implementedinplaceoftheindicatedresponse. by the observers briefly discussing response Experimenters conducted 15-min observations definitions. 2 to 3 days each week. Paper and pencil were used to record data during small- and large- Design and Procedure group activities. The effects of self-monitoring on procedural Students. The dependent measures were the integritywereanalyzedusingamultiplebaseline percentage of intervals students engaged in two design similar to that in DiGennaro et al. academic readiness behaviors (i.e., appropriate (2005). A second multiple baseline design sitting and vocalizing) simultaneously. Appro- across students was used to assess the effects of priate sitting was defined as sitting in a staff- any changes in staff behavior on student designated location and in a manner instructed behavior. by staff with minimal movement for the entire Staff baseline.Staffbaselineconsistedofthree interval. Appropriate vocalizing was defined as phases: pretraining, training, and implementa- talking at or below conversational volume (i.e., tion. Consultants developed a token economy could not be heard from more than 3 m away). procedure prior to the pretraining phase and Datawerecollectedwithpaperandpencilusing measured the number of components complet- EFFECTS OF SELF-MONITORING 317 ed when staff participants addressed student iable in effect for students was the token engagement in academic readiness behavior as economy system as implemented by staff theyhadthroughouttheschoolyearpriortothe participants in each condition. start of research activities. Following pretrain- ing, the experimenters conducted the training RESULTS AND DISCUSSION phase, which consisted of two 1-hr training Figure 1 shows the percentage of token sessions and used procedures similar to those of economy steps implemented correctly across DiGennaro et al. (2007) to train staff partici- staff participants. Token economy implementa- pants to implement each item on the token tion did not occur during pretraining; the economy checklist. The first session involved combined procedural integrity for all staff was staff participants only and consisted of didactic 0%. During training, implementation, and self- review, modeling, and role play. The second monitoring, the mean percentage of token session involved staff and student participants. economy steps implemented correctly for all During the second training session, the exper- participantswas70%(range,45%to82%),45% imenter first modeled token economy imple- (range, 0% to 91%), and 84% (range, 45% to mentation with student participants and then 100%),respectively.Figure 2 showstherelation provided coaching and feedback to staff between levels of procedural integrity and participants who implemented the procedure. student behavior across experimental conditions Once a staff participant demonstrated proce- andparticipants.Meanengagementinacademic dural integrity of 80% for one token economy readiness behaviors during pretraining, training, session,coachingandfeedbackwereterminated, implementation, and self-monitoring was 25% and the staff participant implemented the (range, 20% to 40%), 95% (range, 80% to intervention independently. The implementa- 100%), 52% (range, 0% to 100%), and 89% tion phase continued for each staff participant (range, 20% to 100%), respectively. until procedural integrity was stable or down- The results suggest that self-monitoring can ward trending, and the experimenter and improve the implementation of a token econ- individualstaffparticipantcouldmeettoreview omy system in a public school setting. Consis- the self-monitoring procedure. tent with the findings of DiGennaro et al. Staff self-monitoring. Prior to beginning self- (2007), behavioral interventions were not monitoring, the experimenter met briefly with implemented accurately following initial train- each staff participant and explained the mon- ing. This investigation extends previous proce- itoring checklist, reviewed the token economy dural integrity research by demonstrating the procedure,andanswered anyquestions. During effectiveness of self-monitoring for increasing self-monitoring, staff participants continued to posttraining procedural integrity levels with implement the token economy and were minimal support provided by external agents. instructed to complete a token economy Future researchers should evaluate long-term checklist(identicaltothatoftheexperimenters) implementation while employing school per- following two token sessions of their choice sonnel (e.g., school psychologist) to collect eachday.Completedchecklistswereleftinafile self-monitoring data and evaluate procedural folderfor the experimenters to collect following integrity. observations. Although these results demonstrate positive Student conditions. Experimenters observed outcomes, some limitations should be consid- and recorded the occurrence or nonoccurrence ered. First, staff and student participants of academic readiness behavior during all demonstrated variability in responding follow- experimental conditions. The independent var- ing the introduction of self-monitoring proce- 318 JOSHUA B. PLAVNICK et al. Figure 1. The percentage of accurately completed token economy steps by each staff participant throughout all conditions. Phases in baseline are pretraining, training, and implementation, and the intervention condition is self- monitoring. dures. The cause of variability was unknown, nents as opposed to the overall procedural although procedural integrity may have been integrity within a token economy session. controlled by competing demands, and aca- Future researchers could isolate the effects of demic readiness behavior could have been individual components on student outcomes. controlled by the accurate or inaccurate imple- Second, Ingrid’s accelerating trend in procedur- mentation of specific token economy compo- al integrity during the implementation condi- EFFECTS OF SELF-MONITORING 319 Figure2. Thepercentageofintervalsstudentsengagedinacademicreadinessbehaviors duringcorresponding staff conditions. Phases in baseline are pretraining, training, and implementation, and the intervention condition is self- monitoring. tion suggests that an unknown variable con- efficacy of self-monitoring for supporting tributed to this increase. This may have been accurate token economy implementation in a due to observation of other educators imple- public school setting. In addition, student menting the procedure accurately or to practice participants demonstrated improvements in effectsovertheextendedbaselineperiod.Future academic readiness behaviors following the research could address this limitation by introduction of the token economy. The use examining the effects of observing accurate of self-management practices in school settings implementationonratesofproceduralintegrity. may be an effective and efficient approach to Despite these limitations, this investigation improve implementation of school-based inter- extends previous research by demonstrating the ventions. 320 JOSHUA B. PLAVNICK et al. REFERENCES Kazdin, A. E. (1982). Single-case research designs. New York:Oxford. Allen,S.J.,&Blackston,A.R.(2003).Trainingpreservice Najdowski,A.C.,Wallace,M.D.,Penrod,B.,Tarbox,J., teachers in collaborative problem solving: An inves- Reagon, K., & Higbee, T. S. (2008). Caregiver- tigationoftheimpactonteacherandstudentbehavior conducted experimental functional analyses of inap- change in real-world settings. School Psychology propriate mealtime behavior. Journal of Applied Quarterly,18,22–51. BehaviorAnalysis,41,459–465. DiGennaro, F. D., Martens, B. K., & Kleinman, A. E. Richman, G. S., Riordan, M. R., Reiss, M. L., Pyles, D. (2007). A comparison of performance feedback M., & Bailey, J. S. (1988). The effects of self- procedures on teachers’ treatment implementation monitoring and supervisor feedback on staff perfor- integrity and students’ inappropriate behavior in mance in a residential setting. Journal of Applied special education classrooms. Journal of Applied BehaviorAnalysis,21,401–409. BehaviorAnalysis,40,447–461. Seligson-Petscher, E., & Bailey, J. S. (2006). Effects of DiGennaro, F. D., Martens, B. K., & McIntyre, L. L. training, prompting, and self-monitoring on staff (2005). Increasing treatment integrity through nega- behavior in a classroom for students with disabil- tive reinforcement: Effects on teacher and student ities. Journal of Applied Behavior Analysis, 39, 215– behavior.School Psychology Review,34,220–231. 226. Hagermoser-Sanetti,L.M.,&Kratochwill,T.R.(2008). Treatment integrity in behavioral consultation: Mea- surement, promotion, and outcomes. International Received November 4,2008 Journal of Behavioral Consultation and Therapy, 4, Final acceptance August16,2009 95–114. Action Editor,Chris Ninness

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