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NASP Communiqué, Vol. 35, #1
September 2006

Research Reviews/Evaluating Intervention Outcomes

Using Single-Subject Research in the Practice of School Psychology

By Michelle Marchant, Tyler Renshaw & Ellie Young, NCSP

Associate Ed. note: In this issue (and occasionally in future issues), the Research Committee deviates from its typical two-column format of research reviews and outcome evaluation protocols to focus on a specific research paradigm.—Steve Landau

The ratio of school psychologists to students is continually improving, but far from ideal (Fagan & Wise, 2000). Recent estimates range from a high of 1:1816 (Thomas, 1999) to a low of 1:1500 (Bramlett, Murphy, Wallingsford, & Hall, 2002). National surveys have indicated that current practitioners spend 50% of their time on assessment, with only 20 to 35 % of their time immersed in intervention, consultation, and problem-solving processes with student problem behavior (Bramlet et al., 2002; Reschly & Wilson, 1995; Stinett, Havey, & Oehler-Stinett, 1994). The secondary beneficiaries of school psychologists’ services, (i.e., parents and school personnel for whom direct time and attention would be most helpful) are difficult to support due to time constraints. With new policy mandates, priorities for school psychologists tend to be focusing on positive learning and behavioral outcomes rather than lengthy assessment procedures.

Teachers often seek a school psychologist’s expertise regarding behavioral issues within the classroom: How can I improve the on-task behavior of my students? What can be done to help a student who cannot or will not follow classroom routines? Is it possible to motivate a student to work independently? Parents, on the other hand, are likely to approach school psychologists with a greater variety of behavioral concerns: What can I do to help my son play less aggressively with his siblings? Why does my daughter resist coming to school? How do I stop my child from engaging in self-injurious behavior? Confronted with these questions, school psychologists problem-solve by answering the following questions: How can this problem be solved most efficiently? What intervention will best meet the needs or the child and the adults involved with the child? How can I ensure the change in the student’s behavior will be significant and lasting? Considering practitioners’ previously mentioned time limitations, single-subject research designs can be helpful in identifying strategies to aid teams in finding and monitoring effective solutions.

Linking Needs With Research-Based Practices

The use of empirical research to design interventions, while not a new emphasis in the field of school psychology, is becoming prominent in the educational literature. In response to the federal No Child Left Behind Act of 2001, the United State Department of Education Institute of Education Sciences designed a user-friendly guide to assist educators to identify and implement educational practices supported by research (U.S. Department of Education, 2003). The intent of this guide is to reduce the common practice of using strategies that are merely popular among practitioners or other influential individuals within the educational arena, by providing tools to those who need “to distinguish intervention supported by scientifically-rigorous evidence from those which are not” (U.S. Department of Education, p. iii). This effort encourages practitioners to improve the services they provide to students by promoting carefully selected interventions that are supported by research.

Various research methodologies help school psychologists become “practitioner-researchers” who have acquired the skills to systematically evaluate their own practice and share their results with others. One research methodology is single-subject research methods and designs that are integrally connected to behavior-analytic theory (Tawney & Gast, 1984). What follows is a definition of single-subject research, along with its corresponding characteristics, techniques, and advantages, as well as techniques to effectively implement these principles within an educational setting.

Overview

Single-subject research emerged as a necessary product of Applied Behavior Analysis (ABA), a discipline aimed at understanding and improving maladaptive human behavior. Unlike other methodologies with similar intent, ABA accomplishes this by targeting only observable behaviors of social significance (Cooper, Heron, & Heward, 1987). ABA does not seek a complete analysis of a behavior—accounting for all possible contributions of a behavior’s cause—but rather an applied analysis. As referred to in the discipline’s name, applied connotes using isolated variables to obtain practical and meaningful change in behavior (Bailey & Burch, 2002); analysis implies that these variable effects on behavior are reliable and replicable (Cooper et al., 1987). In short, ABA requires more than an isolated incident of demonstrated causation; it demands establishment of a functional (or predictable) relationship between variable(s) and behavior. This relationship is achieved only through replication in which one variable (or a package of variables) is the only element (or elements) varying within experimental conditions (Tawney & Gast, 1984). Thus, single-subject designs arose as behavior analysts organized procedures to ensure verification of meaningful behavior change that contributes to academic and social success.

The following synopsis on behalf of the field of applied behavior analysis and its integration with research seems to nicely summarize the ideals of ABA and single-subject research:

“The field of applied behavior analysis stresses the study of socially important behavior that can be readily observed, and it uses research designs that demonstrate functional control usually at the level of the individual performer. The procedures developed by this field must be replicable, and the extent of the resulting behavior change must have important practical significance for the social community” (Bailey & Burch, 2002, p. 17).

Characteristics and Techniques of Single-Subject Research Designs

As presented above, the overarching purpose of applied behavior analysis or single-subject research is to improve the behavior of individuals (Cooper et al., 1987).  To be successful, the practitioner-researcher must adhere to designated characteristics associated with single-subject designs. These characteristics include repeated measures, baseline performance, intervention measures, and experimental control that will be described in more detail, along with their corresponding techniques.

Repeated Measures

The first step in the research process is identifying the problem behavior and its magnitude. This is done by collecting data daily, weekly, or even more frequently, and then placing the data on a graph where analysis can be easily done for all conditions including baseline and treatment.  To obtain valid data, the target behavior (dependent variable) must be defined in operational terms and then measured with sensitive and reliable methods (Alberto & Troutman, 2006; Tawney & Gast, 1984). In an example of single-subject research, Marchant and Young (2001) targeted and measured the compliant behavior of preschool-age children. A direct observation system was used to measure the operationalized definition of compliance that consisted of the child looking, saying “OK,” beginning the task within five seconds, and checking back with the person who gave the instruction. Specifically, event recording, making a notation to indicate if the behavior did or did not occur, was the data collection system of choice because the objective of this particular study was to increase a discrete behavior or compliance.

As the observers viewed the parent-child interaction, they attended to each step of compliance separately rather than as a collective behavior. To capture the behavior in detail, compliance was broken into the four steps mentioned above and data were collected separately for each step. If the child “looked” at the parent accurately, based on the designated definition, a “+” was placed in a box on the data collection form. The observers marked a “–” if eye contact did not occur or did not match the definition. This same process transpired for the remaining three steps of compliance. This provides an example of how single-subject research describes behavior in very finite components.

For this study, data were, on average, collected three times per week by independent observers in order to acquire the necessary repeated measures on the participants’ behavior. The observations occurred in the home when the parents were giving the child instructions to complete household chores. Typically, these instructions were dispensed at the same time for each session during late afternoon or evening. These data collection efforts supplied the researchers with sufficient repeated measures that could then be graphed and analyzed often in order to make data-based decisions. Ultimately, it is the repeated measures that contribute to making the study analytic.

Data were analyzed by first graphing the repeated measures immediately following the data collection session so that the data path was regularly updated. Next, it was critical that the practitioner-researcher consistently looked at the visual picture of the trend, level, and variability of the data and interpreted the updated outcomes to make informed decisions for the next research step. More information about these evaluation procedures will be discussed in the following section on baseline performance.

Baseline Performance

Graphic analysis. Baseline is the phase of the single-subject research design where the intervention is absent. Data are repeatedly collected and then graphed on the student’s target behavior in the pre-intervention conditions. This provides a visual description of the child’s behavior before application of the treatment (independent variable) begins. A key function of the baseline condition is for researchers to obtain the necessary repeated measures that allow for an analysis between the baseline and treatment conditions. Practitioners can use the single-subject research design methodology to validate interventions by graphing a child’s out-of-seat behavior, physical aggression, or sensory stimulation.

Prediction. Another function of baseline data collection is prediction. “Prediction may be defined as the anticipated outcome of a presently unknown or future measurement” (Johnston & Pennypacker (1980, p. 120). Alberto and Troutman (2006) compared the baseline to a pretest because it provides the bases from which the practitioner-researcher can project the effect of the planned intervention. For example, if a child has a high rate of physical aggression on the playground during the baseline phase, and the pattern is consistent, it is reasonable to predict that the aggression will continue if a suitable intervention is not put in place. Therefore, without an intervention, the practitioner-researcher can predict that the visual display of aggression will be highly similar from baseline to intervention.

In order to effectively project into the intervention phase, it is necessary for baseline data to be stable. Data that fall within a narrow range of values are considered stable, whereas, those that fall outside of this range are considered to show some degree of variability. High rates of variability indicate that the practitioner-researcher should investigate the possibility of confounding variables (uncontrolled environmental events or conditions, such as a change in the recess schedule), a poorly defined behavior, and/or complications with measurement procedures as possible threats to the lack of stability (Alberto & Troutman, 2006; Cooper et al., 1987).

Trend indicates the direction of the behavior and is another critical factor associated with stability of the performance of the behavior. Consider the following scenario that offers an example of the implications of trend in single-subject research: A student’s talk-outs increased in his math class. Specifically, the school psychologist and teacher captured data indicating that over five days the trend of the talk-outs was steadily ascending beginning at five per class for the first data point of baseline and eventually arriving at 20 for the final data point of baseline. In this scenario, the behavioral trend is moving in the appropriate direction for a baseline condition because the school psychologist and teacher desire to reduce the talk-outs during the treatment condition. If the talk-outs were to reverse into a descending trend, that would suggest the baseline is no longer stable and the intervention should not be applied until the trend is reversed. If the intervention is implemented while the trend is descending, it will be difficult to determine if the change in behavior is a function of intervention or other unidentified factors. Cooper et al. (1987) offered the following about a stable baseline: “Stable responding…enables the behavior analyst to employ a powerful form of inductive reasoning sometimes called baseline logic. Baseline logic…entails three elements: prediction, verification, and replication” (p. 154). To this point, we have discussed only one element, prediction. The second, verification, will be presented in the following section with the single subject design characteristic of “intervention.”

Intervention Measures—Experimental Control

Verification involves successfully demonstrating that when the independent variable is imposed on the dependent variable, the desired effect has occurred. For example, Marchant, Lindberg, Young, Fisher, and Solano (2004) demonstrated that a treatment package consisting of playground rules, supervision, positive reinforcement, and self-management reduced the playground aggression of three students. In this study, the desired outcome or reduction in playground aggression was observed, which was the first step toward verifying the prediction that the independent variable or intervention package produced a desirable outcome (Cooper et al, 1987). However, this temporary confirmation is purely the first step. Additional efforts must be made to solidify this assumption; otherwise, one could contend that a confounding variable was the source of changing the targeted behavior. Methods for solidifying this assumption are presented in the next section.

Replication establishes experimental control, an important component of single-subject research because it supports the baseline logic critical to demonstrating a functional relationship between the independent and dependent variables (Cooper et al., 1987). This strengthens the argument that the treatment is the variable most likely producing the desired change in the behavior. As previously discussed, replication is demonstrated by repeated measures within one condition, such as baseline and intervention. “Replication demonstrates the reliability and generality of data. It reduces the scientist’s margin of error and increases confidence that findings that withstand repeated test are real, not accidental” (Tawney & Gast, 1984, p. 95-96).

Experimental control, or replication, is best demonstrated using rigorous research designs that facilitate control over possible confounding variables (Alberto & Troutman, 2006). Options for rigorous, single-subject research designs include reversal, changing criterion, multiple baseline, and alternating treatment (Bailey & Burch, 2002; Cooper et al., 1987; Tawney & Gast, 1984). These designs provide a systematic structure for collecting and analyzing data so that the practitioner-researcher can make confident statements about the relationship between the independent and dependent variables (Alberto & Troutman, 2006). The following examples describe how practitioner-researchers and researchers attempted to establish experimental control and demonstrate a functional relationship between independent and dependent variables.

Multiple baseline design. In the Marchant and Young (2001) study, positive parenting skills were taught to the parents of children identified with antisocial behavior problems. The parents then used their training and skills to increase their children’s compliant behavior. A multiple baseline design across participants allowed the researchers to simultaneously investigate the replication of the intervention across four children’s compliant behavior. In this design, a stable baseline was achieved with the first child before the intervention was introduced, and baseline data collection continued for the remaining participants. Once the first participant was introduced to the intervention and stable data were achieved, the second participant received the treatment after his baseline data were stable. The same pattern continued with the third and fourth participants. Results of the replication across the four parent-child dyads suggested that the replication was successful due to the impact of the independent variable. This design also contributes to establishing a functional relationship between the parents’ implementation of the positive parenting skills (independent variable) and the child’s compliance (dependent variable). This study is an example of how a multiple-baseline-across-participants design allowed for verification and replication of the practitioner-researcher’s prediction that parenting skills could increase the child’s compliance.

Reversal design. Just as a multiple baseline design allows practitioner-researchers to establish experimental control for multiple variables, the reversal design is used to investigate the effectiveness of a single independent variable (Alberto & Troutman, 2006). Using the reversal design, Christensen, Young, and Marchant (2004) investigated a peer-mediated self-management strategy in assisting a student with behavior problems to develop both self-evaluation capabilities and appropriate social skills. Simply stated, when using the reversal design, an intervention is sequentially applied and then withdrawn with one participant.  In the Christensen et al. (2004) study, the peer-mediated self-management intervention was applied and then withdrawn with one student repeatedly while the practitioner-researcher, a behavior specialist in a local public school, oversaw the details of the research efforts to ensure experimental control. The results were favorable as the participant showed a significant increase in his level of socially appropriate classroom behavior during the treatment conditions when the self-management strategy was implemented. A functional relationship was clearly demonstrated across the independent (self-management) and dependent variables (externalizing behaviors).

We have shared two of the four possible single-subject research designs that permit practitioner-researchers to establish experimental control. These examples suggest that practitioner-researchers can successfully demonstrate experimental control by repeating an intervention several times and observing its effect on a dependent variable (Alberto & Troutman, 2006). For further information about each of these designs, it is recommended that the reader access the following texts: Applied Behavior Analysis for Teachers (Alberto & Troutman, 2006), Applied Behavior Analysis (Cooper et al., 1987), and Research Methods in Applied Behavior Analysis (Bailey & Burch, 2002). These texts offer straight-forward information about the field of Applied Behavior Analysis and strategies for effectively developing single-subject research designs.

Advantages of Single-Subject Research Designs

As indicated in the introduction, school psychologists answer questions about intervening with students’ problem behaviors. Experimental designs, such as the single-subject designs presented above, are helpful structures for use in school-based settings in drawing scientific conclusions about student behavior. Both single-subject and group designs can facilitate scientific options for determining evidence-based practices that will reliably evaluate student behavior change. Though both designs facilitate credible results, the type of conclusions derived from the results depends directly on design type.

Practicality. Group designs are formatted to evaluate the effectiveness of an intervention on the behavior of a population of students (e.g., school or class) or a representative sample of the desired population. Their conclusions, based on statistical procedures, are concerned with generalizing and inferring results to a larger group of interest. The inherent problem with this design approach is that it is seldom practical when seeking to improve individual or small group student behavior. Chances are slim that there will ever be a class in which every student presents with identical behavior problems. Comparatively, single-subject designs facilitate improving student behavior by evaluating the effects of variables on the specific behavior of a single student. In other words, “Single-subject designs emphasize the clinical significance of an individual rather than statistical significance among groups” (Alberto & Troutman, 2006, p. 121).

Establishing scientific rigor. Furthermore, single-subject research designs scientifically structure how questions are asked and how data are collected and analyzed, so that meaningful behavior change may be achieved, verified, and believable (Alberto and Troutman, 2006; Cooper et al., 1987). Unlike group designs, in which scientific rigor is concluded pre-study after proper selection of sampling, assignment, and statistical procedures, single-subject designs require that scientific rigor be continually established and calibrated throughout the entire research process. Scientific rigor is judged on three stringent criterions: (a) demonstration of a functional relationship, (b) achievement of clinically significant (or socially important) behavior change, and (c) approval of social validity (Alberto & Troutman, 2006). Scientific rigor can not be assumed or loosely attributed; it must be established by verifying the relationship between variables, and then it is watchfully maintained through the study’s completion. A functional relationship can be inferred only after a relationship has been successfully replicated. Clinically significant change in behavior is evaluated throughout the study and as the study nears completion. Social validity questions are considered pre-, during, and post- study. If scientific rigor is ultimately concluded at the study’s end, then consideration may be given to generalization of the results.

Generalization allows practitioner-researchers and researchers alike to export their results so that they are useful to others in the school community. Using repeated single-subject design studies, the successful intervention may be tested with varying students and behaviors. Thus, though single-subject research seeks first, and most importantly, for a meaningful change in behavior, it also supports the dissemination of evidence-based interventions that have been rigorously tested and proven to be generalizable under a range of circumstances. Practitioners can adopt these procedures with confidence and assume they will work due to the intensive process by which they were tried and found effective (Alberto & Troutman, 2006).

Implications for School Psychologists          

School psychologists who read and apply single-subject-research benefit from learning about carefully controlled intervention strategies that can be used to facilitate behavioral change for students. Single-subject research contributes to the practice of school psychology through identifying specific and detailed interventions and variables that influence change; it helps practitioners recognize the necessity of understanding the functional relationships between behaviors and outcomes. In addition, this type of research has strong internal validity so that there is little, and hopefully no, question about the relationship between dependent and independent variables.

While single-subject research is characterized by quite specific procedures and designs, some procedures may be cumbersome and time consuming for practitioners to replicate. Most practitioners do not have access to the extensive resources used for data collection and analysis in published studies. Furthermore, some designs require an effective intervention to be withdrawn in order to demonstrate that the intervention was effective, but doing so may not please teachers or parents who have witnessed desirable  behavioral change. Another concern arises when applying single-subject research in new settings because research environments, even field-based research settings, have very controlled environments and contingencies. This level of control may not be available in other settings. Furthermore, the target student described in the research may be quite different from the target student in a field-based setting. Reinforcement schedules or types of reinforcement may be distinct for each student, thus changing underlying and important principles which were imperative to the success of the studied intervention.

Even with these caveats, these designs are important for school psychologists to use competently in their work. Generalization of interventions can be easily done if the researcher carefully explained and demonstrated the functional relationship between the studied intervention and the outcome. If the intervention is tried in a new setting and with careful attention to baseline data, treatment integrity, and ongoing data collection and analysis, successful generalization can occur. Learning new strategies for intervention and understanding the environment variables that sustain behavioral change are two of the fundamental contributions of single-subject research for school psychology practice.

References

Alberto, P. A., & Troutman, A. C. (2006). Applied behavior analysis for teachers (7th ed.). Upper Saddle River, NJ: Pearson Education, Inc.

Bailey, J. S., & Burch, M. R. (2002). Research methods in applied behavior analysis. Thousand Oaks, CA: Sage Publications.

Bramlett, R. K., Murphy, J. J., Johnson, J., Wallingsford, L., & Hall, J. D. (2002). Contemporary practices in school psychology: A national survey of roles and referral problems. Psychology in the Schools, 39, 327-335.

Christensen, L., Young, K. R., & Marchant, M. (2004). The effects of a peer-mediated positive behavior support program on socially appropriate classroom behavior. Education and Treatment of Children, 27, 199-234.

Cooper, J. O., Heron, T. E., & Heward, W. L. (1987). Applied behavior analysis. Upper Saddle River, NJ: Pearson-Hall, Inc.

Fagan, T. K., & Wise, P. S. (2000). School psychology: Past, present, and future (2nd ed.). Bethesda, MD: National Association of School Psychologists.

Johnston, J. M., & Pennypacker, H. S. (1980). Strategies and tactics for human behavioral research. Hillsdale, NJ: Lawrence Erlbaum.

Marchant, M., Lindberg, J., Young, K. R., Fisher, A. K., & Solano, B. (2004, May). A treatment package for improving playground behavior among elementary students. Poster presented at the 30th Annual Convention for Applied Behavior Analysis, Boston, MA.

Marchant, M., & Young, K. R. (2001). The effects of a parent coach on parents’ acquisition and implementation of parenting skills. Education and Treatment of Children, 24(3), 351-373.

Reschly, D. J., & Wilson, M. S. (1995). School psychology practitioners and faculty: 1986 to 1991 – 1992—trends in demographics, roles, satisfaction, and system reform. School Psychology Review, 24, 62-80.

Stinett, T. A., Havey, J. M., & Oehler-Stinnet, J. (1994). Current test usage by practicing school psychologists: A national survey. Journal of Psychoeducational Assessment, 12, 331-350.

Tawney, J. W., & Gast, D. L. (1984). Single-subject research in special education. Columbus, OH: Merrill.

Thomas, A. (1999). School psychology 2000. NASP Communiqué, 28, 28.

U.S. Department of Education. (2003). Identifying and implementing educational practices supported by rigorous evidence: A user friendly guide. Washington, DC: Author. Washington, DC: Author.

© 2006, National Association of School Psychologists. Michelle Marchant, PhD, is an Assistant Professor in the Department of Counseling Psychology and Special Education at Brigham Young University. Tyler Renshaw is an undergraduate Psychology student at BYU who will graduate in April 2007, with plans for graduate school. Ellie L. Young, PhD, NCSP, is an Assistant Professor of School Psychology at BYU.