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ADHD symptom reduction in elementary students: a single-case effectiveness design.

The authors used a single-case design to examine the effectiveness of child-centered play therapy (CCPT) and person-centered teacher consultation (PCTC) for four elementary students identified with attention deficit hyperactivity disorder (ADHD) symptoms. Two students participated in CCPT and their teachers participated in PCTC. Two students participated in reading mentoring and CCPT. Behavioral observations of all students occurred three times per week. Results indicated that two students demonstrated a substantial reduction and two students demonstrated questionable reduction in ADHD symptoms due to participation in CCPT Implications for elementary school counselors are discussed.


Students exhibiting behavioral problems associated with attention deficit hyperactivity disorder (ADHD)--inattention, hyperactivity, and impulsivity--are a common concern of teachers, parents, and elementary school counselors (DuPaul & Stoner, 2003). In the classroom, students with ADHD exhibit significantly different behaviors than students without ADHD (Carroll et al., 2006). Students with ADHD are more talkative, two times more likely to display off-task behaviors, and three times more likely to be oppositional than students without ADHD (Carroll et al.). These off-task behaviors are disruptive in the classroom and can interfere with student learning (Mulrine, Prater, & Jenkins, 2008). Without early intervention, children with ADHD can experience negative long-term effects as adults, such as lower levels of education and more arrests (Barkley, Fischer, Smallish, & Fletcher, 2002). Because ADHD is the most common diagnosis of childhood (as cited in Woodard, 2006), it is imperative that elementary school counselors be aware of specific interventions they may use to help decrease the ADHD symptoms that negatively impact student learning. In this article, the authors review the results of a single-case design study examining the effectiveness of play therapy for elementary students with ADHD symptoms.


Play therapy developed out of the realization that traditional talk forms of counseling did not seem to be effective with young children due to their developmental levels and capabilities (LaBauve, Watts, & Kottman, 2001). Children under the age of 10 have not developed the cognitive and verbal abilities to participate fully in talk forms of counseling and instead their natural form of communication occurs through play (Landreth, 2002). Child-centered play therapy has its roots in adult person-centered counseling. A student of Carl Rogers, Virginia Axline, adapted the person-centered theoretical approach to her work with children. Axline (1947) believed that people of all ages have an innate drive toward maturity, independence, and self-direction; thus directing children in counseling would interfere with their natural tendency to grow. Like Rogers, Axline believed that development of the relationship provided the conditions for change. Garry Landreth expanded Axline's nondirective play therapy approach to formalize child-centered play therapy (CCPT).

For young students struggling with personal/ social issues, elementary school counselors can use CCPT. Although a comprehensive developmental guidance program prefers the referral of students with individual counseling issues to a counselor outside of school, many students cannot or will not access counseling outside of school. Therefore, elementary school counselors can utilize CCPT, which falls within the responsive services component of the ASCA National Model[R] (American School Counselor Association, 2005). Gysbers and Henderson (2006) recommended that elementary school counselors devote approximately 30-40% of their time providing responsive services, such as CCPT.

In their exploration of the effectiveness of CCPT in the school setting, researchers have demonstrated student improvement in self-efficacy, self-esteem, teacher relationships, and internalizing and externalizing behavioral problems (Fall, Balvanz, Johnson, & Nelson, 1999; Garza & Bratton, 2005; Packman & Bratton, 2003; Post, 1999; Ray, 2007). Bratton, Ray, Rhine, and Jones (2005) conducted a metaanalytic review of 93 studies examining the effectiveness of play therapy in a variety of settings. The meta-analysis revealed a mean effect size of .80 +/-0.04 (significantly greater than 0, p < .001), signifying a large treatment effect for children who participated in play therapy versus those who did not. Thirty-six of these studies were conducted in school settings. In comparison, the humanistic-nondirective therapies, such as CCPT, demonstrated a greater treatment effect than non-humanistic types (Bratton et al.).

Although meta-analysis and other studies have documented the effectiveness of play therapy in general and CCPT in particular, limited research exists regarding the effectiveness of CCPT for children with ADHD symptoms. Two case studies found mixed results: Hannah (1986) found that play therapy was effective in reducing behavioral problems, whereas Blinn (1999) found that play therapy was not effective. However, both studies contained many limitations that most likely affected the accuracy of the results. In a more recent study, Ray, Schottelkorb, and Tsai (2007) investigated the effectiveness of play therapy for children with ADHD behavioral problems. Sixty elementary students identified with clinical levels of ADHD behavioral problems were randomly assigned either to 16 thirty-minute sessions of CCPT or reading mentoring. The researchers found that children in both groups demonstrated improvement at statistically significant levels on the ADHD Index score of the Conners' Teacher Rating Scale-Revised: Short Form (CTRS-R:S), indicating an overall decrease in ADHD symptoms. In addition, children in the CCPT group demonstrated statistically significant improvement over children who participated in reading mentoring in reduction of anxiety/withdrawal symptoms and emotional lability. A thorough review of the professional literature indicates a need for empirical research on the effectiveness of CCPT for children with ADHD symptoms.


As an adjunct to play therapy and other forms of child counseling, elementary school counselors often use teacher consultation to assist with a student's problematic behaviors at school. ASCA (2005) defined consultation as a way to assist parents, guardians, teachers, other educators, and community agencies in strategies to help students and families. Consultation is an area that falls within two delivery systems of the school counselor: responsive services and system support (ASCA). In their survey of school counselors, Perera-Diltz and Mason (2008) found that 97% of elementary school counselors provide consultation to parents, teachers, and others within the responsive services component of the ASCA National Model. In this survey, elementary school counselors ranked consultation as the duty they perform more than any other. Thus, consultation is considered an important role of the elementary school counselor. However, limited training in consultation is provided to school counselors and limited research exists in this area (Peterson, 2007).

In an examination of teacher consultation literature, it is evident that many types of consultation are used in the schools, such as behavioral, solution-focused, developmental, Adlerian, and person-centered (Busse, Kratochwill, & Elliott, 1999; Clemens, 2007; Kahn, 2000; Kampwirth, 1987; Marchant, 1972; Ray, 2007). In her research of person-centered teacher consultation (PCTC), Ray found that eight sessions of once-weekly 10-minute PCTC, in which the counselor provided the teachers a relationship of empathy, congruence, and unconditional positive regard, helped decrease teaching stress at a significant level. Thus, Ray concluded that PCTC sessions can be helpful in decreasing teaching stress, which can improve the student-teacher relationship.


Elementary school counselors are expected to provide responsive services to students to assist them in attaining their educational goals. Because ADHD behaviors hinder student learning, it is important for elementary school counselors to intervene with evidence-based interventions. The literature demonstrates that CCPT is an effective intervention for many children with varying behavioral difficulties, but limited research exists in its effectiveness for children with ADHD symptomology. Although PCTC has limited effectiveness data, the authors wished to use this form of teacher consultation as it is theoretically consistent with the CCPT intervention. Thus, the purpose of this study was to examine the effectiveness of CCPT and PCTC for children with ADHD symptoms. The following research question guided this study: "Does CCPT alone or CCPT with PCTC decrease the ADHD symptoms of elementary students as rated by trained observers?"


Division 53 of the American Psychological Association (n.d.) has endorsed two types of research designs necessary for researchers to use when determining evidence-based interventions for children: between-group and single-case designs. In recent years, several counseling researchers have called on counselors to utilize single-case design methodology in their work with clients (Morgan & Morgan, 2003; Sharpley, 2007). Morgan and Morgan stated that single-case design is the best type of research to use when trying to explain individual behavior changes, which is useful in examining the effectiveness of counseling interventions. Thus, in the present study, the authors used a single-case design to investigate the effectiveness of CCPT and PCTC for four elementary students identified with ADHD behavioral symptoms. In both CCPT and PCTC, the relationship provides the conditions for student change. Therefore, the authors hypothesized that children who participated in CCPT alone and CCPT with PCTC would demonstrate a decrease in their ADHD symptoms.


This research study was part of a larger experimental research project examining CCPT with children labeled with ADHD problems. Participants for the larger study were recruited from four elementary schools in the Southwestern United States. The authors asked the school counselor at each school to solicit referrals from teachers for students in kindergarten through fifth grade identified with ADHD symptoms in the classroom. These behaviors were defined as those typically associated with ADHD: inattentive, hyperactive, and impulsive. Once parent consent was attained, all teachers who referred students for the larger study completed two assessments: the Teacher Rating Form (TRF; Achenbach & Rescorla, 2001) and the CTRS-R:S (Conners, 2001). Six students qualified for this study based upon their borderline or clinical scores on both the ADHD subscale of the TRY and their borderline or clinical scores on the ADHD Index score of the CTRS-R:S. Because comorbid conditions are common for children with ADHD (Kronenberger & Meyer, 2001; Pfiffner & McBurnett, 2006), students with clinical scores in other areas on the TRY were not included in this study to reduce the likelihood that comorbid factors contributed to their ADHD symptoms. Over the course of the study, 1 student participant moved to a new school district and another student was dropped from analysis due to the prescription of ADHD medication during the study. Therefore, only 4 participants are reviewed in this article. Of the 4 participants, 1 had received a formal diagnosis of ADHD and none took ADHD medication at any time throughout this study. The participants' names were changed to protect their confidentiality.


Direct Observation Form. The Direct Observation Form (DOF; Achenbach & Rescorla, 2001) is a 10-minute observation in which a trained observer examines the behavior of an identified student within a group, classroom, or recess setting and rates the student at each minute interval for on- and off-task behavior. After the observation period, the observer completes a checklist of 96 problem items rated on a scale of 0 (behavior not observed) to 3 (definite occurrence with severe intensity or occurrence lasting more than 3 minutes in duration). Achenbach and Rescorla recommended that three to six 10-minute observations be averaged together in order to obtain a more representative score of the child's on-task behavior. Four studies have examined the reliability and validity of the DOF (Achenbach & Rescorla). For these four studies, the mean interrater reliability was calculated at .84 for the on-task/offtask score.

For this study, the authors used the DOF three times per week to assess student on-task behavior. Although the DOF provides scores in on- and offtask behavior, internalizing and externalizing behavior, total problems, and six syndrome scales, only the on/off-task portion of the DOF was analyzed in this study. Two observers provided all of the DOF observations in this study. Each observer conducted two of the three weekly observation periods prior to noon and one observation period occurred in the afternoon, as recommended by Achenbach and Rescorla. Each observer assessed the same two students through the entire study. One observer was the first author, an advanced doctoral student in counselor education and a former school counselor. The second observer was the second author, a counselor education faculty member with 18 years of professional experience working in school and community settings. Interrater reliability was calculated using a frequency-ratio approach (also known as a total agreement approach). The researchers averaged all of the observations between both observers and found 97% agreement on the on/off task portion of the DOF. Kennedy (2005) stated that a minimum agreement of 80% is expected. Therefore, for purposes of this study, the observers achieved a high level of consistency.

Conners' Teacher Rating Scale-Revised: Short Form. The CTRS-R:S is an assessment completed by teachers to assess problematic behaviors of children and adolescents most commonly associated with ADHD. The CTRS-R:S was normed to be used with children between the age of 3 and 17 years. The CTRS-R:S consists of 28 questions that are rated on a 4-point frequency scale (0 = never, 3 = very often). Angello et al. (2003) recommended the short versions of the Conners' assessments for screening and treatment monitoring for children with ADHD. The CTRS-R:S provides four subscales: oppositional, cognitive problems/inattention, hyperactivity, and an ADHD Index score. Conners (2001) stated that the ADHD Index score is the best indicator of attention difficulties associated with a diagnosis of ADHD. Tests of internal consistency and test-retest reliability for the CTRS-R:S are high (Conners). The internal consistency coefficients for the CTRS-R:S ranged from the mid .80s to the mid .90s and test-retest reliability coefficients ranged from the .60s to the .90s. For purposes of this study, the CTRS-R:S was used only for identification of students with ADHD symptoms: students with inattentive, hyperactive, and impulsive behaviors.

Teacher Report Form. The Teacher Report Form (Achenbach & Rescorla, 2001) has 118 problem items and additional questions that require teachers to rate a student's academic performance and behavior compared to classmates. For the problem items, the student's behavior is rated on a 3-point scale (0 = not true, 2 = very true or often) based on what the teacher has observed during the previous 2 months (McConaughy, Kay, & Fitzgerald, 1998). The TRF provides adaptive scores, problem scores, and DSM-oriented scores. Achenbach and Rescorla reported adequate internal consistency for the TRF: an alpha of .90 for the total adaptive scale; for the problem scales, alphas of .72 to .95; and for the DSM-oriented scales, alphas ranging from .73 to .94. The test-retest reliability for the TRF was high and scaled scores were fairly stable. For purposes of this study, the authors used the TRF only to identify students who qualified for participation in this study--which required clinical or borderline scores on the ADHD problems subscale.


In order to prevent the authors, who conducted the DOF observations, from knowing the treatment the students were receiving, a doctoral student not involved in data collection assigned students to the treatment groups. These students were randomly assigned to child-centered play therapy (with or without person-centered teacher consultation) or reading mentoring. Reading mentoring was used as an alternate condition to prevent the observers from knowing the treatment condition in which the participants were involved. Although originally the authors intended for all students to participate in either CCPT (with or without PCTC) or reading mentoring, due to teacher requests for additional help with escalating inappropriate behaviors from the participating students and because of the flexible nature of single-case design, which allows for intervention changes as needed (Kennedy, 2005), two students switched from reading mentoring to the CCPT intervention. Table 1 illustrates each participant's individualized treatment.

Child-centered play therapy. In this study, two child-centered play therapists provided play therapy for all of the participants. To prevent biased observational results, the authors were not utilized as the play therapists. Instead, the authors selected two child-centered play therapists with extensive training, knowledge, and experience in CCPT. One play therapist had her Ph.D. in counselor education with a specialty in play therapy. The second play therapist was an advanced doctoral student in counselor education earning her specialty in play therapy. Both play therapists had participated in and received supervision on their skills in a minimum of five child-centered play therapy courses. The two child-centered play therapists incorporated both nonverbal and verbal skills as identified by Ray (2004) in their play therapy sessions. For purposes of protocol integrity, after the study was completed, the first author observed 10-minute segments of two sessions from both play therapists. The first author randomly selected these sessions and then rated the therapists using the Play Therapy Skills Checklist (Ray). Results indicated that appropriate levels of nonverbal responses were used (such as appearing interested in the child, relaxed and comfortable in the playroom, and using tone and expression congruent with the child's affect). Additionally, both therapists used appropriate verbal responses to communicate understanding to the child (such as tracking behavior, reflecting content and feeling, facilitating responsibility/creativity, and enlarging the meaning of the play).

All play therapy sessions were conducted in playrooms set up in school. Both playrooms were set up with toys recommended by Landreth (2002). One playroom was set up in an office space adjacent to the library and the second playroom was in a portable classroom outside of the school building. All students who received play therapy left their classroom during the school day to participate in the 30-minute sessions. All play sessions occurred twice weekly, and students left the classroom during times that worked with the teacher's instructional schedule.

Person-centered teacher consultation. One advanced doctoral student trained in the PCTC model of consultation was utilized in this study. This consultant provided the core conditions required of person-centered counseling: unconditional positive regard, genuineness, and empathy. Additionally, this consultant was trained in person-centered counseling skills of content and feeling reflection, encouragement, confrontation, and enlarging the meaning. For this study, two teachers participated in six 10-minute consultation sessions. These consultation times occurred one time per week during which the teacher had no other classroom responsibilities.

Reading mentoring. For this study, two children participated in individual reading mentoring sessions. Reading mentoring was used in this study to reduce the possibility of biased observational results: The observers were blind to the intervention the child received. Additionally, reading mentoring served as an intervention for students for whom the teachers and administrators were concerned. Reading mentors were two undergraduate students who met twice weekly with the identified student participants for 30 minutes each time. During these 30-minute sessions, one of two options occurred: Reading mentors read books of their choosing to the student or the student read to the mentor. Each reading mentor acquired the student participant from the classroom during times the teacher deemed appropriate and would read with the child in a school hallway.

Data Analysis

Observational data using the DOF were gathered by the authors throughout the course of the baseline, intervention, and post-intervention phases. A baseline phase of 3 weeks was utilized because a minimum of 3 data points is considered adequate for a baseline (Kennedy, 2005) and because these students' teachers strongly requested the intervention begin. These teachers were struggling with the students' ADHD behaviors in the classroom; thus it was not practical to extend the baseline period.

Researchers assess single-case data primarily through visual analysis (Morgan & Morgan, 2003). Kennedy (2005) argued that the use of inferential statistics for single-case data is inappropriate because the statistical assumptions do not match those of single-case designs. Morgan and Morgan (2009) stated that the use of a quantitative statistical measure of change, in addition to the visual analysis, is the best way to analyze single-case data. Thus, in this study, visual analysis and the calculation of the percentage of non-overlapping data (PND) statistic are the means through which all data were analyzed. In visual analysis, researchers graph and compare all of the data points for each of the specific phases. Specifically, Kennedy explained that the single-case researcher should examine the level, trend, and variability of the data within each phase. The level of each phase is the mean; the trend is the slope (incline) and magnitude (degree of the slope) of the data within each phase; the variability of the data is the degree of difference between the trend and each data point.

For the quantitative analysis of the data in this study, the authors used the PND statistic because it is one of the most utilized methods of analyzing single-case data (Morgan & Morgan, 2009). In addition, this analysis is straightforward and thus a practical option for school counselors to use. When calculating the PND statistic, one calculates the percentage of data in treatment phases that overlap with the highest or lowest data point during the baseline phase (Morgan & Morgan). To determine whether the highest or lowest data point is used for analysis depends on the goal of the intervention utilized. In this study, for example, the goal of the treatment was to increase on-task behavior in the classroom, thus the highest data point in the baseline would be used for analysis. In this analysis, the authors drew a line extending from the highest baseline data point of each participant through the treatment phases (see Figures 1 to 4). Any points that were a higher numerical value than the highest baseline data point were added and divided by the total number of data points in that phase. This percentage calculation provided the authors an effect size statistic to determine treatment effectiveness. Scruggs and Mastropieri (1998) determined that a PND equal to or greater than 90% indicates a "very effective" treatment, a PND of 70-90% is "effective," 50-70% indicates "questionable" effectiveness, and less than 50% is "ineffective."


Participant 1

John, a 5-year-old Caucasian male, was in kindergarten during this study. John qualified for this study based on his teacher's evaluation of his behaviors to be at clinical levels in difficulty completing tasks, sitting still, and paying attention on the TRF and the CTRS-R:S. John participated in 3 weeks of no-intervention baseline (Phase 1), 6 weeks of twice-weekly CCPT (Phase 2), 6 weeks of continued CCPT while his teacher participated in 6 weeks of once-weekly PCTC (Phase 3), and 3 weeks of a nointervention follow-up (Phase 4). Figure 1 displays the results of the behavioral observations.


In the graphical analysis of the DOF scores for John, the authors found the level (mean) of each phase increased over time: in Phase 1, the level was 6.0; in Phase 2, the level was 6.42; in Phase 3, the level was 7.08; and in Phase 4, the level was 7.33. The increase in level indicated that over time, John's on-task behavior in the classroom increased. Although this increase in on-task behavior indicated change, visual analysis indicated a moderate upward trend and a moderate amount of variability. Because visual analysis alone does not make clear the effectiveness of the interventions for John, the PND statistic was calculated. The highest data point in the baseline was 6.5. This numerical value was used for comparison with the first treatment phase (CCPT only), the second treatment phase (CCPT and PCTC), and the no-intervention follow-up phase. In the CCPT-only phase, the PND was 33%, which indicates the CCPT was ineffective in improving ontask behaviors in the classroom. In the second treatment phase (continued twice-weekly CCPT sessions and once-weekly PCTC), the PND was 50%, which indicates the interventions were "questionable" in improving on-task behaviors. In the 3-week followup period in which no intervention took place, John's PND was 67%. Thus, John's on-task behavior was continuing to maintain questionable effectiveness from the prior phase.

Participant 2

Jorge, a 6-year-old Brazilian-American male, was in first grade at the time of this study. Jorge was referred for participation for inattentive and immature behaviors--such as thumb sucking and hair twirling--by his classroom teacher. Jorge qualified for this study based on his mildly atypical score on the ADHD Index of the CTRS-R:S and the borderline score on the ADHD problems subscale of the TRF. Jorge's father indicated that the family was from Brazil but moved to the United States 2 years before the start of this study. Jorge's father reported that Jorge was able to speak both English and Portuguese, speaking primarily Portuguese at home and English at school.

Following 3 weeks of baseline, Jorge participated in 7 weeks of twice-weekly reading mentoring, 7 weeks of twice-weekly CCPT, and 3 weeks of nointervention follow-up. Although he was not originally intended to participate in CCPT, after many weeks of his participating in reading mentoring, his teacher became discouraged with Jorge's continued inattentive behaviors in the classroom. Unbeknownst to the authors, Jorge's school counselor spoke with the research assistant, who then switched Jorge to CCPT after 7 weeks of reading mentoring.


Figure 2 provides a graphical representation of the observed scores for Jorge's on-task behavior across all phases of the study. From the graphical analysis, it is evident that the level of each phase did not increase from baseline to the second phase. The level did increase in Phases 3 and 4, however. In Phase 1, the level was 6.17; in Phase 2, the level was 6.14; in Phase 3, the level was 6.93; and in Phase 4, the level was 7.67. Thus, there was no change from baseline to reading, but there was a level increase during the play therapy and follow-up phases. When examining the trend line of all phases for Jorge, a moderate upward trend is indicated. Jorge's behavior demonstrated a moderate amount of variability.

Beyond visual analysis, the authors calculated the PND statistic for each phase to determine the effectiveness of each phase's intervention(s). For Jorge, the highest data point in the baseline was 7. This numerical value was used for comparison with the first treatment phase (reading mentoring), the second treatment phase (CCPT only), and the nointervention follow-up phase. In the reading mentoring phase, the PND was 14%, which indicates reading mentoring was ineffective in improving ontask behaviors in the classroom. In the second treatment phase (CCPT only), the PND was 43%, which indicates the intervention was ineffective in improving on-task behaviors. In the 3-week follow-up period in which no intervention took place, Jorge's PND was 67%. Thus, Jorge's on-task behavior improved slightly, at a rate considered "questionable" in effectiveness.

Participant 3

Lee was a 6-year-old Caucasian male in first grade. He was referred for participation by his teacher due to his disruptive behaviors, shortened attention span, and distractibility. Lee qualified for this study because of his clinical score on the ADHD problems subscale of the TRF and mildly atypical score on the ADHD Index of the CTRS-R:S. Following 3 weeks of baseline, Lee participated in 6 weeks of twiceweekly play therapy (Phase 2), followed by 6 weeks of continued play therapy and weekly teacher consultation (Phase 3), and 3 weeks of a no-intervention follow-up period.

In the graphical analysis of Lee's on-task behaviors (see Figure 3), it is evident that behavior change occurred over the course of the study. In Phase 1, the level was 3.83; in Phase 2, the level was 6.0; in Phase 3, the level was 7.5; and in the final phase, the level was 7.0. The increase in the level from Phases 1 to 2 and from Phases 2 to 3 indicated an increase in Lee's on-task behavior in the classroom during participation in CCPT. The trend of Lee's on-task behaviors can be described qualitatively as having moderate variability and a moderate upward trend.

To provide a quantitative examination of the effectiveness of the interventions for Lee, the PND statistic was calculated. Lee's highest data point in the baseline was 5. This numerical value was used for comparison with the first treatment phase (CCPT only), the second treatment phase (CCPT and PCTC), and the no-intervention follow-up phase. In the CCPT-only phase, the PND was 67%, which indicates the CCPT was questionable in improving Lee's on-task behaviors in the classroom. In the second treatment phase (continued twice-weekly CCPT sessions and once-weekly PCTC), the PND was 100%, which indicates the interventions were "very effective" in improving Lee's on-task behaviors. In the 3-week follow-up period in which no intervention took place, Lee's PND was 67%. Thus, Lee's on-task behavior was maintaining questionable effectiveness from the prior phase.


Participant 4

Carlos was a 10-year-old Hispanic male in fifth grade. Carlos was identified by his teacher for participation due to his difficulty sitting still, focusing, and paying attention in the classroom. His teacher rated Carlos with clinical scores on the ADHD Index of the CTRS-R:S and the ADHD problems subscale of the TRF. Carlos participated in 3 weeks of baseline, 6 weeks of reading mentoring, 7 weeks of CCPT, and 3 weeks of baseline. The authors intended for Carlos to participate in reading mentoring throughout the entire study. However, because Carlos' teacher expressed concern regarding Carlos' declining behavior to the school counselor midway through the study, the doctoral student who acted as coordinator of the research project placed Carlos in CCPT for 7 weeks, unbeknownst to the observers.

Figure 4 displays the data from all phases of Carlos' participation in this study. The graph makes evident that the level of each phase increases over time, particularly in Phase 3, the play therapy phase. More specifically, in Phase 1, the level was 3.83; in Phase 2, the level was 4.25; in Phase 3, the level was 8.14; and in the final phase, the level was 9.83. The phase change from the baseline to the reading mentoring phase is minimal; however, a large shift in ontask behavior for Carlos occurred during the play therapy phase (Phase 3). The trend line indicated a high magnitude, upward trend over time, with a moderate amount of variability across all phases.

To supplement the visual analysis of Carlos' data, the PND statistic was calculated. The highest data point in the baseline was 5.5. This numerical value was used for comparison with the first treatment phase (reading mentoring), the second treatment phase (CCPT only), and the no-intervention followup phase. In the reading mentoring phase, the PND was 0%, which indicates the reading mentoring was ineffective in improving on-task behaviors in the classroom. In the second treatment phase (CCPT only), the PND was 86%, which indicates the CCPT intervention was "effective" in improving Carlos' on-task behaviors. In the 3-week follow-up period in which no intervention took place, Carlos' PND was 100%. Thus, Carlos' on-task behavior was continuing to maintain effectiveness from the prior phase.


When reviewing the observational results of each child, it is evident that two children showed clear change during participation in play therapy (Lee and Carlos). Lee's on-task behavior decreased during the no-intervention baseline. However, once play therapy began, Lee's on-task behavior improved steadily and significantly over time. For Carlos, the baseline and reading mentoring phases demonstrated a low level of on-task behavior. Once the play therapy intervention began, Carlos' on-task behavior improved significantly. This improvement in on-task behavior remained after the play therapy intervention ended. Results indicated that play therapy demonstrated effective to very effective results during or following treatment.


While two students' on-task behaviors improved at clear and significant levels, the observational data of two students were not clear in providing considerable improvement in their ADHD behaviors (John and Jorge). For John, the observational data indicate that his on-task behavior improved slightly over time. John's baseline data were not stable, which also makes conclusions about the results more difficult to ascertain. For Jorge, the observational data indicate that his on-task behaviors did not change during the reading intervention but improved slightly during the CCPT intervention phase. The most improvement in on-task behavior was observed during the follow-up phase during which no intervention occurred. However, for both John and Jorge, participation in play therapy demonstrated some positive change that led to promising questionable effectiveness of intervention.

When reviewing all four students, it was evident that the reading intervention was ineffective for improving on-task behaviors. CCPT did not appear to effect significant change for students who participated in only 12 sessions; however, the more sessions these students had, the more improvement occurred in their on-task behaviors. This finding supports the research of Ray (2008), who found that statistically significant behavioral change for children participating in CCPT occurred when children participated in more than 11 sessions of CCPT.

In answering the original research question, the authors conclude that CCPT alone and CCPT with PCTC were clearly helpful in decreasing ADHD symptoms for two children and were questionably effective in reducing ADHD symptoms for two children. Of the two students who participated in CCPT with PCTC (Lee and John), Lee was the student who showed a clear decrease in ADHD symptoms. Of the two students who participated in CCPT alone (Carlos and Jorge), Carlos showed a clear decrease in ADHD symptoms. Due to the nature of our design, it is difficult to report if the addition of PCTC made a significant impact on the ADHD symptoms of students. Overall, the authors conclude that CCPT can be helpful for children with ADHD symptoms.

Parent and Teacher Observations

The first author reviewed all observational results with parents and teachers at the end of the study. During those meetings, some information was shared that could explain the off-task behaviors of some of the students. The teachers of Carlos and Jorge both indicated concern with possible learning problems by the end of the study. Lee's father shared that he separated and then divorced Lee's mother during the course of the study. The authors speculate that these learning problems and life changes could explain the inattentive, off-task behaviors of these students rather than ADHD. This information fits with previous research that ADHD symptoms may be associated not with ADHD, but with other problems, such as trauma, stress, learning disabilities, and mood/anxiety disorders (Furman, 2005; Kronenberger & Meyer, 2001; Pfiffner & McBurnett, 2006). The parent and teacher observational information that the authors gathered as a part of this study was important in understanding the findings. Without this qualitative component of single-case design, the authors would have missed crucial information that assisted them in analyzing the results.

Limitations and Recommendations for Future Research

In the assessment of ADHD in children, teachers' ratings are considered one of the most important and most utilized methods (Loughran, 2003). Thus, the authors chose to identify children for participation in this study through teacher assessment. However, a stronger method of identifying students with ADHD symptoms would be through use of an additional rater, such as parents, and perhaps an additional source of information, such as a structured interview. The manner of identifying children with ADHD behavioral problems solely with teacher report on two instruments was a limitation of the study. Future research could utilize multiple sources of information in order to diagnose participants with ADHD prior to using the CCPT intervention.

The design of this study was an additional limitation. Although single-case design can provide the level of experimental control equal to that of larger between-group designs (Kennedy, 2005), in the real world setting of schools, this may be difficult to achieve. In single-case design, experimental control is achieved through establishment of a stable baseline, from which any changes in behavior can be explained as being due to the intervention used in treatment phases (Kennedy). However, in this study, the authors were unable to provide a lengthy baseline due to the needs of the school, and therefore a stable baseline was not established with every student. Future single-case research should seek to attain this stable baseline.

Another limitation and implication for future research regarding single-case design is the use of various interventions and a follow-up period of assessment. Due to the likelihood of carry-over effects from one phase to the next in counseling research, the authors discourage the use of additional intervention phases. In this study, it is impossible to rule out the cumulative effect of play therapy from Phases 2 to 3. Thus, when teacher consultation was used concomitantly with play therapy, it is difficult to determine what intervention is contributing to behavior change. Future studies investigating the effectiveness of counseling interventions, such as CCPT, should seek to only have one intervention per phase.


The results of this study provide several implications for elementary school counselors. First, it does appear that CCPT can be helpful for children with ADHD symptoms. Two students demonstrated noteworthy improvement in their ADHD symptoms during CCPT and two students demonstrated a questionable level of change for on-task behavior. This study supports the findings of Ray et al. (2007), in which CCPT was effective in reducing ADHD symptoms for elementary students. Thus, elementary school counselors may wish to use CCPT for children with ADHD symptoms.

The results indicated that children with ADHD symptoms may need more than 12 CCPT sessions to demonstrate improvement in their on-task behaviors. None of the students demonstrated a clear change in treatment after 12 sessions. This finding supports Ray (2008), who found that more than 11 CCPT sessions were needed to demonstrate significant behavioral change. An elementary school counselor might need to assess the benefits versus limitations of offering an individual intervention to a student for longer than 12 sessions.

Another implication for elementary school counselors is to consider gathering multiple sources of data when trying to determine an intervention to use for students with ADHD symptoms. As was evident in this study, students qualified for participation due to their clinical or borderline levels of ADHD behaviors that are associated with an ADHD diagnosis. However, as was discovered through the course of the study, several of the students experienced life events (e.g., parental separation and divorce) or learning difficulties that may have influenced their behaviors. The authors propose that life events and learning problems may have been evidenced through ADHD symptoms. Thus, when elementary school counselors work with students who have ADHD symptoms, it is important to gather information from a variety of sources to determine if additional and/or alternate interventions (e.g., referral for testing for learning problems) may be appropriate.

The design of this study provides yet another implication for elementary school counselors. The ASCA National Model encourages school counselors to provide effectiveness data and share this information with stakeholders (ASCA, 2005). Single-case design research is one way that school counselors can provide this effectiveness data. Elementary school counselors can incorporate a single-case experiment for one or more students with whom they want to assess change. The authors encourage school counselors to attempt to secure a stable baseline and to provide only one intervention per phase to provide a higher level of experimental control. One possible method that school counselors could use to secure a stable baseline is to increase the number of observations to one per day or several per day instead of three per week as was utilized in this study. School counselors could develop their own observational tool or could use a standardized instrument to assess student change.


Researchers have identified ADHD as one of the most common disorders of childhood (as cited in Woodard, 2006), and thus ADHD affects the lives of countless children, families, and teachers every day. Because elementary school counselors work with students, many of whom will be impacted by ADHD, it is important that they know how to use interventions that can help these students be more successful in school. This study demonstrated that elementary school counselors can utilize CCPT to help students decrease their ADHD symptoms. The authors suggest that future research investigating the effectiveness of CCPT for students with ADHD symptoms is needed.


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April A. Schottelkorb, Ph.D., is an assistant professor of counselor education at Boise State University, Boise, ID. E-mail: aprilschottelkorb@ Dee C. Ray, Ph.D., is an assistant professor of counselor education at the University of North Texas, Denton.
Table 1. Participants' Treatments

 CCPT PCTC Reading
Participant Grade Sessions Sessions Mentoring

John K 24 6 0
Jorge 1 14 0 14
Lee 1 24 6 0
Carlos 5 14 0 12

Note. CCPT = child-centered play therapy; PCTC = person-centered
teacher consultation.
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Title Annotation:attention deficit hyperactivity disorder
Author:Schottelkorb, April A.; Ray, Dee C.
Publication:Professional School Counseling
Article Type:Report
Geographic Code:1USA
Date:Oct 1, 2009
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