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School Psychology Review
1998, Vol. 27, No. 2, pp. 290-303
GENERAL ARTICLES
Reducing Disruptive Behavior
in General Education Classrooms:
The Use of Self-Management Strategies
Kathryn E. Hoff and George J. DuPaul
Lehigh University
Abstract= The use of a self-management strategy in a general education classroom to decrease
the disruptive behavior of three elementary school students with ADHD or ODD was
investigated. A multiple-probe design was used to assess the effects of the intervention in
both structured and unstructured settings. Results indicated that the self-management
intervention led to decreases in disruptive behavior, which was maintained in the absence
of the teacher. These data add to the existing literature suggesting self-management as a
viable alternative to traditional contingency management approaches. Implications for
research and practice are discussed.
Children displaying a high degree of conduct
problems and aggression are at greater risk for
later antisocial behavior and psychiatric disorders
as adolescents (Coie, Lochman, Terry, & Hyman,
1992; Kupersmidt & Coie, 1990; Loeber, 1990).
For example, childhood disruptive behavior such
as aggression can lead to later delinquency
(Kupersmidt & Coie, 1990; Loeber & Dishion,
1983; Loeber & Stouthamer-Loeber, 1987;
Parker & Asher, 1987), school dropout, substance
use, school maladjustment (Kandal, 1982;
Kupersmidt & Coie, 1990; Kupersmidt &
Patterson, 1991), and peer rejection (Coie,
Dodge, & Kupersmidt, 1990).
Children with both attention deficit hyper-
activity disorder (ADHD) and aggression also
have displayed more problematic behavior such
as peer rejection (Milich & Landau, 1989), lying,
and stealing than children who are only
aggressive or merely ADHD (see Hinshaw, 199 1
for review; Walker, Lahey, Hynd, & Frame,
1987). It also is estimated that as many as 45%
of children with ADHD may progress to conduct
disorder (CD) (Barkley, 1990), and hyperactivity
was found to be a catalyst for the continuance of
conduct problems (Abikoff & Klein, 1992). A
developmental model outlined by Lahey and
Loeber (1994) empirically demonstrates a
progression from oppositional behavior to
intermediate CD and then advanced CD with
children who demonstrate an aggressive pattern
of symptoms at increased risk to progress along
the continuum. Thus, children displaying
characteristics of oppositional defiant disorder
(ODD) or ADHD with aggression are at a greater
risk than children exhibiting disruptive behavior
disorders without aggression, further empha-
sizing the need to implement early intervention
programs.
Disruptive behavior also is problematic
within the classroom. Teachers within the general
education classroom encounter significant
This project was conducted in partial fulfillment of the requirements for the doctoral degree for the first
author. We would like to thank the students, teachers, and administrators in the Whitehall-Coplay (PA) school
district for their participation in this project. We also appreciate the assistance of Sara Falcinelli, Alex Hirsch,
Jessica Hoffman, Kristin Renouf, and Drs. Christine Cole and Edward Shapiro.
Address all correspondence concerning this article to George J. DuPaul, School Psychology Program, Lehigh
University, 111 Research Drive, Bethlehem, PA 18015.
Copyright 1998 by the National Association of School Psychologists, ISSN 0279-60 15
290
Reducing Disruptive Behavior: Self-Management 291
challenges managing the behavior of students
with externalizing behavior problems (i.e.,
aggression, disruptions, defiance), and such
children with these behaviors are at higher than
average risk for special education referral (Fabre
& Walker, 1987; Kauffman, Lloyd, & McGee,
1989; Kerr & Zigmond, 1986). According to
Shapiro and Derr (1987), a majority of the
school-based interventions for aggression have
used a contingency management procedure such
as positive reinforcement or response cost.
Contingency management procedures, however,
require an external agent such as the teacher
being responsible for managing the behavior. The
external agent must implement response cost or
timeout to deter undesirable behavior and
reinforce the child’s positive behavior. This
creates an extra burden upon teachers and
detracts from time spent on instructional
activities.
Recently, research investigations have
focused on self-management strategies as a viable
alternative to more traditional contingency
management approaches. Self-management
refers to actions in which an individual takes to
change or maintain his or her own behavior
(Shapiro & Cole, 1994). There are several
potential advantages to using these procedures.
First, the individual takes control of his or her
own behavior, thereby increasing the probability
of maintaining appropriate performance in the
absence of an external agent. Second, past
research has indicated that behavior changes
resulting from self-management interventions
have a greater generalization potential than
contingency management procedures (Fantuzzo
& Polite, 1990). Third, self-management may
be more cost efficient, allowing the teacher to
spend more time teaching (Cole, 1992). The
latter benefit may increase the acceptability of
aggression-reduction interventions among
teachers.
Several studies have demonstrated the
efficacy of self-management procedures in
reducing students’ disruptive behaviors. A study
conducted by Rhode, Morgan, andYoung, (1983)
investigated the use of a self-evaluation procedure
based on a contingency management system to
decrease the frequency of inappropriate beha-
viors. Results of the intervention led to significant
gains in appropriate behavior in the resource
room setting that were maintained in the general
education classroom after specific procedures to
promote generalization were implemented.
Smith, Young, West, Morgan, and Rhode (1988)
further extended the methodology of Rhode et
al. (1983) by targeting the reduction of disruptive
behavior in junior high students. Smith, Young,
Nelson, and West (1992) also extended this work
by examining high school students and using a
peer-mediated procedure for transferring into the
general education classroom. Results of both
studies were similar to the Rhode et al. (1983)
study for decreasing disruptive behavior in the
resource room setting; however, the rates of off-
task and disruptive behavior did not decrease in
the general education setting following a reduced
form of the self-evaluation program for generali-
zation.
The lack of consistent findings regarding the
use of self-management to decrease disruptive
behavior within general education settings
suggests the need to perform further research in
this area. There is limited empirical research that
has addressed the utility of self-management in
decreasing disruptive behavior among at-risk
students in a general education setting. There
also has been a lack of attention to treatment
acceptability and utilization potential for both
the student and teacher. Finally, as suggested by
Smith et al. (1992), the generalizability of
procedures to other general education settings
must be addressed (e.g., class lecture to recess),
rather than from a restricted setting to only one
class lecture setting.
The purpose of this study was to examine
the efficacy of a self-evaluation procedure to
decrease disruptive behavior of three children
who were at risk for later conduct disorder (CD)
and were currently exhibiting behaviors
characteristic of oppositional defiant disorder
(ODD) or attention deficit hyperactivity disorder
(ADHD). The goal was to investigate whether
this intervention would lead to reductions in
aggressive and disruptive behavior that would
be maintained with the passage of time and across
settings (i.e., playground and classroom
environments). This study extended the research
of Rhode et al. (1983), Smith et al. (1988), and
Smith et al. (1992) in several ways. First, the
self-evaluation procedure was implemented in a
general education setting from the outset of the
study. Second, two similar classroom settings
(independent academic work) and one dissimilar
setting (playground) were used to assess
generalization effects across school environ-
ments. Finally, teacher and student acceptability
ratings were collected to determine the feasibility
292 School Psychology Review, 1998, Vol. 27, No. 2
of this procedure in a general education
classroom and playground environment.
Method
Participants and Settings
Participants in this study were three
Caucasian students (age 9) selected from a fourth-
grade public elementary school in southeastern
Pennsylvania, and identified as at risk for conduct
disorder. To be included in the study, subjects
had to pass through a multiple-gating procedure
adapted from Walker and Severson (1990). All
subjects were placed in general education
classrooms and had not received special educa-
tion services from their school district. Additional
criteria were that participants were not currently
receiving psychotropic medication for their
behavior or had not presented any history or
current evidence of neurological problems.
The study was conducted in three settings:
two general education academic lecture settings
and an afternoon recess following lunch (i.e.,
playground). Teachers selected the classroom
academic settings in which to implement the
study based upon their schedule.and which
classes they believed to be the most problematic
for the students.
Participant selection. Subjects were
identified using a multiple-gating procedure.
First, a target student was referred to the primary
investigator by the school psychologist as being
disruptive and aggressive and as in need of
further classroom intervention. A total of nine
third- and fourth-grade students were initially
referred to the investigator. Then, the referred
students’ classrooms were screened (Stage 1)
using the Systematic Screening for Behavior
Disorders (SSBD; Walker & Severson, 1990).
This procedure involved the teacher rank
ordering students with externalizing behavior
problems, a teacher respondent questionnaire of
the frequency and severity of problem behavior,
and direct observation of inattentiveness and peer
relations. Students identified by the SSBD as
having externalizing problems proceeded to the
next gate of the process. Stage 2 consisted of
teachers completing the Child Behavior
Checklist-Teacher Report Form (TRF;
Achenbach, 1991) to determine the clinical
significance of externalizing behavior. Children
who obtained a Tscore of 65 or greater (i.e., 93rd
percentile) on the Aggression factor of the TRF
were considered aggressive and potentially
eligible for the study. Finally, for the children
meeting the latter criterion, parents were
contacted and administered a structured
interview involving a review of the DSM IV
(American Psychiatric Association, 1994)
criteria for a disruptive behavior disorder.
Subjects for the study had to meet diagnostic
criteria for ODD or ADHD to participate and
qualify for the study.
A final sample of three students was
identified to participate in the study. Two of the
students (Joey and Brandon) came from the same
classroom (Teacher l), and the third student
(Megan) was from a different fourth-grade
classroom (Teacher 2). Informed written consent
to participate was obtained from each subject’s
parent or guardian after the student qualified with
the SSBD and TRF,
Dependent Measures
Observations of disruptive behavior.
Dependent measures were the percentages of
intervals in which disruptive and aggressive
behavior occurred within the academic lecture
or playground setting. Subjects’ interactions with
their peers and teachers were observed in 150
second intervals (for 15 minutes total) using a
partial interval recording system. Subjects’
behaviors were then placed into one of six
categories: positive interactions (e.g., sharing,
compliment), negative nonaggressive inter-
actions (e.g., noncompliance, defiance), verbal
aggression (e.g., name calling), physical
aggression (e.g., hitting, kicking), noninteractive
(e.g., not participating in a group activity), or
on- and off-task behavior (adapted from
Guevremont & Foster, 1993).
The Iowa Conners Teacher Rating Scale
(IOWA; Loney & Milich, 1982). The IOWA
Aggression subscale was completed by the
classroom teachers on the average of twice per
phase of the intervention to assess the effects of
the intervention on teacher perceptions of
disruptive and aggressive behavior in the general
classroom environment. The five Aggression
items used in the study were quarrelsome, acts
“smart,” temper outbursts, defiant, and uncoop-
erative. Test-retest reliability on the Aggression
scale is reported to be .86 (Pelham, Milich,
Murphy, & Murphy, 1989).
Reducing Disruptive Behavior: Self-Management 293
Side-effects rating scale. A side-effects
rating scale was developed by the investigators
and was completed an average of twice per phase
by classroom Teacher 1 (Joey and Brandon) and
once per phase by classroom Teacher 2 (Megan).
This was an 1 l-item scale consisting of questions
to determine any adverse collateral effects of the
intervention. Responses were based on a Likert-
type scale ranging from 0 (Absent) to 9 (Serious)
to determine the presence and the seriousness of
each behavior. Scoring was completed by totaling
the severity ratings for each of the response items.
Scoring generated both a total scale score (11
items) and a target behavior score, which
reflected items representing disruptive behavior
(4 items). Items included in the target behavior
score were arguing, crying/temper outbursts,
fighting, and noncompliance with assigned work.
a week by trained data collectors. Data were
collected in a 15.minute session using a IS-
second partial interval recording system.
Observed behaviors were placed in one of six
categories (see Dependent Measures section).
Student and teacher acceptability ques-
tionnaires. These were completed at the end of
the study to assess acceptability and feasibility
of self-management as a general education
intervention for at-risk students. Teachers were
given the Intervention Rating Profile-20 (IRP-
20), a 20.item questionnaire developed by Witt
and Martens (1983). Questions were answered
with a 1 to 6 Likert-type scale to obtain accepta-
bility ratings of the intervention. Students in the
study were administered the Children’s Interven-
tion Rating Profile, a 7-item questionnaire using
a 1 to 6 Likert-type scale (Witt & Elliott, 1985).
Data also were collected (using the same
coding system and procedures) on a same gender
classroom peer. The peer was identified by the
classroom teacher as an “average” student in the
classroom having neither excessive externalizing
nor internalizing behavior problems. Recording
behavioral observations of a classroom peer was
conducted to establish a normative level of
disruptive behavior within the classroom and on
the playground. Data were collected on the
classroom peer by a secondary observer observing
independently and concurrently with the primary
observer using identical coding procedures.
Classroom peer data were gathered for 26% of
the total sessions.
General Procedures
Interobserver agreement. Reliability
observations were conducted for 25% of the total
sessions. Observations were conducted with a
second observer recording independently of and
concurrently with the primary observer. The
secondary observer (recording the classroom
peers’ behavior) also conducted reliability
observations of the target student. Prior to the
daily observations, the secondary observer was
informed which child she should observe (target
or peer). In an attempt to prevent reliability
reactivity, the primary observer was blind as to
whose behavior (the target student or peer) the
secondary observer was coding.
All data were collected by graduate students
currently enrolled in an accredited school
psychology program and undergraduate psychol-
ogy students. All data collectors were blind to
the purpose of the investigation. Training for data
collectors occurred for approximately 12 hours
using videotapes and vignettes provided by the
investigator. Coders were required to attain
interrater agreement of at least 85% before
beginning data collection in the general educa-
tion classroom. During the last phase of training,
the data collectors made two observations with
the primary investigator in the general education
classroom. This was an attempt to assess reliabi-
lity of the direct observation code in the natural-
istic classroom setting and to help diminish
observer reactivity before the study commenced.
Experimental Design and Procedures
A multiple probe across settings (two general
education settings and playground) design was
used with all three subjects. In all conditions,
verbal praise and feedback of appropriate
behavior occurred.
Baseline. Baseline measures of student
behavior were first conducted in all settings. The
self-evaluation procedure was not used during
this time. Teachers were instructed to conduct
their lecture and playground sessions as usual
and to use their normal methods for repri-
manding student problem behavior.
Classroom and playground behavior obser- Token reinforcement/systematic verbal
vations were conducted an average of three times feedback. The purpose of this phase was to teach
294 School Psychology Review, 1998, Vol. 27, No. 2
the rating scale used for the behaviors by which
the student were being rated and to provide
frequent and meaningful teacher feedback about
their performance. Classroom rules and appro-
priate backup reinforcers were first discussed and
agreed upon by both the teacher and student.
Students were informed that the classroom
teacher would be rating their behaviors using a
0 to 5 rating scale with criteria adapted from
Rhode et al. (1983): 5 = excellent-followed all
classroom rules entire interval; 4 = very good-
minor infraction of rules (i.e., a talk out or off
task), but followed rules rest of interval; 3 =
average-did not follow all rules for the entire
time (approximately 80% of the time) but no
serious offenses; 2 = below average-broke one
or more rules to extent that behavior was not
acceptable (e.g., aggressive, noisy, talking) but
followed rules part of the time; 1 = poor-broke
one or more rules almost entire period or engaged
in higher degree of inappropriate behavior most
of the time; and 0 = totally unacceptable-broke
one or more rules during the entire interval.
Students also were told that teacher ratings
of appropriate classroom behavior corresponded
to points, which could then be redeemed for a
backup reinforcer (decided upon jointly by the
student and teacher) at the end of the school day.
Examples of reinforcers used were extra
computer time, free homework pass, and pencils.
Students were signaled by the teacher when the
first 5-minute interval started. During the 5-
minute interval, the teacher evaluated the
students’ behavior based on the rule list. After
the first S-minute interval, the teacher showed
the students their rating, and then continued to
evaluate behaviors for the second 5-minute
interval. Students were shown their ratings after
the second and third 5-minute intervals. At the
end of the 15 minutes (i.e., three 5-minute rating
intervals), the teacher gave verbal feedback to
the students and discussed why they received
their respective ratings.
Student self-evaluation with teacher. The
purpose of this phase was to initiate student self-
evaluation while matching the accuracy of their
ratings to the evaluations of the teacher. Students
were trained to self-evaluate and record their own
behavior during three 20-minute sessions.
Training sessions were conducted individually
by the classroom teacher and occurred in the
general education classroom. Rules of behavior
were briefly reviewed with the student, and then
he/she was provided with vignettes of examples
and nonexamples of classroom behaviors and
asked to assign ratings to those behaviors.
To implement the intervention, the students
were asked to rate their own behavior for three
5-minute intervals using the same 5-point scale
as the teacher. During the same 5-minute
intervals, the classroom teacher also rated the
student’s behavior and informed the student of
his or her rating. At the end of the 15.minute
session, the classroom teacher and student
compared their evaluations. If the student and
teacher ratings matched exactly, then students
earned the points they awarded themselves plus
1 bonus point. If the student and teacher ratings
were within 1 point of each other, then students
kept the evaluation points they assigned
themselves. Finally, if there was a 2-point or more
discrepancy between the student and teacher
ratings (higher or lower), then no points were
earned for the entire interval.
Extension of Rating Interval
To make the intervention more manageable
for the teacher, the rating intervals were extended
from three 5-minute sessions to one 15.minute
session. After the student and teacher were
accurately matching ratings and each student’s
behavior stabilized to an acceptable rate, the
student and teacher performed ratings only once
after the entire 15-minute interval. All other
aspects of the procedure (i.e., points and verbal
feedback) remained the same.
Matching with no verbal feedback.
Matching continued as per the rules established,
although verbal feedback and discussion about
the evaluation occurred only if there was more
than a l-point discrepancy.
Matching at 75%. Teacher and student
matching was faded to matching on a 75%
schedule. The teachers used three pieces of red
paper and one piece of black paper to indicate
75% matching. The students were informed that
their teacher would be conducting surprise
matches, although they were not informed of
them ahead of time. After the rating interval,
the student would blindly select a piece of paper.
If a red piece was selected, then matching would
occur that day. However, if a black piece was
selected, this indicated that teacher matching was
not required; the students kept the ratings they
Reducing Disruptive Behavior: Self-Management 295
assigned themselves. On the days during which
matches were conducted, students continued to
earn bonus points for exactly matching with the
teacher or lost all points for a matching
discrepancy of two or more points.
Fading of teacher matching. Matching
continued to be faded from 75% to 50% to 25%
to 0% (self-evaluation alone) schedules. Both the
accuracy of matching and level of disruptive
behavior were determinants of intervention
fading. During the self-evaluation phase, students
continued to monitor their behavior and kept the
points they assigned to themselves. Occasionally,
some participants began to drift from the point
system and assigned to themselves higher points
than their behavior warranted. Therefore, a
“surprise” match was conducted between the
teacher and the student (at the teacher’s
discretion) an average of every 6 days. When
these occurred, the previously established rules
for earning points during student and teacher
matching were used.
Playground ratings. Baseline data were
gathered continuously. A shortened matching
procedure consisted of a student and teacher 3-
day matching period with 100% agreement
(during three 5-minute intervals). This rating
interval was extended to one 15,minute session
followed by a quicker fading schedule.
Generalization classroom ratings. Base-
line observations of the second classroom lecture
setting occurred throughout all other phases of
the study. A shortened matching procedure
consisted of the teacher and student rating during
the three 5-minute intervals until 100% accuracy
was reached on one occasion. The rating interval
was then extended to a single 15-minute session
and followed by a shortened fading schedule.
Discussion was held only when a 2-point
discrepancy occurred.
Treatment integrity. Treatment integrity
was assessed with an 1 l-item scale developed by
the primary investigator. The 1 l-item scale
detailed specific steps of the intervention.
Measures of treatment integrity were conducted
by the primary investigator for 20% of the
intervention sessions (i.e., once a week). If
teachers were not adhering to the treatment
intervention, then a meeting was immediately
established to review the correct procedures.
Results
Data were collected on verbal and physical
aggression, non-interactive, negative, and off-
task behavior. Due to the low frequency of
aggressive and non-interactive behaviors in the
classroom, however, these behaviors were not
reported. Further, because student off-task and
negative behavior reflect similar trends in the
classroom environment, these data were
aggregated into a “disruptive behavior” category.
In the recess setting, the “disruptive behavior”
definition included negative and aggressive
behavior toward the teacher or peer.
Reliability
Interobserver agreement data were randomly
collected for 25% of the sessions throughout all
phases of the study. The percentage of inter-
observer agreement was computed by dividing
the number of agreements by the number of
agreements plus disagreements and then
multiplying by 100%. The mean percentage of
overall agreement was 98.06%, with a range of
96.35
to 100%.
Kappa
coefficients were
calculated to determine reliability beyond chance
levels. The mean overall
Kappa
for categories
of behavior was .78, with a range of .64 to .90,
indicating acceptable levels of agreement.
Treatment Integrity
Measures of treatment integrity were
conducted by the primary investigator for 20%
of the intervention sessions. The mean treatment
integrity rating was 98.2%, with a range of 81.8
to 100%. Treatment integrity diminished briefly
(i.e., 8 1.8%) with the implementation of the
matching phase as a result of errors in the
awarding of points on two occasions.
Treatment Effects on Disruptive Behavior
The percentage of disruptive behavior for
each student are displayed in Figures 1, 2, and
3. Joey’s initial baseline data for disruptive
behavior averaged 38.44%, 27.96%, and 3 1.67%
for math, recess, and social studies, respectively,
and reflected either a flat or increasing trend (see
Figure 1). During the token phase, his disruptive
behavior decreased to means of 10.73%, 10.28%,
and 14.03%. Joey’s disruptive behaviors
displayed a slight increasing trend in math and
296 School Psvcholom Review,
1998, Vol. 27, No. 2
4 -
a slight decreasing trend in both recess and social Megan’s level of disruptive behavior during
baseline was 31.31%, 38.23%, 26.98% for
reading, recess, and math, respectively, and
exhibited an upward trend in all three settings
(see Figure 3). During implementation of the
token phase, her disruptive behavior reduced to
10.48%, 8.74%, and 12.36% across the three
settings. Her disruptive behavior remained at a
low level during matching (i.e., 11.75%, 7.62%,
and 8.67%), and continued throughout the self-
management phase of the study with means of
9.17%, 4.72%, and 9.29% across the three
settings. Across intervention phases, Megan’s
disruptive behavior displayed a downward trend.
The percentage of nonoverlapping data points
between baseline and intervention phases for
reading, recess, and math, respectively, were
85.7 1%, lOO%, 84% (token phase ); 70%, lOO%,
60% (matching phase); and 80%, lOO%, 7 1.43%
(self-management). With the exception of two
high percentages of disruptive behavior in the
reading setting (matching phase), the overall
level of disruptive behavior remained low and
was relatively stable.
studies during this phase. Disruptive behavior
in the matching phase remained low with mean
percentages of 10.84%, 7.16%, and 10.13%.
Across all three settings for the matching
intervention, the data initially started low and
then displayed a slight increasing trend toward
the end of the matching phase. The mean
percentage of disruptive behavior remained at a
similar level in the self-management phase with
mean rates of 7.65%, 5%, and 8.33% obtained
across the three settings. The percentages of
nonoverlapping data points between the token
phase and baseline phase (for math, recess, and
social studies, respectively) were 1 OO%, 83.33%,
and 100%. The percentages of nonoverlapping
data points between the matching phase and
baseline were 95%, 94.12%, and 100%. Finally,
in the self-management phase the percentages
of nonoverlapping data points were 100% for all
three settings.
Brandon’s mean percentages of disruptive
behavior for baseline in math, recess, and social
studies were 37.64%, 24.5%, and 24.5%,
respectively, with a slight decreasing trend (see
Figure 2). The introduction of the token phase
reflected a slight decreasing trend in math and
recess and a slight increasing trend in social
studies and led to a decrease in his disruptive
behavior to mean percentages of 13.57%, 6.17%,
and 8.0% across the three settings. The matching
phase elicited a mean level of disruptive behavior
of 10.24%, 6.5%, and 5.28% across the three
settings. In the matching phase for math (Figure
2, top graph), Brandon’s disruptive behavior
displayed a slight decreasing trend. Although
Brandon’s level of disruptive behavior was at a
low level in recess and social studies during the
matching portion of the intervention, he did
exhibit a slight increasing trend in these two
settings. Due to time constraints, Brandon only
entered the self-management phase for the first
two settings: math and recess. The mean
disruptive behavior for the self-management
phase in math was 6.43% (with a flat trend line),
and the single data point collected in recess
indicated disruptive behavior to be evident in
2.5% of the intervals. The percentages of non-
overlapping data points between baseline and the
intervention phases for math, recess, and social
studies, respectively, were lOO%, 20%, 20%
(token phase); 92.86%, 50%, 33.33% (matching
phase); and 100% in the math setting (self-
management).
Normative peer comparison data were
collected for 26% of the sessions. The average
level of disruptive behavior was 5.6% across
phases for Teacher 1 (Joey and Brandon’s class-
rooms) and 5.02% for Teacher 2 (Megan’s class-
rooms). Although the average level of disruptive
behavior for the three target students was higher
than their classroom peers, this difference was
much smaller after intervention implementation.
Side-Effects Rating Scale and
IOWA
Comers Teacher Rating Scale
The side-effects and IOWA ratings results
are provided in Table 1. Side-effects scale means
are presented as target behavior (arguing, crying/
temper outbursts, fighting, and non-compliance
with assigned work) and total scores. For Joey
and Megan, slightly lower scores were obtained
for the side-effects ratings and the IOWA
aggression index across baseline and intervention
phases, indicating slightly lower levels of overall
disruptive behavior during intervention.
Brandon’s scores do not reflect a consistent
change across phases. Although there was a
decrease in the total side-effects score during the
self-management phase (from 61 to 38.5), no
change was seen in the target behavior score.
Therefore, negative side effects were not apparent
upon the implementation of the intervention.
Reducing Disruptive Behavior: Self-Management 297
Figure 1. Percentage of disruptive behavior across math, recess, and social studies for Joey.
Baseline Intervention
Token I
Phase 1
I
I
I
I
I
n
l
u
Matching
Self-Management
+ oey
r-l
m Peer
20 25 30 35 40
Sessions
+ oey
r-l
m
Peer
298
School Psychology Review,
1998, Vol. 27,
NO.
2
Figure 2. Percentage of disruptive behavior across math, recess, and social studies for Brandon.
Baseline
60~
50 l -
-:h
l em l l -
30
20
l -
10..
I
OP I
60
50
40 I
30
Intervention Self-Management
Token
Phase I Matching
I
I
I
I +
60
Sessions
Reducing Disruptive Behavior: Self-Management 299
Figure 3. Percentage of disruptive behavior across math, recess, and social studies for Megan.
Baseline Intervention
Token
Phase 1 Matching
I
I
I t
m . a
I I
L
Self-Management
I
m---m i
I
I
I
I
I
I
I
I
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I
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I
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E I
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300
School Psychology Review, 1998, Vol. 27, No. 2
Table 1
Average Scores of Side-effects Rating Scale and Iowa Conners Rating Scale
Across Intervention Phases
Student Scale Baseline Token Self-
management
JWY
Side-effects Target Behavior Score 17 7 9.67
Total Score 33 14 21.3
Iowa 4 3 2.6
Brandon Side-effects Target Behavior Score 30.5 28 30.5
Total Score 61.5 61 38.5
Iowa 6 8 5.5
Megan Side-effects Target Behavior Score 34 19 26.5
Total Score 51 36 45
Iowa 15 10 11
Treatment Acceptability Discussion
Ratings of treatment acceptability on the
IRP-20 were computed for each teacher and
student. Results indicated that both teachers
strongly agreed (i.e., a rating of a 6) on factors
such as treatment procedures being beneficial to
the child and appropriate as a pre-referral
intervention. Overall, Teacher 1 responded to the
intervention with a score of 107 of a possible
rating of 120 points. The mean response on the
scale was a 5.35, with a range of 4 to 6. The
response of Teacher 2 indicated an acceptability
rating of 112, with a mean response of 5.6.
Results of the Children’s Intervention Rating
Profile indicated that all students strongly agreed
(i.e., a rating of a 1) that they liked the
intervention, thought it would help them do better
in school, and did not think there were better
ways to help their behavior. The intervention
acceptability ratings for Joey, Brandon, and
Megan were 9, 7, and 15, respectively, with a
rating of a seven indicating the most acceptable
score. Megan, however assigned a rating of a 4
for feeling the intervention may cause problems
with her friends. On inquiry, she responded that
people could see the teacher coming to her desk
to give her the ratings.
The results of the present study indicate that
self-management is an effective strategy
for
maintaining teacher-mediated reductions in
disruptive behavior in general education
classroom settings. The data reveal that students
decreased their level of disruptive behavior in
both the classroom and recess environment closer
to the level of their classroom peers and
maintained these results in the absence of teacher
feedback (self-management). Although the data
do not indicate a spontaneous generalization to
other class environments, disruptive behavior
was reduced when a less intensive procedure was
introduced into each setting (programmed for
generalization). Overall, these results are
consistent with earlier findings indicating that
self-management is effective for decreasing
disruptive behavior (Rhode et al., 1983; Smith
et al., 1988, Smith et al., 1992).
These findings provide additional support
for the effectiveness of self-management on
disruptive behavior. The results of this study
suggest that elementary school children can
accurately evaluate their behavior and maintain
treatment gains in the absence of the teacher.
These results extend prior findings in the
self-
Reducing Disruptive Behavior: Self-Management 301
management literature by demonstrating that
self-management can be effective with an
elementary-aged population in general education
settings. Further, past investigations have not
addressed the effectiveness of the self-manage-
ment intervention in an unstructured setting. The
present study extends the literature by providing
empirical support that reductions in disruptive
behavior can be maintained across both struc-
tured and unstructured environments. Finally,
there were no apparent side effects to the
intervention, and teacher and students partici-
pating indicated that this was an acceptable
procedure to conduct within the general
education setting.
Limitations
Although generally positive results were
obtained, there were several limitations to this
study. Evaluations of treatment integrity were not
conducted in the absence of the primary author
or research assistants. Anecdotal reports received
from Teacher 2, however, indicate that treatment
integrity may have been compromised some
school days. On several occasions when direct
observation data were not being collected,
Teacher 2 reported that she did not have time to
do the intervention or forgot to implement the
procedure. Using an additional treatment
integrity measure (e.g., self-report scale) to
supplement the direct observation measure may
be warranted in further studies.
Time constraints were an additional
limitation to the investigation. For example,
Brandon reached the self-management phase in
only one of the settings because the end of the
school year was reached. Further, due to lack of
time before the end of the school year, the
intervention was only employed during a
15.
minute interval in each subject area. Because a
relatively short time period was used, general-
ization of results for longer durations (e.g., whole
class, entire school day) must be determined. This
investigation also was not able to collect follow-
up data for disruptive behavior and was not able
to assess self-management solely for an extended
amount of time. Further research needs to address
if the students can continue to use self-
management effectively for an extended amount
of time.
Finally, an additional constraint of the
intervention includes the presence of order
effects. Due to the sequence of the intervention
(teacher evaluation, matching training, and
systematic fading), the final levels of disruptive
behavior cannot be reliably attributed solely to
the self-management procedure alone. The
student’s behaviors were first brought under
control through an externally managed token
economy system, then control was transferred to
the student. Although the statement cannot be
made that self-management in isolation was
responsible for student’s low levels of disruption,
the end results are promising because students
maintained the change in the absence of the
teacher.
Although the results of the intervention led
to positive gains, that does not imply that the
same gains would be met by all students.
Different results may be produced depending
upon the function of the student’s behavior.
Therefore best practices may denote conducting
a functional assessment (identifying the
antecedent and consequent events which evoke
or maintain behavior) to guide the treatment
selection process in choosing the intervention
that best matches the function of the behavior
and to avoid selecting a potentially ineffective
treatment regimen.
Future Research
An important area for further investigation
would involve examining the critical factors
related to the effectiveness of self-management.
Although the teachers participating in the study
rated self-management as an acceptable and
feasible intervention, the procedure was rather
obtrusive, initially making this a time-intensive
procedure. Because this intervention requires
considerable teacher time at the outset, the
feasibility of teachers using this procedure with
adequate integrity in the absence of investigator
support is questionable. The fact that Teacher 2
occasionally did not implement the intervention
because she “did not have time” limits the
practicality of classroom intervention. This
finding was similar to research conducted by
Smith et al. (1988), i.e., the teachers in their study
did not consistently rate the students because they
were “too busy or they forgot” (p. 238). If self-
management is as effective as teacher-managed
systems in producing behavior change (Fantuzzo,
Polite, Cook, & Quinn, 1988), will teachers
choose this procedure? More research should
investigate the critical components that should
be employed in a self-management intervention.
302
School Psychology Review,
1998, Vol. 27, No. 2
For example, can the token phase be eliminated
completely? Can longer time intervals be used
initially? What are the most efficient fading
procedures? Finding a less intrusive, effective
technique may potentially make self-manage-
ment more acceptable to teachers.
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Kathryn E. Hoff is a doctoral student in school psychology at Lehigh University. Her research
interests
include disruptive behavior disorders and school-based interventions for students with ADHD and
aggressive behavior.
George J. DuPaul, PhD, is an associate professor of school psychology at Lehigh University. His
research interests include disruptive behavior disorders, school-based interventions for students
with
ADDID, and early intervention for young children with behavior disorders. He is an associate editor of
School Psychology Review.
