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Within-subject analysis of a prevention strategy for problem behavior

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Abstract

Although decades of research on functional analysis methodology have identified common contingencies that maintain problem behavior and effective interventions, relatively little research has been conducted on strategies to prevent the initial development of problem behavior. We conducted a 2-part case study, the purposes of which were to illustrate the use of sensitivity tests as the bases for intervention (Study 1) and subsequently to assess the efficacy of a prevention strategy using a single-subject design (Study 2). Results showed that the sensitivity tests identified establishing operations that may set the occasion for the development of problem behavior and that interventions based on differential reinforcement prevented increases in the severity of problem behavior relative to untreated and control baselines. Benefits and limitations to this individualized approach to prevention are discussed.
WITHIN-SUBJECT ANALYSIS OF A PREVENTION STRATEGY FOR
PROBLEM BEHAVIOR
TARA A. FAHMIE
CALIFORNIA STATE UNIVERSITY,NORTHRIDGE
AND
BRIAN A. IWATA AND SARAH C. MEAD
UNIVERSITY OF FLORIDA
Although decades of research on functional analysis methodology have identied common con-
tingencies that maintain problem behavior and effective interventions, relatively little research
has been conducted on strategies to prevent the initial development of problem behavior. We
conducted a 2-part case study, the purposes of which were to illustrate the use of sensitivity tests
as the bases for intervention (Study 1) and subsequently to assess the efcacy of a prevention
strategy using a single-subject design (Study 2). Results showed that the sensitivity tests identi-
ed establishing operations that may set the occasion for the development of problem behavior
and that interventions based on differential reinforcement prevented increases in the severity of
problem behavior relative to untreated and control baselines. Benets and limitations to this
individualized approach to prevention are discussed.
Key words: differential reinforcement, functional analysis, prevention, problem behavior,
single-subject design
Research on the functional analysis of prob-
lem behavior has produced a powerful technol-
ogy of behavior change (Beavers, Iwata, &
Lerman, 2013). Despite suggestions that this
same technology may be applied to prevention
(Iwata, 1991; Richman, 2008), the prevailing
focus in applied behavior analysis remains on
the treatment of existing problem behavior.
Several factors may account for the paucity
of research on the prevention of problem
behavior. First, little is known about the emer-
gence (or risk factors for the emergence) of
severe problem behavior in children with dis-
abilities (McClintock, Hall, & Oliver, 2003;
C. Oliver, Hall, & Murphy, 2005). Second,
research on the establishment of appropriate
behavior, although common, has not been eval-
uated as a prevention strategy and, therefore,
typically is not viewed as prevention research.
Nonetheless, decades of research on the assess-
ment and treatment of severe behavior support
an operant model of prevention. For instance,
there is extensive evidence to show that com-
mon social events (withholding or delivering
attention, work, or toys) frequently serve as
establishing operations (EOs) and reinforcers
for existing problem behavior (Beavers et al.,
2013). These ndings suggest three potential
approaches to the prevention of severe behav-
ior, if implemented before its onset:
(a) eliminating relevant EOs (noncontingent
reinforcement); (b) withholding reinforcers for
emerging, less severe problem behavior (extinc-
tion); and (c) teaching adaptive responses in
the presence of EOs that evoke severe behavior
(preemptive differential reinforcement of alter-
native behavior).
The differential reinforcement approach was
taken by Hanley, Heal, Tiger, and Ingvarsson
(2007), who taught typically developing pre-
schoolers several skills hypothesized to be
Address correspondence to Tara A. Fahmie, Psychology
Department, 18111 Nordhoff St., Northridge, California
91330 (e-mail: tara.fahmie@csun.edu).
doi: 10.1002/jaba.343
JOURNAL OF APPLIED BEHAVIOR ANALYSIS 2016, 49, 915926 NUMBER 4(WINTER)
915
substitutable for common social functions of
problem behavior. Skills included functional
communication (e.g., Excuse me, may I have
the toy?) and delay-tolerance training
(e.g., waiting when a request for a toy was
denied). Although these interventions often are
used to replace existing problem behavior, they
were implemented on a classwide basis inde-
pendent of the presence of problem behavior.
Training occurred in the presence of EOs
(e.g., low adult attention, being told to wait)
that were embedded in the daily classroom rou-
tine. Most children acquired the skills and
showed a concurrent reduction in problem
behavior. However, the design of this study did
not permit an evaluation of the program as a
preventive intervention because it is unknown
whether students who participated in the pro-
gram were less likely to develop problem behav-
ior later.
Luczynski and Hanley (2013) subsequently
evaluated the same skills program by comparing
changes in appropriate and problem behaviors
in two experimental groups (exposure to EOs
plus functional communication training
[FCT]) and two control groups (exposure to
noncontingent reinforcement); each group con-
tained three children. Statistical analysis of data
from pre- and posttraining probes revealed a
signicant increase in problem behavior for
only the control group, thus providing evidence
of a prevention effect in the experimental
group. The analysis used by Luczynski and
Hanley illustrated a group-comparison model,
which is common in prevention research. One
limitation of group designs, however, is their
lack of functional control on an individual
basis. By contrast, single-subject designs confer
the advantages of precision in within-subject
measurement, replication, and control, all of
which are desirable in the initial stages of exper-
imental evaluation, as in the case of prevention.
However, single-subject designs present a chal-
lenge when one attempts to demonstrate a pre-
vention effect: How does one experimentally
validate the clinical utility of no change
(i.e., prevention) from baseline?
The current case study illustrates an exten-
sion of functional analysis methodology to the
problem of prevention by combining assess-
ment and treatment phases in a unique single-
subject design. The purpose of Study 1 was to
create a set of tests to screen for the potential
emergence of problem behavior in an individ-
ual. The purpose of Study 2 was to evaluate
the preventive effects of intervention on prob-
lem behavior maintained by access to tangible
items, which allowed us to use a varied set of
EOs (e.g., removing, withholding, and delaying
tangible items) to serve as different baselines.
GENERAL METHOD
Participant and Setting
Shawn, a 20-year-old man who had been
diagnosed with an autism spectrum disorder
and speech-language impairment, was selected
for participation because his teachers reported
that he had minor or emerging problem beha-
viors in response to the restriction of tangible
items but no history of severe problem behavior
(aggression, property destruction, or self-
injury). Sessions were conducted in a therapy
room at Shawns special education school,
which contained a table, chairs, cabinets, and
four high-preference leisure items (sensory
water bottle, squishy animal toy, bristle blocks,
snap-lock shape toy) that were selected based
on results of a paired-stimulus preference
assessment. Two video cameras always were
present at opposite corners of the area for post-
session video scoring of all dependent variables.
In addition, a mirror was afxed to one wall so
that the therapist was able to detect all target
behaviors during sessions.
Response Measurement and Reliability
Because this study was designed to detect the
emergence of novel forms of problem behavior
that were unknown before the onset of the study,
TARA A. FAHMIE et al.916
we developed a checklist of all potential topogra-
phies and grouped them according to severity.
This process involved several steps. First, we cre-
ated broad topographical categories as described
by Fritz, Iwata, Hammond, and Bloom (2013),
which included (a) vocalizations, (b) facial expres-
sions, (c) postures, (d) repetitive motor move-
ments, (e) locomotion, (f ) object manipulation,
and (g) other problem behaviors. We then listed
examples of behaviors within each of these cate-
gories by reviewing target behaviors described
in research on the functional analysis of prob-
lem behavior (e.g., Beavers et al., 2013; Han-
ley, Iwata, & McCord, 2003), assessment of
precursors to problem behavior (e.g., Fahmie &
Iwata, 2011; Fritz et al., 2013), checklists for
problem behavior (e.g., the Modied Overt
Aggression Scale; P. C. Oliver, Crawford, Rao,
Reece, & Tyrer, 2007; Sorgi, Ratey, Knoedler,
Markert, & Reichman, 1991), and proto-
injurious behavior (e.g., Richman & Lindauer,
2005). Finally, we grouped all examples of
behavior into four levels of severity. Level
1 included neutral self-, object-, or nondirected
movements (e.g., face tapping, object tapping,
body rocking, respectively). Level 2 included
minor inappropriate behaviors (e.g., groaning,
shaking head no) that would be considered
tolerable in a classroom. Level 3 included major
inappropriate behaviors (e.g., yelling, dropping
to the ground) that would be considered fairly
intolerable in a classroom. Level 4 included
behaviors that commonly are classied as severe
problem behavior: aggression (e.g., hit thera-
pist), destruction (e.g., hit table), and self-injury
(e.g., hit head). We excluded from the checklist
those behaviors that constituted play with the
toys in the manner intended. Operational de-
nitions were developed for all behaviors before
the onset of assessment. Level assignment was
based on consensus among eight certied
behavior analysts who had extensive experience
in assessment and treatment of problem beha-
viors. The consensus process was initiated by
reviewing the level descriptions as a group and
then independently assigning each topography
to a level. A majority was reached on the level
assignments for 100% of topographies. The
resulting topographies, operational denitions,
and level assignments constituted the Neutral
to Severe Behavior (NSB) scale, which is
included as Supporting Information.
Trained observers watched each of the two
video angles, successively, and scored each trial
for the presence or absence of each behavior in
the NSB scale (see Figure 1). The observers
paused, rewound, and reviewed the videos as
needed to capture the occurrence of all possible
topographies. The frequency or duration of
behaviors was not scored because these features
of behavior were not as important as the
absence or presence of new behaviors in our
analysis. Behaviors not listed on the NSB scale
but that happened to occur during a trial were
either classied as Level 0 (if the behavior was
nonproblematic, e.g., smiling) and omitted
from subsequent analyses or added to the rele-
vant level (e.g., Level 1) and subjected to a rea-
nalysis for all previously scored trials. The
classication of these topographies was sub-
jected to the same consensus procedures
described above. The highest level of behavior
severity was noted for each trial, and this meas-
ure comprised the main basis for visual analysis
(see Figure 2).
Observers scored two additional dependent
variables on each trial. Appropriate behavior was
scored when the participant engaged in either
manding or sharing. Manding consisted of
handing a communication card, which was
freely available on all trials of both studies, to
the therapist, and sharing consisted of placing a
leisure material in the therapists hand.
We assessed interobserver agreement by
having a second trained observer independ-
ently score videotapes for a total of 39% of
trials. We compared observer records on a
trial-by-trial basis, and an agreement was
scored when both observers recorded the same
target behavior on the same trial. For each
917WITHIN-SUBJECT PREVENTION
0
5
10
15
20
25
PERCENTAGE OF TRIALS
SEVERITY LEVEL
1- neutral 2 - minor 3 - moderate 4 - severe
Screening Pre-FCT Inoculation
Conditions A through E
Post-FCT Inoculation
Conditions A and B only
0
5
10
15
20
25
Tap surface/object
Tap person
Taps self
Finger play
Shake torso
Whine/groan
Grunt
Facial disgust
Shake head no
Reach tangible
Push tangible
Push furniture
Stomp feet
Push person away
Cry
Run away
Drop to ground
Spit
IUD
Grab/pull tangible
Climb on furniture
Shake furniture
Loud vocalization
Throw object
Kick object/surface
Hit object/surface
Punch object/surface
Bite object
Break object
Crumple object
Rip object
Vomit
Pull hair of self
Grind teeth
Aerophagia
Hit self
Punch self
Poke eye
Bite self
Bang head/surface
Ingest inedible object
Kick person
Scratch person
Bite person
Hit person
Grab person
Pinch person
Pull hair of person
Punch another person
Throw object at person
0
5
10
15
20
25
Figure 1. Percentage of trials on which target behaviors occurred in test conditions of the screening (Study 1; left),
pre-FCT inoculation (Study 2; middle), and post-FCT inoculation (Study 2; right) phases. Behaviors that occurred in
the control condition of the screening are not shown.
TARA A. FAHMIE et al.918
trial, the number of target behaviors with
agreement was divided by total target beha-
viors scored, and the mean agreement across
trials was 76% (range, 0% to 100%). No
agreement occurred on three of 75 trials in
which one observer scored the occurrence of
one behavior and the other observer did not.
These three trials contained only Levels 0 and
1 target behaviors. Another measure of trial-
by-trial agreement was calculated by dividing
the number of trials with exact agreement
(same topographies scored by both observers)
by the total number of trials, which equaled
81%. Finally, reliability was assessed for the
highest severity level scored on each trial
(a main dependent variable) by dividing the
number of trials with exact agreements (the
same level assigned by both observers) by the
total number of trials. Observers agreed on
the highest level of behavior on 87% of trials.
10 20 30
0
1
2
3
4
Non.
Occ.
10 20 30
0
1
2
3
4
Non.
Occ.
10 20 30
0
1
2
3
4
Non.
Occ
0 204060
0
1
2
3
4
Non.
Occ.
10 20 30
0
1
2
3
4
Non.
Occ.
10 20 30
0
1
2
3
4
Non.
Occ.
Screen
Pre-
FCT Inoculation Screen
Post-
FCT Inoculation
A. Restrict Access
B. Remove Access
C. Block Access
D. Work Task
E. Request Access
F. Control
TRIALS
TRIALS
Pre-
FCT Inoculation
APPROPRIATE BEHAVIOR
PROBLEM BEHAVIOR SEVERITY LEVEL
APPROPRIATE BEHAVIOR
A
B
C
D
E
F
Prob Behavior
Manding
Sharing
Figure 2. Highest level of problem behavior, and presence of appropriate behavior, observed during screening
(Study 1) and the prevention evaluation (Study 2).
919WITHIN-SUBJECT PREVENTION
STUDY 1: SENSITIVITY TESTS
(SCREENING)
Procedure
The purpose of the sensitivity tests was
threefold. First, we used the tests to identify
response topographies that occurred in both
the test and control conditions. Given that
these responses persisted in the absence of
social contingencies (i.e., they did not appear
to be sensitive to the antecedent and conse-
quent events associated with tangible reinforce-
ment contingencies), we eliminated these
topographies from all subsequent analyses. Sec-
ond, the sensitivity tests allowed us to screen
Level 1, 2, and 3 topographies that occurred in
the test conditions alone. Third, we needed to
conrm that Shawn did not already engage in a
repertoire of Level 4 (severe) behaviors in the
presence of common tangible EOs.
Before the study, we developed a checklist of
situations that might evoke problem behavior
maintained by access to tangible items based
on a review of functional analysis research. This
checklist was presented separately to two of
Shawns teachers, who had the opportunity to
suggest additional situations related to tangible-
item access. Based on these discussions, four
situations were identied as potential EOs for
problem behavior maintained by access to tan-
gible reinforcement. We also included an EO
unrelated to tangible items: the presentation of
a work task (silverware sorting) and its associ-
ated negative reinforcer (escape from sorting)
because it was a context in which generalization
of trained skills during Study 2 was less likely
to occur (see below).
We conducted the sensitivity tests using a
variation of a trial-based functional analysis
(Bloom, Iwata, Fritz, Roscoe, & Carreau,
2011). Each test trial lasted 2 min. In the
restricted-access test condition (A), the thera-
pist positioned the preferred tangible items on
a shelf so that the participant could easily see
the items but not reach them. In the
removed-access test condition (B), the therapist
allowed Shawn to engage with the tangible
items for a few seconds and then removed them.
In the blocked-access test condition (C), the
therapist allowed Shawn to approach (but not
touch) the items and then she physically
blocked Shawns access to them. In the work-
task test condition (D), the therapist used a
verbal-model-physical (three-step) hierarchy to
prompt Shawn to engage in a silverware-sorting
task. Finally, in the request-access test condition
(E), the therapist allowed Shawn to engage with
the items freely while she repeatedly requested
the items in his possession (my turn,”“thats
mine,”“Can I have it?).
If the participant emitted either appropriate
(manding or sharing) behavior or Level
4 (severe) behavior during a test condition, the
therapist removed the potential EO for the
remainder of the trial (up to 2 min) by either
delivering the tangible items (Conditions A, B,
and C), ceasing to deliver prompts to work
(Condition D), or ceasing to request tangible
items in Shawns possession (Condition E).
Levels 1, 2, and 3 responses produced no pro-
grammed consequences because reinforcement
of these behaviors may have precluded the
observation of severe (Level 4) behavior if they
were precursors to severe behaviors. We alter-
nated the test conditions in a random order
across trials until all EOs were presented ve
times each, which yielded repeated opportu-
nities to observe behavior while extended expo-
sure to potentially problematic situations was
avoided.
We implemented control trials that consisted
of continuous (4-min) access to tangible items
and noncontingent (xed-time 15 s) attention
after every two test trials (i.e., 2:1 ratio of test to
control trials) to demonstrate experimental con-
trol and to ensure Shawns continued participa-
tion. We gave Shawn free access to both tangible
items and attention in these trials to control for
the presence of both stimuli in the test trials. We
conducted two to six trials per day.
TARA A. FAHMIE et al.920
Results and Discussion
Figure 1 (left) shows topographies of behav-
ior that Shawn exhibited during the screening
trials. Six topographies (pump st, shake torso,
shake head no,tap object to surface, tap self,
and appropriate sharing; not shown on the
graph) occurred exclusively in the presence of
the EOs (test trials), and all consisted of Level
1 (neutral) or Level 2 (minor) behaviors. Shawn
exhibited ve additional topographies of behav-
ior during the screening phase (body rock, head
bob, scratch self, shake limbs, and tap object to
self ), but these also were observed during con-
trol trials when no programmed EOs were pres-
ent. Because it seemed unlikely that these
responses were evoked by programmed EOs
during test trials, we reclassied them as Level
0 behaviors and omitted them from further
analysis. Figure 1 (left) also shows that Shawn
did not have an established repertoire of severe
(Level 4) behavior, thereby permitting an anal-
ysis of the preventive effects of intervention in
Study 2.
The rst phase of the graphs in Figure 2
shows the highest level of problem behavior
severity and the presence of appropriate behav-
ior across all test and control conditions during
screening. The Level 1 and 2 behaviors, noted
above, occurred in the context of Conditions A
(restrict access), B (remove access), and D
(present work task). Two test conditions, C
(block access) and E (requests), and the control
condition (F) evoked no problem behaviors
during the screening phase. Moreover, Condi-
tion E was the only condition in which appro-
priate behavior (sharing) was observed. Thus,
Study 1 also conrmed the absence of appro-
priate requests (manding with a picture card),
which would have been reinforced had they
occurred during these test trials.
Study 1 identied potential behavioral
(minor problem behavior) and environmental
(tangible EO) risk factors for the development
of severe behavior. However, it remains unclear
whether the occurrence of these behaviors in
the presence of particular EOs increased
Shawns likelihood to develop severe behavior
in Study 2. In addition, the brevity of screening
provided only tentative conrmation of the
absence of Level 4 behavior. An extended
screening may have presented conditions, such
as the extinction of minor topographies and
reinforcement of severe topographies, more
likely to lead to the emergence of problem
behavior, which we sought to capture and pre-
vent in Study 2.
STUDY 2: PREVENTION EVALUATION
Procedure
Pre- and post-FCT inoculation (baseline)
trials. The pre- and post-FCT baseline phases of
Study 2 involved test and control FA trials using
the same format as described in Study 1, with
one exception: Reinforcement was delivered
intermittently for all appropriate (31% of occur-
rences reinforced) and neutral to moderate
(25% of Level 1 occurrences, 47% of Level
2 occurrences, and 67% of Level 3 occurrences
reinforced) behaviors. Severe (Level 4) behaviors
continued to produce reinforcement on a xed-
ratio 1 schedule. This modication was made to
approximate more closely the conditions found
in a typical school setting, in which some appro-
priate requests are reinforced and some are
ignored (Luczynski, Hanley, & Rodriguez,
2014), and in which minor problem behaviors
may become more severe through shaping or
differential reinforcement (Mace, Pratt, Pra-
ger, & Pritchard, 2011). Reinforcers, after deliv-
ery, remained available for the entire trial.
FCT inoculation (training). Shawn was taught
an appropriate request (mand) for tangible
items, which consisted of a card exchange in
the presence of specic EOs, and subsequently
was taught to tolerate delayed or denied access
to the items. A therapist initiated each training
trial by presenting an EO. Contingent on an
921WITHIN-SUBJECT PREVENTION
independent or prompted mand, the EO was
removed immediately, and the trial was termi-
nated after 2 min. If independent manding did
not occur, a second therapist delivered a ges-
tural prompt and, if necessary, a physical
prompt approximately 2 s later. Prompt delays
were increased by about 2 s after three succes-
sive trials with no independent responding.
Control trials (free access to attention and tan-
gible items, as described in Study 1) were alter-
nated evenly with training trials and sequenced
randomly across 10-trial blocks (i.e., ve train-
ing and ve control trials), with ve trials per
day. This design enabled a multielement com-
parison of behavior under conditions in which
the EO and prompting were present (training)
and absent (control).
Training took place in three phases. First, we
established the response under a continuous
schedule of reinforcement, as described above.
Second, we trained delay tolerance by alternating
trials in which manding was reinforced immedi-
ately with trials on which manding was rein-
forced after a 30-s delay. On delay trials, Shawn
was instructed to waitfollowing a mand, and
a red card was presented for 30 s to signal the
delay. Finally, denial tolerance was trained by
alternating trials in which manding was and was
not reinforced. On denial trials, Shawn was told
nofollowing a mand, and the red card
remained visible for the remainder of the trial;
the EO was never removed during the denial
trials. The appropriate response was considered
mastered in a given phase when one or fewer
prompts preceded correct responding across
15 consecutive training trials, and no manding
occurred across 15 consecutive control trials.
The red card was removed as a signal in post-
FCT inoculation (baseline) trials, so that pre-
training and posttraining probes were identical.
Design
A multiple baseline design across EO con-
texts was used to evaluate the effects of training
as both treatment and prevention. A baseline
was established simultaneously for each EO,
and training was staggered across two EOs:
Conditions A (restrict access) and B (remove
access). To test the effect of training as treat-
ment, we compared behavior across the base-
lines on which training was staggered.
A reduction in the severity of problem behavior
after training demonstrated a direct treatment
effect; that is, training reduced current levels of
emerging problem behavior.
To test the effect of training as prevention
(i.e., inoculation), we implemented no inter-
vention in Conditions C (block access), D (the
work task EO), and E (request access). Evi-
dence of a preventive effect in the context of
this study would be seen in one or more of the
following three outcomes: Neutral to moderate
(Levels 1, 2, and 3) problem behavior
(a) increased in severity until training was
implemented (Conditions A and B),
(b) became more severe (Level 4) in baselines
in which training was not implemented, or
(c) did not increase in severity when an appro-
priate response generalized from a trained base-
line. The work task EO was included to make
it less likely that the latter pattern of generaliza-
tion would be observed across all baselines,
thus impeding our analysis of preventive
effects.
Results and Discussion
Both Figures 1 and 2 show the results of
Study 2. A comparison of screening (left) and
pre-FCT inoculation (middle) of Figure 1
shows the moderate to severe topographies that
emerged as a function of either repeated expo-
sure to the EOs, intermittent reinforcement, or
both. Figure 1 (right) shows that all but two
target behaviors were eliminated during the
posttraining trials of Conditions A and B (the
conditions in which intervention was applied),
and these two topographies were neutral (shake
torso) or minor (pump sts).
TARA A. FAHMIE et al.922
Whereas Figure 1 displays topographies of
behavior observed across test conditions,
Figure 2 displays the highest level of behavior
within each condition collapsed across topogra-
phies. Thus, Figure 2 permits an inspection of
the various patterns of treatment and preven-
tion effects described above (see Design).
In Condition A (restrict access; Figure 2, top
left), the rst baseline on which we introduced
training, behavior severity ranged from 0 to
4 in the pretraining baseline. During training
(not shown on graphs), Shawn acquired the
mand after 88 test trials of immediate rein-
forcement. We subsequently introduced delay
and denial trials, with mastery achieved after an
additional 126 and 18 test trials, respectively.
When we reintroduced baseline contingencies
during the posttraining condition (see
Figure 2), the severity of behavior decreased
below that observed during the screening and
pretraining phases and eventually reached zero,
demonstrating a treatment effect. In addition,
manding was present in all test trials after train-
ing. The nal three test trials of Condition A
contained only Level 0 and appropriate
behaviors.
In Condition B (remove access; Figure 2, sec-
ond left), behavior severity gradually increased
from Level 0 to Level 3 during the pretraining
baseline phase. This increasing trend before
training conrmed one of the three conditions
of our single-subject demonstration of preven-
tion: Behavior that was untreated in a given
condition increased in severity with continued
exposure to the EO. We subsequently intro-
duced training, and Shawn displayed mastery
performance in noticeably fewer trials (118 total,
including delay and denial training), presuma-
bly due to a history of previous training in Con-
dition A. When we reintroduced baseline
contingencies in the post-FCT-inoculation
phase (see Figure 2), Shawn displayed only
Level 0 and appropriate behavior (manding) in
Condition B, again conrming the treatment
effect.
Condition C (block access; Figure 2, third
left) occasioned an immediate increase in the
severity of problem behavior after the screening
phase. However, behavior severity did not
increase across the pretraining phase
(i.e., behavior severity cycled between Levels
0 through 2 primarily) as it had in Condition
B. One difference between Conditions B and
C was the fact that Shawn never displayed
manding before training in Condition B,
whereas we observed manding consistently after
12 pretraining baseline trials in Condition
C. The emergence of manding in Condition C
coincided exactly with the completion of train-
ing in Condition A, an apparent generalization
effect. Thus, the overall patterns of problem
and appropriate behavior in Condition C were
compatible with one of the conditions of our
single-subject demonstration of prevention:
When appropriate behavior generalizes to an
untreated condition, severity of problem behav-
ior does not continue to increase.
Condition D (work task; Figure 2, bottom
left), was included because it involved a differ-
ent EO and reinforcer (escape) than the other
conditions, and we therefore expected little
generalization of training to this condition. The
data in Figure 2 show that Condition D seem-
ingly accomplished the goal of inhibiting gener-
alization of trained appropriate behavior, which
was exhibited on only one trial of this condi-
tion. In addition, responding across this
untreated baseline increased from Levels
0 through 2 (rst 20 trials) to Levels 3 and
4 in the last six trials. That is, problem beha-
viors in the form of property destruction (grab-
bing and pulling on tangible items not in
Shawns possession) and self-injury (eye pok-
ing) emerged over time.
Condition E (request access; Figure 2, top
right) allowed an interesting analysis because
appropriate behavior (sharing) occurred consist-
ently in both the screening and the pretraining
baseline phases. If the occurrence of appropriate
behavior (perhaps as a protective factor)
923WITHIN-SUBJECT PREVENTION
before training inoculates an individual from
the development of severe behavior, the
expected outcome would be similar to results
shown in this condition: Behavior severity did
not increase incrementally across repeated expo-
sure to the test trials and never increased above
Level 2 (minor severity).
Condition F (control condition; Figure 2,
bottom right) provided an additional control
(via the multielement design) for both the
intervention and prevention effects. That is,
free access to the tangible items and attention
consistently produced only low-severity behav-
ior (Levels 0 and 1) in this condition.
The design of this study allowed identica-
tion of several within-subject patterns of a pre-
vention effect, each of which was conrmed at
least partially in the data obtained. However,
generalization of appropriate behavior across
the restrict access (Condition A) and block
access (Condition C) EOs in some ways limited
our conclusions and may have been mitigated
by the use of a multiple baseline design across
reinforcer classes. The added benet of this var-
iation would have been the potential conrma-
tion of prevention across varied sources of
reinforcement.
The fact that moderate (Level 3) and severe
(Level 4) problem behaviors occurred at all dur-
ing Study 2 provided some support for our
hypothesis that the EOs and response topogra-
phies identied in Study 1 appeared to be risk
factors for the development of problem behav-
ior. Although this evidence is suggestive (and
not yet conrmed), it may prove to be useful
in future research on risk factors for severe
behavior.
GENERAL DISCUSSION
We extended the use of functional analysis
methodology to identify risk factors for prob-
lem behavior and subsequently to prevent its
development. In Study 1, we conducted a series
of sensitivity tests involving exposure to
potential EOs for problem behavior while we
monitored behaviors that ranged from neutral
to severe. We observed several behaviors of low
severity during test trials but not control trials,
suggesting that the tests successfully screened
for the presence of minor problem behavior.
Study 2 investigated whether minor behaviors
would increase in severity when reinforced
intermittently and whether a training program
could prevent this trajectory. Results provided
preliminary evidence for both processes.
Results of this study extend those of previ-
ous research (Luczynski & Hanley, 2013), sug-
gesting that FCT followed by delay-tolerance
training are helpful strategies in the prevention
of problem behavior. The current study is
notable because it illustrates the logic of single-
subject design applied to prevention research.
Typical methods for identifying risk factors
involve comparisons of experimental and con-
trol groups at a single point in time or longitu-
dinal analyses of these groups at several points
in time. Aside from the fact that these
approaches rely heavily on indirect sources of
information such as caregiver reports, data col-
lection usually is based on minimal sampling
of behavior and does not adequately capture
its environmental context. A notable exception
is a study by C. Oliver et al. (2005), who
collected observational data at several points
in time and recorded both child behavior
and caregiver response; the qualitative (i.e.,
naturalistic observations) nature of this study,
however, resulted in 2 years of data collection.
The experimental approach used in the current
analysis involved repeated measures of behavior
during a series of 2-min sensitivity tests.
Although we collected more data than
C. Oliver et al. on a per subject basis, our
sampling procedure was more thorough, tem-
porally compressed, and controlled in that we
experimentally manipulated the relevant ante-
cedent and consequent events.
Group designs also have been used to deter-
mine whether an intervention prevents the
TARA A. FAHMIE et al.924
development of problem behaviors
(e.g., Luczynski & Hanley, 2013). The process
typically involves exposing an experimental
group to an intervention; preintervention and
postintervention differences then are compared
across groups. Although group comparisons are
an acceptable way of showing that some per-
sons will or will not develop problem behavior,
one benet of single-subject research applied to
prevention is that it allows closer inspection of
individual trends across time for varied
responses and in different but controlled con-
texts. The multiple baseline design seems par-
ticularly well suited to this type of
demonstration. Of course, the utility of the
design used in this study relies at least partially
on a lack of generalization of treatment effects
across challenging situations, which was one
limitation.
Nevertheless, several features of the current
design may be useful in future research on the
prevention of problem behavior. Although we
captured relatively short-term prevention effects
in the current study, our methodology could
incorporate longitudinal models (e.g., C. Oliver
et al., 2005) that probe for the emergence of
problem behavior across months or years. This
would help to reveal the long-term effects of
FCT inoculation as well as the concurrent
validity of our brief analysis when compared to
a more extended assessment. Furthermore, our
multiple baseline design across EOs conceivably
could be adapted to t group-design research in
prevention. For example, a curriculum that tar-
gets specic functional response classes could
be staggered across a school year while data on
classwide instances of problem behavior under
relevant EOs (as distinct baselines) are col-
lected. Finally, our screening procedure was
designed to be brief so as not to interfere with
the development of problem behavior per
se. However, it is unknown whether our
screening phase captured sufcient data to pre-
dict the development of problem behavior in
later phases. Additional applications of this
screening approach (with individuals who have
not yet developed severe behavior) are needed
to reveal whether screening aids in identica-
tion of risk factors.
Research on the prevention of severe prob-
lem behavior among individuals with disabil-
ities is still in its early stages. Our hope is that
this study provides one framework for intensive
analyses of preventive efforts, including both
assessment and intervention, with a range of
subject behavior serving as its own control.
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Action Editor, Wayne Fisher
SUPPORTING INFORMATION
Additional Supporting Information may be
found in the online version of this article at the
publishers web-site
TARA A. FAHMIE et al.926

Supplementary resource (1)

... Two additional studies conducted repeated analyses to identify changes in the topography, severity, or function of problem behavior over time (Fahmie et al., 2016;Richman & Lindauer, 2005). Richman and Lindauer (2005) conducted FA probes once per month for an average of 11 months (range, 2 to 23 months) to track the proto-injurious (i.e., behavior similar in topography to self-injury but not yet producing damage) and self-injurious behavior of infants with an IDD. ...
... Although the majority of functional analyses were undifferentiated, the authors' series of controlled observations allowed them to identify topographical shifts in emerging self-injury in several participants. In addition, the authors identified unique characteristics of two distinct subgroups of their sample-some children showed reductions in problem behavior during analysis conditions containing high levels of stimulation and others did not show such reductions. 1 Finally, Fahmie et al. (2016) developed "sensitivity tests" to screen the emerging problem behavior of an individual with an intellectual disability under a variety of contexts. Sensitivity tests were composed of brief and repeated exposure to establishing operations commonly used to determine the function of severe problem behavior. ...
... All other topographies of both problem and appropriate behavior (Levels 1, 2, or 3, as described below) were ignored during test segments. Similar to Fahmie et al. (2016), the experimenter ignored less severe problem behavior to increase the probability of evoking the highest level of problem behavior in the child's current repertoire. This rendered the test more similar to a structured descriptive assessment than an FA for lower-level topographies. ...
Article
The current study builds on a small but growing body of research evaluating the formal and functional characteristics of emerging problem behavior before it becomes harmful and requires costly treatment. The researchers tested 21 preschool children's sensitivity to establishing operations that commonly precede severe problem behavior. Sensitivity tests were embedded in a small group play context to optimize safety, efficiency, and ecological validity. The tests screened several levels of problem‐behavior severity as well as the presence of adaptive alternatives (i.e., communication) to problem behavior. Overall, outcomes suggested sources of reinforcement for minor‐ and moderate‐severity problem behavior in 86% of children. Only 17% of children exhibiting problem behavior also engaged in appropriate requests in the same condition(s) as problem behavior. The present data are compared to published functional analyses of severe behavior. The results are discussed as a preliminary step towards a function‐based model of risk identification and behavioral prevention of severe problem behavior.
... In Figure 2, to illustrate the relations among visual analysis and five methods, four different real-world data points were used, including the graphical data in which (a) there was no overlap, but the M-C could not be achieved (Lerman et al., 2015), (b) there was too much overlap, and the M-C was attained (Fahmie et al., 2016), (c) there was baseline trend, the M-C was attained, and there were fewer data points in the treatment phase (Scott et al., 2018), and (d) there was baseline trend, the M-C was attained after a while, and there were more data points in the treatment phase (Sherrow et al., 2016). ...
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Visual analysis and nonoverlap-based effect sizes are predominantly used in analyzing single case experimental designs (SCEDs). Although they are popular analytical methods for SCEDs, they have certain limitations. In this study, a new effect size calculation model for SCEDs, named performance criteria-based effect size (PCES), is proposed considering the limitations of 4 non-overlap-based effect size measures, widely accepted in the literature and that blend well with visual analysis. In the field test of PCES, actual data from published studies were utilized, and the relations between PCES, visual analysis, and the 4 nonoverlap-based methods were examined. In determining the data to be used in the field test, 1,052 tiers (AB phases) were identified from 6 journals. The results revealed a weak or moderate relation between PCES and nonoverlap-based methods due to its focus on performance criteria. Although PCES has some weaknesses, it promises to eliminate the causes that may create issues in nonoverlap-based methods, using quantitative data to determine socially important changes in behavior and to complement visual analysis.
... Future research is needed to develop and examine the degree to which flow charts or problemsolving tools may support practitioners in making these decisions. Furthermore, given what we 42 know about the conditions under which challenging behavior is evoked and maintained, guidelines for proactively arranging environments and establishing systematic prevention procedures in educational and clinical settings with populations at risk for developing challenging behavior (Fahmie et al., 2016;Hanley et al., 2007) is an important next step. Finally, FA methodology is only as good as the intervention it informs; therefore, continued efforts to improve upon methods for programming durable treatment effects that prevent or mitigate relapse are needed. ...
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Functional analysis (FA) methodology is a well-established standard for identifying the precise conditions that evoke and maintain problem behavior, thus leading to effective, function-based interventions (Beavers et al., 2013; Hanley et al., 2003; Hagopian et al., 2013). Although considered best practice, many behavior analysts report not conducting FAs prior to intervention due to implementation barriers including potential safety concerns and insufficient time (Oliver et al., 2015; Roscoe et al., 2015). Over the past two decades, a tremendous amount of research has been conducted to address these and other commonly reported barriers to FA implementation (e.g., JABA Special Issue on FA methodology, 2013, volume 46, issue 1). The outcomes of these studies suggest methodological refinements that offer a wide range of solutions to previously described barriers, resulting in an overall improved approach toward conducting FAs in practice. The purpose of this chapter is to provide an overview of FA methodology, review best practice considerations for designing and conducting FAs, provide recommendations for analyzing FA outcomes, and review procedural modifications that can be applied to address implementation challenges in various contexts and situations.
... In Figure 3, to illustrate the relationship among visual analysis, four nonoverlap-based methods and PCES, four different real-world data were used, including the graphical data in which (a) there was no overlap, but the M-C could not be achieved (Lerman et al., 2015), (b) there was too much overlap, and the M-C was attained (Fahmie et al., 2016), (c) there was baseline trend, the M-C was attained, and there were fewer data in the treatment phase (Scott et al., 2018), and (d) there was baseline trend, the M-C was attained after a while, and there were more data in the treatment phase (Sherrow et al., 2016). ...
Preprint
Visual analysis and nonoverlap-based effect sizes are predominantly used in analyzing single case experimental designs (SCEDs). Although they are popular analytical methods for SCEDs, they have certain limitations. In this study, a new effect size calculation model for SCEDs, named performance criteria-based effect size (PCES), is proposed considering the limitations of four nonoverlap-based effect size measures, widely accepted in the literature and blend well with visual analysis. In the field test of PCES, actual data from published studies were utilized, and the relationship between PCES, visual analysis, and the four nonoverlap-based methods was examined. In determining the data to be used in the field test, 1,012 tiers (AB phases) were identified from four journals, which have the highest frequency of SCEDs studies, published between 2015 and 2019. The findings revealed a weak or moderate relationship between PCES and nonoverlap-based methods due to its focus on performance criteria. Although PCES has some weaknesses, it promises to eliminate the causes that may create issues in nonoverlap-based methods, using quantitative data to determine socially significant changes in behavior and complement visual analysis.
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... The presence of genetic conditions that may be associated with problem behavior, the diagnosis of ASD, intellectual and sensory impairments, and deficits in adaptive skills are known risk factors for problem behavior and, therefore, must be assessed to determine the relative risk. Many recommendations on pediatric management of ASD [68][69][70] also are applicable to the broader population of children with IDD. Awareness of the family's social supports, resources, and the caregivers' capacity to physically manage problem behavior can inform efforts to seek supports available through insurance or social service organizations. ...
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Background Reliable measures of aggressive challenging behaviour are required if interventions aimed at reducing this behaviour among people with intellectual disability (ID) are to be formally evaluated. The present authors examined the reliability of the Modified Overt Aggression Scale (MOAS), an instrument not yet formally tested in those with ID, in a sample of people who participated in a randomized trial of neuroleptic medication for aggressive challenging behaviour. Method Sixty interviews using the MOAS were carried out by two interviewers 2–5 days apart with 23 carers of 14 people who had shown aggressive challenging behaviour. Level of agreement between these two ratings was examined for four subscales of aggression and for total MOAS score. Results The level of agreement between the raters was high for verbal aggression (intraclass correlation coefficient, ICC = 0.90), physical aggression against others (ICC = 0.90) and for total MOAS score (ICC = 0.93). Levels of agreement on the other two subscales were lower but still in the good/moderate range. Conclusion The MOAS provides a reliable measure of verbal and physical aggression among people with ID who reside in community settings and is suitable for use in studies evaluating the effectiveness of interventions aimed at reducing aggressive challenging behaviour in this group.