Journal of Positive Behavior Interventions 1 –13© Hammill Institute on Disabilities 2014Reprints and permissions: sagepub.com/journalsPermissions.navDOI: 10.1177/1098300714548799jpbi.sagepub.com

Article

Students with autism spectrum disorders (ASD) characteris-tically demonstrate inflexible adherence to specific routines (American Psychiatric Association, 2000), which may lead to displays of challenging behaviors during transitions. The tendency to engage in problem behavior during transitions causes difficulties for the students with ASD and those in their immediate environment (e.g., teachers and peers). Large-scale survey studies (range = 84–176 participants) using the Behavior Problems Inventory (BPI-01; Rojahn, Matson, Lott, Esbensen, & Smalls, 2001) or the ASD–Behavior Problems for Children (ASD-BPC; Matson, Gonzales, & Rivet, 2008) report that 94% of the ASD popu-lation display some challenging behavior as reported by cli-nicians or parents (Jang, Dixon, Tarbox, & Granpeesheh, 2011; Matson, Wilkins, & Macken, 2009; McTiernan, Leader, Healy, & Mannion, 2011), of which 63% exhibit externalizing behaviors and 83% exhibit internalizing behaviors (Matson et al., 2009). Flannery and Horner (1994) suggested that the characteristic behavioral rigidity is due to a preference for highly predictable and consistent routines.

In an eco-behavioral assessment, including repeated direct observations of preschool classrooms for an entire day, researchers found that students spend more than 20% of the school day engaging in some type of transition (Carta,

Greenwood, & Robinson, 1987). Similar rates (25% of the day engaged in some type of transition) were observed by Schmit, Alper, Raschke, and Ryndak (2000). These data sug-gest that students who have difficulties with transitions may engage in high rates of challenging behavior. This is particu-larly problematic because challenging behavior is a common rationale for excluding students with ASD from educational programs and general education settings (Strain, Wilson, & Dunlap, 2011; Volkmar & Wiesner, 2009). Such difficulties can also limit the amount of academic instruction provided to students with ASD (Banda & Kubina, 2006; Sterling-Turner & Jordan, 2007) as well as their peers due to teachers’ need to use instructional time to respond to challenging behavior.

Common challenging behaviors exhibited during transi-tions by students with ASD include aggression, inappropriate vocalizations, off-task behavior (e.g., engaging in tasks other

548799 PBIXXX10.1177/1098300714548799Journal of Positive Behavior InterventionsLequia et al.research-article2014

1University of Wisconsin–Madison, USA

Corresponding Author:Jenna Lequia, University of Wisconsin–Madison, 1000 Bascom Mall, 435 Education Building, Madison, WI 53706, USA. Email: lequia@wisc.edu

Action Editor: Lee Kern

Improving Transition Behaviors in Students With Autism Spectrum Disorders: A Comprehensive Evaluation of Interventions in Educational Settings

Jenna Lequia, MS1, Kimber L. Wilkerson, PhD1, Sunyoung Kim, MEd1, and Gregory L. Lyons, MA1

AbstractStudents with autism spectrum disorders (ASD) often exhibit rigidity, which can lead to difficulties with transitions. Such difficulties can explain why students with ASD are placed in more restrictive educational environments. This review offers a quantitative synthesis of effects of interventions aimed to improve transitions of students with ASD and provides a descriptive overview of the quality of the included studies. Analyses focused on the main component of the intervention, topography of challenging behavior, and the type of transition expected of students with ASD. Activity schedules were most prominently used and most successful to ease transition difficulties. Strategies that align with preferences of students with ASD also successfully improved transitions. Practical implications and suggestions for future research are provided.

Keywordschallenging behavior(s), intervention(s), single-case designs, data analysis, studies, special education

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2 Journal of Positive Behavior Interventions

than what is expected), dropping to the floor, and elopement (Buschbacher & Fox, 2003; Horner, Carr, Strain, Todd, & Reed, 2002). Regardless of the topography and severity, without intervention, challenging behaviors are likely to con-tinue and increase in intensity (Murphy et al., 2005). Research has demonstrated that simple strategies (i.e., pre-planned sound stimuli) can facilitate smooth transitions for students without disabilities (Register & Humpal, 2007). Although these strategies may be effective with typically developing students, students with ASD generally require more substan-tial, individualized intervention strategies to reduce problem behavior during transitions.

Currently, there is no quantitative synthesis that specifi-cally evaluates the effects of interventions on transition behaviors in students with ASD in educational settings. Thus, the primary aim of this review was to perform such an evaluation. We examined three variables: the main compo-nent of intervention, the topography of challenging behav-ior, and the type of transition (i.e., within classroom, across classroom, exiting or entering school). In addition, we assessed the overall quality of the research studies. Specific research questions included the following:

Research Question 1: What interventions are used to improve transition behaviors?Research Question 2: What types of transitions are tar-geted for intervention?Research Question 3: What behavioral topographies are targeted during transitions?Research Question 4: Are interventions differentially effective depending on the main component of the inter-vention, behavioral topography, or transition type?Research Question 5: Are specific intervention types differentially effective depending on behavioral topogra-phies or targeted transitions?Research Question 6: Do research designs for included studies meet quality indicators?

Method

Inclusion Criteria

Five inclusion criteria were established a priori to deter-mine eligible studies: (a) at least one participant included in the study had to have a diagnosis of ASD and be between the ages of 3 and 21 years, (b) the intervention under evalu-ation had to be implemented in an educational setting, (c) the intervention under evaluation had to be aimed at improving transition behaviors of students, (d) the study must have used single-case research (SCR) methodology, and (e) the study must have been published in a peer-reviewed journal. Educational settings included any con-text where a child received instruction (e.g., an inclusive classroom, segregated classroom, or in-home educational

program). Transition behaviors were defined as those occurring when a student was expected to move from one activity to the next during the school day.

Search Procedure

First, electronic searches were conducted of five databases (i.e., PsycINFO, Academic Search Premier, ERIC, MEDLINE, and CINAHL Plus with Full Text) simultane-ously using the following keywords: autis*, Asperger*, developmental disab*, transition*, behavior*, intervention, and treatment. Keywords were connected by appropriate logical operators “or” and “and.” Of the 170 studies yielded by the database search, 10 fit the inclusion criteria. Most of the excluded studies were descriptive and did not evaluate an intervention using SCR. Ancestral searches of the 10 articles were completed to locate additional studies—result-ing in the identification of four studies. Thus, a total of 14 studies were included in this review. Sterling-Turner and Jordan (2007) noted the research base in the area of inter-ventions to address transitions for students with ASD is lim-ited; this is likely why so few studies met the inclusion criteria for this review as well.

Analysis of Included Studies

Included studies were quantitatively evaluated across the main component of the intervention, targeted topography of challenging behavior, and the targeted transition. Each of the 14 studies included in the review was categorized into one of six categories of main intervention component, defined as follows. Activity schedules (AS) are visual depic-tions of the sequence of activities for the day. Social narra-tives (SN) included Social Stories™ and power cards. Social Stories™ are short, individualized stories that high-light behavioral expectations for various social situations that a student may encounter and power cards are individu-alized cue cards that indicate a behavioral expectation. Video models (VM) are videos showing either the student or a model (e.g., same age peer) engaging in desired behaviors for the specific transition. The high-p procedure (HP) is a procedure where the individual is asked two to three high-probability questions (i.e., questions or requests that the stu-dent is likely to answer or comply with), followed by a low-probability request (i.e., targeted transition). For exam-ple, before requesting a student with ASD transition to a task that may be aversive, the teacher might request two to three tasks (e.g., give me a high five, ask how do you spell your name) that are typically responded to with high levels of compliance. Reinforcement-based procedures (RF) focus on providing a reinforcer following displays of appropriate transition behaviors. For a study to be categorized as RF, reinforcement had to be the only intervention component. Studies using reinforcement as part of the procedure for

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Lequia et al. 3

implementation for another intervention were not included in this category. Peer-mediation (PM) consisted of a buddy system (i.e., typically developing peer with student with ASD) to facilitate proper transition behaviors. Studies were placed into a category based on the main component of the intervention under evaluation. Some studies evaluated more than one type of intervention; therefore, participant data were separated and placed in appropriate categories. For example, Cihak (2011) compared the use of VM and AS in four participants—each participant’s data for VM condi-tions were used in the video modeling category whereas participant data for AS condition were included in the AS category.

Targeted behaviors of each participant were categorized into one of the following five behavioral topographies. Aggression consisted of one or more behaviors with the potential to cause harm to self or others (e.g., pushing, destruction, scratching, hitting, kicking, and biting). Off task included requiring prompts by an adult to complete a transition. Inappropriate vocalizations consisted of verbal utterances deemed unacceptable due to the topic or the vol-ume of the utterance. Dropping to the floor consisted of physically falling to the floor or sitting on the floor when asked to transition. Elopement consisted of running away from the group during transitions. If one participant had multiple targeted behaviors that were not reported sepa-rately, data from the participant were used in each category of behavior that was targeted.

Studies were also categorized into one of the following three transition types. Across classroom transitions required ending an activity in one classroom to move to another classroom or other location outside the classroom, such as a locker in the hallway. Within classroom transitions required ending one activity and moving to another activity in the same classroom. Entering or exiting the school were transi-tions that required entering or exiting the school building. For studies that targeted more than one type of transition, only those that reported data separately for each type of transition were used in effect size calculations considering both the main component of the intervention and the type of transition.

Although acknowledging that use of effect sizes in SCR is still debated (see Parker & Hagan-Burke, 2007), we com-puted effect sizes for all of the included studies using Non-Overlap of All Pairs (NAP) as the main effect size measurement and Tau-U as a way to demonstrate added confidence for effect size results (Campbell, 2013; see Table 1). Procedures similar to those used by Lequia, Machalicek, and Rispoli (2012) were used to calculate effect sizes. Non-overlap indices are more robust than mean- or median-level changes across phases because such techniques compare each baseline data point with each intervention data point (Parker & Vannest, 2009). Parker, Vannest, and Davis (2011) suggested that connections to

nonparametric tests provide a rationale for use of some indi-ces (i.e., NAP) in SCR as a way to validate visual analysis. Moreover, there are currently no acceptable procedures for using only visual analysis to quantitatively synthesize SCR and conduct moderator analyses (Campbell, 2013). UnGraph (Biosoft, 2004; Shadish et al., 2009) was used to extract exact data from the included studies and an online calculator was used to compute effect sizes and 85% confi-dence intervals (CIs; Vannest, Parker, & Gonen, 2011). Forest plots were created to visually display the findings. Parker and Vannest (2009) suggested the following inter-pretation of NAP calculations: weak effect (0–0.65), mod-erate effect (0.66–0.92), and strong effect (0.93–1.0).

Each study’s research design was coded using a research design quality checklist that included criteria outlined by the What Works Clearinghouse (WWC) Procedures and Standards Handbook (U.S. Department of Education, 2011). Specific categories of quality indicators included experimental effect, inter-observer agreement (IOA), pro-cedural integrity, and social validity. Standards for two cat-egories were amended to reflect additional, more stringent, criteria suggested by Kennedy (2005) and Horner and col-leagues (2005). Specifically, for a study to be coded as meeting standards (MS) for IOA, such data needed to be collected for 30% of all sessions, rather than 20% as recom-mended by WWC (see Kennedy, 2005). In addition, the standard for procedural integrity was also amended to reflect criterion outlined by Horner and colleagues (2005), coded as MS if there was direct measurement of interven-tion implementation and meeting standards with reservation (MSR) if measured using self-report. Checklists are avail-able from authors on request.

Studies categorized as MS met all of the criteria for each category of quality indicator evaluated. Studies were coded as MSR if (a) demonstrations of experimental effect were coded as MSR or (b) either IOA or procedural integrity were coded as MSR and social validity data were not col-lected. Studies classified as not meeting standards (NMS) had two or more categories on the quality indicator check-list that did not meet criteria for meeting design quality standards.

IOA

Three types of IOA were calculated: study selection, article evaluation, and research design quality. IOA was computed by dividing the number of agreements by the number of agreements plus disagreements, and multiplying by 100. For study selection and article evaluation, procedures simi-lar to those used by Horner and colleagues (2002) were implemented to calculate IOA. For study selection, the sec-ond author independently coded a batch of 24 studies using a checklist to indicate whether each inclusion criterion was met. The batch of 24 studies included the 14 studies coded

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4

Tab

le 1

. Su

mm

ary

of In

clud

ed S

tudi

es.

Ref

eren

cePa

rtic

ipan

t(s)

Tra

nsiti

on(s

)T

opog

raph

yIn

terv

entio

n co

mpo

nent

sFi

ndin

gsD

esig

n qu

ality

Ang

ell,

Nic

hols

on,

Wat

ts, a

nd

Blum

(20

11)

11-y

ear-

old

mal

e,

ASD

WC

IVSN

: Ada

pted

pow

er c

ard;

initi

al S

D

; pos

itive

rei

nfor

cem

ent

Use

of a

dapt

ed p

ower

car

d st

rate

gy s

ucce

ssfu

lly d

ecre

ased

late

ncy

to

initi

ate

inte

ract

ivity

tra

nsiti

ons.

M T

au =

1, 8

5% C

I = [

0.73

8, 1

.262

]M

NA

P =

1, 8

5% C

I = [

0.73

8, 1

.262

]

Mee

ts s

tand

ards

Band

a an

d K

ubin

a (2

006)

13-y

ear-

old

mal

e,

PDD

-NO

SW

C, A

CO

TH

P: T

wo

to t

hree

hig

h-p

ques

tions

follo

wed

by

a lo

w-p

req

uest

; pra

ise

for

com

plia

nce;

re

peat

ed fo

r no

ncom

plia

nce

Dec

reas

es w

ere

obse

rved

in t

he t

otal

tim

e re

quir

ed t

o co

mpl

ete

all

thre

e tr

ansi

tion

situ

atio

ns a

nd in

the

freq

uenc

y of

ver

bal p

rom

pts.

M T

au =

0.3

56, 8

5% C

I = [

0.14

1, 0

.571

]M

NA

P =

0.6

78, 8

5% C

I = [

0.46

3, 0

.983

]

Mee

ts s

tand

ards

w

ith r

eser

vatio

n

Blai

r, F

ox, a

nd

Lent

ini (

2010

)3-

year

-old

mal

e,

PDD

-NO

SES

AG

AS:

Vis

ual s

ched

ule;

firs

t, th

en s

tate

men

ts

and

visu

al c

ues;

diff

eren

tial r

einf

orce

men

tSt

uden

ts d

ispl

ayed

low

er r

ates

of c

halle

ngin

g be

havi

or a

nd h

ighe

r le

vels

of e

ngag

emen

t du

ring

tra

nsiti

on t

imes

.M

Tau

= 0

.667

, 85%

CI =

[0.

148,

1.1

85]

M N

AP

= 0

.833

, 85%

CI =

[0.

315,

1.3

52]

Mee

ts s

tand

ards

w

ith r

eser

vatio

n

Brya

n an

d G

ast

(200

0)T

wo

8-ye

ar-o

ld

mal

es, 7

-yea

r-ol

d m

ale,

and

an

8-ye

ar-o

ld fe

mal

e,

ASD

WC

OT

AS:

Ver

bal i

nstr

uctio

ns fo

r ac

tiviti

es t

o co

mpl

ete;

pra

ise

for

on-t

ask

or o

n-sc

hedu

le

beha

vior

s; in

appr

opri

ate

beha

vior

s ig

nore

d

Incr

ease

s ob

serv

ed in

the

leve

l of p

erfo

rman

ce in

bot

h on

-tas

k an

d on

-sch

edul

e be

havi

ors

of a

ll pa

rtic

ipan

ts.

M T

au =

1, 8

5% C

I = [

0.87

6, 1

.124

]M

NA

P =

1, 8

5% C

I = [

0.87

6, 1

.112

]

Mee

ts s

tand

ards

w

ith r

eser

vatio

n

Cih

ak (

2011

)T

wo

13-y

ear-

old

mal

es, 1

2-ye

ar-o

ld

mal

e, 1

1-ye

ar-o

ld

fem

ale

with

ASD

WC

, AC

, ES

AG

, IV

, DF

AS/

VM

: Lea

st-t

o-m

ost

prom

ptin

g; v

erba

l pr

aise

upo

n su

cces

sful

inde

pend

ent

tran

sitio

n; s

tatic

pic

ture

sch

edul

es o

r vi

deo

mod

elin

g sc

hedu

les

Inde

pend

ent

tran

sitio

ns in

crea

sed;

thr

ee s

tude

nts

reac

hed

crite

ria

usin

g st

atic

sch

edul

es, t

wo

reac

hed

crite

ria

usin

g vi

deo

mod

elin

g sc

hedu

le, a

nd o

ne r

each

ed c

rite

ria

for

both

.A

S: M

Tau

= 0

.937

, 85%

CI =

[0.

694,

1.1

79]

VM

: M T

au =

0.9

41, 8

5% C

I = [

0.69

8, 1

.184

]A

S: M

NA

P =

0.9

68, 8

5% C

I = [

0.72

5, 1

.211

]V

M: M

NA

P =

0.9

70, 8

5% C

I = [

0.72

7, 1

.213

]

Mee

ts s

tand

ards

w

ith r

eser

vatio

n

Cih

ak,

Fahr

enkr

og,

Ayr

es, a

nd

Smith

(20

10)

6-ye

ar-o

ld m

ale,

7-

year

-old

mal

e,

7-ye

ar-o

ld fe

mal

e,

and

8-ye

ar-o

ld

mal

e w

ith A

SD

AC

, ES

AG

, EP,

DF

VM

: Vid

eo s

elf-m

odel

ing

via

iPod

; ver

bal

prom

pts;

ver

bal p

rais

e up

on s

ucce

ssfu

l tr

ansi

tion;

leas

t-to

-mos

t pr

ompt

ing

All

stud

ents

had

incr

ease

s in

inde

pend

ent

tran

sitio

ns u

sing

the

in

terv

entio

n, w

hile

stil

l occ

asio

nally

req

uiri

ng a

dditi

onal

pro

mpt

s.M

Tau

= 0

.922

, 85%

CI =

[0.

741,

1.1

338]

M N

AP

= 0

.961

, 85%

CI =

[0.

780,

1.1

42]

Mee

ts s

tand

ards

w

ith r

eser

vatio

n

Det

tmer

, Si

mps

on, M

yles

, an

d G

anz

(200

0)

5-ye

ar-o

ld m

ale,

A

SDN

SO

TA

S: V

isua

l sch

edul

e in

dica

ting

orde

r of

ac

tiviti

es fo

r th

e da

y; s

ub-s

ched

ule

and

finis

hed

box

for

wor

k tim

e ic

ons;

Tim

e T

imer

for

favo

rite

act

iviti

es

Both

par

ticip

ants

dis

play

ed d

ram

atic

dec

reas

es in

the

ir la

tenc

y to

tr

ansi

tion

betw

een

activ

ities

; als

o de

crea

ses

in v

erba

l and

phy

sica

l pr

ompt

s as

wel

l as

phys

ical

rem

oval

s.M

Tau

= 1

, 85%

CI =

[0.

662,

1.3

38]

M N

AP

= 1

, 85%

CI =

[0.

662,

1.3

38]

Doe

s no

t m

eet

stan

dard

s

Doo

ley,

W

ilcze

nski

, and

T

orem

(20

01)

3-ye

ar-o

ld m

ale,

PD

D-N

OS

NS

AG

AS:

Rev

iew

ed s

ched

ule

with

tea

cher

; led

to

first

act

ivity

; rei

nfor

ced

with

pre

tzel

s up

on

com

plet

ion

of e

ach

activ

ity (

with

draw

n af

ter

6 da

ys);

visu

al a

nd v

erba

l pro

mpt

s to

tr

ansi

tion

Dec

reas

es in

bot

h ch

alle

ngin

g be

havi

ors

and

incr

ease

s in

com

plia

nce

wer

e de

mon

stra

ted.

M T

au =

1, 8

5% C

I = [

0.52

0, 1

.480

]M

NA

P =

1, 8

5% C

I = [

0.52

0, 1

.480

]

Doe

s no

t m

eet

stan

dard

s

(con

tinue

d)

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5

Ref

eren

cePa

rtic

ipan

t(s)

Tra

nsiti

on(s

)T

opog

raph

yIn

terv

entio

n co

mpo

nent

sFi

ndin

gsD

esig

n qu

ality

Kut

tler,

Myl

es,

and

Car

lson

(1

998)

12-y

ear-

old

mal

e,

ASD

, FX

S,

inte

rmitt

ent

expl

osiv

e di

sord

er

WC

IV, D

FSN

: Soc

ial S

tori

es™

; cla

ssro

om p

ictu

re

sche

dule

; ind

ivid

ual p

ictu

re s

ched

ule;

re

info

rcem

ent

at d

esig

nate

d in

terv

als;

st

icke

r ch

arts

; poi

nt c

hart

s; t

oken

sys

tem

s

Dec

reas

es in

pre

curs

ors

to t

antr

um b

ehav

iors

wer

e di

spla

yed

upon

sy

stem

atic

intr

oduc

tion

and

with

draw

al o

f the

Soc

ial S

tory

™

com

pone

nt o

f the

inte

rven

tion.

M T

au =

0.9

89, 8

5% C

I = [

0.70

8, 1

.269

]M

NA

P =

0.9

94, 8

5% C

I = [

0.71

4, 1

.275

]

Doe

s no

t m

eet

stan

dard

s

Man

cil,

Hay

don,

an

d W

hitb

y (2

009)

Tw

o m

ales

and

one

fe

mal

e w

ith A

SD,

betw

een

ages

6

and

9

AC

AG

SN: S

ocia

l Sto

ry™

(pa

per

or c

ompu

ter

assi

sted

) re

ad d

urin

g la

st 5

min

of r

eadi

ng

time

All

stud

ents

dis

play

ed d

ecre

ases

in p

ushi

ng d

urin

g tr

ansi

tion

situ

atio

ns.

Pape

r: M

Tau

= 1

, 85%

CI =

[0.

753,

1.2

47]

CA

SST

: M T

au =

0.9

93, 8

5% C

I = [

0.76

9, 1

.218

]Pa

per:

M N

AP

= 1

, 85%

CI =

[0.

753,

1.2

47]

CA

SST

: M N

AP

= 0

.997

, 85%

CI =

[0.

740,

1.2

53]

Mee

ts s

tand

ards

w

ith r

eser

vatio

n

Mas

sey

and

Whe

eler

(20

00)

4-ye

ar-o

ld m

ale,

A

SDW

CA

GA

S: A

ctiv

ity s

ched

ule;

pro

mpt

s (v

erba

l, ge

stur

al, p

hysi

cal);

gra

duat

ed g

uida

nce

(mos

t-to

-leas

t)

Incr

ease

in t

ask

enga

gem

ent

duri

ng a

ll co

nditi

ons,

dec

reas

es in

ch

alle

ngin

g be

havi

or d

urin

g w

ork

and

lunc

h co

nditi

ons;

incr

ease

s in

ch

alle

ngin

g be

havi

ors

disp

laye

d du

ring

leis

ure

cond

ition

s.M

Tau

= 0

.555

, 85%

CI =

[0.

350,

0.7

60]

M N

AP

= 0

.778

, 85%

CI =

[0.

572,

0.9

83]

Doe

s no

t m

eet

stan

dard

s

Sain

ato,

Str

ain,

Le

febv

re, a

nd

Rap

p (1

987)

Tw

o 4-

year

-old

m

ales

and

one

3-

year

-old

mal

e,

seve

re A

SD

WC

, AC

OT

PM: T

rans

ition

with

a b

uddy

RF:

Chi

ld in

form

ed t

o go

to

area

and

rin

g be

ll

Both

inte

rven

tions

res

ulte

d in

incr

ease

s in

chi

ld r

ate

of m

ovem

ent

duri

ng t

rans

ition

s; h

owev

er, t

he b

ell s

eem

ed t

o ha

ve m

ore

dram

atic

im

prov

emen

t; de

crea

ses

in t

each

er p

rom

pts

wer

e ob

serv

ed a

s w

ell.

PM: M

Tau

= 0

.863

, 85%

CI =

[0.

690,

1.0

36]

RF:

M T

au =

0.9

95, 8

5% C

I = [

0.67

8, 1

.288

]PM

: M N

AP

= 0

.932

, 85%

CI =

[0.

758,

1.1

05]

RF:

M N

AP

= 0

.997

, 85%

CI =

[0.

827,

1.1

68]

Mee

ts s

tand

ards

w

ith r

eser

vatio

n

Schm

it, A

lper

, R

asch

ke, a

nd

Ryn

dak

(200

0)

6-ye

ar-o

ld m

ale,

A

SDW

C, A

C, E

SA

GA

S: P

hoto

grap

hic

cue

of n

ext

activ

ity

pres

ente

d to

chi

ld p

rior

to

tran

sitio

n tim

e al

ong

with

ver

bal c

ues

Giv

ing

adva

nce

notic

e of

an

activ

ity c

hang

e in

com

bine

d fo

rm o

f ve

rbal

and

pho

togr

aphi

c cu

es h

elpe

d to

red

uce

chal

leng

ing

beha

vior

M T

au =

0.8

20, 8

5% C

I = [

0.59

8, 1

.042

]M

NA

P =

0.9

10, 8

5% C

I = [

0.68

8, 1

.132

]

Doe

s no

t m

eet

stan

dard

s

Wat

ers,

Ler

man

, an

d H

ovan

etz

(200

9)

Tw

o 6-

year

-old

m

ales

, ASD

WC

AG

AS:

Vis

ual s

ched

ule

alon

e an

d w

ith D

RO

RF:

DR

O w

ithou

t sc

hedu

leIn

the

vis

ual s

ched

ule

only

con

ditio

n, t

here

was

no

chan

ge in

fr

eque

ncy

of c

halle

ngin

g be

havi

or. W

ith t

he in

clus

ion

of D

RO

and

ex

tinct

ion,

cha

lleng

ing

beha

vior

dec

reas

ed fo

r bo

th p

artic

ipan

ts.

Best

res

ults

with

vis

ual s

ched

ule,

DR

O a

nd e

xtin

ctio

n pr

oced

ures

im

plem

ente

d.A

S: M

Tau

= 0

.548

, 85%

CI =

[0.

242,

0.8

53]

RF:

M T

au =

0.8

58, 8

5% C

I = [

0.45

4, 1

.262

]A

S: M

NA

P =

0.7

74, 8

5% C

I = [

0.46

9, 1

.079

]R

F: M

NA

P =

0.9

29, 8

5% C

I = [

0.52

5, 1

.333

]

Doe

s no

t m

eet

stan

dard

s

Not

e. A

SD =

aut

ism

spe

ctru

m d

isor

der;

WC

= w

ithin

cla

ssro

om t

rans

ition

; IV

= in

appr

opri

ate

voca

lizat

ions

; SN

= s

ocia

l nar

rativ

es; D

S =

dis

crim

inat

ive

stim

ulus

; CI =

con

fiden

ce in

terv

al; N

AP

= n

on-o

verl

ap o

f all

pair

s; P

DD

-N

OS

= p

erva

sive

dev

elop

men

tal d

isor

der–

not

othe

rwis

e sp

ecifi

ed; A

C =

acr

oss

clas

sroo

m t

rans

ition

s; O

T =

off

task

; HP

= h

igh-

p pr

oced

ure;

ES

= e

nter

ing/

exiti

ng s

choo

l tra

nsiti

on; A

G =

agg

ress

ion;

AS

= a

ctiv

ity s

ched

ules

; D

F =

drop

ping

to

the

floor

; VM

= v

ideo

mod

els;

EP

= el

opem

ent;

NS

= no

t sp

ecifi

ed; F

XS

= fr

agile

X s

yndr

ome;

CA

SST

= C

ompu

ter-

Ass

iste

d So

cial

Sto

ry™

; PM

= p

eer-

med

iatio

n; R

F =

rein

forc

emen

t-ba

sed

proc

edur

es; D

RO

=

diffe

rent

ial r

einf

orce

men

t of

oth

er b

ehav

ior.

Tab

le 1

. (c

ont

inue

d)

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6 Journal of Positive Behavior Interventions

as meeting all inclusion criteria by the first author and 10 randomly selected studies coded as not meeting all inclu-sion criteria by the first author (M = 99.3%; range = 83.3%–100%). For article evaluation, the first and third author independently extracted data on targeted behavioral topog-raphy, targeted transition, main component of intervention, and findings for each study (M = 98.2%, range = 75%–100%). For research design quality, the first and third authors independently coded each included study using the research design quality checklist described in the previous section (M = 98.1%; range = 90.9%–100%). Following independent initial coding for each type of IOA, authors discussed each disagreement until consensus on how an item should be coded was reached.

Results

Overview of Study Characteristics

Each study included one to four participants, with a total of 28 participants. Of the 28 participants from the included studies, 89% had diagnoses of ASD (n = 25 participants), 11% had diagnoses of pervasive developmental disorder–not otherwise specified (PDD-NOS; n = 3 participants), and 86% were male (n = 24 participants). Participants ranged in age from 3 to 13 years. All but one study had natural change agents (i.e., staff who regularly work with the student) implementing the intervention procedures for transitions and all transitions occurred in authentic settings. Nine stud-ies examined the effects of intervention strategies in segre-gated settings, four evaluated intervention effects in inclusive settings, and one study analyzed intervention effects in a home-based educational program. A summary of the included studies can be found in Table 1.

For each variable analyzed quantitatively, the number of contrasts (i.e., the number of times a phase without an inter-vention is compared with a phase with an intervention) used to calculate effect sizes is important to consider when inter-preting effect sizes. More contrasts included in effect size calculations allow for increased confidence of interpreta-tions using effect sizes. The number of contrasts was calcu-lated for each variable of interest: AS (n = 55 contrasts), SN (n = 47), HP (n = 8), VM (n = 20), RF (n = 5), PM (n = 3), aggression (n = 65), off-task behavior (n = 54), inappropri-ate vocalizations (n = 19), dropping to the floor (n = 14), elopement (n = 4), across classroom transitions (n = 37), within classroom transitions (n = 54), and entering or exit-ing school transitions (n = 2).

Main Component of Intervention

Effect sizes for most of the main components of the inter-ventions suggested strong effects: AS (n = 15 participants; M = 0.934, 85% CI = [0.858, 1.011]), SN (n = 5; M = 0.998,

85% CI = [0.858, 1.137]), VM (n = 8; M = 0.964, 85% CI = [0.819, 1.110]), RF (n = 5; M = 0.987, 85% CI = [0.830, 1.144]), and PM (n = 3; M = 0.932, 85% CI = [0.758, 1.105]). One study (Banda & Kubina, 2006) evaluated the effects of using HP on the behavior of one participant. The effect size for this study was 0.678, 85% CI = [0.463, 0.893], suggesting only a moderate effect in reducing off-task behavior during transitions. The effect size and CI of effect sizes of each study according to the main component of the intervention under evaluation in the study are visually displayed in a forest plot in Figure 1. Considering the qual-ity of the studies, one study that evaluated the use of SN was coded as MS. Nine studies met standards with reserva-tions (MSR) and assessed the use of AS (n = 3 studies), SN (n = 1), HP (n = 1), VM (n = 2), RF (n = 1), and PM (n = 1). Six studies were categorized as NMS; those studies evalu-ated the use of AS (n = 5), SN (n = 1), and RF (n = 1). A table that summarizes the results of the research design quality analysis is available from the authors on request.

Topography of Challenging Behavior

Similarly, the majority of the studies assessing the effects of interventions on various topographies of challenging behav-iors demonstrated strong effects: off-task behavior (n = 8 participants; M = 0.943, 85% CI = [0.864, 1.021]), inappro-priate vocalizations (n = 3; M = 1, 85% CI = [0.816, 1.184]), dropping to the floor (n = 3; M = 0.967, 85% CI = [0.759, 1.175]), and elopement (n = 1; M = 0.964, 85% CI = [0.552, 1.305]). Studies evaluating off-task behavior used the fol-lowing interventions: AS (n = 5; M = 1, 85% CI = [0.884, 1.116]), HP (n = 1; M = 0.678, 85% CI = [0.463, 0.893]), RF (n = 3; M = 0.997, 85% CI = [0.827, 1.168]), and PM (n = 3; M = 0.932, 85% CI = [0.758, 1.105]). Interventions used to evaluate inappropriate vocalizations include AS (n = 1; M = 1, 85% CI = [0.520, 1.480]), SN (n = 2; M = 1, 85% CI = [0.782, 1.218]), and VM (n = 1; M = 1, 85% CI = [0.520, 1.480]). Studies that assessed the effects of interventions on dropping to the floor used AS (n = 1; M = 0.975, 85% CI = [0.458, 1.442]), SN (n = 1; M = 0.987, 85% CI = [0.581, 1.134]), and VM (n = 2; M = 0.953, 85% CI = [0.672, 1.234]). The study that examined intervention effects on decreasing elopement for one participant used VM (M = 0.964, 85% CI = [0.552, 1.305]).

Combined, studies targeting aggression established moderate effects (n = 13 participants; M = 0.905, 85% CI = [0.815, 0.994]). Studies evaluating the effects of interven-tion on decreasing aggression during transitions analyzed the effects of AS (n = 9; M = 0.852, 85% CI = [0.733, 0.970]), SN (n = 3; M = 0.998, 85% CI = [0.832, 1.164]), VM (n = 4; M = 0.964, 85% CI = [0.757, 1.171]), and RF (n = 2; M = 0.929, 85% CI = [0.525, 1.333]). Figure 2 visu-ally depicts the effect sizes and CIs of individual studies according to the topography of the challenging behavior.

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Lequia et al. 7

Figure 1. Forest plot of aggregated NAP and confidence intervals of effect sizes according to the main component of the intervention.Note. Vertical lines represent the suggested interpretation criteria (i.e., weak, moderate, strong) for effect sizes. NAP = non-overlap of all pairs.

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8 Journal of Positive Behavior Interventions

Figure 2. Forest plot of aggregated NAP and confidence intervals of effect sizes according to the topography of challenging behavior.Note. Vertical lines represent the suggested interpretation criteria (i.e., weak, moderate, strong) for effect sizes. NAP = non-overlap of all pairs.

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Lequia et al. 9

Considering research quality indicators, one study that evaluated intervention effects on dropping to the floor was coded as MS. Eleven studies were coded as MSR and assessed intervention effects on aggression (n = 4 studies), off-task behavior (n = 3), inappropriate vocalizations (n = 1), dropping to the floor (n = 2), and elopement (n = 1). Seven studies were categorized as NMS; those studies eval-uated the effects of interventions on aggression (n = 4), off-task behavior (n = 1), inappropriate vocalizations (n = 1), and dropping to the floor (n = 1).

Targeted Transitions

When considering transition type, intervention effects addressing both across classroom transitions (n = 15 partici-pants; M = 0.990, 85% CI = [0.802, 1.178]) and within classroom transitions (n = 18; M = 0.940, 85% CI = [0.855, 1.025]) demonstrated strong effects. Six studies examined interventions during transitions across different classrooms in the same building, but only two of those studies reported data specifically on across classroom transitions; the others combined intervention results for different types of transi-tions. For studies addressing across classroom transitions, the effects of AS (n = 1; M = 0.945, 85% CI = [0.414, 1.367]), VM, HP, SN (n = 3; M = 0.998, 85% CI = [0.832, 1.164]), RF, and PM on transition behaviors were evalu-ated. Nine of the 14 included studies (64%) assessed inter-vention effects during transitions within a classroom, with only 6 studies reporting data explicitly on within classroom transitions. The studies assessing effects of interventions for within classroom transitions included AS (n = 8; M = 0.929, 85% CI = [0.525, 1.333]), VM, SN (n = 2; M = 0.997, 85% CI = [0.806, 1.189]), PM, HP, and RF (n = 2; M = 0.929, 85% CI = [0.525, 1.333]). The combined effect sizes and CIs according to the type of transition expected of the student with ASD for each study are visually displayed in a forest plot in Figure 3.

Overall, the intervention effects for transitions for enter-ing or exiting school transitions suggested moderate effects (n = 11 participants), with a combined effect size of 0.853, 85% CI = [0.586, 1.120]. Four studies (29%) evaluated the effects of interventions on improving entering or exiting school transitions, with two explicitly reporting data on these transitions. Studies evaluating the effects of interven-tions on transition behaviors during these specific transi-tions examined the use of VM and AS (n = 2 participants; M = 0.853, 85% CI = [0.586, 1.053]). Considering the qual-ity of the included studies, one study that evaluated inter-vention effects on within classroom transitions was coded as MS. Twelve studies were coded as MSR and assessed intervention effects on within classroom transitions (n = 4 studies), across classroom transitions (n = 5), and entering or exiting school transitions (n = 3). Six studies were cate-gorized as NMS; those studies evaluated the effects of

interventions on within classroom transitions (n = 4), across classroom transitions (n = 1), and entering or exiting school transitions (n = 1).

Discussion

Despite the limited number of studies addressing transition difficulties for students with ASD in educational settings, this review indicates that all strategies evaluated in the lit-erature show promising effects. Across all variables ana-lyzed, there was overlap in the CIs of the mean effect sizes at the 85% confidence level. Thus, despite variability among average effect sizes across categories, we cannot say that the effects of interventions were significantly different between the different main components of intervention, the different topographies of challenging behavior, or the dif-ferent types of transitions. However, Figures 1 to 3 illustrate the variability in the amount of evidence included in the literature supporting the effects across these variables. As relevant studies are added to the literature, future quantita-tive syntheses should consider moderator analyses to ana-lyze potential interactions among these variables as well as participant characteristics that may contribute to and explain this variability. Below we provide an informal examination of the possible trends among and differences between inter-vention variables and possible interactions.

First, however, it is important to note several limitations of the current review. Selection bias may be reflected in the data provided by the included studies due to the lack of ran-dom assignment of participants to phases, or tiers in multiple baseline studies; this ultimately causes gaps in the conclu-sions we are able to draw. In addition, overall, there were a small number of participants and some studies only included one participant, which may limit the external validity of the data provided. Last, authors of the article completed the IOA procedures, which may lead to skewing of the IOA data.

Acknowledging these limitations, emerging trends are still evident when considering the variables of interest. Across the main components of intervention packages, AS resulted in highly variable effects, with more participants demonstrating moderate effects than strong effects. Other interventions (e.g., SN, VM) reported strong effects for more participants compared with the other strategies, sug-gesting that they may be most promising in addressing tran-sition difficulties. Across behavioral topographies, effect sizes suggest that interventions are more effective in reduc-ing less severe behaviors. For example, studies demonstrate only moderate effects in improving transitions in students who display aggression, while strong effects were demon-strated for students who display off-task behavior. No trends were evident in effect sizes for interventions across transi-tion type. However, there were fewer studies, and thus fewer demonstrations of experimental effects for entering or exiting school transitions.

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10 Journal of Positive Behavior Interventions

Figure 3. Forest plot of aggregated NAP and confidence intervals of effect sizes according to the type of transition.Note. Vertical lines represent the suggested interpretation criteria (i.e., weak, moderate, strong) for effect sizes. NAP = non-overlap of all pairs.

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Lequia et al. 11

Concurrent analyses of the main component of interven-tion within different topographies of behavior suggest cer-tain intervention strategies may be more promising in reducing specific topographies of challenging behaviors during transitions. For aggression, results indicated that SN and VM are promising techniques, whereas AS and RF both only resulted in moderate effects. For off-task behavior, three strategies (i.e., AS, RF, and PM) showed promising effects in improving student behavior during transitions. AS, SN, and VM were all found to have strong effects in reducing inappropriate vocalizations and dropping to the floor. Strong effects were also demonstrated using VM to reduce elopement.

Only a few of the studies included in the review reported data separately for the type of transition that was being tar-geted; but for those few, effect sizes were analyzed to deter-mine which intervention component was most effective for specific transitions. For within classroom transitions, results indicated that SN is a promising technique whereas AS and RF both only resulted in moderate effects. For across class-room transitions, both AS and SN demonstrated strong effects in improving student behavior. In terms of entering or exiting school transitions, the use of AS was examined and found to be moderately effective.

Different types of transitions require varying levels of response effort from the student, which can directly influ-ence the effectiveness of a behavioral intervention (Buckley & Newchok, 2005). Consider within classroom versus entering or exiting school transitions. Within classroom transitions consist of wrapping up one activity and moving to another within fairly close proximity. In contrast, enter-ing or exiting school transitions might consist of several expectations: finishing an activity that they are currently working on, putting materials away, identifying the materi-als that need to be brought home, and gathering belongings. This may explain why interventions targeting entering or exiting school transitions reported only moderate effect sizes.

Sterling-Turner and Jordan (2007) emphasized the importance of functional behavior assessments (FBA) in the selection of interventions. Three of the studies included in the current review utilized FBA procedures, which sup-ports the findings of a review suggesting that successful interventions for addressing the challenging behaviors of students with ASD in educational settings frequently did not utilize FBAs (Machalicek, O’Reilly, Beretvas, Sigafoos, & Lancioni, 2007). Given the emphasized importance of using FBAs in selecting interventions (Cooper, Heron, & Heward, 2007), procedures specific to transitions may need to be explored. For example, practitioners may consider evaluating the variables such as location change, activity initiation or termination, and preference of activity (McCord, Thomson, & Iwata, 2001) in their direct observa-tions during FBAs.

Practitioners must also consider the evidence base for an intervention for a specific context, but there is no easy method to do so. The use of forest plots to visually display data from a combination of studies with similar characteris-tics (e.g., targeted transition), in combination with consider-ation of the number of contrasts and the quality of the study, can facilitate appropriate interpretation of the evidence base of particular interventions by practitioners. The creation of a national database for special education intervention researchers to enter SCR data, which output forest plots of aggregate data from studies meeting minimal quality requirements, is a practical way to increase the dissemina-tion and accurate interpretation of the evidence behind par-ticular interventions. Due to the variation of intervention effects across this population of students, practitioners will still need to assess the ongoing effects of the intervention on student behavior to ensure optimal outcomes and identify alternative strategies as needed (Kalberg, Lane, & Menzies, 2010; Snell & Brown, 2011).

AS were the most commonly investigated intervention strategy across studies in this review. However, AS demon-strated variable effects (see Figure 1) in decreasing problem behavior associated with moving from one activity to another within a classroom. In addition, across interven-tions, studies that investigated AS had the highest propor-tion that did not meet quality standards. Therefore, we suggest that there is a need for more research, with increased rigor, to investigate the effects of AS. We also suggest future researchers investigate other interventions that have, thus far, shown to be highly effective for improving within class-room transitions, such as VM and SN to determine whether these strong effects are replicable. Comparison of effects across different types of interventions during various types of transitions is an important consideration for future research efforts.

Most of the included studies were coded as MS or MSR. Only half of the studies examined procedural integrity using either self-report or direct observation, and just over half of the studies considered social validity or maintenance of the intervention under examination. The use of a typically developing peer as a comparison is a potential method to objectively address the social validity of interventions, given that transitioning from one activity to the next is a high frequency and sometimes challenging task for students regardless of disability status. Researchers should also report data separately for each type of transition because, as evinced from this review, interventions were associated with differential effects across transition types.

Conclusion

The literature identifies a handful of effective strategies in improving transition behaviors in students with ASD in educational settings. Although AS have the most studies

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12 Journal of Positive Behavior Interventions

evaluating their effectiveness during transitions, results suggest that other strategies are also effective. Forest plots are a promising mode for practitioners to determine and keep current on the evidence behind various interventions. In addition, researchers need to increase the quality of stud-ies used to evaluate intervention effects on challenging behaviors evoked by transitions in educational settings. Improving transition behaviors in educational settings may lead to other socially significant outcomes, including increased time spent in academic instruction and increased inclusion in general education settings.

Declaration of Conflicting Interests

The author(s) declared no potential conflicts of interest with respect to the research, authorship, and/or publication of this article.

Funding

The author(s) received no financial support for the research, authorship, and/or publication of this article.

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