Key Words auditory training - autism spectrum disorder - remote microphone technology
INTRODUCTION
Individuals diagnosed with autism spectrum disorder (ASD) exhibit auditory dysfunction
and deficits in social communication ([Tomchek and Dunn, 2007 ]; [Ashburner et al, 2008 ]; [American Psychiatric Association, 2013 ]; [Schafer et al, 2013 ]; [2016 ]). More specifically, parents of children with ASD report that their children have
atypical auditory filtering and processing, difficulty attending to auditory stimuli,
distractibility, and dysfunction in noisy environments ([Tomchek and Dunn, 2007 ]; [Ashburner et al, 2008 ]). In addition, many individuals with ASD display significantly poorer speech recognition
in noise, temporal processing, and spatial processing (i.e., binaural integration)
than age-matched, typically developing peers ([Alcántara et al, 2004 ]; [Schafer et al, 2013 ]; [Rance et al, 2014 ]). Strategies to enhance the auditory performance of children and young adults with
ASD are paramount, given the poor acoustics and high levels of noise found in typical
school classrooms paired with the academic difficulties that most children with ASD
experience ([Cruckley et al, 2011 ]).
Two management approaches to address the auditory deficits in individuals with ASD
include the use of remote microphone (RM) technology and the completion of auditory
training. RM technology, consisting of a microphone coupled to a transmitter for the
primary talker and open-ear receivers for individuals with normal pure-tone hearing,
is a highly beneficial strategy that improves speech recognition in noise, auditory
comprehension, acceptance of noise, on-task behaviors, teacher- and parent-rated auditory
listening behaviors, physiologic stress levels, and self-perceived listening difficulty
([Schafer et al, 2013 ]; [2014b ]; [2016 ]; [Rance et al, 2014 ]; [2017 ]).
Although this technology addresses the effects of external noise and poor acoustics,
few research studies have investigated strategies to improve auditory processing abilities
in individuals with ASD. One strategy that has gained some attention in ASD and other
populations is the use of dichotic auditory training (i.e., practice identifying different
stimuli presented to the two ears), given that dichotic listening or binaural integration
is generally poor in individuals with ASD ([Hayashi et al, 1989 ]; [Kozou et al, 2018 ]). In one study, three participants with ASD showed improved language and auditory
processing following 12 weeks of dichotic listening training ([Denman et al, 2015 ]), and more recently, four sessions of dichotic training improved dichotic scores
in 125 children and adolescents who had auditory processing deficits, unilateral ear
weaknesses, and binaural interaction deficits ([Moncrieff et al, 2017 ]). In addition, auditory training with speech-in-noise and dichotic stimuli improved
auditory processing abilities in 39 children diagnosed with APD ([Loo et al, 2016 ]).
Given the documented benefits of RM technology and the potential benefits of dichotic
and speech-based training for individuals diagnosed with ASD, the purpose of the present
study was to determine the efficacy and effectiveness of a 12-week auditory processing
training (APT) program for children and young adults with ASD. The program consists
of computerized dichotic training, one-on-one therapist-directed auditory training,
and the use of RM technology at home and in the classroom.
METHODS
Before the candidacy screening, assent was obtained from children aged less than 18
years, and signed consent forms were obtained from parents of those children and adult
participants. Candidates for the study were required to pass a pure-tone air conduction
hearing screening in each ear at 15-dB HL for 500–8000 Hz (audiometer: GSI-51 [Grason
Stadler, Eden Prairie, MN]; headphones: TDH-50 [Telephonics, Farmingdale, NY]), have
normal middle ear function as measured by Type A tympanograms (Maico MI34; Maico Diagnostics,
Eden Prairie, MN), and have normal nonverbal intelligence (i.e., ≥70) on the Comprehensive
Test of Nonverbal Intelligence—Second Edition ([Hammill et al, 2009 ]).
Participants
This study was approved by the Institutional Review Board at the University of North
Texas. The 15 participants who met the inclusion criteria were high functioning and
aged between 7 and 22 years with a formal diagnosis of ASD as his (n = 10) or her
(n = 5) primary disability ([Table 1 ]). According to the parent report, the participants were diagnosed with ASD by a
licensed specialist in school psychology, a pediatric neurologist, a developmental
pediatrician, or a school diagnostician. Participants had no reported otologic history.
According to the case history form summarized in [Table 2 ], all participants had major listening difficulties in numerous situations. All participants
were right-handed (two participants used both hands for some tasks).
Table 1
Participant Demographic Characteristics
Subject No.
Age (years; months)
Gender
Other Disabilities
% of CAPDOTS Completed
Test Sessions Completed
1
9; 6
F
ADHD and APD
80
1, 2, and 3
2
21; 9
M
ADHD
67
1, 2, and 3
3
7; 5
M
ADHD
91
1, 2, and 3
4
7; 11
M
ADHD, language disability, and anxiety disability
51
1, 2, and 3
5
14; 7
M
ADHD and SLI
100
1, 2, and 3
6
10; 3
M
Language disability
51.1
1, 2, and 3
7
12; 0
F
SLI and language disability
89
1, 2, and 3
8
20; 6
M
ADHD, learning disability, and APD
88
1 and 2
9
16; 4
F
Anxiety disabiity
100/98.1
1 and 2
10
21; 8
F
ADHD and anxiety disability
100/73.1
1 and 2
11
21; 5
F
ADHD
100/73.1
1 and 2
12
10; 2
M
Language disability
100/71.1
1 and 2
13
15; 10
M
Did not complete form
100/31.1
1 and 2
14
9; 5
M
Did not complete form
100/88.9
1 and 2
15
15; 7
M
Language disability
100
1 and 2
Note: Some participants repeated the CAPDOTS program within the 12-week training period.
ADHD = attention-deficit hyperactivity disorder; APD = auditory processing disorder;
SLI = specific language impairment.
Table 2
Parent- or Participant-Reported Listening Difficulties
Participant Number
Listening situation
In most situations
1, 5, 7, 9, 10, 11, and 15
In small groups
5, 7, 9, and 15
In large groups
3, 4, 5, 6, 8, 9, 10, 12, and 15
In the classroom
4, 5, 6, 7, 8, 9, 10, and 15
At parties
3, 4, 5, 8, 9, 10, 11, 12, and 15
In restaurants
3, 4, 5, 7, 8, 9, 10, 15
In other social situations
3, 9, 10, 11, 12, and 15
Listening problems
Paying attention
1, 2, 3, 4, 5, 6, 7, 8, 10, and 15
Easily distracted
1, 2, 3, 4, 5, 6, 7, 8, 10, 11, 12, and 15
Confused in noisy situations
1, 3, 4, 5, 6, 7, 8, 10, 11, and 12
Difficulty following directions
1, 3, 5, 6, 7, 8, 9, 11, and 15
Sensitive to loud sounds
1, 2, 3, 4, 5, 6, 7, 8, 10, 11, and 12
Easily upset by new situations
1, 3, 5, 7, 9, 10, and 11
Difficulty sitting still
3, 4, 5, 8, 9, 10, 11, and 12
Impulsive
2, 4, 5, 8, 9, 10, and 12
Often daydreams
1, 2, 3, 5, 7, 9, 10, 11, 12, and 15
Often asks for repetition
1, 3, 5, 6, 7, 9, 10, and 11
Prefers to play/do activities alone
3, 5, 7, 8, 10, 11, and 12
Yelling or rowdy behavior
5, 6, and 9
Shy and anxious
3, 5, 6, 7, 9, 10, and 15
Lacks self confidence
5, 7, 9, 10, 11, 12, and 15
Does not complete assignments
1, 5, 7, 8, and 10
Easily frustrated
1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, and 15
Test Measures and Questionnaires
The behavioral test measures for this study are detailed in [Table 3 ] and were selected to represent a broad range of auditory processing skills. Participants
were asked to complete three, two-day test sessions (three hours each) conducted at
baseline (Pretest), immediately after completing the 12-week APT program (Posttest
1), and 12 weeks after the APT program was completed (Posttest 2). Fifteen participants
completed the first and second test sessions, and seven participants agreed to complete
the third session (participants 1–7). Some participants were unable to complete all
test measures because of fatigue, lack of focus, unreliability, or unwillingness to
cooperate.
Table 3
Detailed Descriptions of Behavioral Test Measures
Test Name
General Description
Test Detail
TAPS-3
Hierarchy of Aud. processing skills needed for development, use, and understanding
of language in academic and everyday settings
Word discrimination, Phon. segmentation, Phon. blending, numbers forward and reversed,
word memory, sentence memory, Aud. comprehension, and Aud. reasoning
CELF-5
Examines understanding of spoken directions, recall of information, and recognition
of pictured objects
Following Directions subtest
BKB-SIN test—two-list pairs
Estimates the SNR necessary for the listener to repeat 50% of key words in multitalker
babble
Determined dB SNR with loudspeakers at 0°; also tested live voice—5 dB SNR (speech
60/noise 65) with and without RM technology to yield % correct.
ANL test
Quantifies SNR listener is willing to accept or “put up with” for a long period of
time
Tested with and without RM technology, male talker at 0° azimuth, noise at 180°, and
ANL repeated twice and averaged
LiSN-S
Evaluates the listener’s ability to separate stimuli differing in space (±0° azimuth
vs. ±90° azimuth) and vocal quality (same vs. different voices)
Low-cue SRT: no spatial/vocal cues available; high-cue SRT: both vocal/spatial cues
available; talker Adv: use of different vocal characteristics; spatial Adv: use differences
in the physical location; and total Adv: use of talker and spatial Adv cues
DWT and RDDT
Assess binaural integration or significant ear differences for dichotic word or digit
stimuli.
Stimuli include 4 lists of 25 word pairs and 2 lists of 54 sets of 1-, 2-, and 3-digit
pairs. Stimuli presented simultaneously to ears; listener asked to repeat stimuli
free recall
Child Sensory Profile 2
Parent ranks child’s sensory processing patterns on a scale of 5 (almost always) to
1 (almost never) in the context of everyday situations
Ratings analyzed for audition, social–emotional, attention, seeking/seeker, avoiding/avoider,
sensitivity/sensor, and registration/bystander
LIFE-R—student and teacher version
Teacher or student rates his or her own classroom listening abilities as compared
with peers on a scale of 5 (always easy) to 1 (always difficult)
No listening challenges = 75
Occasional listening challenges = 60
Sometimes challenged = 45
Often or regularly has challenges = 30
Almost always challenged = 15
CHAPS
Teacher rates listening behaviors in the classroom relative to peers on a scale from
+1 (less difficulty) to −5 (cannot function at all)
Rating averaged across conditions to determine if child is at-risk for academic issues:
noise, quiet, ideal conditions, multiple inputs, auditory memory sequencing, auditory
attention span
Adv = advantage; Aud. = auditory; Phon. = phonological.
General auditory processing abilities were evaluated with the Test of Auditory Processing
Skills—Third Edition (TAPS-3; [Martin and Brownell, 2005 ]) and the Clinical Evaluation of Language Fundamentals—Fifth Edition (CELF-5; [Wiig et al, 2013 ]) Following Directions subtest. Stimuli were presented as live voice by the examiner
who was seated approximately three feet from the participant in a quiet room.
Speech recognition in noise and acceptance of noise were assessed with the Bamford–Kowal–Bench
Speech-in-Noise ([BKB-SIN, 2005 ]) and the Acceptable Noise Level ([ANL, 2009 ]) tests, respectively, in a sound booth. The BKB-SIN stimuli, which are prerecorded
on a compact disc, were presented from a loudspeaker located at 0° azimuth. This test
yields a 50% correct speech-in-noise threshold in dB SNR (i.e., SNR-50). In addition
to the threshold testing, following the 12-week training period, separate lists of
the BKB-SIN test were used to assess percent-correct speech recognition in noise with
fixed signal levels (−5-dB SNR) with and without the RM technology (Phonak Roger Focus;
Sonova USA Incorporated Phonak, Warrenville, IL). In these conditions, the examiner
presented the sentence stimuli through the audiometer microphone (i.e., monitored
live voice at 65-dBA/55-dB HL) in the no-technology condition and both the audiometer
microphone and the Roger Pen transmitter microphone (6 in. from the mouth) in the
RM technology condition. The fixed-intensity noise (70-dBA/60-dB HL) was presented
from the BKB-SIN compact disc.
The Listening in Spatialized Noise-Sentences Test (LiSN-S) ([Cameron and Dillon, 2007 ]) software, administered under circumaural headphones (Sennheiser HD 215), assesses
spatial processing abilities in five conditions. The low-cue speech reception threshold
(SRT) condition presents the speech and masker at 0° azimuth, and the high-cue SRT
condition presents the speech at 0° and noise at ±90° azimuth. The three remaining
conditions yield different scores in dB to assess the potential benefit of (a) same
versus different talkers for the stimulus and masker presented at 0° azimuth (talker
advantage), (b) same talkers with noise at 0° versus ±90° azimuth (spatial advantage),
and (c) same stimulus and masker at 0° versus different stimulus and masker with speech
at 0° and the masker at ±90° azimuth (total advantage). Binaural integration was assessed
with the Dichotic Words Test (DWT) and Randomized Dichotic Digits Test (RDDT), which
were administered under circumaural headphones (Sennheiser HD 215) using the Audia
Dichotic software ([Dichotics, Inc., n.d. ]).
Participants who were able to reliably complete questionnaires were asked to complete
the Listening Inventory for Education—Revised (LIFE-R; [Anderson et al, 2011 ]). Parents of children (≤14 years) were asked to complete the Sensory Profile 2 ([Dunn, 2014 ]), and classroom teachers of the children (≤18 years) were asked to complete the
teacher version of the LIFE questionnaire and the Children’s Auditory Performance
Scale (CHAPS; [Smoski et al, 1998 ]).
Auditory Processing Training Program
The APT program required participants to complete a one-hour training session three
times/week for 12 weeks in the laboratory and to use RM technology at home and school.
Each training consisted of 30 minutes of an active, web-based dichotic integration
listening training known as the Central Auditory Processing Disorder Online Therapy
System ([CAPDOTS-Integrated, 2018 ]) and 30 minutes of one-on-one, clinician-developed, auditory training in a quiet
room.
CAPDOTS is a dichotic listening training program that uses interaural and adaptive
lead–lag timing differences to improve binaural integration skills of different speech
stimuli (words, numbers, and syllables). Its goal is similar to the dichotic interaural
intensity difference (DIID) training ([Weihing and Musiek, 2014 ]) but differs from DIID in approach. DIID uses interaural intensity or loudness differences.
However, with CAPDOTS, the dichotic stimuli are equal in intensity in each ear but
only differ in the timing of the presentation stimuli. CAPDOTS is a free-recall training
program whereby the participant repeats what is heard in both ears and is not required
to repeat a specific side (left or right) first, as is the case in directed-ear exercises.
Directed-ear exercises require higher levels of cognitive control and executive function
([Hugdahl et al, 2009 ]). As with all free-recall exercises, there is no need to identify a dominant ear.
With this in mind, CAPDOTS exercises are balanced with half of the items presented
on the left side first, followed by the right side after a prescribed lag time. The
other half of the items are presented to the right side, followed by the left side
after a prescribed lag time. Again, the participant’s order of response was not a
scoring factor. Handedness, also, is not a necessary consideration during training.
A graduate student serving as a test assistant was seated next to the participant
to record all correct responses. CAPDOTS was administered via a laptop computer and
supra-aural headphones (Sony ZX310; Sony Corporation of America, New York, NY). The
percentage of CAPDOTS completion is shown in [Table 1 ]. Participants who have two percentages completed the program and began the program
a second time.
The 30 minutes of one-on-one adaptive training activities were individualized for
each participant based on Pretest functioning levels on the TAPS-3 and CELF-5. In
addition to examining overall subtest scores for each participants, the speech-language
pathologist noted where breakdowns started to occur (e.g., repeating sentences with
three major components) to determine appropriate tasks for each participant. Training
tasks included (a) following directions (e.g., “point to the boy with brown hair”),
(b) word and sentence repetition (e.g., repeat three word set: “row, baby, and light”),
and (c) auditory comprehension (e.g., three components: “Sam/went to the park/to play
on the slide.”; “Where the boy did he go?”; “What was the boy’s name who went?”; and
“What did he play on?”). Training stimuli were presented in quiet and increasing levels
of background noise (i.e., quiet room, 45, 50, 55, and 60 dBA). The noise level was
increased by one step each time the task was mastered with 80% accuracy. Linguistic
complexity was increased by 5 dB once a particular level was mastered at each of the
four background noise levels. The overall goal was to achieve maximum linguistic functioning
at noise levels experienced in everyday listening situations.
After the first testing session, the participants were fit with bilateral Roger Focus
receivers with a small dome used in conjunction with a Roger Pen transmitter. Appropriate
volume settings on the receivers were determined using the Desired Sensation Level
v5 prescriptive targets for 15-dB HL hearing thresholds as measured with the Audioscan
Verifit 2 (Audioscan, Dorchester, Ontario) ([Scollie et al, 2005 ]; [Schafer et al, 2014a ]). During the 12-week training period, the participants were asked to use the RM
technology at home and at school during direct instruction from the teacher. It is
important to note that the investigators could not determine exact hours of RM technology
use per day; however, parents and participants confirmed that the system was used
on a regular basis.
RESULTS
Average raw scores across TAPS-3 subtests are shown in [Figure 1 ]. According to a paired t -test, the average raw scores significantly improved on six subtests. However, average
raw scores on the CELF-5 Following Directions subtest were not significantly different
between Pretest (M = 20.1; standard deviation [SD] = 8.8) and Posttest 1 [M = 22.0; SD = 6.9; t
(14) = −1.7, p = 0.06, one-tailed].
Figure 1 Average raw scores on the TAPS pre- and post-APT program (N = 15). Data were analyzed
with a paired t -test; statistical results are provided. Vertical lines represent one SD.
Average BKB-SIN thresholds (n = 15) were not significantly different between Pretest
(M = 0.76 dB; SD = 3.0) and Posttest 1 (M = −0.14 dB; SD = 2.2) [t
(14) = −0.14, p = 0.44]. Similarly, the average ANLs (n = 14) were not significantly different at
Pretest (M = 4.3 dB; SD = 9.0) and Posttest 1 (M = 4.7 dB; SD = 6.7) [t
(14) = −0.14, p = 0.44].
However, when comparing the performance in the no-technology condition (M = 63.3%; SD = 28.5) with the RM technology condition (M = 99.6%; SD = 0.93), a paired t -test (n = 11) showed a significant average improvement [t
(11) = −4.1, p = 0.001] in percent-correct speech recognition in noise scores. Likewise, participants
(n = 8) showed a significantly lower (better) ANL when using the RM system (M = 0.69; SD = 7.0) as compared with the condition with no-RM system (M = 7.4; SD = 7.4) [t
(8) = 2.4, p = 0.02].
The average performance (N = 15) and data analyses for the LiSN-S are shown in [Figure 2 ]. For the SRT conditions, significantly better performance was found after training
in the high-cue condition (i.e., lower thresholds), but not the low-cue condition.
For the advantage conditions, no difference was detected across test time, but significant
differences were found across all three conditions (total > spatial > talker). No
significant interaction effects were found for either analysis.
Figure 2 Results on the LiSN-S for the SRT conditions (in dB SNR where lower is better) and
the advantage conditions (dB where higher is better). LiSN-S data were analyzed with
two separate, two-factor repeated measures analysis of variance with a Greenhouse-Geisser
correction. Adv = advantage; vertical lines represent one SD.
Average performance and analyses for the DWT and RDDT are shown in [Figures 3 ] and [4 ], respectively, where data were categorized according to the dominant (i.e., higher
score) and nondominant ear ([Moncreiff, 2015 ]). For the DWT, post hoc analyses suggested that Posttest 1 scores were significantly
higher than Pretest scores, but the significant improvements occurred only in the
nondominant ear. Interaural asymmetry (ear differences) significantly decreased from
Pretest to Posttest 1 ([Figure 5 ]). For the RDDT ([Table 4 ]), all Posttest 1 scores were significantly better than the Pretest score for the
nondominant ear. Interaural asymmetry significantly decreased from Pretest to Posttest
1 for the two- and three-pair digits.
Figure 3 Average percent-correct scores on the DWT (N = 15). Because of expected performance
differences ([Moncreiff and Wilson, 2009 ]), data were analyzed with a two-factor repeated measures analysis of variance with
a Greenhouse-Geisser correction. Vertical lines represent one SD.
Figure 4 Average percent-correct scores on the RDDT (N = 15). Vertical lines represent one
SD. Dom = dominant ear; Non-Dom = Nondominant ear.
Figure 5 Average interaural asymmetry calculations on the RDDT. Vertical lines represent one
SD.
Table 4
Statistical Analyses of the RDDT Data
Test
Main Effect
df
F -Statistic
p -Value
Interpretation and Post Hoc Results
One pair
Time
1,60
6.6
0.02*
Posttest 1 > Pretest
Ear
1,60
7.1
0.02*
Dominant > nondominant
Interaction
1,60
9.8
0.01*
All conditions > Pretest for nondominant ear
Two pair
Time
1,60
10.8
0.005*
Posttest 1 > Pretest
Ear
1,60
14.8
0.001*
Dominant > nondominant
Interaction
1,60
14.2
0.002*
All conditions > Pretest for nondominant ear
Three pair
Time
1,60
15.8
0.001*
Posttest 1 > Pretest
Ear
1,60
13.1
0.003*
Dominant > nondominant
Interaction
1,60
6.8
0.02*
All conditions > Pretest for nondominant ear
Ear advantage
Time
1,90
19.6
0.002*
Posttest 1 < Pretest
Digit pair
1,90
3.0
0.09
No advantage differences among digit pairs
Interaction
1,90
2.2
0.15
No interaction
Note: Data were analyzed with a two-factor repeated measures analysis of variance with
a Greenhouse-Geisser correction; post hoc comparisons were conducted with the Tukey–Kramer
multiple comparisons test. N = 15.
*Statistically significant.
Questionnaires
On the participant LIFE-R questionnaire (n = 10), the average sum of the ratings for
the Pretest was 50.2 (SD = 16.7) and for Posttest 1 was 59.3 (SD = 7.4). According
to a Wilcoxon signed-rank test, the participants perceived significant improvements
in classroom listening after training and the use of the RM technology (z = −1.5, p = 0.05). Average ratings on the Sensory Profile 2 (n = 10) are shown in [Figure 6 ]; significant results were found in several conditions. Despite multiple inquiries,
the response rate for the LIFE-R and the CHAPS teacher questionnaires was poor, and
as a result, these results do not represent the entire sample. The results of the
few questionnaires that were returned are provided in [Table 5 ]. Overall, most participants were reported to have difficulties listening before
the study, and for those who completed the posttest questionnaires, modest improvements
in listening ability were documented.
Figure 6 Average raw scores on the Sensory Profile 2 questionnaire. The attention ratings
relate to the child’s attentional responses associated with sensory processing. Data
were analyzed with the Wilcoxon signed-rank test. Vertical lines represent one SD.
Table 5
Teacher Ratings on LIFE-R and CHAPS Questionnaires
Participant
Pretest
Posttest 1
Interpretation from Pretest to Posttest 1
LIFE-R
1
43
57
Sometimes experiences listening challenges to occasional listening challenges at posttest
3
61
75
Occasional listening challenges to no listening challenges or very rare at posttest
4
47
55
Sometimes experiences listening challenges to occasional listening challenges at posttest
5
20
*
Almost always has listening challenges at pretest
6
*
58
Occasional listening challenges at posttest
7
18
*
Almost always has listening challenges at pretest
14
47
*
Sometimes experiences listening challenges at pretest.
CHAPS
1
−2.47
−0.47
At risk to normal
3
−0.14
0
Normal to normal
4
−2.2
−0.5
At risk to normal
5
−4.27
−1.05
At risk to at risk
6
*
−0.83
* to normal
7
−4.03
−3.72
At risk to at risk
12
−1.14
−1.16
At risk to at risk
13
−1.6
*
At risk to *
14
−1.8
*
At risk to *
15
−2.38
*
At risk to *
*Indicates that the teacher did not return the questionnaire. Higher ratings on the
LIFE-R indicate fewer listening challenges. Lower ratings (more negative) on the CHAPS
indicate greater listening difficulty.
Posttest 2 Results
The analyses for the seven participants (1–7 in [Table 1 ]), aged 7 years 5 months to 21 years 9 months, who completed a third test session
(12-week training) are provided in [Table 6 ]. Overall, the significant performance improvements measured for most tests from
the Pretest to the Posttest 1 sessions were maintained in the Posttest 2 session.
Table 6
Results of Repeated Measures ANOVA from Participants Who Completed Three Test Sessions
Test
Subtest
df
F -Statistic
p -Value
Interpretation and Post Hoc Results
TAPS-3
Word discrimination
2,21
0.64
0.54
No differences across three test sessions
Phonol segmentation
2,21
1.5
0.26
No differences across three test sessions
Num Mem forward
2,21
6.8
0.01*
Posttest 2 > Pretest; Posttest 1 = Posttest 2
Num Mem reversed
2,21
2.7
0.12
No differences across three test sessions
Word memory
2,21
2.2
0.15
No differences across three test sessions
Sentence memory
2,21
0.76
0.50
No differences across three test sessions
Auditory comp
2,21
0.01
0.99
No differences across three test sessions
Auditory reasoning
2,21
7.3
0.009*
Posttest 1 > Pretest; Posttest 1 = Posttest 2
Phonol blending
2,21
8.4
0.005*
[Posttest 1 > Pretest; Posttest 2 > Pretest; Posttest 1 = Posttest 2]
CELF
Following Directions
2,21
5.8
0.04*
Posttest 1 and Posttest 2 > Pretest; Posttest 1 = Posttest 2
BKB-SIN
2,18
4.9
0.03*
Posttest 2 > Pretest
ANL
2,21
0.96
0.41
No differences across three test sessions
LiSN-S
SRT Conditions
Main effect: time
2,42
2.1
0.017
No differences across three test sessions
Main effect: condition
1,42
81.7
0.0001*
High-cue SRT better than low-cue SRT
Interaction effect
1,42
1.1
0.37
No interaction effect
Advantage Conditions
Main effect: time
1,63
1.3
0.31
No differences across three test sessions
Main effect: condition
2,63
36.6
0.0008*
Total > spatial > talker condition
Interaction effect
4,63
2.3
0.09
No interaction effect
DWT
Main effect: time
2,42
20.5
0.001*
Posttest 1 and Posttest 2 > Pretest
Main effect: ear
1,42
3.4
0.11
Nondominant ear < all other conditions
Interaction effect
2,42
6.8
0.01*
Dominant ear Pretest < dominant ear Posttest 2
RDDT
One-digit Pairs
Main effect: time
2,42
12.9
0.001*
Posttest 1 and Posttest 2 > Pretest
Main effect: ear
1,42
5.9
0.051
Nondominant ear Pretest < all conditions
Interaction effect
2,42
5.2
0.02*
Dominant ear Pretest < dominant ear Posttest 2
Two-digit Pairs
Main effect: time
2,42
15.2
0.0005*
Posttest 1 and Posttest 2 > Pretest
Main effect: ear
1,42
8.1
0.03*
Dominant ear > nondominant ear
Interaction effect
2,42
11.3
0.002*
Nondominant ear Pretest < all other conditions
Three-Digit Pairs
Main effect: time
2,42
13.8
0.0008*
Posttest 1 and Posttest 2 > Pretest
Main effect: ear
1,42
9.8
0.02*
Dominant ear > nondominant ear
Interaction effect
2,42
5.0
0.03*
Nondominant ear Pretest < all other conditions
Advantage-All Pairs
Main effect: time
2,63
17.2
0.0003*
Posttest 1 and Posttest 2 > Pretest
Main effect: pairs
2,63
1.8
0.20
Interaction effect
4,63
0.59
0.67
Notes: Data were analyzed with repeated measures ANOVA; post hoc comparisons were conducted
with the Tukey–Kramer multiple comparisons test. N = 7. ANOVA = analysis of variance;
Comp = comprehension; Mem = memory; Num = number; Phonol = phonological.
*Statistically significant.
DISCUSSION
The primary goal of this study was to determine the efficacy and effectiveness of
the 12-week APT program for enhancing general auditory processing skills in individuals
with ASD. Following the completion of the APT program, on average, the 15 participants
exhibited behavioral improvements in multiple areas, including phonological segmentation
and blending (TAPS-3), number and word memory (TAPS-3), auditory reasoning (TAPS-3),
and binaural integration of words and digit spans (DWT and RDDT). In particular, the
abnormal interaural asymmetry on dichotic testing was significantly reduced. When
the RM technology was in use, percent-correct speech recognition in noise and acceptance
of background noise levels significantly improved on the BKB-SIN and ANL tests, respectively.
However, results on these tests did not show improvement after training when the RM
technology was not in use. The ability to hear a speaker in speech competition showed
significant improvement after training as measured by the LiSN-S high-cue condition,
although improvement was not seen on the advantage conditions. When examining the
effectiveness of the training, participant, parent, and/or teacher questionnaires
confirmed improvements in auditory processing (Sensory Profile 2), attentional responses
associated with sensory processing (Sensory Profile 2), the detection of sensory input
(Sensory Profile 2), and reduced listening challenges in the classroom across various
listening situations (LIFE-R and CHAPS).
When considering the specific areas of improvement and areas that did not improve,
several noteworthy findings were considered. First, when considering all of the areas
that improved on the TAPS-3 (phonological segmentation and blending; number and word
memory; and auditory reasoning) and the binaural integration tasks (DWT and RDDT),
it is evident that each of these tests and subtests required verbal and auditory working
memory for various stimuli, areas in which those with ASD struggle when compared with
neurotypical peers ([Macizo et al, 2016 ]; [Wang et al, 2017 ]; [Vogan et al, 2018 ]). As a result, completion of the APT program addressed a significant deficit area
for children with ASD. Given the wide range of stimuli used across the two training
components of the APT program, the authors hypothesize that both aspects of the program,
the one-on-one therapy and the dichotic listening training, resulted in the improved
working memory on the various tasks. A similar type of training focused on auditory,
visual, and visual–spatial working memory has also been successful for individuals
with ASD ([Weckstein et al, 2017 ]).
Second, the Pretest and Posttest 1 scores on the DWT and RDDT highlight the substantial
ear differences found for most participants, particularly on the RDDT. In addition,
there is a possibility of age effects on these tests. On average, the eight older
participants (>12 years) had higher scores of 79% (SD = 10) and 64% (SD = 20) for
the dominant and nondominant ears, respectively, than the dominant and nondominant
scores of 66% (SD = 21) and 41% (SD = 32), respectively, for the younger participants.
Similarly, when examining the average two-pair digit data, the eight older participants
(>12 years) had higher scores of 89% (SD = 18) and 71% (SD = 24) for the dominant
and nondominant ears, respectively, than the dominant and nondominant scores of 77%
(SD = 16) and 35% (SD = 30), respectively, for the younger participants.
Most notable, however, is that following training, all participants improved their
nondominant ear scores on the DWT, and all but one participant (who had 97% correct
on the Pretest) improved their scores on the two-pair digits. In addition, in the
dominant ear, seven participants improved their DWT scores, and eight participants
showed improved performance on the two-pair digits. Age did not appear to be a factor
in the presence or absence of improvements in the dominant ear. More specifically,
for the seven participants who had abnormal DWT performance at Pretest, four showed
typical performance after training, and abnormal interaural asymmetries were eliminated
in two additional participants. For the 11 subjects with abnormal RDDT performance
at Pretest, four had typical performance after training. Two additional participants
who had unilateral weakness and poor scores bilaterally no longer showed unilateral
weakness after training. Given the substantial improvements, it is evident that the
CAPDOTS training directly addressed some of the binaural integration weaknesses seen
on the dichotic tests. Similar training has been successful in children diagnosed
with auditory processing disorders ([Moncrieff et al, 2017 ]).
Third, although the response rate was poor for some of the questionnaires, particularly
those from the teachers, at least two questionnaires for each participant documented
listening difficulties in various everyday situations. In addition, participant listening
difficulties were documented on the case history form (summarized in [Table 2 ]). Following training, at least one questionnaire for each participant documented
decreased listening difficulty in various listening situations inside or outside of
the classroom. The most complete Pretest and Posttest datasets were obtained for the
participant LIFE-R (n = 10) and the parent Sensory Profile (n = 10). Results of these
questionnaires suggested improvements for listening in classroom situations, processing
of general sensory input, and attentional behaviors (e.g., eye contact and paying
attention). Given the poor return rate from the teacher questionnaires, caution must
be used when interpreting these limited results ([Table 5 ]).
In contrast to the aforementioned tests and questionnaire results, after the APT program,
no group improvements in spatial processing were measured on the LiSN-S test, likely
because of normal Pretest scores, and no group improvements were measured for speech
recognition in the presence of noise on the BKB-SIN. Although the APT program did
not significantly improve speech recognition in noise performance on the BKB-SIN,
descriptive analysis of the individual data provides some insights into the speech
recognition deficits of the participants. First, when comparing individual Pretest
performance with normative data by age in the BKB-SIN test manual (2005), 11 of the
15 participants had speech-in-noise thresholds that were worse than most similarly
aged neurotypical peers (i.e., >1 SD and worse thresholds than 68% of children his/her
age), consistent with previous research ([Alcántara et al, 2004 ]; [Schafer et al, 2013 ]). After training, 6 of these 11 participants improved their thresholds to within
one SD of the BKB-SIN normative data. Thus, despite the lack of a significant group
finding on the BKB-SIN test, individual data suggest that the APT program improved
performance for some individuals. In addition, when the RM technology was in use,
speech recognition in noise and the acceptance of background noise was significantly
improved for all participants, suggesting that this type of technology is beneficial
in noisy listening situations ([Knecht et al, 2002 ]; [Cruckley et al, 2011 ]).
Study Limitations
Limitations of this study relate to sample size, age range of the participants, heterogeneity
of the ASD population, lack of a control group or repeated baseline measure, limited
control over hours of RM technology use, poor response rate for the teacher questionnaires,
and the inability to determine the relative contributions of the three interventions.
Continued data collection from individuals diagnosed with ASD and age-matched neurotypical
peers will address some of these limitations. However, it is important to note that
in any sample of individuals with ASD, multiple factors will contribute to the variability
in performance. These factors include age, coexisting disabilities, auditory attention,
hours of RM technology use per day, and maturation of auditory skills (particularly
for dichotic testing). Given the heterogeneity (i.e., spectrum of abilities) in the
ASD population and the range of educational environments in which children with ASD
are taught, most of these factors are difficult to control. In addition, it is challenging
to recruit and retain participants and families who are willing and able to complete
training studies that require a substantial time commitment (approximately 42 days).
Clinical Implications
Although it was important to test the APT program in a laboratory-based study, the
time commitment that was required for the participants and families was a substantial
barrier. However, the investigators believe that it is feasible to implement each
of these interventions through clinical or school-based audiology services and through
speech-language therapy. Clinical or educational audiologists can fit and monitor
the RM technology, and audiologists or speech-language pathologists can administer
the web-based CAPDOTS program. In the present study, it is evident that CAPDOTS improved
binaural integration, and multiple studies, including the present, support the use
of RM technology for improving classroom and self-perceived listening abilities ([Schafer et al, 2013 ]; [2016 ]; [Rance et al, 2014 ]). Consistent use of the RM technology for a longer period of time (i.e., >12 weeks)
may result in even greater benefits than those measured in the present study ([Friederichs and Friederichs, 2005 ]; [Johnston et al, 2009 ]; [Hornickel et al, 2012 ]; [Smart et al, 2017 ]). Implantation of the one-one-one auditory training in background noise with a speech-language
pathologist or audiologist is also viable in a school- or therapy-based setting. Manuscript
preparation is underway to provide more detailed information about implementing the
one-on-one auditory training and expected training improvements over time in a group
of individuals with ASD.
To summarize, this study provides evidence that the APT program consisting of computerized
dichotic training, one-on-one therapist-directed auditory training, and the use of
RM technology at home and in the classroom significantly enhanced auditory processing
abilities and working memory in 15 children and young adults diagnosed with ASD.
Abbreviations
ANL:
Acceptable Noise Level
APD:
auditory processing disorder
APT:
auditory processing training
ASD:
autism spectrum disorder
BKB-SIN:
Bamford–Kowal–Bench Speech-in-Noise
CAPDOTS:
Central Auditory Processing Disorder Online Therapy System
CELF-5:
Clinical Evaluation of Language Fundamentals—Fifth Edition
CHAPS:
Children’s Auditory Performance Scale
DIID:
dichotic interaural intensity difference
DWT:
Dichotic Words Test
LIFE-R:
Listening Inventory for Education—Revised
LiSN-S:
Listening in Spatialized Noise—Sentence Test
RDDT:
Randomized Dichotic Digits Test
RM:
remote microphone
SD:
standard deviation
SRT:
speech reception threshold
TAPS-3:
Test of Auditory Processing Skills—Third Edition
