COMPARISON OF INTENSIVE VERB INTERVENTIONS WITH AND WITHOUT
THE REQUIREMENT OF SPEECH PRODUCTION IN THE TREATMENT OF
FLUENT APHASIA
Gretchen Amy Hess
B.A., California State University, Sacramento, 2000
M.A., California State University, Sacramento, 2004
THESIS
Submitted in partial satisfaction of
the requirements for the degree of
MASTER OF SCIENCE
in
SPEECH PATHOLOGY
at
CALIFORNIA STATE UNIVERSITY, SACRAMENTO
FALL
2011
COMPARISON OF INTENSIVE VERB INTERVENTIONS WITH AND WITHOUT
THE REQUIREMENT OF SPEECH PRODUCTION IN THE TREATMENT OF
FLUENT APHASIA
A Thesis
by
Gretchen Amy Hess
Approved by:
__________________________________, Committee Chair
Dr. Laureen O’Hanlon
___________________________________, Second Reader
Dr. Robert Pieretti
____________________________
Date
ii
Student: Gretchen Amy Hess
I certify that this student has met the requirements for format contained in the University
format manual, and that this thesis is suitable for shelving in the Library and credit is to
be awarded for the thesis.
_______________________, Department Chair
Dr. Laureen O’Hanlon
Department of Speech Pathology and Audiology
iii
___________________
Date
Abstract
of
COMPARISON OF INTENSIVE VERB INTERVENTIONS WITH AND WITHOUT
THE REQUIREMENT OF SPEECH PRODUCTION IN THE TREATMENT OF
FLUENT APHASIA
by
Gretchen Amy Hess
Aphasia interventions that do not require verbal responses (implicit therapy approaches)
can be beneficial when verbal errors are prevalent and frustrating for the individual.
Intensive, error-reducing interventions utilizing computerized four-picture stimuli and
requiring inhibition of close semantic competitors as well as activation of the target have
also been shown to improve word retrieval. This study, which was counterbalanced to
address order effects, compared an implicit, semantic decision-based verb intervention
with an intervention identical in all respects except for the requirement of speech
production in an individual with fluent aphasia. Clear response to both production-free
and production-required interventions was observed, and training effects in both phases
were maintained. Order effects were observed, with the first training method in each
phase demonstrating a larger size effect. Findings support the use of semantic decisionbased, production-free training as a potentially valuable augmentation to conventional
therapy for aphasia rehabilitation. In addition, verb training may have direct effects on
spontaneous speech and fluency.
_____________________________, Committee Chair
Dr. Laureen O’Hanlon
iv
_____________________
Date
ACKNOWLEDGEMENTS
Dr. Christine Davis made this research possible. She introduced me to and shared
her knowledge about this topic during my first undergraduate year, encouraged and
guided my participation in her research projects, ushered me into the greater community
of aphasia researchers, provided countless additional learning opportunities, made me
feel my ideas were valuable, and just generally served as role model and inspiration in
every possible way. To whatever degree I have helped or will ever help to improve the
communication skills of individuals with aphasia or further the cause of research
conducted on their behalf, you are responsible. I can never thank you enough.
My deepest thanks to my thesis chair, Dr. Laureen O'Hanlon, whose palpable
enthusiasm for research and lifelong learning—and whose confidence in me, in
particular—gave me, in turn, the confidence to believe that a mere English major could
think like a scientist and researcher. It is because of you, ultimately, that I ever saw
myself as someone who could succeed in this field, and that I was able to be open to
surprising and counterintuitive new ideas (such as speech therapy that discourages the
client from speaking!). Many thanks also to Dr. Kathleen Baynes, pioneer in the area of
production-free treatment methods, for assisting in the compilation of the initial figures
for this study, as well as by taking time out of her busy schedule to answer my questions.
Thanks, too, to the ever-dependable Robert Pieretti, for stepping in as second reader, and
to Jeanne Wielgus Marlatt, lifelong friend extraordinaire, for late-night, remote
formatting assistance when I needed it most.
Finally, to Bob and our children, I give thanks for all….now and always.
v
DEDICATION
For I.T., whose curiosity, love of learning, and lively sense of humor made every session
a delight.
vi
TABLE OF CONTENTS
Page
Acknowledgements ............................................................................................................. v
Dedication .......................................................................................................................... vi
List of Tables ..................................................................................................................... ix
List of Figures ..................................................................................................................... x
Chapter
1. INTRODUCTION AND REVIEW OF RESEARCH ................................................... 1
Purpose of the Study ............................................................................................... 1
Traditional speech therapy for aphasia ................................................................... 4
Intensive treatment .................................................................................................. 5
Confrontation naming and verbal repetition ......................................................... 11
Lexical retrieval and semantic processing models ................................................ 13
Semantic-based intervention ................................................................................. 19
Errorless and error-reducing approaches .............................................................. 29
Implicit therapy ..................................................................................................... 35
Mental practice and inner speech .......................................................................... 37
Development of the implicit method for treatment of aphasia ............................. 41
The present study .................................................................................................. 48
2. METHODS .................................................................................................................. 54
Participant ............................................................................................................. 54
Procedure .............................................................................................................. 56
3. RESULTS .................................................................................................................... 69
Comparison of Implicit and Explicit Training Methods ....................................... 69
Error Patterns ........................................................................................................ 73
Change in Standardized and Non-Standardized Language Measures .................. 74
4. DISCUSSION .............................................................................................................. 77
Major Findings and Implications .......................................................................... 77
vii
Limitations of the Present Study and Directions for Future Research.................. 82
Conclusions ........................................................................................................... 87
Appendix A. Trained and Untrained Verb Lists ............................................................... 89
Appendix B. Verb Use in Training Templates ................................................................. 91
Appendix C. Sample Training Templates ......................................................................... 93
References ....................................................................................................................... 109
viii
LIST OF TABLES
Page
1.
Table 1. Classification of responses according to error type. ............................... 73
2.
Table 2. Participant’s pre-and post-treatment scores ............................................ 76
3.
Table A3. Phase One Trained and Untrained Verbs ............................................. 89
4.
Table A4. Phase Two Trained and Untrained Verbs ............................................ 90
5.
Table B5. Question Types with Sample Questions .............................................. 91
6.
Table B6. Sample Typical and Atypical Exemplars ............................................. 92
ix
LIST OF FIGURES
Page
1.
Figure 1. Outline of Levelt’s (1999) theory. ......................................................... 19
2.
Figure 2. Illustration of treatment study design .................................................... 53
3.
Figure 3. Participant’s MRI and CT scans showing area and extent of lesion. .... 54
4.
Figure 4. Phase One: Comparison of implicit and explicit training effects. ......... 71
5.
Figure 5. Phase Two: Comparison of explicit and implicit training effects. ........ 72
6.
Figure 6. Percentage of responses in each phase classified by type. .................... 74
x
1
Chapter 1
INTRODUCTION AND REVIEW OF RESEARCH
Purpose of the Study
Aphasia, an acquired communication impairment most frequently associated with
stroke and traumatic brain injury (TBI), can have devastating effects on all aspects of a
person’s life and work (National Aphasia Association, 2010). Among the most common
and most distressing consequences of aphasia are profound word retrieval deficits
(Hashimoto & Thompson, 2010; Raymer, Kohen, & Saffell, 2006), and much clinical
time is devoted to the remediation of these word retrieval or naming problems (Nickels,
2002). Although speech-language therapy can improve outcomes for individuals (Basso,
Capitani, & Vignolo, 1979; Best & Nickels, 2000; Mazzoni et al., 1995), sometimes even
when delivered to patients in “quite small amounts” (Howard, 2000), the most effective
therapy for many patients may require anywhere from 9 to 20 or more hours of therapy
per week (Basso & Caporali, 2001; Bhogal, Teasell, & Speechley, 2003; Hinckley &
Craig, 1998). This level of treatment is unavailable to many patients due to financial
considerations, health insurance limitations, the relative shortage of available speechlanguage pathologists, and logistical factors such as the time and travel required to
transport clients to treatment facilities (Davis & Baynes, 2009). In addition, much
therapy currently being conducted with individuals with aphasia can be classified as
“errorful” in that it allows the client numerous opportunities for making—or, in effect,
practicing—numerous speech production errors. Errorful therapy, in turn, can have the
unintended consequence of increasing the likelihood of subsequent errors (Brookshire,
2
1972, 1975; Brookshire, Nicholas, Redmond, & Krueger, 1979), an effect which “may be
even more harmful or pervasive in cases of neurological damage” such as that often
sustained by stroke or TBI survivors with aphasia (Frattali, 2004).
Aphasia interventions which require the client to make semantic decisions without
producing explicit verbal responses have resulted in improvements in naming which last
longer than the effects of interventions requiring articulation of the target (Howard,
Patterson, Franklin, Orchard-Lisle, & Morton, 1985a). Therapy focusing on semantic
decision-making in the absence of explicit naming can be especially beneficial for clients
whose verbal errors tend to be prevalent, self-reinforcing, and frustrating (Davis,
Harrington, & Baynes, 2006, 2007; Davis, Farias, & Baynes, 2009). When applied
intensively, such production-free interventions, sometimes referred to as “implicit
therapy” or “error-reducing” approaches, have significantly improved naming and
discourse, hypothetically through activation of the two neural networks—semantic and
phonological—assumed to support naming ability and speech production (Davis &
Baynes, 2009). The activation of these neural networks during implicit semantic
processing tasks has been well-documented in fMRI studies (Ruff, Blumstein, Myers, &
Hutchinson, 2008). Production-free interventions, by reducing error productions, are also
thought to decrease the likelihood that the client will “practice” and therefore reinforce
his or her own error productions during therapy (Davis & Baynes, 2009). An additional
benefit of production-free interventions is that they can be individualized to match
specific client needs and interests, and, via the use of computerized programs, can be
included in home carryover programs for clients who need additional language practice,
3
or for whom continued or intensive treatment by a speech-language pathologist is not an
option (Davis & Baynes, 2009).
Although production-free treatment methods have recently begun to be compared
experimentally with methods requiring explicit speech production (Davis, Baynes, &
Hess, 2009; Davis, Farias, & Baynes, 2008), no previous experiment compared these two
types of interventions in the treatment of a client with fluent aphasia, or used a crossover
design to control for order effects. This single-subject, multiple baseline, counterbalanced
study was conducted over the course of many months, between July, 2009 and
September, 2010, at U.C. Davis Medical Center, and was presented at the international
Academy of Aphasia (Davis, Hess, & Baynes, 2010). It compared a production-free,
semantic decision-based verb intervention with an intervention identical in all respects
except for the requirement of speech production in an individual with fluent aphasia
secondary to a traumatic brain injury.
Before beginning this study, the researchers hypothesized that both productionfree and conventional training would improve production of trained verbs, but asked the
question whether such improvements would be essentially equal or would significantly
differ due to the differing (speech production) response requirements in each condition.
They also sought to determine whether training would generalize to untrained verbs,
whether a measure of effect size would supplement observations from visual inspection
of results, and whether order effects would be observed.
4
Traditional speech therapy for aphasia
Although the consensus seems to be that aphasia therapy improves outcomes for
individuals (Albert, 2003; Basso, 2005; Wertz, 2000), and numerous studies have
demonstrated that treatment is generally efficacious and associated with statistically
significant, long-term improvement in language skills (U.S. Department of Veterans
Affairs & Department of Defense, 2003), there are still unanswered questions regarding
which type of treatment may be the best match for a particular individual, or even for a
particular profile of deficits. It has been observed that “in particular, it is still difficult to
predict which therapeutic task or approach will be successful at remediating which
particular disorders. We argue that this is particularly true in the rehabilitation of
anomia” (Best & Nickels, 2000). Matching treatment and deficit is not always effective
(Best & Nickels, 2000; Drew & Thompson, 1999; Wambaugh, Linebaugh, Doyle,
Martinez, & Kalinyak-Fliszar, 2001). Moreover, treatment parameters and patient
descriptions differ so much across studies that it is difficult to identify the individual
factors that predict response to treatment (Davis & Baynes, 2009).
The general approach most frequently used to treat anomia in aphasia is to
explicitly train individuals in whole word naming (Maher & Raymer, 2004), or in other
words, to have them practice production of target words in the hope that this exercise will
increase their word-finding abilities in spontaneous speech (Nickels, 2002a, 2002b).
Studies have shown that this method may improve naming performance for trained items
but that generalization tends to be very limited, with “at best very modest improvement in
naming performance with untrained words” (Kendall et al., 2008). In traditional speech
5
therapy, clinicians have long used prompts and cueing in naming tasks to elicit spoken
words from patients “with the hope that the patients will subsequently be able to retrieve
the names without help,” and yet this hope may be entirely without foundation (Howard,
Patterson, et al., 1985a); after successfully naming a target picture, aphasic patients were
shown to be no more likely to successfully name the target when presented with the same
picture 30 minutes after training (Patterson, Purell, & Morton, 1983).
Even when therapy does appear to have a positive effect, it is often difficult to
determine precisely which variables were responsible for the improvement in
performance, and thus “there is still no clear agreement on how to manage [the] deficits”
of patients with anomia (Maher & Raymer, 2004). Poeck, Huber, and Willmes (1989)
noted that although the efficacy of treatment had been generally demonstrated, “the
mechanisms or factors that are related to the beneficial effects of treatment remain poorly
understood.” Some authors have hypothesized that we know so little about the precise
mechanisms of improvement in aphasia therapy that we may inadvertently be subjecting
patients to therapies that have minimal effect, have no effect, or, even worse, may
actually be harmful (Howard, Patterson, et al., 1985a). It is therefore of the greatest
importance that investigators attempt to determine precisely which factors are associated
with improvements in word retrieval for patients with aphasia.
Intensive treatment
Some studies have found that although factors such as age, duration, size and site
of lesion, and impairment in intelligence were not related to improvement with therapy,
one factor of crucial importance was the intensity or dosage at which therapy was
6
delivered (Basso, 2005; Basso & Caporali, 2001; Poeck, Huber, & Willmes, 1989). Some
authors have suggested that intensity of treatment may be the single most important
factor contributing to the inconsistency of treatment effects across studies, and that “the
failure to identify a consistent benefit might have been due to the low intensity of speechlanguage therapy applied in the negative studies, whereas higher intensities of therapy
were present in positive studies” (Bhogal, Teasell, & Speechley, 2003). Principles of
neurobiological learning explored in animal studies (Squire, 1992) and in human research
(Poldrack & Gabrieli, 2001) suggest that treatment intensity is a significant factor for
learning (Off, Kavalier, & Rogers, 2008). Further research addressing neural plasticity
involved in memory and learning indicates that a large number of trials are required to
elicit change (Squire, 1992), but that such change can have long-lasting results. Hinckley
(2002) reported that many patients continued to describe improved life satisfaction two
years after receiving intensive therapy. Davis, Harrington and Baynes (2006), in a review
of the evidence on intensive therapy, concluded that “intense, repetitive stimulation can
have both behavioral and neural effects,” and that the neuropsychological effects of such
intensive applications of speech and language therapy, once attained, can be both
“significant and persistent.”
Numerous studies have demonstrated that intensive intervention is effective for
individuals with aphasia (Miceli, Amitrano, Capasso, & Caramazza, 1996) and may be
the most potentially beneficial regimen of treatment (Bhogal, Teasell, & Speechley,
2003; Davis, Harrington, & Baynes, 2006; Wertz et al., 1986), although authors have
differed in their definition of “intensive” (Basso, 2005). Results of a meta-analysis of
7
studies showed that the total number of therapy sessions was an important factor in
recovery, with indications that “when therapy is protracted for many months or even
years with a very strict regimen” of two to four hours daily, individuals with aphasia
“showed clear improvement in their daily use of language and communicative
competence” (Basso, 2005).
Some authors have noted improvements—even long-lasting improvements—with
therapy delivered intensively over a much shorter period of time (Davis, Harrington, &
Baynes, 2006). Bhogal, Teasell, and Speechley (2003), “building upon the idea that more
is better,” conducted a review of previous studies to determine the relationship of
intensity of aphasia therapy and aphasia recovery after stroke. The authors found that
“intense aphasia therapy over a short period of time has greater impact on recovery than
less intense therapy over a longer period of time.” Brindley, Copeland, Demain, and
Martyn (1989) found that three months of intensive speech therapy in a residential setting
resulted in significant speech improvements for patients with chronic Broca’s aphasia
even when the patients were many years post-onset. Miceli, Amitrano, Capasso, and
Caramazza (1996) found that participants receiving one hour of treatment five days a
week for one week (for a total of only five sessions/five hours of therapy) showed
marked improvement of treated words, and that one patient continued to display a
difference between treated and untreated items 17 months post-treatment. Poeck, Huber
and Willmes (1989) investigated whether intensive language treatment led to
improvement beyond the rate of spontaneous recovery and whether such treatment was
effective for patients in the chronic phase (over 12 months post-onset). They found that
8
with intensive treatment, defined as six to eight weeks of therapy consisting of five onehour individual sessions and four one-hour group sessions per week, improvement went
beyond that expected with spontaneous recovery alone in up to 78% of patients,
depending upon time since onset. With intensive treatment, aphasia improved even in the
chronic stage for 68% of the patients, and these positive results appeared to be
maintained. Furthermore, the authors felt that the actual percentages of patients who
improved may have been much higher than these numbers reflected, due to the overly
“strict” correction procedures used to account for spontaneous recovery. Only global
aphasics failed to improve significantly when intensive treatment was administered
beginning over one year post-onset (Poeck, Huber, & Willmes, 1989).
Basso and Caporali (2001), noting that “it has never been our experience” that
patients recover with therapy delivered at standard intensity levels, conducted a study to
compare the relative effectiveness of intensive and less intensive therapy regimens. They
found that intensive therapy resulted in more dramatic, sustained, and generalized
improvements than did therapy delivered at less intensive treatment intervals, even for
participants whose aphasia was chronic and whose previous (standard) therapy had been
halted after further improvement was deemed unlikely. In their study, intensive therapy
was defined as therapy received for two to three hours per day, seven days a week, over
the course of many months. This level of intensity was achieved through use of a
combination of one-to-one therapy with a speech pathologist for one hour per day,
supplemented by intensive homework supported by family members and volunteers for
an additional one to two hours per day. The authors noted that those participants who
9
received the more intensive therapy experienced improvements in word retrieval which
improved their confidence in their language abilities and carried over to spontaneous
speech in their everyday communication interactions. The authors concluded that the
patients’ recovery, “and particularly their better use of language for communication
purposes, was the result of intense work done with each patient, and that such a regimen
could be successful in a number of patients for whom a less intensive regimen would be
ineffective” (Basso & Caporali, 2001). Dronkers, Husted, Deutsch, Taylor, Saunders, and
Merzenich (1999) reported similar results with therapy delivered to patients for one and a
half hours per day, five days a week, for eight weeks.
Although there is no consensus on what constitutes an ideal level of therapy
intensity, the outcome data on aphasia treatment indicate that three sessions per week for
five to six months (Basso, Capitani, & Vignolo, 1979) or eight to ten sessions per week
for twelve weeks (Wertz et al., 1986) is the minimum amount of therapy needed to
demonstrate significantly more improvement in treated patients than in untreated patients.
For therapy to be intensive enough to maximize recovery, then, some amount over and
above that minimum is needed. However one chooses to define “intensive therapy,” it
may be that if there is an upper limit to the ideal level of intensity, no one has found it
yet; a meta-analysis of studies including patients with aphasia from all etiologies yielded
the general rule of thumb that “the more intensive the therapy, the greater the
improvement” (Bhogal, Teasell, Foley, & Speechley, 2003). In short, although the
precise number of presentations of a given stimulus required to yield consistent
improvement of naming is not known, and although questions remain regarding just how
10
intensively delivered a treatment should be in order to maximize an individual’s potential
for recovery (Off, Kavalier, & Rogers, 2008), “there appears to be evidence that intensive
treatment is useful in both the short and long term” (Davis, Harrington, & Baynes, 2006).
Regardless of findings such as these, aphasic patients typically do not receive
therapy approaching levels that could reasonably be called “intensive.” Patients with
aphasia who reside in the United States are likely to receive speech-language therapy for
one hour per day, one to three days per week, over the course of three to four weeks
(Davis, Harrington, & Baynes, 2006). This is a discouraging statistic, especially in light
of the fact that therapy delivered for two hours per week for 24 weeks or less—a level of
intensity “representative of clinical practice”—has been shown to result in no statistical
difference in improvement between treated and untreated patients, and therefore to be
“ineffective for most” aphasic patients (Lincoln et al., 1984). It has been argued that
therapy delivered at this low level of intensity—that is, over a short course of time, or in
a limited number of sessions—may benefit some patients but not others, and some
authors have questioned whether the latter should even be subjected to therapy that “may
have no benefit” when delivered at such low intensities (Wertz, 2000). Bhogal, Teasell,
and Speechley (2003) concluded that “intensive aphasia therapy delivered over two to
three months is critical to maximizing aphasia recovery, and failure to provide it
potentially compromises individual outcomes.” Some authors have gone so far as to
suggest that if aphasia therapy cannot be administered with sufficient intensity, it may not
result in any improvement for individuals (Brindley, Copeland, Demain, & Martyn,
1989), and therefore perhaps ought not to be attempted at all (Wertz, 2000). Brindle et al.
11
(1989) posited that “it is only by radically reorganizing current provision or increasing
the time allocated to speech therapists that their expertise can be effective in the field of
chronic aphasia.”
Confrontation naming and verbal repetition
Next to intensity of treatment, the factor thought to exert the greatest influence on
the results of efficacy studies is the type of task used during intervention (Bhogal,
Teasell, & Speechley, 2003). Naming skills, the expressive verbal skills most frequently
targeted by speech-language pathologists (Roseberry-McKibbin & Hegde, 2006), are
usually treated through the elicitation of spoken words using a variety of methods,
including confrontation naming tasks and verbal repetition (Raymer, 2005). While
picture-naming tasks do provide a valid means of assessment of lexical retrieval, such
tasks may not be therapeutic (Herbert et al., 2008). Even when such treatments appear to
result in improved naming, it is not always clear “that the improvement reported in these
experiments is a specific consequence of the particular treatment regimens applied”
(Howard et al., 1985a). The difficulty in interpreting many studies examining aphasia
therapy “is that it is unclear which, if any, of the many techniques that were used actually
helped the patients to improve their naming; some may have been beneficial, others
useless, or even…actually harmful; we simply do not know” (Howard et al., 1985b).
Howard et al. (1985a) emphasized a distinction between prompts and facilitators,
a distinction crucial to understanding the difference between immediate and long-term
effects of therapy. By facilitation, the authors explained, “we mean one application of a
single technique with a view to assessing its specific effects at some later time. If the
12
patient is significantly more likely to be able to name the appropriate object some
minutes, hours or days after a specific treatment has been applied to the target word, we
would say that facilitation has been successful” (Howard et al., 1985a). The authors
stated that while a variety of prompting techniques, most notably phonemic cueing, had
been shown to effectively enable aphasic patients to verbally produce a picture name
which they had been previously unable to produce, there was no evidence of any longterm effects from such techniques. Patterson, Purell, and Morton (1983) found that the
naming facilitation effects of phonemic cueing lasted for less than 30 minutes. Howard
et al. (1985a) found similar effects for the technique of word repetition. “When an
aphasic patient could not find a picture name, repeating it was an effective naming
prompt if the picture was presented for naming again immediately afterwards,” the
researchers reported. After about five minutes, however, “all benefit from having
repeated the word had disappeared; the aphasic subjects were then no more likely to
name the picture than if they had had no opportunity to repeat its name” (Howard et al.,
1985a). In other words, the authors argued, effective prompts may not be effective longterm facilitators; the evidence supported the conclusion that repetition, phonemic cues,
rhyme cues and rhyme judgments all work as prompts, but “are not facilitators in any
lasting sense” (Howard et al., 1985b). Other authors have reported similar findings.
Investigating the possibility that “simply saying the words was important” in successful
traditional lexical therapy requiring the individual to look at a picture and produce the
word, Nickels and Best (1996) found that evidence for this claim was inconclusive.
Patterson et al. (1983) found that the benefits of producing words in repetition or in
13
response to phonological cues (in picture naming) were very short lasting, although
Miceli et al. (1994) subsequently demonstrated that such a task could have long-lasting
benefits. Nickels and Best (1996) concluded that “a more complex explanation” than
mere practice in word production might be necessary to account for such benefits, an
explanation requiring an understanding of the complex processes underlying naming.
Lexical retrieval and semantic processing models
One factor limiting the effectiveness of standard confrontation naming and verbal
repetition tasks may be that they treat only the surface of the problem (explicit
production, or articulation of the target), ignoring the psycholinguistic/semantic processes
that underlie the process of naming. In other words, although object naming may seem
on the surface to be a simple task, the underlying process of retrieving and formulating a
word is extraordinarily complex (Levelt, Roelofs, & Meyer, 1999) and there may be
benefits to therapy focusing on an earlier stage of the word production process (e.g.,
lexical selection or semantic processing) rather than on the last or end stage of
articulation. Guidelines for future research consistently “stress the need for evidencebased practice that is based on clinical experience integrated with theoretical rationale”
(Davis & Farias, 2010), and authors have noted that psycholinguistic models of word
production “are increasingly specific and provide a theoretical foundation for treatment
interventions of this type” (Davis & Baynes, 2009). The training method used in the
present study is based on psycholinguistic models in which at least two interrelated
networks—lexical selection (often referred to as the semantic network) and form
encoding (often referred to as the phonological network)—underlie word production, and
14
in which naming involves spread of activation in these two distributed and interrelated
networks (Davis & Baynes, 2009; Davis, Harrington, & Baynes, 2006).
Current models of spoken word production emphasize the identification of
processing levels necessary for lexical access and single word retrieval (Hashimoto &
Thompson, 2010). Although details of the lexical model are the subject of debate
(Hashimoto & Thompson, 2010; Raymer, 2005), it is widely agreed that at least two
lexical stages or levels of representation, semantic and phonological, are critical to the
process of word retrieval that occurs as part of normal language output (Caramazza,
2000; Raymer, 2005) and that speakers with aphasia make errors that arise at either or
both of these levels (Davis, Harrington, & Baynes, 2006). The “semantic processing level
governs operations involved in lexical selection of an intended concept” while the
“phonological processing level governs operations involved in its phonological
specification” (Hashimoto & Thompson, 2010). Psycholinguistic stage models such as
that proposed by Levelt (see Figure 1) postulate discrete movement from stage to stage,
involving both lexical selection (semantic level) and form encoding (phonological level)
(Davis et al., 2006). In this type of model, naming is primarily a serial or sequential
process in which “feed-forward” patterns of spreading activation result in a “top-down”
flow of information moving in one direction only (Hashimoto & Thompson, 2010;
Levelt, Roelofs, & Meyer, 1999). The speaker begins with a conceptual preparation or
communicative intention, and then proceeds to lexical selection (retrieving a word, or
more specifically a lemma, or “package of syntactic information” about a word, from the
mental lexicon) in a high-speed process that is “surprisingly robust” in normal speakers,
15
allowing for the retrieval of two to three words per second (Level et al., 1999). Only once
the syntactic word or lemma has been selected can the speaker “cross the rift” between
the lexical selection (conceptual/semantic/syntactic) domain to the form encoding
(phonological/articulatory) domain, a crossing whose momentary failure (occurring when
a lemma has been selected, but perhaps with insufficiently strong activation, leaving the
speaker unable to retrieve the corresponding word form) is known as “tip-of-the-tongue”
phenomenon (Levelt et al., 1999).
Levelt’s model is especially useful in helping to conceptualize the steps that must
occur before a word is articulated, and how a speaker making a lexical selection without
proceeding to the final step of articulation may, with the assistance of the self-monitoring
process, or “internal monitoring loop” (Levelt, 1983,1993) that occurs during inner
speech, obtain the semantic-level practice necessary to increase spread of activation while
preventing speech errors. According to the author, “as long as the buffered internal
speech has not been articulated,” the brief interruption in the process caused by the
speaker checking the accuracy of his or her speech as it passes through the internal
monitoring loop “can prevent the production of an error” (Levelt, 1993). Levelt’s model
assumes “competition, but no inhibition” of competitors during lexical selection,
although node selection is “subject to competition” from distractors or competitors
(Levelt, Roelofs, & Meyer, 1999) in what is sometimes referred to as the “semanticinhibition effect” (Levelt, 1999).
When you are naming a picture of a sheep and you decide to go for the basic level
term, you will activate the lexical concept sheep as your target and activation
16
spreads to the corresponding lemma. In the semantic network activation spreads
to related concepts, such as goat and llama. They, in turn, spread activation to
their lemmas. . . . In other words, there is competition between semanticallyrelated lemmas. Active alternatives slow down the selection process . . . If you
present the semantically related word goat as a distracter, the already-activated
lemma goat will receive an additional boost, thereby becoming a strong
competitor to sheep. By contrast, if you present a semantically unrelated word,
such as chair, as a distracter, there will be no convergence of activation and,
correspondingly, competition will be relatively weak. That explains the semanticinhibition effect. (Levelt, 1999, p. 228)
Other models (Dell, 1986; Dell & O’Seaghda, 1992) describe a similar process,
but assume a more cascaded and continuous flow of information and “without any need
for a particular meaning or lexical item to be selected before the next level initiates
processing” (Davis, Harrington, & Baynes, 2006). Recent intensive production-free
treatment investigations have concentrated on the semantic level of processing, assuming
“an interactive account” of naming, with intra-level activation and bi-directionality of
inhibition and excitation between levels (Davis et al., 2006). This model of naming
assumes a continuous information transmission whereby activation (both excitation and
inhibition) occurs throughout the network in a generalized top-down manner
(Humphreys, Price, & Riddock, 1999). The process has been described this way:
Each stage consists of processing the stored structural, semantic, and/or
phonological aspects of the target. Structural characteristics are the perceptual
17
aspects of the picture or object, such as color, shape, and size; semantic
characteristics are the associative and categorical aspects of the object; and
phonological characteristics are the sound representations. At each level of the
processing network, there are excitatory and inhibitory connections to related
items that are co-activated by the object. The strength of the activation of the
target must exceed its semantic competitors to successfully go to the next level
and reach phonological encoding. If the target is not substantially stronger than its
semantic or phonological alternatives, then a competitor will achieve activation
and hence an error will be produced. (Davis et al., 2006, p. 62)
The amount of activation depends on two factors: the strength of connections among
units and the rate by which activation decays. After a period of time, the most activated
word is selected (Davis & Baynes, 2009; Hashimoto & Thompson, 2010). Naming errors
are thought to occur at either level, when a competitor achieves higher activation than the
target and/or is insufficiently inhibited, and is therefore inappropriately selected for
production (Davis & Baynes, 2009; Davis & Farias, 2010). Production-free, semanticlevel interventions are based on improvements of reaction time and accuracy during
semantic and phonological priming, a benefit believed to arise from activation of neural
networks and well-documented in fMRI studies (Ruff, Blumstein, Myers, & Hutchinson,
2008). The use of a lexical entry—even a use that precludes explicit articulation of the
name of the target—is assumed to result in its being ‘primed’; that is, the activation
threshold needed to produce the word will be temporarily lowered, increasing the
18
likelihood of an accurate verbal response during subsequent naming attempts (Howard et
al., 1985a).
Recent approaches to intervention rest on the assumption that a widely
distributed, interactive semantic network supports naming, and that a neurological injury
such as a stroke or TBI can cause interruptions in this network, which in turn disrupts
naming (Davis & Baynes, 2009; Davis & Farias, 2010; Davis, Harrington, & Baynes,
2006; Drew & Thompson, 1999; Hashimoto & Thompson, 2010; Raymer, 2005).
According to Levelt, “activation spreading through a semantic network” is “the obvious
explanation for semantic naming errors, the dominant speech error type” for individuals
with aphasia (Levelt, 1999). It has been posited that an intervention that seeks to improve
speech production by implementing semantic level treatment may have “the best chance
of restoring or redirecting the flow of activation” (Davis et al., 2006). In addition,
semantic-based treatment, when combined with a production-free approach, allows for
exploitation of the normal process of inner speech monitoring, a necessary precursor to
self-correction and self-monitoring of overt speech for increased accuracy of speech
production and the avoidance of explicitly articulated naming errors.
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Figure 1. Outline of Levelt’s (1999) theory.
Preparing to produce a spoken word “proceeds through stages of conceptual preparation,
lexical selection, morphological and phonological encoding, and phonetic encoding
before articulation can be initiated” (Levelt, Roelofs, & Meyer, 1999). Output
monitoring, or self-monitoring of inner speech, occurs prior to overt articulation in a
process which involves the speaker’s normal speech comprehension mechanism (Levelt,
et al., 1999) and which can be exploited to allow for mental practice without the
possibility of unintended error practice during implicit therapy interventions.
Semantic-based intervention
The semantic system (the store of meanings and information an individual has
learned about words, objects, or actions) is known to play a common role in both word
comprehension and word retrieval (Raymer, 2005). Numerous studies suggest that
semantic-based interventions can result in improvements in naming ability (Coelho,
20
McHugh, & Boyle, 2000; Davis, Harrington, & Baynes, 2006; Drew & Thompson, 1999;
Howard, Patterson, Franklin, Orchard-Lisle, & Morton, 1985a, 1985b; Kiran, 2008; Pring
et al., 1990; Scott, 1987), even in patients with good semantic processing (Nickels &
Best, 1996) and patients whose deficits are partly or primarily phonological rather than
semantic (Raymer, 2005). Dukette, Baynes, Redfern, Share, Ludy, and Dronkers (1998),
after grouping participants into those whose errors were primarily phonological in nature
and those whose errors were primarily semantic in nature and exposing both groups to
both phonological and semantic therapy, found that while phonological training was of
greatest benefit to participants with more phonological errors, semantic training was
effective for both groups. The reasons for this may have to do with semantic processing
and its role in the larger process underlying naming. Although there is no single agreedupon model of semantic processing (Behrmann & Lieberthal, 1989; Nickels & Best,
1996), it is helpful to recall that the process underlying object naming is thought to
involve a continuous information transmission, wherein activation, both excitation and
inhibition, occurs throughout the semantic network in a generalized top-down fashion
(Davis & Baynes, 2009; Davis et al., 2006; Kiran, 2008). The fundamental assumption of
semantic-based treatment has been “the spreading activation theory of semantic
processing” which holds that “by activating the semantic network surrounding the target,
the target itself may be activated above its ‘threshold’ level, increasing the probability
that its name can be retrieved” (Coelho, McHugh, & Boyle, 2000). One reason semantic
therapy may work to increase naming even for patients with primarily phonologic deficits
may be “that strengthening access to semantic attributes results in facilitation of target
21
semantic nodes at the semantic level, which cascades downstream to the phonological
representations, thereby strengthening phonological nodes as well” (Kiran, 2008). Also,
as some authors have noted, semantic interventions are thought to be potentially
advantageous based on the assumption that the neural network supporting semantic
knowledge is more widely distributed than the one supporting phonological knowledge
(Davis & Baynes, 2009).
In contrast to confrontation naming or repetition tasks, wherein a patient may be
asked simply to verbally produce the name of the target, semantic training refers to
“techniques that require the patient to process the meaning” corresponding to the name
(Howard et al., 1985b). Howard et al. (1985a), noting that semantic facilitation effects
last longer than the effects of naming tasks providing phonemic cueing, argued that the
longer-lasting effects of the semantic therapy were due to “priming of a word-specific
lexical semantic representation”; in other words, access to semantics in the
comprehension task primed a lemma representation, and this primed lemma was then
more easily accessible when the picture was subsequently presented for naming”
(Howard, 2000). The finding that “a single semantic task could improve the accessibility
of a target word for at least 24 hours, in contrast to phonological techniques, which have
only short-lasting effects, prompted the first systematic use of these tasks in treatment”
(Howard, 2000). It has been posited that tasks which require a search in semantic
memory have greater long-term effects than the relatively automatic production of a word
in response to a cliché cue (Cohen et al., 1979; Howard et al., 1985a; 1985b). Nickels and
Best (1996) hypothesized that semantic-based therapy may work either by facilitating
22
general semantic processes or through the use of a specific strategy (perhaps
unconscious) of exploring the semantics of an item, which, when naming fails, may
facilitate retrieval of that item.
Many different techniques have been considered semantic interventions, including
auditory or written word-to-picture matching, answering yes/no questions about the
target, picture and spoken word categorization, and judging relatedness of target words to
a series of pictures (Drew & Thompson, 1999; Raymer, 2005). One technique “that
characterizes the general philosophy” behind many semantic-based aphasia treatments is
semantic feature analysis, or SFA (Nickels, 2002). Although SFA applications differ
across studies in terms of precise task requirements (Boyle, 2001), the general procedure
is that the patient is first provided with a picture and asked to name it, and is then
encouraged to describe the semantic features of the target, for example listing its group,
use, action, properties, location and association (Coelho, McHugh, & Boyle, 2000;
Nickels, 2002). A “matrix of printed cue words” regarding the object’s semantic features
may also be presented along with the target picture, to assist in the process (Raymer,
2005). Boyle (2001), in a review of four studies employing SFA, reported that SFA
training, when provided at sufficient intensity, led to improved naming of trained pictures
and generalization to some untrained pictures. Coelho et al. (2000), using SFA in an
intervention designed “to increase the activation in the semantic network,” posited that
“by activating the semantic network surrounding the target word, that word may be
activated above its threshold, thereby facilitating retrieval.” The authors reported that
SFA resulted in improved confrontation naming on trained and untrained items, and was
23
associated with modest improvements in measures of connected speech, with naming
accuracy improved at a two-month follow-up (Coelho, et al., 2000). Hillis (1991) used a
similar technique, in which the participant was first asked to name a picture, and then, if
the naming attempt resulted in a semantic error, a drawing of the error was made and
compared to the target picture, after which semantic differences between the two were
discussed. The treatment resulted in improvements in word comprehension as well as in
both verbal and written naming (Hillis, 1991).
Semantic interventions have differed as to whether the participants’ exposure was
purely semantic or whether the target word form (either spoken or written) was provided
at any point during training. Although some authors have noted an advantage for purely
semantic treatment over phonological treatment that provides the patient with information
about the phonological form of a name (Howard et al., 1985b), evidence from other
studies has indicated that semantic treatment that includes at least some aspects of
phonologic treatment (e.g., provision of the spoken or written word form) may be most
efficacious (Baynes, Share, & Redfern, 1995; Boyle & Coelho, 1996; Drew &
Thompson, 1999; Howard et al., 1985a; Le Dorze, Boulay, Gaudreau, & Brassard, 1994;
Thompson et al., 1986). Le Dorze et al. (1994) compared the effects of a purely semantic
technique (a semantic comprehension task without the word form) with a “formalsemantic facilitation technique” in which information about the spoken or written word
form of the target was provided. The researchers found that while there was no change in
naming for items treated with the purely semantic technique, naming improved
significantly for items treated with the formal-semantic technique. They posited that
24
“inclusion of word forms in the semantic tasks is a critical element” of naming
facilitation techniques (Le Dorze et al., 1994). In a study conducted by Drew and
Thompson (1999), semantic treatment for a group of four Broca’s aphasics with
identified semantic-level deficits consisted of a sorting task, a yes/no judgment task, and
a definition-to-picture matching task, with no explicit naming, no orthography, and “no
phonological information made available to participants” during treatment. Results were
mixed; two of the participants showed treatment effects and two did not. When additional
semantic treatment including the word form was provided, the two participants who had
not shown effects for the semantic treatment showed immediate improvement in picture
naming, whereas the two who had already demonstrated semantic treatment effects
showed a further increase in picture naming. The authors concluded that further research
was necessary to “clarify the differences between pure semantic treatments and those that
include the word form or their additive effects” (Drew & Thompson, 1999).
Howard (2000), considering evidence showing that patients with the least
semantic impairment made the most improvement, noted that if semantic therapies were
effective at a purely semantic level, “the treatment should be primarily effective for
subjects with a semantic impairment.” He put forth the hypothesis that so-called
“semantic therapy” may work not on a semantic level as previously assumed, but instead
by strengthening “the mapping from semantics to phonology,” or in other words, through
simultaneous activation of semantics and phonology. He noted that this hypothesis
(supported by “abundant” evidence that normal subjects automatically activate the
phonological representations of words when comprehending the words in written form)
25
provides a simple explanation for the fact that semantic therapy treatment effects tend to
be item-specific rather than generalizing to untreated items (Howard, 2000).
Semantic treatments have generally yielded improvements, however (Howard et
al., 1985b; Nickels, 2002), and in some cases have not only resulted in generalization to
untrained items (Boyle & Coelho, 1985; Coelho, McHugh, & Boyle, 2000) but also in
generalization to connected speech (Coelho et al., 2000; Davis, Harrington & Baynes,
2006). Boyle and Coelho (1995), applying semantic feature analysis treatment with a
Broca’s aphasic, found that generalization to untreated items occurred when as few as
seven exemplars were treated, although the authors noted that “whether such a small
number of exemplars is sufficient for other subjects with aphasia is not clear.” In a
replication of that study, Coelho et al. (2000) found that generalization to untreated items
was noted to be more substantial when only a small number of exemplars were trained.
In some cases, semantic treatments have resulted in impressive speech production
improvements for patients who had previously failed to improve despite long exposure to
therapy. Jones (1986) used a semantic intervention to improve sentence production in a
patient with non-fluent aphasia whose single word output had remained unchanged for
six years despite long-standing, intensive speech therapy. The author concluded that
previous therapy may have been ineffective because it had focused on “the more
superficial aspects” of the patient’s deficit, “ignoring the fundamental problem in
mapping meaning relations between semantics and syntax” (Jones, 1986).
The most important factor determining the success of a semantic intervention may
be the precise type of task and its requirements. Howard, Patterson et al. (1985a) noted
26
that although many “schools of aphasia therapy assume that eliciting a response from an
aphasic patient makes it more likely that the patient will subsequently be able to produce
that response without the help of a therapist,” the evidence suggests that “the true picture
is more complex; it is crucially important how responses are elicited.” Nickels and Best
(1996) observed that “not every ‘semantic’ task can be expected to produce the same
results,” and that semantic therapy “clearly cannot be considered a unitary treatment;
slight changes in the nature of the task and its presentation may radically affect the
effects of the therapy on naming.” The authors concluded that the “form of the semantic
task influences the outcome; one semantic task may not be as good as any other” (Nickels
& Best, 1996).
Semantic interventions that use word-to-picture matching tasks or otherwise
employ pictures during training may produce greater improvements in naming than other
types of interventions (Nickels, 2002; Raymer & Ellsworth, 2002). Word-picture
matching tasks have been demonstrated to produce effects lasting as long as a year in
some studies, including small but significant improvement for untreated items that were
semantically related to treated items (Pring, White-Thompson, Pounds, Marshall, &
Davis, 1990). Word-picture matching tasks may have an advantage due to the changes in
processing associated with the addition of picture stimuli to purely auditory or auditoryorthographic stimuli. When a patient is presented with a picture to name, “activation
cascades through the lexical system, engaging visual, semantic, and phonogic
information relevant to the picture” (Nickels, 2001). Some authors have suggested that
there might be “specifically visual or pictorial semantics which is at least partially
27
independent from the verbal semantic system” (Howard et al., 1985a), which may help
explain why the meaning of a word is more likely to be activated during a repetition task
if the repetition is carried out in the presence of a picture (Whitworth, Webster, &
Howard, 2005). Semantically-based tasks requiring word-to-picture matching are “often
very effective,” and their use “is justified in that they stand a very good chance of
working for the maximum number of people” (Best & Nickels, 2000). Raymer and
Ellsworth (2002), in a comparison of semantic interventions with repetition treatments
designed to improve verb retrieval, concluded that “the presence of the picture stimulus”
used in all treatment conditions may have been the “key factor” that influenced treatment
outcomes. The authors posited that their positive findings for all treatments may have
been related to “semantic activation that occurs whenever a word is retrieved in the
context of picture presentation, thereby fundamentally altering semantic activation
patterns and making the word more easily accessible in subsequent retrieval attempts.”
They concluded that different treatments could be equally effective in improving verb
naming abilities in some individuals “as long as training takes place in the context of
pictured targets” (Raymer & Ellsworth, 2002).
Achieving significant improvements in naming ability may require more than just
inclusion of picture stimuli, however. Howard et al. (1985a) found that the tasks which
resulted in the most substantial and long-lasting improvements in naming ability were
“comprehension tasks requiring the subject to access a semantic representation
corresponding to a picture name,” although the authors hypothesized that the key factor
affecting outcomes may have been the requirement of making semantic judgments, rather
28
than the influence of the visual stimuli itself. Along with semantic judgments, the type
and/or number of pictures presented has been shown to be of potential importance in the
success of anomia investigations incorporating picture stimuli. Nickels & Best (1996)
found long-lasting improvement in the naming abilities of several patients with semantic
therapy using written word-to-picture matching, with each training set consisting of one
target picture and three other pictures representing semantic distractors. Using this
technique, the authors found significant improvements in naming in treated items and
some evidence of generalization to untreated items, although only the treated items
showed long-lasting effects of therapy (Nickels & Best, 1996). The authors concluded
that perhaps “it is the use of a task where four semantically related pictures are presented
which is important” (Nickels & Best, 1996). Investigations into adult brain plasticity
elicited by anomia treatment using picture stimuli have resulted in similar conclusions.
Cornelissen et al. (2003) showed improved naming accompanied by increased lefthemisphere activation in all participants using a contextual priming technique wherein
target items (e.g., a cow) were presented along with other semantically related items (e.g.,
a larger set of farm animals) rather than in isolation. According to the authors, “the
semantic network representing domestic animals is activated because the picture of the
cow is presented in the context of other semantically related items. This enhanced activity
in the semantic network facilitates transfer of activity from the semantic to the
phonological stage, and naming may succeed” (Cornelissen et al., 2003).
One potential problem with word-picture matching tasks, although they are often
classified as “error-reducing” (Davis & Baynes, 2009), is that they usually involve the
29
requirement of explicit verbal production of the target. This requirement is not unique to
word-picture tasks, of course; most standard speech therapy approaches for aphasia
require verbal responses from the individual (Davis & Baynes, 2009; Raymer, 2005), and
repeated verbal practice is “inherent to nearly all anomia treatment protocols” (Off,
Kavalier, & Rogers, 2008). For patients whose verbal errors are prevalent, this can result
in the unintended consequence of the patient actually “practicing” his or her errors (Davis
& Baynes, 2009; Nickels & Best, 1996), or, in effect, inadvertently “practicing a
mistake” (Davis, Harrington & Baynes, 2006). As Turkstra and Bourgeois (2005) have
speculated, the re-learning of speech and language in adults with acquired neurological
disorders may engage communication processes known to be especially vulnerable to the
effects of errors. The authors concluded that increased “attention to errors may benefit
patients” with acquired neurological disorders (Turkstra & Bourgeois, 2005).
Errorless and error-reducing approaches
Errorless learning has a long history. Grounded in research on neural plasticity
(Hebb, 1961), the success of errorless learning approaches has been linked to increases in
synaptic strength (Frattali & Kang, 2004). Although errorless learning was first proven
successful in animal research, a number of errorless learning approaches have since been
shown to significantly improve learning in patients with amnesia and other memory
impairments (Turkstra & Bourgeois, 2005). One reason for the success of errorless
learning approaches may be that they reduce feelings of frustration or discouragement
that might result from more errorful training, and correspondingly increase the
individual’s feelings of success (Davis & Farias, 2010). As has often been noted, therapy
30
designed to ensure a certain level of success appears to help sustain patient motivation
(Howard et al., 1985a; Webster & Gordon, 2009). Whatever the mechanisms behind the
success of such therapy, recent evidence suggests that errorless learning approaches can
benefit everyone, even young, non-neurologically impaired individuals (Baddeley &
Wilson, 1994). Such approaches may therefore be effective with a wide variety of
patients requiring speech and language services, “particularly when teaching changes in
articulation, specific sentence structures, the use of compensatory strategies, or
augmentative device use” (Turkstra & Bourgeois, 2005). Errorless learning approaches
have been shown to help remediate deficits for individuals with aphasic disorders,
particularly anomia (Baddeley & Wilson, 1994; McKissock & Ward, 2007), and have
been shown in neuroimaging studies to result in neural activation patterns more
consistent with activation patterns observed in normal controls (Fillingham, Hodgson,
Sage, & Lambon Ralph, 2003; Jackson, Lafleur, et al., 2003).
In traditional therapy, patients who do not know the answer to a question are
typically “encouraged to guess or learn via trial-and-error” (McKissock & Ward, 2007), a
condition which researchers have described as “errorful” (Baddeley & Wilson, 1994).
Errorless learning, by contrast, is based on the principle that “errors generate errors”
(Brookshire, 1979)—in other words, that the mere production of an incorrect response
may be self-reinforcing, making the incorrect response more likely to occur on
subsequent occasions (Baddeley & Wilson, 1994; McKissock & Ward, 2007; Turkstra &
Bourgeois, 2005). Because of this self-reinforcing tendency of errant behavior, the
probability of correct responses decreases with each error production (Brookshire, 1979).
31
The opposite also appears to be true; Frattali and Kang (2004) note that “if a stimulus
elicits an errorless response, [errorless] learning will strengthen the tendency to activate
the same pattern of response on subsequent occasions.” Treatment is therefore more
likely to be successful if patients are not only assisted in providing correct responses but
also prevented from reinforcing their own errors (Brookshire, 2007; Frattali, 2004).
Although the definition for “errorless” (sometimes also called “error elimination”)
methods varies depending on the source, the term is generally used to refer to any type of
treatment or approach whereby the task is manipulated to eliminate or reduce errors
(Fillingham et al., 2003; McKissock & Ward, 2007). Fillingham et al. (2003) noted that
although the aphasic literature contained no examples of purely errorless learning
methods, some studies had shown that anomia could be successfully treated using errorreducing techniques. Techniques described as “errorless” or “error-reducing” typically
consist of the clinician verbally providing the participant with the correct response to an
item before asking them to verbally provide the response themselves (Turkstra &
Bourgeois, 2005) during tasks such as confrontation naming (e.g., “I’m going to show
you a picture, then I’m going to say the name of the object, then I want you to say the
name of the object”), or by otherwise lowering the difficulty level of the task to the point
that errors become very unlikely (Baddeley & Wilson, 1994; Fillingham et al., 2003).
Researchers have noted several problems with such techniques. Because such
tasks “are unlike real language use” and because “errorless paradigms can seem
inherently boring” to patient, clinician, or both (Fillingham et al., 2003), they may fail to
pose sufficient challenge, and therefore fail to fully engage the patient’s focus. The best
32
condition for learning is one that prevents errors while also requiring effort on the part of
the learner (Komatsu et al., 2000). A lack of sufficient task difficulty may have been a
factor in studies demonstrating that errorless learning, though it improved naming in the
short term, was shown to have limited long-term benefit (McKissock & Ward, 2007).
An even more basic problem is that whether or not the target production is
modeled/ provided by the clinician in advance, in most “errorless” or “error-reducing”
interventions, the patient is still required to verbally produce the response (Fillingham et
al., 2003; Turkstra & Bourgeois, 2005); logically, then, despite claims that “by providing
[the patient with] a correct response at the outset, [errors] can be avoided” (McKissock &
Ward, 2007), the potential for errors of speech production still exists. Although some
authors have classified tasks in which the patient is provided with a whole-word cue (in
effect being given the answer to the question before being required to answer it) as “error
eliminating” (McKissock & Ward, 2007), the reality is that for many patients, even
simple word repetition tasks (“Repeat after me; say _____”) can be fraught with the
potential for error (Davis & Baynes, 2009). The fact that “errorless” therapies have
traditionally focused on eliminating errors of word retrieval rather than errors of speech
production may help explain the surprising and counterintuitive results of “errorless-vs.errorful” treatment studies, wherein some authors have concluded that “there is little
compelling evidence to suggest that errorless learning . . . outperforms errorful learning
in the treatment of anomia” and that “it does not matter whether anomic patients are
allowed to make errors” (McKissock & Ward, 2007).
33
The success of “errorless” interventions may depend upon “matching the type of
training to the nature of patients’ errors” for maximum effect (Davis & Baynes, 2009).
Because they only target errors at the level of word retrieval (rather than speech
production), many “errorless” or “error-reducing” treatment methods ignore the
possibility that for many patients, the most harmful, self-reinforcing errors (and therefore
the errors arguably most in need of reduction or elimination) may be errors of speech
production. It would appear that the way to eliminate or reduce speech production errors
is to focus not on simplifying the word-retrieval task, but on changing the task so as to
eliminate the requirement of speech production in patient responses. Errors of speech
production, such as verbal and literal paraphasias and perseverations, “are pervasive in
aphasia and can interfere with treatment” (Davis, Harrington & Baynes, 2006). When an
individual with prevalent naming or speech production errors is required to give verbal
responses, one consequence is “the unavoidable production of errors, which may
inadvertently strengthen unwanted neural-motor pathways” (Davis, Farias, Baynes,
Chand, & Orgun, 2007). According to Veterans Affairs and Department of Defense
clinical practice guidelines, the goals of post-stroke rehabilitation include not only
helping to maximize recovery of communication abilities, but also to help “prevent
learning of ineffective or inappropriate compensatory behaviors” (U.S. Department of
Veterans Affairs, 2003). Surely, in the case of a patient for whom verbal errors are
prevalent and represent a significant component of the communication impairment, such
behaviors might reasonably be supposed to include the production of self-reinforcing
verbal errors, to whatever degree such production can be avoided during therapy.
34
Recent evidence suggests that performing semantic- based tasks which are free of
the requirement of spoken responses (and which thereby eliminate many, if not most,
potentially self-reinforcing verbal errors) can yield improvements for patients, especially
those for whom verbal errors are especially prevalent or frustrating (Davis & Baynes,
2009; Davis, Harrington, & Baynes, 2006). Nickels and Best (1996) noted that “large
and robust facilitating effects” of semantic processing therapy had been found even for
tasks with no requirement of speech production of the target during training, and
concluded that for some patients at least, explicit production of the target appeared to be
unnecessary. Howard et al. (1985a) found that semantic-based therapy resulted in
“dramatically improved accessibility of the name that lasts for at least 24 hours,” even
though such techniques did not require patients to articulate the names of the pictures. In
a type of target-production-free (or at least production-reducing) intervention described
as “error-reducing” by some authors (McKissock & Ward, 2007), Frattali and Kang
(2004) asked their anomic patients to discuss a picture without naming it, a task which
was shown to be beneficial relative to an untreated set. Studies have shown that half an
hour after successfully producing the picture name in response to a phonemic cue, an
aphasic patient is no more likely to be able to name the same picture than if it had not
been cued (Patterson, Purell, et al., 1983). If, on the other hand, the patient is simply
asked to point to that picture out of a choice of four, he is “substantially more likely to be
able to name the picture half an hour later (or, indeed, 24 hours later) than if he had not
been given this treatment” (Howard et al., 1985a).
35
Implicit therapy
Semantic interventions that rely on judgments and do not require explicit naming
are thought to provide activation of the semantic networks that support naming “while
minimizing the introduction of errors” (Davis, Harrington & Baynes, 2006). This type of
speech therapy that does not require spoken responses is often referred to in the literature
as “implicit therapy.” The approach is said to be ‘implicit’ in that “it requires no verbal
response, in contrast to most traditional treatment methods” (Davis & Baynes, 2009) and
in contrast to “standard techniques which require patients to speak as part of their
treatment” (Davis & Farias, 2010). Implicit interventions are based on the same
principles as errorless or error-reducing methods, but with the added benefit of
specifically reducing or eliminating precisely those types of errors—namely, speech
production errors—which are often most problematic and most self-reinforcing for
aphasic clients (Davis & Baynes, 2009). While most error-reducing methods require
explicit speech production (Fillingham et al. 2003), implicit methods use “semantic and
phonological judgment tasks in the absence of explicit naming to produce learning with
fewer errors than traditional interventions” (Davis & Baynes, 2009). Implicit
interventions have been effective in patients with a wide range of disorders, and have
been shown to improve naming in patients with aphasia (Baynes, Share, et al., 1995;
Dukette, Baynes, et al., 1998; Davis, Harrington, et al., 2006). Researchers “have
continued to develop this implicit method and to apply it to a broader range of aphasic
disorders at the level of single case studies” (Davis & Baynes, 2009).
36
Investigators employing implicit methods acknowledge that their ongoing use of
the term “implicit” is somewhat problematic, and that it is ongoing mainly due to lack of
a more precise (yet concise) alternative. Although the term “implicit therapy” is known to
its primary researchers and practitioners to refer to training which “involves a mental
practice that uses the prearticulatory ‘inner speech’ mechanism and a spread of activation
into other related verb/noun/tactile event nodes,” there are “no one or two words”
sufficiently descriptive to do it justice (C. Davis, personal communication, March 18,
2010). Referring to implicit interventions as “interventions requiring non-verbal
responses” lacks elegance as well as specificity regarding type of task (e.g., semantic
decision-based), and although “error-reducing” might be a partial solution to the
question of what to call this type of therapy, “errorless” is, strictly speaking, inaccurate
(K. Baynes, personal communication, March 15, 2010). Acronyms such as NoVERT
(Non-Verbal Error Reducing Therapy), REST (Reduced Error Semantic Therapy), and
REPT (Reduced Error Phonological Therapy) have been proposed and used as alternative
terms in some studies (K. Baynes, personal communication, July 25, 2010). However,
since these acronyms do not specify the type of error (verbal) that is being reduced, and
since the term “implicit” has received increasingly widespread use in the research
community to refer to interventions that do not require explicit articulation of target
responses (Wambaugh, 2010), the terms “production-free” and “implicit” are used
interchangeably in the present study to refer to therapy tasks free of the requirement of
speech production.
37
Part of the problem with the “implicit therapy” label is that it can be confused
with the term “implicit learning,” which refers to learning that occurs outside conscious
awareness (Turkstra & Bourgeois, 2005). Implicit therapy, by contrast, occurs with the
patient’s full conscious awareness, explicit consent, and active participation. The
importance of the patient’s understanding both the particular task requirements and the
overall goals of therapy is undisputed in the implicit therapy literature. This may have
contributed to the success of many implicit interventions conducted to date, since
evidence suggests that greater transparency between therapy task and goals of improved
speech production may increase the efficacy of intervention (Webster & Gordon, 2009).
Implicit therapy does share one important characteristic of implicit learning, however. A
key feature of implicit learning is that it is “probabilistic,” meaning that “the probability
of learning a new association is dependent on the relative frequency of correct responses
versus errors,” and therefore, for optimal learning, tasks should be designed to minimize
errors (Turkstra & Bourgeois, 2005). This focus on error reduction is also a key feature,
and in fact forms the foundation, of implicit therapy methods (Davis & Baynes, 2009).
Mental practice and inner speech
Implicit therapy interventions reduce production errors by discouraging speech
while requiring intensive “mental practice” during rehabilitation (Davis, Farias, Baynes,
Chand, & Orgun, 2007). Mental Practice, mental imagery, and implicit practice are used
to describe techniques in which an individual thinks about performing a task but does not
actually execute the task. Implicit techniques have been used widely in physical
rehabilitation, and have demonstrated that the neural substrates that underlie motor tasks
38
are activated during implicit practice and imagery (Braun, Beurskens, Borm, Schack, &
Wade, 2006; Harrington, Farias, & Davis, 2009; Jackson, Lafleur, Malouin, Richards, &
Doyon, 2003). During mental practice, “an internal representation of the movement is
activated and the execution of the movement is repeatedly simulated, without physical
activity” (Braun et al., 2006). Recent evidence suggests that motor imagery training may
help access the motor network independently of recovery, increasing motor recovery after
stroke (Sharma, Pomeroy, & Baron, 2006), even in patients with complete spinal cord
injury (Cramer, Orr, Cohen, & Lacourse, 2007). Authors have noted that although these
techniques have received much more attention in the fields of sports psychology and
physical and occupational therapy (Davis, Farias et al., 2007), mental practice is
increasingly being acknowledged as a technique that “may need to be considered” as a
complementary treatment technique in the field of speech pathology (Van der Merwe,
2007). Recent studies have shown that both aphasia and apraxia of speech may be well
suited to this type of intervention, for reasons related to the process of pre-articulatory
editing of inner speech that occurs prior to overt speech.
Pre-articulatory editing, the process of detecting and suppressing speech errors
prior to overt speech production, “may be viewed as a form of self-monitoring of overt
speech” using the inner speech loop (Davis, Farias, & Baynes, 2009). Levelt, Roelofs,
and Meyer (1999) hypothesized that “the person to whom we listen most is ourself” and
that “just as we can detect trouble in our interlocutor’s speech, we can discover errors,
dysfluencies, or other problems of delivery” in our own inner speech, as well as in our
own overt speech. Levelt et al. (1999) claimed that inner speech is produced in essentially
39
the same way that we speak, but without the final stage of overt articulation. Selfmonitoring of inner speech occurs after speech preparation but prior to articulation, as the
inner speech is “heard” by the speaker through an inner loop that transmits the speech
plan at the phonological level (Levelt, 1983, 1989). This inner loop feeds the constructed
phonological word back into the speech comprehension system for monitoring. The
process of pre-articulatory editing allows the speaker to mentally practice speech
production while internally monitoring his or her planned utterances for errors, thereby
“allowing a correction prior to speech production” instead of executing a speech error,
which could then make the error much more likely to occur on subsequent attempts
(Davis, Farias, & Baynes, 2009). It is possible that resource allocation also plays a part
in the success of implicit interventions, since the practice these interventions afford is
solely mental, and therefore free of the additional effort required for physical articulation.
Davis and Farias (2010) suggested that “aphasic individuals can benefit from practice in
semantic-lexical or phonological decision-making when they are free from the additional
burden of actual word production.”
Apraxia of speech (AOS) is generally agreed to be a breakdown in the motor
programming or motor planning process of speech production. Even so, “traditional
approaches to treatment of AOS have incorporated motor execution into therapeutic
activities despite the consensus that the breakdown probably occurs prior to speech
execution” (Davis, Farias, Baynes, Chand, & Orgun, 2007). In a review of apraxia
treatment studies conducted through 2003, the Academy of Neurologic Communication
Disorders and Sciences (ANCDS) found that one commonality observed across all
40
investigations was motoric practice of speech targets, or in other words, “verbal
production was requisite” in all studies (Wambaugh, Duffy, McNeil, Robin, & Rogers,
2006). New studies, however, have provided evidence that phonological awareness
training can yield positive results in the absence of overt production, and that implicit
therapy targeting phoneme manipulation can result in improved speech production for
patients with AOS (Davis, Farias, Bord, & Baynes, 2006). Farias, Davis, and Whittmann
(2009) used an implicit intervention requiring intensive mental practice with phoneme
manipulation tasks to improve consonant blend production in an individual with a
primary diagnosis of AOS. The authors, who posited that the patient’s concurrent
improvements in auditory discrimination may have been “a byproduct of mental
practice,” concluded that their findings supported “the use of mental practice as a
complementary technique to overt practice.” Treatment for AOS, the authors noted, “is
well suited to mental practice, as it requires the individual to focus on inner speech, a
necessary precursor to self-correction and self-monitoring for accurate overt speech”
(Farias, Davis, et al., 2009). In another case study, Davis, Farias, and Baynes (2009)
found that intensive therapy requiring implicit phoneme manipulation improved speech
sound production and resulted in significant generalization to untreated words for a
patient with mild aphasia whose primary speech disturbance was AOS. Neuroimaging
studies have supported these findings; phoneme manipulation tasks performed mentally,
without speech production, have been shown to activate regions of the brain known to be
activated during motor planning and programming (Davis, Farias, & Wilson, 2011). New
ANCDS AOS Treatment Guidelines, currently being updated based on evidence obtained
41
from studies conducted since the last review in 2006, will include implicit therapy
evidence (Shuster, 2011; Wambaugh, 2010).
Implicit therapy interventions incorporating intensive mental practice have been
used as supplementary techniques in the rehabilitation of patients with a wide variety of
disorders. Baynes, Truong, Jonathan, Farias, and Davis (2008) employed an implicit
method in combination with explicit therapy requiring verbal responses to improve the
reading of grammatical morphemes in a patient with phonological alexia. The patient, a
mildly anomic aphasic with moderate alexia, was highly motivated to improve his
impaired reading ability so that he could read to his child. He began each session by
explicitly reading aloud a set of probe words, but also practiced reading using a
computerized implicit intervention. During implicit training, each trained word was
presented visually on the computer screen for 500 ms, followed by an auditory
presentation of a word that either matched the presented word or not; the participant’s
task was to respond nonverbally by pressing a button indicating “match” or “no match.”
Foils were unrelated, phonologically related, or related in both sound and word class
(e.g., for target him, foils were cash, hem, and his). The participant took the computer
home in between sessions for additional unsupervised practice. Results indicated that the
combined explicit and implicit training increased accuracy of word retrieval, although
improvement appeared to be limited to reading fluency (Davis & Baynes, 2009).
Development of the implicit method for treatment of aphasia
Implicit investigations to date have provided compelling evidence to suggest the
potential usefulness for this method in the treatment of individuals with aphasia. Howard
42
et al. (1985a, 1985b) demonstrated that naming improvements were greatest and persisted
longest when patients with semantic deficits were given semantic-based therapy tasks
that did not require explicit naming. Training requiring pointing responses was more
effective and the effects of training persisted longer than the effects of more traditional
speech rehabilitation methods, such as confrontation naming, phonemic cueing, or
repetition. Baynes, Share, et al. (1995) designed a study modeled on the semantic
decision-making approach used by Howard et al. (1985a). During treatment, patients saw
the training pictures embedded in a set of three distractor pictures on a computer screen.
A verbal question required categorical, featural, or associative knowledge for a correct
response. Pointing responses were requested and naming of the items was discouraged.
Results strongly supported the efficacy of implicit training, both for trained items and in
generalization to untrained items as demonstrated by improved naming on the Boston
Naming Test (BNT). The authors found these results especially encouraging due to the
fact that the training was not intensive; sessions were relatively brief and were only
provided two days per week (Baynes, Share, et al., 1995)
The impetus for the development of current implicit methods also grew out of the
observation made by Baynes, Wessinger, Fendrich, and Gazzaniga (1993), that the
previously mute right hemisphere of a callosotomy patient gained the ability to produce
verbal responses to words and pictures after several months of steady participation in
experiments based on semantic decisions and semantic priming. This raised the question
of whether activation of semantic networks in the right hemisphere might provide a basis
for speech production, at least at the single word level. Dukette, Baynes, Redfern, Share,
43
Ludy, and Dronkers (1998) designed a study to test this hypothesis. The researchers
tested eight patients who had suffered left CVAs at least one year prior to intervention
using a confrontation naming task, and grouped them according to their predominant
error type (semantic or phonological). All patients received three weeks of implicit
semantic training, three weeks of implicit phonological training, and three weeks of no
training. Phonological training had the largest effect on participants whose errors were
primarily phonological in nature; semantic training was effective for both groups. Most
encouraging, the results generalized to improved scores on the BNT, which was “a
striking result given the modest length of time spent in each training method . . . and the
fact that there was no explicit naming practice” (Davis & Baynes, 2009).
In the implicit phonological treatment investigation conducted by Davis, Farias,
Bord, and Baynes (2006), the participant, a mildly anomic aphasic with apraxia as his
primary complaint and speech disturbance, performed several types of covert (responsefree) phoneme manipulation tasks including rhyming, alliteration, insertion, and deletion
tasks. During training sessions, he was instructed to make choices based solely on the
mental manipulation of sounds, with no accompanying verbal output. Training resulted in
improved overt speech production and significant generalization to non-treatment words.
Although the authors concluded that questions remained regarding whether different
tasks exerted differential effects on treatment, they noted that all of the tasks encouraged
semantic access (in addition to lexical, phonological, and motor planning) and required
inhibition of closely related competitors as well as activation of the target, which may
have played a role in the success of the intervention (Davis, Farias, & Baynes, 2009).
44
Baynes, Shenaut, Ober, Davis, D’Angelo, and Teague (2010), noting that “the
intensive practice and decreased opportunity for error” provided by production-free
semantic training “may provide improved word retrieval equivalent to that of
conventional methods,” compared the results of a hierarchical cueing intervention
requiring overt speech with results of a nonverbal intervention using REST (Reduced
Error Semantic Therapy). The REST intervention required the participant to touch the
correct picture in response to a categorical or associative level question about a target
natural or manmade item, without verbally producing the name of the item. The order of
presentation of the two types of questions (categorical vs. associative) was random in the
REST intervention, but was hierarchical in the hierarchical cueing condition, with
categorical templates for each training item preceding the associative level templates
(Baynes et al., 2010). Despite the pre-treatment limitations of the participant, a
conduction aphasic with perseveration tendencies and working memory impairment, the
authors found a modest improvement in retrieval of words used in REST training, as well
as in post-intervention naming ability as measured by the BNT.
The type of semantic training employed by Dukette, Baynes, et al. (1998) was
applied intensively in an implicit, semantic-based, single subject aphasia intervention
designed by Davis, Harrington, and Baynes (2006). Stimuli were designed to use “the
structural and semantic aspects of the target object to help the patient practice selection of
the object under competition,” and consisted of four-picture displays in which each of the
three foils chosen was a close semantic competitor of the target (Davis et al., 2006). For
example, for target “binoculars,” selected foils in one four-image display included a
45
microscope, a telescope, and bifocals, all objects related to, and therefore activated by
(and in competition with) the target, due to their shared perceptual, semantic, and/or
phonological characteristics. The participant, a patient with Wernicke’s aphasia, was
asked to perform tasks requiring judgments about the categorical, associative or
perceptual characteristics of the target object by pointing to the target in each field of four
closely semantically related objects. Overt naming was discouraged. The researchers felt
that “selection under these conditions provides practice that strengthens activation, both
excitatory and inhibitory patterns, necessary to perform accurate word selection and
ultimately production” (Davis et al., 2006). According to the authors, if selection of the
target “requires activation of the target as well as inhibition of competitors, particularly
close competitors,” it was expected that this type of task would provide practice in
inhibition of competing items in much the same way that such inhibition occurs during
overt speech production. The authors hypothesized that since production of semantic
paraphasias constitutes a common error type for speakers with aphasia, and since
semantic paraphasias can reasonably be supposed to occur precisely because they are
close semantic competitors for the target, then practice with inhibition of such
competitors would be beneficial, especially if it occurred without inadvertent
simultaneous “practicing” of error productions (Davis et al., 2006). Results demonstrated
improvement on trained items, with generalization to untrained items from the same
category. The patient also demonstrated improvements in narrative speech (specifically,
increased use of nouns) consistent with his improvements in word retrieval, along with
improved communication at home per family report. Pre- and post-training fMRI
46
scanning demonstrated changes in neural activation consistent with the behavioral results
(Davis et al., 2006). The researchers concluded that their results supported the
effectiveness of intensive intervention methods that require semantic judgments rather
than explicit naming (Davis & Baynes, 2009; Davis et al., 2006).
Davis, Farias, and Baynes (2008) conducted the first study in which implicit
treatment was compared experimentally with an explicit treatment method identical in all
respects except for the requirement of verbal responses. The patient presented with nonfluent (mixed type) aphasia secondary to a stroke suffered four years earlier. His speech
was characterized by agrammatism with a mean length of utterance of two words, almost
entirely nouns and often paraphasic. Twelve sessions of implicit verb training were
conducted first, followed by twelve sessions of explicit (production-required) training.
The treatment stimuli consisted of computerized DynaVox® templates, each with a
single written question at the top concerning a trained verb, and four pictures below, one
the target and the other three foils (chosen for their categorical, associative or perceptual
similarity to the target). An auditory presentation of the question was given with a button
press, at the patient’s discretion. His task was to answer the question by touching one of
the four pictures. Templates advanced automatically, but only when the correct picture
was selected. In order to strictly adhere to the implicit treatment, and to avoid the
possible confound of the necessity of speech production during probes testing, no probes
were collected. The patient did not show significant gains in naming accuracy after the
implicit training, but increased his percentage of correct responses after the explicit
training. However, error analysis showed that implicit training had the effect of
47
decreasing the number of “no response” errors and increasing the number of
semantically-related or “smart” errors. The researchers felt that this pattern suggested that
implicit treatment may have helped the participant to overcome a reluctance to respond,
which in turn may have contributed to his excellent response to the second (explicit)
phase of treatment (Davis, Farias, et al., 2008). The authors concluded that although it
was clear that implicit training “did change the nature of the patient’s responses,” further
research was necessary to determine “if patient variables, lack of probe stimuli, or word
class of the targets” might have lessened the apparent effectiveness of the implicit
intervention (Davis, Farias, et al., 2008).
In an attempt to answer some of the questions posed by Davis, Farias, and Baynes
(2008), Davis, Baynes, and Hess (2009) compared the results of an intensive, semantic
decision based, implicit verb training with those of a method identical in all respects
except for the requirement of speech production in a patient with non-fluent (Broca’s
type) aphasia secondary to a pedestrian-versus-automobile accident. Just as in the
previous study, stimuli consisted largely of templates featuring icons selected from the
available images in a DynaVox® program. This time, however, despite the potential
confound of explicit naming during probe testing, probes were conducted every other
session during both explicit and implicit phases of training to assess the participant’s
response to training. In addition, stimuli were more individualized and more challenging,
in that not only were the foils varied in semantic distance to the targets, but the
participant’s error productions in her attempts to name the targets during pre-testing were
incorporated into the templates as foils for those targets. For example, because
48
“combing” was the participant’s frequent error substitution for the target brushing, a
picture of a comb or of the action of combing hair was incorporated as a foil into all
templates used to train the verb brushing. The authors hypothesized that this practice
required increased activation of the target, as well as inhibition of its competitors. The
authors found that the implicit intervention resulted in more rapid acquisition of trained
verbs than that which occurred during the explicit (production required) training.
However, due to the fact that the explicit training had been conducted first, they could not
be certain as to whether implicit results reflected the cumulative effects of previous
training. Therefore, the determination was made to embark upon the present study, using
the same type of interventions with a cross-over design to address order effects.
The present study
Purpose, research questions, and hypotheses
The purpose of the present study was to compare the results of two interventions,
identical in all respects except for the requirement of speech production during training,
in a patient with fluent aphasia. Both interventions were intensive, semantic decisionbased, and highly individualized to match the needs and interests of the participant. The
intent was to determine what effects each type of training would have on the participant’s
word retrieval abilities, and whether the order of treatments would be seen to have an
effect on treatment results. In terms of potential benefit to the participant, a 24-year-old
anomic aphasic with profound word retrieval deficits whose progress appeared to have
plateaued prior to this intervention, the aim of intervention was to potentially facilitate
naming of a larger scope of verbs through intensive, highly challenging semantic training
49
of a smaller set of verbs. Verbs, rather than nouns, were chosen as treatment targets due
to the potential for verb training to increase spread of activation (Damasio & Tranel,
1993; Perani et al., 1999; Tyler, Bright, Fletcher, & Stamatakis, 2004), lead to greater
improvements in word retrieval and sentence production (Raymer & Kohen, 2006), and
result in greater generalization to spontaneous speech (Conroy, Sage, & Lambon Ralph,
2006). All lists of trained and untrained verbs in each phase were matched for frequency
and baseline performance. Computer-based stimuli were used exclusively in all training
sessions, in keeping with findings from previous studies suggesting the potential benefits
of computerized interventions to client motivation and engagement (Petheram, 2004;
Raymer, Kohen, et al., 2006; Wertz, 2000). In the implicit condition, the participant
responded by pointing to the correct picture or pictures in a field of four images on a
computerized template in response to a semantic question about the categorical,
associative or perceptual qualities of the target verb. Verbal responses were discouraged,
and templates moved forward only when the correct target was chosen. The explicit
condition was identical, except that the participant was required to verbally produce the
target verb before advancing to the next question. Training templates, which incorporated
multiple-target questions, multiple-verb questions, and embedded negatives, were
sufficiently challenging to require intense focus. Templates were also individualized so
that the foils frequently comprised substitutions produced by the participant in attempts to
name the action, thereby requiring increased inhibition of competitors as well as
activation of the target.
50
The current research study posed four questions: 1.) To what degree would
implicit and explicit training improve production of targeted verbs as measured by
accuracy of probe verb production? 2.) Would these training effects generalize to
untrained verbs in either condition, or in both conditions, as measured by production
accuracy of non-targeted verbs? 3.) How would the effects of these training methods
compare upon visual inspection and as measured by d statistic (Beeson & Robey, 2006)
size effects? 4.) Would order effects be observed?
Prior to the start of this experiment, the researchers hypothesized that both
production-free and production-required training would improve naming of trained verbs,
but asked the question whether such improvements would be essentially equal or would
significantly differ due to the differing (speech production) response requirements in each
condition. We also sought to determine whether the effects of training would generalize
to untrained items, whether a measure of effect size (Beeson & Robey, 2006) would
supplement observations from visual inspection of results, and whether order effects
would be observed.
Design
A single subject, multiple baseline intervention with a crossover design (ABCA /
ACBA) to address order effects was used in the current study (see Figure 2 for an
illustration of the design). The participant’s speech and language were assessed prior to
intervention using standardized measures including the Western Aphasia Battery (WAB)
(Kertesz, 1982), the Pyramids and Palm Trees Test (P&PTT) (Howard and Patterson,
1992), and the BNT. Baseline naming performance on a large set of verbs was
51
established over a period of baseline testing prior to the start of Phase One of the
intervention. Baseline performance was used to help select and match verbs for trained
and untrained lists. A period of implicit treatment (B) was then initiated, with treatment
probes every other session to monitor progress for trained and untrained stimuli. After a
three-week break to help ensure lack of carryover from the previous treatment, a period
of explicit treatment (C) was initiated, with treatment probes administered every other
session. Following Phase One and prior to the start of Phase Two, generalization to verbs
on the set of 96 verbs was assessed. Generalization to a larger corpus of 125 additional
untrained verbs was also assessed, to monitor improvement in untrained items and to help
determine new treatment targets. The participant was also re-tested on the WAB and
BNT to monitor any generalization to naming of nouns and spontaneous speech that may
have occurred during Phase One. A three-week break between Phase One and Phase Two
was observed, and new treatment targets, matched for frequency and for accuracy of
production during baseline testing, were selected. At the start of Phase Two, baseline
performance (A) was again established over a period of baseline testing. A new period of
explicit treatment (C) was initiated, followed by a three-week break, and then the
initiation of a new period of implicit treatment (B). During both periods of treatment in
Phase Two, treatment probes were administered following the same every-other-session
schedule as in Phase One. Following cessation of treatment, maintenance (A) of verb
naming for trained and untrained stimuli was tested. Maintenance testing (an essential
component in studies of treatment efficacy) was conducted again at one month, three
months, and eight months post-training, to measure the sustainability of treatment gains
52
over time. Post-testing on the WAB, BNT, P&PTT, and both larger sets of verbs was
conducted following Phase Two.
To summarize, all four periods of training were identical except for the
independent variable of speech production, which was discouraged during the two
implicit training (B) periods, and was required during the two explicit training (C)
periods. Similarly, each phase of treatment was identical except for the order of the two
treatments. It is anticipated that the findings of this study will inform future research on
the potential use of implicit therapy as a potentially valuable adjunct to traditional
speech-language therapy for individuals with aphasia.
53
Figure 2. Illustration of treatment study design
PHASE ONE
BASELINE
MIDTESTING
Implicit Tx
Explicit Tx
(3 wks later)
WAB
List 1A
Training
List 2B
Training
PPT
BNT
Three
baselines of 96
Verbs
WAB
PHASE TWO
MAINTENANCE
Explicit Tx Implicit Tx
(3 wks later)
List 3A
Training
List 4B
Training
BNT
Lists 1A, 2B*,
and Phase One
Untrained*
probed every
other session
Lists 1A*, 2B,
and Phase One
Untrained
probed every
other session
(*Probes =
continued
baseline
testing)
(*Probes =
maintenance
testing)
WAB
PPT
Post-treatment
testing of 96
Verbs
Maintenance
testing of Lists
1A and 2B
Three Baselines
on 125 verbs
Lists 3A,
4B*, and
Phase Two
Untrained
probed every
other session
Lists 3A*, 4B,
and Phase Two
Untrained
probed every
other session
(*Probes =
continued
baseline
testing)
(*Probes =
maintenance
testing)
Baselines on
lists 3A, 4B,
and Phase Two
Untrained verbs
established
Maintenance
testing of all
trained and
untrained lists:
BNT
1 month posttreatment
Maintenance
testing: all
trained and
untrained
verbs
3 months posttreatment
8 months posttreatment
Posttreatment
testing of 96
Verbs
Posttreatment
testing of
125 verbs
TIME
53
54
Chapter 2
METHODS
Participant
At the time of his recruitment to participate in this study, I.T. was a 24-year-old,
right-handed, native English-speaking male who presented with fluent aphasia secondary
to a traumatic brain injury from a gunshot wound sustained eight months earlier, in
November, 2008. Hospital records indicate that the damage was mostly to his left
temporal lobe, specifically to the inferior, superior, and middle temporal gyri (see Figure
3). Although no bullet fragments had directly entered the brain, they had penetrated bone
and caused severe swelling and a 5 mm left-to-right midline shift.
Figure 3. Participant’s MRI and CT scans showing area and extent of lesion.
Left and center MRI scans were obtained through the cranial vault with axial T2weighted images six weeks post-injury. Lesion included region of encephalomalacia
involving the superior, middle, and inferior temporal gyri on the left. Extensive
abnormalities also included residuals of left frontoparietal craniotomy and ex vacuo
enlargement of anterior tip of the temporal horn. Right image is chronic comparison CT
scan taken two years post-injury. The area of encephalomalacia involving the left
temporal lobe was unchanged from previous images. For all images, note that the left side
of the picture shows the right side of the brain, and vice versa.
Prior to his injury, I.T. had attained a high school education and had been enrolled
in community college for several semesters. He was also employed as a telemarketer, a
55
job which required excellent verbal communication skills and at which he excelled per
self-report. He had no reported pre-morbid history of psychiatric, neurological,
cognitive, or speech-language deficits. His medical history was significant for diabetes
diagnosed at age 16.
In the year following his injury, I.T. underwent numerous surgeries including
craniotomy, left ear canal reconstruction (including canaloplasty and tympanoplasty),
medial and lateral facial nerve decompression, and mandibular and lower facial
reconstruction. He had residual left facial paralysis but had developed good
compensatory strategies resulting in clear articulation. He demonstrated no verbal or nonverbal oral apraxia and no articulatory weakness. Pure tone audiometric testing
performed six months post-injury showed that he had normal pure tone thresholds in the
right ear and a profound mixed hearing loss in the left ear with a 30 to 40 dB air-bone
gap. A hearing aid for the left ear had been recommended but was not yet being worn at
the time of this intervention. Due to this hearing issue, the clinician sat on I.T.’s right
side during all training, probe and testing sessions. I.T.’s vision was within normal limits
with corrective lenses, which he consistently wore. He had no identified spatial neglect or
visual field deficits.
I.T. received standard speech and language therapy consistently from the time of
his hospitalization until his recruitment for this study. At the time he was recruited and
consented to participate in this study, he was receiving services twice weekly for one
hour per session as a speech therapy outpatient at the U.C. Davis Medical Center
Department of Physical Medicine and Rehabilitation.
56
Although he tested as an anomic aphasic according to the WAB, and presented
with spontaneous speech consistent with that aphasia profile, I.T. exhibited some verbal
behaviors similar to those often demonstrated by patients with Wernicke’s aphasia: he
demonstrated frequent topic shifts, tended to become distracted and tangential while
telling a story, and occasionally related a narrative without realizing he had left out a
crucial or salient detail necessary for listener comprehension. In conversation, he
demonstrated frequent instances of word-finding difficulty (for nouns and verbs
approximately equally), although he was fairly skilled at using alternative modalities
(circumlocution, gestures, etc.) to effectively communicate his message. His speech,
which was typically grammatically correct, was characterized by frequent hesitations and
attempted self-corrections, whole-word phonemic and semantic paraphasias, occasional
neologisms, and revisions and explicit expressions of frustration typical of an individual
with significant word retrieval difficulties (“I know that word, it’s….wait, no, it’s not
that, it’s…oh, what is the word for that, when you’re going, no, not going but when
you’re doing the thing where you go like this?”).
Procedure
U.C. Davis Medical Center Institutional Review Board approval was obtained
prior to I.T.’s recruitment. I.T. signed informed consent prior to participation, and his
parents also gave their informed consent prior to the start of the intervention.
Language testing pre- and post-intervention.
The participant’s language and word retrieval skills were assessed prior to
intervention using standardized measures including the Western Aphasia Battery (WAB)
57
(Kertesz, 1982), the Pyramids and Palm Trees Test (P&PTT) (Howard & Patterson,
1992), and the Boston Naming Test (BNT) (Goodglass & Kaplan, 2000). Standardized
instruments were administered according to clinical protocol, and results were used to
characterize in detail the deficits that hindered I.T.’s verbal communication and to aid in
focusing the intervention. Non-standardized measures were also used, and consisted of
large verb lists with corresponding picture stimuli selected from the Picture This®
program. Pre-intervention scores were obtained two weeks prior to the intervention and
post-intervention scores were obtained three weeks after the conclusion of the six month
intervention. In addition, standardized testing and assessment of non-standardized verb
naming performance measures were conducted in between Phase One and Phase Two of
the intervention, to determine effects of treatment (see Table 2).
I.T.’s pre-intervention classification on the WAB was anomic aphasia. This
standardized test was also used to obtain an aphasia quotient (A.Q.), a composite severity
score determined by the participant’s performance on picture description, auditory
comprehension, repetition, and naming tasks. I.T.’s pre-intervention A.Q. was 72.4,
according to the WAB. He demonstrated relatively spared auditory comprehension
(auditory comprehension score of 4.0 or higher) and slightly impaired repetition
(repetition score below 7.9) per normative data on performance of participants with
aphasia (Kertesz, 1982). The proportion of nouns and the proportion of verbs used in a
connected speech task were also computed using the participant’s picnic picture
descriptions from the WAB. This was done in order to help determine the suitability of a
verb intervention for this participant, as well as to provide data for post-intervention
58
comparison. During pre-intervention testing, 9% of the total words produced by the
participant in response to the picnic picture were verbs, and 20% were nouns.
The BNT, which assesses naming responses on 60 black and white line drawings
of high- to low-frequency English words, was also administered. I.T.’s pre-intervention
score of 18 was more than five standard deviations below the norm, which equated to a
profound naming deficit. I.T.’s errors on the BNT were classified as a combination of
semantically related and unrelated verbal paraphasias, neologisms, and non-word
phonemically based paraphasias. It is also worth noting that a significant number of the
participant’s errors constituted perseverations. Out of 21 phonemic cues given after
incorrectly named items, I.T. gave nine correct responses following the cue.
The Pyramids and Palm Trees Test (P&PTT) (Howard & Patterson, 1992) was
also administered pre- and post-intervention. The P&PTT is thought to be particularly
useful for theoretically-motivated testing of picture and word comprehension in
participants with aphasia, because it makes semantic demands (determining the degree to
which a subject can access meaning from pictures and words) but without requiring
verbal expression. Information from the P&PTT enables clinicians to establish whether
the patient’s difficulty in naming or pointing to a named picture is due to a difficulty in
retrieving semantic information from pictures, a difficulty in retrieving semantic
information from words, or a naming failure due to a difficulty in retrieving the
appropriate spoken form of the word. P&PTT performance can help determine if a
patient’s naming errors are due to a breakdown at the semantic-lexical level or to postlexical phonological disorders. The picture condition of the P&PTT was administered to
59
determine if the participant was able to draw inferences about pictorial material. In the
picture version, the target picture is presented above two pictures, and the individual is
asked to indicate which picture is most closely associated to the target. The word
condition requires the individual to access semantic information by deciding which of
two written concepts (e.g., pine tree or palm tree) is most related to the target concept
(e.g., pyramid). Results from the two versions of the test were analyzed to compare the
participant’s performance on tasks that require access to the object semantic system
(three-picture version) and the lexical semantic system (three-word version). I.T.’s scores
on both the word and picture versions of the P&PTT were approximately equal (45.5 and
45, respectively) and were both within normal limits, providing evidence that his object
and lexical semantics were intact, or in other words, that the semantic system was intact
between object and meaning. This led to the conclusion that his naming failure was due
to poor representation of the word in the lexicon, and/or to poor lexical access due to
insufficient semantic activation of the target and/or insufficient inhibition of competitors.
Thus, the use of an intervention designed to increase spread of activation through
semantic-level tasks (tasks believed to cause wider spread of activation than other types
of tasks) was thought to be potentially beneficial to the participant.
In addition to standardized testing, naming performance on a large verb list was
assessed to confirm the presence of a verb retrieval deficit (operationally defined as an
accuracy score below 75% on this measure) and establish the items needed for training
sets. Responses were elicited using images from the Picture This® program. Error types
during pre- and post-tests were recorded for later analysis. All the testing and
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experimental stimuli were one- to two-syllable verbs. The present progressive form of
the verb was elicited (e.g., “What is he doing?”) for all verbs in both pre- and post-tests
and in training sets. Responses were not timed, and independently self-corrected
responses were accepted. In all, 96 verbs were tested during pre-intervention and during
the three sessions of pre-intervention baseline testing.
Development of test and treatment stimuli.
Three lists of eleven verbs each—one Trained Implicit list, one Trained Explicit
list, and one Untrained list—were created for each phase of the experiment (see
Appendix A). The lists were matched according to verb frequency (Francis & Kucera,
1982) and according to the participant’s baseline performance during assessment (using a
compilation of 96 verbs paired with images from the Picture This® program).
Imageability was also a consideration; only verbs judged to be unambiguously
representable in picture form were selected for inclusion.
For each trained list, at least 179 templates were created (with an average of 222
templates per trained list, or 20 templates per trained verb), using a Microsoft
PowerPoint® program and images selected from Google Images® readily available on
the internet. This method proved to be an immense improvement over previous implicit
training methods (e.g., creation of templates using images from the limited pool in a prepackaged DynaVox® program) in many respects. Perhaps the most important of these
was that it permitted creation of unique computer templates that were matched to the
participant’s areas of interests. The participant, a lively, curious young man with a keen
sense of humor, was especially interested in small furry animals, cute babies, food, sports
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(particularly football), slapstick humor, cartoons, popular culture, attractive young
women, and pets. Because Google Images® enables searching of any terms (i.e., any
verb, paired with any noun that was anticipated to provide a theme of interest to the
participant), there were virtually no limitations in terms of possible templates. This
method of stimuli creation also allowed for a strong element of visual appeal and balance
in the training templates; if, for instance, a blue sky with puffy white clouds was visible
in the top left image, it was possible to ensure that there was also a blue and white image
in the lower right, or that a blue sky with puffy white clouds (or just four blue and white
images) appeared in all four quadrants of the template. It was also possible to include
dynamic (moving) images, by including the words “animated” or “gif” (graphics
interchange format) in any image search. Although most images used were static (photos
or illustrations), the occasional inclusion of moving images was thought to be especially
helpful in the training of action verbs (McCann & Greig, 2010). These features of the
stimuli creation method all apparently helped ensure that the participant’s interest in and
motivation for the tasks remained high; he always appeared to enjoy the sessions greatly,
and often expressed eagerness to see what new templates had been created since his last
session.
This method of stimuli creation also allowed images to be matched according to
visual/perceptual as well as categorical and associative features, which was thought to
increase the level of challenge offered by the tasks. For example, when training the verbs
yawning, drying, digging, and balancing, four semantically unrelated verbs, four images
could be easily located and selected for their similar features (e.g., a puppy yawning, a
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puppy being dried with a towel, a puppy digging in a yard, a puppy balancing on a ball),
which were all related to one another (in this example, through the common theme of a
puppy). This ensured that the four pictures were all close competitors, whether or not the
common theme itself (e.g., puppies, hamsters, black and white line drawings, cartoon
characters, sea creatures, gorillas, panda bears, red objects, metal objects, babies, kittens,
football, attractive young women, or food) was semantically related to the target verb. In
other words, the four pictures might be semantically related to the target verb (e.g., Which
one splashes? accompanied by pictures of a starfish, an octopus, an anemone, and a
dolphin, all creatures that live in water, which is semantically related to the verb splash),
but might only be related to each other visually or featurally in some way unrelated to the
target verb (e.g., Which two are not swinging or sailing? with pictures of an owl and a
pussycat swinging on a playground, sailing in a boat, eating a meal, and playing a board
game). Another way in which the stimuli selection ensured that tasks required inhibition
of close semantic competitors for the target was that the participant’s own error
productions (e.g., mowing for harvesting) were included as foils during training as often
as possible. This was done to ensure that the task required inhibition of the very semantic
competitors which had previously resulted in verbal errors.
The stimuli creation method also allowed for the training of multiple verb
meanings using atypical exemplars (see Appendix B, Table B6), which was thought to
have benefit in terms of increasing spread of activation (Kiran, 2001, 2008; Kiran &
Thompson, 2003). For any atypical meaning or usage of the verb thought to be imageable
(e.g., pouring rain, versus simply pouring liquid into a container), searching the term
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(e.g., “pouring rain”) yielded countless image choices for inclusion in training templates.
Whenever a question arose regarding precise or allowable definitions (e.g., whether
carving could legitimately be used to refer to the action of cutting a pattern or design into
a vegetable), this was resolved through consulting the definitions offered by the Oxford
English Dictionary.
Approximately 50% of all templates included an orthographically presented
question at the top of the four-picture display. Those that did not feature a printed
question were often versatile enough to be used for more than one question, and more
than one question type. Question types were varied to allow for increased grammatical
complexity and the inclusion of plural markers, multiple verbs, and embedded negatives,
in order to offer greater challenge and require more intense focus. Embedded negatives in
particular (teaching not only the concept, but also what the concept is not) were thought
to help ensure deeper understanding of the concept.
Question types took eight basic forms (see Appendix B, Table B5): Single-target,
single-verb questions (the form used most often during the first day or two of training of
a new list, such as Which one is skating?); multiple-target, single-verb questions (Which
two are sniffing?); single-target, single-verb questions with embedded negatives (Which
one is not drying?); multiple-target, single-verb questions with embedded negatives
(Which two are not reaching?); single-target, multiple-verb questions (Which one goes
with both painting and drying?); multiple-target, multiple-verb questions (Which three
are rolling and floating?); single-target, multiple-verb questions with embedded negatives
(Which one goes with baking but not carving?); and multiple-target, multiple-verb
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questions with embedded negatives (Which two are jumping but not splashing?; Which
ones are not rocking or swinging?). Approximately the same number of questions of
each type was included in each training phase. There were minor variations among
questions of any given type according to the specific focus of the question. Questions
primarily used the present participle form of the verb (e.g., slicing), to differentiate the
word clearly as an action and avoid confusion with usage of the root form in other
grammatical categories, such as noun usage (e.g., [a] slice). An auxiliary form of the
verb was often used along with the main infinitive form (e.g., Which one can jump?) to
encourage more intense concentration than that required by relatively simple
identification tasks (e.g., Which one is jumping?). Occasionally, the past participle form
of the verb was used (e.g., Which one was baked? Which one is closed?) to encourage
focus on the verb as a past event. Sometimes the main form of the infinitive verb was
used, such as when use of future tense was needed in order to encourage consideration of
the verb in the context of consequences of a future event (e.g., Which one will splash?).
Verbs from Phase One Untrained and Phase Two Untrained lists were never
included as foils on templates during either phase of training. The Untrained list from
Phase Two did not include any verbs ever used as foils during Phase One. The Untrained
list from Phase One remained untrained during Phase Two.
Treatment protocol.
The participant received three to four sessions per week, for one to one and a half
hours per session. All training sessions were conducted in the offices of the U.C. Davis
Medical Center Department of Physical Medicine and Rehabilitation by the author, with
65
direct supervision by a licensed and ASHA-certified speech-language pathologist. During
the intervention, I.T. did not participate in any group or individual speech-language
therapy. Probe sessions were administered at the start of every other session. The criteria
for cessation of training during any phase of the experiment were when the participant
met one of two conditions: 1.) demonstrated accuracy of 90% (correct naming of 10 out
of 11 verbs) on three consecutive treatment probes, or 2) reached the end of 12 training
sessions for that particular training set.
During every treatment session, including probe sessions, I.T. was presented with
the training templates for the verb list then being trained. Templates were presented on a
laptop computer with a 17 ½ inch screen placed at a distance comfortable to the
participant. For each template, I.T. was asked at least one question requiring him to make
a semantic decision regarding the target verb. Question types on the templates varied (see
Appendix C for examples) and were generally evenly distributed in each training set as
previously described, with the exception that the first one or two training sessions with
each new set featured more questions of the simpler types (e.g., single-target, single-verb
questions) and fewer of the more grammatically complex question types (e.g., multipletarget, multiple-verb questions with embedded negatives). During implicit training, I.T.
either read the question silently or listened as the clinician presented the question
verbally. After considering the question and visually inspecting the four options, he
responded nonverbally, selecting an image by touching it with a rubber-tipped pointing
stick. All tasks were untimed; the participant was permitted to take as much time as he
needed or wanted to make his decision.
66
Sometimes, undoubtedly because I.T. enjoyed talking and because he was
accustomed to “thinking out loud,” he attempted to repeat the question verbally while
deliberating and considering the available choices. Because this tendency in effect
equated to practicing explicit production of the target verb, it was discouraged with a
nonverbal signal (finger held to clinician’s lips) or an explicit verbal reminder
(“Remember, try to do this without talking”) whenever it occurred. I.T.’s accuracy and
errors were tallied during each session, partly to ensure that tasks were not too difficult
and that his accuracy was maintained at greater than 90% on total semantic decisions per
session, and partly to ensure that any errors could be incorporated as foils in the creation
of future templates. Whenever I.T. selected an incorrect target in response to a question,
the question was repeated verbally and/or key features of the printed question (plural s, or
key words such as not, best or most often) were pointed out. Whenever the correct target
or targets had been selected, the clinician or the participant pressed a computer key to
advance to the next template.
The treatment was intensive in that it required intense concentration on the part of
the participant, who reported that he often found himself thinking about the verbs
throughout the day, even on days when he did not have a treatment session. I.T.
approached each session with apparent eagerness, and referred to the training sessions as
a “fun learning game.” At no time did he appear discouraged or overwhelmed, and on
those few occasions when he demonstrated fatigue and began making more errors instead
of fewer errors as a training session progressed, he was encouraged to take a short break,
67
drink some water, and chat about his current activities for a few minutes before returning
to the training set.
During the explicit condition, the same treatment protocol was followed, except
that I.T. was asked to verbally produce each target verb before advancing to the next
template. If he did not remember this step on his own, he was reminded by the clinician.
For example, if the question at the top of the template asked “Which two are jumping?”
and I.T. merely pointed to the images illustrating the concept of jumping before
attempting to advance to the next template, the clinician pointed to each target and said,
“So, s/he is doing what?” to prompt him to verbally produce the target verb. On those
rare occasions when I.T. did not remember the target verb when asked to produce it, he
was given a phonemic cue. If this did not result in a correct production, the full form of
the target was modeled and he was asked to repeat it before advancing to the next target.
No incorrect productions were accepted; advancement to the next template was always
contingent upon a correct production (one per target) from the participant. If there were
three targets on a template, I.T. was required to say the target word three times correctly,
pointing to each target image in turn (e.g., “jumping, jumping, jumping”), before
advancing to the next template.
During both conditions, images were switched to different positions or replaced
with new images, questions were altered, and/or new templates were added before each
training session, so that no two training sessions ever featured exactly the same series of
templates, and often two back-to-back training sessions featured entirely unique
templates with minimal or no overlap of previously viewed stimuli. This was made
68
possible by creating such a large number of templates (between 179 and 261 templates
per training set) that the same exact series never had to be viewed twice. The decision to
create sufficient templates to ensure a unique presentation during each training session
was made in response to an incident that occurred on the second day of training, when it
became clear that the participant had memorized, after only one exposure, the positions
of at least some of the target images on the templates. When I.T. was observed to point to
the upper right corner of the screen in anticipation of the advancement of the current
template (preparing to point to the correct target on a template not yet visible to him, to
correctly answer a question he had not yet been asked), the determination was made that
template images had to be altered, questions changed, and/or new templates added prior
to each day’s training.
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Chapter 3
RESULTS
Comparison of Implicit and Explicit Training Methods
Clear response to both production-free and conventional interventions was
verified by medium to large size effects in both phases of training (see Figures 4 and 5).
Training effects in both phases were maintained three months after cessation of training.
Eight months after the end of Phase Two of the intervention, training effects for verbs
trained explicitly in both phases were maintained, although training effects for both sets
of verbs trained implicitly had declined somewhat.
Order effects were observed. The first training method in each phase had a larger
size effect. In Phase One, a larger size effect was observed for the implicit (d = 9.9) than
for the explicit condition (d = 6.9). In Phase Two, a larger size effect was observed for
the explicit (d= 18.1) compared to the implicit condition (d= 8.7). No significant
generalization to untrained verbs occurred in either condition in either phase of training.
Visual inspection of Phase One indicated that both types of training were effective
(see Figure 4). However, visual inspection of Phase One revealed greater generalization
to untrained items during implicit training than during explicit training.
Visual inspection of Phase Two revealed a steeper learning curve, along with
solid retention of training effects, for verbs trained explicitly (see Figure 5). In Phase
Two, clear effects of training, and good maintenance of improvements, were observed for
verbs trained implicitly. In Phase Two, very little generalization of either list into
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untrained items was observed upon visual inspection; there was some generalization
during implicit training, and none during explicit training.
There appeared to be tight experimental control with explicit training; in other
words, explicit training only affected the items that were trained. There was some
generalization to untrained items during implicit training in both phases, although the
increases in accuracy for untrained items were not significant.
Explicit training was observed to yield greater, more consistent retention of
trained items in both phases.
Maintenance
Baseline
Implicit Tx
< 3 mo
Explicit Tx
3 mo
6 mo
>8 mo
Number of accurate probe responses
12
10
8
6
4
2
0
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
Probe Sessions
List 1A Trained Implicit
List 2B Trained Explicit
Untrained/Never Trained
Figure 4. Phase One: Comparison of implicit and explicit training effects.
71
Baseline
Explicit Tx
Maintenance
<3 mo
3 mo
Implicit Tx
8 mo
Number of accurate responses
12
10
8
6
4
2
0
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
Probe Sessions
List 3A Trained Explicit
List 4B Trained Implicit
Untrained
Figure 5. Phase Two: Comparison of explicit and implicit training effects.
72
73
Error Patterns
Error analysis was performed on the original 96-verb list used to establish
baseline performance. The 96-verb list was tested three additional times during the
intervention (pre-, mid-, and post-intervention). Treatment generalization on the list was
observed with results as shown in Table 2. Error analysis was performed (see Table 1) to
determine an increase in correct responses and a shift in error response types. Along with
the expected increase in the number of correct responses, there was a clear decrease in the
number of non-semantically-related responses, as well as in the number of neologisms
and no response/“I don’t know” responses (see Figure 6).
Table 1. Classification of responses according to error type (expressed as a percentage of
total responses).
NonNo
Correct Semantically- semantically- Neologisms response
related
related
(IDK)
61
13
19
3
4
Baseline
72
15
11
1
1
Post-Phase
One
90
9
1
0
0
Post-Phase
Two
74
100
90
80
70
Correct
60
Semantically-related
50
Non-semantically-related
40
Neologisms
30
No response
20
10
0
Baseline
Post-Phase One
Post-Phase Two
Figure 6. Percentage of responses in each phase of assessment classified by type.
Change in Standardized and Non-Standardized Language Measures
Training resulted in improvements on the Western Aphasia Battery, with
increased scores in spontaneous speech, including information content, fluency and
grammatical competence, along with improved object naming (see Table 2). The
participant’s A.Q. as measured by the WAB increased from 72.4 to 90.9. The proportion
of verbs in spontaneous speech increased from 9% to 13% of total words produced, while
the proportion of nouns as a percentage of total words remained approximately the same.
Auditory comprehension scores on the WAB increased from 8.5 to 9.9. Scores on the
BNT increased slightly, from 18 to 22. Although this score remained over five standard
deviations below the norm, the participant’s errors consisted solely of semantically
related verbal paraphasias (sweeper/broom; chair/bench), with no perseveration or
neologisms, in contrast to his pre-intervention error profile. Scores on the P&PTT
75
remained essentially unchanged. Improvements were noted on naming of the larger set of
96 verbs (binomial p < 0.04, z = 5.0).
Anecdotally, it is worth noting that I.T.’s regular conversational partners reported
that he appeared to be expressing himself verbally with more precise word choice postintervention, and that I.T. reported subjective improvements in his word retrieval abilities
in conversation.
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Table 2. Participant’s pre-and post-treatment scores
Pre-Intervention
Post- Phase One
Western Aphasia
Battery
Spontaneous Speech:
Information Content*
8
9
Fluency &
Grammatical
6
8
Competence*
Verbs**/total words
produced in picture
6/66 (9%)
10/103 (10%)
description
Nouns/total words in
13/66 (20%)
18/103 (17%)
picture description
Post-Phase Two
10
10
16/125 (13%)
21/125 (17%)
Auditory Verbal
Comprehension*
8.5
8.9
9.9
Naming & Word
Finding*
5.9
6.9
7.4
Aphasia Quotient
72.4
82.4
90.9
Boston Naming Test
18
20
22
Pyramids and Palm
Trees Test
Pictures
Written Words
45
45.5
N/T
N/T
48
44
96 Verbs
67 (70%)
70 (73%)
86 (90%)
50 (40%)
79 (63%)
N/T
125 Verbs
*WAB subtest scores out of a possible 10 points
**Excluding auxiliary verb forms of be and have
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Chapter 4
DISCUSSION
Major Findings and Implications
The purpose of the present study was to compare the results of two interventions,
identical in all respects except for the requirement of speech production during training.
The intent was to determine what effects each type of training would have on the
participant’s word retrieval abilities, as well as whether the order of treatments would be
seen to have an effect on treatment results. The first finding was that both implicit and
explicit training methods were effective in training of verbs. This finding supports the use
of implicit therapy as a potentially valuable adjunct to traditional therapy in the treatment
of fluent aphasia. The fact that both methods were efficacious, and that post-intervention
improvements were noted in the participant’s spontaneous speech, also suggests that
intensive, semantic decision-based verb interventions can have direct effects on
spontaneous speech and fluency.
One factor unrelated to the presence or absence of verbal production requirements
may have helped increase the effectiveness of training overall for this participant.
Training effects in both conditions may have been maximized by the fact that training
tasks were made as enjoyable as possible for I.T., partly through incorporation of images
specifically chosen to match his interests and appeal to his sense of humor, which in turn
resulted in a great deal of laughter and positive emotion during each session. Humor has
been found to enhance the learning process (Dormann & Biddle, 2006; Potter &
Goodman, 1983) and has been referred to as an important (though often overlooked)
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therapy tool (Simmons-Mackie & Schultz, 2003). The fact that the stimuli were
specifically chosen to engage the client by employing images reflecting his interests
undoubtedly enhanced his learning of the target verbs. The use of stimuli with a high
degree of emotional salience can serve as a potent aid to later recall of the stimuli (Janata,
2009), and tasks for which a participant expresses enthusiasm have been shown to be
most beneficial in naming interventions (Nickels & Best, 1996).
In addition to the overall efficacy of the intervention, a second finding was that
order effects were observed; the first training method in each phase had a larger size
effect, regardless of whether or not it required speech production. This finding helps
answer questions raised by previous research (Davis, Baynes, & Hess, 2009) regarding
whether apparent gains from implicit therapy may have been due to the cumulative
effects of previous training. It would appear that, for this participant at least, the effects of
implicit therapy were not due to the cumulative effects of previous training.
Another finding was that no significant generalization to untrained verbs occurred
in either condition. As has been often noted, generalization beyond the trained items,
though very limited in most studies of verb training (Raymer & Ellsworth, 2002), is
crucial for improving the participant’s communication in daily life, not just in the
restricted environment of therapy (Basso & Caporali, 2001; Davis, Harrington, &
Baynes, 2006). However, although treatments that generalize are preferable to those with
effects limited to a small set of items, “item-specific effects can be worthwhile,
particularly when they are on items that are functionally useful and when the effects
maintain” (Nickels & Best, 1996). Also, the intervention was shown to have effects
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beyond generalization to specific verbs, in that it improved the participant’s spontaneous
speech and fluency as demonstrated by pre- and post-intervention standardized test scores
(particularly an increase in A.Q. on the WAB) and narrative speech samples, and per
patient report.
Although there was little generalization to untrained items overall, visual
inspection revealed more generalization to untrained items during the implicit
interventions regardless of order effects. This could be due to resource allocation; it may
be that language resources used for retrieval of the word for articulation during explicit
production were used in the implicit intervention (when the participant did not need to
focus on explicit articulation) to mentally process aspects of the action, and the resulting
increased spread of activation resulted in generalization to other untrained verbs.
Another finding was that although both implicit and explicit training yielded
medium to large size effects, explicit training yielded greater, more consistent retention
of trained items. The first possibility to consider is that for some participants at least,
some degree of verbal production practice may be necessary to achieving the greatest
possible maintenance of treatment gains. Although Nickels and Best (1996) argued that if
output of the item were a key part of therapy, then only those items which had been
produced would improve and there would be no generalization untrained items, other
authors have differed on this point. As some authors have noted, it is possible that
production-free therapy may be appropriate for some individuals, but not for others,
depending on the nature of the deficit (Nickels & Best, 1996).
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A second possibility is that feedback regarding production, rather than production
practice itself, is an important component for some patients. Although significant
improvements in naming have resulted from repeated presentation of stimuli even when
no feedback or error correction was provided (Howard, 1985a, 1985b; Nickels, 2002;
Nickels & Best, 1996; Pring, White-Thompson, Pounds, Marshall, & Davis, 1990), it
may be that “although overt naming seems unlikely to be essential, internal activation of
the phonological (or orthographic) representation could be necessary to produce the
effect” (Nickels & Best, 1996). Perhaps this internal activation is not fully achieved
without at least occasional feedback regarding correct articulation of the target. This
could help explain why explicit training yielded more consistent retention than implicit
training. I.T. demonstrated numerous mispronunciations and error productions during
explicit training (e.g., “suing”/sewing), receiving feedback and eventually correctly
producing the target after each mispronunciation. It is reasonable to assume that he would
have made just as many production errors with verbs trained implicitly, if he had been
given the opportunity to produce the word and receive feedback regarding his
productions, and that this feedback might have been beneficial.
Another possibility to consider is that although the verb lists appeared to be
balanced, they may have actually differed in some way in terms of difficulty. It was noted
that one reason for the relatively poor maintenance of the implicitly trained verb list in
Phase Two (List 4B) may have been the fact that I.T. did not achieve mastery of those
verbs during training. Because he never achieved 90% criteria on that list, his learning of
81
those verbs never had the advantage of consolidation during training, an advantage seen
during the other implicit training and both explicit trainings.
This raises the question of why the participant demonstrated such relative
difficulty with learning the verbs in List 4B. One possibility that needs to be considered is
that although the verb lists were thought to be evenly matched due to having been
matched for frequency and for baseline performance, they may have varied in difficulty
due to factors that were not taken into account. Recent evidence suggests that matching
training sets of verbs according to frequency and baseline performance may be
inadequate, and that other criteria may need to be considered (Graham, 2009). Semantic
weight (Barde, Schwartz, & Boronat, 2006), semantic verb category (Kemmerer, Castillo,
Talavage, Patterson, & Wiley, 2008), semantic relatedness (Cornelissen et al., 2003), and
overlap of semantic features between training verbs (Graham, 2009; Faroqi-Shah, Wood,
& Gassert, 2010) are all factors shown to potentially affect the naming performance of
anomic patients.
In particular, for List 4B, there may have been issues related to semantic weight
and/or overlapping semantic features. During List 4B training, I.T. was observed
frequently attempting to use his body to simulate and differentiate the actions of rocking,
swinging, reaching and crouching as he heard or read each target verb. The distinctions
between these verbs often appeared to confuse him, particularly the differences between
rocking and swinging. The fact that there was significant semantic feature overlap for
List 4B, with seven of the 11 verbs (reaching, rocking, crouching, rolling, leaping,
swinging, and floating) potentially involving full-body actions, may have resulted, in
82
effect, in that list presenting a higher level of difficulty, especially in light of the fact that
only two to three verbs in any other list involved full-body actions. It has been
demonstrated that body part features are activated by verbs and by pictures of actions,
and that listeners mentally simulate actions denoted by verbs, even when the verbs are
presented as decontextualized single words (Faroqi-Shah, Wood, & Gassert, 2010). This
results in an increase in the difficulty of verb retrieval tasks when two verbs with
overlapping semantic features (especially somatotopically congruent verbs, or verbs with
overlapping body part features) are presented together (Faroqi-Shah, Gassert, & Wood,
2009). Future implicit therapy investigations should incorporate consideration of
semantic weight and semantic feature overlap during the selection of training items, to
ensure that training sets present an equal level of difficulty in each condition.
Limitations of the Present Study and Directions for Future Research
There were several confounds in the present study. One was the need for overt
production during probe sessions, as has been noted by previous researchers using
implicit training methods. Also, simple exposure to the pictures shown to the participant
during probes testing could have had an effect. Another potential confound was the
necessary inclusion of non-target, unrelated verbs--any untrained verbs at all, even if they
appeared nowhere in the 96 verbs or 125 verb assessments administered during pre-and
post-testing—as foils on training templates, because one of the research questions we
asked was whether there would be generalization to untrained items, and if either the
participant or the clinician ever produced these extraneous verbs, we were in effect
partially training them.
83
An additional confound was the fact that although speech production during the
implicit condition was discouraged, it was neither absolutely prohibited nor entirely
prevented. I. T. often attempted/began to read the orthographically-presented questions
aloud, and/or to verbally repeat the verbally-presented questions (containing the target
word) , and/or to verbally repeat, if only subvocally/sotto voce, the target word prior to
making a decision and pointing to one of the four pictures. This may be a common
occurrence for individuals with effortless (fluent) speech who enjoy talking and are
enthusiastic about the task, even when they are instructed (and even frequently reminded,
as I.T. was) to complete a task silently. Nickels and Best (1996) observed that, in the
absence of explicit instructions regarding production, one participant “always attempted
to read the words aloud (not always successfully) prior to matching the picture(s).”
As has been previously mentioned, lists were matched only according to
frequency and baseline performance, which, although standard practice in verb naming
studies, may be insufficient to prevent differences in difficulty level between lists of
training items. Future research may need to control for semantic distance and degree of
overlap of semantic features in trained and untrained verbs. This should be done not
because tasks with a high degree of overlap between training items are too difficult—
effortful tasks have been shown to be beneficial, as demonstrated by Frattali and Kang
(2004)—but because lists of training items should be matched as precisely as possible in
terms of task difficulty to prevent unintended variables.
Another factor that could be taken into account in future studies is the degree to
which trained verbs are meaningful to the participant. The present study could potentially
84
have incorporated the participant’s specific needs and interests as selection criteria not
only for picture stimuli but also for the trained verbs themselves. The training verb
selection criteria employed in the present study resulted in the inclusion of numerous
verbs related to food preparation and cooking (harvesting, peeling, slicing, grating,
stirring, baking, roasting, and grilling), activities the participant admitted that he rarely or
never engaged in, and which he (perhaps as a consequence) demonstrated relative
difficulty with learning and differentiating during training sessions. It has been observed
that in treating naming, it is important to select words that are both client specific and
functional (Nickels & Best, 1996; Roseberry-McKibbin & Hegde, 2006).
Future research may also need to control more carefully for factors related to the
semantic questions asked in each training set. Counting and matching the number of
question types used for training each list, to ensure that no one list contains more
challenging questions overall than another list, could help eliminate the possibility of
unintended variables related to training set difficulty. Related to this issue, the present
study could have eliminated questions potentially requiring increased word retrieval
which were used in explicit training but not in implicit training (e.g., What is each one
doing?). Although the difference between this type of training question and other types of
questions used was thought to be inconsequential, it is possible that providing no
information about the word form made this type of question more difficult for the
participant, and therefore, could have influenced the results to some degree. Future
researchers may also wish to manipulate such factors deliberately, to help determine the
85
precise effects of grammatical complexity of the question (e.g., Which one is sneezing,
versus Which ones are not sneezing) on retrieval of verbs.
Another way in which training sets could perhaps be more carefully balanced
would be to count and match the number of dynamic and static images used for each
training corpus, to ensure that no training set contains more dynamic images than another
training set. Dynamic images may provide increased benefit over static images when
training action verbs (McCann & Greig, 2010). The present study could also have
potentially ensured closer matching of the lists according to how many verbs per list had
multiple meanings and atypical exemplars being trained. For example, although
numerous multiple meanings and atypical exemplars were used to train the verbs popping
and rolling, many verbs had fewer meanings or exemplars trained, and for some verbs
(e.g., sneezing, yawning, hopping), there was only one imageable meaning.
The present study could also have employed a hierarchy, as did Baynes, Shenaut,
Ober, Davis, D’Angelo, and Teague (2010), in presentation of templates, rather than
presenting them essentially in random order. In the comprehensive group study planned
by Davis and Baynes (2009) to rigorously investigate the behavioral and neural treatment
effects of semantic and phonological training on a heterogeneous group of aphasia
patients, the authors designed a set of computerized semantic tasks with two to three
difficulty levels for each task type, with difficulty level manipulated through altering
display and response times, varying the frequency of items in a category, and varying the
semantic distance between the training items and the foils, using semantic analysis
procedures. Participants in this study would not move on to the next level until they
86
reached criterion at the present level (Davis & Baynes, 2009). Future research may also
wish to incorporate pre-intervention assessment to determine any individual variance on,
or hierarchy of difficulty regarding, categorical, associative or perceptual levels.
Although we do not know of any norms for which levels are generally found by patients
to be more difficult, if there is a difference for the participant, then this should be taken
into account so that training templates (and the number of templates of each level
included in training sets) can be matched more precisely in terms of difficulty.
In each condition, some templates contained orthographically presented questions
and some did not. Questions for those that did not were presented verbally by the
clinician. It is possible that this may have affected the results, since the percentages of
templates in each condition that contained orthographically presented questions were not
calculated precisely and therefore may have differed slightly between the two conditions.
Nickels and Best (1996) found that “the modality of input can affect whether or not the
therapy influences output, and this may be related to differences in comprehension in the
two modalities.”
Our therapy could have been more intensive, which might have helped
consolidate learning (of List 4B, in particular): While the present study defined intensity
partly in terms of intense focus on a small number of training items, and involved
scheduling the maximum number of sessions per week thought possible for this
participant due to transportation issues and other considerations, it might have been
possible to train a volunteer or family member to provide additional practice on a home
or laptop computer, as other researchers have done (Davis & Baynes, 2009). Some
87
authors have urged further investigation to determine both the ideal length of therapy and
the number of hours of therapy per week that would be most likely to “allow for
maximum recovery” (Bhogal, Teasell, & Speechley, 2003).
In this as in any other study, a critical appraisal can suggest numerous ways to
increase rigor and control for extraneous factors. While no study can control for every
potential variable or confound, Nickels and Best (1996) noted that by varying aspects of
tasks used in semantic therapy, it is possible to tease apart the differential treatment
effects and identify which aspects of therapy may be crucial to success. “Although we
are not recommending this ‘reductionist’ approach for clinical practice, it is nonetheless
effective for determining why treatments may be differentially effective” (Nickels &
Best, 1996).
Conclusions
Despite limitations, this comparison of two intensive, semantic decision-based,
computerized verb interventions, one free of the requirement of speech production and
one requiring spoken responses, was accompanied by improvements in naming of trained
verbs in both conditions and improvements in spontaneous speech for a patient with
fluent anomic aphasia. Findings support the use of semantic decision-based, productionfree training as valuable augmentation to conventional therapy for aphasia rehabilitation.
In addition, verb training may have direct effects on spontaneous speech and fluency.
Studies such as the present investigation suggest that implicit treatments have the
potential to become an important part of an integrated approach to treatment that would
allow clinicians to provide patients with intensive therapy that would otherwise be cost
88
prohibitive. Interventions which do not require explicit speech production may present
the opportunity to develop treatment programs that can be adapted for use at home to
offer extended practice with minimal supervision between speech therapy sessions, or to
offer a means of allowing patients to continue improving their word retrieval skills long
after their speech therapy sessions have ended. In the face of declining insurance
coverage for therapy, interventions amenable to use on a home computer may provide an
ideal method for individuals requiring or desiring additional treatment (Davis & Baynes,
2009; Petheram, 2004, Raymer, Kohen, et al., 2006). As one author noted, with clinicians
everywhere increasingly required to “do more with less,” it may be “essential to explore
alternative methods of service delivery,” for example, using clinicians “as consultants to
patient and family rather than as the primary treatment provider” (Wertz, 2000).
Further research is needed to determine if results of this study were directly
related to the presence or absence of the requirement of speech production, and if so,
whether results would replicate in other patients, in other aphasic syndromes, and in
combination with other types of therapy approaches. In addition, future investigations
may wish to consider which specific factors may have contributed to improvements in
verb naming and spontaneous speech.
89
APPENDIX A
Trained and Untrained Verb Lists
Table A3. Phase One Trained and Untrained Verbs
List
List 1A:
Trained Implicit
List 2B:
Trained Explicit
Untrained List
Verb
Peeling
Slicing
Skating
Biking
Shoveling
Jumping
Splashing
Chewing
Pouring
Closing
paddling
K-F Frequency
3
13
1
5
5
24
3
6
9
234
1
Baseline Performance
(# of times missed)
3
3
1
1
1
0
3
3
3
1
3
Sneezing
Sniffing
Hiking
Roasting
Painting
Balancing
Feeding
Digging
Grilling
Drying
Yawning
Total: 304
Average: 27.64
3
2
4
10
37
32
123
10
3
72
2
Total: 22
Average: 2.0
3
3
3
3
1
3
1
1
3
2
0
Tying
Whispering
Dipping
Diving
Plowing
Climbing
Falling
Undressing
Crawling
Riding
Juggling
Total: 298
Average: 27.09
23
12
6
23
16
12
147
1
11
49
2
Total: 23
Average: 2.09
2
1
3
1
3
1
1
3
1
1
3
Total: 302
Average: 27.45
Total: 20
Average: 1.81
90
Table A4. Phase Two Trained and Untrained Verbs
List
List 3A
Trained Explicit
Verb
Marching
Dressing
Filling
Rescuing
Squirting
Popping
Harvesting
Grating
Fixing
Sewing
Hopping
K-F Frequency
120
67
50
15
1
8
12
3
14
6
2
Total: 298
Average: 27.09
List 4B
Trained Implicit
Untrained List
Baseline Performance
(# of times missed)
3
3
3
3
3
2
3
3
3
2
3
Reaching
Rocking
Baking
Stirring
Sailing
Crouching
Rolling
Leaping
Carving
Swinging
Floating
106
75
12
7
12
7
35
14
3
24
3
Total: 31
Average: 2.82
3
3
3
3
3
3
2
3
3
3
3
Resting
Milking
Towing
Delivering
Orbiting
Scooping
Punching
Scrubbing
Serenading
Drilling
Parachuting
Total: 298
Average: 27.09
163
49
1
18
16
5
5
9
1
33
1
Total: 32
Average: 2.90
2
3
3
3
3
3
2
3
3
3
1
Total: 301
Average: 27.36
Total: 29
Average: 2.63
91
APPENDIX B
Verb Use in Training Templates
Table B5. Question Types with Sample Questions
Single Target
Multiple Targets
Single Target with
(Single Verb)
(Single Verb)
Embedded Negative
(Single Verb)
Which one is peeling?
Which one goes with biking?
Who can paint?
Who paddles?
Where can you skate?
What do you chew with?
What can you balance on?
Which one will float?
Which one do you sail?
Who splashed?
What goes best with baking?
Which one was roasted?
Which one swings?
Which one would you slice?
Who is crouching?
Which one will splash?
Where would you bake?
Which one is about to roll?
Which one is rocking?
Multiple Targets
with Embedded
Negative
(Single Verb)
Which ones are leaping?
Which ones go with painting?
Which ones can yawn ?
Which ones are hiking?
Which two are balancing?
Which three are feeding?
Which ones would you feed?
Which three are drying?
Which two are digging?
Which ones are harvesting?
Which ones do you use for
sewing?
Which ones are rescuing?
Which three can you close?
Which two will splash?
Which ones would you sniff?
Which ones go with sneezing?
Which three are filling?
Which three go with dressing?
Which one is not leaping?
Which one is not grilling?
Which one does not go with
shoveling?
What does not go with biking?
Who is not jumping?
Which one does not paddle?
Which one is not for pouring?
Which one does not hike?
Who does not reach?
Who is not dressing?
Which one is not for fixing?
Where can you not skate?
Where can you not bike?
Where should you not leap?
What never closes?
Who never marches?
Which one was not rescued?
Which one has not been filled?
Which ones cannot float?
Which ones do not go with
grilling?
Which ones should you not
roast?
Which ones can you not close?
Which two cannot hike?
Which three cannot bake?
Which ones will not roll?
Which ones cannot rock?
Which ones can you not stir?
Which three are not reaching?
Which two were not baked?
Which ones do not go with
biking?
Which ones are not stirring?
Which two are not for baking?
Which three do not go with
dressing?
Single Target
(Multiple Verbs)
Multiple Targets
(Multiple Verbs)
Single Target with
Embedded Negative
(Multiple Verbs)
Multiple Targets
with Embedded
Negatives
(Multiple Verbs)
Which one is both floating and
sailing?
Which one will pop and
squirt?
What can crouch and leap?
Which one is reaching and
swinging?
Which one is squirting and
filling?
Which one is rocking while
floating?
Which one is marching while
dressing?
Which one is feeding and
grilling?
Which one is both drying and
yawning?
Which one goes with stirring
and baking?
Which one floats and sails?
Who is harvesting and filling?
Which one can roll and float?
Which one goes with both
fixing and sewing?
Which one goes with both
leaping and carving?
Which ones are both stirring
and baking?
Which ones go with either
rocking or swinging?
Which ones go with both
fixing and sewing?
Which ones are hopping and
popping?
Which ones are crouching or
leaping?
Which two are marching or
hopping?
Which three go with grating or
harvesting?
Which two are jumping and
splashing?
Which ones would you peel or
slice?
Which three go with carving
or stirring?
Which two are rocking, rolling
or swinging?
Where can you skate or bike?
Where can you jump, splash or
paddle?
Who is reaching and carving?
Which one is pouring but not
splashing?
What goes with grilling but
not roasting?
Which one is not sneezing or
yawning?
Which one is not sneezing,
sniffing, or yawning?
Which one is not filling or
squirting?
Which one is filling but not
squirting?
Which one is reaching but not
crouching?
Which one is not biking or
skating?
Which one does not go with
peeling or slicing?
Which one can you not roast
or grill?
Which one goes with sewing,
but not dressing?
Where can you skate but not
bike?
Where can you grate but not
harvest?
Which ones are not rocking,
rolling, or swinging?
Which ones cannot crouch or
leap?
Which three are popping but
not squirting?
Which ones go with stirring
but not with baking?
Which ones float but do not
sail?
Which ones do not go with
grilling or roasting?
Which two are crouching but
not reaching?
Which two are jumping but
not splashing?
Which three are paddling but
not splashing?
Which two would you not
grate or harvest?
Which two rock, but cannot
roll?
Which ones are for carving but
not for stirring?
Which ones cannot hop or
pop?
92
Table B6. Sample Typical and Atypical Exemplars
Verb
Typical Exemplar
Peeling
Peeling a banana
Closing
Closing container (box) lid
Pouring
Balancing
Pouring liquid into glass
Standing on one leg
Drying
Drying with a towel
Dressing
Person getting dressed
Filling
Filling a glass with water at
faucet
Squirting
Squirt gun squirting water
Popping
Popping balloon with a pin
Stirring
Stirring food or beverage with a
spoon
Rolling
Ball rolling on ground
Carving
Etching design into wood or soap
Swinging
Child on playground swing
Atypical Exemplar(s)
Peeling a hard-boiled egg
Peeling paint
Peeling sunburned skin
Peeling off adhesive backing
Closing a shop
Closing a gate
Pouring rain
Using balancing scales
Balancing objects on head
Air drying on clothesline
Drying hair with blow dryer
Air drying fingernails or hands
Drying on a drying rack
Drying meat or fish
Dressing a doll or mannequin
Putting a sweater on a dog
Filling gas tank at gas pump
Filling muffin cups with batter
Filling swimming pool using hose
Santa filling Christmas stocking
Grapefruit squirting juice in eye
Elephant squirting from trunk
Eyes popping out
Corn popping
Children’s Popper toy popping
Pop-up book “popping” open
Pop-gun popping
Fingers popping bubble wrap
Champagne cork popping
Popping soap bubbles
Stirring paint with a stick
Stirring witch’s cauldron
Stirring chemicals in a lab
Rolling dice
Rolling dough with rolling pin
Child rolling down a hill
Rolling dough into a ball in hand
Rolling object with wheels
Rolling a tire or inner tube
Log rolling on water
Carving a turkey
Carving a jack-o-lantern
Carving Mount Rushmore
Pendulum swinging to and fro
Sign swinging on hinges
Swinging bed or hammock
Tarzan swinging on vine
Swinging from chandelier
93
APPENDIX C
Sample Training Templates
.
Templates with visual and featural similarities between images to offer greater challenge.
94
Which one is shoveling?
Templates featuring single-target, single-verb questions were the primary template type
used in the intervention, especially for early training of each new list.
95
What goes best with jumping?
Images selected to match the participant’s areas of interest (cute babies and sports).
96
What goes with chewing?
Templates featuring four images with strong categorical, associative, or perceptual
similarities.
97
Who is biking?
Templates with a strong unifying theme were thought to offer greater challenge.
98
Multiple-target, single-verb questions training multiple meanings/atypical exemplars of
target verbs.
99
Template with multiple-target, single-verb question used in explicit training of feeding.
Single-target, single-verb question with embedded negative.
100
As often as possible, images were selected to appeal to the participant’s sense of humor.
101
Templates were designed to be aesthetically pleasing, and to require intense focus.
102
Whenever possible, the participant’s own most frequent error productions (e.g.,
mowing/harvesting) were incorporated as foils.
Images on templates were visually balanced for maximum visual appeal.
103
Multiple-target, single-verb question with embedded negative.
Single-target, multiple verb question: Which one rocks and floats?
104
Multiple-target, multiple verb question (Which two are both reaching and leaping?”)
incorporating football, one of the participant’s primary areas of interest.
Primate-themed template featuring single-target, multiple-verb question with embedded
negative.
105
Single-target, multiple-verb question with embedded negative (and cute hamsters).
.
Versatile template suitable for single target, multiple verb question with embedded
negative (Which one rocks, but does not swing or float?)
106
Multiple-target, multiple-verb question with embedded negative (and cute pandas).
Versatile bride-themed template used for training hiking, balancing, feeding, and grilling.
107
Versatile template.used for a variety of question types, e.g., single-target, single-verb
questions (Which one goes best with peeling?), multiple-target, single-verb questions
(Which two can you peel with?), Multiple-target, single-verb questions with embedded
negatives (Which three can you not slice with?), Single-target, multiple-verb questions
(Which one can you peel or slice with?), Single-target, multiple-verb questions with
embedded negatives (Which one can peel but not slice?), and multiple-target, multipleverb questions with embedded negatives (Which two cannot peel or slice?).
Versatile template used for single-target, single-verb question (Which one can roll?),
multiple-target, single-verb question (Which two rock?), or single-target, multiple-verb
question with embedded negative (Which one does not roll or rock?).
108
A Name-the-Verb template, one of the only template types occasionally used during one
condition (explicit training) but not in the other condition (implicit training), due to the
requirement of explicit naming.
The implicit therapy counterpart to the explicit therapy Name-the-Verb template type
(see Figure 29, above). For this template, the clinician asked “Which one is
grilling/balancing/yawning/drying” questions.
109
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