Effect of Verb Network Strengthening

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AJSLP

Supplement

Effect of Verb Network Strengthening

Treatment (VNeST) in Persons With

Aphasia: Extension and Replication

of Previous Findings

Lisa A. Edmonds,a,b Kevin Mammino,a and Jimena Ojedaa,b

Purpose:Verb Network Strengthening Treatment(VNeST)

is an aphasia treatment that targets verbs (e.g., measure)and their related thematic roles (e.g., carpenterlumber).Previous studies reported encouraging results in a number ofparticipants using single-subject design with improvementsobserved on naming, sentence production, and discourse.The purpose of the current study was to conduct a groupanalysis evaluating the effect of VNeST on similar outcomes.Method:A multiple baseline design across participantswas conducted with 11 persons with aphasia due to stroke.Wilcoxon signed-ranks tests were used to evaluate potentialimprovement from pre- to posttreatment and maintenance.Individual effect sizes were also calculated to evaluatemagnitude of change within and across participants.Results:Results showed significant improvement atposttreatment and maintenance on trained and untrained

sentence probes and object and action naming. Improvement

in the production of sentences not targeted in treatment wasnonsignificant at posttreatment assessment but significantat maintenance. Moderate increases in percentage ofcomplete utterances and overall informativeness wereobserved on discourse.Conclusion: The results of this study replicate previousfindings and provide evidence that VNeST may promotespecific and generalized lexical retrieval abilities and affectbasic syntax production in both constrained and discourseproduction tasks.

Key Words: aphasia, VNeST, verbs, treatment, thematicroles, sentences, discourse

The most pervasive symptom in aphasia is anomia,or difficulty retrieving words (e.g., Laine & Martin,2006), which can affect language production at the

single word, sentence, and discourse level. The majorityof lexical retrieval treatment paradigms reported in theliterature have targeted single-word noun production, andalthough generalization to improved retrieval of semanti-cally related nouns has been observed across a number ofstudies, generalization to sentences or discourse has beennegligible (see Kiran & Bassetto, 2008; Nickels, 2002).Treatments targeting single verb retrieval have primarily

focused on provision of semantic and/or phonological cues.

Overall, improvement has been limited to trained verbs, withvirtually no improvement to untreated verbs, though someimprovement to sentence production and/or connectedspeech has been reported in some studies. (For relevantreviews, see Conroy, Sage, & Lambon Ralph [2006] andWebster & Whitworth [2012].)

In an attempt to promote sentence production andconnected speech, a number of verb treatments haveintegrated arguments into treatment. A subset of thesestudies (as described by Webster & Whitworth, 2012) focusedprimarily on sentence structure, syntax, and/or morphosyn-

tax (e.g., Bastiaanse, Hurkmans, & Links, 2006; Conroy,Sage, & Lambon Ralph, 2009; Edwards & Tucker, 2006;Links, Hurkmans, & Bastiaanse, 2010; McCann & Doleman,2011; Raymer & Kohen, 2006). Trained tasks included sen-tence completion and production and sentence productioncuing hierarchies. Overall, improvements were observedfor trained verbs, but there was limited improvement tosingle-word retrieval of untrained verbs (Links et al., 2010;Raymer & Kohen, 2006). Some improvements to sentence

aBrain Rehabilitation and Research Center, Malcom Randall VA

Medical Center, Gainesville, FLbUniversity of Florida, Gainesville

Correspondence to Lisa A. Edmonds: [email protected]

Editor: Swathi Kiran

Associate Editor: Yasmeen Faroqi-Shah

Received August 16, 2013

Revision received January 24, 2014

Accepted February 25, 2014

DOI: 10.1044/2014_AJSLP-13-0098Disclosure:The authors have declared that no competing interests existed at thetime of publication.

American Journal of Speech-Language Pathology Vol. 23 S312S329 May 2014 AAmerican Speech-Language-Hearing Association

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production were reported (Bastiaanse et al., 2006; Edwards& Tucker, 2006; Links et al., 2010; McCann & Doleman,2011), with improvement to connected speech in a fewparticipants (Bastiaanse et al., 2006; Edwards & Tucker,2006; Links et al., 2010). Although the improvements tosentence production and connected speech are encouraging,

the gains observed in these studies were primarily structuraland/or grammatical (Webster & Whitworth, 2012), notlexical.

As discussed in Webster and Whitworth (2012), thedegree of improvement to argument structure depends onwhether argument structure is lexically specified. If it is,improvement will be restricted to treated verbs, but if it isnot, improvement in sentence production could be morewidespread. Thus, the lack of generalized lexical improve-ment in these studies could reflect a focus on structurewithout explicit semantic training. Promoting semanticrelationships between verbs and their thematic roles could

potentially promote more generalized improvement to

sentence production and discourse (e.g., Edmonds & Babb,2011; Edmonds, Nadeau, & Kiran, 2009). Some studies haveattempted this with tasks such as identifying agents andthemes in pictures and picture description (Fink, Martin,Schwartz, Saffran, & Myers, 1992), story production withan emphasis on verbnoun associations (Kim, Adingono,& Revoir, 2007), descriptions of a verbs semantics andthematic roles (Schneider & Thompson, 2003), semanticfeature analysis (SFA) with verbs (which focuses on singleverbs but includes thematic roles) (Faroqi-Shah & Graham,2011 [modified SFA]; Wambaugh & Ferguson, 2007;Wambaugh, Mauszycki, & Wright, 2014), and tasks target-ing associations between verbs and nouns, sometimes in

conjunction with sentence production (Webster & Gordon,2009; Webster et al., 2005).

The overall results of these studies showed improve-ment to trained verbs, but improvement to untrained verbswas still not observed in the vast majority of the studies (butsee Object and Action Naming Battery [OANB] verb nam-ing improvement in two participants in Faroqi-Shah &Graham [2011]). For the studies that examined potentialgeneralization to sentence production, some observedimprovement only with sentences containing trained verbs(Kim et al., 2007; Schneider & Thompson, 2003), whileothers saw improvement with untrained verbs as well

(Webster & Gordon, 2009; Webster et al., 2005). Of the

studies that examined connected speech, only a few reportedimprovement on lexical retrieval and/or improved syntaxor structure (Fink et al., 1992; Kim et al., 2007; Webster et al.,2005). Although there is some evidence of generalization inthese studies, there is still limited improvement to untrainedlexical items. Verb Network Strengthening Treatment(VNeST), the focus of the current study, is principally similarto these treatments. However, there are some differences,especially with regard to the scope of semantic training.

VNeST is a theoretically motivated treatment designedto promote lexical retrieval in sentence contexts, withpotential generalization to more widespread lexical accessimprovement (Edmonds et al., 2009). The fundamental

theoretical premise of VNeST is that semantic verb networksare represented as neural networks that strengthen viaHebbian learning through repeated activation and use(Edmonds et al., 2009). A growing body of research withyoung adults suggests that verbs and their related thematicroles are neurally coactivated such that agents and patients

prime or facilitate activation of related verbs (Edmonds &Mizrahi, 2011; McRae, Hare, & Ferretti, 2005) and viceversa (Edmonds & Mizrahi, 2011; Ferretti, McRae, &Hatherell, 2001). There is also bidirectional neural coacti-vation between verbs (e.g., slicing) and their instruments (e.g.,knife) (Ferretti et al., 2001; McRae et al., 2005; Park &Edmonds, 2013) and priming from locations (e.g., restaurant)to related verbs (e.g., eating) (Ferretti et al., 2001).

The treatment steps of VNeST follow directly from thistheoretical framework. Participants are given a verb (e.g.,measure) and are asked to retrieve related agents (doers of theaction, e.g., carpenter) and patients (receivers of the action,e.g., lumber). Participants generate multiple pairs of agents

and patients per verb, thereby eliciting various event schemas(e.g., carpenterlumber, chefsugar, seamstressfabric formeasure). Because a verbs conceptual meaning is somewhatloose(relative to nouns) (Black & Chiat, 2003) and thuscan have different meanings based on its thematic roles,generation of multiple agentpatient pairs actualizes variousdimensions of the verbs meaning. Retrieving verb schemasalso activates a large network of world, autobiographic, andsemantic knowledge that could potentially maximize gener-alization of lexical retrieval to a relatively large corpus oftrained and untrained words in untrained language contextsand tasks. Thus, the scope of semantic treatment is greaterthan other treatments that target verbs and their thematic

roles, as multiple event schemas that can represent differentmeanings or uses of trained verbs are not targeted in thosestudies.

Another aspect of VNeST that is different from otherstudies is that no pictures are used in treatment, so partic-ipants cannot associate or learn responses related to pictures(e.g., Webster & Gordon, 2009) but rather must search,activate, and retrieve their own memories and representa-tions. Participants also answer wh-questions (where, when,why) about one scenario per verb to further develop theschema and expand its saliency and relevancy. For the car-penter measuring lumber example, a participant may discussthat her bathroom was remodeled last summer because of

flood damage. Thus, VNeST requires divergent productionof multiple event schemas in a systematic way without beinglimited by the entities and action represented in trainedpictures.

While VNeST attempts to engage a large semanticnetwork, treating verbs in conjunction with their thematicroles also activates the syntactic elements of sentences (i.e.,subjectverbobject) in a number of related ways. Becauseargument structure is considered an integral part of a verbslexical representation, training them together potentiallystrengthens both the verb representation and its connectionsto its arguments. In addition, the repeated and diverseselection of subjectagents and objectpatients potentially

Edmonds et al.: Verb Network Strengthening Treatment S313


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on our primary discourse measure, complete utterances(Edmonds et al., 2009). We also predicted improvement onpercentage correct information units (CIUs), a measure ofinformative words, from Nicholas and Brookshire (1993).Although we were primarily interested in group results forthis study, we also report individual responses to treatment,

including effect sizes.

Method

Experimental Design

A multiple baseline approach across participants wasused with four phases: (a) baseline (probe testing; n = 5);(b) treatment (biweekly probe testing; n = 5); (c) posttreat-ment probes (n= 1 [because of time constraints in posttestingfor some participants] or n = 3); and (d) 3-month main-tenance probes (n= 1). The probe task was sentence pro-duction for pictures depicting trained (The carpenter is

measuring the lumber) and untrained semantically relatedverbs (The farmer is weighing the apples). A control task wasadministered during the same time points for demonstrationof experimental control. Additional outcome measures,described below, were administered at posttreatment andmaintenance.

Participants

Treatment Participants

Eleven participants (mean age = 63.1, 7 males) with aminimum of 12 years of education were recruited from theBrain Rehabilitation and Research Center at the Malcom

Randall VA Medical Center in Gainesville, Florida, and fromBrooks Rehabilitation in Jacksonville, Florida. None of theparticipants had participated in previous VNeST studies.Participants met several inclusion criteria, including (a) di-agnosis of aphasia based on the WABR (Kerstesz, 2006),(b) monolingual English speaking, (c) right-handedness priorto stroke, (d) negative history of diagnosed learning disorderor drug or alcohol addiction, (e) maximum baseline aver-age of 40% on the sentence probes, and (f ) no worse thana composite score of a moderate deficit on the CognitiveLinguistic Quick Test (CLQT; Helm-Estabrooks, 2001). Allparticipants had aphasia as a result of stroke. Nine of the11 experienced a single left hemisphere ischemic stroke, one

(P3) had an aneurysm rupture during a clipping procedure,and one (P4) had a left middle cerebral artery ischemic strokeafter two aneurysm ruptures. Finally, no participants exhib-ited more than moderate apraxia of speech (AOS) on thebasis of their performance on the Apraxia Battery for AdultsSecond Edition (Dabul, 2000) and on evaluation of McNeil,Robin, and Schmidts (2009) characteristics of AOS. SeeTable 1 for demographic details.

Six additional participants were evaluated. Five werenot included because they did not meet the inclusion andexclusion criteria (e.g., multilingual, high scores on sentenceprobes), and one chose not to enroll due to living too faraway.

Communication Partners

Ten treatment participants had a family member whocommunicated with them regularly and agreed to complete aquestionnaire about the treatment participants communi-cation. Eight of the 10 communication participants com-pleted the Montreal Cognitive Assessment (Nasreddine et al.,

2005), and of those eight, seven scored within normal limits(WNL) and were included in the study (the one who wasnot enrolled scored 21/30 [with 26 considered WNL]). Theother two participants were not available to come to theclinic for testing, but they were both below 60 years of age,gainfully employed, and showed no signs of inability tocomplete the questionnaire competently, so they were enrolledwithout cognitive testing. Thus, 9 of the 11 treatment partic-ipants had communication partners who were enrolled andwho completed the CETI (Lomas et al., 1989). Communica-tion partners (7 women) included four spouses, three adultchildren, one sibling, and one grandmother, with an averageage and education of 56.0 (SD= 17.5) and 14.1 (SD= 1.3),

respectively.

Materials

The following measures were administered to deter-mine pretreatment language abilities and to serve as outcomemeasures at posttreatment. Table 2 shows group scores,and Table 3 shows individual scores.

Outcome Measures for Research Question 1

Sentence probe pictures.Sentence probe developmentis discussed in Edmonds et al. (2009) and Edmonds and Babb(2011). Briefly, 28 pictures were developed to elicit sentences

containing an agent, verb, and patient, where agents havespecific titles (e.g., nurse, carpenter) to promote specificlanguage (as opposed to general terms, such as woman, man).A few additional sentences were added in this study, andsome previous sentences were reconfigured to ensure noreversible sentences and no entities with general titles (e.g.,boy, woman). Sentences were divided into sets, so that eachverb (measure) was semantically related to another verb(weigh) across sets. See Supplemental Table 1 for details.

Control task.Two control tasks were administered toparticipants during the baseline phase to rule out the pos-sibility that improvements during treatment reflected anonspecific effect on semantic knowledge (i.e., to demon-

strate internal validity). The first was a single-word adjective-retrieval task used previously (see Edmonds et al., 2009).This task requires participants to complete 11 sentences byproviding a synonym to a provided adjective (e.g., Someonewho is sick is also said to be _____ [target: ill]). Adjectiveswere chosen rather than verbs, because a sufficient number ofverbs unrelated to treatment verbs and balanced acrosspsycholinguistic variables (e.g., frequency, length) could notbe generated (Edmonds et al., 2009). This is a conserva-tive task, because participants are required only to provideone word, and they are provided with a carrier phrasethat contains a synonym to the target word. However, thistask was hypothesized not to improve, because adjectives



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and features of objects were not explicitly trained. Further, asimilar task demonstrated control in a previous verb treat-

ment study (Marshall, Pring, & Chiat, 1998).The second control task was the nonword repetition

task (Number 8) from the Psycholinguistic Assessment ofLanguage Processing (Kay, Lesser, & Coltheart, 1992). Thistask was chosen because disproportionate nonword repetition,as compared with real word repetition, has been reported inaphasia (Rapcsak et al., 2009). The hypothesized mechanismis a phonological deficit that disproportionately affects theprocessing of unfamiliar phonological patterns (Rapcsaket al., 2009). Because VNeST does not target phonology,nonword repetition was not hypothesized to improve.

Procedures for Collecting Probe Data

and Administering TreatmentProbe and control measures. During baseline, the probe

pictures and control items were administered at the begin-ning of each session and were audio- and video-recorded.Pictures were presented pseudorandomly with semanticallyrelated verbs (boilfry) in nonsequential order. For eachpicture, participants were instructed to Make a sentenceand include him/her, the action, and thiswhile pointing tothe agent (carpenter), verb (measure), and patient (lumber).Prompts were not provided unless the participant produced ageneral word for the target (e.g., cut instead ofsliceor man

instead ofcarpenter), for which a prompt for a more specificword was given. After the baseline period, trained and

untrained semantically related verbs were chosen based onthe 10 sentence probe pairs that resulted in the lowest aver-

age starting point with similar averages for the trained anduntrained sets.

Transcription from audio files was conducted for allprobe responses. One point was awarded for each correctagent, verb, and patient, with one phonemic error allowed(e.g.,bilot for pilot) per word. Grammatical and morpho-logical errors were not penalized, because they were not tar-geted in the treatment. If a response matched all three targetsfor the agent, verb, and patient, then 1 point was given for thetotal sentence score. Accurate alternative words were givencredit (e.g., loggerfor lumberjack, jetfor airplane). To ensureconsistency in probe scoring, we conducted interrater reli-ability for 100% of weekly probes. A point-to-point evaluation

showed 97% agreement in scoring.Treatment materials and protocol. Treatment was

provided two times per week for 10 weeks, for a total of20 sessions. Each session was 2 hr long. With time subtractedfor sentence probes during the treatment phase, participantsreceived approximately 35 hr of total treatment. (Becauseof scheduling issues, P5 received only 18 sessions.) Ten verbswere trained per participant, and each verb was trained 1 timeper week. See the Appendix for materials and protocol.


Single-word lexical retrieval was evaluated with theOANB (Druks & Masterson, 2000), which contains pictures

Table 1.Demographic and lesion information for all participants.

Pt M/F Age Ed Race MPO Aphasia type Stroke or lesion information

1 M 49 14 AfAm 61 Anomic Large left MCA CVA with changes in the left frontoparietal subcorticalwhite matter.

2 M 69 12 Cauc 74 Anomic Left frontal, temporal, and parietal CVA. Involved regions include

frontal operculum, triangular part of the frontal gyrus, superiortemporal gyrus, superior and middle frontal gyrus, precentralgyrus, dorsolateral frontal cortex, perisylvian region, hand and armregions of primary motor cortex.

3 M 69 13 AfAm 144 Anomic Left posterior communicating artery aneurism rupture during asurgery attempt to clip it. Left caudate head and internal capsuleinvolvement.

4 F 70 15 Cauc 15 Anomic Anterior communicating artery aneurysm, basilar tip aneurysm withPCA ischemia, and subsequent left MCA CVA (embolism).

5 M 35 14 Cauc 59 Anomic Large left MCA CVA, thrombosis.6 F 81 16 Cauc 72 Conduction Moderate-sized CVA in the left parietal lobe extending to the junction

of the temporal and parietal lobes.7 M 63 18 Cauc 14 Conduction-Jargon Left MCA CVA. Left anterior temporal infarct extension to the

adjacent portions of the left parietal lobe and deep white matter ofthe left frontal lobe, including the head of the caudate nucleus andposterior insula.

8 M 61 18 Cauc 23 Conduction Moderate left CVA involving temporal lobe, parietal lobe, and part of the left frontal lobe, including the insular cortex.

9 F 68 16 Cauc 95 Wernickes Large left MCA CVA involving mid- to peripheral distribution of theMCA with vascular compromise to the periphery of the parietallobe and portions of the periphery of the temporal lobe.

10 F 58 15 Cauc 26 TCM Large left anterior division MCA CVA.11 M 71 22 Cauc 16 TCM Moderate-sized left MCA CVA involving the left frontal lobe, insular

cortex, and left basal ganglia.

Note. Pt = participant; M = male; F = female; Ed = education; MPO = months postonset; AfAm = African American; Cauc = Caucasian;TCM = transcortical motor aphasia; MCA= middle cerebral artery; CVA = cerebrovascular accident; PCA = posterior cerebral artery.

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of objects (N= 162) and actions (N= 100). The object andaction stimuli are divided into two forms (A and B) that arebalanced for psycholinguistic (e.g., frequency, age of acqui-sition) and nonlinguistic (e.g., imageability, visual com-

plexity) variables. All participants completed both forms,and no cues or feedback were given.

Lexical retrieval in sentences was evaluated withstimuli from the Argument Structure Production Test fromthe NAVS (Thompson, 2011). Verbs included one-, two-,and three-place verbs (e.g., The dog is barking; The womanis kissing the man; The man is putting the box on the shelf).

The NAVS protocol requires showing and reading the verbto the participant, but we did not do either; rather, par-ticipants just saw the pictures and made a sentence. Further-more, the test contains two- and three-place verbs in optional(The man is sweeping) and obligatory contexts (The manis sweeping the dirt), but we tested only the more complex

sentence to avoid multiple presentations. Thus, 36 of50 pictures were administered (one-place, n = 8; two-place,n= 17; three-place, n = 11).

For OANB and the NAVS, scoring was conducted

according to the test manuals, though one phonemic errorper lexical item was allowed. One hundred percent reliabilitywas conducted (point to point) for both measures, with anaverage scoring agreement of 96.5%.


Participants responded to all 10 discourse elicitationmaterials from Nicholas and Brookshire (1993), whichinclude procedural, personal, single-picture, and sequential-picture stimuli. Participant responses were blinded and thentranscribed using Systematic Analysis of Language Tran-scripts software (Miller & Iglesias, 2012). Utterances werebroken into T-units, or a main clause with its subordinate

Table 2.Group statistics details and results for tasks corresponding to all research questions evaluated at posttreatment and 3-monthmaintenance.

Generalization measurePre-tx mean

(SD)Post-tx mean

(SD) WilcoxonZ pPre-tx meana

(SD)Maintenance

(SD) Wilcoxon Z- p

Research Question 1

Sentence probesSentencesTR (n= 10) 20.4% (13.3) 58.8% (33.9) 2.803 .005 20.4% (13.3) 56.0% (29.9) 2.705 .007SentencesUT (n = 10) 19.8% (11.0) 40.9% (24.9) 2.703 .007 19.8% (11.0) 43.0% (27.5) 2.805 .005WordsTR (n= 30) 58.5% (11.1) 80.7% (17.0) 2.803 .005 58.5% (11.1) 80.3% (13.5) 2.805 .005

Agents (n= 10) 57.6% (21.6) 84.7% (19.6) 2.803 .005 57.6% (21.6) 86.0% (18.4) 2.805 .005Verbs (n = 10) 52.4% (16.1) 74.0% (21.8) 2.395 .017 52.4% (16.1) 68.0% (25.3) 2.492 .013Patients (n= 10) 65.6% (17.4) 83.5% (18.6) 2.703 .007 65.6% (17.4) 87.0% (10.6) 2.654 .008

WordsUT (n = 30) 59.8% (10.0) 73.1% (15.5) 2.701 .007 59.8% (10.0) 73.3% (14.7) 2.701 .007Agents (n= 10) 63.6% (21.9) 74.3% (19.9) 2.075 .038 63.6% (21.9) 76.0% (21.2) 1.994 .046Verbs (n = 10) 49.4% (16.7) 61.3% (22.6) 1.779 .075 49.4% (16.7) 64.0% (23.2) 2.668 .008Patients (n= 10) 66.4% (12.8) 83.7% (14.2) 2.803 .005 66.4% (12.8) 79.0% (16.6) 2.293 .022

Control 34.7% (14.5) 42.0% (18.0) 1.838 .066 34.7% (14.5) 36.6% (20.4) 0.841 .400

Research Question 2Single words and sentences

OANBnouns (n= 162) 79.91% (12.3) 85.07% (12.6) 2.402 .016 N/A N/A N/A N/A

OANB

verbs (n= 100) 64.64% (18.2) 74.18% (16.0)

2.668 .008 N/A N/A N/A N/A NAVS sentences (n = 36) 29.04% (23.7) 42.42% (25.6) 1.719 .086 29.04% (23.7) 40.15% (23.8) 2.807 .005

Research Question 3Discourse

% Comp utterances 39.73 (11.9) 46.74 (16.0) 2.223 .026 40.85 (11.9) 47.98 (13.8) 1.580 .114Number of words 922.18 (584.2) 1,036.82 (638.4) 1.156 .248 986.80 (572.9) 1,093.40 (546.6) 0.764 .445Number of CIUs 408.45 (251.0) 469.91 (269.1) 1.682 .093 438.80 (242.4) 538.70 (281.2) 1.955 .051% CIUs 46.63 (11.8) 48.70 (13.8) 0.622 .534 47.49 (12.0) 51.42 (13.3) 1.988 .047CIUs per minute 27.69 (15.1) 28.90 (16.6) 0.978 .328 29.55 (14.5) 33.51 (21.4) 0.764 .445Number of utterances 132.18 (69.3) 143.36 (85.1) 0.408 .683 141.20 (65.9) 142.90 (74.2) 0.415 .678% Pauses 37.39 (24.0) 35.74 (24.4) 0.978 .328 34.52 (23.3) 33.82 (24.2) 0.663 .508% Mazes 10.99 (5.6) 10.71 (5.5) 0.712 .477 10.00 (4.7) 10.93 (5.2) 0.868 .386

Research Question 4Aphasia severity:

WAB AQ 75.91 (10.4) 82.12 (8.6) 2.395 .017 N/A N/A N/A N/A

Functional communication:CETI (N= 100 possible) 32.61 (9.7) 65.28 (11.2) 2.666 .008 32.61 (9.7) 58.29 (15.6) 2.666 .008

Note. Data in bold were significant at thep< .05 level. tx = treatment; TR = trained; UT = untrained; OANB = Object and Action Naming Battery;NAVS = Northwestern Assessment of Verbs and Sentences; Comp = complete; CIU = content information unit; WAB AQ = Western AphasiaBattery Aphasia Quotient; CETI = Communication Effectiveness Index; N/A = not applicable.aAn additional Pre-tx column is present because of a different number of participants that were evaluated at maintenance than at posttreatment.



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Table3.

Individualparticipantscoresforpretreatment,posttreatment,andmain

tenanceresultsforthesentenceprobes,

OANB,

NAVSsentenceproduction,

Nich

olasandBrookshire

(1993)discourseresults,andCETIsco

resforallparticipants.

Pt

Sentenceprobesa

Lexicalretrieval

NicholasandBrookshire

(1993)discoursetasks(n=10)

Funct

Comm:

CETI

AvgTR

Sent

(N=10)

AvgUT

Sent

(N=10)

OANB

%

Nounsb

(N

=162)

OANB%

Verbsb

(N=100)

%

NAVS

SentProdc

(N=36)

%

Comp

Uttsc

Number

ofwordsd

Number

ofCIUsd

%CIUse

CIUs/min

Words/min

%

P

auses

1Pre

3.8

2.8

90.1

82

72.2

54.7

811

469

57.8

35.7

65.9

24.1

DNT

Post

9.0***

5.0***

96.9

95

72.2

58.3

843

490

58.1

42.2

76.8

18.4

DNT

Main

9.0***

7.0***

N/A

N/A

75.0

63.5

696

439

63.1

39.7

65.0

22.3

DNT

2Pre

1.6

1.8

88.2

81

19.4

47.3

540

287

53.2

20.4

42.6

48.6

41.3

Post

4.7

4.3**

93.8

81

11.1

32.8

831

390

46.9

15.2

38.5

58.5

72.4

Main

7.0*

5.0***

N/A

N/A

19.4

33.6

1,0

89

515

47.3

16.2

36.7

50.3

64.4

3Pre

0.4

0.8

53.7

49

5.6

39.2

1,3

97

440

31.5

29.9

100.0

20.4

DNT

Post

2.0*

2.0

63.6

51

19.4

51.2

1,5

11

443

29.3

27.1

98.4

20.5

DNT

Main

3.0**

2.0

N/A

N/A

19.4

52.4

1,5

81

516

32.6

32.8

94.7

15.4

DNT

4Pre

2.8

2.6

89.5

61

16.7

28.6

276

105

38.0

9.1

26.8

66.1

25.3

Post

9.3***

7.3***

97.5

81

50.0

29.5

486

184

37.9

8.8

28.7

59.3

39.6

Main

8.0***

4.0*

N/A

N/A

22.2

N/A

N/A

N/A

N/A

N/A

N/A

N/A

56.5

5Pre

4.4

4.0

95.7

75

63.9

43.1

310

202

65.2

13.5

24.9

65.3

23.1

Post

10.0**

9.0**

97.0

86

66.7

64.6

339

261

77.0

15.7

23.0

63.8

83.7

Main

10.0**

10.0***

N/A

N/A

69.4

58.2

365

265

72.60

16.9

3

26.1

66.0

74.5

(tablecontinues)



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Table3(Continued).

Pt

Sentenceprobesa

Lexicalretrieval

NicholasandBrookshire

(1993)discoursetasks(n=10)

Funct

Comm:

CETI

AvgTR

Sent

(N=10)

AvgUT

Sent

(N=10)

OANB

%

Nounsb

(N

=162)

OANB%

Verbsb

(N=100)

%

NAVS

SentProdc

(N=36)

%

Comp

Uttsc

Number

ofwordsd

Number

ofCIUsd

%CIUse

CIUs/min

Words/min

%

P

auses

6Pre

1.8

2.0

67.3

63

41.7

57.4

1,4

11

721

51.1

42.7

80.7

20.4

45.6

Post

8.7***

4.3**

63.6

67

83.3

60.4

1,1

46

612

53.4

40.5

75.8

16.5

63.5

Main

5.0*

6.0**

N/A

N/A

50.0

55.1

1,1

16

603

54.0

33.4

64.9

13.1

60.3

7Pre

0.8

1.6

75.9

69

5.6

28.4

1,3

51

444

32.9

29.2

87.2

11.2

17.1

Post

3.7*

3.0*

75.7

69

44.4

28.6

1,3

23

431

32.6

31.1

94.9

12.0

59.7

Main

5.0**

2.0

N/A

N/A

30.6

29.5

1,3

08

444

33.9

25.6

68.2

31.2

37.3

8Pre

DNT

DNT

82.0

72

33.3

52.7

1980

916

46.3

57.0

119.5

15.7

36.4

Post

DNT

DNT

88.2

80

38.9

73.9

1,6

66

916

55.0

60.4

108.8

8.4

55.1

Main

DNT

DNT

N/A

N/A

50.0

62.9

1,7

12

1,0

41

60.8

77.1

121.8

6.2

45.5

9Pre

0.6

0.0

77.2

18

2.8

30.9

1,2

85

535

41.6

39.4

97.0

13.8

30.1

Post

1.7

1.0

**

84.6

41

2.8

46.1

2,3

73

974

41.1

46.5

109.2

13.9

77.6

Main

0.0

1.0

**

N/A

N/A

5.6

45.5

1,9

55

997

51.0

63.0

125.4

8.4

78.3

10 P

re

2.4

1.8

88.8

76

41.7

27.4

393

238

60.6

14.7

27.9

74.7

42.8

Post

7.7**

3.0*

91.9

84

27.8

38.4

472

284

60.2

14.1

26.1

69.2

48.3

Main

4.0

3.0*

N/A

N/A

69.4

53.1

639

384

60.1

16.4

31.4

63.4

50.9

11 P

re

1.8

2.4

72.7

65

16.7

27.5

390

136

34.9

13.1

43.5

51.1

31.9

Post

2.0

2.0

85.1

81

50.0

30.4

415

184

44.3

16.5

41.1

52.7

67.3

Main

5.0*

3.0

N/A

N/A

30.6

26.1

473

183

38.7

14.0

40.0

61.8

73.9

Note.

Scoreswithunderscorearewithinnormallimitsaccordingtothetestmanual.Avg=average;Sent=sentence;TR

=trained;UT=untrained;NAVSSentPro

d=NAVSSentence

Production;CompUtts=completeutte

rances;CIU=contentinformationunits;FunctComm=functionalcommunication;P

re=pretreatment;Post=posttreatment;M

ain=maintenance;

DNT=didnottest.

aBoldeditemsforsentenceprobesindicatesmall*,medium**,orlarge***effects

izescomparedwithpretreatmentscore.

b

BoldeditemsforanOANBindicateanincreaseof>2standard

deviationsfromthemeanasindicatedinthetestsmanual.cBoldeditemsforNAV

SSentenceProductionand%

completeu

tterancesindicatemediumorlargeeffectsizescomparedwith

pretreatment.dItemswerenotanalyzed

againstNicholasandBrookshire(1993)n

ormativedata.

eBoldeditemsfor%

CIUs,

CIUsperminuteandwordsperminuteind

icateanincreaseof

>2SEM(Nicholas&Brookshire,

1993)

comparedwithpretreatment.



9/19

clauses. Pauses 2 s were coded, and mazes, which weredefined as any filled pause (e.g., uh, um), false start (e.g.,b* b*), or part word (e.g., fir*), were also transcribed andcoded.

Transcriptions were coded for number of words andCIUs (Nicholas & Brookshire, 1993), from which percentage

CIUs (% CIU), CIUs per minute, and words per minute(WPM) were calculated. Complete utterances, which containboth a complete sentence frame and relevance to the topic(Edmonds et al., 2009), were also coded. A complete sen-tence frame [+SV] was defined as an utterance containing asubject, verb, and object (S-V-O). Grammatical, morpho-logical, and phonemic errors were acceptable, as these werenot targeted in treatment and are not penalized accordingto Nicholas and Brookshire (1993).

Relevance of utterances [+REL] was determined byevaluating whether the entire S-V-(O) segment was relevantto the topic. Multiple utterances with identical meaning

and containing no new information were considered relevant

only the first time. Thus, a complete utterance [+COMP]had to be coded as both [+SV] and [+REL] as shown by thefollowing examples (Edmonds et al., 2009):

1. The tree is open [+SV][REL][COMP].

2. A little guy with some sand on the shore with his handsthe sand [SV][+REL][COMP] (missing main verb).

3. To walk through the step [SV][REL][COMP].

4. The son is flying is a kite [+SV][+REL][+COMP].

Once coding was complete, percentage of completeutterances was determined. Reliability for transcription andcoding was done on 100% of transcripts. Transcript reli-

ability was 96%, and coding reliability ranged from 92% to96% across coding types.


The WABR (Kerstesz, 2006) was administered todetermine presence and severity of aphasia. The CETI(Lomas et al., 1989) questionnaire was used to gather proxyratings of functional communication. The responses to the16 questions are represented on a visual analogue scale,which participants mark fromNot at all able to As able asbefore stroke along a 100-mm line. The higher the line ismarked, the more as able as before the stroke the commu-nication is rated. A range of communication scenarios are

represented, includingcommunicating physical problems suchas aches and pains and being part of a conversation when itis fast and there are a number of people involved.

Additional Testing

The following tests were administered to provide amore comprehensive picture of pretreatment cognitive andlinguistic abilities and potentially to provide insight intoresponses to treatment across participants. They were alsoadministered posttreatment but were not evaluated as out-come measures.

The CLQT (Helm-Estabrooks, 2001) was adminis-tered as a screen for cognitive impairments. All participants

achieved a composite score of a moderate deficit or betterwith a range of abilities across the five subtests (Attention,Memory, Executive Function, Language, and VisuospatialSkills). See Table 4.

Semantic processing of objects and actions was testedusing the pictures in Pyramids and Palm Trees (Howard &

Patterson, 1992) and Kissing and Dancing (Bak & Hodges,2003). For both tests, participants point to one of two itemsthat goes best with the target item (e.g., eyesfor eyeglasses

rather thanears). To reduce testing burden at posttreatment,we did not readminister these tests if participants scoredwithin normal limits at pretesting ( 47 points for each).See Table 4.

The Sentence Comprehension Test from the NAVS(Thompson, 2011) was administered to examine compre-hension of sentences controlled by syntactic complexity. Thetest contains 30 items, including active and passive sentences,subject- and object-extracted wh-questions, and subjectand object relatives. See Table 4 for results.

Treatment Training and Reliability

Three licensed speech-language pathologists withextensive clinical (830 years) and research experience withaphasia conducted the treatment at the Malcom Randall VAMedical Center in Gainesville, Florida, and Brooks Rehab-ilitation in Jacksonville, Florida. Clinicians received com-prehensive training from the first author, which includedreview of a comprehensive treatment manual, videos ofVNeST being delivered, and practice conducting VNeST.They were also given answer sheets and checklists to ensureproper administration of VNeST. Once clinicians exhibitedthorough knowledge and ability, they began treatment withparticipants.

To ensure consistency in execution of the treatmentprotocol, the first author watched 25% of the treatmentsessions live or on video and determined whether each stepwas conducted correctly. Clinicians were made aware of anydiscrepancies between the treatment protocol and execution.Percent reliability was calculated by dividing the totalnumber of steps that were conducted correctly by the totalnumber of steps observed. The treatment protocol wasfollowed with a reliability of 95.3%.

Analysis and Results

A Wilcoxon signed-ranks test was conducted todetermine whether there were significant (p < .05) groupchanges from pre- to posttreatment on all measures and frompretreatment to maintenance (3 months) for sentence probes,NAVS, and discourse. Given the relatively small sample sizeand the diversity of participantslinguistic profiles, we alsoprovide individual participantsscores. In order to interpretindividual changes, we used normative reference samples,when available. For measures without normative references,effect sizes were calculated. Details are provided belowand in tables. Finally, there were two instances of missingdata: no posttreatment WABR or sentence probe results



10/19

Table4.

Pre-andposttreatmentscoresforaphasiaseverity,cognitivescreening

,semanticprocessing,attention,andsen

tencecomprehensionforallparticipants.

Test

P1:AnomicP

2:Anomic

P3:Anomic

P4:Anomic

P5:Anomic

P6:Cond

P7:Cond

P8:Cond

P9:Wern

P10:TCA

P11:TCA

Pre

Post

Pre

Post

Pre

Post

Pre

Post

Pre

Post

Pre

Post

Pre

Pos

t

Pre

Post

Pre

Post

PreP

ost

Pre

Post

Aphasiaseverity:

WABAQa

81.6

93.6

88.1

86.1

81.9

81.1

78.5

84.5

84

92.5

72

82

66.6

75

75.6

DNT

52.9

63.8

81.4

8

2.8

72.1

79.4

Information

8

10

9

8

9

8

8

9

9

10

8

8

8

8

8

DNT

5

7

8

8

6

8

Fluency

5

9

9

8

8

9

5

6

9

9

6

9

7

8

6

DNT

7

7

5

5

4

5

Comprehension

196

200

177

177

159

163

181

189

184

187

196

196

148

172

184

DNT

91

138

192

200

195

196

Repetition

91

90

87

96

90

88

88

92

60

85

63

70

66

68

64

DNT

37

42

97

98

94

88

Naming

90

88

85

86

70

66

84

86

88

94

59

72

43

61

82

DNT

62

68

84

86

69

81

Cognition

CLQTb

Attention

174

Mild

200

WNL

185

W

NL

167

Mild

58

Mod

90

Mod

DNT

DNT

193

WNL

191

WNL

176

WNL

207

WNL

183

WNL

172Mild

198

WNL

197

WNL

160

Mild

182

WNL

201

WNL

191

W

NL

167

WNL

175

WNL

Memory

136

Mod

155

WNL

130

W

NL

124

Mod

94Sev

110

Mod

DNT

DNT

175

WNL

169

WNL

126

Mild

174

WNL

90

Sev

102Sev

149

Mild

168

WNL

77

Sev

81

Sev

138

Mod

149

M

ild

116

Mild

134

Mild

Executive

function

22Mild

29WNL

22

Mild

22

Mild

19

Mod

16

Mod

DNT

DNT

26

WNL

34

WNL

23

WNL

25

WNL

23

Mild

21Mild

27

WNL

30

WNL

18Mod

26WNL

30

WNL

27

W

NL

15

Mild

15

Mild

Language

23Mod

27Mild

22

Mod

20

Sev

21

Mod

21

Mod

DNT

DNT

31

WNL

31

WNL

21Mod

28.5

WNL

18

Sev

20Sev

26Mild

30WNL

17

Sev

19

Sev

25

Mild

26

M

ild

19

Mod

22

Mod

Visuospatial

84

WNL

99

WNL

92

W

NL

87

WNL

46

Mod

47

Mod

DNT

DNT

90

WNL

99

WNL

84

WNL

93

WNL

87

WNL

78Mild

98

WNL

98

WNL

73Mild

83WNL

97

WNL

96

W

NL

81

WNL

82

WNL

Composite

2.8Mild

3.8

WNL

3.4Mild

2.6Mild

1.8Mod

2.0Mod

DNT

DNT

4.0

WNL

4.0

WNL

3.4Mild

4.0

WNL

2.6Mild

2.2Mod

3.6

WNL

4.0

WNL

2.0Mod

2.8Mild

3.4Mild

3.6

W

NL

3.4Mild

3.2

Mild

Semantic

processing

P&Pc

(nouns)

(n=52)

46

50

46

47

40

47

48

DNT

48

51

52

DNT

51

51

50

DNT

47

46

50

D

NT

47

48

K&Dc

(verbs)

(n=52)

48

50

48

DNT

43

42

51

DNT

52

DNT

51

DNT

51

49

49

DNT

43

47

51

D

NT

44

47

Sentence

comprehension:

NAVS

sentences%

97.1

100

62.9

88.6

77.1

68.6

80.0

97.1

91.4

100

91.4

91.4

5.6

44.4

33

28

60

48.6

41.6

2

7.8

93.3

90

Note.

Cond=conduction;Wern=Wernickes;CLQT=CognitiveLinguisticQuickTest;P&P=PyramidsandPalmTreestest;K&D=KissingandDancingtest;WNL=

withinnormallimits;

Mod=moderate;Sev=severe.

aBoldedWABscoreswithimprovemen

t5pointsareconsideredclinicallysignificant(Katz&Wertz,

1997).bBoldedCLQT

subtestsindicateimprovementinseverityratingfrompre-to

posttreatment.cScoresfrom47to52a

reWNLaccordingtotestmaterials.

ManyparticipantswerenottestedduringposttestingiftheyscoredWNLpriortotreatm

ent.



11/19

for P8 because of researcher error and no maintenancediscourse for P4 because of illness.

Research Question 1: Improvement to Sentence

Probes Containing Trained and Untrained Verbs

Sentences containing trained and untrained wordsimproved significantly from pre- to posttreatment, and theseimprovements were maintained 3 months after completion oftreatment. No improvement was observed on the controltask, as hypothesized, at posttreatment or maintenance(p > .05). See Table 2.

During the baseline phase, most participants scoredtoo high on the nonword repetition task to allow for po-tential improvement. Thus, the adjective control task wasused for all but two participants, P6 and P5. For P6, thetwo-syllable nonwords (n= 10) were used from the repeti-tion task. P5, who had a mild anomic aphasia with highconfrontation naming scores on other pretesting measures,

scored too high on both control tasks, so forward andbackward digit span were used for his control.

All participants averaged less than 50% accuracyacross all baseline probes. However, P1 and P4 exhibitedvariability during the baseline phase and had individual data

points equaling 63.6%, thereby leaving less chance for po-tential improvement. A post hoc examination of the post-treatment control results shows that P1 did not exhibitimprovement. P4 showed miminal improvement on thecontrol task by repeating one nonword at posttreatmentthat was not produced during baseline. See sentence probeand control data for all participants in SupplementalTable 2.

Although it was not an a priori research question, wewere interested in what components of the probe sentencesimproved. Virtually all words showed significant improve-ment posttreatment and at maintenance. See Table 2 fordetails.

Effect sizes for trained and untrained sentence probeswere calculated for each participant. We used Cohens dcalculation (Cohen, 1988; d= M2 M1/s, whereM= themean, and s = the standard deviation at pretreatment). If thepretreatment standard deviation was zero, the trained anduntrained scores were pooled to calculate a nonzero standard

deviation. When no existing effect size benchmarks existfor a specific task, it is optimal to estimate effect sizes from

the task itself, if possible (Robey, Schultz, Crawford, &Sinner, 1999). Thus, we used the effect sizes from the par-ticipants in this study to calculate estimated benchmarks. Tocalculate benchmarks for trained sentence probes, we cal-culated the first, second, and third quartiles for all the effect

sizes from the trained sentence probes (Beeson & Robey,2006), and those values (2.3, 3.7, and 5.5) were designated assmall, medium, and large effects. Because using the sameeffect sizes for trained and untrained probes is not advisable(Beeson & Robey, 2006; Robey et al., 1999), we calculatedseparate benchmarks for the untrained sentence probesand got slightly lower cutoffs (1.2, 1.7, and 3.3) for small,medium, and large effects. See Table 5 for effect sizes.

Research Question 2: Confrontation Naming

of Object and Actions on OANB and

in Sentences on NAVS

OANB

There was a significant increase in noun and verb

naming accuracy on OANB. See Table 2. To interpretindividual naming changes, we used the standard deviationsprovided in the OANB manual from a group of cognitivelynormal older adults (there are no comparable measuresfor people with aphasia). A standard deviation of 1.87 wasreported for nouns, 2.40 for verbs. Using two standarddeviations, an increase of 4 or more noun responses or 5 ormore verb responses was used as an indicator of improve-ment. See Table 3.

To further refine our results, we adjusted OANB scoresby removing any words that happened to be trained duringtreatment or seen in trained sentence probes (30 possiblewords: 10 trained verbs [e.g., writing] and 20 corresponding

agents and patients [e.g.,pipe]) to determine whether OANBimprovements were due to training and not necessarily anindication of generalization. Once we removed the overlap-ping items (37 nouns and verbs across participantsnotall participants were trained on the same verbs), we recal-culated percent correct accuracy. The pre- and posttreatmentscores (pre- and posttreatment nouns: 79.75% [12.57] and84.84% [12.80], respectively; pre- and posttreatment verbs:64.68% [18.48] and 73.24% [38.30], respectively) were vir-tually the same as those with all items included, and post-treatment significance was maintained for nouns (p= .016)and verbs (p = .007) (see Table 2).

NAVSA significant increase in the production of sentences

at posttreatment was not observed (p= .086), though therewas an increase in average accuracy from 29% to 42.4%.However, a significant increase was observed from pre-treatment to 3-month maintenance (p = .008). See Table 2for group results.

Similar to the OANB, we wanted to ensure that the

improvement on the NAVS was not due to improvementon items that were trained. Thus, we removed the results ofany sentences that contained a trained item (e.g., shaving,driving; range was 26 across participants) and recalculatedthe results. The results were similar to our original findings

with pre- to posttreatment not being significant (p = .075)despite an increasing trend in percentage correct (pre: 26.88%[24.81]; post: 40.46% [27.05]). Maintenance results weresimilar to the original results (Table 2) as well (37.41% [26.13];accuracy,p = .010).

The NAVS and the measure of complete utterancesused for discourse (discussed below) do not have normalreference measures to interpret individual change aftertreatment. Thus, we calculated effect sizes using Cohens d

(Cohen, 1988) with a pooled group standard deviation.There was more variability in the group pretreatment scoresas compared with individual sentence probe baseline scores,resulting in much lower effect sizes for the group statistics.



12/19

For these measures, Cohens (1988) benchmarks of 0.5 and0.8 as medium and large effects were used. See Table 5 forall effect sizes.

Research Question 3: Lexical Retrieval in Discourse

The primary discourse measure was percentage ofcomplete utterances, which increased significantly from pre-to posttreatment with no change in number of utterances.

At maintenance, percentage of complete utterances did notmaintain significance despite a similar average comparedwith posttreatment. This loss of significance may be dueto lower power at maintenance (n = 9) as compared withposttreatment (n= 11).

In addition to percentage of complete utterances, weexamined potential lexical retrieval improvement at the wordlevel with % CIU. We also evaluated potential changes in

efficiency with CIUs per minute and WPM (Nicholas &Brookshire, 1993). We used the standard error of the meanvalues reported for the aphasia group in Nicholas andBrookshire (1993): % CIU SEM= 2.0; CIUs/min = 4.0;WPM = 6.2. Changes of more than two standard errors of

the mean were used as an indicator of improvement. Nogroup changes were observed for any of these measures. Per-cent pauses and mazes were also evaluated, with no changesobserved. See Tables 2 and 3.

Research Question 4: WABR and CETI

Posttreatment aphasia quotients improved signifi-cantly from an average of 75.91 to 82.12 (p= .017), with

seven of the 10 participants exhibiting clinically significantimprovement (5 points; Katz & Wertz, 1997). See Tables 2and 4. Average scores for the CETI showed a significantincrease from pre- to posttreatment and 3-month mainte-nance. Changes for all participants at both time pointssurpassed the retest standard error of the mean of 5.2 es-tablished during CETI development (Lomas et al., 1989).See Tables 2 and 3.

Discussion

Previous studies with VNeST (Edmonds & Babb,2011; Edmonds et al., 2009) using single-subject design

Table 5.Effect sizes for sentence probes, control task, NAVS sentence production, and complete utterances for all participants.

Posttreatment Maintenance

Sentence probesa Sentence probesa

Pt TR UT Controlb TR UT Controlb

1 6.22*** 4.92*** 0.15 6.22*** 9.39*** 0.922 2.02 3.03** 0.94 3.56* 3.82*** 0.3 2.92* 1.10 0.67 4.75** 1.10 0.114 7.81*** 4.15*** 2.68** 6.22*** 1.23* 1.57*5 3.69** 3.54** 0 3.69** 4.24*** 0.6 8.21*** 1.65* 0.66 3.82** 2.83** 0.617 2.62* 1.23* 0.94 3.83** 0.35 1.23*8 DNT DNT DNT DNT DNT DNT9 1.95 1.91c 0.94 1.10 1.91c 1.23*

10 4.62** 1.43* 0.56 1.40 1.43* 2.6211 0.18 0.45 3.80*** 2.92* 0.67 1.57*

Posttreatment Maintenance

Pt % NAVS Sent Productiond % Complete Utterancesd % NAVS Sent Productiond % Complete Utterancesd

1 0.00 0.25 0.12 0.69**2 0.34 1.03 0 1.053 0.56** 0.85*** 0.60** 1.01***4 1.35*** 0.07 0.23 N/A 5 0.11 1.53*** 0.23 1.17***6 1.69*** 0.22 0.36 0.187 1.58*** 0.01 1.07*** 0.088 0.23 1.51*** 0.71** 0.79**9 0 1.09*** 0.12 1.12***

10 0.56 0.78** 1.19*** 1.08***11 1.35*** 0.21 0.60** 0.11

aBolded items for sentence probes indicatesmall*, medium**, or large*** effect sizes as compared with pretreatment. bControls with boldedeffect sizes did not improve over the highest point at baseline (P7, P9), improved by 1 point (P4), or improved by 2 points (P11; he showed notreatment effect on probes). cWe did not note the medium effect of this value because of apparent inflation of the effect size due to a low standarddeviation calculation.dBolded items for NAVS Sentence Production and % complete utterances indicate medium and large effect sizes comparedwith pretreatment.

*p< .05. **p< .01. ***p < .001.



13/19

reported encouraging results in six participants. The currentgroup study showed significant improvement on productionof sentences containing trained and untrained semanticallyrelated stimuli, replicating previous findings. Improvementon trained verb probes indicates that trained verb networkswere sufficiently activated during treatment to allow gener-

alization to picture description, an untrained task. It washypothesized that such improvement would occur becauseof strengthened connections between the trained verb andrelated agentpatient combinations. Other researchers haveargued that such improvement could potentially be due toincreased awareness about verbs and/or a general strategy tospecify arguments around verbs (e.g., Marshall et al., 1998),improved efficiency in verb retrieval (e.g., Conroy et al.,2006), or, similarly, a freeing up of resources to facilitateimproved sentence retrieval (Linebarger, McCall, & Berndt,2004). Although these explanations are certainly possible,the improvement to untrained semantically related probes

indicates more generalized semantic improvement and,

potentially, generalization of improved structuralsyntacticabilities for simple sentences.

Because VNeST aims to promote widespread lexicalretrieval abilities through activation of a multitude of diverseevent schemas, our outcome measures evaluated lexicalretrieval across a hierarchy of tasks. Group improvementwas observed on both object and action naming on OANB(Druks & Masterson, 2000), indicating improved access toand lexical retrieval of untrained object and action concepts.The majority of participants also exhibited generalizedimprovement to NAVS sentences. These findings, along withthose from previous studies, support the hypothesis thatVNeST may promote generalization of sentence production

abilities beyond treated concepts and tasks (response andstimulus generalization, respectively). Presumably, im-provement beyond trained networks occurred, at least inpart, because of increased lexical retrieval. However, ade-quate sentence frame construction abilities are important forintegrating improved lexical retrieval into sentences (seeWebster & Whitworth, 2012). It is conceivable that VNeSTtasks, such as agent and patient retrieval around a trainedverb and reading aloud the agentverbpatient responses incanonical order, may have strengthened both lexical retrievaland basic sentence construction abilities. Participants whodid not improve on the NAVS may have had impairments

in constructing a sentence frame requiring more explicit

syntactic treatment in addition to the lexical retrieval tasks,as they all improved on OANB naming but not on NAVSsentences.

Connected speech improved from pre- to posttreat-ment on percentage of complete utterances, suggestingimproved integration of relevant content words into a com-plete sentence frame. We also hypothesized improvementon % CIUs, a measure of relevant lexical retrieval. Onepossibility for the lack of % CIU improvement could be atradeoff between improved lexical retrieval within utterancesand increased informativeness overall. However, the find-ings do not support this, as four of the five participantswho improved on % CIUs also improved on percentage of

complete utterances, thereby increasing the proportion ofinformative content while also integrating relevant wordsmore fully into sentence frames. Two additional participantsimproved on percentage of complete utterances but not on% CIUs, and one participant improved only on % CIUs.Thus, about a third of participants showed no improvement

on discourse, a third showed improvement in either infor-mativeness or complete utterances, and a third showedimprovement to both informativeness and sentence produc-tion. Variable improvement on discourse within and acrossparticipants is commonly reported in verb treatmentsstudies (e.g., Edwards, Tucker, & McCann, 2004; Fink et al.,1992; Links et al., 2010; Schneider & Thompson, 2003;Webster et al., 2005) and is not surprising, given that dis-course requires the integration of cognitive (e.g., attention),micro-linguistic skills (e.g., lexical retrieval, syntax), andmacro-linguistic skills (e.g., coherence and cohesion). Thus,the persistent finding of variable outcomes in connectedspeech across studies is likely a reflection of the diversity and

complexity of participant impairment patterns, the scopeand focus of treatment protocols, and the outcome measuresused to evaluate improvement (see Conroy et al., 2006;Webster & Whitworth, 2012). However, the participants whodid not improve on discourse in the current study showedimprovement on some combination of the other generaliza-tion tasks, suggesting a response treatment that did not gen-eralize to or was not captured in our outcome measures. Infuture studies, we plan to refine pretreatment testing measuresto better characterize impairment patterns and diversifydiscourse outcomes to better capture potential improvement.

More global language abilities were measured on theWABR and the CETI. WABR scores improved signifi-

cantly across the group, with 7 of the 10 participants showinga clinically significant improvement (Katz & Wertz, 1997).Increases in the WABR score corresponded to improve-ments in Production and/or Comprehension subtests. For allbut one (P9, who has Wernickes aphasia) of those whoimproved on WABR comprehension, comprehension alsoimproved on NAVS sentences. Although VNeST does notexplicitly target comprehension, this improvement may berelated to participants having to respond to many questions,includingwh-questions, during treatment.

The responses from communication partners on theCETI reflect the perception of improved functional com-munication of treatment participants from pre- to post-

treatment and maintenance. To ensure that communicationpartners would not be influenced by their initial scoring,we did not provide them with their pretreatment responsesat posttreatment or maintenance (which is different fromthe CETI protocol). Unsolicited responses from participantsfamilies also revealed functional communication changes.P4s spouse reported the following regarding her ability toparticipate in her medical care: You guys helped her speechand communication so much. She was talking in completesentences when she was done with it. When she got thediagnosis of [omitted for privacy], she was able to talk to us.She was able to ask the doctors questions and participatein her medical plan. That was so very important to us.See



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additional family comments in Supplemental Table 3. Pleasenote that we acknowledge that proxy and anecdotal reportare not direct evaluations of functional communication.However, combined with the impairment-based results, it isconceivable that participants experienced some improvedcommunication abilities outside of the clinic.

Because VNeST-related improvements are assumed tobe, at least in part, due to activation of a large number ofdiverse event schemas, we evaluated actual responses toverify that participants were, in fact, producing a varietyof responses. We found that participants produced a largenumber of novel agents and patients throughout the courseof treatment (first half: 52 agents and 48 patients: secondhalf: 44 agents and 46 patients). That is, the 52 agents and48 patients produced in the first half of treatment were notproduced again in the second half of treatment, and thosenovel 44 and 46 agents and patients produced in the secondhalf were not produced in the first half. Participants also

produced an additional 46 agents and 46 patients across both

halves of treatment, totaling 145 agents and 138 patientsproduced during treatment.

We also examined the nature of responses and foundthat participants produced a diverse mix of scenarios, in-cludingprototypical(e.g., quarterbackthrowsfootball,womancarriespocketbook, oxpullswagon), personal(e.g.,bossdrivesbig truck, [dogs name]shakestoy, Iread

funny pages, Uncleboilsshrimp, [wifes name]sewscurtains),encyclopedic or world knowledge (e.g.,judgereadsconstitutional law book, hula dancershakeships, state

policeweightrucks, Benjamin Franklinflykite, funeral

directorbrusheshair, Mrs. Clintonwritesbiography), andother (e.g., mad scientistboilhead of Frankenstein, vampires

bite

humans) topics. Thus, treatment on only 10 verbs resultedin activation and production of a wide range of noun con-cepts (not including responses towh-questions).

These data highlight the extent of noun retrievalin VNeST, where the semantics and phonology of nounconcepts are presumably strengthened. However, there isrelatively little production of the trained verb, and thatproduction occurs only after the verb is provided by theclinician. Step 5 of the protocol was added to promoteindependent verb retrieval. However, this task is not entirelyin the spirit of VNeST, which encourages truly independentretrieval of concepts. Further, this step could be achieved

through recruitment of short-term memory. Given the

relative complexity of verb retrieval and the necessity forverb retrieval to construct a sentence (Marshall et al., 1998),more access to phonology (i.e., more production) of verbs inVNeST may be warranted to maximize the potential forgeneralization. Evidence for this is seen in the sentence proberesults, where verbs improved less robustly than the agentsand patients. Future studies will investigate integration ofmore verb production into the protocol.

The improvements reported in the current and pre-vious VNeST studies in (the reduction of) aphasia severity,functional communication (by report), and lexical retrievaland sentence production abilities from single words throughdiscourse are generally more robust than reports from

other verb treatment studies reported in the literature (seeConroy et al., 2006; Webster & Whitworth, 2012). Thefindings also suggest high potential clinical utility of VNeST.We controlled treatment dosage to 35 hr per week over10 weeks, consistent with a traditional aphasia treatmentplan and treated only 10 verbs per participant (fewer than

other verb treatments; e.g., Raymer & Ellsworth, 2002;Wambaugh & Ferguson, 2007; Webster, Morris, & Franklin,2005), though personal and salient responses to verb promptswere encouraged from participants to promote relevanceand interest. Treatment is also low-tech (only pen and paperrequired) and as such is transportable and easily deliveredin multiple settings. In addition, VNeST adapts relativelyeasily to computer and telepractice use (Furnas & Edmonds,2014), providing clinicians and participants with morepotential opportunities for home treatment and practice.Thus, VNeST is easy to administer and potentially efficient,and it offers high potential gains.

Though more research is needed to better define par-

ticipant characteristics, results across VNeST studies sug-gest that participants with moderatesevere to mild aphasiamay be potential candidates. We have not conducted adetailed analysis of outcomes based on aphasia types. How-ever, on the basis of our observations, persons with nonfluent,even agrammatic, aphasia show gains to lexical retrievalof content words in sentence production with mixed im-provement to discourse. Syntax (i.e., word order) in theseparticipants is typically well maintained. It should be notedthat none of the sentence probes are reversible. Because wordorder is highly biased toward animate subjects, partici-pants with potential syntax or mapping impairments may beusing animacy cues to aid production. Persons with fluent

aphasia tend to exhibit more efficient and informativesentence production posttreatment, including reduced cir-cumlocution and reduced use of general terms (e.g., guy,lady) and pronouns. Discourse is also variable in theseparticipants. Finally, we used fairly permissible inclusioncriteria, to allow for relatively broad generalization ofresults. This resulted in a mix of aphasia types, including onlyone person with Wernickes aphasia. In future studies, wewill increase targeted recruitment and perform more detailedtesting to gain more insight into the effects of pretreatmentimpairment patterns and aphasia types.

The development of aphasia treatment protocols caninvolve many Phase 2 studies to narrow potential candidates,

refine treatment and outcome measures, and estimate dos-age (Robey, 2004). Three studies with VNeST have nowtested 17 participants, with overall positive results. However,there are still limitations that need to be addressed inaddition to those we have already mentioned. First, we needobjective measures of functional communication in additionto proxy report. Second, we need to evaluate the effectsof treating verbs with more diverse semantic and syntacticrepresentations, as only a small number of verbs and verbtypes have been trained, largely because of the limitations ofthe sentence probes (e.g., semantically related, imageable,transitive verbs). The process of refining an aphasia treat-ment protocol and understanding who might optimally



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benefit from it is a long process. However, we are committedto that process in order to contribute evidence-based optionsto clinicians who serve persons with aphasia.

Acknowledgments

This work was supported by the Department of VeteransAffairs, Veterans Health Administration, Rehabilitation Researchand Development Grant 1I01RX000563-01 (to Lisa A. Edmonds).We acknowledge the research participants and their families fortheir enthusiasm and motivation throughout. We also extend ourthanks to the following collaborators, research assistants, andclinicians in the Aphasia Lab at the Brain Rehabilitation andResearch Center at the Malcom Randall VA Medical Center andBrooks Rehabilitation in Jacksonville, FL: Sam Wu, Jodi Morgan,Ceil Brooks, Brayleah Kernan, Flo Singletary, and CarolynHanson.

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Appendix(p. 1 of 2)

Verb Network Strengthening Treatment Materials and Protocol

Treatment Materials

Treatment stimuli consisted of the following:

1. 10 cards containing the names of the 10 trained verbs (Verb Set 1) (e.g.,measure)2. 68 cards for each verb containing 34 agents and 34 patients that form 34 pairs related to each verb (e.g., chefsugar,

carpenterlumber, surveyorland,and designerroomfor the verb measure)3. 5 cards containing the following words: who, what, where, when, why4. An average of 25 sentences per verb to be used for semantic judgment.

These sentences spanned four categories: (a) correct (The designer measures the room), (b) inappropriate agent (The infantmeasures the lumber), (c) inappropriate patient (The chef measures the television), and (d) thematic reversal (The room measuresthe designer).

Treatment Protocol

Step 1: The clinician layswhoandwhatcards on the table facing the participant and asksWho can/might verb something/someone?(e.g., Who might drive something?). When the participant cannot produce an agent, he or she is given a semanticor context cue (e.g.,Who might drive for his/her job?). If that cue does not work, then four cards with possible choices areprovided, three cards with foils and one plausible option. The participant reads through the options one at a time (with assistancefrom the clinician, if needed) and chooses the correct response. Once an agent is chosen, then a corresponding patient isrequested (e.g., If the participant said soldier,then the patient might be tank). Participants are encouraged to provide at leastone personal pair (e.g., dadboatfordrive), and responses can change from week to week. (Previous VNeST studies requesteda list of agents or patients and then the corresponding noun, but it is more natural to generate one schema at a time.) In aneffort to promote more participant involvement during this step in the current study, the last six participants wrote their responseafter they said it (rather than the clinician providing the written word). If they were incorrect about the spelling, they were giventhe word to copy (and in the same way no phonemic cues or feedback was given, neither was there any writing feedback[e.g., phoneme to grapheme correspondence]). Examination of probe results revealed no advantage or difference for participantswho wrote responses.

Step 2: The participant reads the triads aloud (e.g., cheffrytomatoes). Morphology or inflection is not required, but it is notdiscouraged if participants use it (e.g., The chef is frying the tomatoes).

Step 3: The participant chooses one scenario (e.g., chef scenario) and answers three wh-questions about it (e.g.,where?[restaurant], when?[before restaurant opens], why? [to make them delicious]) about it. If the participant has difficulty

understanding thewh-questions, then clarification is given (e.g.,Where? What location or place?) See Figure A1.Step 4: The participant decides whether semantic judgment sentences (12 total, 3 from each category) are correct or not.The four categories are (a) correct (The designer measures the room), (b) inappropriate agent (The infant measures the lumber),(c) inappropriate patient (The chef measures the television), and (d) thematic reversal (The room measures the designer).

Step 5: The participant is asked what verb or action he or she has been working on. This step was added to allow oneopportunity for independent verb retrieval.

Step 6: Step 1 is repeated, but no cues are given, and the step is terminated when the participant retrieves three to four pairsor when the participant cannot generate any more pairs, whichever occurs first.



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Appendix(p. 2 of 2)

Verb Network Strengthening Treatment Materials and Protocol

Figure A1. Example of card layout for VNeST steps 1 and 3.



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