The Aphasia Communication Outcome Measure (ACOM) is a patient-reported measure of communicative functioning developed for persons with stroke-induced aphasia. It was motivated by the desire to include the perspective of persons with aphasia in the measurement of treatment outcomes and to apply newly accessible psychometric tools to improve the quality and usefulness of available outcome measures for aphasia. The ACOM was developed within an item response theory framework, and the validity of the score estimates it provides is supported by evidence based on its content, internal structure, relationships with other variables, stability over time, and responsiveness to treatment. This article summarizes the background and motivation for the ACOM, the steps in its initial development, evidence supporting its validity as a measure of patient-reported communication functioning, and current recommendations for interpreting change scores.

Purpose The aim of this study was to examine the effects of dose frequency, an aspect of treatment intensity, on articulation outcomes of sound production treatment (SPT). Method Twelve speakers with apraxia of speech and aphasia received SPT administered with an intense dose frequency and a nonintense/traditional dose frequency (SPT-T). Each participant received both treatment intensities in the context of multiple baseline designs across behaviors. SPT-Intense was provided for 3 hourly sessions per day/3 days per week; and SPT-T for 1 hour-long session per day/3 days per week. Twenty-seven treatment sessions were completed with each phase of treatment. Articulation accuracy was measured in probes of production of treated and untreated words. Results All participants achieved improved articulation of treated words with both intensities; there were no notable differences in magnitude of improvement associated with dose frequency. Positive response generalization to untrained words was found in 21 of 24 treatment applications; the cases of negligible response generalization occurred with SPT-T words. Conclusions Dose frequency (and corresponding total intervention duration) did not appear to impact treatment response for treated items. Disparate response generalization findings for 3 participants in the current study may relate to participant characteristics such as apraxia of speech severity and/or stimuli factors.

Purpose Semantic feature analysis (SFA) is a naming treatment found to improve naming performance for both treated and semantically related untreated words in aphasia. A crucial treatment component is the requirement that patients generate semantic features of treated items. This article examined the role feature generation plays in treatment response to SFA in several ways: It attempted to replicate preliminary findings from Gravier et al. (2018), which found feature generation predicted treatment-related gains for both trained and untrained words. It examined whether feature diversity or the number of features generated in specific categories differentially affected SFA treatment outcomes. Method SFA was administered to 44 participants with chronic aphasia daily for 4 weeks. Treatment was administered to multiple lists sequentially in a multiple-baseline design. Participant-generated features were captured during treatment and coded in terms of feature category, total average number of features generated per trial, and total number of unique features generated per item. Item-level naming accuracy was analyzed using logistic mixed-effects regression models. Results Producing more participant-generated features was found to improve treatment response for trained but not untrained items in SFA, in contrast to Gravier et al. (2018). There was no effect of participant-generated feature diversity or any differential effect of feature category on SFA treatment outcomes. Conclusions Patient-generated features remain a key predictor of direct training effects and overall treatment response in SFA. Aphasia severity was also a significant predictor of treatment outcomes. Future work should focus on identifying potential nonresponders to therapy and explore treatment modifications to improve treatment outcomes for these individuals. Supplemental Material https://doi.org/10.23641/asha.12462596.

Event Abstract Back to Event Structural fragmentation of linguistic brain networks predicts aphasia severity, but not response to treatment. Alexander M. Swiderski1, 2*, Haley Dresang2, William Hula1, 2, Michael W. Dickey1, 2, Fang-Cheng Yeh2, Juan Fernandez-Miranda3 and Patrick J. Doyle1 1 VA Pittsburgh Healthcare System, United States 2 University of Pittsburgh, United States 3 Stanford University, United States Introduction. Network measures [1]–[3] can characterize the complex relationship between brain regions and their connectivity. Research has shown that (dis)organization of language-related neural networks predicts both aphasia severity and treatment response. For example, individuals with more severe neural-network disorganization post-stroke have more severe aphasia than individuals with relatively preserved network organization [4] and measures of temporal-lobe network integration predict patient response to phonological/semantic cueing treatment [5]. Semantic Feature Analysis (SFA; [6]), one of the most well-studied aphasia treatments, improves both naming and overall aphasia severity [7]–[9]. However, it remains unknown how residual neural networks of stroke survivors support response to this treatment. The purpose of this study was to replicate the finding that global network integration predicts aphasia severity [4]-[5] and assess whether temporal-lobe network organization is predictive of response to SFA. Methods. Eighteen participants with aphasia secondary to left-hemisphere stroke > 6 MPO participated. The Comprehensive Aphasia Test (CAT[10]) was administered before treatment to estimate aphasia severity. Diffusion spectrum images were collected with a Siemens 3T Tim Trio Scanner using a 2D EPI diffusion sequence and were reconstructed by q-space diffeomorphic reconstruction [11]. A connectivity matrix was then generated from language specific ROIs (Figure 1) to estimate normalized small worldness (NSW[2]) and average left-temporal betweenness centrality (BC[1]). Estimates of NSW and BC were binary, denoting the presence or absence of connections, but not information regarding connection strengths [3]. Treatment: Participants received intensive SFA treatment (3-3.5 hours/day, 4-5days/week, for 4 weeks) as part of a clinical trial at the VA Pittsburgh Healthcare System. Analysis: CAT Modality Mean T-score served as the aphasia severity outcome variable. The difference in empirical logit-transformed proportion-correct scores between post- and pre-treatment of treated items was the SFA treatment-response outcome variable. Bayesian linear regression and Bayes Factors (BF) were used to analyze the relationship between network measures and behavioral measures. Each regression model was validated with leave one out (LOO) cross-validation [12]. Results. Fit statistics and LOO estimates for each model were excellent (Table 1). NSW was a moderately strong predictor of aphasia severity (r = .48, 95%HDI: 0.01,0.95), with a BF of .99 not favoring the naïve model over the predictor model. The relationships between SFA treatment response and NSW (r = 0.31, 95%HDI: -0.21, 0.84) and left-temporal lobe BC (r = -0.17, 95%HDI: -0.70, 0.37) were not reliably different from zero. Discussion. Community structure of preserved neural networks was predictive of overall aphasia severity [4]-[5], [8]. However, the lack of relationship between the network measures and response to treatment is not consistent with prevailing findings that global and peri-Svlvian network architecture are critical in the promotion of response to treatment for aphasia [5],[8]. A potential cause for these unexpected findings may be related to the variable connection densities of ROIs [3]. Further investigations of response to SFA varying as a function of network measures may benefit from controlling for the size of ROIs and examining ROI-specific estimates of BC. Figure 1 Figure 2 References [1] S. Kintali, “Betweenness Centrality : Algorithms and Lower Bounds,” ArXiv08091906 Cs, Sep. 2008. [2] D. S. Bassett and E. T. Bullmore, “Small-World Brain Networks Revisited,” The Neuroscientist, vol. 23, no. 5, pp. 499–516, Oct. 2017. [3] E. Bullmore and O. Sporns, Complex brain networks: Graph theoretical analysis of structural and functional systems, vol. 10. 2009. [4] B. K. Marebwa, J. Fridriksson, G. Yourganov, L. Feenaughty, C. Rorden, and L. Bonilha, “Chronic post-stroke aphasia severity is determined by fragmentation of residual white matter networks,” Sci. Rep., vol. 7, no. 1, p. 8188, Aug. 2017. [5] L. Bonilha, E. Gleichgerrcht, T. Nesland, C. Rorden, and J. Fridriksson, “Success of Anomia Treatment in Aphasia Is Associated With Preserved Architecture of Global and Left Temporal Lobe Structural Networks,” Neurorehabil. Neural Repair, p. 1545968315593808, Jul. 2015. [6] M. Boyle and C. A. Coelho, “Application of Semantic Feature Analysis as a Treatment for Aphasic Dysnomia,” Am. J. Speech Lang. Pathol., vol. 4, no. 4, p. 94, Nov. 1995. [7] E. A. Efstratiadou, I. Papathanasiou, R. Holland, A. Archonti, and K. Hilari, “A Systematic Review of Semantic Feature Analysis Therapy Studies for Aphasia,” J. Speech Lang. Hear. Res. JSLHR, vol. 61, no. 5, pp. 1261–1278, 17 2018. [8] W. D. Hula et al., “Left Ventral Stream White Matter Connectivity Predicts Response to Semantic Feature Analysis Treatment in Chronic Aphasia,” Front. Hum. Neurosci., 2017. [9] S. J. Oh et al., “Treatment Efficacy of Semantic Feature Analyses for Persons with Aphasia: Evidence from Meta-Analyses,” Commun. Sci. Disord., vol. 21, no. 2, pp. 310–323, Jun. 2016. [10] K. Swinburn, G. Porter, and D. Howard, Comprehensive aphasia test. Hove, UK: Psychology Press, 2004. [11] F. Yeh, V. J. Wedeen, and W. I. Tseng, “Generalized q-Sampling Imaging,” IEEE Trans. Med. Imaging, vol. 29, no. 9, pp. 1626–1635, Sep. 2010. [12] A. Vehtari, A. Gelman, and J. Gabry, “Practical Bayesian model evaluation using leave-one-out cross-validation and WAIC,” Jul. 2015. Keywords: Diffusion Spectrum Imaging (DSI), Aphasia, semantic feature analysis (SFA), Bayesian inference, graph theory Conference: Academy of Aphasia 57th Annual Meeting, Macau, Macao, SAR China, 27 Oct - 29 Oct, 2019. Presentation Type: Poster presentation Topic: Eligible for student award Citation: Swiderski AM, Dresang H, Hula W, Dickey MW, Yeh F, Fernandez-Miranda J and Doyle PJ (2019). Structural fragmentation of linguistic brain networks predicts aphasia severity, but not response to treatment.. Front. Hum. Neurosci. Conference Abstract: Academy of Aphasia 57th Annual Meeting. doi: 10.3389/conf.fnhum.2019.01.00116 Copyright: The abstracts in this collection have not been subject to any Frontiers peer review or checks, and are not endorsed by Frontiers. They are made available through the Frontiers publishing platform as a service to conference organizers and presenters. The copyright in the individual abstracts is owned by the author of each abstract or his/her employer unless otherwise stated. Each abstract, as well as the collection of abstracts, are published under a Creative Commons CC-BY 4.0 (attribution) licence (https://creativecommons.org/licenses/by/4.0/) and may thus be reproduced, translated, adapted and be the subject of derivative works provided the authors and Frontiers are attributed. For Frontiers’ terms and conditions please see https://www.frontiersin.org/legal/terms-and-conditions. Received: 07 May 2019; Published Online: 09 Oct 2019. * Correspondence: Mr. Alexander M Swiderski, VA Pittsburgh Healthcare System, Pittsburgh, Pennsylvania, 15240, United States, Aswiderski@pitt.edu Login Required This action requires you to be registered with Frontiers and logged in. To register or login click here. Abstract Info Abstract The Authors in Frontiers Alexander M Swiderski Haley Dresang William Hula Michael W Dickey Fang-Cheng Yeh Juan Fernandez-Miranda Patrick J Doyle Google Alexander M Swiderski Haley Dresang William Hula Michael W Dickey Fang-Cheng Yeh Juan Fernandez-Miranda Patrick J Doyle Google Scholar Alexander M Swiderski Haley Dresang William Hula Michael W Dickey Fang-Cheng Yeh Juan Fernandez-Miranda Patrick J Doyle PubMed Alexander M Swiderski Haley Dresang William Hula Michael W Dickey Fang-Cheng Yeh Juan Fernandez-Miranda Patrick J Doyle Related Article in Frontiers Google Scholar PubMed Abstract Close Back to top Javascript is disabled. 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Purpose This study investigated the predictive value of practice-related variables—number of treatment trials delivered, total treatment time, average number of trials per hour, and average number of participant-generated features per trial—in response to semantic feature analysis (SFA) treatment. Method SFA was administered to 17 participants with chronic aphasia daily for 4 weeks. Individualized treatment and semantically related probe lists were generated from items that participants were unable to name consistently during baseline testing. Treatment was administered to each list sequentially in a multiple-baseline design. Naming accuracy for treated and untreated items was obtained at study entry, exit, and 1-month follow-up. Results Item-level naming accuracy was analyzed using logistic mixed-effect regression models. The average number of features generated per trial positively predicted naming accuracy for both treated and untreated items, at exit and follow-up. In contrast, total treatment time and average trials per hour did not significantly predict treatment response. The predictive effect of number of treatment trials on naming accuracy trended toward significance at exit, although this relationship held for treated items only. Conclusions These results suggest that the number of patient-generated features may be more strongly associated with SFA-related naming outcomes, particularly generalization and maintenance, than other practice-related variables. Supplemental Materials https://doi.org/10.23641/asha.5734113

PurposeThis investigation was designed to examine the effects of treatment intensity (i.e., dose frequency) on the outcomes of Sound Production Treatment (SPT) for acquired apraxia of speech.MethodFive men with chronic apraxia of speech and aphasia received both intense SPT (3 hr per day/3 days per week) and nonintense/traditional SPT (SPT-T; 1 hr per day/3 days per week) in the context of single-case experimental designs. Each treatment was applied separately to a designated set of experimental words with 1 treatment applied at a time. Twenty-seven treatment sessions were conducted with each phase of treatment. Accuracy of articulation of target sounds within treated and untreated experimental words was measured during the course of the investigation.ResultsAll participants demonstrated improved articulation with both treatment intensities. Better maintenance of gains for treated items was found with SPT-T for 2 participants as measured at an 8-week posttreatment retention probe. Superior maintenance of increased accuracy of production of untreated items was also observed with SPT-T for all participants.ConclusionA less intense (distributed) application of SPT facilitated better maintenance of improved articulatory accuracy for untreated items, and in some cases treated items, than intense SPT.Supplemental Materialshttps://doi.org/10.23641/asha.5734053.

Purpose: The purpose of this study was to evaluate the ability of persons with aphasia, with and without hearing loss, to complete a commonly used open-set word recognition test that requires a verbal response. Furthermore, phonotactic probabilities and neighborhood densities of word recognition errors were assessed to explore potential underlying linguistic complexities that might differentially influence performance among groups. Method: Four groups of adult participants were tested: participants with no brain injury with normal hearing, participants with no brain injury with hearing loss, participants with brain injury with aphasia and normal hearing, and participants with brain injury with aphasia and hearing loss. The Northwestern University Auditory Test No. 6 (NU-6; Tillman & Carhart, 1966) was administered. Those participants who were unable to respond orally (repeating words as heard) were assessed with the Picture Identification Task (Wilson & Antablin, 1980), permitting a picture-pointing response instead. Error patterns from the NU-6 were assessed to determine whether phonotactic probability influenced performance. Results: All participants with no brain injury and 72.7% of the participants with aphasia (24 out of 33) completed the NU-6. Furthermore, all participants who were unable to complete the NU-6 were able to complete the Picture Identification Task. There were significant group differences on NU-6 performance. The 2 groups with normal hearing had significantly higher scores than the 2 groups with hearing loss, but the 2 groups with normal hearing and the 2 groups with hearing loss did not differ from one another, implying that their performance was largely determined by hearing loss rather than by brain injury or aphasia. The neighborhood density, but not phonotactic probabilities, of the participants' errors differed across groups with and without aphasia. Conclusions: Because the vast majority of the participants with aphasia examined could be tested readily using an instrument such as the NU-6, clinicians should not be reticent to use this test if patients are able to repeat single words, but routine use of alternative tests is encouraged for populations of people with brain injuries.

Event Abstract Back to Event Left Ventral Stream White Matter Connectivity Predicts Response to Semantic Feature Analysis Treatment in Chronic Aphasia William Hula1, 2*, Juan Fernandez-Miranda3, Fang-Cheng Yeh3, David Fernandes-Cabral3, Michael W. Dickey1, 2, Michelle Gravier1, Sandip Panesar3, Vijay Rowthu3 and Patrick J. Doyle1, 2 1 VA Pittsburgh Healthcare System, GRECC, United States 2 University of Pittsburgh, Communication Science and Disorders, United States 3 University of Pittsburgh Medical Center, Neurological Surgery, United States INTRODUCTION Identifying predictors of treatment response in aphasia is important for understanding the mechanisms underlying particular interventions and informing treatment candidacy. Aphasia severity is one predictor of outcomes (Dignam et al., 2017; Lambon Ralph, Snell, Fillingham, Conroy, & Sage, 2010; Winans-Mitrik et al., 2014), and gray matter correlates have also been identified (Fridriksson, 2010; Meinzer, Harnish, Conway, & Crosson, 2011; Parkinson, Raymer, Chang, FitzGerald, & Crosson, 2009). However, only one study has reported associations between treatment response and white matter integrity (Meinzer et al., 2010). We used high definition fiber tractography (Fernandez-Miranda et al., 2012) to investigate whether integrity of language-related white matter tracts predicts improvement in overall language function associated with intensive semantic feature analysis treatment for anomia (SFA; Boyle, 2010). Our approach was oriented toward dual-stream neurolinguistic models in which a ventral stream maps sound to meaning, and a dorsal stream maps sound to articulation (Hickok & Poeppel, 2004; Saur et al., 2008). The arcuate and superior longitudinal fasciculi have been proposed as white matter substrates for the dorsal stream (Saur et al., 2008), while the inferior fronto-occipital and uncinate fasciculi have been identified as potential components of the ventral stream (Parker et al., 2005). METHOD Thirteen participants with aphasia due to left-hemisphere stroke received four weeks of intensive SFA as part of a larger ongoing trial. The Comprehensive Aphasia Test (CAT; Swinburn, Porter, & Howard, 2004) was administered pre- and post-treatment. Aphasia severity was estimated using the CAT Modality Mean T-score, and the difference between post-test and pre-test was taken as treatment-related change (ΔCAT). Diffusion spectrum imaging data were acquired pre-treatment via Siemens 3T Tim Trio Scanner using a 2D EPI diffusion sequence and reconstructed by q-space diffeomorphic reconstruction (Yeh, Wedeen, & Tseng, 2010). Orientation distribution functions quantifying directional probability of diffusion were used to calculate quantitative anisotropy (QA) values for dorsal and ventral stream tracts using whole-brain seeding and defined ROIs. Correlations and a path model were estimated using Bayesian methods. Spin distribution functions were also used to construct a connectometry analysis (Yeh, Badre, & Verstynen, 2016) (Figure, Panel B), which shows white matter pathways correlated with ΔCAT. RESULTS The zero-order correlations (95% CIs) between ΔCAT and baseline CAT, left ventral QA, and left dorsal QA were 0.57 (0.04, 0.83), 0.80 (0.35, 0.95), and 0.29 (-0.41, 0.78), respectively. Baseline CAT correlated 0.75 (0.24, 0.94) with ventral QA and 0.29 (-0.42, 0.78) with dorsal QA. Ventral and dorsal QA correlated 0.56 (-0.11, 0.88). A path model regressing ΔCAT on ventral QA with baseline CAT as a mediator (see Figure, Panel B) obtained a robust direct effect and a null indirect effect. The r-squared estimate for ΔCAT was 0.51 (0.11, 0.76). Model fit was acceptable. DISCUSSION These results suggest that the integrity of left-hemisphere ventral pathways may account for the relationship between baseline aphasia severity and treatment-related change, which constrains the interpretation of baseline severity as a prognostic indicator. The results are also consistent with dual-stream models of language and the hypothesized mechanisms underlying response to SFA. Figure 1 Acknowledgements This research was supported by the National Institute on Deafness and Other Communication Disorders of the National Institutes of Health under award number R01DC013803. The authors gratefully acknowledge the assistance of Angela Grzybowski, Rebecca Owens, Alyssa Verlinich, and Emily Boss. The contents of this paper do not represent the views of the Department of Veterans Affairs of the United States Government. References Boyle, M. (2010). Semantic feature analysis treatment for aphasic word retrieval impairments: What’s in a name? Topics in Stroke Rehabilitation, 17(6), 411–422. Dignam, J., Copland, D., O’Brien, K., Burfein, P., Khan, A., & Rodriguez, A. D. (2017). Influence of Cognitive Ability on Therapy Outcomes for Anomia in Adults With Chronic Poststroke Aphasia. Journal of Speech, Language, and Hearing Research, 60(2), 406–421. Fernandez-Miranda, J. C., Pathak, S., Engh, J., Jarbo, K., Verstynen, T., Yeh, F.-C., … Schneider, W. (2012). High-definition fiber tractography of the human brain: neuroanatomical validation and neurosurgical applications. Neurosurgery, 71(2), 430–453. Fridriksson, J. (2010). Preservation and modulation of specific left hemisphere regions is vital for treated recovery from anomia in stroke. Journal of Neuroscience, 30(35), 11558–11564. Hickok, G., & Poeppel, D. (2004). Dorsal and ventral streams: a framework for understanding aspects of the functional anatomy of language. Cognition, 92(1), 67–99. Lambon Ralph, M. A., Snell, C., Fillingham, J. K., Conroy, P., & Sage, K. (2010). Predicting the outcome of anomia therapy for people with aphasia post CVA: Both language and cognitive status are key predictors. Neuropsychological Rehabilitation, 20(2), 289–305. Meinzer, M., Harnish, S., Conway, T., & Crosson, B. (2011). Recent developments in functional and structural imaging of aphasia recovery after stroke. Aphasiology, 25(3), 271–290. Meinzer, M., Mohammadi, S., Kugel, H., Schiffbauer, H., Flöel, A., Albers, J., … Knecht, S. (2010). Integrity of the hippocampus and surrounding white matter is correlated with language training success in aphasia. Neuroimage, 53(1), 283–290. Parker, G. J., Luzzi, S., Alexander, D. C., Wheeler-Kingshott, C. A., Ciccarelli, O., & Ralph, M. A. L. (2005). Lateralization of ventral and dorsal auditory-language pathways in the human brain. Neuroimage, 24(3), 656–666. Parkinson, R. B., Raymer, A., Chang, Y.-L., FitzGerald, D. B., & Crosson, B. (2009). Lesion characteristics related to treatment improvement in object and action naming for patients with chronic aphasia. Brain and Language, 110(2), 61–70. Saur, D., Kreher, B. W., Schnell, S., Kümmerer, D., Kellmeyer, P., Vry, M.-S., … Abel, S. (2008). Ventral and dorsal pathways for language. Proceedings of the National Academy of Sciences, 105(46), 18035–18040. Swinburn, K., Porter, G., & Howard, D. (2004). Comprehensive aphasia test. New York: Psychology Press. Winans-Mitrik, R. L., Hula, W. D., Dickey, M. W., Schumacher, J. G., Swoyer, B., & Doyle, P. J. (2014). Description of an intensive residential aphasia treatment program: Rationale, clinical processes, and outcomes. American Journal of Speech-Language Pathology, 23(2), S330–S342. Yeh, F.-C., Badre, D., & Verstynen, T. (2016). Connectometry: A statistical approach harnessing the analytical potential of the local connectome. Neuroimage, 125, 162–171. Yeh, F.-C., Wedeen, V. J., & Tseng, W.-Y. I. (2010). Generalized-sampling imaging. Medical Imaging, IEEE Transactions on, 29(9), 1626–1635. Keywords: Aphasia, Treatment outcomes, Semantic Feature Analysis, white matter, tractography, connectome mapping Conference: Academy of Aphasia 55th Annual Meeting , Baltimore, United States, 5 Nov - 7 Nov, 2017. Presentation Type: poster or oral Topic: General Submission Citation: Hula W, Fernandez-Miranda J, Yeh F, Fernandes-Cabral D, Dickey MW, Gravier M, Panesar S, Rowthu V and Doyle PJ (2019). Left Ventral Stream White Matter Connectivity Predicts Response to Semantic Feature Analysis Treatment in Chronic Aphasia. Conference Abstract: Academy of Aphasia 55th Annual Meeting . doi: 10.3389/conf.fnhum.2017.223.00038 Copyright: The abstracts in this collection have not been subject to any Frontiers peer review or checks, and are not endorsed by Frontiers. They are made available through the Frontiers publishing platform as a service to conference organizers and presenters. The copyright in the individual abstracts is owned by the author of each abstract or his/her employer unless otherwise stated. Each abstract, as well as the collection of abstracts, are published under a Creative Commons CC-BY 4.0 (attribution) licence (https://creativecommons.org/licenses/by/4.0/) and may thus be reproduced, translated, adapted and be the subject of derivative works provided the authors and Frontiers are attributed. For Frontiers’ terms and conditions please see https://www.frontiersin.org/legal/terms-and-conditions. Received: 02 May 2017; Published Online: 25 Jan 2019. * Correspondence: Dr. William Hula, VA Pittsburgh Healthcare System, GRECC, Pittsburgh, United States, william.hula@va.gov Login Required This action requires you to be registered with Frontiers and logged in. To register or login click here. Abstract Info Abstract The Authors in Frontiers William Hula Juan Fernandez-Miranda Fang-Cheng Yeh David Fernandes-Cabral Michael W Dickey Michelle Gravier Sandip Panesar Vijay Rowthu Patrick J Doyle Google William Hula Juan Fernandez-Miranda Fang-Cheng Yeh David Fernandes-Cabral Michael W Dickey Michelle Gravier Sandip Panesar Vijay Rowthu Patrick J Doyle Google Scholar William Hula Juan Fernandez-Miranda Fang-Cheng Yeh David Fernandes-Cabral Michael W Dickey Michelle Gravier Sandip Panesar Vijay Rowthu Patrick J Doyle PubMed William Hula Juan Fernandez-Miranda Fang-Cheng Yeh David Fernandes-Cabral Michael W Dickey Michelle Gravier Sandip Panesar Vijay Rowthu Patrick J Doyle Related Article in Frontiers Google Scholar PubMed Abstract Close Back to top Javascript is disabled. Please enable Javascript in your browser settings in order to see all the content on this page.

Event Abstract Back to Event Cognitive predictors of response to semantically-based naming treatment in chronic aphasia Michelle Gravier1*, Michael W. Dickey1, 2, William Hula1, 2 and Patrick Doyle1, 2, 3 1 VA Pittsburgh Healthcare System, GRECC, United States 2 University of Pittsburgh, Communication Science and Disorders, United States 3 VA Pittsburgh Healthcare System, Audiology and Speech Pathology, United States INTRODUCTION A growing body of evidence suggests that cognitive factors like executive functioning, visuospatial skills, memory, and attention may be predictive of aphasia treatment outcomes [1-3]. For example, Lambon Ralph and colleagues [1] found that scores on three cognitive measures (Test of Everyday Attention [TEA] Elevator Counting with distraction subtest; Rey Figure copy and delayed-recall subtests) correlated significantly with naming improvements following combined phonemic/orthographic cueing therapy. However, it is unknown whether these measures predict response to other types of treatment, or generalization to untreated items: Lambon-Ralph and colleagues only analyzed treated items. The current study investigated whether cognitive measures were predictive of acquisition and generalization in response to Semantic Feature Analysis (SFA[4]), a commonly-used semantically-focused naming treatment. METHOD Participants: Twenty-six adults with chronic aphasia following single left-hemisphere stroke participated. All participants were right-handed with normal or corrected hearing and vision and no history of other neurological disease. Assessment: Prior to treatment, all participants were given a battery of assessments including: Camden Memory Test[5] Topographical and Word Memory subtests (episodic memory); TEA[6] Elevator Counting with and without Distraction subtests (attention); the Rey Complex Figure Test[7] copy, immediate-, and delayed-recall subtests (visuospatial ability and memory); and the Wisconsin Card Sort Test[8] (problem solving). Treatment: All participants received intensive SFA treatment as part of an ongoing clinical trial. Treatment was administered 4-5 days per week for 4 weeks, in two daily sessions of approximately 120 minutes each. Analysis: The outcome measure was naming-probe accuracy for both treated and semantically-related untreated items at entry (immediately before first treatment session) and exit (morning after final treatment session). Item-level data were analyzed using multilevel generalized linear regression with a logistic link function in R. Each cognitive measure was tested in a separate model including main effects and interactions of cognitive measure, probe time (entry/exit), and item type (treated/untreated). Models also included aphasia severity (Comprehensive Aphasia Test[9] modality mean T-score) as a covariate and random intercepts for items and participants. RESULTS A significant interaction of cognitive measure and probe time was found for the Camden Word Memory Test (p= 0.03) and the TEA with Distraction subtest (p= 0.01), indicating that higher scores on both measures predicted greater entry-to-exit naming improvement, controlling for aphasia severity. However, the three-way interactions with probe time and item type were not significant (p> 0.4), suggesting that the measures were predictive of both acquisition of treated items and generalization to untreated items. No other two- or three-way interactions reached significance. DISCUSSION The finding that TEA significantly predicted SFA treatment response (both acquisition and generalization) replicates and extends previous findings[1]. It also suggests that attention may be a general prerequisite for response to different aphasia-treatment approaches. However, the fact that Rey Figure subtests were not predictive of SFA response suggests that visuospatial skills may be of greater importance for treatments relying primarily on phonemic/orthographic cues[1]. Furthermore, the finding that Camden Word Memory predicted response to SFA, but not to semantic/orthographic cueing[1], suggests that episodic memory for words may be particularly important for semantically-based treatments. Acknowledgements This research was supported by VA Rehabilitation Research and Development Award I01RX000832 to the second and last authors and the VA Pittsburgh Healthcare System Geriatric Research Education and Clinical Center. The contents of this paper do not represent the views of the Department of Veteran’s Affairs of the Unites States Government. References 1. Lambon Ralph, M. A., Snell, C., Fillingham, J. K., Conroy, P., & Sage, K. (2010). Predicting the outcome of anomia therapy for people with aphasia post CVA: Both language and cognitive status are key predictors. Neuropsychological Rehabilitation, 20(2), 289-305. 2. Fillingham, J. K., Sage, K., & Lambon Ralph, M. A. (2006). The treatment of anomia using errorless learning. Neuropsychological Rehabilitation, 16(2), 129-154. 3. Hinckley, J. J., & Carr, T. H. (2001). Differential contributions of cognitive abilities to success in skill-based versus context-based aphasia treatment. Brain and Language, 79(1) 3-6. 4. Boyle, M., & Coelho, C. A. (1995). Application of semantic feature analysis as a treatment for aphasic dysnomia. American Journal of Speech-Language Pathology, 4(4), 94-98. 5. Warrington, E. K. (1996). The Camden Memory Tests. Hove, UK: Psychology Press. 6. Robertson, I. H., Ward, T., Ridgeway, V., & Nimmo-Smith, I. (1994). The Test of Everyday Attention (TEA). Bury St Edmunds, UK: Thames Valley Test Company. 7. Meyers, J. E., & Meyers, K. R. (1995). Rey Complex Figure Test and Recognition Trial. USA: Psychological Assessment Resources, Inc. 8. Grant, D. A., & Berg, E. A. (1993). Wisconsin Card Sorting Test. San Antonio, TX: Psychological Assessment Resources, Inc. 9. Swinburn, K., Porter, G., & Howard, D. (2004). CAT: comprehensive aphasia test. Psychology Press. Keywords: Aphasia, Treatment outcomes, Semantic Feature Analysis, cognitive predictors, generalization Conference: Academy of Aphasia 55th Annual Meeting , Baltimore, United States, 5 Nov - 7 Nov, 2017. Presentation Type: poster presentation Topic: Consider for student award Citation: Gravier M, Dickey MW, Hula W and Doyle P (2019). Cognitive predictors of response to semantically-based naming treatment in chronic aphasia. Conference Abstract: Academy of Aphasia 55th Annual Meeting . doi: 10.3389/conf.fnhum.2017.223.00059 Copyright: The abstracts in this collection have not been subject to any Frontiers peer review or checks, and are not endorsed by Frontiers. They are made available through the Frontiers publishing platform as a service to conference organizers and presenters. The copyright in the individual abstracts is owned by the author of each abstract or his/her employer unless otherwise stated. Each abstract, as well as the collection of abstracts, are published under a Creative Commons CC-BY 4.0 (attribution) licence (https://creativecommons.org/licenses/by/4.0/) and may thus be reproduced, translated, adapted and be the subject of derivative works provided the authors and Frontiers are attributed. For Frontiers’ terms and conditions please see https://www.frontiersin.org/legal/terms-and-conditions. Received: 21 Apr 2017; Published Online: 25 Jan 2019. * Correspondence: Dr. Michelle Gravier, VA Pittsburgh Healthcare System, GRECC, Pittsburgh, PA, United States, michelleferrill@gmail.com Login Required This action requires you to be registered with Frontiers and logged in. To register or login click here. Abstract Info Abstract The Authors in Frontiers Michelle Gravier Michael W Dickey William Hula Patrick Doyle Google Michelle Gravier Michael W Dickey William Hula Patrick Doyle Google Scholar Michelle Gravier Michael W Dickey William Hula Patrick Doyle PubMed Michelle Gravier Michael W Dickey William Hula Patrick Doyle Related Article in Frontiers Google Scholar PubMed Abstract Close Back to top Javascript is disabled. Please enable Javascript in your browser settings in order to see all the content on this page.

Background:Neuropsychological testing is a central aspect of stroke research because it provides critical information about the cognitive-behavioral status of stroke survivors, as well as the diagnosis and treatment of stroke-related disorders. Standard neuropsychological methods rely upon face-to-face interactions between a patient and researcher, which creates geographic and logistical barriers that impede research progress and treatment advances.Introduction:To overcome these barriers, we created a flexible and integrated system for the remote acquisition of neuropsychological data (RAND). The system we developed has a secure architecture that permits collaborative videoconferencing. The system supports shared audiovisual feeds that can provide continuous virtual interaction between a participant and researcher throughout a testing session. Shared presentation and computing controls can be used to deliver auditory and visual test items adapted from standard face-to-face materials or execute computer-based assessments. Spoken and manual responses can be acquired, and the components of the session can be recorded for offline data analysis.Materials and Methods:To evaluate its feasibility, our RAND system was used to administer a speech-language test battery to 16 stroke survivors with a variety of communication, sensory, and motor impairments. The sessions were initiated virtually without prior face-to-face instruction in the RAND technology or test battery.Results:Neuropsychological data were successfully acquired from all participants, including those with limited technology experience, and those with a communication, sensory, or motor impairment. Furthermore, participants indicated a high level of satisfaction with the RAND system and the remote assessment that it permits.Conclusions:The results indicate the feasibility of using the RAND system for virtual home-based neuropsychological assessment without prior face-to-face contact between a participant and researcher. Because our RAND system architecture uses off-the-shelf technology and software, it can be duplicated without specialized expertise or equipment. In sum, our RAND system offers a readily available and promising alternative to face-to-face neuropsychological assessment in stroke research.

PURPOSE The purpose of this study is to investigate the structure and measurement properties of the Aphasia Communication Outcome Measure (ACOM), a patient-reported outcome measure of communicative functioning for persons with aphasia. METHOD Three hundred twenty-nine participants with aphasia responded to 177 items asking about communicative functioning. The data were analyzed using a categorical item factor analysis approach. Validity of ACOM scores on the basis of their convergence with performance-based, clinician-reported, and surrogate-reported assessments of communication was also assessed. RESULTS Fifty-nine items that obtained adequate fit to a modified bifactor measurement model and functioned similarly across several demographic and clinical subgroupings were identified. The factor model estimates were transformed to item response theory graded response model parameters, and the resulting score estimates showed good precision and moderately strong convergence with other measures of communicative ability and functioning. A free software application for administration and scoring of the ACOM item bank is available from the first author. CONCLUSIONS The ACOM provides reliable measurement of patient-reported communicative functioning in aphasia. The results supported the validity of ACOM scores insofar as (a) factor analyses provided support for a coherent measurement model, (b) items functioned similarly across demographic and clinical subgroups, and (c) scores showed good convergence with measures of related constructs.

View addendum:A good outcome for aphasiaThis article is referred to by:Time for a step change? Improving the efficiency, relevance, reliability, validity and transparency of aphasia rehabilitation research through core outcome measures, a common data set and improved reporting criteriaMeasuring outcomes in aphasia research: A review of current practice and an agenda for standardisation

Purpose The purpose of this article is to describe the rationale, clinical processes, and outcomes of an intensive comprehensive aphasia program (ICAP). Method Seventy-three community-dwelling adults with aphasia completed a residentially based ICAP. Participants received 5 hr of daily 1:1 evidence-based cognitive-linguistically oriented aphasia therapy, supplemented with weekly socially oriented and therapeutic group activities over a 23-day treatment course. Standardized measures of aphasia severity and communicative functioning were obtained at baseline, program entry, program exit, and follow-up. Results were analyzed using a Bayesian latent growth curve model with 2 factors representing (a) the initial level and (b) change over time, respectively, for each outcome measure. Results Model parameter estimates showed reliable improvement on all outcome measures between the initial and final assessments. Improvement during the treatment interval was greater than change observed across the baseline interval, and gains were maintained at follow-up on all measures. Conclusions The rationale, clinical processes, and outcomes of a residentially based ICAP have been described. ICAPs differ with respect to treatments delivered, dosing parameters, and outcomes measured. Specifying the defining components of complex interventions, establishing their feasibility, and describing their outcomes are necessary to guide the development of controlled clinical trials.

Computerized adaptive testing (CAT), based on the mathematical framework of item response theory (IRT), has increasingly been implemented in patient reported outcome measures over the past decade (Fries, Bruce, & Cella, 2005). Given a calibrated item pool fit by an appropriate IRT measurement model, a CAT can produce reliable ability estimates more efficiently than traditional paper-and-pencil tests by administering items that are most informative given the examinee’s estimated ability level (Wainer, 2000). As conventional measures employed in the measurement of aphasia were developed under traditional measurement theory, many of these measures are long and inefficient, and are consequently unsuitable for regular clinical care. In addition, these conventional measures often fail to meet the needs of many community-dwelling stroke survivors whose impairments falls outside the range reliably measured by these tests (Doyle et al. 2012). IRT-based and in particular CAT patient reported outcome measures offer the possibility of substantial improvements in measurement technology for persons with aphasia.

To evaluate the dimensionality and measurement invariance of the aphasia communication outcome measure (ACOM), a self- and surrogate-reported measure of communicative functioning in aphasia.

While there have been many advances over the past 40 years, barriers to effective measurement of functional communication skills in adults with aphasia remain. First, the ability range targeted by current assessments frequently falls below the ability level of many community-dwelling stroke survivors (Frattali, 1992). Second, the burden of assessment associated with most functional communication assessments is high, limiting their use in the current healthcare environment (Worrall, 2001).