The influence of bilingualism on the assessment and treatment of an Italian–English speaker with the logopenic variant of PPA

The influence of bilingualism on the assessment and treatment of an Italian–English speaker with the logopenic variant of PPA | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Case Report The influence of bilingualism on the assessment and treatment of an Italian–English speaker with the logopenic variant of PPA Roberta Tomasoni, Gaia C. Santi, Serena Tagliente, Chiara Griseta, and 7 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-7835928/v1 This work is licensed under a CC BY 4.0 License Status: Posted Version 1 posted You are reading this latest preprint version Abstract INTRODUCTION: The impact of bilingualism on speech-language assessment and therapy in Primary Progressive Aphasia (PPA) remains underexplored, despite its suggested influence on disease presentation. METHODS: A bilingual Italian (L1)-English (L2) individual with logopenic-variant PPA completed a bilingual assessment and dual-language Lexical Retrieval Therapy. His bilingual experience was characterized, and therapy outcomes were evaluated within and across languages. RESULTS: Pre-morbidly, the patient was a relatively balanced bilingual with stronger L1 literacy. Following disease onset, L2 showed faster decline, while L1 remained stable. Age of acquisition, dominance, and language use were among the main factors contributing to language maintenance and decline. Therapy yielded equivalent item- specific gains in both languages (L1 d₂ =5.0; L2 d₂ =5.6), asymmetric cross-linguistic transfer to L2 > L1, and modest functional improvements. DISCUSSION: Findings support the relevance of in-depth bilingual assessment and therapy underpinning successful treatment in PPA, unveiling the significance of bilingual experience in shaping treatment outcomes. Neurology Physical Medicine & Rehab Primary progressive aphasia bilingual experience multilingualism cross-linguistic transfer lexical retrieval therapy bilingual speech-language assessment bilingual speech-language intervention Figures Figure 1 Figure 2 Figure 3 1. INTRODUCTION Bilingualism can reshape neurodegenerative trajectories by bolstering cognitive reserve, enhancing executive control and attentional flexibility and has been linked to delayed dementia onset [ 1 ]. Its effects in language-led dementias (PPA) are understudied: retrospective data suggest a ~ 4-year delay in onset of logopenic variant of PPA (lvPPA), with smaller, variable delays in non-fluent (nfvPPA) and semantic PPA (svPPA) [ 2 ]. Existing work in bilingual PPA shows parallel or asymmetric L1/L2 decline, with L1 consistently better preserved than L2, shaped by age of acquisition, premorbid and postmorbid proficiency. However, the lack of systematic language‑ sensitive assessments in both languages is detrimental to capturing patients’ cognitive‑ linguistic strengths and impairments, thereby limiting a comprehensive tracking of the evolution of individual abilities. In the same vein, few studies have examined how bilingualism impacts outcomes in speech and language therapy (SLT) for individuals with this syndrome [ 3 ]. The effectiveness of SLT can depend on the individual's proficiency in each language, with therapy potentially being more successful in the more dominant language. Evidence suggests that bilingual patients may experience comparable or even better outcomes when therapy is appropriately adapted, as skills acquired in one language can sometimes transfer to the other, facilitating recovery or maintenance of language functions across both languages [ 4 – 5 ]. In this case report, we characterized the bilingual profile of an Italian-English lvPPA participant by developing an in-depth functionally equivalent bilingual assessment and a tailored Lexical Retrieval Therapy (LRT) administered in Italian and English. The relationship between bilingual experience with speech and language profile before and after treatment was explored by considering the most relevant bilingual features in shaping L1 and L2 performance. We analyzed whether intervention leads to within- and cross-linguistic improvement in (i) naming; (ii) formal speech and language assessment; (iii) connected-speech production. Based on prior work, we hypothesised that (1) baseline performance would be modulated by age of acquisition, with more preserved L1 abilities [ 6 ]; (2) LRT would yield gains in both L1 and L2, with greater cross-linguistic transfer (CLT) to L1 [ 7 – 9 ] in the context of more stable performance on language assessments for L1 compared to L2 after therapy; and (3) generalisation effects would extend beyond lexico-semantic tasks to functional communication although evidence in PPA is inconsistent [ 10 , 11 ]. 2. METHODS 2.1 Case history In April 2025, a bilingual speaker of Italian and English (L.R.), a right-handed 60-year-old male with eighteen years of formal education, was referred to our Laboratory of Neuropsychology by his family after a 2-year history of progressive language deficits. He was diagnosed with lvPPA in 2024 according to the criteria of Gorno-Tempini et al. (2011) [ 12 ]. Genetic testing identified a heterozygous 6-bp frameshift deletion in exon 6 of the GRN gene (NM_002087.4). A positive family history of early-onset neurodegeneration was reported. Baseline neuropsychological assessment in Italian showed mild impairments in verbal episodic memory and visuospatial skills, with a moderate executive deficit. On the Frontal Behavioural Inventory (FBI) [ 13 ], moderate disorganization and inattention were noted, while activities of daily living remained intact. MRI (3T) demonstrated left-greater-than-right temporo-parietal atrophy (Fig. 1 A). FDG-PET showed hypometabolism in the left posterior temporo-parietal and inferior frontal cortices (Fig. 1 B). 2.2 Speech and language assessment To fully characterise L.R.'s speech and language profile, a structured assessment protocol was administered in Italian and English before and after LRT (Table S1 of Supplementary Material). The protocol assessed articulatory, phonetic– phonological, lexico-semantic, morphosyntactic and discourse domains. When parallel validated tools were not available across both languages, functionally equivalent assessments were adopted (e.g., Screening for Aphasia in Neurodegeneration, SAND [ 14 , 15 ] was compared to the equivalent Mini-Linguistic State Examination, MLSE [ 16 ]). Since one of the patient’s main language difficulties related to naming, developing an ad hoc naming task was essential to directly compare lexical retrieval in the two languages. Thus, an experimental 20-item task was developed in Italian and English. Items consisted of 10 living and 10 non-living nouns, balanced across frequency tiers (low, medium, high) and matched for word length and semantic category. Italian words were selected from the COLFIS database [ 17 ] and English words from Celex [ 18 ]. Frequency groups were defined using log10 of frequency, and translation equivalents were carefully matched across languages. All images were selected from the BOSS database [ 19 ] and the same images were probed in Italian and English. Stimulus lists and lexical characteristics are provided in Supplementary Material (Table S2). Connected speech was elicited with the “Cat Rescue” picture [ 20 ], and self-perceived communication outcomes were assessed with the Communication Outcomes After Stroke (COAST) questionnaire [ 21 ]. 2.3 Bilingual Language Background Bilingual experience was assessed with the Bilingual Language Profile (BLP) [ 22 ] and the Language History Questionnaire (LHQ-3) [ 23 ]. The BLP provided a quantitative index of pre and post-morbid dominance, proficiency, and usage, while the LHQ-3 detailed age of acquisition, frequency of use, self-rated proficiency, and sociolinguistic context. These complementary instruments were selected to provide both quantitative pre and post-morbid dominance indices (BLP) and qualitative developmental context (LHQ-3) necessary for comprehensive bilingual profiling in progressive aphasia. 2.4 Treatment design A single-subject, multiple baseline experimental design was adopted to assess the effect of language intervention on L.R., with a focus on within-language gains and potential CLT. The treatment lasted five weeks, with three one-hour sessions per week and daily home practice. Therapy was delivered in three stages: two weeks in Italian (L1), two weeks in English (L2), and a final review week in both languages to mitigate potential effects of temporal delay between the initial Italian baseline assessment and the subsequent post-therapy evaluations. Sessions were provided remotely using Microsoft Teams by a bilingual speech-language therapist qualified in both the UK and Italy (RT). Therapy was delivered in L1 first to facilitate comprehension of the therapy task. The study design flowchart is presented in Fig. 2 . Therapy followed an adapted LRT following the Lexical Retrieval Cascade Treatment protocol [ 24 , 25 ] including eight steps: (i) naming; (ii) semantic self-cue using semantic prompts; (iii) orthographic cue (first syllable); (iv) reading; (v) writing and repeating; (vi) semantic plausibility judgment; (vii) word recall; (viii) generalisation tasks (i.e., sentence production using the item in context). Daily homework used a copy-and-recall procedure [ 26 ]. In order to select the therapy items, 155 functional items (selected by the participant and his partner) were probed twice in each language at baseline for naming accuracy. From this pool, 40 items were selected to form four sets of five words in each language: two trained and two untreated. Selection prioritized items named incorrectly or inconsistently at baseline and were balanced for word frequency, length, syllable count, and semantic category (e.g., food, hygiene, clothing). Each therapy set was treated for one week, so items were treated during three sessions. In each therapy session, half of all items - five treated and untreated - were elicited to ensure regular exposure. 2.5 Statistical analysis The bilingual experience was derived from the scoring of LHQ3 and BLP questionnaires. To fully characterize the bilingual profile, we also compared baseline speech and language performance at formal testing in Italian and English using a non- parametric unpaired permutation test, with 10,000 Monte Carlo permutations. To evaluate whether treatment was effective within and across the two languages, we evaluated the number of correctly named treated and untreated items post-therapy relative to baseline in both languages. Effects were quantified using Percentage of Non-Overlapping Data (PND) and d₂ effect sizes due to limited data variability [ 27 – 30 ]. Conventionally, PND > 90 is highly effective, < 50 is ineffective; d₂ values of 2.6, 3.9, and 5.8 indicate small, medium, and large effects, respectively. CLT was defined as any improvement obtained at the naming task for treated items in the untreated language (e.g., training “burro di arachidi” in Italian, leading to the correct naming of “peanut butter” in English). We also investigated pre–post changes in Italian and English across formal speech and language testing, performing a paired permutation test (10,000 iterations). To assess generalization effects (i.e., the patient’s lexical retrieval ability in non- naming tasks), two independent raters extracted and qualitatively compared connected-speech measures of lexical density (ratio of nouns/verbs to total words) and syntactic complexity (subordinate clauses per utterance) [ 31 , 32 ] pre and post- treatment. Finally, COAST scores were directly compared before and after therapy to assess self-perceived changes in functional communication. 3. RESULTS 3.1 Bilingual language background L.R. grew up in an Italian–Japanese family, exposed to Italian (L1) from birth and English (L2) from age 4. Italian predominated in family and informal contexts, while English was primarily used in school and work. In adulthood, he acquired oral fluency in French and passive knowledge of Japanese without literacy. At the time that this study was conducted, L.R. did not report any use of French and Japanese. Pre- morbidly, Italian and English oral proficiency was relatively balanced, with stronger literacy in Italian. After symptom onset, English (L2) use declined, with Italian remaining the dominant and less impaired language (Table 1). 3.2 Speech and language characterization At baseline, L.R. exhibited deficits in line with lvPPA. Naming and sentence repetition were predominantly impaired, with English (L2) naming (p = 0.038) and reading (p < 0.001) performances worse than Italian (L1). The patient also showed simplified sentence structure and argument-structure errors, especially in L2 (p = 0.044). Connected speech showed reduced lexical density in L2 compared to L1, with contextual comprehension relatively preserved across languages. 3.3 Treatment Therapy produced item-specific gains in both Italian and English. PND values indicated medium-to-large effect sizes (Italian d₂ = 5.0; English d₂ = 5.6) (see Figure 3a). Untreated items showed no improvement (PND = 0–50). CLT was asymmetric: items treated in English improved when probed in Italian (PND = 100; d₂ = 3.0), but no transfer occurred from Italian to English (PND = 0) (See Figure 3b) . Overall performance was maintained post-treatment. Within-language comparisons showed a trend toward improvement in Italian NAT (p = 0.063) and significant gains in English argument structure production (NAVS; p = 0.008). Despite these improvements, English syntactic abilities showed an overall tendency toward decline (Table 2). Between-language comparisons revealed significantly lower scores in English than Italian for reading (p = 0.005) and morphosyntactic tasks, including NAVS sentence production priming, NAT, and syntax comprehension (all p < 0.05) (Table 3). Qualitatively , at baseline, connected speech was more preserved in Italian than in English for lexical density (35.17 and 14.18, respectively). After therapy, English showed broader improvements, with lexical density nearly doubling (from 14.18 to 30.21) and verb production increasing in both languages (from 32 to 37 in Italian, from 21 to 48 in English). Syntactic complexity diverged: it increased in Italian (greater use of subordinate clauses, scoring from 0.69 to 1) but decreased in English (from 1.36 to 0.64). Finally, COAST scores improved from 62.5% to 73.3%, indicating a modest but subjectively meaningful functional benefit in the following areas: speaking with a familiar interlocutor, a reduction of the impact of language difficulties on family life, social life, and hobbies. 4. DISCUSSION This single-case study shows that an extensive assessment of bilingual experience was crucial since it allowed identifying age of acquisition, dominance, and language use as main factors contributing to language maintenance and decline in our bilingual patient with lvPPA. Moreover, we found that a structured LRT can improve naming of treated items in both languages. Notably, greater gains were observed in L1 because of the cross-linguistic transfer resulting from treatment of L2. The naming improvement came in the context of a stable speech-language profile in both languages. With respect to generalization to other linguistic tasks (i.e., connected speech), L.R. 's lexical density improved, with a greater number of nouns produced in L2 and of verbs retrieved in both languages. In functional communication, measured by the COAST scale, L.R. reported a small but personally significant improvement in interaction with familiar speakers and in social participation. Before treatment, L.R. was more impaired in English (L2) than Italian (L1), which echoes previous reports of faster decline in the less dominant, second-learned language [ 6 ]. This pattern cannot be explained by age of acquisition alone: his pre- morbid dominance, patterns of use, and stronger literacy in Italian appear to have offered greater protection for L1. The drop in his confidence and use of English after symptom onset may have further accelerated L2 decline. These observations align with the Adaptive Control Hypothesis [ 33 ], which posits that bilinguals recruit domain- general cognitive control networks, including prefrontal, anterior cingulate, and basal ganglia circuits, to manage processes of language selection, inhibition, and switching. Neurodegeneration may differentially affect these networks, reducing the efficiency of control and thereby increasing the likelihood that the less practiced or less dominant language becomes more vulnerable to decline [ 34 ]. In L.R. 's case, this may account for both the steeper post-morbid decline in English and the asymmetric transfer, with the weaker language driving maintenance in the stronger one. LRT led to substantial item-specific gains in both languages and CLT from English to Italian. The direction of transfer is noteworthy. The Revised Hierarchical Model [ 35 ], often used to explain CLT in bilingual speakers, predicted stronger influences of L1 on L2. However, studies on bilingual healthy populations revealed that lexical retrieval tasks activate the same semantic networks across languages. When bilinguals named items, they presented with a similar degree of semantic interference in L1 and L2, suggesting that semantic control abilities are independent of the language being utilised [ 36 ]. Accordingly, evidence from post-stroke aphasia [ 37 ] and PPA literature [ 4 ] also highlighted greater CLT from L2 to L1, suggesting that shared semantic representations can facilitate improvement even when the treated language is comparatively less dominant. This is in line with dual-language intervention studies evidencing that targeting the weaker language seems to benefit both L1 and L2, supporting broader communication gains [ 4 , 38 ]. Our results align with the latter findings, suggesting a benefit in training L2 and L1, leading to greater gains in L1 by activating the same shared semantic network. This is further confirmed by a recent meta-analysis by Lee & Faroqi-Shah (2024) [ 38 ], which reported medium-to- large effect sizes for dual-language anomia treatment in aphasia. Our d₂ values (≈ 5.0–5.6) fall squarely in that range, which adds weight to these findings despite the single-case design. Additionally, existing literature suggests that the asymmetry of transfer may be influenced by other factors, including which language is treated and in what order, the relative pre- and post-morbid dominance and proficiency of the two languages, and how frequently and confidently they are used [ 9 , 39 , 40 ]. In PPA, differential patterns of language decline can shape confidence and frequency of use in the more impaired language, which may in turn influence cross-linguistic treatment effects [ 4 ]. Accordingly, in the present case, L.R. 's dominance and frequency of use for L2 presented a slight imbalance compared to L1 pre-morbidly and a significant reduction of frequency, dominance, confidence and use post-morbidly. This might have contributed to the lack of transfer from L1 to L2. Changes in connected speech mirrored the main therapy results: lexical density qualitatively improved in both languages, with particularly striking gains in English. Syntax followed a different trajectory, improving in Italian but declining in English, which likely reflects the combined effects of disease progression and the item-specific focus of therapy. Improvements on argument-structure tasks support this interpretation, as they were indirectly targeted during generalization activities. Healthy controls typically produce picture descriptions that are considerably more content-rich and syntactically more complex than those of individuals with aphasia [ 41 , 42 ]. Against this backdrop, L.R.’s English lexical density improved from ~ 14% at baseline to ~ 30% post-therapy, approaching the level typically seen in healthy discourse. Although direct comparisons for Italian should be interpreted with caution, given the lack of Italian- specific normative data for the “Cat Rescue” connected speech task. Beyond behaviour, there may also be a neurobiological explanation. Luk et al. (2011) [ 43 ] showed that lifelong bilingualism helps maintain white-matter integrity in older adults. This preservation may underlie the resilience we observed in L.R.’s connected speech, particularly when coupled with the modest but meaningful boost in self-reported communication. Taken together, these results suggest that bilingual experience might support language performance both through behavioral strategies and through underlying neuroprotective mechanisms. In addition, these results provide candidate measures derived from connected speech that may prove useful in detecting treatment response in the study of PPA treatment more broadly. Several limitations must be acknowledged. The single-case design, small treatment set, and binary scoring limited our analyses' variability and statistical power. In addition, not all assessments were fully matched across languages. Although this was a pragmatic choice given the lack of equivalent Italian–English tools, international guidelines on bilingual practice [ 44 ] stress the importance of matched assessments and cultural competence, pointing to an area for future improvement in the field more generally. It is also worth situating this report within the broader field. A recent scoping review of bilingual PPA [ 3 ] emphasised the limited systematic evidence on therapy outcomes in this population. This is further compounded by several barriers in the Italian context, where accessing SLT services is challenged by long waiting times, reduced awareness, and limited experience of the SLT role in managing people with PPA, and insufficient funding in providing proactive and long-term services [ 45 ]. By providing detailed assessment and intervention data, our study contributes to filling this gap. It underscores the need for larger, multi-site studies that can explore therapy responsiveness across different bilingual profiles. Incorporating literacy and neuroimaging measures that correlate with therapy's effects will also be necessary. To conclude, this case study illustrates how bilingual experience shapes not only the trajectory of language decline in PPA but also the effectiveness of therapy. In L.R., Italian was preserved longer, likely supported by greater dominance, literacy and use, while English declined steeply yet provided the entry point for cross-language transfer. These findings extend earlier work showing that lifelong bilingualism contributes to cognitive reserve and shapes cognitive profile in the case of neurodegenerative onset [ 46 , 47 ]. They are also consistent with the Adaptive Control Hypothesis [ 33 ], which frames neurodegeneration as a disruption of language-control networks. Integrating these perspectives makes it clear that bilingual profiles must be considered when planning therapy. For aging bilingual populations, cross-linguistic treatment approaches and bilingual service provision are not optional but essential to ensure equitable and effective care. CONSENT STATEMENT Institutional review board approval (Prot. n. 1767/CEL) and informed consent were obtained during enrollment into the study by the participant according to the Declaration of Helsinki. Declarations Written informed consent was obtained from the patient for publication of this clinical case and any accompanying images. CONSENT STATEMENT Institutional review board approval (Prot. n. 1767/CEL) and informed consent were obtained during enrollment into the study by the participant according to the Declaration of Helsinki. ACKNOWLEDGMENTS We would like to thank the participant and his family for participating in this study. SOURCES OF FUNDING The author(s) declare that financial support was received for the research, authorship and/or publication of this article. The study was funded by the European Union–Next- Generation EU - NRRP M6C2 - Investment 2.1 Enhancement and strengthening of biomedical research in the NHS (Project-ID PNRR-MCNT2-2023-12378220). P.B. is an Atlantic Fellow at the Global Brain Health Institute (GBHI). P.B. receives research support from the Italian Ministry of Health and Alzheimer’s Association (GBHI ALZ UK- 22-866347), ML is funded by NIH RF1NS050915, P01AG019724, R01AG080396. SG is funded by the National Institute on Aging of the National Institutes of Health (R01AG080470) and the Alzheimer’s Association Research Grant to Promote Diversity (AARG-D). DISCLOSURES None ACKNOWLEDGMENTS We would like to thank the participant and his family for participating in this study. 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J Speech Lang Hear Res 67(5):1558–1600. 10.1044/2024_JSLHR-23- 00026 Faroqi-Shah Y, Frymark T, Mullen R, Wang B (2010) Effect of treatment for bilingual individuals with aphasia: A systematic review of the evidence. J neurolinguistics 23(4):319–341. 10.1016/j.jneuroling.2010.01.002 Peñaloza C, Marte MJ, Billot A, Kiran S Cross-language interaction during sequential anomia treatment in three languages: Evidence from a trilingual person with aphasia. Cortex 2025 Jun 4. doi.org/10.1016/j.cortex.2025.05.017 Hameister I, Nickels L (2018 Nov) The cat in the tree–using picture descriptions to inform our understanding of conceptualisation in aphasia. Lang Cognition Neurosci 26(10):1296–1314. 10.1080/23273798.2018.1497801 Fergadiotis G, Wright HH (2011) Lexical diversity for adults with and without aphasia across discourse elicitation tasks. Aphasiology 25(11):1414–1430. 10.1080/02687038.2011.603898 Luk G, Bialystok E, Craik FIM, Grady CL (2011) Lifelong bilingualism maintains white matter integrity in older adults. J Neurosci 31(46):16808–16813. 10.1523/JNEUROSCI.4563-11.2011 Pert S, Bradley B (2018) RCSLT Clinical Guidance – Bilingualism: Clinical guidelines for speech and language therapists working with bilingual clients. Royal College of Speech and Language Therapists, London Battista P, Piccininni M, Montembeault M, Messina A, Minafra B, Miller BL, Henry ML, Gorno Tempini ML, Grasso SM (2023) Access, referral, service provision and management of individuals with primary progressive aphasia: A survey of speech– language therapists in Italy. Int J Lang communication disorders 58(4):1046–1060. 10.1111/1460-6984.12843 Bialystok E, Craik FIM, Freedman M (2007) Bilingualism as a protection against the onset of symptoms of dementia. Neuropsychologia 45(2):459–464. 10.1016/j.neuropsychologia.2006.10.009 Alladi S, Bak TH, Shailaja M, Gollahalli D, Rajan A Surampudi B Bilingualism delays the onset (2017) of behavioral but not aphasic forms of frontotemporal dementia. Neuropsychologia 99:207–212. 10.1016/j.neuropsychologia.2017.03.021 Tables Table 1. Bilingual language background. LHQ3 Italian English French Japanese Spoken language Learning 0.975 0.966 0.941 0.27 Written Language Learning 0.962 0.958 0.937 0.266 Spoken Language Proficiency 0.928 0.857 0.714 0.258 Written Language Proficiency 0.714 0.714 0.642 0.285 Spoken Language Usage 0.906 0.5 0.281 0.281 Written Language Usage 0.187 0.062 0.062 Spoken Language Dominance 0.583 0.446 0.338 0.177 Written Language Dominance 0.466 0.45 0.352 0.174 Spoken Language Dominance Ratio 1 0.764 0.579 0.305 Written Language Dominance Ratio 1 0.966 0.755 0.73 BLP Italian English French Japanese Linguistic History 95 77 35 5 Language use before symptoms 30 18 2 0 Language use currently 40 10 0 0 Linguistic competence before symptoms 24 21 13 1 Linguistic competence currently 18 14 10 0 Language attitude 20 17 8 2 Global score before symptoms 175.1 140.8 65.7 9 Global score currently 172.99 116.2 56.7 6.8 Ita- Eng Ita- Fre Eng- Fre Ita- Jap Eng- Jap Dominance Before Symptoms 34.8 109.9 75 166.6 131.7 Dominance Currently 56.7 116.2 59.4 166.1 109.4 Linguistic profile from the LHQ3: Language History Questionnaire (unpublished in Italian) and the BLP: Bilingual Language Profile. Table 2. Within-language comparisons of pre- and post-treatment assessment scores. Speech and Language Test Italian T0 (pre) Italian T1 (post) p- value English T0 (pre) English T1 (post) p- value SAND MLSE - - - Articulation - - - 1/3 3/3 0.500 Naming Naming 9.5/14 7/14 0.625 2/6 3/6 1 Single word Single word comprehension comprehension 12/12 10/12 0.500 2/3 2/3 1 Sentence Sentence comprehension comprehension I 8/8 7/8 1 3/4 2/4 1 Sentence - comprehension II - - - 3/4 2/4 1 Single word Single word repetition repetition 10/10 9/10 1 5/6 4/6 1 Sentence repetition Sentence repetition 2/6 3/6 1 1/4 1/4 1 Reading Reading 15/16 15/16 1 1/10 4/10 0.250 Writing Writing 4/6 4/6 1 N.A N.A Semantic Semantic association association 3/4 3/4 1 4/4 4/4 1 Picture description Picture description 8/8 7/8 1 NAVS ITA NAVS ENG Verb naming Verb naming 18/22 14/22 0.289 14/22 15/22 1 Verb comprehension Verb comprehension 22/22 22/22 1 22/22 22/22 1 Argument structures production Argument structures production 30/32 30/32 1 23/32 31/32 0.008 Sentence production priming Sentence production priming 21/30 25/30 0.388 17/30 14/30 0.506 Sentence comprehension test Sentence comprehension test 24/30 25/30 1 25/30 24/30 1 NAT ITA NAT ENG 16/22 21/22 0.063 18/30 15/30 1 Ad hoc picture naming ITA Ad hoc picture naming ENG 14/20 11/20 0.250 11/20 12/20 1 Pyramids and Palm Trees ITA Pyramids and Palm Trees ENG 14/14 12/14 0.500 10/14 9/14 1 Syntax Comprehension ITA Syntax Comprehension ENG 42/48 46/48 0.219 40/48 38/48 0.774 ENPA - - Words repetition 14/15 15/15 1 Sentences repetition 3/3 3/3 1 Numbers repetition 10/10 9/10 1 WAB Sentences repetition 0.625 86/100 80/100 0.625 CAGI - - Naming 23/48 22/48 1 Comprehension 46/48 48/48 0.500 SAT 72/76 73/76 1 Picture Description ITA Picture Description ENG Total words Total words 188 176 111 220 Total nouns Total nouns 35 31 14 30 Total verbs Total verbs 32 37 21 48 Lexical Density Lexical Density 35.17 31.21 14.18 30.21 Syntactic Complexity Syntactic Complexity 0.69 1 1.36 0.64 Differences within language were derived from paired permutation tests (10,000 Monte Carlo resamples). N.A: non available data; in grey: permutation not performed. Table 3. Between language comparisons pre- and post-LRT. Test n. Item PRE TREATMENT ENG ITA Mean Mean ENG- p value ENG ITA ITA POST TREATMENT Mean Mean ENG- p value ENG ITA ITA SAND MLSE Naming 6 14 0.333 0.857 -0.524 0.038 0.500 0.714 -0.214 0.610 Single word 3 12 0.667 1.000 -0.333 0.203 0.667 0.833 -0.167 1.000 comprehension Sentence 4 8 0.750 1.000 -0.250 0.337 0.500 0.875 -0.375 0.504 comprehension Single word 6 10 0.833 1.000 -0.167 0.381 0.667 0.900 -0.233 0.520 repetition Sentence 4 6 0.250 0.333 -0.083 1.000 0.250 0.500 -0.250 0.577 repetition Reading 10 16 0.100 0.938 -0.838 0.000 0.400 0.938 -0.538 0.005 Semantic 4 4 1.000 0.750 0.250 1.000 1.000 0.750 0.250 1.000 Association Ad hoc naming task 20 20 0.550 0.700 -0.150 0.519 0.600 0.550 0.050 1.000 Pyramids and Palm 14 14 0.714 1.000 -0.286 0.099 0.643 0.857 -0.214 0.390 NAT 30 22 0.600 0.727 -0.127 0.393 0.567 0.955 -0.388 0.002 NAVS Verb naming test 22 22 0.636 0.818 -0.182 0.311 0.682 0.636 0.046 1.000 Verb 22 22 1.000 1.000 0.000 1.000 1.000 1.000 0.000 1.000 comprehension test Argument 32 32 0.719 0.938 -0.219 0.044 0.969 0.938 0.031 1.000 structure production Sentence 30 30 0.567 0.700 -0.133 0.430 0.467 0.833 -0.367 0.006 production priming Sentence 30 30 0.833 0.800 0.033 1.000 0.800 0.833 -0.033 1.000 comprehension test Syntax Comprehension 48 48 0.833 0.875 -0.042 0.770 0.792 0.958 -0.167 0.028 Permutation tests’ results. Mean: proportion of correct answers. ENG-ITA: differences between English and Italian performances, Note: LRT: Lexical Retrieval Therapy; SAND: Screening for Aphasia in Neurodegeneration; NAT: Northwestern Anagram Test Additional Declarations The authors declare no competing interests. Supplementary Files SupplementaryMaterials1.docx Supplementary Material Cite Share Download PDF Status: Posted Version 1 posted You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. As a division of Research Square Company, we’re committed to making research communication faster, fairer, and more useful. We do this by developing innovative software and high quality services for the global research community. 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Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-7835928","acceptedTermsAndConditions":true,"allowDirectSubmit":true,"archivedVersions":[],"articleType":"Case Report","associatedPublications":[],"authors":[{"id":528119554,"identity":"9a42aaa1-d5cf-497d-be01-5cf21bda6fd2","order_by":0,"name":"Roberta Tomasoni","email":"","orcid":"","institution":"Istituti Clinici Scientifici Maugeri IRCCS Bari","correspondingAuthor":false,"prefix":"","firstName":"Roberta","middleName":"","lastName":"Tomasoni","suffix":""},{"id":528119555,"identity":"bc9d8af3-ba37-4292-989d-a1cc0f537ca8","order_by":1,"name":"Gaia C. 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12:42:42","extension":"html","order_by":10,"title":"","display":"","copyAsset":false,"role":"acdc-reference","size":197999,"visible":true,"origin":"","legend":"","description":"","filename":"earlyproof.html","url":"https://assets-eu.researchsquare.com/files/rs-7835928/v1/ed26f92edaa4f30e5099d498.html"},{"id":93777734,"identity":"f7443c76-3af0-4a87-a186-9315dad82576","added_by":"auto","created_at":"2025-10-17 12:42:42","extension":"jpg","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":182436,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eFigure 1. Imaging. (A) \u003c/strong\u003eT1-weighted MRI demonstrates predominantly left-sided atrophy in frontal and temporo-parietal regions. \u003cstrong\u003e(B) \u003c/strong\u003ePET FDG shows hypometabolism (blue areas) in the left posterior temporo-parietal and inferior frontal cortices.\u003c/p\u003e","description":"","filename":"Figure1.jpg","url":"https://assets-eu.researchsquare.com/files/rs-7835928/v1/bddfdaf3035787f0c807b899.jpg"},{"id":93777731,"identity":"b3eeb3dd-4395-4b2a-9fbf-29bc577e5888","added_by":"auto","created_at":"2025-10-17 12:42:42","extension":"jpg","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":98876,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eFigure 2. Study Design Flowchart. \u003c/strong\u003eTwo baseline assessments (n = 40 items) were collected pre-therapy in both Italian and English. The treatment phase included Phase 1 (Italian, 2 weeks, 20 items, 10 treated and 10 untreated) and Phase 2 (English, 2 weeks, 20 items, 10 treated and 10 untreated), followed by a 1-week review of all items in both languages. In the post-therapy phase, all items were probed twice in both languages.\u003c/p\u003e","description":"","filename":"Figure2.jpg","url":"https://assets-eu.researchsquare.com/files/rs-7835928/v1/9224c6b865432f9ce361acab.jpg"},{"id":93777732,"identity":"ce171b3f-04ef-48fd-9fdf-aef9ea3ab597","added_by":"auto","created_at":"2025-10-17 12:42:42","extension":"jpg","order_by":3,"title":"Figure 3","display":"","copyAsset":false,"role":"figure","size":78356,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eFigure 3. Summary of results on treated and untreated items in Italian and English. \u003c/strong\u003eThe figure shows the percentage of non-overlapping data (i.e., the number of times that the patient performed better at post-treatment probing compared to pre- treatment probing). Grey columns refer to the two baseline assessments performed in Italian, and black columns refer to the ones in English.\u003c/p\u003e","description":"","filename":"Figure31.jpg","url":"https://assets-eu.researchsquare.com/files/rs-7835928/v1/d18e8031efa3251ca3c6d459.jpg"},{"id":93780429,"identity":"2826f709-009b-4b46-a547-f38c6ba6e548","added_by":"auto","created_at":"2025-10-17 13:06:42","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":1617031,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-7835928/v1/25c3c765-9bef-4be5-921e-e93a9cbdb758.pdf"},{"id":93777729,"identity":"fa4bbaef-b364-450e-b461-17a719d9d8cf","added_by":"auto","created_at":"2025-10-17 12:42:42","extension":"docx","order_by":1,"title":"","display":"","copyAsset":false,"role":"supplement","size":10236,"visible":true,"origin":"","legend":"\u003cp\u003eSupplementary Material\u003c/p\u003e","description":"","filename":"SupplementaryMaterials1.docx","url":"https://assets-eu.researchsquare.com/files/rs-7835928/v1/f86ae9af2fa52207b70d80ad.docx"}],"financialInterests":"The authors declare no competing interests.","formattedTitle":"\u003cp\u003eThe influence of bilingualism on the assessment and treatment of an Italian–English speaker with the logopenic variant of PPA\u003c/p\u003e","fulltext":[{"header":"1. INTRODUCTION","content":"\u003cp\u003e\u003cdiv class=\"BlockQuote\"\u003e\u003cp\u003eBilingualism can reshape neurodegenerative trajectories by bolstering cognitive reserve, enhancing executive control and attentional flexibility and has been linked to delayed dementia onset [\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e]. Its effects in language-led dementias (PPA) are understudied: retrospective data suggest a\u0026thinsp;~\u0026thinsp;4-year delay in onset of logopenic variant of PPA (lvPPA), with smaller, variable delays in non-fluent (nfvPPA) and semantic PPA (svPPA) [\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e]. Existing work in bilingual PPA shows parallel or asymmetric L1/L2 decline, with L1 consistently better preserved than L2, shaped by age of acquisition, premorbid and postmorbid proficiency. However, the lack of systematic language‑ sensitive assessments in both languages is\u003c/p\u003e\u003cp\u003edetrimental to capturing patients\u0026rsquo; cognitive‑ linguistic strengths and impairments,\u003c/p\u003e\u003cp\u003ethereby limiting a comprehensive tracking of the evolution of individual abilities. In the same vein, few studies have examined how bilingualism impacts outcomes in speech and language therapy (SLT) for individuals with this syndrome [\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e]. The effectiveness of SLT can depend on the individual's proficiency in each language, with therapy potentially being more successful in the more dominant language. Evidence suggests that bilingual patients may experience comparable or even better outcomes when therapy is appropriately adapted, as skills acquired in one language can sometimes transfer to the other, facilitating recovery or maintenance of language functions across both languages [\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e]. In this case report, we characterized the bilingual profile of an Italian-English lvPPA participant by developing an in-depth functionally equivalent bilingual assessment and a tailored Lexical Retrieval Therapy (LRT) administered in Italian and English. The relationship between bilingual experience with speech and language profile before and after treatment was explored by considering the most relevant bilingual features in\u003c/p\u003e\u003cp\u003eshaping L1 and L2 performance. We analyzed whether intervention leads to within- and cross-linguistic improvement in (i) naming; (ii) formal speech and language assessment; (iii) connected-speech production.\u003c/p\u003e\u003cp\u003eBased on prior work, we hypothesised that (1) baseline performance would be modulated by age of acquisition, with more preserved L1 abilities [\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e]; (2) LRT would yield gains in both L1 and L2, with greater cross-linguistic transfer (CLT) to L1 [\u003cspan additionalcitationids=\"CR8\" citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e] in the context of more stable performance on language assessments for L1 compared to L2 after therapy; and (3) generalisation effects would extend beyond lexico-semantic tasks to functional communication although evidence in PPA is inconsistent [\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e, \u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e].\u003c/p\u003e\u003c/div\u003e\u003c/p\u003e"},{"header":"2. METHODS","content":"\u003cdiv id=\"Sec3\" class=\"Section2\"\u003e\u003ch2\u003e2.1 Case history\u003c/h2\u003e\u003cp\u003e\u003cdiv class=\"BlockQuote\"\u003e\u003cp\u003eIn April 2025, a bilingual speaker of Italian and English (L.R.), a right-handed 60-year-old male with eighteen years of formal education, was referred to our Laboratory of Neuropsychology by his family after a 2-year history of progressive language deficits. He was diagnosed with lvPPA in 2024 according to the criteria of Gorno-Tempini et al. (2011) [\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e]. Genetic testing identified a heterozygous 6-bp frameshift deletion in exon 6 of the GRN gene (NM_002087.4). A positive family history of early-onset neurodegeneration was reported. Baseline neuropsychological assessment in Italian showed mild impairments in verbal episodic memory and visuospatial skills, with a moderate executive deficit. On the Frontal Behavioural Inventory (FBI) [\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e], moderate disorganization and inattention were noted, while activities of daily living remained intact. MRI (3T) demonstrated left-greater-than-right\u003c/p\u003e\u003cp\u003etemporo-parietal atrophy (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003eA). FDG-PET showed hypometabolism in the left posterior temporo-parietal and inferior frontal cortices (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003eB).\u003c/p\u003e\u003c/div\u003e\u003c/p\u003e\u003cp\u003e\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec4\" class=\"Section2\"\u003e\u003ch2\u003e2.2 Speech and language assessment\u003c/h2\u003e\u003cp\u003e\u003cdiv class=\"BlockQuote\"\u003e\u003cp\u003eTo fully characterise L.R.'s speech and language profile, a structured assessment protocol was administered in Italian and English before and after LRT (Table S1 of Supplementary Material). The protocol assessed articulatory, phonetic\u0026ndash; phonological, lexico-semantic, morphosyntactic and discourse domains. When parallel validated tools were not available across both languages, functionally equivalent assessments were adopted (e.g., Screening for Aphasia in Neurodegeneration, SAND [\u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e, \u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e] was compared to the equivalent Mini-Linguistic State Examination, MLSE [\u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e]). Since one of the patient\u0026rsquo;s main language difficulties related to naming, developing an ad hoc naming task was essential to directly compare lexical retrieval in the two languages. Thus, an experimental 20-item task was developed in Italian and English. Items consisted of 10 living and 10 non-living nouns, balanced across frequency tiers (low, medium, high) and matched for word length and semantic category. Italian words were selected from the COLFIS database [\u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e] and English words from Celex [\u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e]. Frequency groups were defined using log10 of frequency, and translation equivalents were carefully matched across languages. All images were selected from the BOSS database [\u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e] and the same images were probed in Italian and English. Stimulus lists and lexical characteristics are provided in Supplementary Material (Table S2). Connected speech was elicited with the \u0026ldquo;Cat Rescue\u0026rdquo; picture [\u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e], and self-perceived communication outcomes were assessed with the Communication Outcomes After Stroke (COAST) questionnaire [\u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e].\u003c/p\u003e\u003c/div\u003e\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec5\" class=\"Section2\"\u003e\u003ch2\u003e2.3 Bilingual Language Background\u003c/h2\u003e\u003cp\u003e\u003cdiv class=\"BlockQuote\"\u003e\u003cp\u003eBilingual experience was assessed with the Bilingual Language Profile (BLP)\u003c/p\u003e\u003cp\u003e[\u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e] and the Language History Questionnaire (LHQ-3) [\u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e23\u003c/span\u003e]. The BLP provided a quantitative index of pre and post-morbid dominance, proficiency, and usage, while the LHQ-3 detailed age of acquisition, frequency of use, self-rated proficiency, and sociolinguistic context. These complementary instruments were selected to provide both quantitative pre and post-morbid dominance indices (BLP) and qualitative developmental context (LHQ-3) necessary for comprehensive bilingual profiling in progressive aphasia.\u003c/p\u003e\u003c/div\u003e\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec6\" class=\"Section2\"\u003e\u003ch2\u003e2.4 Treatment design\u003c/h2\u003e\u003cp\u003e\u003cdiv class=\"BlockQuote\"\u003e\u003cp\u003eA single-subject, multiple baseline experimental design was adopted to assess the effect of language intervention on L.R., with a focus on within-language gains and potential CLT.\u003c/p\u003e\u003cp\u003eThe treatment lasted five weeks, with three one-hour sessions per week and daily home practice. Therapy was delivered in three stages: two weeks in Italian (L1), two weeks in English (L2), and a final review week in both languages to mitigate potential effects of temporal delay between the initial Italian baseline assessment and the subsequent post-therapy evaluations. Sessions were provided remotely using Microsoft Teams by a bilingual speech-language therapist qualified in both the UK and Italy (RT). Therapy was delivered in L1 first to facilitate comprehension of the therapy task.\u003c/p\u003e\u003cp\u003eThe study design flowchart is presented in Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003e.\u003c/p\u003e\u003c/div\u003e\u003c/p\u003e\u003cp\u003e\u003c/p\u003e\u003cp\u003eTherapy followed an adapted LRT following the Lexical Retrieval Cascade Treatment protocol [\u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e24\u003c/span\u003e, \u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e25\u003c/span\u003e] including eight steps: (i) naming; (ii) semantic self-cue\u003c/p\u003e\u003cp\u003eusing semantic prompts; (iii) orthographic cue (first syllable); (iv) reading; (v) writing and repeating; (vi) semantic plausibility judgment; (vii) word recall; (viii) generalisation tasks (i.e., sentence production using the item in context). Daily homework used a copy-and-recall procedure [\u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e26\u003c/span\u003e].\u003c/p\u003e\u003cp\u003eIn order to select the therapy items, 155 functional items (selected by the participant and his partner) were probed twice in each language at baseline for naming accuracy. From this pool, 40 items were selected to form four sets of five words in each language: two trained and two untreated. Selection prioritized items named incorrectly or inconsistently at baseline and were balanced for word frequency, length, syllable count, and semantic category (e.g., food, hygiene, clothing). Each therapy set was treated for one week, so items were treated during three sessions. In each therapy session, half of all items - five treated and untreated - were elicited to ensure regular exposure.\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec7\" class=\"Section2\"\u003e\u003ch2\u003e2.5 Statistical analysis\u003c/h2\u003e\u003cp\u003e\u003cdiv class=\"BlockQuote\"\u003e\u003cp\u003eThe bilingual experience was derived from the scoring of LHQ3 and BLP questionnaires. To fully characterize the bilingual profile, we also compared baseline speech and language performance at formal testing in Italian and English using a non- parametric unpaired permutation test, with 10,000 Monte Carlo permutations.\u003c/p\u003e\u003cp\u003eTo evaluate whether treatment was effective within and across the two languages, we evaluated the number of correctly named treated and untreated items post-therapy relative to baseline in both languages. Effects were quantified using Percentage of Non-Overlapping Data (PND) and d₂ effect sizes due to limited data variability [\u003cspan additionalcitationids=\"CR28 CR29\" citationid=\"CR27\" class=\"CitationRef\"\u003e27\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR30\" class=\"CitationRef\"\u003e30\u003c/span\u003e]. Conventionally, PND\u0026thinsp;\u0026gt;\u0026thinsp;90 is highly effective, \u0026lt;\u0026thinsp;50 is ineffective; d₂\u003c/p\u003e\u003cp\u003evalues of 2.6, 3.9, and 5.8 indicate small, medium, and large effects, respectively. CLT was defined as any improvement obtained at the naming task for treated items in the untreated language (e.g., training \u0026ldquo;burro di arachidi\u0026rdquo; in Italian, leading to the correct naming of \u0026ldquo;peanut butter\u0026rdquo; in English). We also investigated pre\u0026ndash;post changes in Italian and English across formal speech and language testing, performing a paired permutation test (10,000 iterations).\u003c/p\u003e\u003cp\u003eTo assess generalization effects (i.e., the patient\u0026rsquo;s lexical retrieval ability in non- naming tasks), two independent raters extracted and qualitatively compared connected-speech measures of lexical density (ratio of nouns/verbs to total words) and syntactic complexity (subordinate clauses per utterance) [\u003cspan citationid=\"CR31\" class=\"CitationRef\"\u003e31\u003c/span\u003e, \u003cspan citationid=\"CR32\" class=\"CitationRef\"\u003e32\u003c/span\u003e] pre and post- treatment.\u003c/p\u003e\u003cp\u003eFinally, COAST scores were directly compared before and after therapy to assess self-perceived changes in functional communication.\u003c/p\u003e\u003c/div\u003e\u003c/p\u003e\u003c/div\u003e"},{"header":"3. RESULTS","content":"\u003ch2\u003e3.1\u0026nbsp;Bilingual\u0026nbsp;language background\u003c/h2\u003e\n\u003cp\u003eL.R. grew up in an Italian–Japanese family, exposed to Italian (L1) from birth and English (L2) from age 4. Italian predominated in family and informal contexts, while English was primarily used in school and work. In adulthood, he acquired oral fluency\u0026nbsp;in\u0026nbsp;French\u0026nbsp;and\u0026nbsp;passive\u0026nbsp;knowledge\u0026nbsp;of\u0026nbsp;Japanese\u0026nbsp;without\u0026nbsp;literacy.\u0026nbsp;At\u0026nbsp;the\u0026nbsp;time\u0026nbsp;that this study was conducted, L.R. did not report any use of French and Japanese. Pre- morbidly, Italian and English oral proficiency was relatively balanced, with stronger literacy in Italian. After symptom onset, English (L2) use declined, with Italian remaining the dominant and less impaired language (Table 1).\u003c/p\u003e\n\u003ch2\u003e3.2\u0026nbsp;Speech\u0026nbsp;and\u0026nbsp;language\u0026nbsp;characterization\u003c/h2\u003e\n\u003cp\u003eAt baseline, L.R. exhibited deficits in line with lvPPA. Naming and sentence repetition were predominantly impaired, with English (L2) naming (p = 0.038) and reading (p \u0026lt; 0.001) performances worse than Italian (L1). The patient also showed simplified sentence structure and argument-structure errors, especially in L2 (p = 0.044).\u0026nbsp;Connected\u0026nbsp;speech\u0026nbsp;showed\u0026nbsp;reduced\u0026nbsp;lexical\u0026nbsp;density\u0026nbsp;in\u0026nbsp;L2\u0026nbsp;compared\u0026nbsp;to\u0026nbsp;L1,\u0026nbsp;with contextual comprehension relatively preserved across languages.\u003c/p\u003e\n\u003ch2\u003e3.3 Treatment\u003c/h2\u003e\n\u003cp\u003eTherapy produced item-specific gains in both Italian and English. PND values indicated medium-to-large effect sizes (Italian d₂ = 5.0; English d₂ = 5.6) (see Figure 3a). Untreated items showed no improvement (PND = 0–50). CLT was asymmetric: items treated in English improved when probed in Italian (PND = 100; d₂ = 3.0), but no transfer occurred from Italian to English (PND = 0) (See Figure 3b)\u003cstrong\u003e.\u0026nbsp;\u003c/strong\u003eOverall performance was maintained post-treatment. Within-language comparisons showed a trend toward improvement in Italian NAT (p = 0.063) and significant gains in English argument structure production (NAVS; p = 0.008). Despite these improvements, English syntactic abilities showed an overall tendency toward decline (Table 2). Between-language comparisons revealed significantly lower scores in English than Italian for reading (p = 0.005) and morphosyntactic tasks, including NAVS sentence production priming, NAT, and syntax comprehension (all p \u0026lt; 0.05) (Table 3). Qualitatively\u003cem\u003e,\u0026nbsp;\u003c/em\u003eat baseline, connected speech was more preserved in Italian than in English for lexical density (35.17 and 14.18, respectively). After therapy, English showed broader improvements, with lexical density nearly doubling (from 14.18 to 30.21) and verb production increasing in both languages (from 32 to 37 in Italian, from\u003c/p\u003e\n\u003cp\u003e21 to 48 in English). Syntactic complexity diverged: it increased in Italian (greater use of subordinate clauses, scoring from 0.69 to 1) but decreased in English (from 1.36 to 0.64). Finally, COAST scores improved from 62.5% to 73.3%, indicating a modest but subjectively meaningful functional benefit in the following areas: speaking with a familiar interlocutor, a reduction of the impact of language difficulties on family life, social life, and hobbies.\u003c/p\u003e"},{"header":"4. DISCUSSION","content":"\u003cp\u003e\u003cdiv class=\"BlockQuote\"\u003e\u003cp\u003eThis single-case study shows that an extensive assessment of bilingual experience was crucial since it allowed identifying age of acquisition, dominance, and language use as main factors contributing to language maintenance and decline in our bilingual patient with lvPPA. Moreover, we found that a structured LRT can improve naming of treated items in both languages. Notably, greater gains were observed in L1 because of the cross-linguistic transfer resulting from treatment of L2. The naming improvement came in the context of a stable speech-language profile in both languages. With respect to generalization to other linguistic tasks (i.e., connected speech), L.R. 's lexical density improved, with a greater number of nouns produced in L2 and of verbs retrieved in both languages. In functional communication, measured by the COAST scale, L.R. reported a small but personally significant improvement in interaction with familiar speakers and in social participation.\u003c/p\u003e\u003cp\u003eBefore treatment, L.R. was more impaired in English (L2) than Italian (L1), which echoes previous reports of faster decline in the less dominant, second-learned language [\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e]. This pattern cannot be explained by age of acquisition alone: his pre- morbid dominance, patterns of use, and stronger literacy in Italian appear to have offered greater protection for L1. The drop in his confidence and use of English after\u003c/p\u003e\u003cp\u003esymptom onset may have further accelerated L2 decline. These observations align with the Adaptive Control Hypothesis [\u003cspan citationid=\"CR33\" class=\"CitationRef\"\u003e33\u003c/span\u003e], which posits that bilinguals recruit domain- general cognitive control networks, including prefrontal, anterior cingulate, and basal ganglia circuits, to manage processes of language selection, inhibition, and switching. Neurodegeneration may differentially affect these networks, reducing the efficiency of control and thereby increasing the likelihood that the less practiced or less dominant language becomes more vulnerable to decline [\u003cspan citationid=\"CR34\" class=\"CitationRef\"\u003e34\u003c/span\u003e]. In L.R. 's case, this may account for both the steeper post-morbid decline in English and the asymmetric transfer, with the weaker language driving maintenance in the stronger one.\u003c/p\u003e\u003cp\u003eLRT led to substantial item-specific gains in both languages and CLT from English to Italian. The direction of transfer is noteworthy. The Revised Hierarchical Model [\u003cspan citationid=\"CR35\" class=\"CitationRef\"\u003e35\u003c/span\u003e], often used to explain CLT in bilingual speakers, predicted stronger influences of L1 on L2. However, studies on bilingual healthy populations revealed that lexical retrieval tasks activate the same semantic networks across languages. When bilinguals named items, they presented with a similar degree of semantic interference in L1 and L2, suggesting that semantic control abilities are independent of the language being utilised [\u003cspan citationid=\"CR36\" class=\"CitationRef\"\u003e36\u003c/span\u003e]. Accordingly, evidence from post-stroke aphasia\u003c/p\u003e\u003cp\u003e[\u003cspan citationid=\"CR37\" class=\"CitationRef\"\u003e37\u003c/span\u003e] and PPA literature [\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e] also highlighted greater CLT from L2 to L1, suggesting that shared semantic representations can facilitate improvement even when the treated language is comparatively less dominant. This is in line with dual-language intervention studies evidencing that targeting the weaker language seems to benefit both L1 and L2, supporting broader communication gains [\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e, \u003cspan citationid=\"CR38\" class=\"CitationRef\"\u003e38\u003c/span\u003e]. Our results align with the latter findings, suggesting a benefit in training L2 and L1, leading to greater gains in L1 by activating the same shared semantic network. This is further confirmed by a recent meta-analysis by Lee \u0026amp; Faroqi-Shah (2024) [\u003cspan citationid=\"CR38\" class=\"CitationRef\"\u003e38\u003c/span\u003e], which reported medium-to-\u003c/p\u003e\u003cp\u003elarge effect sizes for dual-language anomia treatment in aphasia. Our d₂ values (\u0026asymp;\u0026thinsp;5.0\u0026ndash;5.6) fall squarely in that range, which adds weight to these findings despite the single-case design.\u003c/p\u003e\u003cp\u003eAdditionally, existing literature suggests that the asymmetry of transfer may be influenced by other factors, including which language is treated and in what order, the relative pre- and post-morbid dominance and proficiency of the two languages, and how frequently and confidently they are used [\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e, \u003cspan citationid=\"CR39\" class=\"CitationRef\"\u003e39\u003c/span\u003e, \u003cspan citationid=\"CR40\" class=\"CitationRef\"\u003e40\u003c/span\u003e]. In PPA, differential patterns of language decline can shape confidence and frequency of use in the more impaired language, which may in turn influence cross-linguistic treatment effects [\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e]. Accordingly, in the present case, L.R. 's dominance and frequency of use for L2 presented a slight imbalance compared to L1 pre-morbidly and a significant reduction of frequency, dominance, confidence and use post-morbidly. This might have contributed to the lack of transfer from L1 to L2.\u003c/p\u003e\u003cp\u003eChanges in connected speech mirrored the main therapy results: lexical density qualitatively improved in both languages, with particularly striking gains in English. Syntax followed a different trajectory, improving in Italian but declining in English, which likely reflects the combined effects of disease progression and the item-specific focus of therapy. Improvements on argument-structure tasks support this interpretation, as they were indirectly targeted during generalization activities. Healthy controls typically produce picture descriptions that are considerably more content-rich and syntactically more complex than those of individuals with aphasia [\u003cspan citationid=\"CR41\" class=\"CitationRef\"\u003e41\u003c/span\u003e, \u003cspan citationid=\"CR42\" class=\"CitationRef\"\u003e42\u003c/span\u003e]. Against this backdrop, L.R.\u0026rsquo;s English lexical density improved from ~\u0026thinsp;14% at baseline to ~\u0026thinsp;30% post-therapy, approaching the level typically seen in healthy discourse. Although direct comparisons for Italian should be interpreted with caution, given the lack of Italian-\u003c/p\u003e\u003cp\u003especific normative data for the \u0026ldquo;Cat Rescue\u0026rdquo; connected speech task. Beyond behaviour, there may also be a neurobiological explanation. Luk et al. (2011) [\u003cspan citationid=\"CR43\" class=\"CitationRef\"\u003e43\u003c/span\u003e] showed that lifelong bilingualism helps maintain white-matter integrity in older adults. This preservation may underlie the resilience we observed in L.R.\u0026rsquo;s connected speech, particularly when coupled with the modest but meaningful boost in self-reported communication. Taken together, these results suggest that bilingual experience might support language performance both through behavioral strategies and through underlying neuroprotective mechanisms. In addition, these results provide candidate measures derived from connected speech that may prove useful in detecting treatment response in the study of PPA treatment more broadly.\u003c/p\u003e\u003cp\u003eSeveral limitations must be acknowledged. The single-case design, small treatment set, and binary scoring limited our analyses' variability and statistical power. In addition, not all assessments were fully matched across languages. Although this was a pragmatic choice given the lack of equivalent Italian\u0026ndash;English tools, international guidelines on bilingual practice [\u003cspan citationid=\"CR44\" class=\"CitationRef\"\u003e44\u003c/span\u003e] stress the importance of matched assessments and cultural competence, pointing to an area for future improvement in the field more generally.\u003c/p\u003e\u003cp\u003eIt is also worth situating this report within the broader field. A recent scoping review of bilingual PPA [\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e] emphasised the limited systematic evidence on therapy outcomes in this population. This is further compounded by several barriers in the Italian context, where accessing SLT services is challenged by long waiting times, reduced awareness, and limited experience of the SLT role in managing people with PPA, and insufficient funding in providing proactive and long-term services [\u003cspan citationid=\"CR45\" class=\"CitationRef\"\u003e45\u003c/span\u003e]. By providing detailed assessment and intervention data, our study contributes to filling\u003c/p\u003e\u003cp\u003ethis gap. It underscores the need for larger, multi-site studies that can explore therapy responsiveness across different bilingual profiles. Incorporating literacy and neuroimaging measures that correlate with therapy's effects will also be necessary.\u003c/p\u003e\u003cp\u003eTo conclude, this case study illustrates how bilingual experience shapes not only the trajectory of language decline in PPA but also the effectiveness of therapy. In L.R., Italian was preserved longer, likely supported by greater dominance, literacy and use, while English declined steeply yet provided the entry point for cross-language transfer. These findings extend earlier work showing that lifelong bilingualism contributes to cognitive reserve and shapes cognitive profile in the case of neurodegenerative onset [\u003cspan citationid=\"CR46\" class=\"CitationRef\"\u003e46\u003c/span\u003e, \u003cspan citationid=\"CR47\" class=\"CitationRef\"\u003e47\u003c/span\u003e]. They are also consistent with the Adaptive Control Hypothesis [\u003cspan citationid=\"CR33\" class=\"CitationRef\"\u003e33\u003c/span\u003e], which frames neurodegeneration as a disruption of language-control networks. Integrating these perspectives makes it clear that bilingual profiles must be considered when planning therapy. For aging bilingual populations, cross-linguistic treatment approaches and bilingual service provision are not optional but essential to ensure equitable and effective care.\u003c/p\u003e\u003cp\u003e\u003cb\u003eCONSENT STATEMENT\u003c/b\u003e\u003c/p\u003e\u003cp\u003eInstitutional review board approval (Prot. n. 1767/CEL) and informed consent were obtained during enrollment into the study by the participant according to the Declaration of Helsinki.\u003c/p\u003e\u003c/div\u003e\u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003eWritten informed consent was obtained from the patient for publication of this clinical case and any accompanying images.\u003c/p\u003e\u003cp\u003eCONSENT STATEMENT\u003c/p\u003e\n\u003cp\u003eInstitutional review board approval (Prot. n. 1767/CEL) and informed consent were obtained during enrollment into the study by the participant according to the Declaration of Helsinki.\u003c/p\u003e\n\u003cp\u003eACKNOWLEDGMENTS\u003c/p\u003e\n\u003cp\u003eWe\u0026nbsp;would\u0026nbsp;like\u0026nbsp;to\u0026nbsp;thank\u0026nbsp;the\u0026nbsp;participant\u0026nbsp;and\u0026nbsp;his\u0026nbsp;family\u0026nbsp;for\u0026nbsp;participating\u0026nbsp;in\u0026nbsp;this\u0026nbsp;study.\u003c/p\u003e\n\u003cp\u003eSOURCES\u0026nbsp;OF FUNDING\u003c/p\u003e\n\u003cp\u003eThe\u0026nbsp;author(s)\u0026nbsp;declare\u0026nbsp;that\u0026nbsp;financial\u0026nbsp;support\u0026nbsp;was\u0026nbsp;received\u0026nbsp;for\u0026nbsp;the\u0026nbsp;research,\u0026nbsp;authorship and/or publication of this article. The study was funded by the European Union\u0026ndash;Next- Generation EU - NRRP M6C2 - Investment 2.1 Enhancement and strengthening of biomedical research in the NHS (Project-ID PNRR-MCNT2-2023-12378220). P.B. is an Atlantic Fellow at the Global Brain Health Institute (GBHI). P.B. receives research support\u0026nbsp;from\u0026nbsp;the\u0026nbsp;Italian\u0026nbsp;Ministry\u0026nbsp;of\u0026nbsp;Health\u0026nbsp;and\u0026nbsp;Alzheimer\u0026rsquo;s\u0026nbsp;Association\u0026nbsp;(GBHI\u0026nbsp;ALZ\u0026nbsp;UK- 22-866347),\u0026nbsp;ML\u0026nbsp;is\u0026nbsp;funded\u0026nbsp;by\u0026nbsp;NIH RF1NS050915, P01AG019724, R01AG080396. SG\u003c/p\u003e\n\u003cp\u003eis funded by the National Institute on Aging of the National Institutes of Health (R01AG080470) and the Alzheimer\u0026rsquo;s Association Research Grant to Promote Diversity (AARG-D).\u003c/p\u003e\n\u003cp\u003eDISCLOSURES\u003c/p\u003e\n\u003cp\u003eNone\u003c/p\u003e\u003cp\u003eACKNOWLEDGMENTS\u003c/p\u003e\u003cp\u003eWe would like to thank the participant and his family for participating in this study.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\u003cli\u003e\u003cspan\u003eAlladi S, Bak TH, Duggirala V, Surampudi B, Shailaja M, Shukla AK et al (2013) Bilingualism delays age at onset of dementia, independent of education and immigration status. 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Neuropsychologia 99:207\u0026ndash;212. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1016/j.neuropsychologia.2017.03.021\u003c/span\u003e\u003cspan address=\"10.1016/j.neuropsychologia.2017.03.021\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e\u003c/ol\u003e"},{"header":"Tables","content":"\u003cp\u003e\u003cstrong\u003eTable\u0026nbsp;1.\u0026nbsp;Bilingual\u0026nbsp;language background.\u003c/strong\u003e\u003c/p\u003e\n\u003ctable border=\"0\" cellspacing=\"0\" cellpadding=\"0\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eLHQ3\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eItalian\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eEnglish\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eFrench\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eJapanese\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eSpoken\u0026nbsp;language Learning\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e0.975\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e0.966\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e0.941\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" valign=\"top\"\u003e\n \u003cp\u003e0.27\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eWritten\u0026nbsp;Language Learning\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e0.962\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e0.958\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e0.937\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" valign=\"top\"\u003e\n \u003cp\u003e0.266\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eSpoken\u0026nbsp;Language Proficiency\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e0.928\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e0.857\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e0.714\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" valign=\"top\"\u003e\n \u003cp\u003e0.258\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eWritten\u0026nbsp;Language Proficiency\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e0.714\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e0.714\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e0.642\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" valign=\"top\"\u003e\n \u003cp\u003e0.285\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eSpoken\u0026nbsp;Language Usage\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e0.906\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e0.5\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e0.281\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" valign=\"top\"\u003e\n \u003cp\u003e0.281\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eWritten\u0026nbsp;Language Usage\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e0.187\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e0.062\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" valign=\"top\"\u003e\n \u003cp\u003e0.062\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eSpoken\u0026nbsp;Language Dominance\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e0.583\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e0.446\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e0.338\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" valign=\"top\"\u003e\n \u003cp\u003e0.177\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eWritten\u0026nbsp;Language Dominance\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e0.466\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e0.45\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e0.352\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" valign=\"top\"\u003e\n \u003cp\u003e0.174\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eSpoken\u0026nbsp;Language\u0026nbsp;Dominance Ratio\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e0.764\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e0.579\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" valign=\"top\"\u003e\n \u003cp\u003e0.305\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eWritten\u0026nbsp;Language\u0026nbsp;Dominance Ratio\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e0.966\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e0.755\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" valign=\"top\"\u003e\n \u003cp\u003e0.73\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eBLP\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eItalian\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eEnglish\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eFrench\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eJapanese\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eLinguistic\u0026nbsp;History\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e95\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e77\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e35\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" valign=\"top\"\u003e\n \u003cp\u003e5\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eLanguage\u0026nbsp;use\u0026nbsp;before symptoms\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e30\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e18\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" valign=\"top\"\u003e\n \u003cp\u003e0\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eLanguage\u0026nbsp;use currently\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e40\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e10\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" valign=\"top\"\u003e\n \u003cp\u003e0\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eLinguistic\u0026nbsp;competence\u0026nbsp;before symptoms\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e24\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e21\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e13\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" valign=\"top\"\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eLinguistic\u0026nbsp;competence currently\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e18\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e14\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e10\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eLanguage attitude\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e20\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e17\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e8\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eGlobal\u0026nbsp;score\u0026nbsp;before symptoms\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e175.1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e140.8\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e65.7\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e9\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eGlobal\u0026nbsp;score currently\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e172.99\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e116.2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e56.7\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e6.8\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eIta-\u003c/strong\u003e\u003cstrong\u003eEng\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eIta-\u003c/strong\u003e\u003cstrong\u003eFre\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eEng-\u003c/strong\u003e\u003cstrong\u003eFre\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eIta-\u003c/strong\u003e\u003cstrong\u003eJap\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eEng-\u003c/strong\u003e\u003cstrong\u003eJap\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eDominance\u0026nbsp;Before Symptoms\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e34.8\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e109.9\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e75\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e166.6\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e131.7\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eDominance Currently\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e56.7\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e116.2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e59.4\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e166.1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e109.4\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003eLinguistic profile from the LHQ3: Language History Questionnaire (unpublished in Italian) and the BLP: Bilingual Language Profile.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eTable\u0026nbsp;2.\u0026nbsp;Within-language\u0026nbsp;comparisons\u0026nbsp;of\u0026nbsp;pre-\u0026nbsp;and\u0026nbsp;post-treatment\u0026nbsp;assessment scores.\u003c/strong\u003e\u003c/p\u003e\n\u003ctable border=\"0\" cellspacing=\"0\" cellpadding=\"0\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eSpeech and\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eLanguage Test\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eItalian T0\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003e(pre)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eItalian T1\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003e(post)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003ep-\u003c/strong\u003e\u003cstrong\u003evalue\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eEnglish T0\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003e(pre)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eEnglish T1\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003e(post)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003ep-\u003c/strong\u003e\u003cstrong\u003evalue\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eSAND\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eMLSE\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e-\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e-\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003e-\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" valign=\"top\"\u003e\n \u003cp\u003e\u003cem\u003eArticulation\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e-\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e-\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e-\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e1/3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e3/3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e0.500\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u003cem\u003eNaming\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" valign=\"top\"\u003e\n \u003cp\u003e\u003cem\u003eNaming\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e9.5/14\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e7/14\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e0.625\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e2/6\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e3/6\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u003cem\u003eSingle word\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" valign=\"top\"\u003e\n \u003cp\u003e\u003cem\u003eSingle word\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u003cem\u003ecomprehension\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" valign=\"top\"\u003e\n \u003cp\u003e\u003cem\u003ecomprehension\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e12/12\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e10/12\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e0.500\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e2/3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e2/3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u003cem\u003eSentence\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" valign=\"top\"\u003e\n \u003cp\u003e\u003cem\u003eSentence\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u003cem\u003ecomprehension\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" valign=\"top\"\u003e\n \u003cp\u003e\u003cem\u003ecomprehension I\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e8/8\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e7/8\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e3/4\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e2/4\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd colspan=\"2\" valign=\"top\"\u003e\n \u003cp\u003e\u003cem\u003eSentence\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"2\" valign=\"top\"\u003e\n \u003cp\u003e-\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u003cem\u003ecomprehension II\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e-\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e-\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e-\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e3/4\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e2/4\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"2\" valign=\"top\"\u003e\n \u003cp\u003e\u003cem\u003eSingle word\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u003cem\u003eSingle word\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"2\" valign=\"top\"\u003e\n \u003cp\u003e\u003cem\u003erepetition\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u003cem\u003erepetition\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e10/10\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e9/10\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e5/6\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e4/6\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"2\" valign=\"top\"\u003e\n \u003cp\u003e\u003cem\u003eSentence repetition\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u003cem\u003eSentence repetition\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e2/6\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e3/6\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e1/4\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e1/4\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"2\" valign=\"top\"\u003e\n \u003cp\u003e\u003cem\u003eReading\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u003cem\u003eReading\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e15/16\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e15/16\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e1/10\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e4/10\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e0.250\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"2\" valign=\"top\"\u003e\n \u003cp\u003e\u003cem\u003eWriting\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u003cem\u003eWriting\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e4/6\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e4/6\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eN.A\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eN.A\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"2\" valign=\"top\"\u003e\n \u003cp\u003e\u003cem\u003eSemantic\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u003cem\u003eSemantic\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"2\" valign=\"top\"\u003e\n \u003cp\u003e\u003cem\u003eassociation\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u003cem\u003eassociation\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e3/4\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e3/4\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e4/4\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e4/4\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"2\" valign=\"top\"\u003e\n \u003cp\u003e\u003cem\u003ePicture description\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u003cem\u003ePicture description\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e8/8\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e7/8\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"2\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eNAVS ITA\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eNAVS ENG\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003ctable border=\"0\" cellspacing=\"0\" cellpadding=\"0\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u003cem\u003eVerb naming\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u003cem\u003eVerb naming\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e18/22\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e14/22\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e0.289\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e14/22\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e15/22\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u003cem\u003eVerb\u0026nbsp;\u003c/em\u003e\u003cem\u003ecomprehension\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u003cem\u003eVerb\u0026nbsp;\u003c/em\u003e\u003cem\u003ecomprehension\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e22/22\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e22/22\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e22/22\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e22/22\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u003cem\u003eArgument structures production\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u003cem\u003eArgument structures production\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e30/32\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e30/32\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e23/32\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e31/32\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u003cem\u003e0.008\u003c/em\u003e\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u003cem\u003eSentence\u0026nbsp;\u003c/em\u003e\u003cem\u003eproduction\u0026nbsp;priming\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u003cem\u003eSentence\u0026nbsp;\u003c/em\u003e\u003cem\u003eproduction\u0026nbsp;priming\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e21/30\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e25/30\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e0.388\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e17/30\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e14/30\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e0.506\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u003cem\u003eSentence comprehension\u0026nbsp;\u003c/em\u003e\u003cem\u003etest\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u003cem\u003eSentence comprehension\u0026nbsp;\u003c/em\u003e\u003cem\u003etest\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e24/30\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e25/30\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e25/30\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e24/30\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eNAT ITA\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eNAT ENG\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e16/22\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e21/22\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e0.063\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e18/30\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e15/30\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eAd\u0026nbsp;hoc\u0026nbsp;picture naming ITA\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eAd\u0026nbsp;hoc\u0026nbsp;picture naming ENG\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e14/20\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e11/20\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e0.250\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e11/20\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e12/20\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003ePyramids and Palm\u0026nbsp;Trees\u0026nbsp;ITA\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003ePyramids and Palm\u0026nbsp;Trees\u0026nbsp;ENG\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e14/14\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e12/14\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e0.500\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e10/14\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e9/14\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eSyntax Comprehension\u0026nbsp;\u003c/strong\u003e\u003cstrong\u003eITA\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eSyntax Comprehension\u0026nbsp;\u003c/strong\u003e\u003cstrong\u003eENG\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e42/48\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e46/48\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e0.219\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e40/48\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e38/48\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e0.774\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eENPA\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e-\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e-\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u003cem\u003eWords\u0026nbsp;repetition\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e14/15\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e15/15\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u003cem\u003eSentences repetition\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e3/3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e3/3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u003cem\u003eNumbers repetition\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e10/10\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e9/10\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003ctable border=\"0\" cellspacing=\"0\" cellpadding=\"0\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eWAB\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"10\" valign=\"top\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u003cem\u003eSentences repetition\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e0.625\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e86/100\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e80/100\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e0.625\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eCAGI\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e-\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e-\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u003cem\u003eNaming\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e23/48\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e22/48\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u003cem\u003eComprehension\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e46/48\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e48/48\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e0.500\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eSAT\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e72/76\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e73/76\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003ePicture\u0026nbsp;\u003c/strong\u003e\u003cstrong\u003eDescription\u0026nbsp;ITA\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003ePicture\u0026nbsp;\u003c/strong\u003e\u003cstrong\u003eDescription\u0026nbsp;ENG\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u003cem\u003eTotal words\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u003cem\u003eTotal words\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e188\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e176\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e111\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e220\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u003cem\u003eTotal nouns\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u003cem\u003eTotal nouns\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e35\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e31\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e14\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e30\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u003cem\u003eTotal verbs\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u003cem\u003eTotal verbs\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e32\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e37\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e21\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e48\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u003cem\u003eLexical Density\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u003cem\u003eLexical Density\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e35.17\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e31.21\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e14.18\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e30.21\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u003cem\u003eSyntactic Complexity\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u003cem\u003eSyntactic Complexity\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e0.69\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e1.36\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e0.64\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003eDifferences within language were derived from paired permutation tests (10,000 Monte Carlo resamples). N.A: non available data; in grey: permutation not performed.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eTable\u0026nbsp;3.\u0026nbsp;Between\u0026nbsp;language\u0026nbsp;comparisons\u0026nbsp;pre-\u0026nbsp;and\u0026nbsp;post-LRT.\u003c/strong\u003e\u003c/p\u003e\n\u003ctable border=\"0\" cellspacing=\"0\" cellpadding=\"0\" class=\"fr-table-selection-hover\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"8\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eTest\u003c/strong\u003e\u003cstrong\u003e\u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp;n. Item PRE TREATMENT\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003eENG\u003c/strong\u003e\u003cstrong\u003e\u0026nbsp;ITA\u0026nbsp;\u003c/strong\u003e\u003cstrong\u003eMean\u003c/strong\u003e\u003cstrong\u003e\u0026nbsp;Mean ENG- p value\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003eENG\u003c/strong\u003e\u003cstrong\u003e\u0026nbsp;ITA ITA\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"4\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003ePOST TREATMENT\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003eMean\u003c/strong\u003e\u003cstrong\u003e\u0026nbsp;Mean ENG- p value ENG ITA ITA\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eSAND MLSE\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u003cem\u003eNaming\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e6\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e14\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e0.333\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e0.857\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e-0.524\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003e0.038\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e0.500\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e0.714\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e-0.214\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e0.610\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u003cem\u003eSingle word\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e12\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e0.667\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e1.000\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e-0.333\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e0.203\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e0.667\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e0.833\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e-0.167\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e1.000\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u003cem\u003ecomprehension\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u003cem\u003eSentence\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e4\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e8\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e0.750\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e1.000\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e-0.250\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e0.337\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e0.500\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e0.875\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e-0.375\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e0.504\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u003cem\u003ecomprehension\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u003cem\u003eSingle word\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e6\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e10\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e0.833\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e1.000\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e-0.167\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e0.381\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e0.667\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e0.900\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e-0.233\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e0.520\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u003cem\u003erepetition\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u003cem\u003eSentence\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e4\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e6\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e0.250\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e0.333\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e-0.083\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e1.000\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e0.250\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e0.500\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e-0.250\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e0.577\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u003cem\u003erepetition\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u003cem\u003eReading\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e10\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e16\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e0.100\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e0.938\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e-0.838\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003e0.000\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e0.400\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e0.938\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e-0.538\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003e0.005\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u003cem\u003eSemantic\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e4\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e4\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e1.000\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e0.750\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e0.250\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e1.000\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e1.000\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e0.750\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e0.250\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e1.000\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u003cem\u003eAssociation\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eAd\u0026nbsp;hoc\u0026nbsp;naming task\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e20\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e20\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e0.550\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e0.700\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e-0.150\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e0.519\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e0.600\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e0.550\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e0.050\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e1.000\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003ePyramids\u0026nbsp;and Palm\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e14\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e14\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e0.714\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e1.000\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e-0.286\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e0.099\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e0.643\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e0.857\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e-0.214\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e0.390\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eNAT\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e30\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e22\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e0.600\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e0.727\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e-0.127\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e0.393\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e0.567\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e0.955\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e-0.388\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003e0.002\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eNAVS\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u003cem\u003eVerb\u0026nbsp;naming test\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e22\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e22\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e0.636\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e0.818\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e-0.182\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e0.311\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e0.682\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e0.636\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e0.046\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e1.000\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003ctable border=\"0\" cellspacing=\"0\" cellpadding=\"0\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u003cem\u003eVerb\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e22\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e22\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e1.000\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e1.000\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e0.000\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e1.000\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e1.000\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e1.000\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e0.000\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e1.000\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u003cem\u003ecomprehension\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u003cem\u003etest\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u003cem\u003eArgument\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e32\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e32\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e0.719\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e0.938\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e-0.219\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003e0.044\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e0.969\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e0.938\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e0.031\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e1.000\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u003cem\u003estructure\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u003cem\u003eproduction\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u003cem\u003eSentence\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e30\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e30\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e0.567\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e0.700\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e-0.133\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e0.430\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e0.467\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e0.833\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e-0.367\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003e0.006\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u003cem\u003eproduction\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u003cem\u003epriming\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u003cem\u003eSentence\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e30\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e30\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e0.833\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e0.800\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e0.033\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e1.000\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e0.800\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e0.833\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e-0.033\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e1.000\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u003cem\u003ecomprehension\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u003cem\u003etest\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u003cem\u003eSyntax Comprehension\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e48\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e48\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e0.833\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e0.875\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e-0.042\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e0.770\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e0.792\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e0.958\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e-0.167\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003e0.028\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003ePermutation\u0026nbsp;tests\u0026rsquo;\u0026nbsp;results. Mean:\u0026nbsp;proportion\u0026nbsp;of\u0026nbsp;correct\u0026nbsp;answers.\u0026nbsp;ENG-ITA:\u0026nbsp;differences\u0026nbsp;between English and Italian performances,\u003c/p\u003e\n\u003cp\u003eNote:\u0026nbsp;LRT:\u0026nbsp;Lexical\u0026nbsp;Retrieval\u0026nbsp;Therapy;\u0026nbsp;SAND:\u0026nbsp;Screening\u0026nbsp;for\u0026nbsp;Aphasia\u0026nbsp;in\u0026nbsp;Neurodegeneration;\u0026nbsp;NAT: Northwestern Anagram Test\u003c/p\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":true,"hideJournal":true,"highlight":"","institution":"Istituti Clinici Scientifici Maugeri IRCCS","isAcceptedByJournal":false,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true},"keywords":"Primary progressive aphasia, bilingual experience, multilingualism, cross-linguistic transfer, lexical retrieval therapy, bilingual speech-language assessment, bilingual speech-language intervention","lastPublishedDoi":"10.21203/rs.3.rs-7835928/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-7835928/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003eINTRODUCTION: The impact of bilingualism on speech-language assessment and therapy in Primary Progressive Aphasia (PPA) remains underexplored, despite its suggested influence on disease presentation.\u003c/p\u003e\u003cp\u003eMETHODS: A bilingual Italian (L1)-English (L2) individual with logopenic-variant PPA completed a bilingual assessment and dual-language Lexical Retrieval Therapy. His bilingual experience was characterized, and therapy outcomes were evaluated within and across languages.\u003c/p\u003e\u003cp\u003eRESULTS: Pre-morbidly, the patient was a relatively balanced bilingual with stronger L1 literacy. Following disease onset, L2 showed faster decline, while L1 remained stable. Age of acquisition, dominance, and language use were among the main factors contributing to language maintenance and decline. Therapy yielded equivalent item- specific gains in both languages (L1 d₂ =5.0; L2 d₂ =5.6), asymmetric cross-linguistic transfer to L2\u0026thinsp;\u0026gt;\u0026thinsp;L1, and modest functional improvements.\u003c/p\u003e\u003cp\u003eDISCUSSION: Findings support the relevance of in-depth bilingual assessment and therapy underpinning successful treatment in PPA, unveiling the significance of bilingual experience in shaping treatment outcomes.\u003c/p\u003e","manuscriptTitle":"The influence of bilingualism on the assessment and treatment of an Italian–English speaker with the logopenic variant of PPA","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2025-10-17 12:42:37","doi":"10.21203/rs.3.rs-7835928/v1","editorialEvents":[{"type":"communityComments","content":0}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"3e980a61-5556-499b-b307-ec1510152985","owner":[],"postedDate":"October 17th, 2025","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"posted","subjectAreas":[{"id":56138828,"name":"Neurology"},{"id":56138829,"name":"Physical Medicine \u0026 Rehab"}],"tags":[],"updatedAt":"2025-10-17T12:42:37+00:00","versionOfRecord":[],"versionCreatedAt":"2025-10-17 12:42:37","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-7835928","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-7835928","identity":"rs-7835928","version":["v1"]},"buildId":"8U1c8b4HqxoKbykW_rLl7","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}