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Purpose: Analysis of spontaneous speech samples is important for determining patterns of language production in people with aphasia. To accomplish this, researchers and clinicians can use either hand coding or computer-automated methods. In a comparison of the two methods using the hand-coding NNLA (Northwestern Narrative Language Analysis) and automatic transcript analysis by CLAN (Computerized Language Analysis), Hsu and Thompson (2018) found good agreement for 32 of 51 linguistic variables. The comparison showed little difference between the two methods for coding most general (i.e., utterance length, rate of speech production), lexical, and morphological measures. However, the NNLA system coded grammatical measures (i.e., sentence and verb argument structure) that CLAN did not. Because of the importance of quantifying these aspects of language, the current study sought to implement a new, single, composite CLAN command for the full set of 51 NNLA codes and to evaluate its reliability for coding aphasic language samples. Method: Eighteen manually coded NNLA transcripts from eight people with aphasia and 10 controls were converted into CHAT (Codes for the Human Analysis of Talk) files for compatibility with CLAN commands. Rules from the NNLA manual were translated into programmed rules for CLAN computation of lexical, morphological, utterance-level, sentence-level, and verb argument structure measures. Results: The new C-NNLA (CLAN command to compute the full set of NNLA measures) program automatically computes 50 of the 51 NNLA measures and generates the results in a summary spreadsheet. The only measure it does not compute is the number of verb particles. Statistical tests revealed no significant difference between C-NNLA results and those generated by manual coding for 44 of the 50 measures. C-NNLA results were not comparable to manual coding for the six verb argument measures. Conclusion: Clinicians and researchers can use the automatic C-NNLA to analyze important variables required for quantification of grammatical deficits in aphasia in a way that is fast, replicable, and accessible without extensive linguistic knowledge and training.

Reorganization of language networks in aphasia takes advantage of the facts that (a) the brain is an organ of plasticity, with neuronal changes occurring throughout the life span, including following brain damage; (b) plasticity is highly experience dependent; and (c) as with any learning system, language reorganization involves a synergistic interplay between organism-intrinsic (i.e., cognitive and brain) and organism-extrinsic (i.e., environmental) variables. A major goal for clinical treatment of aphasia is to be able to prescribe treatment and predict its outcome based on the neurocognitive deficit profiles of individual patients. This review article summarizes the results of research examining the neurocognitive effects of psycholinguistically based treatment (i.e., Treatment of Underlying Forms; Thompson & Shapiro, 2005) for sentence processing impairments in individuals with chronic agrammatic aphasia resulting from stroke and primary progressive aphasia and addresses both behavioral and brain variables related to successful treatment outcomes. The influences of lesion volume and location, perfusion (blood flow), and resting-state neural activity on language recovery are also discussed as related to recovery of agrammatism and other language impairments. Based on these and other data, principles for promoting neuroplasticity of language networks are presented.

BackgroundThere is no model to estimate absolute invasive breast cancer risk for Hispanic women.MethodsThe San Francisco Bay Area Breast Cancer Study (SFBCS) provided data on Hispanic breast cancer case patients (533 US-born, 553 foreign-born) and control participants (464 US-born, 947 foreign-born). These data yielded estimates of relative risk (RR) and attributable risk (AR) separately for US-born and foreign-born women. Nativity-specific absolute risks were estimated by combining RR and AR information with nativity-specific invasive breast cancer incidence and competing mortality rates from the California Cancer Registry and Surveillance, Epidemiology, and End Results program to develop the Hispanic risk model (HRM). In independent data, we assessed model calibration through observed/expected (O/E) ratios, and we estimated discriminatory accuracy with the area under the receiver operating characteristic curve (AUC) statistic.ResultsThe US-born HRM included age at first full-term pregnancy, biopsy for benign breast disease, and family history of breast cancer; the foreign-born HRM also included age at menarche. The HRM estimated lower risks than the National Cancer Institute's Breast Cancer Risk Assessment Tool (BCRAT) for US-born Hispanic women, but higher risks in foreign-born women. In independent data from the Women's Health Initiative, the HRM was well calibrated for US-born women (observed/expected [O/E] ratio = 1.07, 95% confidence interval [CI] = 0.81 to 1.40), but seemed to overestimate risk in foreign-born women (O/E ratio = 0.66, 95% CI = 0.41 to 1.07). The AUC was 0.564 (95% CI = 0.485 to 0.644) for US-born and 0.625 (95% CI = 0.487 to 0.764) for foreign-born women.ConclusionsThe HRM is the first absolute risk model that is based entirely on data specific to Hispanic women by nativity. Further studies in Hispanic women are warranted to evaluate its validity.

Purpose: Analysis of spontaneous speech samples is important for determining patterns of language production in people with aphasia. To accomplish this, researchers and clinicians can use either hand coding or computer-automated methods. In a comparison of the two methods using the hand-coding NNLA (Northwestern Narrative Language Analysis) and automatic transcript analysis by CLAN (Computerized Language Analysis), Hsu and Thompson (2018) found good agreement for 32 of 51 linguistic variables. The comparison showed little difference between the two methods for coding most general (i.e., utterance length, rate of speech production), lexical, and morphological measures. However, the NNLA system coded grammatical measures (i.e., sentence and verb argument structure) that CLAN did not. Because of the importance of quantifying these aspects of language, the current study sought to implement a new, single, composite CLAN command for the full set of 51 NNLA codes and to evaluate its reliability for coding aphasic language samples. Method: Eighteen manually coded NNLA transcripts from eight people with aphasia and 10 controls were converted into CHAT (Codes for the Human Analysis of Talk) files for compatibility with CLAN commands. Rules from the NNLA manual were translated into programmed rules for CLAN computation of lexical, morphological, utterance-level, sentence-level, and verb argument structure measures. Results: The new C-NNLA (CLAN command to compute the full set of NNLA measures) program automatically computes 50 of the 51 NNLA measures and generates the results in a summary spreadsheet. The only measure it does not compute is the number of verb particles. Statistical tests revealed no significant difference between C-NNLA results and those generated by manual coding for 44 of the 50 measures. C-NNLA results were not comparable to manual coding for the six verb argument measures. Conclusion: Clinicians and researchers can use the automatic C-NNLA to analyze important variables required for quantification of grammatical deficits in aphasia in a way that is fast, replicable, and accessible without extensive linguistic knowledge and training., The spoken language of people with aphasia (PWA) is often impaired. Individuals with nonfluent agrammatic aphasia show a range of grammatical errors, including omissions, additions, and substitutions of grammatical markers [...]

Purpose: Reorganization of language networks in aphasia takes advantage of the facts that (a) the brain is an organ of plasticity, with neuronal changes occurring throughout the life span, including following brain damage; (b) plasticity is highly experience dependent; and (c) as with any learning system, language reorganization involves a synergistic interplay between organism-intrinsic (i.e., cognitive and brain) and organism-extrinsic (i.e., environmental) variables. A major goal for clinical treatment of aphasia is to be able to prescribe treatment and predict its outcome based on the neurocognitive deficit profiles of individual patients. This review article summarizes the results of research examining the neurocognitive effects of psycholinguistically based treatment (i.e., Treatment of Underlying Forms; Thompson & Shapiro, 2005) for sentence processing impairments in individuals with chronic agrammatic aphasia resulting from stroke and primary progressive aphasia and addresses both behavioral and brain variables related to successful treatment outcomes. The influences of lesion volume and location, perfusion (blood flow), and resting-state neural activity on language recovery are also discussed as related to recovery of agrammatism and other language impairments. Based on these and other data, principles for promoting neuroplasticity of language networks are presented. Conclusions: Sentence processing treatment results in improved comprehension and production of complex syntactic structures in chronic agrammatism and generalization to less complex, linguistically related structures in chronic agrammatism. Patients also show treatment-induced shifts toward normal-like online sentence processing routines (based on eye movement data) and changes in neural recruitment patterns (based on functional neuroimaging), with posttreatment activation of regions overlapping with those within sentence processing and dorsal attention networks engaged by neurotypical adults performing the same task. These findings provide compelling evidence that treatment focused on principles of neuroplasticity promotes neurocognitive recovery in chronic agrammatic aphasia. Presentation Video: https://doi.org/10.23641/asha.10257587, Recovery of language following brain damage takes advantage of two now well-known facts. First, the brain is an organ of plasticity, with neuronal changes occurring throughout the life span, including [...]

Increasing population, total economic volume, and human consumption levels have resulted in problems of resource shortages, climate change, ozone layer depletion, land regression, and deteriorating environmental pollution. Printing and related industries constitute one of the major sources of environmental pollution due to heavy energy and resource (materials) use. Therefore, there is a need to adopt resourceful thinking regarding activities in the printing and related industries, so they can contribute to environmental protection by adhering to greener, eco-friendly, and sustainable practices. This article discusses strategies that these industries could adopt, which would put their businesses on sound economic footing as they adhere to sustainable business practices that contribute to and safeguard the environment.

Purpose: The purpose of this study is to compare the outcomes of the manually coded Northwestern Narrative Language Analysis (NNLA) system, which was developed for characterizing agrammatic production patterns, and the automated Computerized Language Analysis (CLAN) system, which has recently been adopted to analyze speech samples of individuals with aphasia (a) for reliability purposes to ascertain whether they yield similar results and (b) to evaluate CLAN for its ability to automatically identify language variables important for detailing agrammatic production patterns. Method: The same set of Cinderella narrative samples from 8 participants with a clinical diagnosis of agrammatic aphasia and 10 cognitively healthy control participants were transcribed and coded using NNLA and CLAN. Both coding systems were utilized to quantify and characterize speech production patterns across several microsyntactic levels: utterance, sentence, lexical, morphological, and verb argument structure levels. Agreement between the 2 coding systems was computed for variables coded by both. Results: Comparison of the 2 systems revealed high agreement for most, but not all, lexical-level and morphological-level variables. However, NNLA elucidated utterance-level, sentence-level, and verb argument structure-level impairments, important for assessment and treatment of agrammatism, which are not automatically coded by CLAN. Conclusions: CLAN automatically and reliably codes most lexical and morphological variables but does not automatically quantify variables important for detailing production deficits in agrammatic aphasia, although conventions for manually coding some of these variables in Codes for the Human Analysis of Transcripts are possible. Suggestions for combining automated programs and manual coding to capture these variables or revising CLAN to automate coding of these variables are discussed.

Purpose: The purpose of this paper is to answer the following research questions: what characteristics do key Belizean educational leaders value in teacher applicants and why? What hiring tools do they use to ascertain whether teacher applicants have the characteristics they prefer? Design/methodology/approach: The authors utilized a mixed-methods approach drawing upon three data sources--face-to-face interviews with Belizean educational leaders, field notes, and government documents. A card sorting activity of applicant characteristics and tools was embedded into the interview. Findings: Informants preferred motivation, caring, subject matter knowledge, and teaching skills. Intelligence was perceived as a potentially negative characteristic unless coupled with other characteristics, such as strong teaching skills, motivation, and caring or the umbrella of other characteristics, such as content knowledge or university training/credentialing. Professional characteristics, such as where one went for teacher training and academic performance, were perceived as having less relative importance than personal characteristics. Least important were applicant demographics. Consistent with the extant literature, Belizean informants perceived the interview, evidence of prior experience, and certification as the most important tools in vetting and hiring applicants. Research limitations/implications: The exploratory study is limited by the small sample of informants, but provides insights into preferences for applicant characteristics and hiring tools in an understudied international context. This study informs future research that may seek to survey representative samples of various stakeholder groups (i.e. general managers and principals) for their preferences in applicant characteristics and hiring tools from across Belizean schools and educational providers. Originality/value: The study adds to limited research on preferred teacher characteristics among educational leaders responsible for hiring and/or working with teachers and to the limited international educational leadership research.

The Northwestern Assessment of Verbs and Sentences (NAVS) assesses verb and sentence production and comprehension in aphasia. Results from the original English version and from its adaptation to German have shown that the NAVS is able to capture effects of verb-argument structure (VAS) complexity (i.e., lower accuracy for two- and three-argument vs. one-argument verbs) and syntactic complexity (i.e., lower accuracy for non-canonical vs. canonical sentences) in both agrammatic participants and individuals with fluent forms of aphasia. The NAVS has been recently adapted to Italian (NAVS-I) and tested on a group of healthy participants, with results showing longer reaction times to complex vs. simple verbs and sentences. The present study aimed to test the ability of NAVS-I to i) capture verb/sentence production and comprehension deficits in Italian-speaking individuals with agrammatism or with fluent aphasia, and ii) differentiate individuals with aphasia from healthy age-matched participants, with the overall goal to validate its use in clinical practice. Forty-four healthy participants and 28 individuals with aphasia (10 with agrammatic speech production) were administered the NAVS-I, which includes tasks assessing production and comprehension of verbs requiring one, two or three arguments, as well as production and comprehension of canonical and non-canonical sentences. On the Verb Naming Task (VNT), better production of one- (vs. two- and three-) argument verbs was found in the agrammatic group, whereas, verb production in the fluent group was solely predicted by word length and imageability. No effects of argument optionality (i.e., greater difficulty for optionally transitive verbs than for 1-argument verbs) were found. Sentence-level tasks found no differences between the agrammatic and the fluent group in production or comprehension of both canonical and non-canonical sentences; rather, sentence comprehension accuracy was predicted by demographic variables and by aphasia severity. At the individual level, performance on the NAVS-I was significantly different from that of healthy speakers in 26/28 patients. Data show that the NAVS-I is able to capture effects of argument structure complexity in verb production, and effects of syntactic complexity in sentence production and comprehension. In addition, our results point to verb production as the task with greater capability to differentiate agrammatism from other (fluent) forms of aphasia. The study provides support for the use of the NAVS-I in the diagnosis of aphasia, as it is able to detect language deficits at the individual level, even in participants with mild (residual) forms of aphasia. [ABSTRACT FROM AUTHOR]

SUMMARY: Research on the relationship between obstructive sleep apnea and cognitive functioning has yielded conflicting results, particularly in the older population, and moderators of this association have rarely been studied. Here we investigated the cross‐sectional association between obstructive sleep apnea and cognitive functioning as well as the moderating effect of age, sex, apolipoprotein E4, and obesity on this association among community‐dwelling older people. We analysed data from 496 participants (71.4 ± 4.4 years; 45.6% men) of the HypnoLaus study who underwent polysomnography and a battery of neuropsychological tests. The sample was categorised as no‐to‐mild obstructive sleep apnea (apnea–hypopnea index 0–14.9/h; reference), moderate obstructive sleep apnea (apnea–hypopnea index 15.0–29.9/h), or severe obstructive sleep apnea (apnea–hypopnea index ≥30/h). Regression and moderation analyses were performed with adjustment for confounders. Apolipoprotein E4 and obesity moderated the association between severe obstructive sleep apnea and processing speed, whereas no moderating effects were found for age and sex. In apolipoprotein E4 carriers only, severe obstructive sleep apnea was associated with lower performance in Stroop condition 1 (B = 3.13, p = 0.024). In obese participants only, severe obstructive sleep apnea was associated with lower performance in Stroop condition 1 (B = 3.02, p = 0.025) and Stroop condition 2 (B = 3.30, p = 0.034). Severe obstructive sleep apnea was also associated with lower executive function in the whole sample according to Stroop condition 3 (B = 3.44, p = 0.020) and Stroop interference score (B = 0.24, p = 0.006). Our findings support associations of severe obstructive sleep apnea (but not moderate obstructive sleep apnea) with lower performance in processing speed and executive function in the older general population. Apolipoprotein E4 and obesity appear to be vulnerability factors that strengthen the association between severe obstructive sleep apnea and lower performance in processing speed. [ABSTRACT FROM AUTHOR]