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To do so, we added temporal information (a time stamp) to categorical data (i.e., language), and applied joint recurrence analysis methods to visualize and quantify speech-motion coordination coupling during a rap performance. We illustrate how new dynamic methods may capture this coordination in a small case-study design on this expert rap performance. We describe a case study suggesting this kind of dynamic analysis holds promise, and end by discussing the theoretical implications of studying complex performances of this kind as a dynamic, coordinated phenomenon.Introduction People with Spinal Cord Injury (SCI) are at risk of feeling socially disconnected. Competitive esports present an opportunity for people with SCI to remotely engage in a community. The aim of this study is to discuss barriers to esports participation for people with SCI, present adaptive solutions to these problems, and analyze self-reported changes in social connection. Materials and Methods We presented a descriptive data collected in the process of a quality improvement initiative at Mount Sinai Hospital. In 2019, seven individuals with cervical SCI and quadriplegia participated in a special interest group on esports. Group scores were then analyzed for evidence of between subjects variability using a single sample t-test. A Pearson’s correlation was conducted to determine the relationship between social connectedness and demographic data. Results All players experienced functional limitations as a result of their injury but managed to design personalized gaming setups with adaptive equipment that allowed them to successfully compete in esports. All players reported a positive change in perceived social connectedness (p less then 0.001) after participating in the special interest group. Score on Social Connectedness Scale negatively correlated with Time since injury (years). Discussion It is feasible to create adaptive gaming setups that can be used by people with differing degrees and severity of SCI in a competitive esports environment. Technology and adaptive competitive esports have a potential to improve social connectedness and inclusion in people with quadriplegia. Further research on efficacy and effectiveness of these inclusive environments and their effects on quality of life, activity, and participation is warranted.COVID-19 severity and mortality risk are greater for older adults whereas economic impact is deeper for younger adults. Using the Health Belief Model (HBM) as a framework, this study used a web-based survey to examine how perceived COVID-19 susceptibility and severity and perceived efficacy of recommended health behaviors varied by age group and were related to the adoption of health behaviors. Proportional odds logistic regression was used to examine the relationship between age group and perceived COVID-19 susceptibility, severity, impact, and health behavior efficacy and adoption. Proteasome inhibitor Structural equation modeling based on HBM constructs examined the relationships between health beliefs and behaviors. Data from 820 participants (Ontario, Canada) were analyzed (age 42.7, 16.2 years; 79% women). Middle-aged and older adults reported greater concerns about the personal risk of hospitalization and mortality, economic impact, and social impact of COVID-19 than young adults. Middle-aged adults also reported greatest concern for other age groups. Adoption and perceived efficacy of health behaviors was similar across age groups with few exceptions. Both middle-aged and older-adults were more likely to perceive their own and each other’s age groups as responding adequately to COVID-19 compared to young adults. Structural equation modeling indicated perceived benefits of health behaviors were the primary driver of behavior uptake, with socioeconomic factors and perceived severity and susceptibility indirectly associated with uptake through their influence on perceived benefits. Overall, these results suggest adoption of health behaviors is very high with few differences between age groups, despite differences in perceived impact of COVID-19. Public health communications should focus on the benefits of health behaviors to drive adoption.Auditory scene analysis is an elementary aspect of music perception, yet only little research has scrutinized auditory scene analysis under realistic musical conditions with diverse samples of listeners. This study probed the ability of younger normal-hearing listeners and older hearing-aid users in tracking individual musical voices or lines in JS Bach’s The Art of the Fugue. Five-second excerpts with homogeneous or heterogenous instrumentation of 2-4 musical voices were presented from spatially separated loudspeakers and preceded by a short cue for signaling the target voice. Listeners tracked the cued voice and detected whether an amplitude modulation was imposed on the cued voice or a distractor voice. Results indicated superior performance of young normal-hearing listeners compared to older hearing-aid users. Performance was generally better in conditions with fewer voices. For young normal-hearing listeners, there was interaction between the number of voices and the instrumentation performance degraded less drastically with an increase in the number of voices for timbrally heterogeneous mixtures compared to homogeneous mixtures. Older hearing-aid users generally showed smaller effects of the number of voices and instrumentation, but no interaction between the two factors. Moreover, tracking performance of older hearing aid users did not differ when these participants did or did not wear hearing aids. These results shed light on the role of timbral differentiation in musical scene analysis and suggest reduced musical scene analysis abilities of older hearing-impaired listeners in a realistic musical scenario.Cognitive diagnostic models (CDMs) show great promise in language assessment for providing rich diagnostic information. The lack of a full understanding of second language (L2) listening subskills made model selection difficult. In search of optimal CDM(s) that could provide a better understanding of L2 listening subskills and facilitate accurate classification, this study carried a two-layer model selection. At the test level, A-CDM, LLM, and R-RUM had an acceptable and comparable model fit, suggesting mixed inter-attribute relationships of L2 listening subskills. At the item level, Mixed-CDMs were selected and confirmed the existence of mixed relationships. Mixed-CDMs had better model and person fit than G-DNIA. In addition to statistical approaches, the content analysis provided theoretical evidence to confirm and amend the item-level CDMs. It was found that semantic completeness pertaining to the attributes and item features may influence the attribute relationships. Inexplicable attribute conflicts could be a signal of suboptimal model choice.