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This study aims to investigate the prevalence and characteristics of dysphagia among adults with intellectual disabilities (ID) referred to speech and language therapy for swallow assessment, providing information on the demographic characteristics, referral trends, co-occurring health conditions and reasons for referrals highlighting the complex health-care needs of this population.

This study used a standardised patient data extraction method over a six-month period involving 74 adults with ID referred to speech and language therapy for swallow assessment.

This study revealed a high prevalence of dysphagia among adults with ID referred to speech and language therapy for swallow assessment. Increasing age and severity of ID were associated with an increased likelihood of swallowing difficulties. Co-occurring health conditions such as mobility difficulties, epilepsy and gastrointestinal conditions were prevalent, suggesting that adults with ID and swallowing difficulties are often living with complex health conditions. Choking incidents and hospital admissions were primary reasons for referral.

This study stresses the pressing need for strategies to mitigate risks associated with choking incidents and hospital admission among this vulnerable population. Possible limitations include a reliance on referral and the focus being on a single service over a short period which may limit generalisation to the wider ID population.

This study emphasises the need to understand each person’s unique profile of health needs and the value of a specialised speech and language therapy service.

The importance of increasing awareness among caregivers and medical experts is highlighted.

The findings underscore the importance of tailored assessment, caregiver involvement and heightened interdisciplinary awareness to effectively manage dysphagia in individuals with ID.

The study aims to explore the overall growth trend, top publishing countries, co-authorship and author keywords in the field of Industry 5.0.

This study presents the outcomes of a bibliometric analysis conducted using VOSviewer software. The analysis retrieved data from the Scopus database, including citations, co-authors, keywords, bibliometric coupling and co-occurrence.

The findings reveal a significant increase in publications and citations related to Industry 5.0 in recent years. China, the USA and India emerge as the leading countries driving research in this field. The co-authorship analysis indicates limited collaboration among authors, with only 48 out of 354 authors being linked through co-authorship. Through co-occurrence analysis, the investigation identifies the most frequently occurring keywords in the research, with “Industry 5.0” and “Industry 4.0” being the most frequently co-occurring keywords. The bibliographic coupling analysis identifies six clusters of research themes.

The study solely relies on data gathered from the Scopus database for analysis on a specific date. Therefore, data from other databases collected at different times may yield different observations and findings.

This study enhances the knowledge of professionals and academia in Industry 5.0, enabling the professionals to efficiently and sustainably manage the sector.

The bibliometric analysis presented in this study provides valuable insights into the contributions made by authors, keywords and co-authors to the field of Industry 5.0. Additionally, the thematic analysis summarized in this study is a novel contribution to the field.

The resource crisis in healthcare can be alleviated by engaging external stakeholders and resources in healthcare delivery. The authors use value and open innovation concepts to understand what motivates the stakeholders to join the healthcare innovation ecosystem and what value such an ecosystem brings to healthcare.

A systematic literature review following the PRISMA framework method was applied to reach the research objective. Out of a total of 509 identified articles published till 2021, 25 were selected as relevant for this review.

Six categories of actors were identified, including innovation intermediaries, which were so far neglected in the healthcare innovation literature. Furthermore, patients, healthcare providers, innovation suppliers, investors and influencers were described. The authors also distinguished internal and external stakeholders. The authors show why and how open innovation projects contribute to involving external stakeholders and resources in healthcare delivery by contributing to patient autonomy, relationship building, knowledge transfer, improving collaborative mindset and culture, advancing know-how and bringing additional finances.

This article is the first one to systematically describe the value of open innovation in healthcare. The authors challenge the positivist approach in value presented by value-based healthcare. The authors show how openness contributes to addressing the resource crisis by involving new stakeholders and resources in the care delivery process.

Communities representing groups of agents with similar interests or functions are one of the essential features of complex networks. Finding communities in real-world networks is critical for analyzing complex systems in various areas ranging from collaborative information to political systems. Given the different characteristics of networks and the capability of community detection in handling a plethora of societal problems, community detection methods represent an emerging area of research. Contributing to this field, the authors propose a new community detection algorithm based on the hybridization of node and link granulation.

The proposed algorithm utilizes a rough set-theoretic concept called closure on networks. Initial sets are constructed by using neighborhood topology around the nodes as well as links and represented as two different categories of granules. Subsequently, the authors iteratively obtain the constrained closure of these sets. The authors use node mutuality and link mutuality as merging criteria for node and link granules, respectively, during the iterations. Finally, the constrained closure subsets of nodes and links are combined and refined using the Jaccard similarity coefficient and a local density function to obtain communities in a binary network.

Extensive experiments conducted on twelve real-world networks followed by a comparison with state-of-the-art methods demonstrate the viability and effectiveness of the proposed algorithm.

The study also contributes to the ongoing effort related to the application of soft computing techniques to model complex systems. The extant literature has integrated a rough set-theoretic approach with a fuzzy granular model (Kundu and Pal, 2015) and spectral clustering (Huang and Xiao, 2012) for node-centric community detection in complex networks. In contributing to this stream of work, the proposed algorithm leverages the unexplored synergy between rough set theory, node granulation and link granulation in the context of complex networks. Combined with experiments of network datasets from various domains, the results indicate that the proposed algorithm can effectively reveal co-occurring disjoint, overlapping and nested communities without necessarily assigning each node to a community.

This study carries important practical implications for complex adaptive systems in business and management sciences, in which entities are increasingly getting organized into communities (Jacucci et al., 2006). The proposed community detection method can be used for network-based fraud detection by enabling experts to understand the formation and development of fraudulent setups with an active exchange of information and resources between the firms (Van Vlasselaer et al., 2017). Products and services are getting connected and mapped in every walk of life due to the emergence of a variety of interconnected devices, social networks and software applications.

The proposed algorithm could be extended for community detection on customer trajectory patterns and design recommendation systems for online products and services (Ghose et al., 2019; Liu and Wang, 2017). In line with prior research, the proposed algorithm can aid companies in investigating the characteristics of implicit communities of bloggers or social media users for their services and products so as to identify peer influencers and conduct targeted marketing (Chau and Xu, 2012; De Matos et al., 2014; Zhang et al., 2016). The proposed algorithm can be used to understand the behavior of each group and the appropriate communication strategy for that group. For instance, a group using a specific language or following a specific account might benefit more from a particular piece of content than another group. The proposed algorithm can thus help in exploring the factors defining communities and confronting many real-life challenges.

This work is based on a theoretical argument that communities in networks are not only based on compatibility among nodes but also on the compatibility among links. Building up on the aforementioned argument, the authors propose a community detection method that considers the relationship among both the entities in a network (nodes and links) as opposed to traditional methods, which are predominantly based on relationships among nodes only.

Disasters and armed conflict often co-occur, but does that imply that disasters trigger or fuel conflict? In the small but growing body of literature attempting to answer this question, divergent findings indicate the complex and contextual nature of a potential answer to this question. The purpose of this study is to contribute a robust cross-country analysis of the co-occurrence of disaster and conflict, with a particular focus on the potential role played by disaster.

Grounded in a theoretical model of disaster–conflict co-occurrence, this study merges data from 163 countries between 1990 and 2017 on armed conflict, disasters and relevant control variables (low human development, weak democratic institutions, natural resource dependence and large population size/density).

The main results of this study show that, despite a sharp increase in the co-occurrence of disasters and armed conflict over time, disasters do not appear to have a direct statistically significant relation with the occurrence of armed conflict. This result contributes to the understanding of disasters and conflicts as indirectly related via co-creation mechanisms and other factors.

This study is a novel contribution, as it provides a fresh analysis with updated data and includes different control variables that allow for a significant contribution to the field.

This study aims to evaluate the quality of a speech and language therapy (SLT) swallow service provided to adults with intellectual disability (ID) by exploring the process and outcome factors; to explore the process of what is done to and for the patient including identifying dysphagia, choking and pneumonia risk, typical interventions and management; examine clinical outcomes; and explore the relationship of outcomes with risk factors, satisfaction with the service and the impact of the service on the number of choking incidents and admissions to acute hospital with swallow concerns.

There were three specific work packages: (1) collecting and scrutinising patient data from the clinical record for adults with ID referred to the SLT swallow service over a six-month period. The researcher created aims, defined the limits to achieve the aims, designed a standardised data collection form, set out where data was in the clinical record, piloted, set limits for collection and trained reviewers; (2) gathering experience and satisfaction surveys from patients, caregivers and referrers over the six-month study period; and (3) monitoring choking adverse incident reports and hospital admission with swallow concerns for the whole ID population.

Choking and hospital admission were the main reasons for referral, and pneumonia risk significantly predicted dysphagia impairment. The research highlighted common dysphagia risk factors, interventions and recommendations for this population. The SLT swallow service is a quality service that is highly valued by patients, their caregivers and referrers. The service achieves significant clinical improvements, helps identify dysphagia and provides management to reduce associated risks.

This study found common dysphagia risk factors, interventions and recommendations; it also found that the therapy outcome measures/Royal College of Speech and Language Therapy online outcome tool was a meaningful outcome measure, and that pneumonia risk significantly predicted dysphagia impairment, all of which could inform the identified dysphagia research priorities for this population.

Naming usual care in treatment and recommendations could help ensure a fair service and could help form quality indicators. People with ID, their caregivers and staff generated valuable ideas for improvement, and further involvement work could create a logic model for the service. Other future work could explore the use of screening tools, increase multidisciplinary team working, improve access to instrumental assessments, raise awareness of swallowing and promote important oral health and medication reviews. By using this information to shape quality improvement work and policies, one can work toward addressing high health-related inequalities and preventable deaths associated with dysphagia in this vulnerable population.

It may be useful to raise awareness that adults with ID age earlier and that one should not exclude them from older people’s services because of an age threshold, often set higher than their life expectancy. This study highlighted a possible inequality of access issue for adults with ID who do not have direct care or day care staff. There is a need to increase access to awareness training so caregivers and general practitioners can recognise swallow difficulties and know how to make a referral for a swallow assessment.

Overall, the evaluation of the swallow service to adults with ID suggests that SLT have a quality service for adults with ID that is highly valued and provides significant clinical improvements. By building on these strengths, SLT could extend the reach, influence and impact of their services to help those adults with ID who have emerging swallow difficulties or who do not access the service.

In recent years, there has been significant interest in adopting XR (extended reality) technologies such as VR (virtual reality) and AR (augmented reality), particularly in retail. However, extending activities through reality-mediation is still mostly believed to offer an inferior experience due to their shortcomings in usability, wearability, graphical fidelity, etc. This study aims to address the research gap by experimentally examining the acceptance of metaverse shopping.

This study conducts a 2 (VR: with vs. without) × 2 (AR: with vs. without) between-subjects laboratory experiment involving 157 participants in simulated daily shopping environments. This study builds a physical brick-and-mortar store at the campus and stocked it with approximately 600 products with accompanying product information and pricing. The XR devices and a 3D laser scanner were used in constructing the three XR shopping conditions.

Results indicate that XR can offer an experience comparable to, or even surpassing, traditional shopping in terms of its instrumental and hedonic aspects, regardless of a slightly reduced perception of usability. AR negatively affected perceived ease of use, while VR significantly increased perceived enjoyment. It is surprising that the lower perceived ease of use appeared to be disconnected from the attitude toward metaverse shopping.

This study provides important experimental evidence on the acceptance of XR shopping, and the finding that low perceived ease of use may not always be detrimental adds to the theory of technology adoption as a whole. Additionally, it provides an important reference point for future randomized controlled studies exploring the effects of technology on adoption.

In times of crisis, such as the Covid-19 global pandemic, journalists who write about biomedical information must have the strategic aim to be clearly and easily understood by everyone. In this study, we assume that journalistic discourse could benefit from language redundancy to improve clarity and simplicity aimed at science popularization. The concept of language redundancy is theoretically discussed with the support of discourse analysis and information theory. The methodology adopted is a corpus-based qualitative approach. Two corpora samples with Brazilian Portuguese (BP) texts on Covid-19 were collected. One with texts from a monthly science digital magazine called Pesquisa FAPESP aimed at students and researchers for scientific information dissemination and the other with popular language texts from a news Portal G1 (Rede Globo) aimed at unspecified and/or non-specialized readers. The materials were filtered with two descriptors: “vaccine” and “test.” Preliminary analysis of examples from these materials revealed two categories of redundancy: paraphrastic and polysemic. Paraphrastic redundancy is based on concomitant language reformulation of words, sentences, text excerpts, or even larger units. Polysemic redundancy does not easily show material evidence, but is based on cognitively predictable semantic association in socio-cultural domains. Both kinds of redundancy contribute, each in their own way, to improving text readability for science popularization in Brazil.

This study explores the determinants of police officer support for pre-arrest/booking deflection programs that divert people presenting with substance use and/or mental health disorder symptoms out of the criminal justice system and connect them to supportive services.

This study analyzes responses from 254 surveys fielded to police officers in Delaware. Questionnaires asked about views on leadership, approaches toward crime, training, occupational experience and officer’s personal characteristics. The study applies a new machine learning method called kernel-based regularized least squares (KRLS) for non-linearities and interactions among independent variables. Estimates from a KRLS model are compared with those from an ordinary least square regression (OLS) model.

Support for diversion is positively associated with leadership endorsing diversion and thinking of new ways to solve problems. Tough-on-crime attitudes diminish programmatic support. Tenure becomes less predictive of police attitudes in the KRLS model, suggesting interactions with other factors. The KRLS model explains a larger proportion of the variance in officer attitudes than the traditional OLS model.

The study demonstrates the usefulness of the KRLS method for practitioners and scholars seeking to illuminate patterns in police attitudes. It further underscores the importance of agency leadership in legitimizing deflection as a pathway to addressing behavioral health challenges in communities.

Science mapping is an essential application of visualization technology widely used in safety, construction management and environmental science. The purpose of this study was to explore thermal comfort in residential buildings (TCinRB) research in India, identify research trends using a science mapping approach and provide a perspective for recommending future research in TCinRB.

This study used the VOSviewer tool to conduct a systematic analysis of the development trend in TCinRB studies in India based on Scopus Index articles published between 2001 and 2020. The annual numbers of articles, geographical locations of studies, major research organizations and authors, and the sources of journals on TCinRB were presented based on the analysis. Then, using co-authorship analysis, the collaborations among the major research groups were reported. Furthermore, research trends on TCinRB studies were visually explored using keyword co-occurrence analysis. The emerging research topics in the TCinRB research community were discovered by analyzing the authors’ keywords.

The findings revealed that studies had been discovered to pay more attention to north-east India, vernacular architecture, Hyderabad apartments and temperature performance in the past two decades. Thermal adaptation, composite climate, evaporative cooling and clothing insulation are emerging research areas in the TCinRB domain. The findings summarized mainstream research areas based on Indian climatic zones, addressed current TCinRB research gaps and suggested future research directions.

This review is particularly significant because it could help researchers understand the body of knowledge in TCinRB and opens the way for future research to fill an important research gap.