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Currently, transition-age youth on the autism spectrum face a loss of access to services. They are at risk for a number of difficulties, including reduced meaningful relationships, internalizing and externalizing problems, and problems with adaptive skills. In the United States, young adults are expected to either attend postsecondary education and/or pursue gainful employment. However, neurodivergent individuals face barriers and often have difficulties meeting these societal expectations. The following chapter will highlight ways that employers and entrepreneurs can support neurodivergent individuals, including meaningful accommodations and inclusive practices.

This study aims to analyze the entrepreneurial intention (EI) of Colombian researchers using machine learning (ML) techniques, considering their academic activity, contexts and social norms (SN).

Unsupervised classification techniques were applied, including principal component analysis, hierarchical clustering with the Ward method and a logistic model to evaluate the classification. This was done to group researchers according to their characteristics and EI.

The methodology used allowed the identification of three groups of academics with distinct characteristics, of which two showed a high presence of EI. The results indicate that EI is influenced by the connection with the private sector (consulting, intellectual property and applied research) and by the lack of institutional support from universities. Regarding SN, only the preference for entrepreneurial activity over being an employee and the social appreciation of entrepreneurial dedication were identified as predictors of EI.

The use of ML techniques to study the EI of researchers is uncommon. This study highlights the ability of the methodology used to identify differences between two groups of academics with similar characteristics but different levels of EI. One group was identified that, despite rejecting values associated with entrepreneurs, has a high predisposition to develop a career as an entrepreneur. This provides valuable information for designing policies that promote EI among Colombian researchers.

Recently, mHealth apps for COVID-19 have emerged as a new research area due to the diverse efforts to control the COVID-19 epidemic. Although there are many bibliometric studies on mHealth and its applications, no bibliometric study sheds light on mHealth apps for COVID-19 as a new research area. To address the above-mentioned research gap, the current study conducts a bibliometric analysis of research in mHealth apps for COVID-19. It aims to provide a comprehensive overview of the new area and its directions.

The study uses a bibliometric approach to provide an analysis of the overall status of research in mHealth apps for COVID-19. The Scopus database provided by Elsevier was used to extract the analyzed data in this study. SciVal was used to perform the analyses, while VOSviewer was used for scientific mapping.

A total of 457 publications were published between 2020 and 2021 (until Tuesday, June 1) and cited 3,559 times. Publications were written by 2,375 authors, with an average of 5.20 authors per publication. Articles play a pivotal role in the literature on mHealth apps for COVID-19 in terms of production and impact. The research area of mHealth apps for COVID-19 is multidisciplinary. The United States made the largest contribution to this area, while the UK was the most influential. This study reveals the most productive and influential sources, institutions and authors. It also reveals the research hotspots and major thematic clusters in mHealth apps for COVID-19, highly cited publications and the international collaboration network.

mHealth apps for COVID-19 are gaining more and more importance due to their influential role in controlling the COVID-19 epidemic. Using bibliometric analysis, the study contributes to defining the knowledge structure of global research in mHealth apps for COVID-19 as a new, interdisciplinary area of research that has not previously been studied. Therefore, the study results and the comprehensive picture obtained about research in mHealth apps for COVID-19, especially at the level of Internet of Things (IoT) and artificial intelligence applications, make it an effective supplement to the expert evaluation in the field.