Background Digital health is growing at a rapid pace, and digital health literacy has attracted increasing attention from the academic community. Objective The purposes of this study are to conduct a systematic bibliometric analysis on the field of digital health literacy and to understand the research context and trends in this field. Methods Methods: A total of 1955 scientific publications were collected from the Web of Science core collection. Institutional co-operation, journal co-citation, theme bursting, keyword co-occurrence, author co-operation, author co-citation, literature co-citation, and references in the field of digital health literacy were analyzed using the VOSviewer and CiteSpace knowledge mapping tools. Results The results demonstrate that the United States has the highest number of publications and citations in this field. The University of California System was first in terms of institutional contributions. The Journal of Medical Internet Research led in the number of publications, citations, and co-citations. Research areas of highly cited articles in the field of digital health literacy mainly include the definition and scale of health literacy, health literacy and health outcomes, health literacy and the digital divide, and the influencing factors of health literacy. Conclusions We summarized research progress in the field of digital health literacy and reveal the context, trends, and trending topics of digital health literacy research through statistical analysis and network visualization. We found that digital health literacy has a significant potential to improve health outcomes, bridge the digital divide, and reduce health inequalities. Our work can serve as a fundamental reference and directional guide for future research in this field.

PurposeExisting studies on the relationship between task description and task performance are insufficient, with many studies considering description length rather than content to measure quality or only evaluating a single aspect of task performance. To address this gap, this study analyzes the linguistic styles of task descriptions from 2,545 tasks on the Taskcn.com crowdsourcing platform.Design/methodology/approachAn empirical analysis was completed for task description language styles and task performance. The paper used text mining tool Simplified Chinese Linguistic Inquiry and Word Count to extract eight linguistic styles, namely readability, self-distancing, cognitive complexity, causality, tentative language, humanizing personal details, normative information and language intensity. And it tests the relationship between the eight language styles and task performance.FindingsThe study found that more cognitive complexity markers, tentative language, humanized details and normative information increase the quantity of submissions for a task. In addition, more humanized details and normative information in a task description improves the quality of task. Conversely, the inclusion of more causal relationships in a task description reduces the quantity of submissions. Poorer readability of the task description, less self-estrangement and higher language intensity reduces the quality of the task.Originality/valueThis study first reveals the importance of the linguistic styles used in task descriptions and provides a reference for how to attract more task solvers and achieve higher quality task performance by improving task descriptions. The research also enriches existing knowledge on the impact of linguistic styles and the applications of text mining.

With the outbreak of the 2019 coronavirus (COVID-19) pandemic, the issue of increasing health disparities has received a great deal of attention from scholars and organizations. This study analyzes 2282 papers on COVID-19-related health disparities that have been retrieved from the WOS database, with 58,413 references. Using bibliometric analysis and knowledge mapping visualizations, the paper focuses on the academic structure and research trends by examining the research distribution of countries, journals and authors, keywords, highly cited articles, and reference co-citation. The results show that the United States has contributed the most, and the International Journal of Environmental Research and Public Health has published the largest number of papers on this topic. As for the core authors, Michael Marmot is the most productive. Issues such as racial health, mental health, and digital health disparities have been the trending topics of the COVID-19-related health disparities. The research directions include the features, factors, and interventions of health disparities under the influence of COVID-19. As such, this study provides literature support and suggestions to investigate COVID-19-related health disparities. The findings of the paper also remind public health regulators to consider factors of health disparities when developing long-term public health regulatory policies related to the pandemic.

Financialization is a phenomenon that concerned the increasing development of finance sector and has received much attention since the 20th century. Especially after the financial crisis in 2008, the financial development has entered a new stage, and the finance sector has become a dominant and important industrial sector in most of economies. The academic community has conducted extensive discussions on it and the researches on financialization involve a wide range theme. Therefore, this paper mainly reviews the typical literature which focused on financialization since 2008. It mainly covers six aspects, including the definition and characteristics of financialization, the motivation and realization mechanism of financialization, and four pairs of relationships including the relationship of financialization and financial crisis, financialization and economic growth, financial and industrial development, financialization and financial supervision. This literature extends a more comprehensive understanding of the development and impact of financialization and shows us the research fields that we could do more research on.

Crowdsourcing has attracted significant attention in the past decade because it has more competitive advantages than traditional methods for mobilizing distributed labor and utilizing innovation. Crowdsourcing contests are one of the most popular and effective crowdsourcing modes. Reasonable task rewards and duration are the key factors for seekers to attract solvers who can efficiently participate in the crowdsourcing contest task. Previous studies have mainly focused on task results to analyze solvers’ participation behavior in crowdsourcing contests, but have paid little attention to the task process, and there have been conflicting conclusions regarding the impact of task rewards and duration on solvers’ participation behavior and the performance of crowdsourcing contests. In view of this gap, this study collected 2706 logo design task data points from 2015–2017 on an online crowdsourcing platform and measured the performance of solvers’ participation behavior in two stages. The participation time was used to represent the performance of solvers’ participation behavior in the task process, while the number of submissions of solutions was used to represent the performance of participation behavior in the task result. The results show that task rewards and duration have an inverted U-shaped effect on the number of submissions, money rewards have a positive impact on participation time, and duration has an inverted U-shaped relationship with participation time. This study proposes the nonlinear effects of task rewards and duration on participation behavior and explains the reason for the conflicting results of previous studies. This paper also expands upon existing research by using solvers’ participation time in the task process to measure the performance of solvers’ participation behavior.