MATERIALS AND METHODS:  The search was performed without any restriction on the study design, publication year, or language using the Web of Science (WoS) group of Clarivate Analytics enabling the search through "All Databases." Based on the citation count as available in WoS, the articles were sorted in a descending manner. Information regarding each article was then extracted, which included its authorship, counts of citation (in other databases), citation density, current citation index (2019), publication year, country of publication, journal of article, evidence level based on study design, and keywords description.

RESULTS:  The count of citation for each article varied in each database, that is, 175 to 2,003 in WoS, 89 to 1,981 in Scopus, and 126 to 3,492 when searched in Google Scholar. The highest number of articles (n = 10) related to dental caries were published in 2004. A total of 301 authors made valuable contributions to this field, out of which J.D. Featherstone had coauthored 6 articles. A significant negative correlation (p < 0.01) was found between the age of the article and the citation density (r =-0.545). However, a nonsignificant correlation (p = 0.952) occurred between the age of publication and the citation count (r = 0.006).

METHODS: The development of the MUAPHQ C-19 was conducted in two stages. Stage I resulted in the generation of the instrument's items (development), and stage II resulted in the performance of the instrument's items (judgement and quantification). Six-panel experts related to the study field and ten general public participated to evaluate the validity of the MUAPHQ C-19. The content validity index (CVI), content validity ratio (CVR) and face validity index (FVI) were analysed using Microsoft Excel.

RESULTS: There were 54 items and four domains, namely the understanding, attitude, practice and health literacy towards COVID-19, identified in the MUAPHQ C-19 (Version 1.0). The scale-level CVI (S-CVI/Ave) for every domain was above 0.9, which is considered acceptable. The CVR for all items was above 0.7, except for one item in the health literacy domain. Ten items were revised to improve the item's clarity, and two items were deleted due to the low CVR value and redundancy, respectively. The I-FVI exceeded the cut-off value of 0.83 except for five items from the attitude domain and four from the practice domains. Thus, seven of these items were revised to increase the clarity of items, while another two were deleted due to low I-FVI scores. Otherwise, the S-FVI/Ave for every domain exceeded the cut-off point of 0.9, which is considered acceptable. Thus, 50-item MUAPHQ C-19 (Version 3.0) was generated following the content and face validity analysis.

METHOD: The primary data source of the study consists of excerpts of verbal expressions within the familial context. The provenance of the locational data can be traced to a familial unit with a cultural legacy deeply embedded in Javanese customs. The data were collected using observation and participation methodologies, employing advanced techniques of recording and note taking. The data were categorized and characterized to identify the various data types and formats. The tabulated results of classification and typification are presented to triangulate theory through expert validation and justification of theories. The method of contextual analysis was utilized to conduct the data analysis that relies on the pragmatic context.

RESULTS: The study's findings indicate the following: The Javanese language encompasses various modes of pseudo-directive utterances, such as commanding, ordering, suggesting, insinuating, and recommending. In addition, the Javanese language encompasses pseudo-directive pragmatics such as warning, prohibiting, reminding, suggesting, and commanding.

METHODS: Structural Equation Modeling (SEM) is utilized for analysis, enabling the creation of a metric set to explore intangibles such as perfectionism, learning self-efficacy, motivation, study habits, cultural influences, and introspection. The research utilizes a diverse sample from multiple universities across different regions of China, incorporating demographic factors to encompass the varied characteristics within the EFL learner community.