Indexes for estimating the overall reliability of a test in the framework of knowledge space theory (KST) are proposed and analyzed. First, the possibility of applying in KST the existing classical test theory (CTT) methods, based on the ratio between the true score variance and the total variance of the measure, has been explored. However, these methods are not suitable because in KST error and true score are not independent. Therefore, two new indexes based on the concepts of entropy and conditional entropy are developed. One index is used to estimate the reliability of the response pattern given the knowledge state, while the second one refers to the reliability of the estimated knowledge state of a person. Some theoretical considerations as well as simulations and an empirical example on real data are provided within a study of the behavior of these indexes under a certain number of different conditions.

Although multiple bibliometric studies have been conducted to analyze publications on various topics within tourism, little attention has been dedicated to systematically analyzing scholarly production on the topic of tourism sustainability. Consequently, this paper aims to conduct a comprehensive bibliometric and systematic review of tourism sustainability. The collected data include 6326 publications retrieved from the Scopus database. The bibliometric technique consists of two major analyses: one on the domain (levels of analysis) and one on knowledge structures. The results indicated a remarkable evolution of tourism sustainability research involving authors, sources, and publications on this subject. Several associations and nations made significant contributions to this theme. Moreover, science mapping approaches were used to thoroughly grasp tourism sustainability-related research\'s social, intellectual, and conceptual structure. By giving in-depth overviews and insights connected to tourism sustainability and its knowledge structures, this review article has various implications for scientific study and practice.

Exposure to family violence (EFV) is proposed as a relevant antecedent of child-to-parent violence (CPV). However, both previous research and practitioner experience suggest that not all cases of CPV involve EFV. This study aimed to identify profiles of adolescents according to their degree of involvement in CPV and their EFV. A sample of 1647 adolescents (mean age = 14.30, SD = 1.21; 50.5% boys) completed measures of CPV, witnessing family violence, victimization by parents, permissive parenting, parental warmth, and several measures of cognitive and emotional characteristics. Latent profile analyses based on measures of CPV and family characteristics supported a four-profile solution. Profile 1 (82.2%) consisted of adolescents with very low scores on both CPV and exposure to family violence. Profile 2 (6.2%) was characterized by medium scores on psychological CPV and high EFV. Profile 3 (9.7%) was characterized by severe psychological CPV and very low EFV. Profile 4 (1.9%) included adolescents with the highest scores on CPV, including physical violence, and high EFV. These profiles were found to differ from each other according to several cognitive and emotional variables of the adolescents. Therefore, not all CPV profiles were associated with a history of EFV. The obtained profiles have implications for interventions.

The organization of medical knowledge is reflected in language and can be studied from the viewpoints of semantics and prototype theory. The purpose of this study is to analyze student verbalizations during an Objective Structured Clinical Examination (OSCE) and correlate them with test scores and final medical degree (MD) scores. We hypothesize that students whose verbalizations are semantically richer and closer to the disease prototype will show better academic performance.
We conducted a single-center study during a year 6 (Y6) high-stakes OSCE where one probing intervention was included at the end of the exam to capture students\' reasoning about one of the clinical cases. Verbalizations were transcribed and coded. An assessment panel categorized verbalizations regarding their semantic value (Weak, Good, Strong). Semantic categories and prototypical elements were compared with OSCE, case-based exam and global MD scores.
Students with Semantic \'Strong\' verbalizations displayed higher OSCE, case-based exam and MD scores, while the use of prototypical elements was associated with higher OSCE and MD scores.
Semantic competence and verbalizations matching the disease prototype may identify students with better organization of medical knowledge. This work provides empirical groundwork for future research on language analysis to support assessment decisions.

UNASSIGNED: Pulmonary embolism (PE) is a popular area of research in the field of respiratory medicine. We performed a bibliometric analysis based on PubMed database to characterize the distribution pattern of literature and knowledge structures related to PE.
UNASSIGNED: Literature pertaining to PE from January 1, 2017, to December 31, 2021, was retrieved from the PubMed database. Bibliographic information was generated using the Bibliographic Item Co-Occurrence Matrix Builder (BICOMB). The visualization matrix was established using gCLUTO software. Strategic diagram analysis was performed using GraphPad Prism 9 software. Social network analysis (SNA) was generated using Ucinet6.0 and NetDraw 2.084 software.
UNASSIGNED: Out of all the retrieved MeSH terms and subheadings, 52 MeSH terms/MeSH subheadings with a high frequency were found, and hot subjects were sorted into 6 clusters. The strategy diagram showed that the epidemiology, etiology, and drug therapy of PE were well advanced. In contrast, studies on diagnostic imaging, pathology, and complications of PE were still immature and offered potential research space. Social network analysis showed that marginal topics such as surgical treatment of pulmonary hypertension, prevention and control of postoperative complications, and metabolism and analysis of fibrin/fibrinogen degradation products were emerging research hotspots.
UNASSIGNED: Objective analysis of the research developments in the field of PE can provide intuitive knowledge structure for researchers and clinicians. Analysis of the research hotspots related to PE is helpful for researchers and clinicians by highlighting future research directions.

[This corrects the article DOI: 10.3389/fonc.2022.854927.].

This study seeks to explore the different knowledge structures in the sphere of educational research into COVID-19 during 2020. Using bibliometric methods, analysis was performed of a sample of 308 scientific articles retrieved from the Web of Science database. Using different data analysis techniques combining co-occurrence analysis, co-citation analysis and factorial analysis, All Keywords and Keywords Plus were used to achieve the main research objective: identification of the main themes and trends of production in the sphere of educational research into COVID-19. The main findings of this study in terms of the conceptual structure show that analysis of the centrality and density of the thematic trends points to a generalised structural change in the entire educational system towards methodological teaching-learning procedures oriented towards distance education. As for the intellectual structure, among the host of authors and sources of information involved only a select few have a greater influence on the scientific community. Finally, in terms of social structure, there is limited collaboration between authors and institutions from different countries. However, this collaboration is more intense within countries themselves and in terms of their own production, with the USA being the country with the strongest links.

UNASSIGNED: In recent years, among the available tools, the concurrent application of Artificial Intelligence (AI) has improved the diagnostic performance of breast cancer screening. In this context, the present study intends to provide a comprehensive overview of the evolution of AI for breast cancer diagnosis and prognosis research using bibliometric analysis.
UNASSIGNED: Therefore, in the present study, relevant peer-reviewed research articles published from 2000 to 2021 were downloaded from the Scopus and Web of Science (WOS) databases and later quantitatively analyzed and visualized using Bibliometrix (R package). Finally, open challenges areas were identified for future research work.
UNASSIGNED: The present study revealed that the number of literature studies published in AI for breast cancer detection and survival prediction has increased from 12 to 546 between the years 2000 to 2021. The United States of America (USA), the Republic of China, and India are the most productive publication-wise in this field. Furthermore, the USA leads in terms of the total citations; however, hungry and Holland take the lead positions in average citations per year. Wang J is the most productive author, and Zhan J is the most relevant author in this field. Stanford University in the USA is the most relevant affiliation by the number of published articles. The top 10 most relevant sources are Q1 journals with PLOS ONE and computer in Biology and Medicine are the leading journals in this field. The most trending topics related to our study, transfer learning and deep learning, were identified.
UNASSIGNED: The present findings provide insight and research directions for policymakers and academic researchers for future collaboration and research in AI for breast cancer patients.

UNASSIGNED: Wayfinding in complex environments is a public issue facing the world and has become a hot research topic in recent years. This article reviews and quantitatively analyzes the literature on wayfinding in healthcare facilities and collates the research trends and hotspots in this area.
UNASSIGNED: The article used bibliometric analysis to search keywords in the Scopus database in the TITLE-ABS-KEY format. In total, 2359 articles were finally collated between 1974 and 2020 after three screening exercises, and a co-citation analysis was conducted by VOSviewer literature visualization analysis software.
UNASSIGNED: Research in the worldwide literature on wayfinding in healthcare facilities has grown steadily year on year since 2002. Computer science (21.5%) and social science (15.5%) are the most common subject categories, with the United States (N = 767) accounting for the largest proportion of research. \"Lecture Notes In Computer Science Including Subseries Lecture Notes In Artificial Intelligence And Lecture Notes In Bioinformatics\" is the most active journal in terms of publications (N = 169).
UNASSIGNED: Wayfinding cognition, wayfinding behavior, and individual and group differences are currently the focus of research in the field of healthcare facilities. Future research on wayfinding in healthcare facilities will further investigate intelligent assistive technologies and universal designs such as universal signage systems. In addition, cross-cultural-based wayfinding research is a hot topic for future studies where the boundaries of research are broadened and have practical value.

In cognitive diagnostic assessment a property of the Q-matrix, usually referred to as completeness, warrants that the cognitive attributes underlying the observed behaviour can be uniquely assessed. Characterizations of completeness were first derived under the assumption of independent attributes, and are currently under investigation for interdependent attributes. The dominant approach considers so-called attribute hierarchies, which are conceptualized through a partial order on the set of attributes. The present paper extends previously published results on this issue obtained for conjunctive attribute hierarchy models. Drawing upon results from knowledge structure theory, it provides novel sufficient and necessary conditions for completeness of the Q-matrix, not only for conjunctive models on attribute hierarchies, but also on more general attribute structures.