Current Trends in Research on Confidence in the Healthcare System
Bibliographic record
Abstract
The sphere of trust in the health care system, which is actively developing in covid and postcovid conditions, is accompanied by a significant increase in the amount of scientific literature that requires detailed analysis. Accordingly, the primary purpose of this study is to conduct a multilevel bibliometric analysis of publications on trust in the health care system. This will provide a global picture of the phenomenon to determine the dynamic aspects of trends from a statistical point of view, using content-contextual, descriptive, comparative, cluster and evolutionary-temporal analysis. The methodological basis of the study is a set of scientific publications indexed in the scientometric database Scopus, which was analyzed using analytical tools ScopusTools and VOSViewer. A total of 1,134 articles published between 1999 and the second quarter of 2022 were analyzed. The results show a growing trend in the spread of research on trust in the health care system. According to the results, five stages of scientific development of the researched subject were identified, in particular, the last one is characterized by extremely high research interest and covers the period from 2020 to the second quarter of 2022. The geographic center of research is the United Kingdom, and a significant contribution to the development of trust research in the health care system has been made by scientists in the United States, Australia and Canada. The analysis of the sectoral structure of financial sector trust research shows a weak diversification, and a comparative analysis of publications shows a close link between the concepts of trust in the health care system, vaccination and COVID-19. Cluster analysis identified five main groups of research. The results of evolutionary-temporal analysis show that at the beginning of scientific interest, research focused on interpersonal relationships between doctors and patients, and the latest area of research is to study the impact of trust on public decision-making on vaccination and other preventive measures. Thus, the study results showed that trust is one of the most crucial components in ensuring an effective health policy.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.009 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".