Research on education of graduates of bonded medical program for rural health in China: A systematic review
Notice bibliographique
Résumé
The government funded bonded medical program for rural health for graduates of bonded medical program for rural health is an essential strategy to alleviate the shortage of healthcare professionals in rural areas of China and to enhance the quality of the primary care professionals. However, previous studies have lacked a comprehensive analysis of the educational methods, current state, and effectiveness across various institutions. This study aims to examine the development, research quality, and future trends in the education of graduates of rural oriented general practice education program from 2010 to 2023, providing insights for future initiatives. Literature on the training of graduates of rural oriented general practice education program published between January 1, 2010, and December 31, 2023, was retrieved from seven databases: CNKI, Wanfang, VIP, PubScholar, PubMed, Web of Science, and the Cochrane Library. Two researchers independently screened the literature, extracted data according to inclusion and exclusion criteria, and assessed the quality of studies using the Medical Education Research Study Quality Instrument (MERSQI) and the Newcastle-Ottawa Scale for Education (NOS-E). Descriptive analysis was performed to summarize and interpret the findings. A total of 37 studies were included, of which 36 were in Chinese and 1 in English. The most common research design was the pre-post test control group (46 %), followed by single-group post-test (22 %) and randomized controlled post-test (22 %). Only 8 % of studies employed a single-group pre-post test design. Of the studies, 97 % focused on undergraduate education, with the primary areas of focus being course adjustments (89 %), teaching method modifications (81 %), and the construction of training models(8 %). Notably, 8 % of training model studies and 19 % of course adjustment studies included courses specifically aimed at rural areas, primary care, or general practice. Outcome evaluations were primarily centered on student feedback (70 %) and improvements in knowledge and skills (86 %), with minimal attention given to behavioral changes (3 %) or benefits to patients and healthcare facilities (3 %). Overall, the quality of the studies was moderate, with a mean MERSQI score of 10.4±2.4 (maximum 14.0). Factors such as sample size, validity of evaluation tools, and outcome indicators contributed to lower scores. The NOS-E score averaged 2.5±1.5 (maximum 5.0), with low scores primarily due to control group comparability and blinding. Although there has been an increase in research on the education and training of graduates of rural oriented general practice education program, the overall quality of the research remains low. Limitations such as insufficient cross-institutional and cross-regional studies, lack of research focusing on the unique characteristics of targeted training, and limited attention to postgraduate and continuing education remain prevalent. Future research should focus on enhancing multi-institutional cooperation, improving research design quality, establishing a unified evaluation system with a focus on rural and general practice education, and integrating continuous curriculum that includes postgraduate and continuing education.
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Comment cette classification a été obtenuedéplier
Prédiction machine sur la base complète
Imitation des enseignantsNi prévalence calibrée, ni vérité terrain. Validation humaine à venir. Le volet Gemma est une étiquette directe du modèle pour chaque travail de la base, lue sur la notice réduite au titre. Le volet Codex est un classifieur appris des 10 348 étiquettes directes de Codex et calibré sur les taux pondérés de l'échantillon; les champs sans appui suffisant ne portent aucun appel Codex. Le mode candidate est l'union des deux volets; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont pas des étiquettes humaines.
Scores du classifieur distillé par catégorie (deux têtes)
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,010 | 0,033 |
| Méta-épidémiologie (sens strict) | 0,001 | 0,001 |
| Méta-épidémiologie (sens large) | 0,008 | 0,005 |
| Bibliométrie | 0,012 | 0,014 |
| Études des sciences et des technologies | 0,001 | 0,001 |
| Communication savante | 0,002 | 0,003 |
| Science ouverte | 0,002 | 0,001 |
| Intégrité de la recherche | 0,002 | 0,001 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,004 | 0,000 |
Scores machine (provisoires)
Les deux têtes enseignantes du modèle étudiant, lues sur ce travail. Un score ordonne la base pour la relecture; il n'affirme jamais une catégorie, et le statut de validation accompagne chaque rangée tel quel.
Scores de référence d'un modèle non mature (critères de maturité non atteints, 7 itérations). Un score ordonne; il n'affirme jamais une catégorie.
score_only:v0-immature-baseline · tel quel depuis la passe de notation : score_only signifie que le nombre peut ordonner les travaux, et qu'aucune étiquette de catégorie n'en découleClassification
machine, non validéePrédiction automatique; un appel candidat d’une seule source (Gemma direct ou Codex distillé), pas un consensus.
Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».