AI Article Synopsis
- This study examined how knowledge sharing (KS) relates to knowledge hiding (KH) among Chinese medical undergraduates, influenced by study climate (SC), interpersonal trust (IT), and sharing intention (SI).
- Conducted on 761 students from two medical colleges in Wuhan, the research utilized path analysis to explore these relationships across different levels of academic performance.
- Results indicated that while KS and KH are weakly related, IT positively impacted KS and negatively impacted KH, with SC exerting indirect effects through IT and SI, affecting students differently based on their academic performance.
Article Abstract
Purpose: This study aimed to explore the relationship between knowledge sharing (KS) and knowledge hiding (KH), and the influence of study climate (SC), interpersonal trust (IT) and sharing intention (SI) on KS and KH among Chinese medical undergraduates within the same framework.
Method: A cross-sectional study was conducted among 761 undergraduates from two medical colleges in Wuhan, China. Measurements included five scales on KS, KH, SC, IT and SI. Three path analysis was performed using a structural equation model (SEM) to examine the influence of SC, IT, and SI on KS and KH for medical students with different academic performance levels.
Results: The mean scores for SC, IT, SI, KS and KH of medical students were 3.79 ± 0.67, 3.92 ± 0.62, 4.05 ± 0.64, 3.68 ± 0.68 and 1.64 ± 0.67, respectively. Path analysis showed that KS and KH were weakly related among three academic performance subgroups (coefficients ranging from -0.193 to -0.112). IT was significantly positively associated with KS (β = 0.268, 0.112 and 0.227, respectively, all P<0.05) among all three subgroups, while IT was negatively associated with KH among medical student with good and average academic performance (β = -0.200 and -0.117, respectively, all P < 0.05). SC could indirectly positively influence KS and negatively influence KH through IT and SI regardless of their academic performance; SC had no direct influence on KH, while only a weak negative influence on KS was identified in the average academic performance group (β=-0.132, P < 0.05). For students with good, below average, and average performance, the models explained 48.7%, 36.3% and 42.0% of the variance in KS, and 34.6%,17.0% and 26.3% of those in KH, respectively.
Conclusions: KS and KH could coexist among medical students in China. The influence of SC and IT on KS and KH varied among medical students with different academic performance. The results demonstrated that educators could develop knowledge management strategies targeting students with different academic performance.
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|---|---|
| http://www.ncbi.nlm.nih.gov/pmc/articles/PMC11590218 | PMC |
| http://dx.doi.org/10.1186/s12909-024-06364-4 | DOI Listing |
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