Full
Outline
To explore the nurses' behavioral intentions and influencing factors of using clinical decision support systems,and to construct a corresponding structural equation model.
A theoretical model of behavior intentions in clinical decision support system was initially constructed by adding personality trait factors to the UTAUT model.A convenience sampling method was used to investigate 301 clinical nurses from a tertiary grade A hospital in Guangdong province in June 2025 through the Chinese Big Five Personality Questionnaire,Behavioral Intention for Clinical Nurses in Clinical Decision Support System Questionnaire,and a self-designed survey questionnaire.The data were statistically analyzed by using SPSS 26.0 software.The structural equation modeling analysis was conducted by the lavaan package in R 4.2.2 software.The maximum likelihood estimation method was used to evaluate the model fit and path coefficient significance test.
The nurses' behavioral intentions of using the clinical decision support system was at a moderate to high level.The structural equation model constructed had an overall good fit.Social influence,performance expectations,effort expectations,age,and openness all had a positive impact on behavioral intentions of nurses in clinical decision support systems,with path coefficients of 0.507,0.217,0.205,0.218,and 0.040,respectively(all P<0.05).Extraversion had a positive promoting effect on effort expectations,performance expectations,and social impact,with path coefficients of 0.072,0.171,and 0.083,respectively(all P<0.001),and showed a negative impact on behavioral intention(β=-0.028,P<0.05).Openness had a positive impact on society(β=0.047,P<0.001).
The model constructed in this study could effectively predict the behavioral intentions of nurses in clinical decision support systems.Improving social influence,performance expectations,effort expectations,age growth,and open personality could significantly enhance the nurses' behavioral intentions of using clinical decision support systems.It is recommended that external environmental shaping and individual trait differences should be taken into account when promoting clinical decision support systems.
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| 科 Family | 属数 Number of genus | 种数 Number of species | 占总种数比例 Percentage of total species (%) | 属 Genus | 种数 Number of species | 占总种数比例 Percentage of total species (%) |
|---|---|---|---|---|---|---|
| 鹅膏菌科Amanitaceae | 2 | 11 | 5.26 | 鹅膏菌属 Amanita | 10 | 4.78 |
| 小菇科 Mycenaceae | 2 | 12 | 5.74 | 丝盖伞属 Inocybe | 5 | 2.39 |
| 多孔菌科 Polyporaceae | 8 | 14 | 6.70 | 蜡蘑属 Laccaria | 5 | 2.39 |
| 红菇科 Russulaceae | 3 | 23 | 11.00 | 小皮伞属 Marasmius | 6 | 2.87 |
| 小菇属 Mycena | 11 | 5.26 | ||||
| 光柄菇属 Pluteus | 5 | 2.39 | ||||
| 红菇属 Russula | 17 | 8.13 | ||||
| 栓菌属 Trametes | 5 | 2.39 |
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