Effect of protective motivation-based theory nursing model on patients with chronic gastroparesis
Objective To explore the effect of the protective motivation-based theory nursing model on the health anxiety metacognition and premonitory sadness of patients with chronic gastroparesis.Methods 98 patients with chronic gastroparesis admitted to the First People's Hospital of Pingdingshan from May 2020 to May 2022 were selectedas the study subjects,they were divided into a control group and an observation group accordingto the principle of comparable baseline data between groups,with 49 cases in each group.The control group received routine nursing model intervention,and the observation group received nursing model intervention based on the theory of protective motivation on the basis of the control group.To observe the recovery of gastroparesis symptoms(GCSI)before the intervention,3 days after the intervention,1 week after the intervention,and 2 weeks after the intervention.To compare the health anxiety metacognitive ability(health anxiety meta cognitive scale),the Anticipatory Grief Scale(AGS),and quality of life(SF-36)before and afterthe intervention.Results During the intervention,the GCSI score in both groups showed a decrease trend(P<0.05).After 2 weeks of intervention,the GCSI score in the observation group was lower than that in the control group(P<0.05).After the intervention,the health anxiety metacognitive scale score and SF-36 score in both groupswere higher than that before the intervention(P<0.05),the observation group was higher than that in the control group(P<0.05),the AGS score in both groupswas lower than that before the intervention(P<0.05),and the observation group was lower than that in the control group(P<0.05).Conclusion The nursing model based on the protection motivation theory can improve the health anxiety metacognition level of patients with chronic gastroparesis,reduce the degree of premonitory sadness,accelerate the recovery of gastroparesis symptoms,and improve the quality of life of patients.
万方数据
维普
