Dies ist eine Übersichtsseite mit Metadaten zu dieser wissenschaftlichen Arbeit. Der vollständige Artikel ist beim Verlag verfügbar.
Analysis on compliance and influencing factors of postoperative function exercise in patients with tibial plateau fractures
0
Zitationen
4
Autoren
2016
Jahr
Abstract
Objective To investigate the compliance and influencing factors of postoperative function exercise in patients with tibial plateau fractures. Methods By convinience sampling method, 60 patients who were diagnosed with tibial plateau fracturesand and needed to receive postoperative function exercise were surveyed at the third day after surgery by general information, compliance of functional exercise, numerical rating scale (NRS), self-rating anxiety scale (SAS) and self-rating depression scale (SDS). Influencing factors of compliance in patients with postoperative function exercise were analyzed by Logistic regression anslysis. Results Among 60 postoperative patients with tibial plateau fractures, there were 28 patients of noncompliance, which accounted for 46.7%, while there were 32 patients of compliance and that accounted for 53.35%. The Logistic regression analysis showed that: anxiety (OR=1.71, 95%CI 1.54~1.90), depression (OR=3.01, 95%CI 1.99~4.54), pain (OR=1.99, 95%CI 1.65~2.38), marital status (OR=1.69, 95%CI 1.22~2.32) were seperated dangerous factors that would affect the early postoperative function exercise of patients with tibial plateau fractures, and cultural degree (OR=0.89, 95%CI 0.81~0.94) was its protective factor. Conclusions The compliance of early functional exercise in patients with tibial plateau fractures is not high, and anxiety, depression, pain, marital status are influencing factors of compliance. Health education and psychological intervention should be strengthened to improve the compliance and rehabilitation effect. Key words: Tibial plateau fracture; Postoperative function exercise; Compliance; Influencing factors
Ähnliche Arbeiten
Explainable Artificial Intelligence (XAI): Concepts, taxonomies, opportunities and challenges toward responsible AI
2019 · 8.644 Zit.
Stop explaining black box machine learning models for high stakes decisions and use interpretable models instead
2019 · 8.550 Zit.
High-performance medicine: the convergence of human and artificial intelligence
2018 · 8.061 Zit.
BioBERT: a pre-trained biomedical language representation model for biomedical text mining
2019 · 6.850 Zit.
Proceedings of the 19th International Joint Conference on Artificial Intelligence
2005 · 5.781 Zit.