RESUMEN
AIMS AND OBJECTIVES: To compare the results of haematology, blood chemistry and coagulation tests between two blood sampling methods via venipuncture and peripheral venous catheter. BACKGROUND: Laboratory results of the previous studies on blood sampling methods through peripheral venous catheter versus venipuncture are inconsistent. Therefore, it is necessary to better understand the discrepancies between the two blood sampling methods and to provide evidence for practice. DESIGN: Systematic literature review and meta-analysis were conducted in accordance with the PRISMA reporting guideline. METHODS: Reviewed articles for this study were searched through database, including PubMed, Cochrane Library, EMBASE, SCOPUS, Web of Science, ProQuest Dissertations & Theses, CINAHL (Cumulative Index to Nursing and Allied Health Literature) and ERIC (Educational Resource Information Centre). Hand-searching was also conducted. RESULTS: We finally identified 17 studies for a systematic review, and 10 studies out of them were selected for a meta-analysis. A total of 678 participants were included in the meta-analysis. Overall, there was no significant difference in haematology, blood chemistry and coagulation test values between two sampling methods via venipuncture and peripheral venous catheter. CONCLUSION: Findings of this study provide substantial evidence that most blood tests via venipuncture and peripheral venous catheter would not be different. Patients will be benefitted by reducing the number of venipuncture if a series of blood tests can be conducted by using peripheral venous catheter. Thus, healthcare providers may refer to more reliable laboratory results on using peripheral venous catheter for without increasing the risk of bleeding events and pain on blood sampling sites due to frequent phlebotomies. RELEVANCE TO CLINICAL PRACTICE: The results of this study will be a good evidence to decide blood sampling methods in clinical practice.
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Cateterismo Periférico/métodos , Flebotomía/métodos , HumanosRESUMEN
Self-management behavior is an important component for successful pain management in individuals with chronic low back pain. Motivation has been considered as an effective way to change behavior. Because there are other physical, social, and psychological factors affecting individuals with pain, it is necessary to identify the main effect of motivation on self-management behavior without the influence of those factors. The purpose of this study was to investigate the effect of motivation on self-management in controlling pain, depression, and social support. We used a nonexperimental, cross-sectional, descriptive design with mediation analysis and included 120 participants' data in the final analysis. We also used hierarchical multiple regression to test the effect of motivation, and multiple regression analysis and Sobel test were used to examine the mediating effect. Motivation itself accounted for 23.4% of the variance in self-management, F(1, 118) = 35.003, p < .001. After controlling covariates, motivation was also a significant factor for self-management. In the mediation analysis, motivation completely mediated the relationship between education and self-management, z = 2.292, p = .021. Motivation is an important part of self-management, and self-management education is not effective without motivation. The results of our study suggest that nurses incorporate motivation in nursing intervention, rather than only giving information.
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Enfermedad Crónica/psicología , Dolor de la Región Lumbar/rehabilitación , Motivación , Autocuidado , Anciano , Estudios Transversales , Femenino , Humanos , Dolor de la Región Lumbar/terapia , Masculino , Manejo del Dolor/métodos , Apoyo Social , Encuestas y CuestionariosRESUMEN
The authors reported the association between motivation and self-management behavior of individuals with chronic low back pain after adjusting control variables using hierarchical multiple regression (). This article describes details of the hierarchical regression applying the actual data used in the article by , including how to test assumptions, run the statistical tests, and report the results.