Wenqi Mok1, Wenru Wang2, Simon Cooper3, Emily Neo Kim Ang2, Sok Ying Liaw2. 1. Khoo Teck Puat Hospital, Singapore 768828, Singapore. 2. Alice Lee Centre for Nursing Studies, Yong Loo Lin School of Medicine, National University of Singapore, Singapore 117597, Singapore. 3. School of Nursing, Midwifery and Healthcare, Federation University Australia, Ballarat VIC 3353, Australia School of Nursing, The University of Hong Kong, Pokfulam, Hong Kong School of Nursing and Midwifery, University of Brighton, Brighton BN1 9PH, United Kingdom.
Abstract
OBJECTIVE: To develop and determine the psychometrics properties of an instrument (V-scale) and to explore nurses' attitudes towards vital signs monitoring in the detection of clinical deterioration in general wards. DESIGN: Scale development with psychometric testing and a descriptive quantitative survey. SETTING: Tertiary acute care hospital. PARTICIPANTS: A total of 614 general ward nurses. FINDINGS: Principal component analysis revealed a 16-item instrument in a five-factor solution (key indicators, knowledge, communication, workload and technology) that explained 56.27% of the variance. The internal consistency was sufficient with Cronbach's alpha of 0.71 and strong item subscale correlations (0.56-0.89). The test-retest reliability was adequate with an Intraclass Correlation Coefficient (ICC) of 0.85. Many nurses (56.9%) erroneously perceived blood pressure changes as the first indicator of deterioration, and 46% agreed that an altered respiratory rate was the least important indicator. Most nurses (59.8%) also reported relying on oxygen saturation to evaluate respiratory dysfunction, and 27.4% indicated that they make quick estimates of the respiratory rate. Current practices for vital signs monitoring were considered to be time consuming (21.0%) and overwhelming (35.3%). Nurses' attitudes were most significantly influenced by whether they had a degree qualification followed by whether they worked in a general ward with a specialty and had >5 years of experience. CONCLUSIONS: This exploratory study provides evidence for the psychometric properties of the V-scale. It reveals a need for continuous professional development to improve ward nurses' attitudes towards vital signs monitoring. Vital signs monitoring needs to be prioritized in workload planning.
OBJECTIVE: To develop and determine the psychometrics properties of an instrument (V-scale) and to explore nurses' attitudes towards vital signs monitoring in the detection of clinical deterioration in general wards. DESIGN: Scale development with psychometric testing and a descriptive quantitative survey. SETTING: Tertiary acute care hospital. PARTICIPANTS: A total of 614 general ward nurses. FINDINGS: Principal component analysis revealed a 16-item instrument in a five-factor solution (key indicators, knowledge, communication, workload and technology) that explained 56.27% of the variance. The internal consistency was sufficient with Cronbach's alpha of 0.71 and strong item subscale correlations (0.56-0.89). The test-retest reliability was adequate with an Intraclass Correlation Coefficient (ICC) of 0.85. Many nurses (56.9%) erroneously perceived blood pressure changes as the first indicator of deterioration, and 46% agreed that an altered respiratory rate was the least important indicator. Most nurses (59.8%) also reported relying on oxygen saturation to evaluate respiratory dysfunction, and 27.4% indicated that they make quick estimates of the respiratory rate. Current practices for vital signs monitoring were considered to be time consuming (21.0%) and overwhelming (35.3%). Nurses' attitudes were most significantly influenced by whether they had a degree qualification followed by whether they worked in a general ward with a specialty and had >5 years of experience. CONCLUSIONS: This exploratory study provides evidence for the psychometric properties of the V-scale. It reveals a need for continuous professional development to improve ward nurses' attitudes towards vital signs monitoring. Vital signs monitoring needs to be prioritized in workload planning.
Authors: Sok Ying Liaw; Lai Fun Wong; Eunice Ya Ping Lim; Sophia Bee Leng Ang; Sandhya Mujumdar; Jasmine Tze Yin Ho; Siti Zubaidah Mordiffi; Emily Neo Kim Ang Journal: J Med Internet Res Date: 2016-02-19 Impact factor: 5.428
Authors: Morris Ogero; Philip Ayieko; Boniface Makone; Thomas Julius; Lucas Malla; Jacquie Oliwa; Grace Irimu; Mike English Journal: J Glob Health Date: 2018-06 Impact factor: 4.413
Authors: Abi Beane; Ambepitiyawaduge Pubudu De Silva; Nirodha De Silva; Jayasingha A Sujeewa; R M Dhanapala Rathnayake; P Chathurani Sigera; Priyantha Lakmini Athapattu; Palitha G Mahipala; Aasiyah Rashan; Sithum Bandara Munasinghe; Kosala Saroj Amarasiri Jayasinghe; Arjen M Dondorp; Rashan Haniffa Journal: BMJ Open Date: 2018-04-27 Impact factor: 2.692
Authors: Wei Ling Chua; Min Ting Alicia See; Helena Legio-Quigley; Daryl Jones; Augustine Tee; Sok Ying Liaw Journal: Int J Qual Health Care Date: 2017-12-01 Impact factor: 2.038
Authors: Alejandra Recio-Saucedo; Antonello Maruotti; Peter Griffiths; Gary B Smith; Paul Meredith; Greta Westwood; Carole Fogg; Paul Schmidt Journal: Nurs Open Date: 2018-07-16