Publications by authors named "Megan Bamford"
Background: Artificial intelligence (AI) is set to transform the health system, yet little research to date has explored its influence on nurses-the largest group of health professionals. Furthermore, there has been little discussion on how AI will influence the experience of person-centered compassionate care for patients, families, and caregivers.
Objective: This review aims to summarize the extant literature on the emerging trends in health technologies powered by AI and their implications on the following domains of nursing: administration, clinical practice, policy, and research.
Background: It is predicted that artificial intelligence (AI) will transform nursing across all domains of nursing practice, including administration, clinical care, education, policy, and research. Increasingly, researchers are exploring the potential influences of AI health technologies (AIHTs) on nursing in general and on nursing education more specifically. However, little emphasis has been placed on synthesizing this body of literature.
View Article and Find Full Text PDFA comprehensive data quality assessment is necessary to expand a nursing database that is designed for evaluating the impact of implementing Best Practice Guidelines (BPG) developed by the Registered Nurses' Association of Ontario (RNAO). This case report presents a method to standardize data quality assessments of the Nursing Quality Indicators for Reporting and Evaluation (NQuIRE) database by developing a data quality framework (DQF) and assessing key dimensions of the framework using a data quality index (DQI). The data quality index is a single key performance metric for assessing the quality of the database.
View Article and Find Full Text PDFBackground: It is predicted that digital health technologies that incorporate artificial intelligence will transform health care delivery in the next decade. Little research has explored how emerging trends in artificial intelligence-driven digital health technologies may influence the relationship between nurses and patients.
Objective: The purpose of this scoping review is to summarize the findings from 4 research questions regarding emerging trends in artificial intelligence-driven digital health technologies and their influence on nursing practice across the 5 domains outlined by the Canadian Nurses Association framework: administration, clinical care, education, policy, and research.
Introduction: The objective of this systematic review was to investigate what education and training characteristics prepares and supports health-care professionals (HCPs) in the delivery of competent and effective care to clients who use tobacco-nicotine.
Aims And Methods: A search of eight bibliographic databases for English-language peer-reviewed publications from January 2006 to March 2015. Studies were included if they met the a priori inclusion criteria, which consisted of: (1) quantitative study design and (2) focus on tobacco-nicotine education or training for HCP students and practitioners.
Background: Existing evidence suggests that a person-centred approach can improve coordination and access to health care and services.
Objectives: This overview sought to: (1) identify and define components of person-centred care; (2) explore nursing and health-care provider behaviours that are person-centred; and (3) identify systems level supports required to enable person-centred care.
Methods: An overview of reviews was conducted to locate synthesized literature published between June 2005 and April 2014.
Aim: To examine the relationships among nurses' perceptions of nurse managers' authentic leadership, nurses' overall person-job match in the six areas of worklife and their work engagement.
Background: Reports have highlighted the impact of demanding and unsupportive work environments on nurses' wellbeing, resulting in a need for strong nursing leadership to build sustainable and healthier work environments.
Methods: A secondary analysis of data collected from a non-experimental, predictive design survey of a random sample of 280 registered nurses working in acute care hospitals was conducted.