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Contextual Factors that Influence Antibiotic Prescribing: A Discrete Choice Experiment of GP Registrars.
Appl Health Econ Health Policy
January 2025
General Practice Clinical Unit, Faculty of Clinical Medicine, The University of Queensland, Brisbane, QLD, Australia.
Introduction: Antimicrobial resistance is a global emergency related to overprescribing of antibiotics. Few studies have explored how prescribing behaviours may change as the consequence of changing resistance. Understanding how contextual factors influence antibiotic prescribing will facilitate improved communication strategies to promote appropriate antibiotic prescribing.
View Article and Find Full Text PDFEmpowering African Expertise: Enhancing Safety Data Integration and Signal Detection for COVID-19 Vaccines Through the African Union Smart Safety Surveillance Joint Signal Management Group.
Drug Saf
January 2025
Department of Public Health Pharmacy and Management, Sefako Makgatho Health Sciences University, Pretoria, South Africa.
Introduction: The COVID-19 pandemic accelerated new vaccine development. Limited safety data necessitated robust global safety surveillance to accurately identify and promptly communicate potential safety issues. The African Union Smart Safety Surveillance (AU-3S) program established the Joint Signal Management (JSM) group to support identification of potential vaccine safety concerns in five pilot countries (Ethiopia, Ghana, Kenya, Nigeria, South Africa), accounting for approximately 35% of the African population.
View Article and Find Full Text PDFRisk of bias tools for medication adherence research: RoBIAS and RoBOAS.
Br J Clin Pharmacol
January 2025
Sydney Pharmacy School, Faculty of Medicine and Health, University of Sydney, Sydney, Australia.
Aims: An unbiased means of documenting medication-taking is important to ensure quality evidence about adherence research and to accurately identify individuals at risk of suboptimal adherence for the development of targeted and effective interventions. Guidance to assist researchers in the understanding of risk of bias when conducting or reviewing adherence research is currently not available. To address this gap, tools to identify and gauge the magnitude of important biases that may impact adherence research have been developed.
View Article and Find Full Text PDFMethods for data extraction and data transformation in convergent integrated mixed methods systematic reviews.
JBI Evid Synth
January 2025
The University of West London Centre for Evidence-Based Healthcare: A JBI Centre of Excellence, College of Nursing, Midwifery and Healthcare, University of West London, London, United Kingdom.
Objective: The objective of this guidance paper is to describe data transformation involving qualitization, including when and how to undertake this process, and to clarify how it aligns with data extraction in order to expand on the current guidance for JBI convergent integrated mixed methods systematic reviews (MMSRs).
Introduction: The convergent integrated approach to MMSRs involves combining extracted data from both quantitative studies (including the quantitative components of mixed methods studies) and qualitative studies (including the qualitative components of mixed methods studies). This process requires data transformation, which can occur either by converting qualitative data into quantitative data (ie, quantitizing) or converting quantitative data into qualitative data (ie, qualitizing).
Exploring surgeon behavioural factors impacting the quality of care: protocol for a scoping review.
BMJ Open
January 2025
CancerCare Manitoba, Winnipeg, Manitoba, Canada
Introduction: Modern surgery incorporates many aspects of care, including preoperative workup, surgical management and multidisciplinary collaboration to achieve favourable outcomes and high patient satisfaction. Current literature identifies variability in surgical practice and quality of care. The objective of this study is to fill the gap in the literature by identifying modifiable surgeon behavioural factors influencing the quality of care and to identify interventions and policies that modify these factors.
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