Academic Articles & Research Papers

Development of a core outcome set for the evaluation of shared decision-making interventions in healthcare: a study protocol.

Shared Decision-Making Theories, Conceptual Models, and Frameworks Within Oral Healthcare: A Theory Analysis.

The influence of patient self-efficacy on value co-creation behavior and outcomes in chronic disease management: a cross-sectional study

Abstract Background In the medical field, value co-creation involves patients’ active involvement. By collaborating with service providers, patients can contribute to the creation of more targeted and effective value. Patients’ self-efficac...

Pilot evaluation of an educational and lived experience training program on ketogenic metabolic therapy in mental health care for health care professionals

BackgroundSerious mental illness imposes a substantial burden. Pharmacologic treatments remain only partially effective and are associated with significant side effects, highlighting the need for novel treatment approaches. Ketogenic metabo...

The impact of an online intervention on the medical, dental and health sciences students about interprofessional education; a quasi-experimental study

Abstract Background Interprofessional education (IPE) encompasses integration, communication, mutual trust and shared decision-making with a common goal of improved patient care and safety. Despite its crucial role, IPE has not gained its a...

Protocol for a mixed methods process evaluation for a randomised controlled trial to improve shared decision-making about, and uptake of, osteoporosis medicines: the iFraP study [version 3; peer review: 2 approved, 1 approved with reservations]

Background High quality shared decision-making (SDM) conversations involve people with or at risk of osteoporosis and clinicians working together to decide, where appropriate, which evidence-based medicines best fit the person’s life, belie...

Acceptance of Machine Learning for Medication Selection in Epilepsy to Inform Clinical Trial Design: Co-Design Survey Study

Abstract BackgroundAntiseizure medications (ASMs) are the mainstay of epilepsy treatment; however, there is currently no reliable way to predict which medication will be most effective for an individual patient. Machine learning...