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Showing 4 of 4 academic articles

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

Sidney L. Murray, Denise Potter, Yaara Zisman-Ilani, Yaara Zisman-Ilani et al. • Frontiers in Psychiatry (2026)

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...

DOAJ Open Access (DOAJ) DOI: 10.3389/fpsyt.2026.1913325

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

Salman Y. Guraya, Leena R. David, Shermin Hashir, Noha A. Mousa et al. • BMC Medical Education (2021)

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...

DOAJ Open Access (DOAJ) DOI: 10.1186/s12909-021-02900-8

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]

Terence W O'Neill, Robert Horne, Clare Jinks, Christian D Mallen et al. • NIHR Open Research (2026)

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...

DOAJ Open Access (DOAJ) DOI: 10.3310/nihropenres.13751.3

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

Madeleine J Smith, Sandra Reeder, Fiona Waugh, Shobi Sivathamboo et al. • JMIR AI (2026)

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...

DOAJ Open Access (DOAJ) DOI: 10.2196/85047