Road map for clinicians to develop and evaluate AI predictive models to inform clinical decision-making.

Background: Predictive models have been used in clinical care for decades. They can determine the risk of a patient developing a particular condition or complication and inform the shared decision-making process. Developing artificial intelligence (AI) predictive models for use in clinical practice is challenging; even if they have good predictive performance, this does not guarantee that they will be used or enhance decision-making.

KidzMed e-learning to upskill student pharmacists to teach pill swallowing to children.

Background: Appropriate medication use is essential in ensuring optimal pharmacotherapeutic outcomes. It is mistakenly assumed that adults can swallow solid oral dosage forms (SODFs, e.g.

Harm and Medication-Type Impact Agreement with Hypothetical Deprescribing Recommendations: a Vignette-Based Experiment with Older Adults Across Four Countries.

Background: Little is known about what factors are important to older adults when deciding whether to agree with a recommendation to deprescribe.

Objective: To explore the extent to which medication type and rationale for potential discontinuation influence older adults' acceptance of deprescribing.

Design: Cross-sectional 2 (drug: lansoprazole - treat indigestion; simvastatin - prevent cardiovascular disease) by 3 (deprescribing rationale: lack of benefit; potential for harm; both) experimental design.