The Medical journal of Australia
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Randomized Controlled Trial
The Health4Life e-health intervention for modifying lifestyle risk behaviours of adolescents: secondary outcomes of a cluster randomised controlled trial.
To investigate the effectiveness of a school-based multiple health behaviour change e-health intervention for modifying risk factors for chronic disease (secondary outcomes). ⋯ Health4Life was not more effective than usual school year 7 health education for modifying adolescent risk factors for chronic disease. Future e-health multiple health behaviour change intervention research should examine the timing and length of the intervention, as well as increasing the number of engagement strategies (eg, goal setting) during the intervention.
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Cardiovascular disease (CVD) is the leading cause of morbidity and mortality globally and is responsible for an estimated one-third of deaths as well as significant morbidity and health care utilisation. Technological and bioinformatic advances have facilitated the discovery of pathogenic germline variants for some specific CVDs, including familial hypercholesterolaemia, cardiomyopathies and arrhythmic syndromes. Use of these genetic tests for earlier disease identification is increasing due, in part, to decreasing costs, Medicare rebates, and consumer comfort with genetic testing. ⋯ This complexity can be expressed mathematically as a polygenic risk score. Genetic testing kits that provide polygenic risk scoring are becoming increasingly available directly to private-paying consumers outside the traditional clinical setting. An improved understanding of the evidence of genetics in CVD will offer clinicians new opportunities for individualised risk prediction and preventive therapy.
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To support a diverse sample of Australians to make recommendations about the use of artificial intelligence (AI) technology in health care. ⋯ The deliberative process supported a nationally representative sample of citizens to construct recommendations about how AI in health care should be developed, used, and governed. Recommendations derived using such methods could guide clinicians, policy makers, AI researchers and developers, and health service users to develop approaches that ensure trustworthy and responsible use of this technology.