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- Thoma, B, et al.
(författare)
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An international, interprofessional investigation of the self-reported podcast listening habits of emergency clinicians: A METRIQ Study
- 2020
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Ingår i: CJEM. - : Springer Science and Business Media LLC. - 1481-8043 .- 1481-8035. ; 22:1, s. 112-117
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Tidskriftsartikel (refereegranskat)abstract
- ObjectivesPodcasts are increasingly being used for medical education. A deeper understanding of usage patterns would inform both producers and researchers of medical podcasts. We aimed to determine how and why podcasts are used by emergency medicine and critical care clinicians.MethodsAn international interprofessional sample (medical students, residents, physicians, nurses, physician assistants, and paramedics) was recruited through direct contact and a multimodal social media (Twitter and Facebook) campaign. Each participant completed a survey outlining how and why they utilize medical podcasts. Recruitment materials included an infographic and study website.Results390 participants from 33 countries and 4 professions (medicine, nursing, paramedicine, physician assistant) completed the survey. Participants most frequently listened to medical podcasts to review new literature (75.8%), learn core material (75.1%), and refresh memory (71.8%). The majority (62.6%) were aware of the ability to listen at increased speeds, but most (76.9%) listened at 1.0 x (normal) speed. All but 25 (6.4%) participants concurrently performed other tasks while listening. Driving (72.3%), exercising (39.7%), and completing chores (39.2%) were the most common. A minority of participants used active learning techniques such as pausing, rewinding, and replaying segments of the podcast. Very few listened to podcasts multiple times.ConclusionsAn international cohort of emergency clinicians use medical podcasts predominantly for learning. Their listening habits (rarely employing active learning strategies and frequently performing concurrent tasks) may not support this goal. Further exploration of the impact of these activities on learning from podcasts is warranted.
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| 2. |
- McGurnaghan, S. J., et al.
(författare)
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Development and validation of a cardiovascular risk prediction model in type 1 diabetes
- 2021
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Ingår i: Diabetologia. - : Springer Science and Business Media LLC. - 0012-186X .- 1432-0428. ; 64, s. 2001-2011
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Tidskriftsartikel (refereegranskat)abstract
- Aims/hypothesis We aimed to report current rates of CVD in type 1 diabetes and to develop a CVD risk prediction tool for type 1 diabetes. Methods A cohort of 27,527 people with type 1 diabetes without prior CVD was derived from the national register in Scotland. Incident CVD events during 199,552 person-years of follow-up were ascertained using hospital admissions and death registers. A Poisson regression model of CVD was developed and then validated in the Swedish National Diabetes Register (n = 33,183). We compared the percentage with a high 10 year CVD risk (i.e., >= 10%) using the model with the percentage eligible for statins using current guidelines by age. Results The age-standardised rate of CVD per 100,000 person-years was 4070 and 3429 in men and women, respectively, with type 1 diabetes in Scotland, and 4014 and 3956 in men and women in Sweden. The final model was well calibrated (Hosmer- Lemeshow test p > 0.05) and included a further 22 terms over a base model of age, sex and diabetes duration (C statistic 0.82; 95% CI 0.81, 0.83). The model increased the base model C statistic foam 0.66 to 0.80, from 0.60 to 0.75 and from 0.62 to 0.68 in those aged <40, 40-59 and >= 60 years, respectively (alp values <0.005). The model required minimal calibration in Sweden and had a C statistic of 0.85. Under current guidelines, >90% of those aged 20-39 years and 100% of those >= 40 years with type 1 diabetes were eligible for statins, but it was not until age 65 upwards that 100% had a modelled risk of CVD >= 10% in 10 years. Conclusions/interpretation A prediction tool such as that developed here can provide individualised risk predictions. This 10 year CVD risk prediction tool could facilitate patient discussions regarding appropriate statin prescribing. Apart from 10 year risk, such discussions may also consider longer-term CVD risk, the potential for greater benefits from early vs later statin intervention. the potential impact on quality of life of an early CVD event and evidence on safety, all of which could influence treatment decisions, particularly in younger people with type 1 diabetes.
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