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- Gyberg, Viveca, et al.
(författare)
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Measuring risk online-Feasibility of using FINDRISC in an online workplace survey
- 2012
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Ingår i: Primary Care Diabetes. - : Elsevier BV. - 1751-9918 .- 1878-0210. ; 6:2, s. 103-107
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Tidskriftsartikel (refereegranskat)abstract
- AIMS: With the globally increasing prevalence of diabetes and the knowledge on how to prevent the disease there is a high demand for an effective way of identifying people at risk. The hypothesis behind this investigation was that incorporation of the FINnish Diabetes Risk SCore (FINDRISC) questionnaire in a regular workplace survey would be a feasible way to identify individuals and groups at risk for diabetes that could benefit from preventive interventions.METHOD: The eight FINDRISC questions were slightly modified and incorporated to Webb-QPS, an online work place survey, and distributed by e-mail to 5166 employees at Karolinska University Hospital (KUH).RESULTS: The total number of responders to Webb-QPS was 3581 (69%). Of those responding 3029 (84%) replied to the FINDRISC section which comprises 59% of the original population. A group of 1082 high risk individuals could be considered for intervention whereof 298 (9.8%) are expected to develop diabetes the upcoming 10 years if left without intervention.CONCLUSION: It is feasible to incorporate a diabetes risk score such as the FINDRISC in a workplace survey. A group that could be subject to preventive intervention programs was identified.
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| 2. |
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| 3. |
- Munkhammar, Joakim, 1982-, et al.
(författare)
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Polynomial probability distribution estimation using the method of moments
- 2017
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Ingår i: PLOS ONE. - : PUBLIC LIBRARY SCIENCE. - 1932-6203. ; 12:4
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Tidskriftsartikel (refereegranskat)abstract
- We suggest a procedure for estimating Nth degree polynomial approximations to unknown (or known) probability density functions (PDFs) based on N statistical moments from each distribution. The procedure is based on the method of moments and is setup algorithmically to aid applicability and to ensure rigor in use. In order to show applicability, polynomial PDF approximations are obtained for the distribution families Normal, Log-Normal, Weibull as well as for a bimodal Weibull distribution and a data set of anonymized household electricity use. The results are compared with results for traditional PDF series expansion methods of Gram-Charlier type. It is concluded that this procedure is a comparatively simple procedure that could be used when traditional distribution families are not applicable or when polynomial expansions of probability distributions might be considered useful approximations. In particular this approach is practical for calculating convolutions of distributions, since such operations become integrals of polynomial expressions. Finally, in order to show an advanced applicability of the method, it is shown to be useful for approximating solutions to the Smoluchowski equation.
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