1 resultado para Markov chains hidden Markov models Viterbi algorithm Forward-Backward algorithm maximum likelihood
em Dalarna University College Electronic Archive
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Resumo:
Objectives: To translate and evaluate the psychometric properties of the Swedish version of the Fear of Complications Questionnaire. Design: Cross-sectional study design and scale development. Settings: Totally, 469 adults (response rate 63.5%) with Type 1 diabetes completed the questionnaires. Participants were recruited from two university hospitals in Sweden. Participants: Eligible patients were those who met the following inclusion criteria: diagnosed with Type 1 diabetes, diabetes duration of at least 1 year and aged at least 18 years. Methods: The Fear of Complications Questionnaire was translated using the forward-backward translation method. Factor analyses of the questionnaire were performed in two steps using both exploratory and confirmatory factor analysis. Convergent validity was examined using the Hospital Anxiety and Depression Scale and the Fear of Hypoglycaemia Fear Survey. Internal consistency was estimated using Cronbach’s alpha.Results: Exploratory factor analysis supported a two-factor solution. One factor contained three items having to do with fear of kidney-related complications and one factor included the rest of items concerning fear of other diabetes-related complications, as well as fear of complications in general. Internal consistency was high Cronbach’s alpha 0.96. The findings also gave support for convergent validity, with significant positive correlations between measures (r = 0.51 to 0.54). Conclusion: The clinical relevance of the identified two-factor model with a structure of one dominant subdomain may be considered. We suggest, however a one-factor model covering all the items as a relevant basis to assess fear of complications among people with Type 1 diabetes.