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Item analysis using Rasch models confirms that the Danish versions of the DISABKIDS® chronic-generic and diabetes-specific modules are valid and reliable

Overview of attention for article published in Health and Quality of Life Outcomes, March 2017
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Title
Item analysis using Rasch models confirms that the Danish versions of the DISABKIDS® chronic-generic and diabetes-specific modules are valid and reliable
Published in
Health and Quality of Life Outcomes, March 2017
DOI 10.1186/s12955-017-0618-8
Pubmed ID
Authors

Julie Bøjstrup Nielsen, Julie Nyholm Kyvsgaard, Stine Møller Sildorf, Svend Kreiner, Jannet Svensson

Abstract

Type 1 Diabetes (T1D) has a negative impact on psychological and overall well-being. Screening for Health-related Quality of Life (HrQoL) and addressing HrQoL issues in the clinic leads to improved well-being and metabolic outcomes. The aim of this study was to translate the generic and diabetes-specific validated multinational DISABKIDS® questionnaires into Danish, and then determine their validity and reliability. The questionnaires were translated using a validated translation procedure and completed by 99 children and adolescents from our diabetes-department; all diagnosed with T1D and were aged between 8 and 18 years old. The Rasch and the graphical log linear Rasch model (GLLRM) were used to determine validity. Monte Carlo methods and Cronbach's α were used to confirm reliability. The data did not fit a pure Rasch model but did fit a GLLRM when item six in the independence scale is excluded. The six subscales measure different aspects of HrQoL indicating that all the subscales are necessary. The questionnaire shows local dependency between items and differential item functioning (DIF). Therefore age, gender, and glycated hemoglobin (HbA1c) levels must be taken into account when comparing HrQoL between groups. The Danish versions of the DISABKIDS® chronic-generic and diabetes-specific modules provide valid and objective measurements with adequate reliability. These Danish versions are useful tools for evaluating HrQoL in Danish patients with T1D. However, guidelines on how to manage DIF and local independence will be required, and item six should be rephrased.

Twitter Demographics

The data shown below were collected from the profile of 1 tweeter who shared this research output. Click here to find out more about how the information was compiled.

Mendeley readers

The data shown below were compiled from readership statistics for 60 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 60 100%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 9 15%
Student > Bachelor 9 15%
Student > Doctoral Student 7 12%
Student > Master 6 10%
Other 4 7%
Other 19 32%
Unknown 6 10%
Readers by discipline Count As %
Medicine and Dentistry 15 25%
Nursing and Health Professions 13 22%
Psychology 9 15%
Social Sciences 3 5%
Computer Science 2 3%
Other 12 20%
Unknown 6 10%

Attention Score in Context

This research output has an Altmetric Attention Score of 1. This is our high-level measure of the quality and quantity of online attention that it has received. This Attention Score, as well as the ranking and number of research outputs shown below, was calculated when the research output was last mentioned on 02 March 2017.
All research outputs
#11,778,607
of 15,442,255 outputs
Outputs from Health and Quality of Life Outcomes
#1,047
of 1,660 outputs
Outputs of similar age
#178,804
of 260,925 outputs
Outputs of similar age from Health and Quality of Life Outcomes
#1
of 1 outputs
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