Cargando…

The Danish Diabetes Musculoskeletal Cohort: Non-Responder Analysis of an Electronic Survey Using Registry Data

PURPOSE: To conduct a non-responder analysis on a musculoskeletal (MSK) electronic questionnaire. METHODS: Individuals aged 18 years and older, diagnosed with diabetes mellitus (DM), and attended an ambulatory DM clinic formed the sample frame. They were invited to complete an electronic musculoskel...

Descripción completa

Detalles Bibliográficos
Autores principales: Boyle, Eleanor, Folkestad, Lars, Frafjord, Erik, Koes, Bart W, Skou, Soren Thorgaard, Hartvigsen, Jan
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Dove 2021
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8180289/
https://www.ncbi.nlm.nih.gov/pubmed/34103998
http://dx.doi.org/10.2147/CLEP.S293186
_version_ 1783703970451030016
author Boyle, Eleanor
Folkestad, Lars
Frafjord, Erik
Koes, Bart W
Skou, Soren Thorgaard
Hartvigsen, Jan
author_facet Boyle, Eleanor
Folkestad, Lars
Frafjord, Erik
Koes, Bart W
Skou, Soren Thorgaard
Hartvigsen, Jan
author_sort Boyle, Eleanor
collection PubMed
description PURPOSE: To conduct a non-responder analysis on a musculoskeletal (MSK) electronic questionnaire. METHODS: Individuals aged 18 years and older, diagnosed with diabetes mellitus (DM), and attended an ambulatory DM clinic formed the sample frame. They were invited to complete an electronic musculoskeletal (MSK) conditions and symptoms questionnaire booklet using a secured electronic email system. Individuals whose secured email box was not active at the time were discarded. Using the Central Person Registry number, a unique number assigned to all Danish residents, we linked the sample frame to different registries to learn more about non-responders. Non-responders were either individuals who did not respond to a single question and those who responded “No” to the first question about willing to participate. We calculated descriptive statistics for each characteristic. Univariate logistic regression models were conducted to determine the relationship between each characteristic and non-responder status. RESULTS: The response rate was 36% (n = 3812). Individuals with type 2 DM (OR 2.0 (95% CI 1.8–2.2)), secondary DM (1.9 (1.3–2.8)) or unspecified DM (2.1 (1.8–2.4)) were more likely to be non-responders than individuals with Type 1 DM. Also, individuals aged 70–79 (1.3 (1.1–1.6)) and 80 years and older (5.9 (4.5–7.7)) were more likely to be non-responders than 18–29 years old individuals. However, individuals aged 40–49 (1.5 (1.2–1.8)), 50–59 (1.5 (1.3–1.8)) or 60–69 (1.4 (1.1–1.6)) were more likely to be responders than 18–29 years old individuals. Individuals with Charlson Comorbidity Index (CCI) of 1 (2.0 (1.3.2.9) or CCI of 2 (1.7 (1.1–2.5) were more likely to be responders than individuals with a CCI of 0. Lastly, individuals who were currently outside of the workforce (1.6 (2.4–2.9) or had unknown/missing socioeconomic status (3.9 (2.8–5.3) were more likely to be non-responders than individuals who were working. CONCLUSION: Although we did find a non-response bias, this cohort will be an important source to determine the prevalence and consequences of MSK conditions in a secondary care DM population.
format Online
Article
Text
id pubmed-8180289
institution National Center for Biotechnology Information
language English
publishDate 2021
publisher Dove
record_format MEDLINE/PubMed
spelling pubmed-81802892021-06-07 The Danish Diabetes Musculoskeletal Cohort: Non-Responder Analysis of an Electronic Survey Using Registry Data Boyle, Eleanor Folkestad, Lars Frafjord, Erik Koes, Bart W Skou, Soren Thorgaard Hartvigsen, Jan Clin Epidemiol Original Research PURPOSE: To conduct a non-responder analysis on a musculoskeletal (MSK) electronic questionnaire. METHODS: Individuals aged 18 years and older, diagnosed with diabetes mellitus (DM), and attended an ambulatory DM clinic formed the sample frame. They were invited to complete an electronic musculoskeletal (MSK) conditions and symptoms questionnaire booklet using a secured electronic email system. Individuals whose secured email box was not active at the time were discarded. Using the Central Person Registry number, a unique number assigned to all Danish residents, we linked the sample frame to different registries to learn more about non-responders. Non-responders were either individuals who did not respond to a single question and those who responded “No” to the first question about willing to participate. We calculated descriptive statistics for each characteristic. Univariate logistic regression models were conducted to determine the relationship between each characteristic and non-responder status. RESULTS: The response rate was 36% (n = 3812). Individuals with type 2 DM (OR 2.0 (95% CI 1.8–2.2)), secondary DM (1.9 (1.3–2.8)) or unspecified DM (2.1 (1.8–2.4)) were more likely to be non-responders than individuals with Type 1 DM. Also, individuals aged 70–79 (1.3 (1.1–1.6)) and 80 years and older (5.9 (4.5–7.7)) were more likely to be non-responders than 18–29 years old individuals. However, individuals aged 40–49 (1.5 (1.2–1.8)), 50–59 (1.5 (1.3–1.8)) or 60–69 (1.4 (1.1–1.6)) were more likely to be responders than 18–29 years old individuals. Individuals with Charlson Comorbidity Index (CCI) of 1 (2.0 (1.3.2.9) or CCI of 2 (1.7 (1.1–2.5) were more likely to be responders than individuals with a CCI of 0. Lastly, individuals who were currently outside of the workforce (1.6 (2.4–2.9) or had unknown/missing socioeconomic status (3.9 (2.8–5.3) were more likely to be non-responders than individuals who were working. CONCLUSION: Although we did find a non-response bias, this cohort will be an important source to determine the prevalence and consequences of MSK conditions in a secondary care DM population. Dove 2021-05-31 /pmc/articles/PMC8180289/ /pubmed/34103998 http://dx.doi.org/10.2147/CLEP.S293186 Text en © 2021 Boyle et al. https://creativecommons.org/licenses/by-nc/3.0/This work is published and licensed by Dove Medical Press Limited. The full terms of this license are available at https://www.dovepress.com/terms.php and incorporate the Creative Commons Attribution – Non Commercial (unported, v3.0) License (http://creativecommons.org/licenses/by-nc/3.0/ (https://creativecommons.org/licenses/by-nc/3.0/) ). By accessing the work you hereby accept the Terms. Non-commercial uses of the work are permitted without any further permission from Dove Medical Press Limited, provided the work is properly attributed. For permission for commercial use of this work, please see paragraphs 4.2 and 5 of our Terms (https://www.dovepress.com/terms.php).
spellingShingle Original Research
Boyle, Eleanor
Folkestad, Lars
Frafjord, Erik
Koes, Bart W
Skou, Soren Thorgaard
Hartvigsen, Jan
The Danish Diabetes Musculoskeletal Cohort: Non-Responder Analysis of an Electronic Survey Using Registry Data
title The Danish Diabetes Musculoskeletal Cohort: Non-Responder Analysis of an Electronic Survey Using Registry Data
title_full The Danish Diabetes Musculoskeletal Cohort: Non-Responder Analysis of an Electronic Survey Using Registry Data
title_fullStr The Danish Diabetes Musculoskeletal Cohort: Non-Responder Analysis of an Electronic Survey Using Registry Data
title_full_unstemmed The Danish Diabetes Musculoskeletal Cohort: Non-Responder Analysis of an Electronic Survey Using Registry Data
title_short The Danish Diabetes Musculoskeletal Cohort: Non-Responder Analysis of an Electronic Survey Using Registry Data
title_sort danish diabetes musculoskeletal cohort: non-responder analysis of an electronic survey using registry data
topic Original Research
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8180289/
https://www.ncbi.nlm.nih.gov/pubmed/34103998
http://dx.doi.org/10.2147/CLEP.S293186
work_keys_str_mv AT boyleeleanor thedanishdiabetesmusculoskeletalcohortnonresponderanalysisofanelectronicsurveyusingregistrydata
AT folkestadlars thedanishdiabetesmusculoskeletalcohortnonresponderanalysisofanelectronicsurveyusingregistrydata
AT frafjorderik thedanishdiabetesmusculoskeletalcohortnonresponderanalysisofanelectronicsurveyusingregistrydata
AT koesbartw thedanishdiabetesmusculoskeletalcohortnonresponderanalysisofanelectronicsurveyusingregistrydata
AT skousorenthorgaard thedanishdiabetesmusculoskeletalcohortnonresponderanalysisofanelectronicsurveyusingregistrydata
AT hartvigsenjan thedanishdiabetesmusculoskeletalcohortnonresponderanalysisofanelectronicsurveyusingregistrydata
AT boyleeleanor danishdiabetesmusculoskeletalcohortnonresponderanalysisofanelectronicsurveyusingregistrydata
AT folkestadlars danishdiabetesmusculoskeletalcohortnonresponderanalysisofanelectronicsurveyusingregistrydata
AT frafjorderik danishdiabetesmusculoskeletalcohortnonresponderanalysisofanelectronicsurveyusingregistrydata
AT koesbartw danishdiabetesmusculoskeletalcohortnonresponderanalysisofanelectronicsurveyusingregistrydata
AT skousorenthorgaard danishdiabetesmusculoskeletalcohortnonresponderanalysisofanelectronicsurveyusingregistrydata
AT hartvigsenjan danishdiabetesmusculoskeletalcohortnonresponderanalysisofanelectronicsurveyusingregistrydata