Donna Rowen1, Jill Carlton2, Jackie Elliott3. 1. Health Economics and Decision Science, School of Health and Related Research, University of Sheffield, Sheffield, UK. Electronic address: d.rowen@sheffield.ac.uk. 2. Health Economics and Decision Science, School of Health and Related Research, University of Sheffield, Sheffield, UK. 3. Academic Unit of Diabetes, Endocrinology and Metabolism, Department of Oncology & Metabolism, University of Sheffield, Sheffield, UK; Sheffield Teaching Hospitals NHS Trust, Diabetes and Endocrine Centre, Northern General Hospital, Sheffield, UK.
Abstract
OBJECTIVE: This study examines the impact of data collection method on the sociodemographic and health profile of samples of people with diabetes who complete either an online or postal patient-reported outcome measure (PROM) validation survey. METHODS: A longitudinal survey of people with diabetes was conducted using online and postal survey versions. The survey consisted of sociodemographic and health questions, a health and self-management PROM (Health and Self-Management in Diabetes [HASMID]), and 5-level version of EQ-5D. Dose adjustment for normal eating Online, Diabetes UK, and social media were used to recruit online survey participants. A panel of patients at a local National Health Service Trust was randomly allocated to participate in either survey version (two-thirds to postal version). Participants were asked to complete the survey again approximately 3 months later. RESULTS: A total of 2784 participants completed the survey (1908 online, 876 postal). The samples (online versus postal) differed; the online sample was younger, with a larger proportion of women and respondents with type 1 diabetes. There were significant differences in sociodemographic characteristics by type of diabetes across data collection mode. The proportion of respondents who responded again at point 2 was higher in the postal sample (525 postal, 698 online). CONCLUSION: The sociodemographic and health profile of samples of people with diabetes differed depending on whether they completed the online or postal survey. Differences are likely due to different recruitment methods and differences in those choosing to respond to different survey versions. Future PROM validation surveys should select data collection methods carefully because these can affect sample characteristics and results.
OBJECTIVE: This study examines the impact of data collection method on the sociodemographic and health profile of samples of people with diabetes who complete either an online or postal patient-reported outcome measure (PROM) validation survey. METHODS: A longitudinal survey of people with diabetes was conducted using online and postal survey versions. The survey consisted of sociodemographic and health questions, a health and self-management PROM (Health and Self-Management in Diabetes [HASMID]), and 5-level version of EQ-5D. Dose adjustment for normal eating Online, Diabetes UK, and social media were used to recruit online survey participants. A panel of patients at a local National Health Service Trust was randomly allocated to participate in either survey version (two-thirds to postal version). Participants were asked to complete the survey again approximately 3 months later. RESULTS: A total of 2784 participants completed the survey (1908 online, 876 postal). The samples (online versus postal) differed; the online sample was younger, with a larger proportion of women and respondents with type 1 diabetes. There were significant differences in sociodemographic characteristics by type of diabetes across data collection mode. The proportion of respondents who responded again at point 2 was higher in the postal sample (525 postal, 698 online). CONCLUSION: The sociodemographic and health profile of samples of people with diabetes differed depending on whether they completed the online or postal survey. Differences are likely due to different recruitment methods and differences in those choosing to respond to different survey versions. Future PROM validation surveys should select data collection methods carefully because these can affect sample characteristics and results.
Authors: Olga María Luque-Alcaraz; Antonio Gomera; África Ruíz; Pilar Aparicio-Martinez; Manuel Vaquero-Abellan Journal: Healthcare (Basel) Date: 2022-07-29