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Factors associated with patient experiences of the burden of using medicines and health-related quality of life: a cross-sectional study

dataset
posted on 2024-07-13, 09:20 authored by Won Sun Chen, Md Rafiqul Islam, Sajini Ambepitiya, William Sim, Wai Yiu, Joseph Carey, Edward OgdenEdward Ogden
This dataset (csv) and field labels (pdf) contains data from three questionnaires: 1) Demographics Background 2) Living with Medicine Questionnaire (LMQ-3) 3) EQ-5D-5L Questionnaire Demographic background includes few questions about participants and their medicines use. The LMQ-3 seeks participants views and opinions about the prescribed medicines use and how they affect their life. It consists of 41 items, measured using a five-point Likert scale (scored from strongly agree to strongly disagree) within eight domains: 1) perceptions about effectiveness, 2) concerns about medicine use, 3) patient-provider relationships and communication about medicines, 4) practical difficulties, 5) interferences with daily life, 6) side effects, 7) costs, 8) autonomy/control over medicine and acceptance of medicine use, all of which have been cited by users of long-term medicines as burdensome. The EQ-5D-5L is a standardised measure of health-related quality of life. It consists of 2 pages: the EQ-5D-5L descriptive system and the EQ visual analogue scale (EQ VAS). The descriptive system comprises 5 dimensions: mobility, self-care, usual activities, pain/discomfort, and anxiety/depression. Each dimension has 5 levels: 1=no problems, 2=slight problems, 3=moderate problems, 4=severe problems, and 5=extreme problems. The EQ VAS captures one’s self-reported overall health on a 20 cm vertical, visual analogue scale with endpoints of 0 (the worst health you can imagine) and 100 (the best health you can imagine).

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Variable labels PDF (Published version), Data CSV (Published version)

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Copyright © 2022 the author(s). This dataset is licensed under a Creative Commons Attribution 4.0 International license (https://creativecommons.org/licenses/by/4.0/)

Notes

This dataset is associated with a paper at PLOS ONE at https://doi.org/10.1371/journal.pone.0267593.

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eng

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