Research Data Leeds Repository

Dataset for a randomised factorial experiment to optimise an information leaflet for women with breast cancer

Green, Sophie M.C. and Smith, Samuel G. (2024) Dataset for a randomised factorial experiment to optimise an information leaflet for women with breast cancer. University of Leeds. [Dataset] https://doi.org/10.5518/1467

Dataset description

Most women with breast cancer are prescribed adjuvant endocrine therapy (AET) to prevent recurrence and mortality, but adherence is low. Negative beliefs about the necessity of AET and high concerns are barriers to adherence. We aimed to optimize the content of an information leaflet intervention, to support AET beliefs. We conducted an online screening experiment using a 2^5 factorial design to optimize the leaflet. The leaflet had five candidate components, each operationalised as factors with two levels; 1) diagrams about AET mechanisms (on/off); 2) infographics displaying AET benefits (enhanced/basic); 3) AET side-effects (enhanced/basic); 4) answers to AET concerns (on/off); 5) breast cancer survivor (patient) input: quotes and photographs (on/off). Healthy adult women (n=1604), recruited via a market research company, were randomized to one of 32 experimental conditions, which determined the combination of components received. Participants completed the beliefs about medicines questionnaire before and after viewing the leaflet. After viewing the leaflet, participants also completed a modified version of the satisfaction with information about medicines questionnaire to assess their satisfaction with information received about AET, and eight true/false questions about AET, to assess their knowledge about AET after reading the leaflet.

Keywords:	breast cancer, medication beliefs, optimization, factorial, information leaflet
Subjects:	A000 - Medicine & dentistry
Divisions:	Faculty of Medicine and Health > School of Medicine > Leeds Institute of Health Sciences (LIHS)
Related resources:	Location Type https://eprints.whiterose.ac.uk/212205/ Publication https://doi.org/10.1093/tbm/ibae029 Publication https://doi.org/10.3310/nihropenres.13547.1 Publication
License:	Creative Commons Attribution 4.0 International (CC BY 4.0)
Date deposited:	14 May 2024 06:51
URI:	https://archive.researchdata.leeds.ac.uk/id/eprint/1278
Additional details Additional details Creators: Creators ORCID Other ID Email Primary affiliation Primary affiliation ID Primary affiliation ID type Secondary affiliation Secondary affiliation ID Secondary affiliation ID type Green, Sophie M.C. https://orcid.org/0000-0002-2622-5377 University of Leeds https://ror.org/024mrxd33 ror Smith, Samuel G. https://orcid.org/0000-0003-1983-4470 University of Leeds https://ror.org/024mrxd33 ror Type of data: Dataset Research funders: Health and Behavior International Collaborative Research Award, sponsored by the International Behavioral Trials Network, NIHR Grant numbers: NIHR300588 Publication date: 2024 Resource language: English Metadata language: English Publisher: University of Leeds Contact Email Address: s.m.c.green@leeds.ac.uk Last Modified: 30 May 2024 13:14

Files

Documentation

Data notes [501kB] Data notes [501kB] Data notes [501kB] Visible to: Anyone File name: Information_Leaflet_Data_Documentation.pdf Content type: Documentation Description: Explanation of the variables in the dataset Mime-Type: application/pdf License: Creative Commons Attribution 4.0 International (CC BY 4.0) File size: 501kB

README.txt [5kB] README.txt [5kB] README.txt [5kB] Visible to: Anyone File name: README.txt Content type: Documentation Mime-Type: text/plain License: Creative Commons Attribution 4.0 International (CC BY 4.0) File size: 5kB

Program

R Script for data cleaning [77kB] R Script for data cleaning [77kB] R Script for data cleaning [77kB] Visible to: Anyone File name: IL_Optimisation_Data_Cleaning_Primary_Secondary_Share.R Content type: Program Description: Code for data cleaning- R Script License: MIT License File size: 77kB