1. ABOUT THE DATASET -------------------- Title: Data associated with 'Optimization of an information leaflet to influence medication beliefs in women with breast cancer: a randomized factorial experiment' Creator(s): Sophie M. C. Green[1], Louise H. Hall[1], David P. French[2], Nikki Rousseau[3], Catherine Parbutt[4], Rebecca Walwyn[3], Samuel G. Smith[1] , on behalf of the ROSETA investigators Organisation(s): 1. Leeds Institute of Health Sciences, University of Leeds, UK 2. Manchester Centre for Health Psychology, University of Manchester, UK 3. Leeds Institute of Clinical Trials Research, University of Leeds, UK 4. Medicines Management and Pharmacy Services, Leeds Teaching Hospitals NHS Trust Leeds, UK Rights-holder(s):Unless otherwise stated, Copyright 2022 University of Leeds Publication Year: 2023 Description: Most women with breast cancer are prescribed adjuvant endocrine therapy (AET) to prevent recurrence and mortality, but adherence is suboptimal. 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 components, each 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 levels of components received. Participants completed the beliefs about medicines questionnaire before and after viewing the leaflet. We estimated the man effects and all interactions on the primary outcome; beliefs about AET. Cite as: Sophie M. C. Green, Louise H. Hall, David P. French, Nikki Rousseau, Catherine Parbutt, Rebecca Walwyn, Samuel G. Smith, on behalf of the ROSETA investigators. Optimization of an information leaflet to influence medication beliefs in women with breast cancer: a randomized factorial experiment. University of Leeds. [Dataset]. https://doi.org/10.5518/1302 Related publication: Sophie M. C. Green, Louise H. Hall, David P. French, Nikki Rousseau, Catherine Parbutt, Rebecca Walwyn, Samuel G. Smith, on behalf of the ROSETA investigators. Optimization of an information leaflet to influence medication beliefs in women with breast cancer: a randomized factorial experiment. Accepted in Annals of Behavioral Medicine. 2023. Contact: Sophie M. C. Green. Leeds Institute of Health Science, University of Leeds, Clarendon Way, Leeds, LS2 9NL, UK. Email: S.m.c.green@leeds.ac.uk 2. TERMS OF USE --------------- This dataset is licensed under a Creative Commons Attribution 4.0 International Licence: https://creativecommons.org/licenses/by/4.0/.] 3. PROJECT AND FUNDING INFORMATION ---------------------------------- Title: Refining and Optimising a behavioural intervention to support endocrine therapy adherence (ROSETA) Dates: 2020-2026 Funding organisation: NIHR Grant no.: This report is independent research supported by the National Institute for Health Research NIHR Advanced Fellowship, Dr Samuel Smith NIHR300588. Smith also acknowledges funding support from a Yorkshire Cancer Research University Academic Fellowship. DF is funded in part by the NIHR Manchester Biomedical Research Centre (He). SG acknowledges receipt of a Health and Behavior International Collaborative Research Award, sponsored by the International Behavioral Trials Network. The views expressed in this publication are those of the author(s) and not necessarily those of the NHS, the National Institute for Health Research or the Department of Health and Social Care. The funders had no role in the design of the study, data collection, analysis, interpretation of data, and in the writing of this manuscript. 4. CONTENTS ----------- File listing Folder: Raw_Data Files: IL_Optimisation_Data_Primary.csv- CSV file containing the raw dataset without the R scripts applied to it. Folder: Raw_Data File: IL_Data_Cleaned_Primary_Full.csv- CSV file containing the cleaned dataset after that data cleaning R script has been applied to the raw dataset. Folder: R_Scripts Files: 1. IL_Optimisation_Data_Cleaning_Primary_Outcome_Share.R- R script containing code used to clean the data. 2. IL_Optimisation_Data_Analysis_PrimaryOutcome_Share.R- R script for analysis of the factorial experiment (analysis included in associated publication) 5. METHODS ---------- The full methods of this paper are described in the associated publication: Sophie M. C. Green, Louise H. Hall, David P. French, Nikki Rousseau, Catherine Parbutt, Rebecca Walwyn, Samuel G. Smith, on behalf of the ROSETA investigators. Optimization of an information leaflet to support medication beliefs in women with breast cancer: a randomized factorial experiment. Submitted. A preprint of this work, containing the methods is available at: https://osf.io/b964s/