'Effect of insufficient information on antibiotic expectations and requests' (AsPredicted #4915)
Author(s) Alistair Thorpe (University of Essex) - alistairthorpe8@gmail.com Miroslav Sirota (University of Essex) - msirota@essex.ac.uk Marie Juanchich (University of Essex) - m.juanchich@essex.ac.uk Sheina Orbell (University of Essex) - sorbell@essex.ac.uk
Pre-registered on 07/21/2017 01:39 AM (PT)
1) Have any data been collected for this study already? No, no data have been collected for this study yet
2) What's the main question being asked or hypothesis being tested in this study? We test whether expectations and requests for unnecessary antibiotics from the general public are driven by imperfect or incomplete information about diseases and about antibiotics. We predict that the provision of information from a medical professional (either only regarding antibiotics, only regarding the nature of the disease or regarding both) will reduce requests and expectations for an unnecessary prescription of antibiotics. Thus, we expect that the provision of complete information about antibiotic efficacy and the nature of the disease from a medical professional will have the greatest reduction for expectations and requests for an unnecessary prescription of antibiotics.
3) Describe the key dependent variable(s) specifying how they will be measured. Expectations for antibiotics: average of 4 items measured on a 6-point scale (1 = Strongly Disagree to 6 = Strongly Agree)
Expectations of doctors prescribing: average of 4 items measured on a 6-point scale (1 = Strongly Disagree to 6 = Strongly Agree)
Request for antibiotics: average of 4 items measured on a 6-point scale (1 = I certainly would not to 6 = I certainly would)
4) How many and which conditions will participants be assigned to? In a 2(disease information: no information vs. viral information) × 2(antibiotics suitability: no information vs. information about antibiotic efficacy) between-subjects design, participants will express their expectations for antibiotics, expectations of doctors prescribing and request for antibiotics. Thus, four conditions with information provided by the medical professional being manipulated:
1) Information about antibiotic efficacy × Viral information
2) No information about antibiotic efficacy × Viral information
3) Information about antibiotic efficacy × No viral information
4) No information about antibiotic efficacy × No viral information
5) Specify exactly which analyses you will conduct to examine the main question/hypothesis. A two-way factorial ANOVA. With 2(disease information: no information vs. viral information) × 2(antibiotics suitability: no information vs. information about antibiotic efficacy) predicting expectations for antibiotics, expectations of doctors prescribing and requests for antibiotics.
We will also then conduct subsequent two-way factorial ANCOVAs. The covariates will be:
1. Pre-existing beliefs about antibiotics and cold perception.
2. Previous medical behaviour and previous medical history
6) Any secondary analyses? We will also perform the same analysis using the Bayesian equivalents. Bayesian analysis of variance (BANOVA) and Bayesian analysis of covariance BANCOVA.
7) How many observations will be collected or what will determine sample size? No need to justify decision, but be precise about exactly how the number will be determined. 187 participants will complete the experiment. Recruited from the ESSEXLab participant pool. Collection will stop once 187 participants have participated or until 31st December (whichever comes first).
8) Anything else you would like to pre-register? (e.g., data exclusions, variables collected for exploratory purposes, unusual analyses planned?) We will include a number of questions for exploratory purposes regarding respondents’ general demographics. We will exclude respondents from analysis who take less than 1/3 of the median time to fully complete the study.
