**10/2016 Deviation from the pre-registered protocol:** A mistake in the code used for generating new stimuli caused that only one letter instead of two was randomly changed in each generated word.
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SAMPLE SIZE & SAMPLE DEMOGRAPHICS
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We expect to collect data from 600 participants. The sample will consist of Amazon Mechanical Turk workers. The study materials will be given as a part of a bundle of several unrelated studies. The subjects will be paid for their participation.
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MATERIALS - OVERVIEW
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Materials will be presented and answers will be collected using EFS survey web platform. The exact wording of all used materials can be also found in Materials node.
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DESIGN
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Participants will be randomly divided into two groups – medicines X poisons. They will be asked to read a short vignette describing a hypothetical scenario and then judge harmfulness (on a 7-point scale) of ten medicines (resp. poisons) based on their names. The ten names for both scenarios are randomly drawn from a group of sixty names with different pronounceability ranging from easily to hard pronounceable.
Ten of the names are from Study 1 of Song & Schwarz (2009), rest we obtained from http://www.rxlist.com/drugs/alpha_a.htm using a Python script that can be found in this node. The script also randomly substituted two letters in each word for two random letters from alphabet, so we are not using names of actual drugs. The script initially selected sixty names, ten that sounded most like known medicines were discarded (e.g. Proeesterone or Valacycloeir). Lists of names obtained from running the script can be found in Files. All names are 12 charactes long.
After the end of the data collection, we will obtain a pronounceability rating of all 60 used names from a different sample of mTurk workers using a 7-point scale ranging from 1-easily pronounceable to 7-hard pronounceable.
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Song, H., & Schwarz, N. (2009). If It's Difficult to Pronounce, It Must Be Risky Fluency, Familiarity, and Risk Perception. *Psychological Science, 20*, 135-138.
