Return to the Reading the Mind in the Eyes Test - Revised page
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											Eyes Test
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Script Author: Katja Borchert, Ph.D. (katjab@millisecond.com) for Millisecond Software, LLC
Date: 02-26-2017
last updated:  11-11-2019 by K. Borchert (katjab@millisecond.com) for Millisecond Software, LLC

Script Copyright © 11-11-2019 Millisecond Software

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BACKGROUND INFO 	
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This script implements a computerized version of the revised Eyes Test; a test of social sensitivity.
The script is based on:

Baron-Cohen, S., Wheelwright, S., Hill, J., Raste, Y., & Plumb, I. (2001). The 'Reading the Mind in the Eyes' Test Revised Version:
A Study with Normal Adults, and Adults with Asperger Syndrome or High-functioning Autism.
Journal of Child Psychiatry and Psychiatry, 42, 241-252

Materials are downloadable from the following link:
https://www.autismresearchcentre.com/arc_tests/

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TASK DESCRIPTION	
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Participants are given 36 photographs of people's eyes and four word descriptions that describe the possible 
mental state of the person in question. Participants are asked to select the option that they think best
describes the mental state of the person. There is no time limit to this test and participants can look up
the descriptions of the words anytime they need to.

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DURATION 
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the default set-up of the script takes appr. 7 minutes to complete

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DATA FILE INFORMATION 
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The default data stored in the data files are:

(1) Raw data file: 'eyestest_raw*.iqdat' (a separate file for each participant)*

build:								The specific Inquisit version used (the 'build') that was run
computer.platform:				the platform the script was run on (win/mac/ios/android)
date, time, 						date and time script was run 
subject, group, 					with the current subject/groupnumber
script.sessionid:					with the current session id

blockcode, blocknum:			the name and number of the current block (built-in Inquisit variable)
trialcode, trialnum: 				the name and number of the currently recorded trial (built-in Inquisit variable)
										Note: trialnum is a built-in Inquisit variable; it counts all trials run; even those
										that do not store data to the data file. 
										
gender:							"f"(emale) 	vs. "m"(ale)	(gender of image)
trialcount:						trial counter
image:								stores the current image name
word1:								stores the current word1 (top left)
word2:								stores the current word2 (top right)
word3:								stores the current word3 (bottom left)
word4:								stores the current word4 (bottom right)
corrResp:							the correct response (1-4)							
response:							the participant's response: selected word (word1-word4)

correct:							accuracy of response: 
									1 = correct response; 
									0 = otherwise

latency: 							the response latency (in ms) of current trial; measured from: onset of image until response is selected

rt:									the cumulative time (in ms) spent on the current image (includes time spent on dictionary);
									measured from onset of image until a word is selected
								
countCorr:						running count of correctly identified expressions


(2) Summary data file: 'eyestest_summary*.iqdat' (a separate file for each participant)*

Computer Platform:				the platform the script was run on (win/mac/ios/android)
Date:								date script was run
Time:								time script was started
Subject ID:							assigned subject id number
Group ID:							assigned group id number
Session ID:							assigned session id number
Script Duration:					time it took to run script (in ms); measured from onset to offset of script
Script Completion:				0 = script was not completed (prematurely aborted); 
									1 = script was completed (all conditions run)
								
generalPopulation_MeanNumberCorrect:	the reported correct count of the general population tested by Baron-Cohen et al (2001, p. 245)						
values.generalPopulation_PropCorrect:	proportion correct of the general population tested by Baron-Cohen et al (2001	)					
generalPopulation_SD:			the reported standard deviation of correct counts of the general population tested by Baron-Cohen et al (2001, p. 245)									
								
countCorr:						count of correctly identified expressions

propCorrect:						proportion correctly identified expressions
									=> the higher the amount, the higher social sensitivity
									
z_value:							the z-value of the Correct Count (using the General Population Correct Count)	
p_value:							the p-value of the correct count	
									
meanRT:							mean latency (ms) of correctly identified expressions

* separate data files: to change to one data file for all participants (on Inquisit Lab only), go to section
"DATA" and follow further instructions

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EXPERIMENTAL SET-UP 
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(1) Practice: 1 image
(2) Test: Part1: 17 images
(3) Test: Part2: 19 images

Trial: an image is presented with 4 surrounding words, guessing probability = 0.25
Chance Performance = 36*0.25 = 9 items

Note: images are presented in a fixed sequence

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STIMULI
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provided by Millisecond Software - can be edited under section Editable Stimuli

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INSTRUCTIONS 
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provided by Millisecond Software - can be edited under section Editable Instructions

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EDITABLE CODE 
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check below for (relatively) easily editable parameters, stimuli, instructions etc. 
Keep in mind that you can use this script as a template and therefore always "mess" with the entire code 
to further customize your experiment.

The parameters you can change are:
/showSummaryFeedback:				true (1): participants are given the number of correctly selected emotions and their median reaction time
									false (0): no performance feedback is provided at the end