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					*SOCIAL EVALUATION LEARNING TASK (mouse/touchscreen version)*
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Script Author: Katja Borchert, Ph.D. (katjab@millisecond.com) for Millisecond Software, LLC
Date: 03-14-2018
last updated:  10-29-2019 by K. Borchert (katjab@millisecond.com) for Millisecond Software, LLC

Script Copyright © 10-29-2019 Millisecond Software

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BACKGROUND INFO 	
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This script implements a Social Evaluation Learning Task that allows to contrast perceived
social evaluations of 'self' vs. social evaluations of 'others'.

The implemented procedure is based on:

Button, K.S., Kounali, D., Stapinski, L., Rapee, R.M, Lewis, G., & Munafò, M.R.M (2015).
Fear of Negative Evaluation Biases Social Evaluation Inference: Evidence from a
Probabilistic Learning Task. PLOS ONE | DOI:10.1371/journal.pone.0119456

Stimuli published in:
Button KS, Browning M, Munafo MR, Lewis G (2012) Social inference and social anxiety: evidence of a
fear-congruent self-referential learning bias. J Behav Ther Exp Psychiatry 43: 1082–1087. doi: 10.
1016/j.jbtep.2012.05.004 PMID: 22699043

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TASK DESCRIPTION	
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Participants encounter 6 computer personas across 2 learning tasks during which they have to learn whether 
the computer personas like them (self referential task, SR) or like 'George' (other referential task, OR).
At the end of the SR condition, participants have to guess if the computer persona (e.g. 'Alex') likes them based on 
learning what 'Alex' thinks of them. To learn what 'Alex' thinks of them, participants are given word pairs
(e.g. 'witty' vs. 'dull') and are asked to choose the word that corresponds to what 'Alex' thinks of them.
Feedback contingencies corresponded to 3 rules, 'like', 'neutral' and ''dislike', with P[positive word correct] = 0.8, 
0.5 and 0.2, respectively. Each feedback contingency block is coupled with a different persona.
In the OR condition, participants have to guess if the computer persona (e.g. 'Charlie') likes a person named
'George' using the same set-up.

Note: this task runs with mouse/touchscreen selections

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DURATION 
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the default set-up of the script takes appr. 15 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: 'socialevaluationlearningtask_mi_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 such as feedback trials. Thus, trialnum 
										may not reflect the number of main trials run per block. 
									
SR = self referential; 
OR = other ('George') referential	
										
values.conditionOrder:						'SR -> OR' vs. 'OR -> SR'
values.condition:							1 = SR (self rating) vs. 2 = OR (other rating) => current rating block	
																
values.LearningTrialCounter:				counts learning trials in each 'rule block' (block.LIKE, block.DISLIKE, block.NEUTRAL) 
									
values.persona:							the 'name' of the computer persona currently 'judging'
values.rule:								rule to be learned: 
										'positive' (persona likes me/George); 
										'negative' (persona does not like me/George)
										'neutral'  (persona is indifferent towards me/George)									
									
values.posWord_location:					stores the current position of the positive word (1-4)
values.negWord_location:					stores the current position of the negative word (1-4)
										Note: 1: upper left; 2: upper right; 3 = lower right; 4 = lower left (clockwise)	
									
values.posWord:							stores the currently presented positive word
values.negWord:							stores the currently presented negative word
	
values.incorrResp:						stores the response key (in scancode) associated with the incorrect word
values.corrResp:							stores the response key (in scancode) associated with the correct word
										Note: 16 = q; 25 = p, 44 = z; 50 = m

response:								the participant's response


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

										Learning Trials:
										LIKE/NEUTRAL condition: 1 = participant chose positive word; 0 = otherwise
										DISLIKE condition: 1 = participant chose negative word; 0 = otherwise
									
										Rating Trials:
										correct = 1 has no meaning
																		
latency: 									the response latency (in ms); measured from: onset of word pairs

values.feedback:							1 = positive feedback for positive words/negative feedback for negative words
										= negative feedback for positive words/positive feedback for negative words
										Note: across every 10 trials, the selection of 1/0 should reflect the feedback-contingency of the block
										Example: condition 'LIKE': across every 10 trials, 8 trials have values.feedback = 1; 2 trials have values.feedback = 0

values.selectFeedbackStim:				1 = correct; 2 = incorrect
										(Note: the presented feedback is NOT based on ACC, but rather on the probability of 
										giving consistent feedback with the current rule)

rating:									converts the rating into a discrete scale from:
										0 = completely dislike to 100 = completely like									
									
								
								
(2) Summary data file: 'socialevaluationlearningtask_mi_summary*.iqdat' (a separate file for each participant)*

computer.platform:				the platform the script was run on (win/mac/ios/android)
script.startdate:					date script was run
script.starttime:					time script was started
script.subjectid:					assigned subject id number
script.groupid:					assigned group id number
script.sessionid:					assigned session id number
script.elapsedtime:				time it took to run script (in ms); measured from onset to offset of script
script.completed:					0 = script was not completed (prematurely aborted); 
								1 = script was completed (all conditions run)

SR = self referential; 
OR = other ('George') referential
									
values.conditionOrder:						'SR -> OR' vs. 'OR -> SR' 

values.persona_SR:							the names used in the SR condition
values.persona_OR:							the names used in the OR condition

values.rating_LIKE_SR:						stores the rating for the LIKE SR condition on a scale from 0 = totally dislike to 100 = totally like
values.rating_DISLIKE_SR:						stores the rating for the DISLIKE SR condition on a scale from 0 = totally dislike to 100 = totally like
values.rating_NEUTRAL_SR:					stores the rating for the NEUTRAL SR condition on a scale from 0 = totally dislike to 100 = totally like

values.rating_LIKE_OR:						stores the rating for the LIKE OR condition on a scale from 0 = totally dislike to 100 = totally like
values.rating_DISLIKE_OR:						stores the rating for the DISLIKE OR condition on a scale from 0 = totally dislike to 100 = totally like
values.rating_NEUTRAL_OR:					stores the rating for the NEUTRAL OR condition on a scale from 0 = totally dislike to 100 = totally like

expressions.propLikeResp_LIKE_SR:			proportion of selecting the positive word in SR 'LIKE' condition
											(=> proportion correct responses in SR 'LIKE' condition)
										
expressions.meanRT_likeResp_LIKE_SR:		mean response time in ms of selecting positive word in SR 'LIKE' condition

expressions.propLikeResp_DISLIKE_SR:			proportion of selecting the positive word in SR 'DISLIKE' condition
											(=> proportion error responses in SR 'DISLIKE' condition)
										
expressions.meanRT_likeResp_DISLIKE_SR:		mean response time in ms of selecting positive word in SR 'DISLIKE' condition

expressions.propLikeResp_NEUTRAL_SR:		proportion of selecting the positive word in SR 'NEUTRAL' condition
											(=> proportion correct responses in SR 'NEUTRAL' condition)
										
expressions.meanRT_likeResp_NEUTRAL_SR:		mean response time in ms of selecting positive word in SR 'NEUTRAL' condition

expressions.propLikeResp_LIKE_OR:				proportion of selecting the positive word in OR 'LIKE' condition
												(=> proportion correct responses in OR 'LIKE' condition)
										
expressions.meanRT_likeResp_LIKE_OR:			mean response time in ms of selecting positive word in OR 'LIKE' condition

expressions.propLikeResp_DISLIKE_OR:				proportion of selecting the positive word in OR 'DISLIKE' condition
												(=> proportion errir responses in OR 'DISLIKE' condition)
										
expressions.meanRT_likeResp_DISLIKE_OR:			mean response time in ms of selecting positive word in OR 'DISLIKE' condition

expressions.propLikeResp_NEUTRAL_OR:			proportion of selecting the positive word in OR 'NEUTRAL' condition
												(=> proportion correct responses in OR 'NEUTRAL' condition)
										
expressions.meanRT_likeResp_NEUTRAL_OR:		mean response time in ms of selecting positive word in OR 'NEUTRAL' condition


* 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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* order of SR (self-referential) vs. OR (other-referential) conditions is counterbalanced by groupnumber
odd groupnumbers : SR->OR
even groupnumbers: OR->SR

* personas are selected randomly for each condition from a pool
of three gender-neutral (English speaking countries) names (see list.personas_SR and list.personas_OR)

SR condition: (reference: self)
- 3 blocks: like, neutral, dislike (order is randomly determined)
- each block runs 32 trials, randomly selecting word pairs from a pool of 64 word pairs (no repeats within a block)
- one word of each word pair is 'positive', the other 'negative'
- the two words are randomly assigned to one of 4 screen locations (upper left, upper right, lower right, lower left)

- LIKE-block: across every 10 trials, participants receive positive feedback if they select the positive description 8 times
(2 randomly selected times, participants get negative feedback for selecting the positive word;
the contingeny is reversed for selecting the negative description)

- NEUTRAL-block: across every 10 trials, participants receive positive feedback if they select the positive description 5 times
(5 randomly selected times, participants get negative feedback for selecting the positive word;
the contingeny is reversed for selecting the negative description)

- DISLIKE-block: across every 10 trials, participants receive positive feedback if they select the positive description 2 times
(8 randomly selected times, participants get negative feedback for selecting the positive word;
the contingeny is reversed for selecting the negative description)

- at the end of each block, participants are asked to decide whether the computer liked them or disliked them and with what
probability (e.g. '70% liked me')

OR condition (reference: a person named George)
- same set up as SR blocks

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STIMULI
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see Button et al (2012)
stimuli under section 'Editable Stimuli'

Note: all elements that present text can be found under section 'Editable Stimuli', 'Editable Instructions'
or 'Editable Lists' for easy editing/translating of the task

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INSTRUCTIONS 
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generated based on Button et al (2015) and an eprime script running the task
see 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:

/feedbackDuration:			the duration (in ms) of the feedback (default: 2000ms)