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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: 10-12-2023 by K. Borchert (katjab@millisecond.com) for Millisecond Software, LLC
Script Copyright © 10-12-2023 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 OUTPUT DICTIONARY
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The fields in the data files are:
(1) Raw data file: 'socialevaluationlearningtask_mi_raw*.iqdat'*
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
session: 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
conditionOrder: 'SR -> OR' vs. 'OR -> SR'
condition: 1 = SR (self rating) vs. 2 = OR (other rating) => current rating block
learningTrialCounter: counts learning trials in each 'rule block' (block.LIKE, block.DISLIKE, block.NEUTRAL)
persona: the 'name' of the computer persona currently 'judging'
rule: rule to be learned:
'positive' (persona likes me/George);
'negative' (persona does not like me/George)
'neutral' (persona is indifferent towards me/George)
posWordLocation: stores the current position of the positive word (1-4)
negWordLocation: stores the current position of the negative word (1-4)
Note: 1: upper left; 2: upper right; 3 = lower right; 4 = lower left (clockwise)
posWord: stores the currently presented positive word
negWord: stores the currently presented negative word
incorrResp: stores the incorrect word ("posWord" or "negWord")
corrResp: stores the correct word ("posWord" or "negWord")
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
feedback: 1 = positive feedback for positive words/negative feedback for negative words
2 = 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 feedback = 1; 2 trials have feedback = 0
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'*
inquisit.version: Inquisit version run
computer.platform: the platform the script was run on (win/mac/ios/android)
startDate: date script was run
startTime: time script was started
subjectId: assigned subject id number
groupId: assigned group id number
sessionId: assigned session id number
elapsedTime: time it took to run script (in ms); measured from onset to offset of script
completed: 0 = script was not completed (prematurely aborted);
1 = script was completed (all conditions run)
sr: self referential;
or: other ('George') referential
conditionOrder: 'SR -> OR' vs. 'OR -> SR'
personaSR: the names used in the SR condition
personaOR: the names used in the OR condition
ratingLikeSR: stores the rating for the LIKE SR condition on a scale from 0 = totally dislike to 100 = totally like
ratingDislikeSR: stores the rating for the DISLIKE SR condition on a scale from 0 = totally dislike to 100 = totally like
ratingNeutralSR: stores the rating for the NEUTRAL SR condition on a scale from 0 = totally dislike to 100 = totally like
ratingLikeOR: stores the rating for the LIKE OR condition on a scale from 0 = totally dislike to 100 = totally like
ratingDislikeOR: stores the rating for the DISLIKE OR condition on a scale from 0 = totally dislike to 100 = totally like
ratingNeutralOR: stores the rating for the NEUTRAL OR condition on a scale from 0 = totally dislike to 100 = totally like
propLikeRespLikeSR: proportion of selecting the positive word in SR 'LIKE' condition
(=> proportion correct responses in SR 'LIKE' condition)
meanRTLikeRespLikeSR: mean response time in ms of selecting positive word in SR 'LIKE' condition
propLikeRespDislikeSR: proportion of selecting the positive word in SR 'DISLIKE' condition
(=> proportion error responses in SR 'DISLIKE' condition)
meanRTLikeRespDislikeSR: mean response time in ms of selecting positive word in SR 'DISLIKE' condition
propLikeRespNeutralSR: proportion of selecting the positive word in SR 'NEUTRAL' condition
(=> proportion correct responses in SR 'NEUTRAL' condition)
meanRTLikeRespNeutralSR: mean response time in ms of selecting positive word in SR 'NEUTRAL' condition
propLikeRespLikeOR: proportion of selecting the positive word in OR 'LIKE' condition
(=> proportion correct responses in OR 'LIKE' condition)
meanRTLikeRespLikeOR: mean response time in ms of selecting positive word in OR 'LIKE' condition
propLikeRespDislikeOR: proportion of selecting the positive word in OR 'DISLIKE' condition
(=> proportion errir responses in OR 'DISLIKE' condition)
meanRTLikeRespDislikeOR: mean response time in ms of selecting positive word in OR 'DISLIKE' condition
propLikeRespNeutralOR: proportion of selecting the positive word in OR 'NEUTRAL' condition
(=> proportion correct responses in OR 'NEUTRAL' condition)
meanRTLikeRespNeutralOR: mean response time in ms of selecting positive word in OR 'NEUTRAL' condition
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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)
