___________________________________________________________________________________________________________________ *SOCIAL EVALUATION LEARNING TASK* ___________________________________________________________________________________________________________________ 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 ___________________________________________________________________________________________________________________ BACKGROUND INFO ___________________________________________________________________________________________________________________ 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 ___________________________________________________________________________________________________________________ TASK DESCRIPTION ___________________________________________________________________________________________________________________ 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: due to the nature of using 4 spatially oriented response keys this task requires a machine with an attached keyboard. Script 'socialevaluationlearningtask_MI.iqjs' runs the same task with mouse/touchscreen input. ___________________________________________________________________________________________________________________ DURATION ___________________________________________________________________________________________________________________ the default set-up of the script takes appr. 15 minutes to complete ___________________________________________________________________________________________________________________ DATA OUTPUT DICTIONARY ___________________________________________________________________________________________________________________ The fields in the data files are: (1) Raw data file: 'socialevaluationlearningtask_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 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 response key (in scancode) associated with the incorrect word 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 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_summary*.iqdat' (a separate file for each participant)* 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 * separate data files: to change to one data file for all participants (on Inquisit Lab only), go to section 'DATA' and follow further instructions _________________________________________________________________________________________________________________ EXPERIMENTAL SET-UP ___________________________________________________________________________________________________________________ * 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 ___________________________________________________________________________________________________________________ STIMULI ___________________________________________________________________________________________________________________ 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 ___________________________________________________________________________________________________________________ INSTRUCTIONS ___________________________________________________________________________________________________________________ generated based on Button et al (2015) and an eprime script running the task see section 'Editable Instructions' ___________________________________________________________________________________________________________________ EDITABLE CODE ___________________________________________________________________________________________________________________ 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: /topLeftKey: the top left key (default: q) /topRightKey: the top right key (default: p) /bottomLeftKey: the bottom left key (default: z) /bottomRightKey: the bottom right key (default: m) Note: if the response keys are changed, picture.keyboard needs to be updated /feedbackDuration: the duration (in ms) of the feedback (default: 2000ms)