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'Me-not Me' Reaction Time Task
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Script Author: Katja Borchert, Ph.D. (katjab@millisecond.com) for Millisecond Software, LLC
Date: 09-20-2017
last updated: 10-31-2019 by K. Borchert (katjab@millisecond.com) for Millisecond Software, LLC
Script Copyright © 10-31-2019 Millisecond Software
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BACKGROUND INFO
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This script implements a computerized version of the the 'Me-not me' reaction time task;
a task to study self-concept particularly in the context of relationships.
The implemented procedure is similarly to the one described in:
Aron, A, Tudor, M, Aron, E, & Nelson, G. (1991). Close relationships as including other in the self.
Journal of Personality and Social Psychology, 60(Feb 91), 241-253.
Slotter, E.B. ; Gardner, W.L. & Simpson, J. (2009). Where Do You End and I Begin? Evidence for Anticipatory,
Motivated Self–Other Integration Between Relationship Partners.
Journal of Personality and Social Psychology, Vol.96(6), pp.1137-1151
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TASK DESCRIPTION
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Participants are presented a series of trait descriptors, one at a time in the middle of the screen,
and are asked to sort the traits as fast as possible via a keypress into category 'me' (-> applies to me a lot)
or 'not me' (-> doesn't really apply to me).
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DURATION
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the default set-up of the script takes appr. 2 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: 'menotme_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.
values.countCategorizationBlocks: running total of all test categorization blocks
values.countCategorizationTrials: running total of the trials within each categorization block
stimulusitem: the presented stimuli in order of trial presentation
values.valence: valence of the presented trait: "positive" vs. "negative" vs. "neutral"
response: scancode of the selected response key (e.g. 18 = E; 23 = I)
values.responseCategory: response category selected: "me" vs. "not me"
latency: the response latency (in ms); measured from:
(2) Summary data file: 'menotme_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)
expressions.meanRT_me: mean latency (in ms) of 'me' categorization across all trait words
expressions.meanRT_notme: mean latency (in ms) of 'notme' categorization across all trait words
expressions.meanRT_me_positive: mean latency (in ms) of 'me' categorization across all positive trait words
expressions.meanRT_me_negative: mean latency (in ms) of 'me' categorization across all negative trait words
expressions.meanRT_me_neutral: mean latency (in ms) of 'me' categorization across all neutral trait words
expressions.meanRT_notme_positive: mean latency (in ms) of 'not me' categorization across all positive trait words
expressions.meanRT_notme_negative: mean latency (in ms) of 'not me' categorization across all negative trait words
expressions.meanRT_notme_neutral: mean latency (in ms) of 'not me' categorization across all neutral trait words
* 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 Block: 5 practice traits are presented to practice the procedure
The practice block turns into the test block without further instructions
(2) Test Block:
* by default the test blocks runs once (see editable parameters.nrCategorizationBlocks)
* by default, each test block runs 45 items
(15 positively valenced descriptors, 15 neutral descriptors, 15 negatively valenced descriptors)
=> number of traits presented adapts automatically to the number of traits listed under item.traits
(see section Editable Stimuli)
* order of traits is selected randomly
Trial Sequence:
trait presented until categorization response -> ITI (default:1000ms)
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STIMULI
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trait words for this script were selected from:
Anderson, N. H. (1968). Likableness ratings of 555 personality-trait
words. Journal of Personality and Social Psychology. 9, 272-279.
Positive Traits: likeability score > 450
Neutral Traits: 350 > likeability score > 250
Negative Traits: 150 > likeability score
(the likeability scores of the default practice traits in this script fall outside these ranges)
The traits can easily be adapted 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:
Response Keys: 'Tools -> keyboard scancodes'
/leftKey: the scancode of the left response key
/leftKey_label: the label of the left response key (here: E)
/rightKey: the scancode of the right response key
/rightKey_label: the label of the right response key (here: I)
/leftcategory: 1 = category 'me'; 2 = category 'not me' (left category is assigned 'me' category)
/leftcategory_label: label of left category ('me')
/rightcategory: 1 = category 'me'; 2 = category 'not me' (right category is assigned 'not me' category)
/rightcategory_label: label of right category ('not me')
/traitSize: size of trait descriptor proportional to canvas height (default: 8%)
/iti: intertrial duration (in ms) (default: 1000ms)
/readyDuration: duration (in ms) of the 'get ready' trial (default: 5000ms)
/nrCategorizationBlocks: number of times the categorization blocks runs (default: 1)