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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)