Return to the Self-Esteem Matrix Task page
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*** Self-Esteem Matrix Task ***
*** Attentional bias re-training***
*** ABMT - attentional bias modification task***
*** Visual search attentional training task ****
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Script and stimuli generously shared by Dr. Stephane Dandeneau. Thank you!
last updated: 06-30-2020 by K. Borchert (katjab@millisecond.com) for Millisecond Software, LLC
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BACKGROUND INFO
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This script runs the Self-Esteem Matrix Task by:
Dandeneau, S.D., & Baldwin, M. W. (2004). The Inhibition of socially rejecting information
among people with high versus low self-esteem: The Role of Attentional bias and the effects
of bias reduction training. Journal of Social and Clinical Psychology, Vol. 23(4), 584-602.
Dandeneau, S. D., Baldwin, M. W., Baccus, J. R., Sakellaropoulo, M., & Pruessner, J. C. (2007).
Cutting stress off at the pass: Reducing stress and hypervigilance to social threat by manipulating attention.
Journal of Personality and Social Psychology, 93(4), 651-666.
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TASK DESCRIPTION
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Participants view a 4x4 matrix of images and are instructed to find a target stim as fast as possible
(visual search task).
In the experimental condition, the target is a smiling face (all other images are frowny faces).
In the control condition, the target is a 5-petal flower (all other images are 7-petal flowers).
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DURATION
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the default set-up of the script takes appr. 7 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: 'sematrixtask_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.
/ tasktype: 1 = experimental condition (with faces);
2 = control condition (with flowers)
Note: assignment is counterbalanced by groupnumber
response: the participant's final (correct) response
correct: the correctness of the INITIAL response (1 = correct; 0 = incorrect)
Note: participants can only move on if they select the target, however,
the accuracy of the initial selection is stored.
latency: the response latency of the final response (in ms)
picture.target.currentitem: the currently selected target picture
/ targetstim: stores the itemnumber of the current target stimulus
/ targetposition: positions 1-16 in a 4 x 4 matrix
Row1: 1-4
Row2: 5-8
Row3: 9-12
Row4: 13-16
trial.tasktrial.totalcount: counts all trials tasktrial run by this script
trial.tasktrial.totalcorrectcount: counts all initially correct tasktrials run by this script
trial.tasktrial.totalerrorcount: counts all initially incorrect tasktrials run by this script
trial.tasktrial.totalpercentcorrect: percent correct of initially correct tasktrials
trial.tasktrial.totalmeanlatency: mean latency (in ms) of all tasktrials
(2) Summary data file: 'sematrixtask_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)
/ tasktype: 1 = experimental condition (with faces); 2 = control condition (with flowers)
Note: assignment is counterbalanced by groupnumber
trial.tasktrial.totalcount: counts all trials tasktrial run by this script
trial.tasktrial.totalcorrectcount: counts all initially correct tasktrials run by this script
trial.tasktrial.totalerrorcount: counts all initially incorrect tasktrials run by this script
trial.tasktrial.totalpercentcorrect: percent correct of initially correct tasktrials
trial.tasktrial.totalmeanlatency: mean latency (in ms) of all tasktrials
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EXPERIMENTAL SET-UP
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2 conditions: experimental vs. control (assignment by groupnumber)
Experimental Condition: 4x4 matrix with 16 images
* face stimuli
-> 1 target: smiling face
-> 15 distractors: frowny faces
Control Condition: 4x4 matrix with 16 images
* drawings of flowers
-> 1 target: 5 petal flower
-> 15 distractors: 7 petal flowers
General:
* 4 blocks of 28 trials = 112 trials; after each block there is a rest trial
* 16 different actors => each actor is provided as a target stim (smiling) and as a distractor stim (frowny)
* position of target randomly determined with the constraint that the targets appear in each cell equally often
(default: 7 times in each of the 16 cells)
* 16 different targets: randomly determined (7 repetitions of each target-> 112 trials)
* 15 distractors: all faces that are not used as the target are used as distractors; they are
randomly assigned to the remaining 15 cell positions
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STIMULI
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see section Editable Stimuli
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INSTRUCTIONS
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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:
/ stimsize: sets the size of stim pictures in proportion to the canvas height (default: 21.25%)
Note: canvas is defined under section DEFAULTS below
/ leftmargin-
/ topmargin: sets the screen positions of the left and top margins of the matrix relative to
the canvas height and width (default: 10%)