Self-Esteem GNAT

Technical Manual

This script is in part based on the original gnatdemo.iqjs by Brian Nosek (nosek@virginia.edu)
Millisecond thanks Dr. Debbie Roy for her collaboration on this script!

Last Modified: January 07, 2024 by K. Borchert (katjab@millisecond.com), Millisecond

Script Copyright © Millisecond Software, LLC

Background

This script implements a Self Esteem Go-Nogo Association Task (GNAT), a measure of a global marker for ego fragility.

In general, the GNAT uses the Go-Nogo framework of responding to signal and noise stimuli to investigate implicit bias towards a target category. In contrast to reaction time based tests of implicit bias (e.g. Implicit Association Test), the GNAT framework mainly focuses on accuracy data and specifically d prime measures (measures of sensitivity to distinguish signals from noise in signal detection theory) to infer implicit bias.

For example, a positive association of 'nice-ME (the target signal) is suggested if the dprime measure in the condition 'nice-ME' (aka both me-targets and nice attributes and are signals) is greater than the dprime measure in the condition 'nasty-ME' (aka me-targets and nasty attributes are signals).

This script implements the self esteem Go-Nogo Association Task (GNAT) similarly to the one described in:

Gregg, A. & Sedikides, C. (2010). Narcissistic Fragility: Rethinking Its Links to Explicit and Implicit Self-esteem, Self and Identity, 9:2, 142-161

GNAT Literature

References

Nosek, B. A., & Banaji, M. R. (2001). The go/no-go association task. Social Cognition, 19(6), 625-666.

Duration

10 minutes

Description

Participants are asked to categorize nice and nasty words (e.g. "friendship"; "murder") and target items (e.g 'myself', 'them') into predetermined categories via keystroke presses. The basic task is to press the Spacebar if an item (e.g. "friendship") belongs to the category currently being tested (e.g. "nice") and to do nothing if it doesn't. For practice, participants sort items into categories "nice", "nasty", "me", and "not me". For the test, participants are asked to sort categories into the paired categories (e.g. "me OR nice"). When an item belongs to either one of these two categories, participants should press the Spacebar. Otherwise they should do nothing.

Procedure

Default GNAT Set-Up in this script:
(1) 4 training blocks: one training block each for targetA (here: me), targetB (here: not me), attributeA (here: Nice),
attributeB (here: Nasty)
with response timeout of 600ms
-> block order is determined randomly
-> run 20 trials each (10 target:10 noise)

(2) 4 test blocks that combine targets and attributes with a response timeout (default: 600ms)
-> block order is determined randomly
-> each block runs 16 'practice trials' followed by 48 test trials (summary variables based on test trial performance only)
-> signal : noise = 1 : 1 (samenumber of attributeA, attributeB, signal and noise trials)
-> each attribute (12) is selected once during the test trials
-> each target is repeated 4x during the test trials

Stimuli

see section Editable Stimuli (stimuli from Gregg & Sedikides, 2010)

Instructions

see section Editable Instructions

Summary Data

File Name: selfesteemgnat_summary*.iqdat

Data Fields

NameDescription
inquisit.version Inquisit version number
computer.platform Device platform: win | mac |ios | android
startDate Date the session was run
startTime Time the session was run
subjectId Participant ID
groupId Group number
sessionId Session number
elapsedTime Session duration in ms
completed 0 = Test was not completed
1 = Test was completed
Parameter Values
responseTimeout1Signal Stores the response timeouts in ms used for signals in the testblocks in this script
responseTimeout1Noise Stores the response timeouts in ms used for noise in in the testblocks in this script
targetALabel The category used for target A
targetBLabel The category used for target B
attributeALabel The category used for attribute A
attributeBLabel The category used for attribute B
propCorrectAA Overall proportion correct for pairing targetA-attributeA (here: me-nice); test trials only
propCorrectAB Overall proportion correct for pairing targetA-attributeB (here: me-nasty); test trials only
propCorrectBA Overall proportion correct for pairing targetB-attributeA (here: not me-nice); test trials only
propCorrectBB Overall proportion correct for pairing targetB-attributeB (here: not me-nasty); test trials only
TARGET A Conditions
signals = ME
AA Condition
signals = ME OR nice
noise = anything else (NOT ME OR nasty)
rHitAA Hit rate for pairing targetA-attributeA across all responsetimeouts; test trials only
hit: pressing spacebar for signals (ME OR nice) in AA condition
rMissAA Miss rate for pairing targetA-attributeA across all responsetimeouts; test trials only
miss: not pressing spacebar for signals (ME OR nice) in AA condition
rFaAA False alarm (FA) rate for pairing targetA-attributeA across all responsetimeouts; test trials only
false alarm: pressing spacebar for noise stims (NOT ME OR nasty) in AA condition
rCrAA Correct rejection (CR) for pairing targetA-attributeA across all responsetimeouts; test trials only
cr: not pressing spacebar for noise stims (NOT ME OR nasty) in AA condition
zHitAA Z-score of hit rate for pairings targetA-attributeA (here: ME-nice)
zFaAA Z-score of FA rate for pairings targetA-attributeA (here: ME-nice)
*Adjustments to z-scores as recommended by
Gregg, A. & Sedikides, C. (2010). Narcissistic Fragility
Rethinking Its Links to Explicit and Implicit Self-esteem, Self and Identity, 9:2, 142-161 (p.148)
=> Adjustments are made if the FArate (hitRate) = 0 (increased to 0.005) or 1 (decreased to 0.995)*
dPrimeAA Computes d' (parametric measure of discriminability btw. signals and noise) for 'ME-nice' Pairings
=> Range (in this script)
-5.1516586840152740479 <= dprime <= 5.1516586840152740479 (=perfect performance)
=> The higher the value, the better signals (go stims) were distinguished from noise (nogo stims)
(d' = 0: chance performance; negative d-primes: participant treated nontargets as targets and targets as nontargets)
cAA C-criterion in signal detection:The absolute value of c provides an indication of the strength of
the response bias/response style
negative: participant more likely to report that signal (go stims) is present (liberal response style)
may favor faster responding in speed-accuracy trade-off response paradigms
positive: favoring caution (conservative response style)
AB Condition
signals = ME OR nasty
noise = anything else (NOT ME OR nice)
rHitAB Hit rate for pairing targetA-attributeB across all responsetimeouts; test trials only
hit: pressing spacebar for signals (ME OR nasty) in AB condition
rMissAB Miss rate for pairing targetA-attributeB across all responsetimeouts; test trials only
miss: not pressing spacebar for signals (ME OR nasty) in AB condition
rFaAB False alarm (FA) rate for pairing targetA-attributeB across all responsetimeouts; test trials only
false alarm: pressing spacebar for noise stims (NOT ME OR nice) in AB condition
rCrAB Correct rejection (CR) for pairing targetA-attributeB across all responsetimeouts; test trials only
cr: not pressing spacebar for noise stims (NOT ME OR nice) in AB condition
zHitAB Z-score of hit rate for pairings targetA-attributeB (here: ME-nasty)
zFaAB Z-score of FA rate for pairings targetA-attributeB (here: ME-nasty)
dPrimeAB Computes d' (parametric measure of discriminability btw. signals and noise) for 'ME-nasty' Pairings
cAB C-criterion in AB condition
TARGET B Conditions
signals = NOT ME
BA Condition
signals = NOT ME OR nice
noise = anything else (ME OR nasty)
rHitBA Hit rate for pairing targetB-attributeA across all responsetimeouts; test trials only
hit: pressing spacebar for signals (NOT ME OR nice) in BA condition
rMissBA Miss rate for pairing targetB-attributeA across all responsetimeouts; test trials only
miss: not pressing spacebar for signals (NOT ME OR nice) in BA condition
rFaBA False alarm (FA) rate for pairing targetB-attributeA across all responsetimeouts; test trials only
false alarm: pressing spacebar for noise stims (ME OR nasty) in BA condition
rCrBA Correct rejection (CR) for pairing targetB-attributeA across all responsetimeouts; test trials only
cr: not pressing spacebar for noise stims (ME OR nasty) in BA condition
zHitBA Z-score of hit rate for pairings targetB-attributeA (here: NOT ME-nice)
zFaBA Z-score of FA rate for pairings targetB-attributeA (here: NOT ME-nice)
dPrimeBA Computes d' (parametric measure of discriminability btw. signals and noise) for 'NOT ME-nice' Pairings
cBA C-criterion in BA condition
AB Condition
signals = NOT ME OR nasty
noise = anything else (ME OR nice)
rHitBB Hit rate for pairing targetB-attributeB across all responsetimeouts; test trials only
hit: pressing spacebar for signals (NOT ME OR nasty) in BB condition
rMissBB Miss rate for pairing targetB-attributeB across all responsetimeouts; test trials only
miss: not pressing spacebar for signals (NOT ME OR nasty) in Bb condition
rFaBB False alarm (FA) rate for pairing targetB-attributeB across all responsetimeouts; test trials only
false alarm: pressing spacebar for noise stims (ME OR nice) in Bb condition
rCrBB Correct rejection (CR) for pairing targetB-attributeB across all responsetimeouts; test trials only
cr: not pressing spacebar for noise stims (ME OR nice) in Bb condition
zHitBB Z-score of hit rate for pairings targetB-attributeB (here: NOT ME-nasty)
zFaBB Z-score of FA rate for pairings targetB-attributeB (here: NOT ME-nasty)
dPrimeBB Computes d' (parametric measure of discriminability btw. signals and noise) for 'NOT ME-nasty' Pairings
cBB C-criterion in BB condition
gnatpart1 (a) subtracting d' for the Not-me & Nice (BA) block from d' for the me & Nice block (AA) => AA-BA
=> if positive: participant is better at discriminating btw. signal and noise
when both 'me' and 'nice' are signals than when 'not me' and 'nice' are signals
This supports closer association of 'me' and 'nice' than 'not me' and 'nice'
gnatpart2 (b) subtracting d' for the me & Nasty (AB) block from d' for the Not-me & Nasty block (BB)=> BB-AB
=> if positive: participant is better at discriminating btw. signal and noise
when both 'not me' and 'nasty' are signals than when 'me' and 'nasty' are signals
This supports closer association of 'not me' and 'bad' than 'me' and 'bad'
gnatall A composite index of implicit self-esteem (Gregg & Sedikides, 2010)
=> sum of GNATpart1 and GNATpart2
=> the higher the composite score, the closer a participant
associates 'me' with 'good' and 'not me' with 'bad' => measure of self-esteem
(3) Datafile "instructions_survey.iqdat" stores the name input raw data

Raw Data

File Name: selfesteemgnat_raw*.iqdat

Data Fields

NameDescription
build Inquisit version number
computer.platform Device platform: win | mac |ios | android
date Date the session was run
time Time the session was run
subject Participant ID
group Group number
session Session number
blockCode Name of the current block
blockNum Number of the current block
trialCode Name of the current trial
trialNum Number of the current trial
phase "training" (single category categorization) vs. "test" (2 categories categorization)
targetALabel The category used for target A
targetBLabel The category used for target B
attributeALabel The category used for attribute A
attributeBLabel The category used for attribute B
responseTimeoutTarget Time in ms that is allowed for response in a signal trial
responseTimeoutNoise Time in ms that is allowed for response in a noise trial
signal 1 = signal trial (spacebar response is correct)
0 = noisetrial (no response is correct)
targetType "A" vs. "B" (here: A-me; B-not me)
pairing "AA" -> targetA-attributeA (here: me and nice)
"AB" -> targetA-attributeB (here: me and nasty)
"BA" -> targetB-attributeA (here: not me-nice)
"BB" -> targetB-attributeB (here: not me-nasty)
trialType Training phase:"training"
Test phase: "practice" vs. "test"
stimulusItem The presented stimulusitems in order of presentation in stimulusframes (see trials)
response Response made (either 57 = Spacebar or 0 for no response)
correct The accuracy of response (1 = correct; 0 = error)
latency The latency of the response in ms (or if no response: response timeout duration)

Parameters

The procedure can be adjusted by setting the following parameters.

NameDescriptionDefault
responseTimeout1Signal Stores the longest response timeouts in ms used in this study for targets
by default, the longest response timeout in this script is used for blocks
that test attributes and targets separately (default: 1000ms)
(samefor noise trials: by default they are the same in this script)
isi Stores the interstimulus interval (time between offset of one stimulus and onset of next)