original Script Author: Brian Nosek (nosek@virginia.edu)
Created: October 29, 2000
Last Modified: January 07, 2024 by K. Borchert (katjab@millisecond.com), Millisecond
Script Copyright © Millisecond Software, LLC
This script implements a demo for the Go-Nogo Association Task (GNAT) using categories 'fruit' and 'insects' as two target categories.
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 'fruit' (the target signal) is suggested if the dprime measure in the condition 'Fruit-Good' (aka both Fruit and good attributes are signals) is greater than the dprime measure in the condition 'Fruit-Bad' (aka both fruit and bad attributes are signals).
Literature Reference: Nosek, B. A., & Banaji, M. R. (2001). The go/no-go association task. Social Cognition, 19(6), 625-666.
Adjustments to z-scores as described 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)
•Note (by B. Nosek - original script author): This task is for demonstration purposes only. Using the GNAT for research requires intentional decisions about numerous design parameters. Discussion of some of those parameters can be found in Nosek and Banaji (2001; Social Cognition). This example is a minimalist example and is not designed to maximize reliability, it only demonstrates the core properties of the task.
Additional Notes (K. Borchert, Millisecond Software): GNATdemo.iqjs was edited to allow for: - easy changes in GNAT target categories (under Editable Stimuli) - easy changes in response timeouts (under Editable Parameters) -> by default the task is set up to run 2 different response timeouts (750ms vs. 600ms) for critical testblocks - easy setting of target vs. noise response timeouts (see Experiment 5 in Nosek & Banaji, 2001) -> by default, response timeouts for target and noise trials are the same - easy changes in interstimulus intervals (time btw. offset of one stimulus and onset of the next) (under Editable Parameters) - recorded correct responses reflect the actual accuracy of the participant's response while keeping feedback accurate - includes summary variables (hits and false alarm counts/rates)
Furthermore script gnat_pictures.iqjs is provided by Millisecond to run a GNAT with picture target/noise items and word attributes.
20 minutes
Participants are asked to categorize attributes (e.g. "happy"; "unhappy") and target items (e.g fruits "apple"; insects "bug") into predetermined categories via keystroke presses. The basic task is to press the Spacebar if an item (e.g. "happy") belongs to the category currently being tested (e.g. "Good") and to do nothing if it doesn't. For practice, participants sort items into categories "Good", "Bad", "Fruit", and "Insect". For the test, participants are asked to sort categories into the paired/combined categories (e.g. "Fruit OR Good"). When an item belongs to either one of these two categories, participants should press the Spacebar.
Default GNAT Set-Up in this script:
(1) 4 training blocks: one training block each for targetA (here: insects), targetB (here: fruits), attributeA (here: good), attributeB (here: bad)
with response timeout of 1000ms (editable under section Editable Values)
-> block order is determined randomly
-> run 20 trials each (10 target:10 noise)
(2) 4 test blocks that combine targets and attributes with a faster response timeout (default: 750ms)
-> block order is determined randomly
-> each block runs 16 'practice trials' followed by 60 test trials (summary variables based on test trial performance only)
-> signal : noise = 1 : 1
(3) 4 test blocks that combine targets and attributes with an even faster response timeout (default: 600ms)
-> block order is determined randomly
-> each block runs 16 'practice trials' followed by 60 test trials (summary variables based on test trial performance only)
-> signal : noise = 1 : 1
• Number of trials run as well as 'signal : noise' ratios can only be edited on block level (see section BLOCKS)
see section Editable Stimuli
Each of the categories runs 15 stims by default. You add further stims to the item elements.
The target/noise pictures were downloaded from https://pixabay.com
see section Editable Instructions
File Name: gnatdemo_summary*.iqdat
| Name | Description |
|---|---|
| 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 |
|
| responseTimeout2Signal | Stores the response timeouts in ms used for signals in the first gnat round (2 blocks) in this script (default: 700ms) |
| responseTimeout2Noise | Stores the response timeouts in ms used for noise in the first gnat round (2 blocks) in this script (default: 700ms) |
| responseTimeout3Signal | Stores the response timeouts in ms used in this study for signals in the second gnat round (2 blocks) in this script (default: 550ms) |
| responseTimeout3Noise | Stores the response timeouts in ms used for noise in the second gnat round (2 blocks) in this script (default: 550ms) responsetimeouts1 (1000ms) are used for practice only and responsetimeouts4 are not run |
Performance Metrics |
|
| propCorrectAA | Overall proportion correct for pairing targetA-attributeA (here: insects-good); test trials only |
| propCorrectAB | Overall proportion correct for pairing targetA-attributeB (here: insects-bad); test trials only |
| propCorrectBA | Overall proportion correct for pairing targetB-attributeA (here: fruit-good); test trials only |
| propCorrectBB | Overall proportion correct for pairing targetB-attributeB (here: fruit-bad); test trials only TARGET A Conditions signals = insects AA Condition signals = insects OR good stims noise = anything else (fruit OR bad stims) |
| rHitAA | Hit rate for pairing targetA-attributeA across all responsetimeouts; test trials only hit: pressing spacebar for signals (insects OR good stims) in AA condition |
| rMissAA | Miss rate for pairing targetA-attributeA across all responsetimeouts; test trials only miss: not pressing spacebar for signals (insects OR good stims) 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 (fruit OR bad stims) in AA condition |
| rCrAA | Correct rejection (CR) for pairing targetA-attributeA across all responsetimeouts; test trials only cr: not pressing spacebar for noise stims (fruit OR bad stims) in AA condition |
| zHitAA | Z-score of hit rate for pairings targetA-attributeA (here: insects-good) |
| zFaAA | Z-score of FA rate for pairings targetA-attributeA (here: insects-good) *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 'insects-good' 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 = insects OR bad noise = anything else (fruit OR good) |
| rHitAB | Hit rate for pairing targetA-attributeB across all responsetimeouts; test trials only hit: pressing spacebar for signals (insects OR bad) in AB condition |
| rMissAB | Miss rate for pairing targetA-attributeB across all responsetimeouts; test trials only miss: not pressing spacebar for signals (insects OR bad) 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 (fruit OR good) in AB condition |
| rCrAB | Correct rejection (CR) for pairing targetA-attributeB across all responsetimeouts; test trials only cr: not pressing spacebar for noise stims (fruit OR good) in AB condition |
| zHitAB | Z-score of hit rate for pairings targetA-attributeB (here: insects-bad) |
| zFaAB | Z-score of FA rate for pairings targetA-attributeB (here: insects-bad) |
| dPrimeAB | Computes d' (parametric measure of discriminability btw. signals and noise) for 'insects-bad' Pairings |
| cAB | C-criterion in AB condition |
| dPrimeDiffTargetA | The difference in dprime btw. AA (insects-good) and AB (insects-bad) => if d prime for insects-good is larger than for insects-bad (positive difference) participant more closely associated insects with good than with bad attributes => if d prime for insects-good is smaller than for insects-bad (negative difference) participant more closely associated insects with bad than with good attributes TARGET B Conditions signals = fruit BA Condition signals = fruit OR good stims noise = anything else (insects OR bad stims) |
| rHitBA | Hit rate for pairing targetB-attributeA across all responsetimeouts; test trials only hit: pressing spacebar for signals (fruit OR good stims) in BA condition |
| rMissBA | Miss rate for pairing targetB-attributeA across all responsetimeouts; test trials only miss: not pressing spacebar for signals (fruit OR good stims) 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 (insects OR bad stims) in BA condition |
| rCrBA | Correct rejection (CR) for pairing targetB-attributeA across all responsetimeouts; test trials only cr: not pressing spacebar for noise stims (insects OR bad stims) in BA condition |
| zHitBA | Z-score of hit rate for pairings targetB-attributeA (here: fruit-good) |
| zFaBA | Z-score of FA rate for pairings targetB-attributeA (here: fruit-good) |
| dPrimeBA | Computes d' (parametric measure of discriminability btw. signals and noise) for 'fruit-good' Pairings |
| cBA | C-criterion in BA condition AB Condition signals = fruit OR bad noise = anything else (insects OR good) |
| rHitBB | Hit rate for pairing targetB-attributeB across all responsetimeouts; test trials only hit: pressing spacebar for signals (fruit OR bad) in BB condition |
| rMissBB | Miss rate for pairing targetB-attributeB across all responsetimeouts; test trials only miss: not pressing spacebar for signals (fruit OR bad) 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 (insects OR good) in BB condition |
| rCrBB | Correct rejection (CR) for pairing targetB-attributeB across all responsetimeouts; test trials only cr: not pressing spacebar for noise stims (insects OR good) in BB condition |
| zHitBB | Z-score of hit rate for pairings targetB-attributeB (here: fruit-bad) |
| zFaBB | Z-score of FA rate for pairings targetB-attributeB (here: fruit-bad) |
| dPrimeBB | Computes d' (parametric measure of discriminability btw. signals and noise) for 'fruit-bad' Pairings |
| cBB | C-criterion in BB condition |
| dPrimeDiffTargetB | The difference in dprime btw. BA (fruit-good) and BB (fruit-bad) => if d prime for fruit-good is larger than for fruit-bad (positive difference) participant more closely associated fruit with good than with bad attributes => if d prime for fruit-good is smaller than for fruit-bad (negative difference) participant more closely associated fruit with bad than with good attributes by default, this script runs testblocks for responsetimeouts2 and responsetimeouts3 |
File Name: gnatdemo_raw*.iqdat
| Name | Description |
|---|---|
| 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" (one category) vs. "test" (two categories) |
| responseTimeoutTarget | Time in ms that is allowed for response in a given target trial |
| responseTimeoutNoise | Time in ms that is allowed for response in a given noise trial |
| signal | 1 = signal trial (spacebar response is correct) 0 = noise trial (no response is correct) |
| targetType | "A" vs. "B" (here: A-insects; B-fruit) |
| pairing | "AA" -> targetA-attributeA (here: insects and good) "AB" -> targetA-attributeB (here: insects and bad) "BA" -> targetB-attributeA (here: fruit-good) "BB" -> targetB-attributeB (here: fruit-bad) |
| 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) |
The procedure can be adjusted by setting the following parameters.
| Name | Description | Default |
|---|---|---|
| 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) | |
| responseTimeout2Signal | Stores the next response timeouts in ms used in this study for targets by default, in this script this is the first response time used for blocks that test attributes and targets simultaneously (default 750ms) | |
| responseTimeout3Signal | Stores the next response timeouts in ms used in this study for targets by default, this is the second response time used for blocks that test attributes and targets simultaneously (default 600ms) | |
| responseTimeout4Signal | Stores a potential next response timeouts in ms that could be used for targets -> code provided under section BLOCKS by default, this responsetimeout4_signal is not used in this script (same for 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) | |
| picHeightPct | The percentage height of the pictures |