Online Cognitive Vigilance Task
Creators: name: Gyles, Shannon
Publisher: name: Open Science Framework
Year: 2022
Subjects: subject: Social and Behavioral Sciences

description: This project will use generative modeling to examine the extent to which losses of operator sensitivity, conservative shifts in response bias, and attentional lapses contribute to the vigilance decrement in an online vigilance task. Unlike previous research examining these three mechanisms of decline, the present study will employ a cognitive vigilance task. Cognitive tasks require observers to judge the value of alphanumeric stimuli, whereas sensory tasks require observers to judge physical features of sensory stimuli. Participants will perform a visual signal detection task, judging whether the average value of a set of four three-digit numbers exceeds a criterion value. Participants will be asked to provide a keypress response if the average on a given trial exceeds the criterion value, and to withhold response otherwise. Signal and non-signal values will be drawn from normal distributions with different means (M noise = 490, M signal = 510) but the same standard deviation (SD = 20). The task will be designed according to conditions that elicit sensitivity decrements in sensory vigilance tasks (Parasuraman, 1979). Participants’ yes-no responses will be fit with a generative cognitive model (see attached model script). with parameters representing sensitivity, response bias, and attentional lapse rate (Lee, 2018; Lee &amp; Wagenmakers, 2013). Statistical analysis will employ hierarchical Bayesian parameter estimation using a Markov chain Monte Carlo (MCMC) sampling procedure. To examine the nature of vigilance losses, we will compare parameters for the first four minutes and the last four minutes of a 12-minute vigil. Additionally, we will collect subjective mental workload ratings using the A-SWAT (Luximon &amp; Goonetilleke, 2001) scale. Mental workload ratings will be collected only once, at the end of the 12-minute vigil. Mean values will be estimated in a one-sample design to characterize the cognitive demands of our task; past work has suggested that vigilance tasks are mentally taxing (Warm, Parasuraman, &amp; Matthews, 2008). Method Participants will be recruited from the Prolific online recruitment system and screened for self-reported normal or corrected-to-normal visual acuity. The minimum sample size will be N = 125 participants. After the initial round of data collection, we will check the Bayes factors for effects of block on shift, scale, and lapse rate. If the strength of evidence is &lt; 10:1 for or against the null hypothesis, we will continue running participants in increments of 25 until the Bayes factors reach the criterion value of 10:1 in either direction, up to a maximum of N = 200. Experimental software for generating stimuli and controlling the experiment will be written in PsychoPy 3 (Peirce et al., 2019) and hosted online on PsychoPy’s Pavlovia. The stimulus each trial will comprise a column of four three-digit numbers. Stimuli will be presented in black text on a white background. Stimuli values will be assigned probabilistically, with a signal rate of 0.5 for practice trials, and 0.2 for experimental trials. Signal values will be drawn from a normal distribution with a mean of 510 and noise values will be drawn from a normal distribution with a mean of 490. Both distributions will have a standard deviation of 20. Procedure: Participants will be asked to perform a yes-no signal detection task, judging whether the average value of the numbers each trial exceeds 500. They will be asked to press the space bar if the gap between probe circles exceeded the criterion value on a given trial, and to withhold response otherwise. Each experimental trial will comprise a 1500 ms stimulus display during which time stimulus remains visible until a response is made. Participants will receive no post-trial feedback to indicate whether their judgments are correct or incorrect. Each participant will complete a practice vigil of 90 trials, followed by an experimental vigil of 12 minutes. The practice vigil will be identical to the experimental vigil except that 1) signal and noise events will be equally probable, creating a signal rate of 0.50, and 2) for the first 25 trials of the vigil, the stimulus display will remain visible for the full trial duration of 1500 ms, 3) response errors will be followed by a 1-second feedback message reading either, “Oops! It was not a target.”, or “Oops! You missed a target.”, as appropriate. As only incorrect answers will be followed by feedback, the exact length of the practice vigil will depend on each participant’s performance. Error-free performance would result in a practice vigil of 2 minutes 15 seconds. Each error would add an additional 1-second. At the end of the experimental block, the participant will be asked to complete a computerized A-SWAT mental workload scale (Luximon &amp; Goonetilleke, 2001). The A-SWAT consists of three subscales: time load, mental effort, and stressfulness. After the participant has read the rating scale instructions and pressed a key to indicate they are ready to proceed, the three subscales will be presented in order, one at a time. Participants will make their rating of each subscale by clicking a horizontal line, anchored with the text descriptions of subscale endpoints, with a range of 1-100.