Tracking the Temporal Dynamics of Distraction in a Continuous Performance Task
Bibliographic record
Abstract
Many daily life tasks require sustained attention (e.g., studying) and are impacted by distractions that are irrelevant to the current task (e.g., friends talking). However, distraction paradigms typically fail to capture the continuous aspect of tasks, and commonly use distractors that are not actually irrelevant to current task goals. Hence, the aim of the present thesis was to provide a measure of distraction that better reflects daily life inattention. In Experiment 1, I tested my novel distraction task, referred to as the Continuous Classification Task, to determine whether previous findings of distraction replicate. Participants proceeded clockwise through a 12-item circular array making forced-choice responses as to whether the identity of each item was a letter or a digit. On thirty percent of the trials, a colorful cartoon character was presented in the center of the display. As predicted, there was significant distractor interference for the first response following distractor presentation. In Experiment 2, using an online version of the Continuous Classification Task, I tested its validity by correlating performance with scores on the Childhood and Current ADHD symptoms scales and the Cognitive Failures Questionnaire. As with Experiment 1, I found significant interference, however, here the interference was present for multiple items following distractor presentation. Furthermore, individuals who scored higher on measures of inattention also experienced greater distraction in my task supporting the external validity of the Continuous Classification Task. Finally, with Experiment 3, I examined the impact of perceptual load on distraction within my task. In a low-load condition, participants discriminated between visibly distinct items (i.e., c and o vs. i and l), whereas in a high-load condition, participants discriminated between visibly similar items (i.e., d and b vs. q and p). As with Experiment 2, I found distraction for multiple items following distractor presentation. However, inconsistent with Load Theory (Lavie & Tsal, 1994), increasing perceptual load increased distraction, suggesting that perceptual load may impact distraction differently in the continuous tasks that are typical of daily life. Together, these findings support the use of my Continuous Classification Task for investigating inattention in daily life.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".