A desire for distraction: uncovering the rates of media multitasking during online research studies
Bibliographic record
Abstract
Interpretations of task performance in many cognitive studies rest on the assumption that participants are fully attentive to the tasks they agree to complete. However, with research studies being increasingly conducted online where monitoring participant engagement is difficult, this assumption may be inaccurate. If participants were found to be engaging in off-task behaviours while participating in these studies, the interpretation of study results might be called into question. To investigate this issue, we conducted a secondary data analysis across nearly 3000 participants in various online studies to examine the prevalence of one form of off-task behaviour: media multitasking. Rates of media multitasking were found to be high, averaging 38% and ranging from 9 to 85% across studies. Our findings broadly raise questions about the interpretability of results from online studies and urge researchers to consider the likelihood that participants are simultaneously engaging in off-task behaviours while completing online research tasks.
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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 | 0.003 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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".