Do Rising Opportunity Costs Lead to Increases in Media Multitasking Over Time?
Bibliographic record
Abstract
Evidence suggests that one’s likelihood of media multitasking increases with time-on-task, which can negatively impact performance. The opportunity costs account of sustained attention might explain this finding. This account states that rising feelings of boredom and effort signal increasing opportunity costs, motivating us to direct our attention elsewhere and causing progressive decreases in performance. We examined whether patterns of media multitasking, boredom, effort and performance during a sustained attention task supported the notion that rising opportunity costs drive temporal increases in media multitasking. We further tested this account by affording one group of participants the option to respond to increasing opportunity costs by watching a video (media multitasking) while completing the task. Another group received no such option. Temporal patterns of media multitasking, boredom, effort and performance partially supported the opportunity costs view. Surprisingly, many also multitasked with activities outside the experimental context. Exploratory analyses revealed that patterns of boredom, effort and performance among these individuals and those who did not multitask supported the opportunity costs view. Our findings suggest that many media multitask in response to rising opportunity costs signaled by changes in feelings of boredom and effort – a relation that may be particularly problematic for online studies.
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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 | 0.001 | 0.004 |
| 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 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.002 |
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".