The dynamics of stability and flexibility: How attentional and cognitive control support multitasking under time pressure.
DOI: 10.1037/xge0001749
archive: archived pipeline: cataloged verified
Get this paper ↗ (DOI — opens at the source; we link to it, we don't host it)
Summary
This study investigates the cognitive mechanisms underlying the stability–flexibility dilemma in multitasking, specifically examining how attentional and cognitive control processes adapt under varying levels of time pressure. The stability–flexibility dilemma refers to the trade-off between maintaining robust focus on a primary goal (stability) and remaining ready to switch tasks or detect critical events (flexibility). The authors address a gap in understanding how individuals manage this trade-off when task demands exceed capacity, a state referred to as the performance “red zone.” The research is motivated by the need to understand cognitive adaptation in complex work settings, such as aviation or healthcare, where operators must balance routine ongoing tasks with infrequent but critical prospective memory (PM) tasks. To address this, the authors developed and applied a computational model based on an evidence accumulation framework. The model quantifies the quality and quantity of attentional capacity directed to competing tasks and distinguishes between proactive (sustained, anticipatory) and reactive (transient, event-triggered) cognitive control. The model was tested against data from a large-scale experiment involving 48 participants who completed 3,200 trials in a PM paradigm. The experimental design systematically manipulated two key variables: time pressure (high vs. low, creating “red zone” conditions) and the relative prevalence of PM trials versus ongoing task trials (favoring stability vs. flexibility). This design allowed for the reliable measurement of how cognitive mechanisms shift in response to context-sensitive demands. The results demonstrated that the computational model provided close fits to both ongoing and PM task performance. The findings indicate that stability and flexibility operate as somewhat independent dimensions of control, constrained by limited human processing capacity. Specifically, requiring behavioral flexibility incurred unintended negative consequences for ongoing task performance, characterized by reduced attentional focus and a greater reliance on effortful proactive control strategies. Furthermore, heightened time pressure compromised the ability to maintain the behavioral flexibility necessary to detect and respond to infrequent critical events. The model explained these behaviors through context-sensitive adjustments in how proactive and reactive control were applied to each task, depending on the expected frequency of interference and the urgency of the context. The significance of this work lies in its provision of a quantitative theory for stability–flexibility adaptation. By demonstrating that flexibility demands can degrade ongoing performance and that time pressure can hinder critical event detection, the study highlights the costs of cognitive control in dynamic environments. These findings have practical implications for work design and training in information-rich settings, suggesting that optimizing performance requires balancing the metabolic and cognitive costs of proactive control against the need for behavioral adaptability. The study advances the understanding of meta-control processes, showing that individuals adapt their control modes based on cost–benefit computations related to task prevalence and time constraints.
Key finding
Requiring behavioral flexibility negatively impacts ongoing task performance by reducing attentional focus and increasing reliance on effortful proactive control, while high time pressure further compromises the ability to detect infrequent critical events.
Methodology
modeling
Sample size: 48
Provenance
The full processing record for this entry. Every stage of this paper's journey through the pipeline is logged — what ran, with which tool and model, how many attempts it took, and when it last completed. Discovered via author_sweep_intake on 2026-05-28.
| Stage | Outcome | Tool | Model | Prompt | Attempts | Completed |
|---|---|---|---|---|---|---|
| discover | success | author_sweep | — | — | 2 | 2026-05-28 |
| archive | success | unpaywall | — | — | 2 | 2026-06-04 |
| extract | success | cached | — | — | 3 | 2026-06-10 |
| clean | success | clean | — | — | 1 | 2026-06-04 |
| chunk | success | chunk | — | — | 1 | 2026-06-04 |
| embed | success | embed | Qwen/Qwen3-Embedding-8B | — | 1 | 2026-06-04 |
| enrich | success | — | — | — | 1 | 2026-05-28 |
| promote | success | — | — | — | 1 | 2026-06-04 |
| summarize | success | llm | qwen3.6-27b-prismaquant | summ-v5 | 2 | 2026-06-10 |
| tag | success | vector_similarity | — | — | 15 | 2026-06-11 |
| verify | success | — | — | — | 2 | 2026-06-10 |
Summary generated by qwen3.6-27b-prismaquant on 2026-06-10; verification: verified.
Topics
Ranked by relevance to this paper. Hover a topic for its definition.
Information type
What kind of knowledge this paper contributes, grouped by family — independent of topic (what it is about) and method (how it was studied).
- Empirical Findings: behavioral performance data
- Theoretical Contribution: theory or model