Understanding the dark and bright sides of anxiety: A theory of workplace anxiety.
Bibliographic record
Abstract
Researchers have uncovered inconsistent relations between anxiety and performance. Although the prominent view is a "dark side," where anxiety has a negative relation with performance, a "bright side" of anxiety has also been suggested. We reconcile past findings by presenting a comprehensive multilevel, multiprocess model of workplace anxiety called the theory of workplace anxiety (TWA). This model highlights the processes and conditions through which workplace anxiety may lead to debilitative and facilitative job performance and includes 19 theoretical propositions. Drawing on past theories of anxiety, resource depletion, cognitive-motivational processing, and performance, we uncover the debilitative and facilitative nature of dispositional and situational workplace anxiety by positioning emotional exhaustion, self-regulatory processing, and cognitive interference as distinct contrasting processes underlying the relationship between workplace anxiety and job performance. Extending our theoretical model, we pinpoint motivation, ability, and emotional intelligence as critical conditions that shape when workplace anxiety will debilitate and facilitate job performance. We also identify the unique employee, job, and situational characteristics that serve as antecedents of dispositional and situational workplace anxiety. The TWA offers a nuanced perspective on workplace anxiety and serves as a foundation for future work. (PsycINFO Database Record
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.001 | 0.008 |
| Scholarly communication | 0.005 | 0.007 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.003 | 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 source (direct Gemma or distilled Codex), 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".