Role Overload and Work Performance: The Role of Psychological Strain and Leader–Member Exchange
Bibliographic record
Abstract
The relation between role overload and work performance remains insufficiently understood. Drawing upon conservation of resources theory, we expected role overload to negatively relate to performance through psychological strain and this relation to be buffered by leader–member exchange (LMX). Study 1 (N = 212) examined depression as a severe type of strain that mediates between role overload and in-role performance, job dedication, and voice behavior. Study 2 (N = 191) used generic, perceived strain as a mediator between role overload and in-role performance and reward recommendations. Both studies tested LMX’s buffering effect, controlling for role ambiguity and conflict. A supplementary panel study (N = 99) assessed the temporal relationship between role overload and strain. Role overload triggered psychological strain, which undermined performance, and LMX acted as a buffer on role overload, but not on role ambiguity or role conflict. We discuss the implications of these findings for theory and practice.
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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 | 0.004 | 0.012 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".