When daily planning improves employee performance: The importance of planning type, engagement, and interruptions.
Bibliographic record
Abstract
Does planning for a particular workday help employees perform better than on other days they fail to plan? We investigate this question by identifying 2 distinct types of daily work planning to explain why and when planning improves employees' daily performance. The first type is time management planning (TMP)-creating task lists, prioritizing tasks, and determining how and when to perform them. We propose that TMP enhances employees' performance by increasing their work engagement, but that these positive effects are weakened when employees face many interruptions in their day. The second type is contingent planning (CP) in which employees anticipate possible interruptions in their work and plan for them. We propose that CP helps employees stay engaged and perform well despite frequent interruptions. We investigate these hypotheses using a 2-week experience-sampling study. Our findings indicate that TMP's positive effects are conditioned upon the amount of interruptions, but CP has positive effects that are not influenced by the level of interruptions. Through this study, we help inform workers of the different planning methods they can use to increase their daily motivation and performance in dynamic work environments. (PsycINFO Database Record
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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 | 0.002 | 0.018 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".