Procrastination and health: A longitudinal test of the roles of stress and health behaviours
Bibliographic record
Abstract
OBJECTIVES: Procrastination is a common form of self-regulation failure that a growing evidence base suggests can confer risk for poor health outcomes, especially when it becomes habitual. However, the proposed linkages of chronic procrastination to health outcomes have not been tested over time or accounted for the contributions of higher-order personality factors linked to both chronic procrastination and health-related outcomes. We addressed these issues by examining the role of chronic procrastination in health outcomes over time in which the hypothesized links of procrastination to health problems operate via stress and health behaviours. DESIGN: Three-wave longitudinal study with 1-month intervals. METHODS: Participants (N = 379) completed measures of trait procrastination at Time 1, and measures of health behaviours, stress and health problems at each time point, in a lab setting. RESULTS: Procrastination and the health variables were inter-related in the expected directions across the three assessments. Chronic procrastination was positively associated with stress and negatively with health behaviours at each time point. Path analysis testing a cross-lagged longitudinal mediation model found an indirect relationship operating between procrastination and health problems via stress, after accounting for the contributions of conscientiousness and neuroticism. CONCLUSIONS: This research extends previous work by demonstrating that the links between chronic procrastination and poor health are accounted for mainly by higher stress, after accounting for other key traits, and that these associations are robust over time. The findings are discussed in terms of the importance of addressing habitual self-regulation failure for improving health.
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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 | 0.006 | 0.012 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| 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".