Psychological Well-Being and Its Relationships with Active and Passive Procrastination
Bibliographic record
Abstract
Procrastination affects many people and impacts overall effectiveness of individuals and organisations. While some studies have examined the correlates of procrastination in terms of impacts on well-being (including depression and anxiety) and on performance, few studies have examined procrastination as a dichotomous construct, with most seeing procrastination as unifactorial. One such study defining procrastination as dichotomous was that of Chu and Choi (2005). The current study examines how psychological well-being is related to the concepts of active procrastination and passive (traditional) procrastination. Active and passive procrastination are related insignificantly to each other (we are not dealing with one dimension); but what would be the relationships among psychological well-being, active procrastination and passive procrastination? The different forms of procrastination may have different relationships to well-being and research is scarce; and further, treatment processes for avoiding the negative effects of procrastination should be tailored to the different forms of procrastination. It was hypothesised that psychological well-being would be related positively to active procrastination and negatively to passive procrastination. To answer this question, 152 university students aged between 18 and 54, mean age of 23.3 (SD = 18) completed the Active Procrastination Scale, the Passive Procrastination Scale, and Ryff’s Scales of Psychological Well-Being. Standard multiple regression was used, linking psychological well-being, age, gender, active and passive procrastination. The findings show active and passive procrastination are in fact separate constructs and need to be treated differently. Being an active procrastinator can be a sign of healthy well-being.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.002 |
| 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 | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".