Perceived distress and relational boredom during the COVID-19 pandemic: The role of shared leisure time
Bibliographic record
Abstract
The COVID-19 pandemic was a time of heightened distress that may have informed couples’ time engaging in shared leisure and, ultimately, negative relational outcomes. A growth-security framework was used to classify shared leisure time into security-restorative (i.e., familiar and comfortable) and growth-enhancing (i.e., novel and exciting). We followed a community sample (N = 257) of people in intimate relationships over six-weeks during the lockdown. Each week we measured perceived distress, subjective shared leisure time, and relational boredom. Multilevel modeling revealed a lack of evidence to support distress increasing shared security-restorative leisure time. However, perceived distress was positively related to relational boredom. Specifically, people who were more distressed than others reduced their time spent engaging in growth-enhancing activities with their partner which, in turn, was associated with relational boredom. Therefore, in the long-term, high environmental distress resulted in less time spent on growth-enhancing shared leisure, likely resulting in more relational boredom.
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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 | 0.009 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.002 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".