Morningness-eveningness and mental health: Initial evidence of the moderating roles of mattering and anti-mattering
Bibliographic record
Abstract
Mental health problems are more prevalent in evening-oriented individuals than in their morning-oriented counterparts. Recently, research has offered first insights into how the negative effects of eveningness on mental health and well-being can be magnified or alleviated depending on accompanying psychological characteristics. In the current study, we evaluated how eveningness relates to mattering and anti-mattering and whether mattering and anti-mattering can moderate the association between eveningness and mental health. The participants were 692 Polish adults (337 women, 355 men) aged between 21 and 57 years (M ± SD: 39.76 ± 9.63). All participants completed measures of morningness-eveningness and depressive and anxiety symptoms, the General Mattering Scale (GMS) and the Anti-Mattering Scale (AMS). Conducted analyses showed that 1) the Polish versions of GMS and AMS have appropriate reliability and validity, 2) eveningness is negatively associated with mattering and positively associated with anti-mattering, depressive, and anxiety symptoms, and 3) the magnitude of the association between eveningness and mental health symptoms increased with higher anti-mattering and lower mattering. Overall, this study presents the first evidence of how feelings of being important and being valued may buffer against the negative effects of eveningness on mental 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 | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| 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".