On the relationship between unprompted thought and affective well-being: A systematic review and meta-analysis.
Bibliographic record
Abstract
There is a growing recognition that thoughts often arise independently of external demands. These thoughts can span from reminiscing your last vacation to contemplating career goals to fantasizing about meeting your favorite musician. Often referred to as mind wandering, such frequently occurring unprompted thoughts have widespread impact on our daily functions, with the dominant narrative converging on a negative relationship between unprompted thought and affective well-being. In this systematic review of 76 studies, we implemented a meta-analysis and qualitative review to elucidate if and when unprompted thought is indeed negatively associated with affective well-being in adults. Using a multilevel mixed-model approach on 386 effect sizes from 23,168 participants across 64 studies, our meta-analyses indicated an overall relationship between unprompted thought and worse affective well-being (r¯ = -.18, 95% CI [-.23, -.14]); however, the magnitude and direction of this relationship changed when considering specific aspects of the phenomenon (including thought content and intentionality) and methodological approaches (including questionnaires vs. experience sampling). The qualitative review further contextualizes this relationship by revealing the nuances of how and when unprompted thought is associated with affective well-being. Taken together, our meta-analysis and qualitative review indicate that the commonly reported relationship between unprompted thought and affective well-being is contingent upon the content and conceptualization of unprompted thought, as well as the methodological and analytic approaches implemented. Based on these findings, we propose emerging directions for future empirical and theoretical work that highlight the importance of accounting for when, how, and for whom unprompted thought is associated with affective well-being. (PsycInfo Database Record (c) 2024 APA, all rights reserved).
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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 | 0.026 | 0.078 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.012 | 0.023 |
| Bibliometrics | 0.010 | 0.009 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.005 | 0.003 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.004 | 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".