Does Mind-Wandering Relate to Mood and Stress in Young Adults? A Narrative Review
Bibliographic record
Abstract
Mind-wandering (MW) is ubiquitous and has been extensively studied in young adults. Studies have shown that MW, daydreaming, and sluggish cognitive tempo symptoms (SCT; e.g., staring, mental fogginess, confusion, hypoactivity, sluggishness, lethargy, and drowsiness) are interrelated constructs and all relate to mood and stress-related symptoms. The aims of the current review are to a) document the associations between MW (and related constructs: daydreaming, and SCT) and mood/stress-related symptoms (e.g., anxiety and depression symptoms) in young adults and b) identify potential mechanisms underlying these relationships. We conducted a narrative review of the literature on the subject. We searched MEDLINE (Ovid) and PsycINFO® (Ovid) databases and performed duplicate and independent screening. A total of 559 unique records were identified, and 22 records (published between 1978 and 2017) were included. We confirmed existing evidence of the associations between MW, daydreaming, SCT and mood/stress-related symptoms in young adults (aged 18 - 30 years). Although these associations are reported, our understanding of its directionality and underlying mechanisms remains incomplete. These findings highlight the need for further research combining experimental and correlational designs and including possible mechanisms of these associations in this population.
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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 | 0.005 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.004 | 0.005 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 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".