By myself and liking it? Predictors of distinct types of solitude experiences in daily life
Bibliographic record
Abstract
OBJECTIVE: Solitude is a ubiquitous experience, often confused with loneliness, yet sometimes sought out in daily life. This study aimed to identify distinct types of solitude experiences from everyday affect/thought patterns and to examine how and for whom solitude is experienced positively versus negatively. METHOD: One hundred community-dwelling adults aged 50-85 years (64% female; 56% East Asian, 36% European, 8% other/mixed heritage) and 50 students aged 18-28 years (92% female; 42% East Asian, 22% European, 36% other/mixed) each completed approximately 30 daily life assessments over 10 days on their current and desired social situation, thoughts, and affect. RESULTS: Multilevel latent profile analysis identified two types of everyday solitude: one characterized by negative affect and effortful thought (negative solitude experiences) and one characterized by calm and the near absence of negative affect/effortful thought (positive solitude experiences). Individual differences in social self-efficacy and desire for solitude were associated with everyday positive solitude propensity; trait self-rumination and self-reflection were associated with everyday negative solitude propensity. CONCLUSIONS: This study provides a new framework for conceptualizing everyday solitude. It identifies specific affect/thought patterns that characterize distinct solitude experience clusters, and it links these clusters with well-established individual differences. We discuss key traits associated with thriving in solitude.
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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 | 0.000 | 0.004 |
| 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 | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".