Loneliness and Social Engagement: The Unique Roles of State and Trait Loneliness for Daily Prosocial Behaviors
Bibliographic record
Abstract
Abstract Loneliness is a distressing yet adaptive emotional experience that alerts us to socially re-engage. However, loneliness can also lead to social withdrawal and isolation. To reconcile the seemingly contradictory consequences of loneliness, we unpack the timing of the underlying processes by distinguishing between the roles of state loneliness (i.e., daily variations in loneliness) and trait loneliness (i.e., person-average loneliness) in predicting social re-engagement. Using ten days of electronic daily assessments from 95 older adults (M age = 67.0 years; 64.2% women), initial findings indicate that trait loneliness moderates time-varying associations between state loneliness and prosocial behavior: On days of elevated state loneliness, older adults low in trait loneliness report increases in prosocial behavior, whereas older adults high in trait loneliness show decreases in prosocial behavior. Findings suggest that transient loneliness may motivate older adults to actively re-engage with others; chronic loneliness may undermine such adaptive responses.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| 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".