Conceptualizing Daily Dynamics of Social Connection in an Adult Lifespan Sample
Bibliographic record
Abstract
Abstract Social connection is central to many aspects of healthy aging, including increased emotional well-being and a reduced risk of mortality. Existing studies examining the link between social connection and health typically conceptualize social connection as a static, trait-like variable. Yet similar to other daily experiences, feeling socially connected fluctuates from day-to-day, and may provide additional insight into how social connection and health are linked. The present research examines three aspects of daily social connection: one structural (positive interactions) and two related to quality: feeling a sense of belonging; and responsivity (i.e., how sense of belonging varies in response to a positive interaction). Using eight days of daily diary data (N = 2,022), we examine the psychometric properties and utility of these three aspects of daily social connection. Each day, participants reported whether they had a positive interaction; their sense of belonging; and their closeness to others over the past 24 hours. Multilevel factor analyses revealed that daily feelings of belonging and closeness to others reflect a reliable unified social connection construct at both the within- and between-person levels (between-person factor loadings=.98, .87; within-person loadings=.67, .65, respectively; reliability=.92). Nearly 40% of the variability in daily social connection is within-person. Furthermore, these aspects of daily social connection demonstrated convergent validity to global indicators of social well-being. We discuss the value of utilizing daily social connection measures to effectively capture experiences of social connection within and between individuals, and how they can be used for future research examining the links between social connection and 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 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".