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Record W3083149734 · doi:10.1093/geronb/gbaa154

Is Loneliness Adaptive? A Dynamic Panel Model Study of Older U.S. Adults

2020· article· en· W3083149734 on OpenAlexaff
Aniruddha Das

Bibliographic record

VenueThe Journals of Gerontology Series B · 2020
Typearticle
Languageen
FieldSocial Sciences
TopicHealth disparities and outcomes
Canadian institutionsMcGill University
FundersNational Institute on AgingNational Institutes of Health
KeywordsLonelinessPsychologyStructural equation modelingComputer scienceCognitive psychologyEconometricsMathematicsSocial psychologyMachine learning

Abstract

fetched live from OpenAlex

OBJECTIVES: Recent evolutionary psychological theory proposes that loneliness is an adaptive mechanism, designed to trigger maintenance and repair of social ties. No population representative analyses have probed loneliness effects on sociality. The present study addressed this gap. METHOD: Data were from the 2006, 2010, 2014, and 2018 waves of the Health and Retirement Study, nationally representative of U.S. adults over age 50. Recently developed cross-lagged models with fixed effects were used to test prospective within-person associations of loneliness with specific dimensions of sociality, taking into account reverse causality as well as all time-invariant confounders with stable effects. Both gender-combined and -specific analyses were conducted. RESULTS: Loneliness did not consistently predict overall sociality: sparse linkages were found only among women. The same null pattern held with family ties. Non-family ties, in contrast, were associated with prior loneliness, but in a gender-specific way. Loneliness positively predicted women's social interactions with friends, but seemed linked to withdrawal from these relationships among men. There were indications that lonely men instead used religious attendance as a social outlet. DISCUSSION: Loneliness seems to induce domain- and gender-specific sociality responses. Findings suggest implications for evolutionary models of sociality as well as for psychosocial and physical health. Pending replication in independent samples, inferences remain tentative.

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 imitation

Not 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.

metaresearch head score (Codex)0.003
metaresearch head score (Gemma)0.004
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.020
Threshold uncertainty score0.040

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0030.004
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.001
Science and technology studies0.0010.000
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0030.001

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.

Opus teacher head0.143
GPT teacher head0.388
Teacher spread0.244 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

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".

Quick stats

Citations10
Published2020
Admission routes1
Has abstractyes

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Same venueThe Journals of Gerontology Series BSame topicHealth disparities and outcomesFrench-language works237,207