MétaCan
Menu
Back to cohort
Record W2789691153 · doi:10.1177/0091415018763402

Loneliness as a Mediator of Perceived Discrimination and Depression: Examining Education Contingencies

2018· article· en· W2789691153 on OpenAlexaff
Yeonjung Lee, Alex Bierman

Bibliographic record

VenueThe International Journal of Aging and Human Development · 2018
Typearticle
Languageen
FieldSocial Sciences
TopicHealth disparities and outcomes
Canadian institutionsUniversity of Calgary
Fundersnot available
KeywordsLonelinessPsychologyHealth and Retirement StudyAssociation (psychology)Everyday lifeEducational attainmentDepression (economics)Depressive symptomsClinical psychologyDevelopmental psychologyCognitionGerontologyMedicinePsychiatryPsychotherapist

Abstract

fetched live from OpenAlex

This study examines whether loneliness explains the association between perceived everyday discrimination and depressive symptoms among older adults as well as whether this indirect pathway differs by education. Three waves (2006, 2010, and 2014) of the Health and Retirement Study ( N = 7,130) are analyzed with random-effects models that adjust for repeated observations and fixed-effects models that control for all time-stable influences. Everyday discrimination is associated with loneliness and depressive symptoms but more weakly in fixed-effects models. The association between discrimination and loneliness is stronger at low educational attainment, leading discrimination to be indirectly associated with depressive symptoms through loneliness only at low education. The consequences of everyday discrimination for depression in late life are limited to older adults with low education due to education-contingent associations with loneliness. Perceived discrimination may have broad health consequences through loneliness, especially for older adults at low education.

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)0.001
metaresearch head score (Gemma)0.008
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 score0.003
Threshold uncertainty score0.010

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.008
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.000
Science and technology studies0.0010.001
Scholarly communication0.0010.001
Open science0.0000.001
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0030.000

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.

Opus teacher head0.048
GPT teacher head0.374
Teacher spread0.325 · 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

Citations48
Published2018
Admission routes1
Has abstractyes

Explore more

Same venueThe International Journal of Aging and Human DevelopmentSame topicHealth disparities and outcomesFrench-language works237,207