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Record W4224242236 · doi:10.1037/pag0000681

The differential roles of chronic and transient loneliness in daily prosocial behavior.

2022· article· en· W4224242236 on OpenAlexfundno aff
Yeeun Lee, Jennifer C. Lay, Theresa Pauly, Peter Graf, Christiane A. Hoppmann

Bibliographic record

VenuePsychology and Aging · 2022
Typearticle
Languageen
FieldSocial Sciences
TopicHealth disparities and outcomes
Canadian institutionsnot available
FundersUniversity of British ColumbiaCanada Research ChairsVancouver Foundation
KeywordsLonelinessProsocial behaviorPsychologyDevelopmental psychologySocial isolationPsycINFODifferential effectsClinical psychologySocial psychologyMedicinePsychiatryMEDLINE

Abstract

fetched live from OpenAlex

= 67.0 years; 64.0% women), findings indicate that chronic loneliness moderates time-varying associations between transient loneliness and prosocial behavior. Simple slope results point to individual differences in daily loneliness-prosocial action associations. Specifically, adults high in chronic loneliness, but not those low in chronic loneliness, showed decreased prosocial behaviors on days with elevated transient loneliness. Findings suggest that chronic loneliness may elicit maladaptive responses to transient loneliness by hampering the use of opportunities to engage in prosocial behavior. Exploratory analyses point to fear of evaluation as a potential mechanism that is associated with increased loneliness and reduced prosocial behavior. Findings highlight the differential roles of transient and chronic loneliness in shaping prosocial activities in midlife and older adulthood, thereby providing a more nuanced picture as well as potential avenues for intervention. (PsycInfo Database Record (c) 2022 APA, all rights reserved).

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)0.002
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 score0.006
Threshold uncertainty score0.018

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0010.000
Scholarly communication0.0010.001
Open science0.0000.001
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0050.000

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 head0.024
GPT teacher head0.372
Teacher spread0.347 · 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

Citations33
Published2022
Admission routes1
Has abstractyes

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