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Record W4312103913 · doi:10.1093/geroni/igac059.502

DAILY ASSOCIATIONS BETWEEN STRESSOR CONTROL AND AFFECT VARY AS A FUNCTION OF STRESSOR TYPE

2022· article· en· W4312103913 on OpenAlexaff
Eric Cerino, Susan T. Charles, Jacqueline Mogle, Laura M Klepacz, Jennifer R. Piazza, Jonathan Rush, David M. Almeida

Bibliographic record

VenueInnovation in Aging · 2022
Typearticle
Languageen
FieldPsychology
TopicMental Health Research Topics
Canadian institutionsUniversity of Victoria
Fundersnot available
KeywordsStressorAffect (linguistics)PsychosocialPsychologyPerceived controlDevelopmental psychologyClinical psychologyMedicinePsychiatryCommunication

Abstract

fetched live from OpenAlex

Abstract Perceived control is an important psychosocial correlate of emotional well-being. Using data from the National Study of Daily Experiences (N=1,797, M=55.82 years, SD=10.35, 57.27% Female), we examined how self-reported control over different types of stressors (arguments, avoided arguments, work, home, network) was associated with negative affect (NA) and positive affect (PA). Over 8 consecutive days in waves conducted in ~2008 and ~2017, people reported their daily NA, PA, and control over stressors they had experienced. Within-person associations revealed lower NA on days when stressor control was higher than usual (p<.001), driven by control over arguments, avoided arguments, and work stressors specifically. PA was higher on days when individuals perceived greater control over avoided and actual arguments (ps<.001), but lower on days when individuals perceived greater control over network stressors (p<.01). Results suggest the facilitative role of control over daily stress for emotional well-being depends on the type of stressor experienced.

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 distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation 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 score0.067
Threshold uncertainty score0.640

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.078
GPT teacher head0.425
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 teacher head, 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

Citations1
Published2022
Admission routes1
Has abstractyes

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