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Record W2274096397 · doi:10.1111/jopy.12247

Do the Emotional Benefits of Optimism Vary Across Older Adulthood? A Life Span Perspective

2016· article· en· W2274096397 on OpenAlexafffund
Carsten Wrosch, Joelle Jobin, Michael F. Scheier

Bibliographic record

VenueJournal of Personality · 2016
Typearticle
Languageen
FieldPsychology
TopicOptimism, Hope, and Well-being
Canadian institutionsConcordia University
FundersNational Center for Complementary and Alternative MedicineSocial Sciences and Humanities Research Council of CanadaCanadian Institutes of Health Research
KeywordsOptimismPsychologyStressorYoung adultLife spanPerspective (graphical)Multilevel modelAssociation (psychology)Depressive symptomsDevelopmental psychologySuccessful agingClinical psychologyLongitudinal studyGerontologyCognitionMedicinePsychiatrySocial psychology

Abstract

fetched live from OpenAlex

This study examined whether the emotional benefits of dispositional optimism for managing stressful encounters decrease across older adulthood. Such an effect might emerge because age-related declines in opportunities for overcoming stressors could reduce the effectiveness of optimism. This hypothesis was tested in a 6-year longitudinal study of 171 community-dwelling older adults (age range = 64-90 years). Hierarchical linear models showed that dispositional optimism protected relatively young participants from exhibiting elevations in depressive symptoms over time, but that these benefits became increasingly reduced among their older counterparts. Moreover, the findings showed that an age-related association between optimism and depressive symptoms was observed particularly during periods of enhanced, as compared to reduced, stress. These results suggest that dispositional optimism protects emotional well-being during the early phases of older adulthood, but that its effects are reduced in advanced old age.

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 score0.001
Threshold uncertainty score0.004

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0000.000
Scholarly communication0.0010.001
Open science0.0000.000
Research integrity0.0000.001
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 head0.031
GPT teacher head0.340
Teacher spread0.309 · 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

Citations39
Published2016
Admission routes2
Has abstractyes

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