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Record W4415247164 · doi:10.1037/pag0000942

A lifespan perspective on daily well-being: Differences in within-person variability by well-being domains and age.

2025· article· en· W4415247164 on OpenAlexaff
Gabrielle N. Pfund, Jonathan Rush

Bibliographic record

VenuePsychology and Aging · 2025
Typearticle
Languageen
FieldPsychology
TopicAging and Gerontology Research
Canadian institutionsUniversity of Victoria
Fundersnot available
KeywordsYoung adultPerspective (graphical)Activities of daily livingAffect (linguistics)Multilevel modelAdult developmentVitalityScale (ratio)

Abstract

fetched live from OpenAlex

= 69.04, SD = 9.06, range = 55-94). Mixed effect location scale models suggested that older adults on average scored higher than young adults on daily self-acceptance, engagement, sense of purpose, autonomy, competence, personal growth, relatedness, vitality, and positive affect; scored lower on negative affect; and did not score differently on life satisfaction. Meanwhile, young adults experienced more daily within-person variability in all 11 well-being domains. Finally, multigroup, multilevel structural equation models showed that, at the between-person level, negative affect was more strongly tied to other well-being domains in young adults, while positive affect and vitality were more strongly tied to other well-being domains in older adults. At the within-person level, changes in one daily well-being domain were more strongly associated with changes in another 65% of the time for young adults and 33% of the time for older adults. The present study highlights differences in daily well-being processes tied to age and the larger role that daily events and experiences may play in shaping the short-term experiences of well-being in young adults' daily lives. (PsycInfo Database Record (c) 2026 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)0.005
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 score0.005
Threshold uncertainty score0.018

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.005
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0010.001
Open science0.0000.001
Research integrity0.0000.001
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 head0.021
GPT teacher head0.361
Teacher spread0.340 · 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

Citations1
Published2025
Admission routes1
Has abstractyes

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