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Record W4399055887 · doi:10.1111/spc3.12972

Everyday acts of kindness predict greater well‐being during the transition to university

2024· article· en· W4399055887 on OpenAlexaff
Tiara A. Cash, Lara B. Aknin, Yuthika U. Girme

Bibliographic record

VenueSocial and Personality Psychology Compass · 2024
Typearticle
Languageen
FieldPsychology
TopicPsychological Well-being and Life Satisfaction
Canadian institutionsSimon Fraser University
Fundersnot available
KeywordsKindnessPsychologyTransition (genetics)Well-beingSocial psychologyChemistryPsychotherapistPhilosophyTheology

Abstract

fetched live from OpenAlex

Abstract From becoming a teenager to starting university, life transitions are an inevitable part of human existence. While exciting, life transitions can be stressful because they involve changes in identity, routine, and expectations. What can support people during this period of change? Informed by past research demonstrating the emotional benefits of prosocial behavior, we examined whether everyday acts of prosociality might predict well‐being during a life transition using a pre‐registered 6‐week diary study conducted with students starting university ( N = 193; 1544 observations). Consistent with pre‐registered hypotheses, participants experienced higher well‐being on scales capturing happiness, flourishing, thriving, optimism, resilience, anxiety and loneliness during weeks in which they completed more prosocial acts than their personal average. This research extends our understanding of the relationship between prosociality and well‐being to new theoretically relevant contexts, including extended, multi‐faceted personal stressors, and suggests that one potentially useful route to well‐being during life transitions could be helping others.

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)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.741
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
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 head0.033
GPT teacher head0.323
Teacher spread0.289 · 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.

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

Citations4
Published2024
Admission routes1
Has abstractyes

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