MétaCan
Menu
← Back to cohort
Record W4200048893 · doi:10.1093/geroni/igab046.507

Self-Transcendent Wisdom Mediates the Association Between Spirituality and Well-Being in Six Nations

2021· article· en· W4200048893 on OpenAlexaffabout
Monika Ardelt, Juensung J. Kim, Michel Ferrari

Bibliographic record

VenueInnovation in Aging · 2021
Typearticle
Languageen
FieldPsychology
TopicPsychological Well-being and Life Satisfaction
Canadian institutionsUniversity of Toronto
Fundersnot available
KeywordsSpiritualityGeneralizability theoryChinaPsychologyAssociation (psychology)Well-beingLife satisfactionSocial psychologySample (material)Developmental psychologyPolitical scienceMedicineChemistryPsychotherapist

Abstract

fetched live from OpenAlex

Abstract Distraught individuals sometimes turn to religion for solace, particularly in old age, so spirituality is not necessarily positively related to well-being. However, spirituality might lead to greater well-being if it promotes self-transcendent wisdom. Using a sample of 307 respondents from six nations (USA, Canada, Serbia, Ukraine, Iran, and China), ranging in age from 59 to 99 years (M=73.00, SD=8.13), this study tested the generalizability of the hypothesized mediated pathway. Results showed only weak correlations between spirituality and well-being measures in the whole sample. Yet, as predicted, spirituality, mediated by self-transcendent wisdom, was indirectly related to greater well-being in all six nations, despite significant differences by nation in variable means. Spirituality had additional direct positive effects on life satisfaction in Canada, Iran, and China and on general well-being in Iran and China. These findings suggest that spirituality likely results in greater well-being when it transcends egocentric concerns.

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 score0.016
Threshold uncertainty score0.031

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 studies0.0010.001
Scholarly communication0.0010.000
Open science0.0000.001
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0030.000

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 head0.023
GPT teacher head0.331
Teacher spread0.308 · 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
Published2021
Admission routes2
Has abstractyes

Explore more

Same venueInnovation in Aging→Same topicPsychological Well-being and Life Satisfaction→French-language works237,207→