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Record W4220790814 · doi:10.1016/j.lanwpc.2022.100391

Ikigai and subsequent health and wellbeing among Japanese older adults: Longitudinal outcome-wide analysis

2022· article· en· W4220790814 on OpenAlexaff
Sakurako S. Okuzono, Koichiro Shiba, Eric S. Kim, Kokoro Shirai, Naoki Kondo, Takeo Fujiwara, Katunori Kondo, Tim Lomas, Claudia Trudel‐Fitzgerald, Ichiro Kawachi, Tyler J. VanderWeele

Bibliographic record

VenueThe Lancet Regional Health - Western Pacific · 2022
Typearticle
Languageen
FieldSocial Sciences
TopicHealth disparities and outcomes
Canadian institutionsUniversity of British Columbia
FundersNational Cancer Institute
KeywordsPsychosocialHappinessSocioeconomic statusGerontologySocial supportHobbyLife satisfactionConfidence intervalQuality of life (healthcare)DistressMedicinePsychologyMental healthActivities of daily livingDemographyClinical psychologyPopulationPsychiatryEnvironmental healthSocial psychology

Abstract

fetched live from OpenAlex

BACKGROUND: "-a related but broader concept in Japan-is also beneficial for various physical and psychosocial outcomes. METHODS: in 2013 and a wide range of subsequent outcomes assessed in 2016 across two databases (n = 6,441 and n = 8,041), including dimensions of physical health, health behavior, psychological distress, social wellbeing, subjective wellbeing, and pro-social/altruistic behaviors. We adjusted for sociodemographic characteristics and the outcome values (whenever data were available) in the prior wave (2010). FINDINGS: was associated with decreased depressive symptoms and hopelessness as well as higher happiness, life satisfaction, instrumental activity of daily living, and certain social outcomes (e.g., more frequent participation in hobby clubs). Some of these associations were stronger for men than women, and among individuals with high socioeconomic status (p-values for effect measure modification < 001). INTERPRETATION: may promote health and wellbeing outcomes among Japanese older adults, but particularly men and individuals with high socioeconomic status. FUNDING: NIH, John Templeton Foundation, JSPS, AMED, MHLW, MEXT, and WPE Foundation.

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)0.004
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesScience and technology studies
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.182
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0040.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.001
Science and technology studies0.0040.001
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0000.000

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 head0.063
GPT teacher head0.359
Teacher spread0.296 · 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

Citations80
Published2022
Admission routes1
Has abstractyes

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