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Record W2529359056 · doi:10.1080/11745398.2016.1238308

The effects of leisure-time physical activity for optimism, life satisfaction, psychological well-being, and positive affect among older adults with loneliness

2016· article· en· W2529359056 on OpenAlexaff
Junhyoung Kim, Sunwoo Lee, Sanghee Chun, Areum Han, Jinmoo Heo

Bibliographic record

VenueAnnals of Leisure Research · 2016
Typearticle
Languageen
FieldHealth Professions
TopicHealth and Wellbeing Research
Canadian institutionsBrock University
Fundersnot available
KeywordsLonelinessOptimismAffect (linguistics)Life satisfactionPsychologyWell-beingPsychological well-beingMental healthPositive psychologyPhysical activityGerontologyClinical psychologyMedicineSocial psychologyPsychiatryPsychotherapistPhysical therapy

Abstract

fetched live from OpenAlex

The purpose of this study was to examine the effects of leisure-time physical activity (LTPA) involvement among older adults suffering from loneliness. Using data released from the Health and Retirement Study in 2008, this study investigated how participation in LTPA leads to well-being such as optimism, life satisfaction, psychological well-being, and positive affect among older adults with loneliness. Results indicated that the LTPA involvement was a significant predictor of optimism, life satisfaction, positive affect, and psychological well-being for older adults with a high level of loneliness. The interesting findings of this study were that LTPA enhanced positive emotions for older adults with loneliness and that positive emotions are one of the important factors in protecting individuals from illnesses.

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)0.003
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
Metaresearch0.0010.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0000.000
Science and technology studies0.0010.000
Scholarly communication0.0010.000
Open science0.0000.001
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 head0.071
GPT teacher head0.501
Teacher spread0.431 · 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

Citations134
Published2016
Admission routes1
Has abstractyes

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