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Record W4386820486 · doi:10.1080/11745398.2023.2254866

Benefits of volunteering on resilience with aging: a case study

2023· article· en· W4386820486 on OpenAlexaff
Rokbit Sanghee Lee, Jinmoo Heo, Sanghee Chun, Jasmyn Kim

Bibliographic record

VenueAnnals of Leisure Research · 2023
Typearticle
Languageen
FieldPsychology
TopicResilience and Mental Health
Canadian institutionsBrock University
FundersYonsei University
KeywordsGratitudePsychological resiliencePsychologyCoping (psychology)Qualitative researchVolunteer workDanceResilience (materials science)Social psychologyGerontologySuccessful agingSociologyPublic relationsMedicineClinical psychologySocial sciencePolitical science

Abstract

fetched live from OpenAlex

As the study of volunteering among older adults continues to evolve, questions related to the benefits of volunteering are of growing interest. Volunteering may create opportunities to develop resilience in older adults as it can serve as a coping strategy. This case study explored the perceived benefits of volunteering on resilience and various dimensions related to aging among elderly volunteer dancers. In this qualitative study, 13 volunteer performers of Korean traditional dance were recruited for in-depth interviews. The analysis of the transcripts generated five themes related to the benefits of volunteering that were unique to older volunteers: (1) finding a sense of self-worth through serving others, (2) finding a sense of purpose, (3) experiencing gratitude, (4) renewing a younger self, and (5) building companionship. The findings revealed that regular volunteering promoted the experience of resilience in the face of the challenges associated with aging.

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)0.003
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation 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 score0.085
Threshold uncertainty score0.804

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0030.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.002
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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 head0.341
GPT teacher head0.564
Teacher spread0.223 · 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.

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

Citations3
Published2023
Admission routes1
Has abstractyes

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