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Record W2899766908 · doi:10.1093/geroni/igy023.2446

COMPLICATED GRIEF AND DEATH ANXIETY AMONG OLDER KOREANS WITH SPOUSAL BEREAVEMENT

2018· article· en· W2899766908 on OpenAlexaff
K Kim, Jing Lyu

Bibliographic record

VenueInnovation in Aging · 2018
Typearticle
Languageen
FieldPsychology
TopicGrief, Bereavement, and Mental Health
Canadian institutionsInstitute of Aging
Fundersnot available
KeywordsGriefAnxietyDeath anxietyPsychologyClinical psychologyPsychiatryPsychotherapist

Abstract

fetched live from OpenAlex

This study was aimed to empirically verify the relationship between complicated grief and death anxiety among the bereaved older adults. The sample consisted of 815 bereaved adults aged 65 and over living in the community. Dependent variable was measured with the Death Anxiety Scale-Korean version (DAS-K), and independent variable was measured with the Inventory of Complicated Grief-Korean version (ICG-K). Adjusting for demographic, psychosocial, and health variables, multiple regression analysis was conducted using SPSS 23.0. The results showed that complicated grief was significantly associated with death anxiety among the bereaved (p<001). This suggests that the unhealed emotional and physical pain after spousal bereavement stimulates death anxiety. Older adults who suffer from complicated grief often fail to integrate the bereavement and loss into reality, and may not accept the death phenomenon itself. Therefore, anxiety and fear of death can emerge when they cannot acknowledge the bereavement. Interventions to enhance adaptation to bereavement should be provided in order to manage complicated grief and alleviate death anxiety.

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)0.004
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 score0.002
Threshold uncertainty score0.005

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.004
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0010.000
Scholarly communication0.0010.001
Open science0.0000.001
Research integrity0.0000.001
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 head0.032
GPT teacher head0.334
Teacher spread0.302 · 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

Citations5
Published2018
Admission routes1
Has abstractyes

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