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Record W4414304610 · doi:10.1080/07481187.2025.2561079

Mourning rituals impact grief outcomes in East and Southeast Asia: A mixed-methods review

2025· review· en· W4414304610 on OpenAlexaff
Huy Hoang Le, Ningning Zhou, John S. Ogrodniczuk, Clare Killikelly

Bibliographic record

VenueDeath Studies · 2025
Typereview
Languageen
FieldPsychology
TopicGrief, Bereavement, and Mental Health
Canadian institutionsUniversity of British Columbia
Fundersnot available
KeywordsGriefCoping (psychology)CategorizationMental healthSoutheast asiaCulturally sensitiveExpression (computer science)Qualitative research

Abstract

fetched live from OpenAlex

Grief expression and coping mechanisms following death vary across cultures, with East and Southeast Asian societies particularly emphasizing cultural practices and rituals. This review investigates the role of mourning rituals in bereavement in these regions. We reviewed literature across PubMed, PsycINFO, and Web of Science databases, finding 10 studies reporting post-funeral rituals and grief outcomes in East and Southeast Asia. We categorize four central themes in which rituals aid post-loss adjustment: (1) death as a private matter, (2) the importance of family support, (3) mourning as an expression of filial piety, and (4) continuing bonds with the deceased. The review suggests that these rituals serve as an important tool for recovery, offering support during the mourning process and helping individuals adjust in the long term. Mental health professionals should consider these cultural practices when supporting grieving clients.

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)0.005
metaresearch head score (Gemma)0.022
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.006
Threshold uncertainty score0.028

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0050.022
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0040.005
Bibliometrics0.0060.007
Science and technology studies0.0010.001
Scholarly communication0.0030.002
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0050.000

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 head0.158
GPT teacher head0.538
Teacher spread0.381 · 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 designQualitative
Domainnot available
GenreReview

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

Citations4
Published2025
Admission routes1
Has abstractyes

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