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Record W3109288996 · doi:10.1177/0030222820977305

What Exactly Is “Complicated” Grief? A Scoping Research Literature Review to Understand Its Risk Factors and Prevalence

2020· article· en· W3109288996 on OpenAlexaff
Donna M. Wilson, Elizabeth Mirekuwaa Darko, Elizabeth Kusi‐Appiah, Sophia J. Roh, Arnel Ramic, Begoña Errasti‐Ibarrondo

Bibliographic record

VenueOMEGA - Journal of Death and Dying · 2020
Typearticle
Languageen
FieldPsychology
TopicGrief, Bereavement, and Mental Health
Canadian institutionsUniversity of Alberta
Fundersnot available
KeywordsGriefComplicated griefIncidence (geometry)Traumatic griefPsychologyDisenfranchised griefMedicineClinical psychologyPsychiatryPsychotherapist

Abstract

fetched live from OpenAlex

Most people will experience bereavement grief, but some suffer from persistent or prolonged (PoP) grief, grief that used to be identified as "complicated" before recent DSM-5 and ICD-11 definitional developments. In 2020, a scoping literature review was undertaken to identify and consolidate contemporary evidence from research articles published in 2018 or 2019 in paper-based and open access peer-review journals on: (a) the incidence or prevalence of PoP grief, and (b) who develops it or is diagnosed as suffering from it, and correspondingly what causative factors or predictors are associated with PoP grief. All of the 11 identified research articles reported an incidence or prevalence rate, with these varying greatly, but with a much higher rate now that a 6-month post-death measurement timeframe is used. The predictors or factors among people who were identified as having PoP grief also varied considerably, although sudden and unexpected deaths were often implicated.

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)0.015
metaresearch head score (Gemma)0.058
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Systematic review · Consensus signal: Systematic review
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.029
Threshold uncertainty score0.077

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0150.058
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0030.004
Bibliometrics0.0290.023
Science and technology studies0.0010.002
Scholarly communication0.0050.006
Open science0.0010.002
Research integrity0.0030.002
Insufficient payload (model declined to judge)0.0040.001

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 head0.193
GPT teacher head0.439
Teacher spread0.247 · 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 designSystematic review
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

Citations33
Published2020
Admission routes1
Has abstractyes

Explore more

Same venueOMEGA - Journal of Death and DyingSame topicGrief, Bereavement, and Mental HealthFrench-language works237,207