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Record W4413891683 · doi:10.1080/07481187.2025.2551378

Coping with suicide bereavement: A focus-group study of adaptation processes over time

2025· article· en· W4413891683 on OpenAlexaff
Clémence Jacquet, Geoffrey Gauvin, Édouard Leaune, Damien Fouques

Bibliographic record

VenueDeath Studies · 2025
Typearticle
Languageen
FieldPsychology
TopicGrief, Bereavement, and Mental Health
Canadian institutionsUniversité du Québec à Montréal
Fundersnot available
KeywordsCoping (psychology)PsychologyClinical psychologySuicide preventionPoison controlCoping behaviorHuman factors and ergonomicsPsychotherapistMedicineMedical emergency

Abstract

fetched live from OpenAlex

This qualitative study explored the coping resources mobilized by individuals bereaved by suicide and examined how these processes evolve over time. Twenty-one participants, bereaved for at least 14 months, took part in five semi-structured focus groups. Data were analyzed using thematic analysis, allowing the identification of key themes and temporal dynamics. Two major phases emerged from participants' narratives. Initially, participants relied on survival strategies and sought meaning through routines, social support, and information-seeking. Over time, participants reported engaging in deeper restructuring processes: reorganizing their daily lives, redefining their identity, and reshaping the bonds with the deceased. Emotionally salient moments-such as anniversaries-were described as both challenging and potentially meaningful. The findings highlight the complexity and non-linearity of suicide grief, with multidimensional processes unfolding over time. These findings offer valuable insights into the lived experiences of people bereaved by suicide and suggest the need for flexible, tailored clinical support.

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)0.008
metaresearch head score (Gemma)0.017
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: Qualitative
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.008
Threshold uncertainty score0.042

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0080.017
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.001
Science and technology studies0.0050.004
Scholarly communication0.0020.002
Open science0.0010.004
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0020.000

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 head0.062
GPT teacher head0.383
Teacher spread0.322 · 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
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

Citations0
Published2025
Admission routes1
Has abstractyes

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