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Record W4324045741 · doi:10.1089/pmr.2022.0060

A Phenomenological and Clinical Description of Pandemic Grief: How to Adapt Bereavement Services?

2023· article· en· W4324045741 on OpenAlexafffund
Mélanie Vachon, Deborah Ummel, Alexandra Guité‐Verret, Émilie Lessard, Dominique Girard

Bibliographic record

VenuePalliative Medicine Reports · 2023
Typearticle
Languageen
FieldPsychology
TopicGrief, Bereavement, and Mental Health
Canadian institutionsMontreal General HospitalUniversité de MontréalUniversité de SherbrookeUniversité du Québec à Montréal
FundersCanadian Institutes of Health Research
KeywordsGriefInterpretative phenomenological analysisPhenomenology (philosophy)PsychologyPandemicContext (archaeology)Hermeneutic phenomenologyPsychotherapistQualitative researchExperiential learningPalliative careLived experienceCoronavirus disease 2019 (COVID-19)NursingMedicineDiseaseSociologyEpistemologyPedagogy

Abstract

fetched live from OpenAlex

Background: Some studies suggest that individuals having lost a loved one during the COVID-19 pandemic report higher levels of grief reactions than people bereaved from natural causes. Little is known about the lived and subjective experience of individuals who lost a loved one under confinement measures. Aim: This research aims to provide a phenomenological description of pandemic grief (PG) that can be useful in clinical settings and bereavement services. Methods: Seventy-six qualitative phenomenological interviews have been conducted with 37 individuals who have lost a loved one during the first wave of the pandemic. Interpretative phenomenological analysis was performed following Tracy's criteria for rigorous qualitative research. Results: The experience of PG comprises clinical manifestations and can be described as "a type of grief occurring in the context of a pandemic, where applicable public health measures have precedence over end of life and caregiving practices as well as funeral rituals, overshadowing the needs, values, and wishes of the dying individuals and those who grieve them." Discussion/Conclusion: This study is the first to provide a phenomenological and experiential understanding of PG. Our phenomenological description can be helpful in clinical settings such as bereavement services within palliative care teams.

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)0.002
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 score0.008
Threshold uncertainty score0.674

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
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 head0.170
GPT teacher head0.430
Teacher spread0.260 · 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

Citations1
Published2023
Admission routes2
Has abstractyes

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