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Record W4281569847 · doi:10.1177/15248380221093694

Measuring Grief in the Context of Traumatic Loss: A Systematic Review of Assessment Instruments

2022· review· en· W4281569847 on OpenAlexfundno aff
Naomi Ennis, Jamison S. Bottomley, Jessica K. Sawyer, Angela D. Moreland, Alyssa A. Rheingold

Bibliographic record

VenueTrauma Violence & Abuse · 2022
Typereview
Languageen
FieldPsychology
TopicGrief, Bereavement, and Mental Health
Canadian institutionsnot available
FundersNational Institute of Mental HealthCanadian Institutes of Health Research
KeywordsGriefComplicated griefContext (archaeology)Traumatic griefPsychologySystematic reviewClinical psychologyPsychotherapistMEDLINE

Abstract

fetched live from OpenAlex

Following traumatic loss, defined as the death of a loved one due to unexpected or violent circumstances, adults may experience a myriad of grief-related problems. Given the addition of Prolonged Grief Disorders into the Diagnostic and Statistical Manual for Mental Disorders Fifth Edition, Text-Revision and influx of unexpected deaths due to the global Coronavirus pandemic, there is heightened interest in the measurement of grief-related processes. We conducted a systematic review according to the Preferred Reporting Items for Systematic Reviews and Meta-Analyses guidelines to identify measures of grief used in studies of adults who experienced traumatic loss. Searches yielded 164 studies that used 31 unique measures of grief-related constructs. The most commonly used instrument was the Inventory of Complicated Grief-Revised. Half of the measures assessed constructs beyond diagnosable pathological grief responses. Given the wide variation and adaptations of measures reviewed, we recommend greater testing and uniformity of measurement across the field. Future research is needed to adapt and/or design measures to evaluate new criteria for Prolonged Grief Disorder.

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)0.004
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
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 score0.175
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0040.000
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0040.001
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.000
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 head0.142
GPT teacher head0.407
Teacher spread0.265 · 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.

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

Citations7
Published2022
Admission routes1
Has abstractyes

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