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Record W2266567217 · doi:10.1177/0030222815572604

A Systematic Review of the Peer-Reviewed Literature on Self-Blame, Guilt, and Shame

2015· review· en· W2266567217 on OpenAlexaff
Catherine Duncan, Joanne Cacciatore

Bibliographic record

VenueOMEGA - Journal of Death and Dying · 2015
Typereview
Languageen
FieldPsychology
TopicGrief, Bereavement, and Mental Health
Canadian institutionsUniversity of Calgary
Fundersnot available
KeywordsShameBlameCINAHLPsychologyAnxietyGriefClinical psychologyGeneralizability theoryPsychotherapistPsychiatryDevelopmental psychologySocial psychologyPsychological intervention

Abstract

fetched live from OpenAlex

This is the first systematic review of the evidence on the prevalence of self-blame, guilt, and shame in bereaved parents. A search of PsychINFO, MEDLINE, Embase, CINAHL, PubMed, and Science Direct resulted in 18 studies for the period 1975 to 2013 which the authors have appraised. Self-blame, guilt, and shame are common in bereaved parents, albeit to varying degrees, with differential relationships to sex, and diminishing over time. There is some evidence that guilt and shame predict more intense grief reactions and that self-blame predicts posttraumatic symptomology, anxiety, and depression in bereaved parents. Heterogeneity of the studies and numerous methodological concerns limit the synthesis and strength of the evidence and the generalizability of the findings. Self-blame, guilt, and shame are commonly experienced by bereaved parents. Awareness of these affective states may assist clinicians in the identification of bereaved parents who are at a higher risk of developing adverse psychological outcomes. Overall, self-blame, guilt, and shame have received very little attention in the bereavement research, leaving many unanswered questions. Implications for practice and recommendations for future research are discussed.

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)0.003
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: Systematic review · Consensus signal: Systematic review
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.326
Threshold uncertainty score0.888

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0030.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0030.001
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0000.000

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 head0.063
GPT teacher head0.392
Teacher spread0.329 · 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 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

Citations78
Published2015
Admission routes1
Has abstractyes

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