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Record W2336210780 · doi:10.1177/1471301216633325

The bereavement experience of spousal caregivers to persons with dementia: Reclaiming self

2016· article· en· W2336210780 on OpenAlexaff
Shelley Peacock, Melanie Bayly, Kirstian Gibson, Lorraine Holtslander, Genevieve Thompson, Megan E. O’Connell

Bibliographic record

VenueDementia · 2016
Typearticle
Languageen
FieldPsychology
TopicGrief, Bereavement, and Mental Health
Canadian institutionsUniversity of ManitobaUniversity of Saskatchewan
Fundersnot available
KeywordsDementiaPsychologyThematic analysisFamily caregiversPopulationGerontologyClinical psychologyPsychotherapistDevelopmental psychologyQualitative researchMedicineDiseaseSociology

Abstract

fetched live from OpenAlex

Spouses of persons living with dementia both anticipate future loss and grieve for multiple losses occurring with caregiving and this ultimately influences their bereavement experience. Little research has been conducted regarding the bereavement experience in the caregiving journey with dementia and what does exist is mostly quantitative in nature. The purpose of this study is to describe the bereavement experience of spousal caregivers ( n = 10) utilizing Thorne's interpretive description. Thematic analysis revealed the features and facilitators of the bereavement process for spousal caregivers to persons with dementia. The unique contribution of this study to the dementia literature is the finding that the overall process of reclaiming self is significant to the bereavement journey. Future work should investigate identity as understood by spousal caregivers to persons with dementia, and further explore the processes, facilitators, and barriers to healthy bereavement in this population.

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)0.000
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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.545
Threshold uncertainty score0.835

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
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)0.0010.000

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 head0.021
GPT teacher head0.303
Teacher spread0.282 · 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

Citations24
Published2016
Admission routes1
Has abstractyes

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