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Record W1964864399 · doi:10.1136/ebn.6.2.64

Learning to live with early stage dementia involved a continuous process of adjustment that comprised 5 stages

2003· letter· en· W1964864399 on OpenAlexaboutno aff
Sue Hall

Bibliographic record

VenueEvidence-Based Nursing · 2003
Typeletter
Languageen
FieldMedicine
TopicDementia and Cognitive Impairment Research
Canadian institutionsnot available
Fundersnot available
KeywordsIntrospectionDementiaPsychologyMedicineGynecologyInternal medicineDisease

Abstract

fetched live from OpenAlex

Werezak L, Stewart N. Learning to live with early dementia. Can J Nurs Res2002 ; 34 : 67 –85. [OpenUrl][1][PubMed][2] QUESTION: How do older adults learn to live with early stage dementia? Grounded theory. Saskatchewan, Canada. 3 women and 3 men (age range 61–79 y) with a diagnosis of Alzheimer’s disease or related disorder and early stage dementia. All participants lived at home with their spouses. Each person participated in 2 semistructured interviews. Transcripts from the first interviews were analysed using constant comparison, and 5 preliminary categories were identified. During second interviews (1–3 mo later) the author validated and expanded on these 5 categories. A theoretical framework outlined the continuous process of adjusting to early stage dementia, which comprised 5 stages: antecedents , anticipation , appearance , assimilation , and acceptance . Different levels of awareness connected the stages. As participants moved through the stages, their awareness shifted from highly introspective to more outwardly focussed. (1) Antecedents included subprocesses that made it difficult to obtain a … [1]: {openurl}?query=rft.jtitle%253DCanadian%2BJournal%2Bof%2BNursing%2BResearch%26rft.stitle%253DCan%2BJ%2BNurs%2BRes%26rft.aulast%253DWerezak%26rft.auinit1%253DL.%26rft.volume%253D34%26rft.issue%253D1%26rft.spage%253D67%26rft.epage%253D85%26rft.atitle%253DLearning%2Bto%2Blive%2Bwith%2Bearly%2Bdementia.%26rft_id%253Dinfo%253Apmid%252F12122774%26rft.genre%253Darticle%26rft_val_fmt%253Dinfo%253Aofi%252Ffmt%253Akev%253Amtx%253Ajournal%26ctx_ver%253DZ39.88-2004%26url_ver%253DZ39.88-2004%26url_ctx_fmt%253Dinfo%253Aofi%252Ffmt%253Akev%253Amtx%253Actx [2]: /lookup/external-ref?access_num=12122774&link_type=MED&atom=%2Febnurs%2F6%2F2%2F64.1.atom

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)0.001
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: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.404
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.002
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 head0.041
GPT teacher head0.327
Teacher spread0.286 · 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 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

Citations3
Published2003
Admission routes1
Has abstractyes

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