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Record W2120884798 · doi:10.1093/geront/45.5.626

Factors Affecting Long-Term-Care Residents' Decision-Making Processes as They Formulate Advance Directives

2005· article· en· W2120884798 on OpenAlex
Heather C. Lambert, Mary Ann McColl, Julie Gilbert, Jiahui Wong, S. E. D. Shortt

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueThe Gerontologist · 2005
Typearticle
Languageen
FieldMedicine
TopicPalliative Care and End-of-Life Issues
Canadian institutionsKingston Health Sciences CentreQueen's University
Fundersnot available
KeywordsGrounded theoryAxial codingPsychologyDecision-makingQualitative researchLong-term carePopulationCoding (social sciences)Process (computing)Health careNursingApplied psychologyGerontologySocial psychologyMedicineTheoretical samplingComputer scienceBusinessSociologyMarketing

Abstract

fetched live from OpenAlex

PURPOSE: The purpose of this study was to describe factors contributing to the decision-making processes of elderly persons as they formulate advance directives in long-term care. DESIGN AND METHODS: This study was qualitative, based on grounded theory. Recruitment was purposive and continued until saturation was reached. Nine residents of a long-term-care facility were interviewed by use of a semistructured format. Open and axial coding of interview transcripts were carried out and the factors contributing to the decision process were defined. RESULTS: Elders based their decisions primarily on information gathered from personal experiences with death and illness. They obtained very little information from professionals or the media. Major factors considered by elders as they weighed information included spiritual, emotional, and social considerations. IMPLICATIONS: The factors considered during the decision-making process were oriented more toward the individual's experiences and less on contributions from objective sources than anticipated. Decision making for advance directives is a highly personalized process. The approach of health professionals when assisting with end-of-life decision making should be planned with these contributing factors in mind, so that the services offered to the individuals in this population best meet their needs.

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.

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)0.003
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 score0.113
Threshold uncertainty score0.552

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.003
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)0.0000.000

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 head0.095
GPT teacher head0.446
Teacher spread0.351 · 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