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Record W1992314184 · doi:10.1177/01939450022044502

Personality Traits and Self-Care in Adults Awaiting Renal Transplant

2000· article· en· W1992314184 on OpenAlexaffabout
Martha E. Horsburgh, Heather Beanlands, Heather Locking-Cusolito, Anne Howe, Diane Watson, Susan E. Pollock, B. Ann Hilton

Bibliographic record

VenueWestern Journal of Nursing Research · 2000
Typearticle
Languageen
FieldPsychology
TopicAttachment and Relationship Dynamics
Canadian institutionsToronto General HospitalSt. Joseph's HospitalUniversity of British ColumbiaToronto Metropolitan UniversityUniversity of Windsor
Fundersnot available
KeywordsPersonalityBig Five personality traitsMedicineDialysisClinical psychologyRenal transplantHealth carePath analysis (statistics)PsychologyTransplantationPsychiatryInternal medicineSocial psychology

Abstract

fetched live from OpenAlex

This article reports the pretransplant findings of the first phase of a three-phase, longitudinal study examining relationships among personality traits and self-care abilities and behaviors of Ontario adults pre- and post-renal transplant. A consortium of Ontario nurse researchers representing three of Ontario's five renal transplant centers conducted this research. All adults on the cadaver transplant lists of 15 Ontario dialysis centers were invited to participate. One hundred ninety-eight adults awaiting renal transplant were enrolled in the study, representing a 70% response rate. A cross-sectional, correlational design was used for the pretransplant phase. Self-report measures with known psychometric properties were used; validity and reliability of the measures were supported by the sample. Data were analyzed using descriptive approaches, correlational analyses, multiple regression, and path analysis. Relationships were supported among selected personality traits, health state and self-care abilities and behaviors. Further research to examine personality traits and health state in relation to adult self-care is warranted.

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 categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.371
Threshold uncertainty score0.413

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
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 integrity0.0000.001
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 head0.062
GPT teacher head0.459
Teacher spread0.397 · 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

Citations20
Published2000
Admission routes2
Has abstractyes

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