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Record W2074289509 · doi:10.1177/089826430101300106

Self-Care among Older Adults

2001· article· en· W2074289509 on OpenAlexaff
Leslie McDonald-Miszczak, Andrew Wister, Gloria Gutman

Bibliographic record

VenueJournal of Aging and Health · 2001
Typearticle
Languageen
FieldMedicine
TopicDiabetes Management and Education
Canadian institutionsSimon Fraser University
Fundersnot available
KeywordsMedicineContext (archaeology)Multilevel modelArthritisTelephone surveyGerontologyClinical psychologyPsychologyInternal medicine

Abstract

fetched live from OpenAlex

OBJECTIVES: The authors hypothesize that older adults diagnosed with arthritis show a greater reliance on objective factors in their self-care behaviors, whereas those diagnosed with heart problems or hypertension demonstrate a greater reliance on more general belief-laden factors. METHODS: A total of 794 older adults (mean age = 69.3) who were professionally diagnosed with arthritis, heart problems, or hypertension completed a telephone survey about a number of aspects of their illness condition and their general well-being. RESULTS: The results from the hierarchical regression analyses indicate that objective factors and illness-specific beliefs are better predictors of self-care behavior in the arthritis group, whereas general beliefs (e.g., self-efficacy and general well-being) are better predictors of such behavior in the heart problems and hypertension groups. DISCUSSION: The analyses support the authors' hypothesis. The results are discussed in the context of expanding the Health Belief Model of self-care.

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.004
Version: metacan-v3-hybrid-931329e0061cValidation 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 score0.005
Threshold uncertainty score0.010

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.004
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)0.0030.000

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 head0.015
GPT teacher head0.315
Teacher spread0.299 · 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 source (direct Gemma or distilled Codex), 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

Citations43
Published2001
Admission routes1
Has abstractyes

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