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Record W1503285900 · doi:10.12968/bjon.2002.11.17.1148

The concept of hope in nursing 4: hope and gerontological nursing

2002· review· en· W1503285900 on OpenAlexaff
Kaye A Henh, John R. Cutcliffe

Bibliographic record

VenueBritish Journal of Nursing · 2002
Typereview
Languageen
FieldPsychology
TopicOptimism, Hope, and Well-being
Canadian institutionsUniversity of Alberta
Fundersnot available
KeywordsGerontological nursingSpecialtyNursingGerontologyPsychologyQualitative researchMedicineSociologyFamily medicine

Abstract

fetched live from OpenAlex

This article is the fourth in a series of six that explores the nature of hope, reviews the existing theoretical and empirical work in several discrete areas of nursing and provides case studies to illustrate the role that hope plays in clinical situations. This article focuses on hope within the specialty of gerontological nursing. To date, most of the hope research, using qualitative and quantitative methodologies, has focused on well and chronically ill young or middle-aged adults; very few studies have examined hope in the older adult and specifically how older adults maintain hope in spite of multiple losses and/or changes. Hope has been studied in several elderly populations, including grieving widow(er)s, community-based older persons, persons living in long term care facilities and elders recruited from senior citizen centres. Research findings provide initial direction for the assessment of hope, and a reference for evaluating the effectiveness of these strategies. There remains, however, a need for continuing research in the area of hope in the older adult that is multifaceted and applicable to both practice and education.

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)0.002
metaresearch head score (Gemma)0.003
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.005
Threshold uncertainty score0.024

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.003
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0030.004
Science and technology studies0.0020.010
Scholarly communication0.0050.007
Open science0.0010.004
Research integrity0.0030.004
Insufficient payload (model declined to judge)0.0030.001

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 head0.061
GPT teacher head0.394
Teacher spread0.333 · 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 designNot applicable
Domainnot available
GenreReview

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

Citations28
Published2002
Admission routes1
Has abstractyes

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