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Record W2040554836 · doi:10.3928/0098-9134-20010701-09

Continuing Care Nurses' Perceptions of Need for Physical Assessment Skills

2001· article· en· W2040554836 on OpenAlexaffabout
Marjorie Anderson, D. Lynn Skillen, Cheryl Knight

Bibliographic record

VenueJournal of Gerontological Nursing · 2001
Typearticle
Languageen
FieldHealth Professions
TopicNursing Roles and Practices
Canadian institutionsUniversity of Alberta
Fundersnot available
KeywordsNursingGerontological nursingPerceptionContinuing educationPsychologyMEDLINEMedicineMedical educationPolitical science

Abstract

fetched live from OpenAlex

The purpose of this descriptive research was to identify the perceived learning needs of registered nurse case managers for physical assessment skills, their facility with computers, and barriers and supports to the enhancement and application of physical assessment by these caregivers in the work-place. Nineteen continuing care facilities in one Alberta Health Region participated. Using data source triangulation, two independent groups, case managers (n = 150) and nurse administrators or staff development officers (n = 39) responded to a questionnaire developed by the researchers. The case managers reported that skill in physical assessment was very important in their work, but current skill was inadequate to meet resident care needs. Both groups ranked the thorax and lungs, cardiovascular/peripheral vascular systems, and abdomen as the top three body systems or regions in terms of the case managers' learning needs. This research identified that for these case managers, upgrading skills in physical assessment was a continuing education priority and suggested computer-assisted instruction as a potential delivery method.

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: Other design · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.658
Threshold uncertainty score0.451

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
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 head0.043
GPT teacher head0.495
Teacher spread0.452 · 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 designOther design
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

Citations5
Published2001
Admission routes2
Has abstractyes

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