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Record W2113522188 · doi:10.1177/1074840710366566

Perceived Level of Knowledge and Difficulty in Applying Family Assessment Among Senior Undergraduate Nursing Students

2010· article· en· W2113522188 on OpenAlexaboutno aff
Angel Chu Kee Lee, Shing On Leung, Polly Siu LingChan, Joyce Oi Kwan Chung

Bibliographic record

VenueJournal of Family Nursing · 2010
Typearticle
Languageen
FieldHealth Professions
TopicFamily and Patient Care in Intensive Care Units
Canadian institutionsnot available
Fundersnot available
KeywordsNursingMedicineFamily healthHealth assessmentFamily medicineNurse educationHealth careMedical educationPsychology

Abstract

fetched live from OpenAlex

Because the structure, development, and functioning of a family plays an important role in health and illness, preparing nursing students to assess families in health care settings is of critical importance. A quasi-experimental design using a pre- and postcourse questionnaire was used to examine students' perceived knowledge about family assessment and perceived difficulty applying family assessment in the clinical setting. The Calgary Family Assessment Model (CFAM) was taught in an elective nursing course, "Families in Health and Illness," offered at the University of Hong Kong. At the completion of the course, 46 senior baccalaureate nursing students showed a significant increase in their perceived understanding of all subcategories in CFAM compared with the control group of 43 senior baccalaureate nursing students who completed an elective nursing course in women's health. Teaching family nursing assessment in undergraduate programs may be useful in ensuring that nurses attend to families in practice.

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)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Research integrity
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.241
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.002
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 head0.155
GPT teacher head0.464
Teacher spread0.309 · 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.

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

Citations8
Published2010
Admission routes1
Has abstractyes

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