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Physiological Knowledge Loss in Fourth-Year Nursing Students

2024· article· en· W4398166126 on OpenAlexaff
Yuwaraj Narnaware, Sharlini Purani, Melanie Neumeier

Bibliographic record

VenuePhysiology · 2024
Typearticle
Languageen
FieldMedicine
TopicClinical Reasoning and Diagnostic Skills
Canadian institutionsMacEwan University
Fundersnot available
KeywordsNursingMedicinePsychologyBiologyPhysiology

Abstract

fetched live from OpenAlex

There is a growing concern that nursing students struggle to retain adequate physiological knowledge throughout their program to meet their entry to practice competencies. However, how much and what knowledge is lost and when this occurs over a four-year undergraduate Bachelor of Science in Nursing program remains to be evaluated. Moreover, physiological knowledge retention has not been studied as extensively as anatomical knowledge retention in health care disciplines, including nursing programs (Narnaware, Y., 2021). Most of these studies are conducted after graduation (Aari et al., 2004) or focused on very limited systems (Pourshanazari et al., 2013). The present study aims to evaluate the level of physiological knowledge loss by nursing students in the fourth year between completing their physiology course in first-year nursing and fourth-year Critical Care nursing course . To evaluate physiological knowledge loss in the fourth year, nursing students were quizzed on ten organ systems using the online quizzing platform- Kahoot. Approximately nine to eleven knowledge and comprehension-level multiple-choice questions were delivered via kahoot. Then, these scores were compared to first-year quiz scores on the same content to determine overall knowledge loss over three years. Using SPSS II, the data was analyzed, and means were compared using 2-sample t-tests. The scores are described for each organ system by reporting the mean and standard deviation (±SD) with statistical significance set at P < 0.05 for all tests. The mean score of questions from all organ systems in year one was 62.89 ± 10.49 (±SD). Comparing that score to matched test items evaluated in the Critical Care course, there is a decrease in the overall mean score from 62.89 ± 10.49 (±SD) to 47.69 ± 8.23 (±SD). This equates to a 15.2% knowledge loss or 84.8% retention rate within three years. Organ-specific knowledge loss was highest for fluid and electrolytes (30.7%), hormones (28.6%), defences (22.5%), and reproductive physiology (22.5%), followed by renal physiology (19.7%). Knowledge loss was comparatively lower for blood (15.9%), inflammation (11.2%), vascular (7.5%) and respiratory physiology (4.7%). However, this loss was lowest for digestive physiology (-3.7%). The results of this study demonstrate a lower level of knowledge loss overall, with variations in loss being system-specific. The level of knowledge loss in the present study was significantly lower than previously reported in medical and allied health students (Pourshanazari et al., 2013) and lowest than anatomical knowledge retention levels in the same population (Narnaware and Neumeier, 2021). However, compared to the third year, knowledge loss in the fourth year is not significantly different (Narnaware et al., 2021). Applied for Teaching Physiology Section- Travel Fellowship Award. This is the full abstract presented at the American Physiology Summit 2024 meeting and is only available in HTML format. There are no additional versions or additional content available for this abstract. Physiology was not involved in the peer review process.

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)0.000
metaresearch head score (Gemma)0.003
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.644
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.003
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)0.0000.001

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 head0.047
GPT teacher head0.427
Teacher spread0.381 · 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".

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Citations1
Published2024
Admission routes1
Has abstractyes

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