Physiological Knowledge Retention in Second‐Year Nursing Students
Bibliographic record
Abstract
Despite anatomy and physiology being foundational courses in medical, nursing, and allied ‐health care programs, there is growing concern that the knowledge in these courses is not being retained by students over time. Numerous studies have demonstrated the difficulty of medical, allied health, and nursing students to retain and apply anatomical knowledge in their future years of study (Doomernik et al., 2017). However, physiological knowledge retention has not been studied as extensively as anatomical knowledge retention in health care disciplines, with very few studies focusing on nursing students (Aari et al., 2004). Of those studies, most are carried out after graduation (Aari et al., 2004) or are focused on a single or limited number of organ systems (Pourshanazari et al., 2013). We have previously shown that nursing students retained 92.0% of their first‐year physiological knowledge, losing 8.% within 4‐months (Narnaware and Neumeier, 2020a). The present study aims to determine the level of physiological knowledge retained by nursing students in the second year. To answer this question, nursing students were quizzed on ten organ systems using the on‐line quizzing system Kahoot. Each Kahoot quiz included nine to eleven knowledge and comprehension level multiple‐choice questions. These scores were compared to first‐year quiz scores on the same content to determine overall knowledge retention over a year. Data were statistically 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). Statistical significance was set at P < 0.05 for all tests. The mean score of questions from all organ systems in year one was 62.9 ± 10.5 (±SD). Comparing that score to matched test items evaluated in the pathophysiology course, there is a decrease in the overall mean score from 62.9 ± 10.5 (±SD) to 47.9 ± 9.2 (±SD). This equates to an 85.0% retention rate, or 15.0% knowledge loss within a year. Organ‐specific knowledge retention was highest for digestive physiology (97.37%), respiratory physiology (92.32%), fluid and electrolyte physiology (90.41%), inflammation (85.99%), reproductive physiology (83.55%), and vascular physiology (85.22%). This was followed by renal physiology (83.37%) and blood (82.49%). Retention was comparatively lower for endocrine physiology (79.47%) and defenses (70.42%). These results demonstrate a high level of knowledge retention overall, with variations in retention being system‐specific. The level of knowledge retention in this study was significantly higher than previous rates reported in medical and allied‐health students (Pourshanazari et al., 2013) and is significantly higher than anatomical knowledge retention levels in the same population (Narnaware and Neumeier, 2020b). This study identifies where nursing students' knowledge retention gaps exist which will help to develop an interventional strategy for nursing students in the future.
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 imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.007 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 0.001 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".