Self-assessment or self deception? A lack of association between nursing students’ self-assessment and performance
Bibliographic record
Abstract
AIM: The aim of this study was to examine senior year nursing students' ability to self-assess their performance when responding to simulated emergency situations. BACKGROUND: Self-assessment is viewed as a critical skill in nursing and other health professional programmes. However, while students may spend considerable time completing self-assessments, there is little evidence that they actually acquire the skills to do so effectively. By contrast, a number of studies in medicine and elsewhere have cast doubt on the validity of self-assessment. METHOD: In 2007, a one-group pre-test, post-test design was used to answer the question, 'How accurate are senior year nursing students in assessing their ability to respond to emergency situations in a simulated medical/surgical environment compared to observer assessment of their performance?' A total of 27 fourth year nursing students from a university in Ontario were asked to complete a questionnaire before and after an objective structured clinical examination which assessed their ability to respond to emergency situations. Self-assessments were compared with observed performance. FINDINGS: The experience of dealing with the simulated crisis situations significantly increased perceived confidence and perceived competence in dealing with emergency situations, although it did not affect self-perceived ability to communicate or collaborate. All but 1 of the 16 correlations between self-assessment and the objective structured clinical examination total scores were negative. Their self-assessment was also unrelated to several indices of experience in critical care settings. CONCLUSION: Self-assessment in nursing education to evaluate clinical competence and confidence requires serious reconsideration as our well-intentioned emphasis on this commonly used practice may be less than effective.
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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 | 0.005 | 0.042 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.000 |
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.
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".