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Record W4417449815 · doi:10.1111/jan.70443

Teaching and Learning Activities That Promote Critical Thinking in Student Nurse Practitioners: A Rapid Review

2025· review· en· W4417449815 on OpenAlexaff
Shannon McNamara, Lisa Cranley, Kelley Kilpatrick, Monica Parry

Bibliographic record

VenueJournal of Advanced Nursing · 2025
Typereview
Languageen
FieldSocial Sciences
TopicEducation and Critical Thinking Development
Canadian institutionsMcGill UniversityUniversité du QuébecUniversity of Toronto
Fundersnot available
KeywordsCritical thinkingStudent nurseMEDLINENurse educatorNurse education

Abstract

fetched live from OpenAlex

BACKGROUND: Critical thinking has been identified as a key requirement for safe and competent practice for Nurse Practitioners. It has been suggested that it is the foundation for the development of clinical reasoning, diagnostic reasoning, and clinical judgement. Poorly developed critical thinking is linked to negative patient outcomes, diagnostic error, cognitive bias, and poor information processing. There is little literature that studies the teaching and learning activities that can be used in the development of critical thinking in Nurse Practitioners. The aim of this rapid review was to identify teaching and learning activities that promote critical thinking in Nurse Practitioners. DESIGN AND METHOD: A rapid review was conducted to identify studies that examined different teaching and learning activities that promoted the development of critical thinking or any of its subthemes such as clinical reasoning, diagnostic reasoning or clinical judgement. Four databases were systematically searched: CINAHL, Medline, Embase and ERIC. The methodology used was guided by the Cochrane Rapid Review Methods Group. Eligible papers included peer-reviewed publications that evaluated the efficacy or effectiveness of teaching or learning strategies used for the development or promotion of critical thinking or its components. The included populations were faculty teaching in a Nurse Practitioner programme, Nurse Practitioners, Nurse Practitioner students or graduate level nursing students. RESULTS: The search yielded 6421 article titles and abstracts. Of these, 12 were included in the final rapid review. Teaching and learning activities were divided into three themes: classroom, simulation, and written. Classroom activities included problem-based learning, unfolding case scenarios, self-explanation, and Socratic inquiry. Simulation was in the form of high fidelity using standardised patients, computer-based programmes, escape rooms and virtual reality. Written activities included concept mapping, evolving case studies and illness scripts. Study participants noted that using a combination of teaching and learning activities had the greatest impact on their development of critical thinking. CONCLUSION: There is limited knowledge on the effects of teaching and learning strategies on the development of critical thinking in nurse practitioners. This review offers a perspective on strategies that were most impactful for student nurse practitioners in their development of the different aspects of critical thinking. Simulation activities were the most researched and using it in combination with other activities was preferred by study participants. PATIENT OR PUBLIC CONTRIBUTION: No patient or public contribution as this is a literature review.

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 imitation

Not 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.

metaresearch head score (Codex)0.016
metaresearch head score (Gemma)0.062
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Systematic review · Consensus signal: Systematic review
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.022
Threshold uncertainty score0.083

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0160.062
Meta-epidemiology (narrow)0.0020.001
Meta-epidemiology (broad)0.0060.005
Bibliometrics0.0220.019
Science and technology studies0.0010.001
Scholarly communication0.0040.005
Open science0.0030.002
Research integrity0.0030.001
Insufficient payload (model declined to judge)0.0050.001

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 head0.049
GPT teacher head0.468
Teacher spread0.419 · 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 source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designSystematic review
Domainnot available
GenreReview

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

Citations1
Published2025
Admission routes1
Has abstractyes

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