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Record W4411934138 · doi:10.1186/s12909-025-07274-9

The efficacy of the BOPPPS teaching model in clinical and health education: a systematic review and meta-analysis

2025· review· en· W4411934138 on OpenAlexaboutno aff
Jing Zhu, Heng Xiao, Rui Zhou, Xiaochuang Gan, Qitao Gou, Hongtao Tie

Bibliographic record

VenueBMC Medical Education · 2025
Typereview
Languageen
FieldSocial Sciences
TopicInnovative Educational Techniques
Canadian institutionsnot available
FundersChongqing Medical University
KeywordsMeta-analysisMedical educationSystematic reviewPsychologyMEDLINEMedicinePolitical scienceInternal medicine

Abstract

fetched live from OpenAlex

BACKGROUND: BOPPPS (Bridge-in, Objective, Preassessment, Participatory learning, Post-assessment, Summary) has emerged as a compelling alternative in clinical and health education, particularly in medical and nursing education. This study aimed to assess the efficacy of BOPPPS in clinical and health education, with a primary focus on medical education, while also considering its applications in related disciplines such as nursing and health services management. METHODS: A systematic review and meta-analysis were conducted using databases of PubMed, EMBASE, Cochrane Library, Scopus, and Web of Science, covering studies up to May 15th, 2023. Inclusion criteria were studies involving undergraduate students in clinical and health disciplines (e.g., medicine, nursing, health services management) using BOPPPS, comparing it to traditional teaching methods, and reporting on relevant outcomes. Exclusion criteria were studies not focused on clinical and health education or without a comparison group. Quality assessment was performed using the Newcastle-Ottawa Scale (NOS) for non-randomized studies and the Jadad scale for randomized controlled trials (RCTs). Heterogeneity among the studies was evaluated using the I² statistic and Cochran's Q test. Publication bias was assessed using funnel plots and Egger's test. RESULTS: A total of 146 publications were initially retrieved, with 16 studies (1198 in the BOPPPS group and 1122 in the control group) included. The pooled result revealed that BOPPPS significantly improved final examination scores (Standardized mean difference: 1.14, 95% CI 0.84-1.43; P < 0.001) compared to traditional teaching. Egger's test indicated no significant publication bias (p-value = 0.12). Additional benefits included improved student satisfaction (SMD 0.94, 95% CI 0.63-1.26; P < 0.001), classroom interaction (SMD 0.83, 95% CI 0.46-1.21; P < 0.001), and learning initiative (SMD 0.73, 95% CI 0.48-0.98; P < 0.001). CONCLUSION: BOPPPS demonstrates significant potential for enhancing various dimensions of clinical and health education, including academic performance, student engagement, and satisfaction. Policymakers and educational leaders should consider integrating BOPPPS into teacher training and curriculum design to promote active learning and improve learning outcomes. However, further research is necessary to explore its effectiveness in diverse cultural and educational contexts, as well as its potential impact on developing higher-order cognitive skills like critical thinking and problem-solving skills. While these findings are generalizable to similar educational settings, caution is recommended when applying them to different cultural contexts.

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)0.027
metaresearch head score (Gemma)0.059
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Meta-analysis · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.027
Threshold uncertainty score0.142

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0270.059
Meta-epidemiology (narrow)0.0030.001
Meta-epidemiology (broad)0.0200.041
Bibliometrics0.0100.009
Science and technology studies0.0010.001
Scholarly communication0.0040.003
Open science0.0030.002
Research integrity0.0030.002
Insufficient payload (model declined to judge)0.0030.000

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 head0.285
GPT teacher head0.600
Teacher spread0.315 · 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 designMeta-analysis
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

Citations17
Published2025
Admission routes1
Has abstractyes

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