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Record W2183395498 · doi:10.1186/s12912-015-0118-2

Registered Nurse to Bachelor of Science in Nursing: nesting a fast-track to traditional generic program, teachings from nursing education in Burkina Faso

2015· article· en· W2183395498 on OpenAlexaff
Idrissa Beogo, Chieh‐Yu Liu, Colile P. Dlamini, Marie‐Pierre Gagnon

Bibliographic record

VenueBMC Nursing · 2015
Typearticle
Languageen
FieldNursing
TopicNursing education and management
Canadian institutionsUniversité Laval
Fundersnot available
KeywordsNursingNursing researchNurse educationMedicineBachelorTest (biology)Descriptive statisticsMedical educationPolitical science

Abstract

fetched live from OpenAlex

BACKGROUND: Nursing education has evolved over time to fit societies' increasing care needs. Innovations in nursing education draw thorny debates on potential jeopardy in the quality, safety, and efficacy of nurse graduates. Accelerated nursing education programs have been among landmark strategic changes to address the persistent bedside nurse shortage. Despite the dearth of empirical studies in sub-Saharan Africa (SSA), the National School of Public Health of Burkina Faso has developed a State Diploma Nursing (SDN) fast-track program. With innovative features, the program is nested into the traditional SDN program. This study investigates preliminary outcomes of the implemented policy using the initial cohort that went through the program. Comparison of the traditional generic program and the fast-track one is drawn to inform nursing education policy. METHODS: The study was conducted in the three campuses delivering the SDN program. Data collected from a representative sample included 255 students from the 2006-2009 cohort, after concluding the program. Surveyed students were assessed according to the program entry status. Outcomes were measured using students' academic performance. Besides descriptive analysis, bivariate t-test, F-test, and multivariate ordinary least square regression (OLSR) were employed to determine the comparative pattern between the traditional generic and the newly nested fast-track program. Students' varied statuses (private pre-registration, state pre-registration, private post-registration, and state post-registration) were kept to better outline the findings trend. RESULTS: A fifth (19.6 %) of surveyed students were enrolled in the fast-track stream from which, one third (33.7 %) consisted of post-registered students. Fast-track students comparatively achieved the best academic performance (mean: 73.68/100, SD: 5.52). Multivariate OLSR confirmed that fast-track students performed better (β: 5.559, p < 0.001), and further informed differences between campuses. Students entry status also displayed significant differences, yet the academic performance of post-registered students from traditional generic versus fast-track was similar (p = 0.409). CONCLUSION: Findings suggest that fast-track program students performed better than the ones from the traditional generic program. The uniqueness and success of this mixed nursing program experience sheds light for nursing educators engaged in policy making. The study results can serve as a crucial foundation for policymakers to alleviate the nurse shortage in SSA.

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)0.001
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Other design · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.883
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0020.003
Science and technology studies0.0000.001
Scholarly communication0.0000.001
Open science0.0010.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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 head0.081
GPT teacher head0.381
Teacher spread0.300 · 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 designOther design
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".

Quick stats

Citations5
Published2015
Admission routes1
Has abstractyes

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