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Record W4409358999 · doi:10.36740/wlek/202524

Prospects, possibilities and determinants of rehabilitation in nursing.

2025· review· en· W4409358999 on OpenAlexaboutno aff
Joanna Niezbecka-Zając, Zuzanna Łuba, Anna Mazurek, Anna Pacian

Bibliographic record

VenueWiadomości Lekarskie · 2025
Typereview
Languageen
FieldHealth Professions
TopicHealth, psychology, and well-being
Canadian institutionsnot available
Fundersnot available
KeywordsRehabilitationNursingPsychologyMedicinePhysical therapy

Abstract

fetched live from OpenAlex

Contemporary nursing models address complex human needs, emphasizing prevention, education, and rehabilitation. Nursing and rehabilitation are closely linked, aiming to restore full or partial functionality and support patients in returning to social, family, and professional life. The aim of this study was to analyze the role of nurses in rehabilitation and assess the potential for developing rehabilitation nursing in Poland, considering current trends and the growing demand for qualified staff. A comprehensive literature analysis was conducted, with a particular focus on the Canadian model and its scope in rehabilitation. The results indicate that rehabilitation nursing should expand in response to the needs of an aging society. The introduction of specialized training and the incorporation of rehabilitation nursing courses into higher education programs could significantly contribute to this field's development. The Canadian model demonstrates that proper education and certification in rehabilitation nursing enhance patient care and recovery. Implementing similar solutions in Poland could improve rehabilitation outcomes and overall patient well-being. However, adapting modern nursing models requires systemic changes and a shift in professional perception. Nursing should evolve from a primarily supportive role focused on basic care to an active, leadership-oriented function within the rehabilitation team. A well-trained rehabilitation nurse can significantly improve the effectiveness of rehabilitation, ensuring a more holistic and patient-centered approach.

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)0.002
metaresearch head score (Gemma)0.002
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: Review · Consensus signal: Review
Teacher disagreement score0.865
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0030.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0010.002
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 head0.049
GPT teacher head0.516
Teacher spread0.467 · 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
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

Citations3
Published2025
Admission routes1
Has abstractyes

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