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Record W4401089192 · doi:10.1590/0034-7167-2024-0066

Telenursing in the postoperative period: a scoping review

2024· review· en· W4401089192 on OpenAlexaff
Viviane Cristina de Albuquerque Gimenez, Graziela Maria Ferraz de Almeida, Cláudia Maria Silva Cyrino, Cassiane de Santana Lemos, Carolina Favoretto, Marla Andréia Garcia de Ávila

Bibliographic record

VenueRevista Brasileira de Enfermagem · 2024
Typereview
Languageen
FieldMedicine
TopicTelemedicine and Telehealth Implementation
Canadian institutionsImpact
FundersFundação de Amparo à Pesquisa do Estado de São Paulo
KeywordsCINAHLScopusChecklistMedicineContext (archaeology)MEDLINECochrane LibraryPhysical therapyNursingMeta-analysisPsychologyPsychological interventionInternal medicine

Abstract

fetched live from OpenAlex

OBJECTIVES: to map available evidence on telenursing use in the postoperative period and its impact on patient outcomes. METHODS: a scoping review, conducted according to the JBI model and the PRISMA-ScR checklist. The search was carried out in the CINAHL, Embase, LILACS, PubMed, Web of Science, SciELO, Scopus and Cochrane Library databases. RESULTS: twelve studies were included, published between 2011 and 2023, 66.6% of which were in developed countries. Of the positive outcomes, we highlight improved levels of disability, autonomy and quality of life, lower rates of post-operative complications, pain and reduced costs. Telephone monitoring was the most widely used modality, but there were few studies in the pediatric context and in Brazil. CONCLUSIONS: of the studies, 11 (91.6%) identified at least one positive outcome in telenursing use and none showed negative aspects in the postoperative period. The role of nurses in digital health needs further study.

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)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Systematic review · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.538
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.001
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0030.001
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
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 head0.141
GPT teacher head0.487
Teacher spread0.346 · 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 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

Citations5
Published2024
Admission routes1
Has abstractyes

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