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Record W4398169243 · doi:10.4103/jms.jms_95_23

Knowledge and practice of handoff among doctors in a tertiary care hospital in Manipur: A cross-sectional study

2023· article· en· W4398169243 on OpenAlexaboutno aff
Ranchandra Nandeibam, A. Adheena Babu, Khangembam Sonarjit Singh, Jalina Laishram, Brogen Singh Akoijam

Bibliographic record

VenueJournal of Medical Society · 2023
Typearticle
Languageen
FieldMedicine
TopicHospital Admissions and Outcomes
Canadian institutionsnot available
Fundersnot available
KeywordsMedicineContext (archaeology)Test (biology)Tertiary careHealth careCross-sectional studyDescriptive statisticsFamily medicineHandoverQuarter (Canadian coin)Nursing

Abstract

fetched live from OpenAlex

ABSTRACT Context: The exchange of patient information and the transfer of responsibility for patient care between health-care providers constitute a vital aspect of health-care communication and maintain continuum of care and patient safety. There are limited data on knowledge and practice of handoff among resident doctors in Manipur. Aims: To assess the knowledge and practice of handoff among resident doctors of a tertiary care hospital, in Imphal, and to determine the association between sociodemographic characteristics and handoff practice. Subjects and Methods: A cross-sectional study among 279 resident doctors of a tertiary care hospital in Manipur was conducted. The data were collected using a pretested structured questionnaire. Statistical Analysis: The data were analyzed using IBM SPSS version 26.0. Descriptive statistics such as percentage, mean, and standard deviation were used to represent quantitative data. Chi-square test or Fisher’s exact test were used for categorical data. P < 0.05 was considered statistically significant. Results: The mean age of participants was 29.65 ± 3.97 years. More than two-thirds of the participants were inadequately practicing handoff in patient care. There were significant associations between the knowledge pertaining to questions, “When does handoff occur in patient care?” ( P = 0.013), “What is the purpose of handoff?” ( P = 0.024), and “What are the characteristics of good handoff?”( P = 0.019) with the practice of handoff. Conclusion: Although more than 4/5 th of the doctors had good knowledge, only a quarter of them had adequate handoff practice.

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)0.003
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.012
Threshold uncertainty score0.327

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
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 head0.018
GPT teacher head0.375
Teacher spread0.356 · 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.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
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

Citations0
Published2023
Admission routes1
Has abstractyes

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