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Care transitions among oncological patients: from hospital to community

2022· article· en· W4318669169 on OpenAlexaff
Caroline Donini Rodrigues, Elisiane Lorenzini, Manuel Portela‐Romero, Nelly D. Oelke, Vanessa Dalsasso Batista Winter, Adriane Cristina Bernat Kolankiewicz

Bibliographic record

VenueRevista da Escola de Enfermagem da USP · 2022
Typearticle
Languageen
FieldEconomics, Econometrics and Finance
TopicEconomic and Financial Impacts of Cancer
Canadian institutionsUniversity of British Columbia
Fundersnot available
KeywordsMedicineMEDLINEFamily medicinePolitical science

Abstract

fetched live from OpenAlex

OBJECTIVE: To analyze the transition of care from the perspective of cancer patients, in a Southern Brazil hospital, correlating perspectives with sociodemographic and clinical characteristics. METHOD: Cross-sectional study using the Care Transitions Measure (CTM) with cancer patients undergoing clinical or surgical treatment following hospital discharge. Data collection was completed by telephone, between June and September 2019. Data analysis was performed using descriptive and inferential statistics. RESULTS: The average CTM score was 74.1, which was considered satisfactory. The CTM factors: understanding about medications (83.3) and preparation for self-management (77.7) were deemed satisfactory; while: secured preferences (69.4) and care plan (66.1) were unsatisfactory for an effective and safe care transition. No statistically significant difference was found between sociodemographic variables and the CTM. Among the clinical variables, primary cancer and the secured preferences factor showed a significant difference (p = 0.044). CONCLUSION: The transition from hospital care to the community was considered satisfactory in the overall assessment.

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)0.001
metaresearch head score (Gemma)0.005
Version: metacan-v3-hybrid-931329e0061cValidation 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 score0.016
Threshold uncertainty score0.032

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.005
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0010.000
Scholarly communication0.0010.001
Open science0.0000.001
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0020.000

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 head0.036
GPT teacher head0.258
Teacher spread0.221 · 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 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

Citations14
Published2022
Admission routes1
Has abstractyes

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