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Record W7029415542

Interaction between professionals and cancer survivors in the context of Brazilian and Canadian care

2017· article· en· W7029415542 on OpenAlexaboutno aff

Bibliographic record

VenueLA Referencia (Red Federada de Repositorios Institucionales de Publicaciones Científicas) · 2017
Typearticle
Languageen
FieldMedicine
TopicWomen's cancer prevention and management
Canadian institutionsnot available
Fundersnot available
KeywordsThematic analysisContext (archaeology)Qualitative researchHealth professionalsHealth careQuality (philosophy)Primary health care
DOInot available

Abstract

fetched live from OpenAlex

ABSTRACT Objective: analyze cancer survivors’ reports about their communication with health professional team members and describe the similarities and differences in interactional patterns between Brazilian and Canadian health care contexts. Method: This study adopted a qualitative health research approach to secondary analysis, using interpretive description as the methodology, allowing us to elaborate a new research question and look at the primary data from a different perspective. There were in total eighteen participants; all of them were adults and elderly diagnosed with urologic cancer. After being organized and read, the data sets were classified into categories, and an analytic process was performed through inductive thematic analysis. Results: This resulted in three categories of findings which we have framed as: Communication between professional and survivor; The symptoms, the doubts, the questions; and Actions and reaction. Conclusion: This comparative study allowed us to bring to the attention of health professionals, especially nurses, findings regarding effective communication, humanization and empathy, supporting both inside and outside support groups, giving pieces of advice, and advocating for the survivor as is necessary. The study also showed the importance of self-development of these professionals as they fight for better quality in the health system for their patients.

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)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.578
Threshold uncertainty score0.885

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
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 integrity0.0000.000
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 head0.027
GPT teacher head0.301
Teacher spread0.275 · 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

Citations4
Published2017
Admission routes1
Has abstractyes

Explore more

Same venueLA Referencia (Red Federada de Repositorios Institucionales de Publicaciones Científicas)Same topicWomen's cancer prevention and managementFrench-language works237,207