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Record W4318499569 · doi:10.7759/cureus.34394

Perception of Survivorship Needs Among Breast Cancer Patients in Trinidad and Tobago

2023· article· en· W4318499569 on OpenAlexaff
Kristy Samaroo, Amalia Hosein, Jameel Ali

Bibliographic record

VenueCureus · 2023
Typearticle
Languageen
FieldMedicine
TopicCancer survivorship and care
Canadian institutionsUniversity of Toronto
FundersPan American Health Organization
KeywordsSurvivorship curveMedicinePsychosocialLikert scaleFamily medicineBreast cancerQuality of life (healthcare)PopulationPatient satisfactionScale (ratio)CancerGerontologyNursingPsychiatryPsychologyEnvironmental health

Abstract

fetched live from OpenAlex

The perception of survivorship among the cancer communities of the Caribbean is largely unknown. This study focused on determining the perception and interest in cancer survivorship among breast cancer (BC) patients in Trinidad and Tobago, as a preliminary, to introducing a pilot survivorship program and evaluating its impact on this patient population. Participants were given a questionnaire to determine needs, expectations and interest in survivorship care. Baseline measurable outcomes reported in this article include the following: 1. Participants' satisfaction with their medical care follow-up plan (if any), 2. Participants' satisfaction with the amount of information provided by healthcare providers, and 3. Participants' satisfaction with their physician's overall concern about their well-being, ranked on a 5-point Likert scale. Participants also reported on the advice/ guidelines provided by their physicians, after surgery and/or on completion of treatment, what they did to cope with BC, and their expectations of what could have been done to improve the quality of care received. A second questionnaire was then used to measure the level of interest in participating in a Cancer Survivorship Program (CSP) with components such as: nutrition, psychosocial development, spiritual well-being, and yoga and mindfulness. The level of interest was ranked by participants on a 5-point Likert scale. Fifteen themes emerged from participants' responses to the first questionnaire. Nutrition stood out as the module of highest interest, followed by psychosocial development among BC 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 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)0.000
metaresearch head score (Gemma)0.002
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.188
Threshold uncertainty score0.373

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0010.001
Scholarly communication0.0010.000
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 head0.017
GPT teacher head0.276
Teacher spread0.259 · 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 designQualitative
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

Citations2
Published2023
Admission routes1
Has abstractyes

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