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Record W2561778199 · doi:10.3747/co.23.3140

The Experiences of Cancer Survivors While Transitioning from Tertiary to Primary Care

2016· article· en· W2561778199 on OpenAlexaffvenue
Bryan B. Franco, Laavanya Dharmakulaseelan, Alison McAndrew, Sejong Bae, Margaret Cheung, Saurabh Singh

Bibliographic record

VenueCurrent Oncology · 2016
Typearticle
Languageen
FieldHealth Professions
TopicAdolescent and Pediatric Healthcare
Canadian institutionsHealth Sciences CentreSunnybrook Health Science Centre
Fundersnot available
KeywordsTimelineCLARITYMedicineFocus groupPrimary careQualitative researchHealth careNursingTransition (genetics)Family medicineTertiary careDescriptive statisticsPolitical science

Abstract

fetched live from OpenAlex

PURPOSE: In current fiscally constrained health care systems, the transition of cancer survivors to primary care from tertiary care settings is becoming more common and necessary. The purpose of our study was to explore the experiences of survivors who are transitioning from tertiary to primary care. METHODS: One focus group and ten individual telephone interviews were conducted. Data saturation was reached with 13 participants. All sessions were audio-recorded, transcribed verbatim, and analyzed using a qualitative descriptive approach. RESULTS: Eight categories relating to the main content category of transition readiness were identified in the analysis. Several factors affected participant transition readiness: how the transition was introduced, perceived continuity of care, support from health care providers, clarity of the timeline throughout the transition, and desire for a "roadmap." Although all participants spoke about the effect of their relationships with health care providers (tertiary, transition, and primary care), their relationship with the primary care provider had the most influence on their transition readiness. CONCLUSIONS: Our study provided insights into survivor experiences during the transition to primary care. Transition readiness of survivors is affected by many factors, with their relationship with the primary care provider being particularly influential. Understanding transition readiness from the survivor perspective could prove useful in ensuring patient-centred care as transitions from tertiary to primary care become commonplace.

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 score0.618
Threshold uncertainty score0.446

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 studies0.0010.000
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 head0.146
GPT teacher head0.492
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.

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

Citations22
Published2016
Admission routes2
Has abstractyes

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