MétaCan
Menu
← Back to cohort
Record W4286209334 · doi:10.3390/curroncol29070406

The Transformation of Adolescent and Young Adult Oncological and Supportive Care in Canada: A Mixed Methods Study

2022· article· en· W4286209334 on OpenAlexafffundvenueabout
Jonathan Avery, Emily Wong, Christine R. Harris, Stacy Chapman, Serena Uppal, Shaayini Shanawaz, Annemarie Edwards, Laura Burnett, Tushar Vora, Abha A. Gupta

Bibliographic record

VenueCurrent Oncology · 2022
Typearticle
Languageen
FieldMedicine
TopicChildhood Cancer Survivors' Quality of Life
Canadian institutionsCancerCare ManitobaUniversity Health NetworkCanadian Cancer SocietyUniversity of ManitobaPrincess Margaret Cancer CentreUniversity of British Columbia
FundersPartenariat Canadien Contre Le CancerUniversity Health Network
KeywordsMentorshipMedicineYoung adultFocus groupHealth careFamily medicineNursingGerontologyMedical education

Abstract

fetched live from OpenAlex

BACKGROUND: Due to ongoing disparity in the specialized care available to adolescents and young adults (AYAs) with cancer, this study aimed to understand the gaps and barriers to accessing care and preferences on types of solutions at a national Canadian level. METHODS: A mixed-methods study involving an online survey and focus groups (FGs) was conducted among AYAs residing in different regions of Canada. RESULTS: = 125, 71.8%). Of the 174 respondents, 36 (20.7%) participated in one of seven FGs. Triangulation of the results illustrated that AYAs are not appropriately informed about the long-term health risks of being treated for cancer and where/how to seek support. These results culminated into three themes: (1) the need for AYA relevant and timely information about health risks; by (a) producing health risk-related content with the AYA life stage in mind; (b) providing a guided "map" to help AYAs anticipate what they may experience, and (c) providing checklists to help AYAs navigate their experience; (2) need for tailored and timely supportive care including (a) establishing ongoing check-ins and (b) receiving navigation support, and (3) need for enhanced connections by creating (a) a space to gather, connect and seek mentorship and (b) a hub to access information. CONCLUSION: AYAs continue to lack sufficient support both during and following cancer and mechanisms are required to ensure longitudinal support is provided across jurisdictions and in all stages of the cancer journey.

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)0.006
metaresearch head score (Gemma)0.007
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 score0.932
Threshold uncertainty score0.492

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0060.007
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0030.005
Science and technology studies0.0120.002
Scholarly communication0.0050.001
Open science0.0020.002
Research integrity0.0010.001
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 head0.075
GPT teacher head0.436
Teacher spread0.361 · 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

Citations8
Published2022
Admission routes4
Has abstractyes

Explore more

Same venueCurrent Oncology→Same topicChildhood Cancer Survivors' Quality of Life→French-language works237,207→