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Record W4317476710 · doi:10.1097/spc.0000000000000628

Sexual and gender diversity in cancer care and survivorship

2023· review· en· W4317476710 on OpenAlexaff
Christian Schulz, Margo Kennedy, Brendan Lyver

Bibliographic record

VenueCurrent Opinion in Supportive and Palliative Care · 2023
Typereview
Languageen
FieldMedicine
TopicCancer survivorship and care
Canadian institutionsPrincess Margaret Cancer CentreUniversity of TorontoUniversity Health Network
Fundersnot available
KeywordsTransgenderLesbianSurvivorship curveMedicineDiversity (politics)MEDLINENarrative reviewHealth careCancerSexual orientationHuman sexualityFamily medicineNursingGerontologyPsychologyGender studiesSocial psychologyIntensive care medicinePolitical scienceSociology

Abstract

fetched live from OpenAlex

PURPOSE OF THE REVIEW: Sexual and gender diverse (SGD) cancer patients possess unique identities and needs that must be considered during their cancer care. This narrative review explores the current literature on sexual and gender diversity in cancer care and survivorship, in addition to providing recommendations encouraged by the current literature. RECENT FINDINGS: We performed a literature search for articles published in English between January 2021 and June 2022 in Medline ALL and Embase. Fifty-two studies were included in this review. The many identities encapsulated in 2SLGBTQIA+ (2 Spirited, Lesbian, Gay, Bisexual, Transgender, Queer, Intersexual, Asexual, Agender, Aromantic and all gender identities and sexual orientations that are not listed) communities each have their own unique backgrounds, needs and disparities in cancer care and survivorship. However, we also identified specific protective factors in the cancer experience of SGD patients such as reports of higher resiliency and stronger support networks. Much of the recent research features recommendations on improving cancer care by creating inclusive patient questionnaires, improving in-person and online resources, and educating healthcare providers and patient-facing staff on inclusive care. SUMMARY: SGD patients have their own specific challenges during and following their cancer care. As the research continues to grow, we gain a better understanding of the needs of these patients and future steps to take to improve SGD patients' cancer experience.

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 categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.668
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0020.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.001
Research integrity0.0000.001
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 head0.387
GPT teacher head0.477
Teacher spread0.090 · 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.

Study designObservational
Domainnot available
GenreReview

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

Citations7
Published2023
Admission routes1
Has abstractyes

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