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Record W4412697615 · doi:10.1177/10732748251364041

Supporting Participant Engagement in Cancer Genomics Research in Rare Cancers: A Qualitative Study of Patients, Caregivers, and Advocates

2025· article· en· W4412697615 on OpenAlex
Vinayak Venkataraman, Lauren Fisher, Andrew Khalaj, Eirian Siegal-Botti, Diane M. Diehl, Katherine A. Janeway, Suzanne George, Jennifer W. Mack

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

aboutThe title or abstract carries a Canadian signal from the geographic lexicon.
no affNo Canadian affiliation: this work is invisible to an affiliation-only frame.
No Canadian affiliation. An affiliation-only frame, the usual design, would never have seen this work. It is one of the works that make the case for inverting the frame.

Bibliographic record

VenueCancer Control · 2025
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicBRCA gene mutations in cancer
Canadian institutionsnot available
FundersNational Cancer InstituteNational Institutes of Health
KeywordsMedicineAcknowledgementConfidentialityQualitative researchEmpowermentInclusion (mineral)Medical educationTransparency (behavior)NursingPsychologySocial psychology

Abstract

fetched live from OpenAlex

IntroductionThe purpose of this study was to identify patterns and themes that support participant engagement in patient-partnered cancer genomics research.MethodsThe Osteosarcoma (OS) and Leiomyosarcoma (LMS) Projects of Count Me In allow any patient with OS and LMS in the US and Canada to contribute their health information, tumor samples, and lived experience to an aggregated, public research database. We conducted in-depth interviews with research partners, including patients, caregivers, and advocates, who were purposefully sampled to ensure inclusion of racial and ethnic minorities, those with less than college education, and adolescents (age 12-17). Coding and analysis were conducted by the research team using NVivo to identify themes that support engagement.ResultsTen patients, ten caregivers, and six advocates were interviewed. Seven themes were identified that support participant engagement: (a) motivation, (b) respect, (c) trust, (d) inclusivity, (e) relationship, (f) engagement, and (g) empowerment. Research partners were motivated to serve others, play a part in scientific discovery, and play a role in a novel initiative. Respect was supported through timeliness in communication or follow-up, an appropriate amount of time and information requested, and an acknowledgement that illness may prevent participation. Trust was developed through ensuring adequate privacy/confidentiality safeguards and demonstrating transparency. Inclusivity was demonstrated through showcasing broad representation and mitigating technical barriers. Research partners wanted to feel a relationship with, and engaged and empowered by, researchers. Adolescents reported their parents were more engaged than they were.ConclusionsResearch partners, including patients, caregivers, and advocates, have a strong desire to engage with researchers. We identified seven themes to support engagement. Researchers can optimize their communication and operations to support participant engagement in cancer genomics research.

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.

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)0.001
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: Qualitative · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.513
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
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 head0.078
GPT teacher head0.447
Teacher spread0.369 · 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