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Record W4408532001 · doi:10.1016/j.gimo.2025.102457

P609: Mainstreaming genetics: Evaluation of a digital application to scale and spread oncologist-initiated genetic testing

2025· article· en· W4408532001 on OpenAlexaff
Daniel Assamad, Marc Clausen, Rita Kodida, Kathleen Bell, Andrea Eisen, Christine Elser, Adena Scheer, Emily Seto, Kevin E. Thorpe, Seema Panchal, Yvonne Bombard

Bibliographic record

VenueGenetics in Medicine Open · 2025
Typearticle
Languageen
FieldEngineering
TopicBiomedical and Engineering Education
Canadian institutionsHospital for Sick ChildrenSickKids FoundationUniversity Health NetworkUniversity of TorontoSunnybrook Health Science CentreSinai Health SystemHealth Sciences CentreMount Sinai HospitalSt. Michael's Hospital
Fundersnot available
KeywordsScale (ratio)MainstreamingMedical physicsMedical geneticsGenetic testingMedicineGeneticsOncologyComputational biologyInternal medicineComputer scienceBiologyPsychologyGeographyMathematics educationCartographyGeneSpecial education

Abstract

fetched live from OpenAlex

Introduction: Reproductive carrier screening, which initially targeted ethic-specific genetic conditions, is now recommended for all populations.Despite technological capacity for expansive screening, in Singapore only thalassemia is routinely offered.Genetic condition severity and prevalence are main considerations in gene panel development, yet carrier screening uptake can be influenced by other factors such as lived experience and available support services.As most exploratory studies have been conducted in healthcare settings with European-derived populations, further research is required regarding participation and barriers amongst diverse populations to understand acceptability and impact.We explored the attitudes and preferences towards the implementation of carrier screening in Singapore, a population comprising of Chinese, Indian and Malay, by engaging with community members, healthcare professionals and religious leaders.Methods: As an initial scoping exercise, individuals of reproductive age attending outpatient appointments at a tertiary hospital in Singapore were invited to complete a questionnaire regarding their preferences towards carrier screening participation and genetic conditions to be screened.In parallel, the views and attitudes from healthcare professionals working in genetics or obstetric departments regarding carrier screening implementation were also collated by questionnaire.To increase awareness, religious leaders representing Islam, Buddhism, Christianity, Hinduism, and Judaism were also engaged.Results: To date, 296 community members have responded, with the majority of participants aged 25 to 44 years (range 18-54 years) and 57% identifying as female.Although most had not previously undergone reproductive carrier screening, 94% expressed interest in learning their carrier status.Concerns over potential insurance implications and increased medical appointments were the most common reasons for declining carrier testing.A large proportion of respondents (85%) indicated they would consider further testing if found to be at increased risk of having a child with a genetic condition, while 48% reported they may consider not having children.In addition to severe conditions, most respondents supported testing for late onset or mild genetic conditions.Among the 94 healthcare professional respondents, most acknowledged carrier screening will be routinely incorporated into clinical practice yet only half felt comfortable offering testing to patients.All religious leaders were supportive of carrier screening being offered to prospective parents.Conclusion: Overall, this preliminary data suggests that there is support for the expansion of carrier screening in Singapore from the perspectives of the community, healthcare providers and religious leaders.The responses also highlight key areas for educational initiatives and as well as insights into which genetic conditions to be considered for screening.These findings will help inform the design and implementation of a carrier screening program which is tailored, accessible and equitable for the Singaporean population.

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)0.001
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: Other design · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.895
Threshold uncertainty score0.471

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
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 head0.057
GPT teacher head0.346
Teacher spread0.289 · 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 designOther design
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".

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Citations0
Published2025
Admission routes1
Has abstractyes

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