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Record W2770865335 · doi:10.1007/s10897-017-0174-8

“Where Does it Come from?” Experiences Among Survivors and Parents of Children with Retinoblastoma in Kenya

2017· article· en· W2770865335 on OpenAlexaff
Amal Gedleh, Siwon Lee, Jessica A. Hill, Yvonne Umukunda, Joy Kabiru, Kahaki Kimani, Lucy Njambi, Grace Kitonyi, Helen Dimaras

Bibliographic record

VenueJournal of Genetic Counseling · 2017
Typearticle
Languageen
FieldMedicine
TopicOcular Oncology and Treatments
Canadian institutionsCentre for Global Health ResearchHospital for Sick ChildrenPublic Health OntarioUniversity of Toronto
Fundersnot available
KeywordsRetinoblastomaGenetic counselingFocus groupCLARITYMedicineThematic analysisQualitative researchFamily medicinePediatricsGeneticsSociologySocial scienceBiology

Abstract

fetched live from OpenAlex

Genetic testing and counseling have become integral to the timely control of heritable cancers, like the childhood eye cancer retinoblastoma. This study aimed to determine attitudes, knowledge and experiences related to retinoblastoma genetics, among survivors and parents of children with retinoblastoma in Kenya. This qualitative study used focus groups as the primary data collection method, coupled with a brief demographic questionnaire. Study settings were Kenyatta National Hospital and Presbyterian Church of East Africa Kikuyu Hospital. Thematic analysis was used to identify key themes. Thirty-one individuals participated in five focus groups. Two main concepts emerged: (1) the origins of retinoblastoma are unclear, and (2) retinoblastoma is associated with significant challenges. The lack of clarity surrounding the origins of retinoblastoma was linked to limited knowledge of retinoblastoma genetics, and limited genetic counseling delivery and uptake. The challenges associated with retinoblastoma were discussed in terms of the impact of the diagnosis on individuals and families, and unmet healthcare needs related to the diagnosis. Next steps will incorporate these findings to develop evidence-informed and accessible cancer genetic services in Kenya.

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: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.002
Threshold uncertainty score0.191

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 studies0.0000.000
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 head0.008
GPT teacher head0.265
Teacher spread0.257 · 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

Citations25
Published2017
Admission routes1
Has abstractyes

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