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Record W4296335335 · doi:10.1002/jgc4.1636

The experiences of adolescent siblings of children with rare genetic conditions: “It's made me who I am”

2022· article· en· W4296335335 on OpenAlexaff
Julia Heaton, Tasha Wainstein

Bibliographic record

VenueJournal of Genetic Counseling · 2022
Typearticle
Languageen
FieldPsychology
TopicFamily and Disability Support Research
Canadian institutionsBC Children's HospitalWomen's Health Research InstituteUniversity of British Columbia
Fundersnot available
KeywordsSiblingGenetic counselingDevelopmental psychologyPsychologyPopulationPublic healthMedicineClinical psychologyGeneticsNursingEnvironmental health

Abstract

fetched live from OpenAlex

Childhood genetic conditions impact not only the child who is diagnosed but also the day-to-day lives of all members of a family. However, our understanding of the perspectives and needs of unaffected adolescents in families affected by rare genetic conditions is limited. To address this gap, we conducted semi-structured interviews with 10 participants aged 14-20 years, all of whom had a sibling with a rare genetic condition. An interpretive description approach was used to develop a framework that described how participants' experiences of having a sibling with a rare genetic condition shaped the formation of their identity. This experience influenced identity formation both directly, and indirectly through four other phenomena: (1) normalization, of both their own experiences and their siblings' differences; (2) knowledge seeking, regarding their sibling's condition and what uncertainties remained; (3) caretaking, which limited some opportunities and was associated with uncertainty around the future; and (4) social experience, including their relationship with their affected sibling, with their peers, and with the rest of their family participants felt that they were isolated and lacked appropriate supports. The results of this study can help to inform a family-centered approach to genetic counseling and highlight the importance of tailored supports for this 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 categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.269
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 science0.0010.000
Research integrity0.0000.000
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 head0.022
GPT teacher head0.317
Teacher spread0.295 · 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
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 routes1
Has abstractyes

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