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Record W4413750133 · doi:10.1177/00469580251366872

Attitudes of Parents With a Child With Autosomal Recessive Disease Toward Consanguinity

2025· article· en· W4413750133 on OpenAlexaff
Yagoub Yousif Al‐Kandari, Shaker Bahzad, Dina Ramadan, Hind Alsharhan, Mohammad Akhtar Hussain, Waleed Al–Herz

Bibliographic record

VenueINQUIRY The Journal of Health Care Organization Provision and Financing · 2025
Typearticle
Languageen
FieldHealth Professions
TopicAdolescent and Pediatric Healthcare
Canadian institutionsUniversité du Québec
Fundersnot available
KeywordsConsanguinityDiseaseGeneticsPediatricsDevelopmental psychologyMedicinePsychologyBiologyPathology

Abstract

fetched live from OpenAlex

Consanguineous marriages are known to increase the risk of autosomal recessive genetic disorder. In this study we aimed to examine the perspective and attitudes of parents with 1 or more affected children by an AR disease toward consanguineous marriages. A total of 285 parents completed a self-administered survey. The participants belonged to 2 groups: a clinical sample defined as consanguineous parents with at least 1 child affected by an AR genetic disease, while the community sample were non-consanguineous parents. The questionnaire was about the subjects’ attitudes toward consanguinity and was divided into 2 parts: sociocultural and health attitudes. The clinical sample showed positive sociocultural views toward consanguineous marriages compared to the community sample as they had statistically significant differences regarding the belief it decreases divorce, general support of consanguinity in general and more specifically encouragement of their children to marry a relative. Regarding health attitudes, statistically significant differences were found between the 2 groups in 6 out of 7 examined variables. Despite the well-known associated reproductive and genetic risks of consanguinity, consanguineous subjects continue to support and positively view such marriages.

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)0.001
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 score0.036
Threshold uncertainty score0.801

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0010.000
Scholarly communication0.0000.000
Open science0.0000.000
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 head0.031
GPT teacher head0.378
Teacher spread0.347 · 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

Citations0
Published2025
Admission routes1
Has abstractyes

Explore more

Same venueINQUIRY The Journal of Health Care Organization Provision and FinancingSame topicAdolescent and Pediatric HealthcareFrench-language works237,207