Adolescents' implicit and explicit attitudes toward their peers with genetic conditions
Bibliographic record
Abstract
INTRODUCTION: Previous research has demonstrated that children lacking knowledge about genetic disorders may have harmful attitudes toward people with disabilities, but disability awareness can successfully modify these attitudes. We explored adolescents' implicit and explicit attitudes toward peers with genetic conditions to determine whether improved genetics/genomics literacy can mitigate the impact of ableism in this population. METHODS: English-speaking adolescents (10-18 years) from British Columbia were invited to complete a Disability Attitudes Implicit Association Test (DA-IAT) and participate in a semi-structured focus group centering on a fictionalized vignette about an adolescent with Down syndrome. We used pragmatism as an analytical paradigm. Descriptive and inferential statistics were used to analyze DA-IAT and sociodemographic data; phronetic iterative analysis with constant comparison as a coding strategy for transcripts; and interpretive description to develop a conceptual model. RESULTS: Twenty-two adolescents completed the DA-IAT and participated in one of four focus groups. Participants had a statistically significant implicit preference for non-disabled people (D-score = 0.72, SD = 0.44; t = 7.18, p < .00001). They demonstrated greater diversity in their explicit attitudes during the focus groups. Although participants articulated a positive attitude toward improved genetics education, results demonstrate their belief that social and personal interactions with disabled peers would be essential to address negative perceptions. CONCLUSIONS: This study lays important groundwork to understand, explain, and influence the negative attitudes of adolescents toward individuals with disabilities. Findings will be used to inform the design of interventions that address biased perceptions of people with genetic disorders, with the goal of reducing prejudices and improving social interactions.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
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".