Genetic counselors' research dissemination practices and attitudes
Bibliographic record
Abstract
Benefits have been demonstrated to disseminating aggregate research results to all relevant audiences, including study participants. Despite this, many health researchers face barriers in dissemination to broad audiences and returning aggregate results to participants is not commonly practiced. Due to their research presence and training in communication, genetic counselors can lead in implementing best practices in this area. We explored genetic counselors' current practices and opinions regarding educating study participants and wider audiences of research findings. We distributed a survey of 32 multiple-choice and open-ended questions to National Society of Genetics Counselors (NSGC) and Canadian Association of Genetic Counsellors (CAGC) members. Most respondents (90.1%, n = 128/142) identified with a responsibility to disseminate their research findings to a broad audience and identified several associated benefits. All respondents saw value in communicating aggregate results to study participants, although over half (53.2%, n = 66/124) had never done so. Genetic counselors reported resource and knowledge barriers to research dissemination. Despite expertise in education and communication, genetic counselors face similar barriers as other researchers toward broad dissemination of research. Formal training and professional guidelines specific to research dissemination practices will equip genetic counselors to reach broader audiences and maximize the impact of research findings.
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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 | 0.002 | 0.001 |
| 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".