The Feelings About genomiC Testing Results (FACToR) Questionnaire: Development and Preliminary Validation
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
The purpose of this study was to develop a brief instrument, the Feelings About genomiC Testing Results (FACToR), to measure the psychosocial impact of returning genomic findings to patients in research and clinical practice. To create the FACToR, we modified and augmented the Multidimensional Impact of Cancer Risk Assessment (MICRA) questionnaire based on findings from a literature review, two focus groups (N = 12), and cognitive interviews (N = 6). We evaluated data from 122 participants referred for evaluation for inherited colorectal cancer or polyposis from the New EXome Technology in (NEXT) Medicine Study, an RCT of exome sequencing versus usual care. We assessed floor and ceiling effects of each item, conducted principal component analysis to identify subscales, and evaluated each subscale's internal consistency, test-retest reliability, and construct validity. After excluding items that were ambiguous or demonstrated floor or ceiling effects, 12 items forming four distinct subscales were retained for further analysis: negative emotions, positive feelings, uncertainty, and privacy concerns. All four showed good internal consistency (0.66-0.78) and test-retest reliability (0.65-0.91). The positive feelings and the uncertainty subscales demonstrated known-group validity. The 12-item FACToR with four subscales shows promising psychometric properties on preliminary evaluation in a limited sample and needs to be evaluated in other populations.
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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 | 0.001 | 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 it