Parent Experience With False-Positive Newborn Screening Results for Cystic Fibrosis
Bibliographic record
Abstract
BACKGROUND: The risk of psychosocial harm in families of infants with false-positive (FP) newborn bloodspot screening (NBS) results for cystic fibrosis (CF) is a longstanding concern. Whether well designed retrieval and confirmatory testing systems can mitigate risks remains unknown. METHODS: Using a mixed-methods cohort design, we obtained prospective self-report data from mothers of infants with FP CF NBS results 2 to 3 months after confirmatory testing at Ontario's largest follow-up center, and from a randomly selected control sample of mothers of screen negative infants from the same region. Mothers completed a questionnaire assessing experience and psychosocial response. A sample of mothers of FP infants completed qualitative interviews. RESULTS: One hundred thirty-four mothers of FP infants (response rate, 55%) and 411 controls (response rate, 47%) completed questionnaires; 54 mothers of FP infants were interviewed. Selected psychosocial response measures did not detect psychosocial distress in newborns or 1 year later (P > .05). Mothers recalled distress during notification of the positive result and in the follow-up testing period related to fear of chronic illness, but valued the screening system of care in mitigating concerns. CONCLUSIONS: Although immediate distress was reported among mothers of FP infants, selected psychometric tools did not detect these concerns. The NBS center from which mothers were recruited minimizes delay between notification and confirmatory testing and ensures trained professionals are communicating results and facilitating follow-up. These factors may explain the presence of minimal psychosocial burden. The screening system reflected herein may be a model for NBS programs working to minimize FP-related psychosocial harm.
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 machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.003 | 0.019 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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 source (direct Gemma or distilled Codex), 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".