Gratitude, fragility and strength: Perspectives of adults born preterm about prematurity
Bibliographic record
Abstract
AIM: The aim of the study was to explore how young adults thought that being born preterm had affected their lives. METHODS: Adult participants of a research cohort were questioned about their perspectives. Answers were analysed using mixed methods. RESULTS: Forty-five participants evaluated their health at median score of 8/10. When asked about the meaning of being born preterm, 65% had positive self-centred answers, invoking two main themes: being stronger/'a fighter'/more resilient and being a survivor/chosen; 42% also reported negative themes, such as having health problems and a difficult start. All heard about their prematurity from their parents, 55% with positive child-centred or healthcare system-centred themes, 19% with neutral themes; 35% also heard negative parent-centred themes (tragic experience, guilt, mother's health). When asked which words were associated with prematurity, participants mainly chose positive words for themselves and their family, but more negative words for how the media and society depicted prematurity. Answers were not correlated with adverse objective health measures. CONCLUSION: Participants evaluated their health in a balanced fashion. Preterm-born adults often feel that they have experienced positive transformations as a result of their traumatic start. They often have feelings of gratitude and strength, independent of health problems.
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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 | 0.007 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.002 | 0.002 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.000 | 0.002 |
| Research integrity | 0.001 | 0.002 |
| 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".