Family Resilience as an Emerging Concept in Neonatology
Bibliographic record
Abstract
BACKGROUND: Family resilience can be observed through specific resilience-promoting processes, namely, shared belief systems, communication, and organizational processes, but the concept remains mostly unstudied in neonatology. This metasummary aims to evaluate the frequency of family resilience processes in qualitative scientific literature to illustrate how family resilience is exhibited in the neonatal intensive care unit (NICU) setting. METHODS: A search among 4 databases yielded 7029 results, which were reviewed for inclusion. Following Sandelowski and Barroso's qualitative metasummary method, findings from each study were independently coded and frequency effect size was calculated. RESULTS: Forty-six primary qualitative studies published between 2016 and 2022 conducted with parents of preterm infants who discussed their NICU hospitalization experience were included in this metasummary. All 9 of Walsh's family resilience processes were identified in the literature, and their frequency effect size ranged from 4% to 91%. Four additional themes emerged pertaining to specific family resilience behaviors exhibited by NICU families. CONCLUSION: This analysis sheds new light on the most recent qualitative evidence of parents' experiences in the NICU by analyzing it through the lens of family resilience and posits family resilience as a promising concept in relation to the predominance of the family-centered care philosophy in neonatal units.
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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 | 0.037 | 0.054 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.003 |
| Bibliometrics | 0.009 | 0.006 |
| Science and technology studies | 0.001 | 0.004 |
| Scholarly communication | 0.004 | 0.005 |
| Open science | 0.001 | 0.003 |
| 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".