Waves of family hope: narratives of families in the context of pediatric chronic illness
Bibliographic record
Abstract
OBJECTIVE: to analyze narratives about the experience of hope of families in the context of pediatric chronic illness. METHOD: a narrative research using Family Systems Nursing as a conceptual framework. Three families of children and adolescents diagnosed with complex chronic illness participated in this study, totaling 10 participants. Data collection was developed using family photo-elicitation interviews. Family narratives were constructed and analyzed according to inductive thematic analysis with theoretical data triangulation. RESULTS: the analytical theme - Waves of Family Hope in the Context of Pediatric Chronic Illness - is composed of four different types of hope: uncertain hope, caring hope, latent hope, and expectant hope. Movement through these hopes generates a driving energy and depends on a number of factors: support, information, searching for normality, and thoughts and comparisons. CONCLUSION: the results highlight the interaction and reciprocities of the members of the family unit, and the dynamics of hope, and illustrate the different types of hope and the factors that influence them. This study highlights the experience of hope as a family resource rather than just an individual resource, and supports health professionals in the planning of family care considering hope as an essential and dynamic family resource.
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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 | 0.006 | 0.014 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.005 | 0.005 |
| Scholarly communication | 0.003 | 0.005 |
| Open science | 0.001 | 0.004 |
| 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".