Posttraumatic growth in parents caring for a child with a life-limiting illness: A structural equation model.
Bibliographic record
Abstract
When parents first meet their child, they take on the entwined joys and burdens of caring for another person. Providing care for their child becomes the basic expectation, during health and illness, through the developmental milestones, into adulthood and beyond. For those parents who have a child who is born with or is later diagnosed with a life-limiting illness, parents also become caregivers in ways that parents of predominantly well children do not. While the circumstances are undisputedly stressful, for some parents benefits can co-occur along with the negative outcomes. This article tests two structural equation models of possible factors that allow these parent caregivers to experience growth in the circumstances. The diagnosis and illness of a child in the context of pediatric palliative care is a very complex experience for parents. The stresses are numerous and life-changing and yet the parents in this research demonstrated growth as measured by the Post Traumatic Growth Inventory. It appears that particular personal resources reflected in personal well-being are a precursor to the process of positive meaning making, which then, in turn, contributes to growth. The path to posttraumatic growth is not a simple one, but this research contributes to further elucidating it.
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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 | 0.007 | 0.011 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.005 | 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".