Children’s Psychological Responses After Critical Illness and Exposure to Invasive Technology
Bibliographic record
Abstract
Children hospitalized in pediatric intensive care units (PICUs) are subjected to highly invasive interventions necessary in overcoming the critical period of their illness, yet little is known about their subsequent psychological adjustment. The purposes of this study were to compare the psychological responses of children hospitalized in a PICU with those of children hospitalized on a general ward and to identify clinically relevant factors that might be associated with psychological outcome. A prospective cohort design was used to follow 120 children for 6 months after PICU and ward discharge. Groups were compared on the children's sense of control over their health, their medical fears, posttraumatic stress, and changes in behavior. Relationships between children's responses and their age, the invasive procedures to which they were exposed, severity of illness, and length of hospital stay were also examined. No significant group differences were found. However, children who were younger, more severely ill, and who endured more invasive procedures had significantly more medical fears, a lower sense of control over their health, and ongoing posttraumatic stress responses for 6 months postdischarge. Findings indicate that regardless of the hospital setting, invasiveness coupled with length of stay and severity of illness in young children may have adverse long-term effects.
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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 | 0.001 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".