Psychometric testing of the Family Satisfaction with Decision Making subscale (FS-ICU/DM) in an acute care pediatric hospital setting
Bibliographic record
Abstract
Aim. This paper is a report of the psychometric testing of the Family Satisfaction with Decision Making subscale of the Family Satisfaction with Care in the Intensive Care Unit questionnaire to determine whether it would be suitable to use as a primary outcome measure in a proposed randomized control trial in a pediatric hospital setting.Background. Parents have reported that relinquishing important aspects of their role is the most stressful element of a child’s hospitalization. Concerns over communication and decision-making processes have been particularly cited. Therefore, increasing parents’ satisfaction with their child’s care and responding to their priorities are key to improving quality of care. Instruments have been developed to measure global satisfaction with care among parents of hospitalized children. However none of these focus specifically on communication and decision-making processes. One instrument was found that measures these items, but in an adult intensive care unit, not a pediatric setting.Design/method. As a component of a larger study, a psychometric study was conducted in 2010 to assess the properties of the Family Satisfaction with Decision Making subscale in a pediatric setting. Eighty-two parents of children admitted to a large metropolitan pediatric hospital completed the subscale prior to their child’s transfer and/or discharge from the hospital.Results/Conclusion. The psychometric data indicated that the Family Satisfaction with Decision Making subscale showed evidence of good reliability and validity as a primary outcome measure that could be used for a future randomized controlled trial in a pediatric setting.
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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 | 0.015 | 0.022 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 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) | 0.002 | 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".