Validity and Reliability of a Thai Version of Family Satisfaction with Care in the Intensive Care Unit Survey
Bibliographic record
Abstract
Purpose: To examine reliability and validity of a Thai version of the Family Satisfaction with Intensive Care Unit (FS-ICU 24) questionnaire and use this survey in intensive care units (ICUs) in Thailand. Materials and methods:The standard English FS-ICU questionnaire was translated into the Thai language using translation and culture adaptation guidelines.After reliability and validity testing, we consecutively surveyed the satisfaction of family members of ICU patients over 1 year.Adult family members of patients admitted to medical or surgical ICUs for 48 hours or more who had visited the patients at least once during the ICU stay were included.Results: In all, 315 (95%) of 332 surveys were returned from family members.Cronbach's α of the Thai FS-ICU 24 questionnaire was 0.95.Factor analysis demonstrated good construct validity.The mean (±SD) of total satisfaction score, overall ICU care subscale, and decision-making subscale were 81.5 ± 14.3, 81.0 ± 15.6, and 82.0 ± 14.0.Items with the lowest scores were the waiting room atmosphere and the frequency of doctors communicating with family members about the patient's condition.The mean total satisfaction score tended to be higher in family members of survivors than in family members of nonsurvivors (81.9 ± 13.8 vs 77.7 ± 16.2, p value = 0.059).The overall satisfaction scores between medial ICU vand surgical ICU were not significantly different. Conclusion:The Thai version of FS-ICU questionnaire was found to have acceptable reliability and validity in a Thai population and can be used to drive improvements in ICU care.Trial registration: www.clinicaltrials.in.th,TCR20160603002
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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 | 0.005 | 0.014 |
| 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 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| 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".