Psychometric properties of Integrated Palliative Outcome Scale: Czech standardization and validation
Bibliographic record
Abstract
Abstract Background Outcome measurement is an essential part of the evaluation of palliative care and the measurements need to be reliable, valid and adapted to the culture in which they are used. The Integrated Palliative Outcome Scale (IPOS) is a widely used tool for assessing outcomes in palliative care. The aim of this study was to provide Czech version of IPOS and asses its psychometric properties.Methods Patients receiving palliative care in hospice or hospitals completed IPOS and part of the sample also completed Edmonton Symptom Assessment System (ESAS) and Palliative Performance Scale (PPS). The reliability of Czech IPOS was tested with Cronbach alpha (internal consistency) and Intraclass correlation coefficient and Weighted Kappa (test-retest reliability). Construct validity was assessed with factor analysis (Exploratory Factor Analysis) and convergent validity was tested with correlation analysis (Spearman correlation).Results Sample consisted of 140 patients (mean age 72; 90 women; 81% oncologic disease). IPOS internal consistency was 0.789; ICC= 0.88. To study convergent validity, we assessed the correlations of IPOS with ESAS (R= 0.4) and PPS (R= -0.2), however, these results have to be considered preliminary due to the small sample size. Exploratory factor analysis revealed a 2-factor solution on our data. The first factor covers emotional and information needs and the second factor covers physical symptoms.Conclusion Czech IPOS has very good reliability regarding both internal consistency and test-retest reliability. Together with an item analysis results, we can conclude that the Czech adaptation of the tool was successful. The convergent validity needs to be assessed on the larger sample and the proposed 2-factor internal structure of the questionnaire has to be confirmed by using CFA.
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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 | 0.011 | 0.029 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".