Structured Interview Assessment of Symptoms and Concerns in Palliative Care
Bibliographic record
Abstract
OBJECTIVE: Assessment in palliative care requires a multidimensional review of physical symptoms and psychosocial concerns in a format appropriate for patients with advanced illness. In this study, we describe the initial development and validation of a structured interview for assessing common symptoms and concerns faced by terminally ill individuals. METHOD: We constructed a 13-item Structured Interview for Symptoms and Concerns (SISC) based on a review of end-of-life issues and administered it to 69 patients receiving palliative care for advanced cancer. Along with the interview, each participant completed visual analog scales (VAS) addressing the same constructs. Test-retest and interrater reliability were determined, as was the concordance between interview ratings and VAS scores. RESULTS: Overall, the interview items had excellent interrater reliability (intraclass correlations were > 0.90) and at least moderate temporal stability (test-retest correlations ranged from 0.50 to 0.90). Concurrent validity was evident in the good concordance between interview items and VAS measures (correlations were > 0.70). The SISC was also sensitive to individual differences between subgroups of participants who did or did not meet diagnostic criteria for anxiety or depressive disorders. CONCLUSIONS: This study demonstrates that structured interviews provide a reliable and valid approach to assessment in palliative care and may be an appropriate alternative for some research applications.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".