Pilot study for the Psychometric Validation of the Sheffield Profile for Assessment and Referral to Care (SPARC) in Korean Cancer Patients
Bibliographic record
Abstract
PURPOSE: This study aimed to validate the Sheffield Profile for Assessment and Referral to Care (SPARC) as an effective tool for screening palliative care needs among Korean cancer patients. MATERIALS AND METHODS: The English version of the SPARC was translated by four Korean oncologists and reconciled by a Korean language specialist and a medical oncologist fluent in English. After the first version of the Korean SPARC (K-SPARC) was developed, back-translation into English was performed by a professional translator and bilingual oncologist. The back-translated version was reviewed by the original author (S.H.A.), and modifications were made (ver. 2). The second version of the K-SPARC was tested against other questionnaires, including the Functional Assessment of Cancer Therapy-General (FACT-G) and the Edmonton Symptom Assessment System (ESAS). RESULTS: Thirty patients were enrolled in the pilot trial. Fifteen were male, and the median age was 64.5 years. Six patients had an Eastern Cooperative Oncology Group performance status of 2 or more. All patients except one were receiving chemotherapy. Regarding internal consistency, the Cronbach's α scores for physical symptoms, psychological issues, religious and spiritual issues, independency and activity, family and social issues, and treatment issues were 0.812, 0.804, 0.589, 0.843, 0.754, and 0.822, respectively. The correlation coefficients between the SPARC and FACT-G were 0.479 (p=0.007) for the physical domain and -0.130 (p=0.493) for the social domain. CONCLUSION: This pilot study indicates that the K-SPARC could be a reliable tool to screen for palliative care needs among Korean cancer patients. A further study to validate our findings is ongoing.
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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".