Swedish Version of the Distress Thermometer: Validity Evidence in Patients With Colorectal Cancer
Bibliographic record
Abstract
Background: The objective of this study was to validate the NCCN Distress Thermometer (DT), including the accompanying Problem List (PL), in a Swedish population of patients diagnosed with colorectal cancer (CRC). Methods: A total of 488 patients diagnosed with CRC completed the DT/PL and EORTC core quality-of-life questionnaire (QLQ-C30) before surgery. Construct validity of the PL was analyzed using a confirmatory factor analysis. Internal consistency reliability (ICR) was tested using Cronbach's alpha coefficient. Correlations between the reported PL areas and QLQ-C30 function scales were used to explore convergent validity. Discriminant validity was examined by evaluating associations between the DT and QLQ-C30 measures of overall health-related quality of life (HRQoL). Results: Findings showed that the Swedish translation of the DT/PL is consistent with the original English version. The DT has good ICR, with the total number of reported problems significantly correlating with DT scores (r=0.67; P<.001). Analysis of convergent validity indicated that the PL areas significantly correlated with QLQ-C30 function scales, with emotional problems showing the highest correlation (r=0.76; P<.001), and item-level correlation analyses showed significant correlations between symptoms. There was also good discriminant validity between the DT and the QLQ-C30 in terms of HRQoL, including overall health status (r=−0.49; P<.001) and overall quality of life (r=−0.57; P<.001). Furthermore, there was good discriminant validity between the DT and QLQ-C30 regarding poor, moderate, and excellent HRQoL. Conclusions: These findings provide validity evidence regarding the DT, including the PL. Findings also show that the DT has good potential for screening distress-related practical, family, emotional, and physical problems during the cancer trajectory in Swedish-speaking patients. Additionally, the DT seems to be an effective screening tool to detect patients with poor, moderate, and excellent HRQoL.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.020 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.000 |
| 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".