Validation of the psychosocial consequences of screening in lung cancer questionnaire in the international lung screen trial Australian cohort
Bibliographic record
Abstract
Abstract Background Evaluation of psychosocial consequences of lung cancer screening with LDCT in high-risk populations has generally been performed using generic psychometric instruments. Such generic instruments have low coverage and low power to detect screening impacts. This study aims to validate an established lung cancer screening-specific questionnaire, Consequences Of Screening Lung Cancer (COS-LC), in Australian-English and describe early results from the baseline LDCT round of the International Lung Screen Trial (ILST). Methods The Danish-version COS-LC was translated to Australian-English using the double panel method and field tested in Australian-ILST participants to examine content validity. A random sample of 200 participants were used to assess construct validity using Rasch item response theory models. Reliability was assessed using classical test theory. The COS-LC was administered to ILST participants at prespecified timepoints including at enrolment, dependent of screening results. Results Minor linguistic alterations were made after initial translation of COS-LC to English. The COS-LC demonstrated good content validity and adequate construct validity using psychometric analysis. The four core scales fit the Rasch model, with only minor issues in five non-core scales which resolved with modification. 1129 Australian-ILST participants were included in the analysis, with minimal psychosocial impact observed shortly after baseline LDCT results. Conclusion COS-LC is the first lung cancer screening-specific questionnaire to be validated in Australia and has demonstrated excellent psychometric properties. Early results did not demonstrate significant psychosocial impacts of screening. Longer-term follow-up is awaited and will be particularly pertinent given the announcement of an Australian National Lung Cancer Screening Program. Trial registration NCT02871856.
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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 | 0.001 | 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 | 0.001 |
| 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 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".