Assessment of trends in socioeconomic inequalities in cancer screening services in Korea, 1998–2012
Bibliographic record
Abstract
BACKGROUND: This study aimed to examine how income-related inequalities in screening services for gastric and colorectal cancer in Korea have changed over the past decades, along with the implementation of the national cancer screening program, and also to quantify each contribution from various socio-demographic factors income-related inequalities with respect to these cancer screening services. METHODS: Three cycles (1998, 2005, and 2010-2012) of Korea National Health and Nutrition Examination Survey (KNHANES) were utilized. To measure income-related inequalities in the use of gastric and colorectal cancer, individuals over the age of 40 and the age of 50 were included respectively, and the Concentration Index (CI) was calculated for each cycle. To identify and quantify contribution from each socio-demographic factor, decomposition of the CIs was conducted. RESULTS: Throughout this study, CIs and horizontal inequity indices (HIs) steadily but consistently decreased, suggesting that inequalities and inequities in participation in gastric and colorectal cancer screening were weakened after the implementation of the national public cancer screening program. Decomposition analyses revealed that whereas decreases in inequalities mostly stemmed from income and educational levels; higher income and better education levels are still major contributors to the observed inequalities that influence participation in cancer screening services in Korea. CONCLUSION: Our empirical findings suggest that, although the policy of reducing out-of-pocket payment for cancer screening may contribute to the observed decreases in inequality, it alone is not likely to completely eliminate inequality. Further research is required to identify barriers that prevent people with lower socioeconomic status from participation in cancer screening, which allows equal access for equal need.
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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 | 0.002 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 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".