Health literacy (HL) is defined as the ability to access, understand, evaluate and apply health-related information, which can influence individuals’ health outcomes. Blue-collar workers, who often have lower educational attainment and experience language barriers, are at increased risk of limited HL. This systematic review aims to assess the prevalence of limited HL among blue-collar workers to inform the development of appropriate interventions for its improvement.

The systematic review will assess the prevalence of limited HL among blue-collar workers. We will include all quantitative study designs using any instrument for measuring general HL. We will exclude studies that focus on specific types of HL and specific health conditions. We have performed a literature search from inception up to 30 April 2025, in the Medline, Embase, CINAHL, Web of Science and Cochrane Central Register of Controlled Trials (CENTRAL) databases. We will also search eligible articles from Google Scholar and Open Grey as sources of unpublished studies/gray literature. Two independent reviewers will conduct the primary screening of articles, data extraction and quality assessment (using the Cochrane risk-of-bias tool for randomised trials and risk of bias in non-randomised studies of exposure), with a third individual available to resolve conflicts. We will assess heterogeneity using the ² test and I² test. If there is sufficient homogeneity, we will pool studies in a meta-analysis or summarise the findings narratively if heterogeneity is too high. We will use a random effects model for our analysis, and we will use funnel plots to evaluate potential publication bias. The Grading of Recommendations Assessment, Development and Evaluation approach will be used to assess the certainty of findings.

Ethical approval will not be required for this review as there is no primary data collection involving humans. The results will be published in a peer-reviewed journal and presented at relevant conferences.

CRD42024597732.

To construct a data-driven composite from (a subset of) currently used quality indicators for oesophagogastric cancer surgery and to evaluate whether this approach enhances the reliability of between-hospital comparisons on outcome relative to the expert-driven composite indicator ‘textbook outcome (TO)’.

In this retrospective cohort study, we applied Item Response Theory (IRT) to construct a data-driven continuous composite indicator reflecting a single latent variable—the quality of surgical care—and estimated latent variable scores for all individual patients. Reliability was compared between the expert-driven (TO) and data-driven (IRT) composite indicators.

All Dutch hospitals providing oesophagogastric cancer surgery.

All patients who underwent oesophagectomy (n=3588) or gastrectomy (n=1782) between 2018 and 2022 as registered in the Dutch Upper GI Cancer Audit (DUCA).

We evaluated the reliability of between-hospital comparisons using ‘rankability’, which quantifies the proportion of observed variation in indicator scores between hospitals not attributable to chance.

Seven out of 15 quality indicators were included in the IRT composite indicator. Most of the patients were assigned the artificial maximum of the continuous quality score (ie, ceiling effect), resulting in similar average hospital scores. Relative to TO, rankability increased when using the IRT composite for oesophagectomy (57% vs 41%) but declined for gastrectomy (38% vs 47%).

The selected seven quality indicators for oesophageal and gastric cancer surgery represent a single latent variable but are not yet optimal for differentiating surgical care quality due to ceiling effects. Despite using fewer indicators, the continuous IRT score showed a promising increase in rankability for oesophagectomy, suggesting that data-driven composite indicators may enhance hospital benchmarking reliability.