Postoperative pulmonary complications (PPCs) represent a significant cause of postoperative morbidity and even mortality. However, there is a lack of consensus regarding this composite endpoint, the definition of the individual components, classification and optimal outcome measures. This study aims to refine the PPCs composite framework by evaluating its construct validity, assessing the necessity and risks of a composite measure and exploring the feasibility of differentiating severity categories.

A Delphi consensus process will be conducted, engaging an international multidisciplinary group of 30–40 panellists, including clinicians, researchers, patients, public representatives and health economists. Through iterative rounds, the study will seek agreement on the individual components of the PPCs composite. Additionally, consensus will establish a framework for a composite outcome measure based on a standardised severity classification, appropriate timeframes and weighted grading of PPCs.

Consensus, defined by ≥75% concurrence in multiple choice questions or on Likert–scale statements, will be evaluated from round 2 onwards. Delphi rounds will be continued until all statements have reached stability of responses evaluated by ² tests or the Kruskal-Wallis test.

The study will be conducted in strict compliance with the principles of the Declaration of Helsinki and will adhere to ACCORD guidance for reporting. Ethics approval has been obtained for this study from the University of Wolverhampton, UK (SOABE/202425/staff/3). Informed consent will be obtained from all panellists before the commencement of the Delphi process. The results of the study will be published in a peer–reviewed journal with the authorship assigned in accordance with ICMJE requirements.

NCT06916598 (clinicaltrials.gov).

It is unclear how mis- and disinformation regarding healthcare policy changes propagate throughout Latino communities via social media. This may lead to chilling effects that dissuade eligible individuals from enrolling in critical safety net programmes such as Medicaid. This study will examine pathways and mechanisms by which sentiment in response to mis- and disinformation regarding healthcare policies on social media differentially impact health disparity populations, thus supporting the design of tailored social media interventions to mitigate this.

We will search social media from X/Twitter, Facebook/Instagram and Reddit for keywords relating to health benefit programmes. Demographic, geographical location and other characteristics of users will be used to stratify social media data. Posts will be classified as fake-news-related or fact-related based on curated lists of fake-news-related websites. The number, temporal dissemination and positive or negative sentiment in reacting to posts and threads will be examined using the Python-based Valence Aware Dictionary and sEntiment Reasoner (VADER). Using a crowd-sourcing methodology, a novel Spanish-language VADER (S-VADER) will be created to rate sentiment to social media among Spanish-speaking Latinos. With the proposed approach, we will explore reactions to the dissemination of fake-news- or fact-related social media tweets and posts and their sources. Analyses of social media posts in response to healthcare-related policies will provide insights into fears faced by Latinos and Spanish speakers, as well as positive or negative perceptions relating to the policy over time among social media users.

Our study protocol was approved by the University of California, Los Angeles IRB (IRB#23–0 01 123). Results from this study will be disseminated in peer-reviewed journals and conference presentations, and S-VADER will be disseminated to public repositories such as GitHub.