Objectives As the pathophysiology of COVID-19 emerges, this paper describes dysphagia as a sequela of the disease, including its diagnosis and management, hypothesised causes, symptomatology in relation to viral progression, and concurrent variables such as intubation, tracheostomy and delirium, at a tertiary UK hospital. Results During the first wave of the COVID-19 pandemic, 208 out of 736 patients (28.9 per cent) admitted to our institution with SARS-CoV-2 were referred for swallow assessment. Of the 208 patients, 102 were admitted to the intensive treatment unit for mechanical ventilation support, of which 82 were tracheostomised. The majority of patients regained near normal swallow function prior to discharge, regardless of intubation duration or tracheostomy status. Conclusion Dysphagia is prevalent in patients admitted either to the intensive treatment unit or the ward with COVID-19 related respiratory issues. This paper describes the crucial role of intensive swallow rehabilitation to manage dysphagia associated with this disease, including therapeutic respiratory weaning for those with a tracheostomy.

Validity of measurement is integral to the interpretability of research endeavours and any subsequent replication attempts. To assess current measurement practices and the construct validity of measures in large-scale replication studies, we conducted a systematic review of measures used in Many Labs 2: Investigating Variation in Replicability Across Samples and Settings (Klein et al., 2018). To evaluate the psychometric properties of the scales used in Many Labs 2 we conducted factor and reliability analyses on the publicly-available data. We report that measures in Many Labs 2 were often short with little validity evidence reported in the original study, that measures with more validity evidence in the original study had stronger psychometric properties in the replication sample, and that translated versions of scales had lower reliability. We discuss the implications of these findings for interpreting replication results, and make recommendations to improve measurement practices in future replications.

The documentation for v 0.1.0 of r2mlm, an R package that calculates both total- and level-specific R-squared measures fromRights and Sterba’s (2019) framework of R-squaredmeasures for multilevelmodels with random intercepts and/or slopes.

Malawi has the second highest age-standardised incidence rate and the highest mortality rate of cervical cancer in the world. Though the prevalence of HIV is currently 11.7% for Malawian women of reproductive age, cervical cancer screening rates remain low. To address this issue, we integrated cervical cancer screening into a dual HIV and non-communicable disease clinic at a rural district hospital in Neno, Malawi. The project was implemented between January 2017 and March 2018 using the Plan-Do-Study-Act model of quality improvement (QI). At baseline (January to December 2016), only 13 women living with HIV were screened for cervical cancer. One year after implementation of the QI project, 73% (n=547) of women aged 25 to 49 years living with HIV enrolled in HIV care were screened for cervical cancer, with 85.3% of these receiving the screening test for the first time. The number of women living with HIV accessing cervical cancer services increased almost 10 times (from four per month to 39 per month, p<0.001). Key enablers in our QI process included: strong mentorship, regular provision of cervical cancer health talks throughout the hospital, nationally accredited cervical cancer prevention training for all providers, consistent community engagement, continuous monitoring and evaluation, and direct provision of resources to strengthen gaps in the public system. This practical experience integrating cervical cancer screening into routine HIV care may provide valuable lessons for scale-up in rural Malawi.

Because of the misspecification of models and specificity of operationalizations, many studies produce claims of limited utility. We suggest a path forward that requires taking a few steps back. Researchers can retool large-scale replications to conduct the descriptive research which assesses the generalizability of constructs. Large-scale construct validation is feasible and a necessary next step in addressing the generalizability crisis.