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To describe educational interventions that have been implemented in healthcare settings to increase the compliance of healthcare personnel (HCP) with cleaning and disinfection of noncritical portable medical equipment (PME) requiring low-level disinfection (LLD). Systematic review. Studies evaluating interventions for improving LLD practices in settings with HCP, including healthcare students and trainees, were eligible for inclusion. In total, 1,493 abstracts were identified and 1,416 were excluded, resulting in 77 studies that underwent full text review. Among these, 68 were further excluded due to study design, setting, or intervention. Finally, 9 full-text studies were extracted; 1 study was excluded during the critical appraisal process, leaving 8 studies. Various forms of interventions were implemented in the studies, including luminescence, surveillance of contamination with feedback, visual signage, enhanced training, and improved accessibility of LLD supplies. Of the 8 included studies, 4 studies reported successes in improving LLD practices among HCP. The available literature was limited, indicating the need for additional research on pedagogical methods to improve LLD practices. Use of visual indicators of contamination and multifaceted interventions improved LLD practice by HCP.

IntroductionTuberculosis (TB) is significantly associated with multiple postinfectious, non-communicable diseases after microbiological cure. For example, those with a history of TB disease have a higher risk of developing chronic lung diseases at a younger age. However, the extent and nature of post-TB complications are not well described. Here, we present a protocol for a systematic review and meta-analysis, which aims to synthesise literature on the burden of post-TB lung disease (PTLD) in sub-Saharan Africa, describe phenotypes, long-term outcomes and the health-related quality of life of people with PTLD.Methods and analysisA systematic search will be conducted using PubMed, EMBASE, Web of Science, African Journals Online and the Cochrane Library of Systematic Reviews. Papers published in English and French languages that report the prevalence, clinical features, quality of life and long-term outcomes of people with PTLD in sub-Saharan Africa will be considered. We will assess and critically appraise the methodological quality of all studies using the modified covidence. Qualitative and quantitative (network and meta-analysis) synthesis will be performed and STATA V.16 will be used to estimate the burden of PTLD.Ethics and disseminationEthical approval is not required for this systematic review and meta-analysis. Our results will be published in peer-reviewed journals.PROSPERO registration numberCRD42021274018.

IntroductionInfants can experience pain similar to adults, and improperly controlled pain stimuli could have a long-term adverse impact on their cognitive and neurological function development. The biggest challenge of achieving good infant pain control is obtaining objective pain assessment when direct communication is lacking. For years, computer scientists have developed many different facial expression-centred machine learning (ML) methods for automatic infant pain assessment. Many of these ML algorithms showed rather satisfactory performance and have demonstrated good potential to be further enhanced for implementation in real-world clinical settings. To date, there is no prior research that has systematically summarised and compared the performance of these ML algorithms. Our proposed meta-analysis will provide the first comprehensive evidence on this topic to guide further ML algorithm development and clinical implementation.Methods and analysisWe will search four major public electronic medical and computer science databases including Web of Science, PubMed, Embase and IEEE Xplore Digital Library from January 2008 to present. All the articles will be imported into the Covidence platform for study eligibility screening and inclusion. Study-level extracted data will be stored in the Systematic Review Data Repository online platform. The primary outcome will be the prediction accuracy of the ML model. The secondary outcomes will be model utility measures including generalisability, interpretability and computational efficiency. All extracted outcome data will be imported into RevMan V.5.2.1 software and R V3.3.2 for analysis. Risk of bias will be summarised using the latest Prediction Model Study Risk of Bias Assessment Tool.Ethics and disseminationThis systematic review and meta-analysis will only use study-level data from public databases, thus formal ethical approval is not required. The results will be disseminated in the form of an official publication in a peer-reviewed journal and/or presentation at relevant conferences.PROSPERO registration numberCRD42019118784.

Shannon D. Jones, AHIP, and Beverly Murphy, AHIP, FMLA, have teamed up to serve as editors of Diversity and Inclusion in Libraries: A Call to Action and Strategies for Success, a timely, much needed book with chapters written by thirty different contributors.