IntroductionSecondhand smoke exposure (SHSe) in childhood is linked with increased morbidity and mortality. Hospital or secondary care contact may present a ‘teachable moment’ to provide parents with support to change their home smoking behaviours to reduce children’s SHSe. There is a lack of robust qualitative evidence around parents and healthcare professionals (HCPs) views on using this teachable moment to successfully initiate behavioural change. We aim to identify and understand what is important to stakeholders with a view to informing the development of a support package to help parents change their home smoking behaviours.Methods and analysisThis qualitative study will be theoretically underpinned by the Capability, Opportunity and Motivation Behaviour (COM-B) model of behavioural change. It will involve semistructured interviews and/or discussion groups with up to 20 parents who smoke and up to 25 HCPs. Stakeholders will be recruited from a single National Health Service children’s hospital in England. Interviews and/or discussion groups will be audio recorded, transcribed and anonymised. The transcripts and any field notes will be analysed using the framework method. Initially, we will apply COM-B to the data deductively and will then code inductively within each domain.Ethics and disseminationThe protocol for this study received a favourable outcome from the East Midlands Leicester Central Research Ethics Committee (19/EM/0171). Results will be written up as part of a PhD thesis, submitted for publication in peer-reviewed journals and presentation at conferences.Trial registration numberISRCTN40084089.

Introduction Childhood secondhand smoke exposure (SHSe) is linked with increased morbidity and mortality. Hospital or secondary care contact presents a ‘teachable moment’ to support parents to change their home smoking behaviours to reduce children’s SHSe. This mixed-methods review explores: (1) if existing interventions in this context are effective, (2) if they are reported in sufficient detail to be replicated, (3) the experiences of HCPs delivering such interventions, and (4) the experiences of parents receiving such interventions. Methods Five electronic databases and the grey literature were searched for relevant literature published and indexed January 1980 to February 2020. Fourteen papers reporting twelve studies (nine quantitative and five qualitative) were included. Aligned with the Joanna Briggs Institute method, a segregated approach was used involving independent syntheses of the quantitative and qualitative data followed by an overall mixed-methods synthesis. Results There was some evidence of effective interventions that resulted in a short-term (< 6 months) reduction in children’s SHSe when SHSe was subjectively measured. This was not seen in longer term follow-up (> 6 months) or when SHSe was measured objectively. Inconsistencies with reporting make replication challenging. Experiential evidence suggests a mismatch between stakeholder preferences and interventions being offered. Conclusions The paediatric secondary care interventions included in this analysis failed to show statistically significant evidence of longer-term effectiveness to reduce children’s SHSe in all but one low quality study. There was also inadequate reporting of interventions limiting assessment of effectiveness. It offer further insights into areas to target to develop effective interventions. Implications This review used rigorous methods to explore the current, global literature on how children’s exposure to SHS is being tackled in secondary care. This review identified only one low quality intervention study showing a statistically significant reduction in children’s SHSe beyond six months. Synthesis with qualitative research identifies a mismatch between what parents want in an intervention and what has been delivered to date. Reporting quality needs to be improved to ensure that interventions can be replicated and studies conducted within the NHS to ensure suitability to this setting.

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Background Glycosylated haemoglobin (HbA1c) measurement is used to diagnose and to guide treatment of diabetes mellitus. Within-subject variability in measured HbA1c affects its clinical utility and interpretation, but no comprehensive systematic review has described within-subject variability. Methods A systematic review and meta-analysis was performed of within-subject variability of HbA1c. Multiple databases were searched from inception to November 2022 for follow-up studies of any design in adults or children, with repeated measures of HbA1c or glycosylated haemoglobin. Title and abstract screening was performed in duplicate, full text screening and data extraction by one reviewer and verified by a second. Risk of bias of included papers was assessed using a modified consensus-based standards for the selection of health measurement Instruments (COSMIN) tool. Intraclass correlation coefficient (ICC) results were pooled with a meta-analysis and coefficient of variation (CV) results were described by median and range. Results Of 2675 studies identified, 111 met the inclusion criteria. Twenty-five studies reported variability data in healthy patients, 19 in patients with type 1 diabetes and 59 in patients with type 2 diabetes. Median within-subject coefficient of variation (CV) was 0.070 (IQR 0.034 to .09). For healthy subjects the median CV for HbA1c % was 0.017 (IQR 0.013 to 0.022), for patients with type 1 diabetes 0.084 (IQR 0.067 to 0.89) and for type 2 diabetes 0.083 (IQR 0.06 to 0.10). CV increased with mean population HbA1c. Limitations Assessment of variability was not the main aim of many of the included studies and some relevant papers may have been missed. Many included papers had few participants or few repeated measurements. Conclusions Within-subject variability of HbA1c is higher for patients with than without diabetes and increases with mean population HbA1c. This may confound observed relationships between HbA1c variability and health outcomes. Because of its importance in clinical decision-making there is a need for better estimates and understanding of factors associated with of HbA1c variability.