The aims of this study were to explore how health visitors (HVs) and community health nurses (CHNs) assess unsettled baby behaviours, how their perceptions of these behaviours influence decisions about support offered, and how able they feel to deliver support to families of unsettled babies.

Qualitative semi-structured interviews were conducted, recorded and transcribed. Data were analysed using Reflexive Thematic Analysis.

Potential participants were invited nationally via social media and via Health Visiting Service managers from an NHS Trust. Interviews took place remotely.

17 HVs and 3 CHNs were purposively selected to include a wide range of perspectives.

Three themes were developed, (1) HVs’ perceptions of parents’ sense-making which explains how HVs/CHNs understand parents’ beliefs around unsettled babies; (2) care pathway which highlights the importance HVs place on creating emotional space for the baby, the parent and the health visitor within the pathway (containment); and (3) service delivery decline, which outlines the impact of funding cuts to the services on the HVs’ ability to provide support for families. Lastly, a new concept – the Tipping Point model - was created to holistically conceptualise the experiences of HVs providing support for unsettled babies in the UK.

Policy makers need to organise services to value and support the role of the health visiting team in ‘containment’. HVs identified a training need around assessing and advising about unsettled babies to place them in a stronger position to support families. Further research is needed into different models of support for families of unsettled babies from the wider primary care team and/or from digital services.

Primary care electronic health records provide a rich source of information for inequalities research. However, the reliability and validity of the research derived from these records depend on the completeness and resolution of the codelists (ie, collections of medical terms/codes) used to identify populations of interest. The aim of this project was to develop comprehensive codelists for identifying people from ethnic minority groups, people with learning disabilities (LDs), people with severe mental illness (SMI) and people who are transgender.

We followed a three-stage process to define and extract relevant codelists. First, groups of interest were defined a priori. Next, relevant clinical codes, relating to the groups, were identified by searching Clinical Practice Research Datalink (CPRD) publications, codelist repositories and the CPRD Code Browser. Relevant codelists were extracted and merged according to group, and duplicates were removed. Finally, the remaining codes were reviewed by two general practitioners (GPs).

The curated codelists were compared using a representative sample in the UK. The frequencies of individuals identified using the curated codelists were assessed and compared with widely used alternative codelists.

Comprehensiveness was assessed in a representative CPRD population of 10 966 759 people.

After removal of duplicates and GP review, codelists were finalised with 325 unique codes for ethnicity, 558 for LD, 499 for SMI and 38 for transgender. Compared with comparator codelists, an additional 48 017 (76.6%), 52 953 (68.9%) and 508 (36.9%) people with LD, SMI or transgender code were identified. The proportions identified for ethnicity, meanwhile, were consistent with expectations for the UK (eg, 6.50% Asian, 2.66% black and 1.44% mixed).

The curated codelists are more sensitive than those widely used in practice and research. Discrepancies between national estimates and primary care records suggest potential record/retention issues. Resolving these requires further investigation and could lead to improved data quality for research.