INTRODUCTIONThe use of applied modeling in dementia risk prediction, diagnosis, and prognostics will have substantial public health benefits, particularly as “deep phenotyping” cohorts with multi‐omics health data become available.METHODSThis narrative review synthesizes understanding of applied models and digital health technologies, in terms of dementia risk prediction, diagnostic discrimination, prognosis, and progression. Machine learning approaches show evidence of improved predictive power compared to standard clinical risk scores in predicting dementia, and the potential to decompose large numbers of variables into relatively few critical predictors.RESULTSThis review focuses on key areas of emerging promise including: emphasis on easier, more transparent data sharing and cohort access; integration of high‐throughput biomarker and electronic health record data into modeling; and progressing beyond the primary prediction of dementia to secondary outcomes, for example, treatment response and physical health.DISCUSSIONSuch approaches will benefit also from improvements in remote data measurement, whether cognitive (e.g., online), or naturalistic (e.g., watch‐based accelerometry).

Background COVID-19 has exacerbated the significant and longstanding mental health inequalities for ethnic minorities, who were less likely to access mental health support in primary care but more likely to end up in crisis care compared to the majority ethnic group. Services were poorly offered and accessed to respond to the increased mental health challenges. Aim To 1) establish evidence on which changes to mental health services provided in response to COVID-19 are beneficial for ethnic minorities who experience mental health difficulties in the North of England, and 2) to inform what and how culturally competent mental health services should be routinely provided. Methods A mixed methods approach comprising 1) a rapid review to map services and models of care designed or adjusted for mental health during the pandemic, 2) an observational study of retrospective routine data to assess changes to mental health services and associated outcomes, 3) qualitative interviews to understand experiences of seeking care and factors associated with high-quality service provision, and 4) a Delphi study to establish consensus on key features of culturally competent services. From the selected areas in the North of England, adults from ethnic minorities who experience mental health difficulties will be identified from the primary, community and secondary care services and local ethnic minority communities. Discussion This study will identify ways to tackle health inequalities and contribute to mental health service recovery post pandemic by providing practice recommendations on equitable and effective services to ensure culturally competent and high-quality care. A list of services and features on what and how mental health services will be provided. Working with study collaborators and public and patient involvement partners, the study findings will be widely disseminated through presentations, conferences and publications and will inform the subsequent funding application for intervention development and evaluation.

IntroductionHyperlipidaemia contributes a significant proportion of modifiable cardiovascular disease (CVD) risk, which is a condition that disproportionally affects disadvantaged socioeconomic communities, with death rates in the most deprived areas being four times higher than those in the least deprived. With the national CVD Prevention programme being delivered to minimise risk factors, no evidence is available on what has been implemented in primary care for deprived populations. This study describes the protocol for the development of a tailored intervention aiming to optimise lipid management in primary care settings to help reduce inequalities in CVD risks and improve outcomes in deprived communities.Methods and analysisA mixed-methods approach will be employed consisting of four work packages: (1) rapid review and logic model; (2) assessment and comparison of CVD risk management for deprived with non-deprived populations in Northern England to England overall; (3) interviews with health professionals; and (4) intervention development. A systematic search and narrative synthesis will be undertaken to identify evidence-based interventions and targeted outcomes in deprived areas. General practice-level data will be assessed to establish the profile of lipid management, compared with the regional and national levels. Health professionals involved in the organisation and delivery of routine lipid management to deprived populations will be interviewed to understand the implementation and delivery of current lipid management and associated challenges. The prototype intervention will be informed by the evidence generated from workpackages 1–3, which will be reviewed and assessed using the nominal group technique to reach consensus. Training and skills development materials will also be developed as needed.Ethics and disseminationEthics approval has been obtained from the Faculty of Medical Sciences Research Ethics Committee at Newcastle University, UK. Findings will be disseminated to the participating sites, participants, commissioners, and in peer-reviewed journals and academic conferences.

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