Paul Clarkson

Background/Objectives: Food insecurity (FI) is an increasing concern in the UK. Early Help (EH) provided by social services, based on strengths-based conversations with families, can address wider social and economic needs experienced by families living with FI. This study aimed to describe needs identified through EH assessments among families attending foodbanks, the proportion of recorded needs met, and stakeholder experiences. Methods: A mixed-methods study was undertaken using 30 months of routinely collected social services data. Regression modelling examined associations between needs identified at the start of EH and the proportion documented as met at the end of support. Semi-structured interviews explored stakeholder experiences using Framework Analysis. Results: Records were available for 385 families comprising 1840 individuals (1108 children; 732 adults). Thirty-five categories of need were recorded, with 2646 needs identified (mean 6.9, standard deviation [SD] 3.2 per family). Of these, 2505 (95%) were documented as met, and 301/385 (78%) families had all identified needs recorded as met. In the primary quasi-binomial regression analysis (n = 378), longer duration of EH involvement was associated with a higher proportion of initially identified needs recorded as met (β = 0.139, p = 0.017). Area-level deprivation was also associated with the outcome (β = −0.179, p = 0.049), whereas household size was not (p = 0.249). The positive association with duration was supported by a Gaussian sensitivity analysis (p = 0.003). Interviews (n = 23) identified three overarching themes: systemic and structural drivers of FI; lived experiences and service engagement; and visions for improvement. Conclusions: Participants described practical and emotional support gained from EH. Families attending foodbanks had multiple needs across diverse domains and most needs were documented as met following EH involvement. However, the study design does not establish that EH caused these outcomes.

Summary: Background: Phenotypic age acceleration (PhenoAgeAccel), derived from PhenoAge, and MetaboHealth are composite exposures of biological ageing and metabolic health associated with dementia-related outcomes. Whether these associations are causal and reflect the exposures, constituent biomarkers, or both remains unclear. Methods: This study included UK Biobank participants of White British genetic ancestry. MetaboHealth was derived from nuclear magnetic resonance (NMR) metabolomics and PhenoAgeAccel from clinical biomarkers and chronological age. Genome-wide association studies (GWAS) were conducted for MetaboHealth (n=272 568) and PhenoAgeAccel (n=274 077). Independent genome-wide significant variants were used as genetic instruments in two-sample Mendelian randomisation (MR) with FinnGen all-cause dementia summary statistics. Inverse-variance weighting was the primary MR method. Causal network analysis estimated relationships among constituent biomarkers and dementia. Findings: GWAS identified 126 and 141 independent genome-wide significant variants for MetaboHealth and PhenoAgeAccel, of which 109 and 141 were retained as genetic instruments. MR found no evidence of a causal effect of genetically predicted MetaboHealth (per unit: OR 0·83, 95% CI 0·49–1·42; p=0·51) or PhenoAgeAccel (per year: OR 0·99, 95% CI 0·95–1·02; p=0·44) on all-cause dementia, with consistent findings across sensitivity analyses and robust MR methods. Lower lymphocyte percentage and higher NMR-derived glucose had direct relationships with dementia in the joint constituent-biomarker network. Interpretation: MR provided no evidence that either composite exposure causally influenced dementia. The network prioritised lymphocyte percentage and NMR-derived glucose, supporting examination of composite exposures alongside their constituent biomarkers. Funding: NIHR, UKRI, MRC, UK Dementia Research Institute, Innovate UK, and European Union. Full funding details are provided in the acknowledgements. Research in context: Evidence before this study: We searched PubMed from database inception to July 11, 2026, without language restrictions, using combinations of the terms “dementia”, “Alzheimer’s disease”, “vascular dementia”, “biological ageing”, “phenotypic age”, “PhenoAge”, “PhenoAgeAccel”, “MetaboHealth”, “metabolomics”, “genome-wide association study”, “Mendelian randomisation”, and “causal network”. Previous GWAS characterised the genetic architecture of PhenoAgeAccel and MetaboHealth. Longitudinal studies linked PhenoAgeAccel, derived from PhenoAge, to incident all-cause, young-onset, and late-onset dementia, dementia subtypes, cognition, and brain structure; MetaboHealth was associated with poorer cognitive performance, 10-year cognitive decline, and reduced functional independence. Related PhenoAge-based measures have also been studied in relation to modifiable factors and intervention response. Genetic causal evidence remained limited: one two-sample MR study found no evidence that PhenoAgeAccel affected Alzheimer’s disease or vascular dementia, while previous causal-discovery research placed Phenotypic Age within a dementia network without examining its constituent biomarkers. Added value of this study: To our knowledge, this is the first study to genetically evaluate PhenoAgeAccel and MetaboHealth as composite exposures and then deconstruct their constituent biomarker relationships using causal network analysis in dementia. It also provides the first large-scale GWAS of MetaboHealth using the complete Phase 3 UK Biobank Nightingale dataset. The expanded GWAS identified additional loci and enlarged the available genetic instrument sets, while the network analysis resolved the constituent biomarker structure underlying both composite exposures. Implications of all available evidence: For causal investigation, analysing PhenoAgeAccel and MetaboHealth alongside their constituent biomarkers reveals relationships obscured within the composite exposures. This does not preclude their use for prediction or risk stratification. Lymphocyte percentage and NMR-derived glucose therefore warrant further investigation as potential indicators of immune and metabolic pathways relevant to dementia.

Background: The need for social care, in the form of practical assistance and personal care, is increasing alongside a growing older population with long‐term conditions and places those with limited or no access to publicly funded care at risk of increasing levels of unmet need. Aim: This systematic review sought to understand the role of social and health conditions in the need, demand, utilization, and expenditure on social care in the United Kingdom. Methods: We searched Medline, CINAHL, EconLit, ASSIA, and the Campbell Collaboration from January 1, 2009 to April 14, 2025, and gray literature on August 21, 2024, for randomized trials, cohort studies, case control studies, and interrupted time series, cross‐sectional, and modeling studies of populations aged ≥ 60 years old, in a UK setting, that examined the association of social and health conditions with the need and demand for, use of and expenditure on social care. We conducted risk of bias assessments using ROBINS‐E for longitudinal studies, and intended to use Risk of Bias 2 for randomized trials. We applied GRADE to assess the certainty of evidence. Results were synthesized narratively, and presented in an Evidence Gap Map. Results: We included 10 longitudinal cohort and eight cross sectional studies, study sample size ranged from 526 to > 400,000 participants. Five of the cohort studies were assessed as high risk of bias, and the cross sectional studies as moderate concern or high risk of bias. Older age was associated with increased unmet need for care in most studies, and living alone with increased unmet need for care and use of residential care. Results for ethnicity, deprivation and sex varied across studies, with studies using different measures of deprivation that limited comparability of findings. A range of long‐term health conditions were assessed, some studies indicated an association with an increased need and use of care; there were mixed findings for cost. For populations with cognitive impairment or dementia, the association with age and the use and cost of care varied, there was no clear association for sex, ethnicity and living alone; a previous hospital admission or ongoing health problems that included severity of dementia were associated with increased use of care. Conclusion: Our review of UK evidence indicates that there is insufficient evidence to accurately identify populations age > 60 years that are at increasing risk for needing care due to their social and health conditions.

Background: Dementia affects nearly 1 million people in the United Kingdom and their unpaid carers physically, psychologically, socially and economically, highlighting that both need support. Post-diagnostic support is recognised as inadequate globally. In England, it is fragmented or absent apart from primary care – leaving many feeling unsupported as the condition progresses. The Dementia PersonAlised Care Team research programme began in 2018 to address evidence gaps on the effectiveness of dementia support roles and what constitutes ‘good’ support. Objective: Dementia PersonAlised Care Team aimed to develop and evaluate an intervention comprising dementia support workers based in primary care, supporting people with moderate to severe dementia and their carers. Phase 1 focused on intervention development and feasibility testing. Phase 2 evaluated the dementia support workers’ value and impact. Our Peer Research Group contributed to the design, analysis and interpretation of data in both phases. Design and methods: Phase 1 employed a realist approach to develop theory, the intervention and practitioner support package. This was informed by literature, consulting experts by experience, academics and practitioners and a formative evaluation. A pilot cluster randomised controlled trial tested the feasibility of recruitment, outcome measures and eligibility criteria. Phase 2 included a realist longitudinal mixed-methods evaluation to determine what worked, for whom and in what circumstances. High-volume qualitative data included realist interviews with participants with dementia and carers at two time points, interviews with dementia support workers and general practitioner staff/other practitioners, observations, dementia support worker case notes and reflections, and medical records. Quantitative measures of health- and quality of life-related outcomes, experience of care, carer well-being and support, and resource use were collected at three time points. A mixed-methods integration was conducted following separate qualitative, quantitative and economic analyses. Setting and participants: Phase 1 recruited participants with dementia (some without capacity) and their carers (if present) from general practitioner practices in rural Devon and Greater Manchester. In phase 2, participants were recruited from practices in rural and coastal areas in Devon (high deprivation) and urban Greater Manchester (including areas with higher representation of South Asian communities). Intervention: The Dementia PersonAlised Care Team intervention, developed in phase 1, delivers personalised, proactive and integrated dementia care via trained dementia support workers embedded in primary care. Drawing on coaching principles, dementia support workers empower decision-making and address psychosocial, health and practical needs through flexible, ongoing support. Support is tailored to individuals’ and carers’ needs. Consented participants were offered 12 months of support, which is flexibly stepped up or down based on need. Findings: In phase 1, the Dementia PersonAlised Care Team intervention was tested in 10 general practitioner practices. COVID-19 necessitated switching to remote intervention delivery, recruitment and data collection. Intervention and recruitment strategy (including capacity assessment) were acceptable. However, only 51% (56/110) of the recruitment target was met, making a fully powered cluster randomised controlled trial unfeasible within the funding envelope. A mixed-methods longitudinal realist approach was therefore adopted for the evaluation (phase 2). In phase 2, 126 PwD and 121 carers were recruited from 13 practices – reaching 70% (126/180) of the recruitment target. Retention in the intervention was high (79%). However, participation in follow-up data collection was poor for all quantitative measures, for example, only 22% (28/126) of participants completed the Engagement and Independence in Dementia Questionnaire at 9–12 months. The longitudinal realist analysis identified four areas of positive impact linked to dementia support worker actions: living well, proactive care, reactive care and care transitions. Participants spoke about improved social engagement, medication management and holistic care outcomes despite the inevitable functional decline. Supervision and peer support for dementia support workers, along with joint work with practice teams, were key to delivering this care. Quantitative data showed either stable or declining trends except for carer perceptions of support, which improved over time. Realist-informed economic analysis identified 23 cases where dementia support workers likely prevented high-cost care escalation through early intervention, access to general practitioner records and ability to prompt general practitioners’ care. Resource use shifted towards increased primary/community care and reduced secondary care costs. At a caseload of 53 dyads at any one time, mean annual cost per dyad was estimated at £1222.48. Limitations: Low data completion rates, individual variability and the non-randomised design significantly limited utility of quantitative findings. Conclusions: This work demonstrated how gaps in post-diagnostic support for people with dementia and carers can be addressed through tailored, proactive support and dementia support workers being fully embedded in primary care. A comprehensive training and ongoing support package is essential for enabling dementia support workers to carry out their role. Future work: Further implementation research is needed to test delivery in changing National Health Service contexts, including whether different roles can deliver personalised dementia support. Study registration: This study is registered as ISRCTN90828574. Funding: This award was funded by the National Institute for Health and Care Research (NIHR) Programme Grants for Applied Research Programme (NIHR award ref: RP-PG-0217-20004) and is published in full in Programme Grants for Applied Research ; Vol. 14, No. 17. See the NIHR Funding and Awards website for further award information.

In Adult Social Care, UK local authorities have statutory responsibilities for assessing needs and delivering services to ensure adults’ wellbeing. Administrative data collected during this process may help local authorities’ compliance with these duties. We developed and internally validated predictive models for older people (>- 60 years) receiving social care for whether they remained at home or were admitted to care homes, two years after index assessments, using administrative data from one English City authority. We enquired whether the right data, to predict older people’s vulnerability to adverse outcome (care home) or evidence their strengths (remaining at home), were present in local authority systems, and if accurate datasets for large numbers of older people could be constructed to allow robust modelling. Logistic regression models were created with binary outcome (remaining at home/entering care homes). Sample size calculations determined the maximum number of candidate predictors we could consider for model development. 20,218 older people in the data cohort indicated we could consider a maximum of 46 candidate predictor parameters. In our final analyses we considered 31 candidate predictor parameters, in the areas of: age, sex, ethnicity, deprivation, housing tenure, abilities in activities of daily living, access to carer, Primary Support Reason, diagnosis of dementia. We used all data for model development and internal validation using cross-validation. Models were robust as to assumptions, with no evidence of overfitting and good predictive accuracy. Circumstances predicting strongly that older people would not remain at home were that they were: from other (non-white) ethnic groups, privately rented tenants or other (unstable) tenancies, not able to eat or keep their home habitable without difficulty, with their Primary Support Reason for personal care, mental health, or support with cognition. With public involvement partners, we created a prototype index for local authority use to inform professional decisions and/or local planning.

Moral injury is the long-term effect of the experience of events that violate deeply held moral beliefs. Social workers in adult care settings are tasked with managing morally complex situations and make decisions that impact the lives of service users. Simultaneously, they adhere to their professional ethical code and organisational standards, potentially giving rise to moral injury. Little is known about these experiences. This qualitative descriptive study aimed to explore social workers' experiences of moral injury. Remote interviews were conducted with ten social work professionals, in adult services in England. Data were inductively analysed using reflexive thematic analysis. Three themes were identified: a) System-related impacts; b) Service-related impacts; c) Individual psychological impacts. Social worker moral injury can arise from efforts to uphold professional values whilst navigating limited resources, interprofessional conflicts, and working within a constrained system. Witnessing dehumanising, low-quality, and impersonal care is a major source of moral injury. This is marked by professional disempowerment, sadness, guilt, betrayal, and helplessness. Recognising these experiences is important. Building psychosocial resilience through formal support is essential for moral repair. Application of the concept for social work, alongside further research, is paramount to adequately support staff.

Introduction: Musculoskeletal conditions burden individuals’ quality of life and health and social care resources. However, we know little about how many of these patients use social care, their characteristics, and costs. Material and Methods: We used routine administrative data from patients attending a U.K. NHS rheumatology clinic, linked with data from their local authority Adult Social Care contacts. Descriptive analyses were undertaken to determine how many patients used social care, types of services used, level of informal care, support with daily living, and social care costs. Further, regression analyses were used to explore associations between rheumatological diagnosis, patient characteristics, number of comorbidities, and whether patients used social care and its annual costs to the local authority. Results: Of 15,876 rheumatology outpatients, between June 2013 and November 2020, 297 (2%) used social care services, between January and December 2022. The highest social care receipt was in females, those in older age groups, from more deprived areas, and with more than one musculoskeletal condition; 27% of patients receiving social care had informal care support. The greatest needs for social care were in patients requiring help with managing and maintaining nutrition and managing personal hygiene, with their Primary Support Reason for local authority contact being for personal care, followed by access and mobility. The relationship between rheumatology condition and social care was complex. Patients with autoimmune connective tissue diseases and inflammatory arthritis received more home care, whereas those with autoimmune connective tissue diseases and crystal arthritis were in care homes. Patients’ total annual local authority cost of social care was nearly £5.5M, with significant associations between crystal arthritis, other musculoskeletal disease, more than one musculoskeletal disease, and higher social care costs. Discussion: Our findings reinforce these patients’ needs for care and support and can facilitate government and local social care planning.

In Adult Social Care, UK local authorities have statutory responsibilities for assessing needs and delivering services to ensure adults’ wellbeing. Administrative data collected during this process may help local authorities’ compliance with these duties. We developed and internally validated predictive models for older people (>- 60 years) receiving social care for whether they remained at home or were admitted to care homes, two years after index assessments, using administrative data from one English City authority. We enquired whether the right data, to predict older people’s vulnerability to adverse outcome (care home) or evidence their strengths (remaining at home), were present in local authority systems, and if accurate datasets for large numbers of older people could be constructed to allow robust modelling. Logistic regression models were created with binary outcome (remaining at home/entering care homes). Sample size calculations determined the maximum number of candidate predictors we could consider for model development. 20,128 older people in the data cohort indicated we could consider a maximum of 46 candidate predictor parameters. In our final analyses we considered 31 candidate predictor parameters, in the areas of: age, sex, ethnicity, deprivation, housing tenure, abilities in activities of daily living, access to carer, Primary Support Reason, diagnosis of dementia. We used all data for model development and internal validation using cross-validation. Models were robust as to assumptions, with no evidence of overfitting and good predictive accuracy. Circumstances predicting strongly that older people would not remain at home were that they were: from other (non-white) ethnic groups, privately rented tenants or other (unstable) tenancies, not able to eat or keep their home habitable, with their Primary Support Reason for personal care, mental health, or support with cognition. With public involvement partners, we created a prototype index for local authority use to inform professional decisions and/or local planning.

Context: The COVID-19 pandemic presented unprecedented challenges for the adult social care sector, necessitating rapid changes in service delivery. Understanding the factors influencing the well-being of staff beyond the pandemic’s initial crisis response phase is crucial. Objective: The article examines the mental well-being, burnout, and the morally injurious experiences of the adult social care workforce in Greater Manchester during the UK’s ’Living with COVID’ phase, initiated in February 2022. Methods: An online survey collected responses from 251 social care staff. Regression analyses, employing a job-demands and resources framework (JD-R), considered demographic, occupational, and COVID-19-related factors to predict psychological outcomes. Findings: Significant levels of low mental well-being (34%) and burnout (31% likely experiencing burnout, 36% at risk) were observed. Additionally, 40% reported experiencing events that were potentially morally injurious. COVID-19-related factors had a significant impact on these outcomes. Satisfaction with infection control measures and access to sufficient resources were associated with more favourable outcomes. Considerable changes in daily activities and dissatisfaction with infection control measures were associated with increased levels of burnout and exposure to morally injurious experiences. Demographic and occupational factors had a lesser influence. Limitations: The study was conducted in a single geographic region of England with non-probability sampling methods and recruitment, potentially impacting the generalisability of the findings. Implications: The findings highlight the importance of adequate resources and infection control measures in reducing harm in the adult social care workforce and building resilience for future sector pressures.

INPLASY2024100127 Moral injury in care settings: A concept analysis protocol Moral injury; social work; social care; social services; healthcare; workforce. Read and download full-text here –…