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There is a strong body of evidence that points to the mental health and wellbeing benefits of nature alongside a growing evidence base on the health and wellbeing benefits of green social prescribing (GSP). Central to the UK government’s commitment to transform mental health services, increase social prescribing (SP), and deliver personalised care, seven successful ‘test and learn’ GSP sites were identified across England, including the Humber and North Yorkshire (HNY) GSP programme. The aim of the ‘test and learn’ sites was to embed GSP into communities to improve mental health outcomes, reduce health inequalities, reduce demand on the health and social care system, and develop best practice in making green social activities more resilient and accessible. This report summarises the findings of the cohort evaluation, a key component of the HNY GSP programme, and reports on the mental health and wellbeing outcomes of participants who took part in nature-based activities linked to the GSP initiative. It discusses the findings in relation to the wider literature, key challenges identified by referring services involved in the cohort evaluation, alongside clinical implications, and future research opportunities in the area of GSP.

Additional file 1. MEDLINE search strategy.

Additional file 2. PRISMA-P 2015 Checklist.

Background People with severe mental illness (SMI), such as schizophrenia, have higher rates of physical long-term conditions (LTCs), poorer health outcomes, and shorter life expectancy compared with the general population. Previous research exploring SMI and diabetes highlights that people with SMI experience barriers to self-management, a key component of care in long-term conditions; however, this has not been investigated in the context of other LTCs. The aim of this study was to explore the lived experience of co-existing SMI and LTCs for service users, carers, and healthcare professionals. Methods A qualitative study with people with SMI and LTCs, their carers, and healthcare professionals, using semi-structured interviews, focused observations, and focus groups across the UK. Forty-one interviews and five focus groups were conducted between December 2018 and April 2019. Transcripts were coded by two authors and analysed thematically. Results Three themes were identified, 1) the precarious nature of living with SMI, 2) the circularity of life with SMI and LTCs, and 3) the constellation of support for self-management. People with co-existing SMI and LTCs often experience substantial difficulties with self-management of their health due to the competing demands of their psychiatric symptoms and treatment, social circumstances, and access to support. Multiple long-term conditions add to the burden of self-management. Social support, alongside person-centred professional care, is a key facilitator for managing health. An integrated approach to both mental and physical healthcare was suggested to meet service user and carer needs. Conclusion The demands of living with SMI present a substantial barrier to self-management for multiple co-existing LTCs. It is important that people with SMI can access person-centred, tailored support for their LTCs that takes into consideration individual circumstances and priorities.

Introduction Depression is a leading mental health problem worldwide. People with long-term conditions are at increased risk of experiencing depression. The COVID-19 pandemic led to strict social restrictions being imposed across the UK population. Social isolation can have negative consequences on the physical and mental wellbeing of older adults. In the Behavioural Activation in Social IsoLation (BASIL+) trial we will test whether a brief psychological intervention (based on Behavioural Activation), delivered remotely, can mitigate depression and loneliness in older adults with long-term conditions during isolation. Methods We will conduct a two-arm, parallel-group, randomised controlled trial across several research sites, to evaluate the clinical and cost-effectiveness of the BASIL+ intervention. Participants will be recruited via participating general practices across England and Wales. Participants must be aged ≥65 with two or more long-term conditions, or a condition that may indicate they are within a ‘clinically extremely vulnerable’ group in relation to COVID-19, and have scored ≥5 on the Patient Health Questionnaire (PHQ9), to be eligible for inclusion. Randomisation will be 1:1, stratified by research site. Intervention participants will receive up to eight intervention sessions delivered remotely by trained BASIL+ Support Workers and supported by a self-help booklet. Control participants will receive usual care, with additional signposting to reputable sources of self-help and information, including advice on keeping mentally and physically well. A qualitative process evaluation will also be undertaken to explore the acceptability of the BASIL+ intervention, as well as barriers and enablers to integrating the intervention into participants’ existing health and care support, and the impact of the intervention on participants’ mood and general wellbeing in the context of the COVID-19 restrictions. Semi-structured interviews will be conducted with intervention participants, participant’s caregivers/supportive others and BASIL+ Support Workers. Outcome data will be collected at one, three, and 12 months post-randomisation. Clinical and cost-effectiveness will be evaluated. The primary outcome is depressive symptoms at the three-month follow up, measured by the PHQ9. Secondary outcomes include loneliness, social isolation, anxiety, quality of life, and a bespoke health services use questionnaire. Discussion This study is the first large-scale trial evaluating a brief Behavioural Activation intervention in this population, and builds upon the results of a successful external pilot trial. Trial registration ClinicalTrials.Gov identifier ISRCTN63034289, registered on 5th February 2021.

BackgroundThe evidence is sparse regarding the associations between serious mental illnesses (SMIs) prevalence and environmental factors in adulthood as well as the geographic distribution and variability of these associations. In this study, we evaluated the association between availability and proximity of green and blue space with SMI prevalence in England as a whole and in its major conurbations (Greater London, Birmingham, Liverpool and Manchester, Leeds, and Newcastle).Methods and findingsWe carried out a retrospective analysis of routinely collected adult population (≥18 years) data at General Practitioner Practice (GPP) level. We used data from the Quality and Outcomes Framework (QOF) on the prevalence of a diagnosis of SMI (schizophrenia, bipolar affective disorder and other psychoses, and other patients on lithium therapy) at the level of GPP over the financial year April 2014 to March 2018. The number of GPPs included ranged between 7,492 (April 2017 to March 2018) to 7,997 (April 2014 to March 2015) and the number of patients ranged from 56,413,719 (April 2014 to March 2015) to 58,270,354 (April 2017 to March 2018). Data at GPP level were converted to the geographic hierarchy unit Lower Layer Super Output Area (LSOA) level for analysis. LSOAs are a geographic unit for reporting small area statistics and have an average population of around 1,500 people. We employed a Bayesian spatial regression model to explore the association of SMI prevalence in England and its major conurbations (greater London, Birmingham, Liverpool and Manchester, Leeds, and Newcastle) with environmental characteristics (green and blue space, flood risk areas, and air and noise pollution) and socioeconomic characteristics (age, ethnicity, and index of multiple deprivation (IMD)). We incorporated spatial random effects in our modelling to account for variation at multiple scales.Across England, the environmental characteristics associated with higher SMI prevalence at LSOA level were distance to public green space with a lake (prevalence ratio [95% credible interval]): 1.002 [1.001 to 1.003]), annual mean concentration of PM2.5(1.014 [1.01 to 1.019]), and closeness to roads with noise levels above 75 dB (0.993 [0.992 to 0.995]). Higher SMI prevalence was also associated with a higher percentage of people above 24 years old (1.002 [1.002 to 1.003]), a higher percentage of ethnic minorities (1.002 [1.001 to 1.002]), and more deprived areas.Mean SMI prevalence at LSOA level in major conurbations mirrored the national associations with a few exceptions. In Birmingham, higher average SMI prevalence at LSOA level was positively associated with proximity to an urban green space with a lake (0.992 [0.99 to 0.998]). In Liverpool and Manchester, lower SMI prevalence was positively associated with road traffic noise ≥75 dB (1.012 [1.003 to 1.022]). In Birmingham, Liverpool, and Manchester, there was a positive association of SMI prevalence with distance to flood zone 3 (land within flood zone 3 has ≥1% chance of flooding annually from rivers or ≥0.5% chance of flooding annually from the sea, when flood defences are ignored): Birmingham: 1.012 [1.000 to 1.023]; Liverpool and Manchester: 1.016 [1.006 to 1.026]. In contrast, in Leeds, there was a negative association between SMI prevalence and distance to flood zone 3 (0.959 [0.944 to 0.975]). A limitation of this study was because we used a cross-sectional approach, we are unable to make causal inferences about our findings or investigate the temporal relationship between outcome and risk factors. Another limitation was that individuals who are exclusively treated under specialist mental health care and not seen in primary care at all were not included in this analysis.ConclusionsOur study provides further evidence on the significance of socioeconomic associations in patterns of SMI but emphasises the additional importance of considering environmental characteristics alongside socioeconomic variables in understanding these patterns. In this study, we did not observe a significant association between green space and SMI prevalence, but we did identify an apparent association between green spaces with a lake and SMI prevalence. Deprivation, higher concentrations of air pollution, and higher proportion of ethnic minorities were associated with higher SMI prevalence, supporting a social-ecological approach to public health prevention. It also provides evidence of the significance of spatial analysis in revealing the importance of place and context in influencing area-based patterns of SMI.

Aims To systematically review and synthesise qualitative evidence about determinants of self-management in adults with SMI. The goal is to use findings from this review to inform the design of effective self-management strategies for people with SMI and LTCs. Background People living with serious mental illness (SMI) have a reduced life expectancy by around 15–20 years, mainly due to the high prevalence of long-term physical conditions such as diabetes and heart disease. People with SMI face many challenges when trying to manage their physical health. Little is known about the determinants of self-management – managing the emotional and practical issues – of long-term conditions (LTCs) for people with SMI. Method Six databases, including CINAHL and MEDLINE, were searched to identify qualitative studies that explored people's perceptions about determinants of self-management in adults with SMI (with or without comorbid LTCs). Self-management was defined according to the American Association of Diabetes Educator's self-care behaviours (AADE7). Determinants were defined according to the Capabilities, Opportunity, Motivations and Behaviours (COM-B) framework. Eligible studies were purposively sampled for synthesis according to the richness of the data (assessed using Ames et al (2017)'s data richness scale), and thematically synthesised. Result Twenty-six articles were included in the synthesis. Seven studies focused on self-management of LTCs, with the remaining articles exploring self-management of SMI. Six analytic themes and 28 sub-themes were identified from the synthesis. The themes included: the additional burden of SMI; living with comorbidities; beliefs and attitudes about self-management; support from others for self-management; social and environmental factors; routine, structure and planning. Capabilities for self-management were linked to people's perceptions about the support they received for their SMI and LTC from healthcare professionals, family and friends. Opportunities for self-management were more commonly expressed in the context of social and environmental factors. Motivation for self-management was influenced by beliefs and attitudes, whilst being closely related to the burden of SMI. Conclusion The themes identified from the synthesis suggest that capabilities, opportunities and motivations for self-management can be negatively influenced by the experience of SMI, whilst social and professional support, improved access to resources, and increased involvement in care, could promote self-management. Support programmes for people with SMI and LTCs need to account for these experiences and adapt to meet the unique needs of this population.