In any given year, one-quarter of adults in England will experience mental ill-health and face consequential difficulties including work absence, unemployment, homelessness, physical health problems, and reduced life expectancy (McManus et al., 2009; ONS, 2017; McManus et al., 2016; WHO, 2013; Walker et al., 2015).

Despite chronic underinvestment in the provision of mental health care (Mental Health Taskforce, 2016) and the COVID-19 impact (ONS, 2020), there is promise within our communities. Public mental health (PMH) promotion is coordinated by third-sector organisations, local communities, and individuals (McManus et al., 2009). The aim is to tackle common risk factors such as discrimination and isolation (McManus et al., 2016), and to increase protective factors such as community safety (Sax Institute, 2020).

Community-based interventions play a key role in this by offering programmes that tackle social determinants at both individual and community levels (Duncan et al., 2021). These interventions demonstrate significant potential (McManus et al., 2009; Faculty of Public Health and Mental Health Foundation, 2016), but their effectiveness, cost-effectiveness, and underlying mechanisms are unclear (McGrath et al., 2021; Lee et al., 2022). This impedes matching interventions and service provision to need, and we miss the chance to learn what is effective (or ineffective) and for whom, to then replicate and scale up (Duncan et al., 2021).

Duncan and colleagues (2021) sought to explore the unknown. The authors aimed to:

1. Identify the range of adult community mental health interventions provided across five localities;
2. Describe the features of each intervention;
3. Identify priority areas for policy and service intervention by critiquing availability against need, alongside determinants of mental health.
   

   Community-based mental health interventions have the potential to tackle social injustice and provide support, space, and recognition, but are we using them to their potential?

Methods

The researchers adopted a mapping methodology, adequately named TIDier (Hoffmann et al., 2014), to systematically collect information on interventions.

Alongside mental health stakeholders and peer researchers, interventions were defined as any non-clinical programme, service or policy that sought to promote the mental wellbeing of its community residents. Included were services for adults (16+), running between July 2019 to May 2020, within the boundaries of five localities spread across England with diverse sociodemographic characteristics, needs, and local authority systems.

To uncover and assess the services available in each locality, standardised data collection started with desk-based research involving an internet deep-dive and then expanded to contacting key informants (e.g., practitioners and link workers) until the researchers had an exhaustive list of programmes.

Once satisfied, they developed a coding framework for comparability across sites and between interventions to categorise programme typology, risk or a protective factor, and target population.

Results

Overall, 407 interventions were identified.

Intervention type

The most common interventions that emerged included social activities and/or befriending, community linking (e.g., signposting, advice, and social prescribing), and peer support and mentoring. The least common interventions targeted food security and connection to animals and green spaces.

Risk and prevention factors

The factors most frequently targeted were social isolation and loneliness, financial stress, stigma, knowledge, and awareness of mental health, stigma, discrimination, and marginalisation of individuals of ethnic minorities and those who have migrated. Despite being strong determinants of mental illness, the least frequently targeted factors were caring responsibilities, bereavement, stigma, discrimination, marginalisation of the LGBTQ+ community, and food insecurity.

Populations targeted

The study suggested that most services were available for older adults, people with ethnic minority backgrounds, carers, and the LGBTQ+ community. This was the case for both men and women. The population found to have the least services tailored to their needs were marginalised individuals at the intersection of ethnicity, gender, and sexual orientation. Within this sub-group, minority ethnic women were the most supported, whilst ethnic men and the ethnic LGBTQ+ community were the least supported.

Matching provision to need

The localities were ranked among the 30% of most deprived areas in England, suggesting frequent exposure to drivers of poor mental wellbeing. Troubling is the finding that although interventions targeted some prevalent drivers (i.e., isolation), many were infrequently supported (i.e., food security) or even unfeatured (i.e., housing).

Service evaluation

Unpromisingly, service stakeholders revealed that due to lack of time and funding, evaluation was impossible and, therefore, data on intervention outcomes, effectiveness and cost-effectiveness, sustainability and to whom and how many people the services reached is lost.

Conclusions

Community services are on the right path, but there is a long way to go. Services are supporting vulnerable groups and responding to needs by tackling certain determinants. However, many crucial factors including those at structural and environmental levels, are less available, and certain marginalised and intersectional groups are left behind.

Strengths and limitations

Some notable strengths:

• The aims. Community services can provide incredible support and this mapping exercise shines a light on their range, focus, and areas for improvement.
• The data collection. The method had been previously tried and tested (Hoffmann et al., 2014) and the authors’ adoption was thorough. Moreover, the authors offer careful reflection on where data was likely missed and its impact.
• The authors’ reflections. At the results stage, careful consideration of people’s challenges was made, as was critical reflection of service provision being based on minimal data.

And some limitations worthy of our attention:

• The methods. Missing data was likely due to using the internet as a main port of information; some websites were outdated, and some services may not have online information at all. Data is also likely missed due to not including private or work-based services, or services that did not label public mental health as a focus. Perhaps the inclusion criteria were too stringent, and a wider cast net would have revealed valuable springs of social support.
• The discussion. No reflection or explanation was provided by the authors on the anomaly that although carers and LGBTQ+ individuals are commonly targeted populations, caring responsibilities and the stigma, discrimination, and marginalisation faced by LGBTQ+ people are infrequently targeted factors. This leaves me wondering: how can we substantially improve existing services and improve inclusivity towards marginalised groups?
• The discussion (again). An aim was to critique availability against need and although this was assessed, ambiguity remains on how this exploration can be deepened, as does the exploration of determinants.

Implications for practice

This study offers a valuable initial sketch of the community service scene. A new detailed map, reflecting our post-lockdown landscape, would help reveal what we need to address to better support community wellbeing.

Future research could replicate this mapping exercise to examine the impact of the pandemic on community service availability. This research may consider widening the inclusion criteria to capture excluded services and those that state to tackle any one determinant of mental wellbeing. Collecting data via social media and land-based fieldwork may also reveal services otherwise missed.

Policy and practice could develop and embed a feasible, systematic service evaluation tool and standardised monitoring system. Services that focus on structural and environmental factors should have their labels reviewed to include public mental health (PMH), and wellbeing determinant labels could be linked to the PMH label for research purposes. Social and political awareness of social determinants of mental health must be raised to find a balance between universal and targeted interventions towards vulnerable groups. Lastly, advocating for service user involvement in service development, provision and evaluation is a key to delivering effective support.

Clinical practice should focus on the assessment of present social determinants. Clinicians can collaboratively explore the importance of these factors with individuals, and where appropriate, encourage people to engage with their communities. Sustaining relationships with Community Link Nurses, signposting leads, or other such figures is valuable for holistic care. Moreover, enabling access for clinical teams to up-to-date and ergonomic community service spreadsheet facilitates tackling wellbeing determinants. Importantly, community services must maintain contact with public health services (and amongst each other), offer information workshops, and raise community awareness of their existence.

Statement of interests

None.

Links

Primary paper

Duncan, F., Baskin, C., McGrath, M., Coker, J. F., Lee, C., Dykxhoorn, J., Adams, E.A., Gnani, S., Lafortune, L., Kirkbride, J.B., Kaner, E., Jones, O., Samuel, G., Walters, K., Osborn, D., & Oliver, E. J. (2021). Community interventions for improving adult mental health: mapping local policy and practice in England. BMC public health, 21(1), 1-14. https://bmcpublichealth.biomedcentral.com/articles/10.1186/s12889-021-11741-5

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