Hostname: page-component-89b8bd64d-r6c6k Total loading time: 0 Render date: 2026-05-08T15:58:51.401Z Has data issue: false hasContentIssue false

Equal, equitable or exacerbating inequalities: patterns and predictors of social prescribing referrals in 160 128 UK patients

Published online by Cambridge University Press:  11 November 2024

Feifei Bu
Affiliation:
Department of Behavioural Science and Health, Institute of Epidemiology & Health Care, University College London, London, UK
Daniel Hayes
Affiliation:
Department of Behavioural Science and Health, Institute of Epidemiology & Health Care, University College London, London, UK
Alexandra Burton
Affiliation:
Department of Behavioural Science and Health, Institute of Epidemiology & Health Care, University College London, London, UK
Daisy Fancourt*
Affiliation:
Department of Behavioural Science and Health, Institute of Epidemiology & Health Care, University College London, London, UK
*
Correspondence: Daisy Fancourt. Email: d.fancourt@ucl.ac.uk
Rights & Permissions [Opens in a new window]

Abstract

Background

Social prescribing is growing rapidly globally as a way to tackle social determinants of health. However, whom it is reaching and how effectively it is being implemented remains unclear.

Aims

To gain a comprehensive picture of social prescribing in the UK, from referral routes, reasons, to contacts with link workers and prescribed interventions.

Method

This study undertook the first analyses of a large database of administrative data from over 160 000 individuals referred to social prescribing across the UK. Data were analysed using descriptive analyses and regression modelling, including logistic regression for binary outcomes and negative binomial regression for count variables.

Results

Mental health was the most common referral reason and mental health interventions were the most common interventions prescribed. Between 72% and 85% of social prescribing referrals were from medical routes (primary or secondary healthcare). Although these referrals demonstrated equality in reaching across sociodemographic groups, individuals from more deprived areas, younger adults, men, and ethnic minority groups were reached more equitably via non-medical routes (e.g. self-referral, school, charity). Despite 90% of referrals leading to contact with a link worker, only 38% resulted in any intervention being received. A shortage of provision of community activities – especially ones relevant to mental health, practical support and social relationships – was evident. There was also substantial heterogeneity in how social prescribing is implemented across UK nations.

Conclusions

Mental health is the leading reason for social prescribing referrals, demonstrating its relevance to psychiatrists. But there are inequalities in referrals. Non-medical referral routes could play an important role in addressing inequality in accessing social prescribing and therefore should be prioritised. Additionally, more financial and infrastructural resource and strategic planning are needed to address low intervention rates. Further investment into large-scale data platforms and staff training are needed to continue monitoring the development and distribution of social prescribing.

Information

Type
Original Article
Creative Commons
Creative Common License - CCCreative Common License - BY
This is an Open Access article, distributed under the terms of the Creative Commons Attribution licence (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted re-use, distribution and reproduction, provided the original article is properly cited.
Copyright
Copyright © The Author(s), 2024. Published by Cambridge University Press on behalf of Royal College of Psychiatrists
Figure 0

Fig. 1 Sociodemographic characteristics of unique individuals by country. (a) Gender; (b) age groups; (c) urbanicity; (d) Index of Multiple Deprivation.

Figure 1

Fig. 2 Odds ratios and 95% confidence intervals from the logistic regression model on being referred via medical routes by country. (a) England; (b) Wales and (c) Scotland. IMD, Index of Multiple Deprivation.

Figure 2

Table 1 Summary of key differences across countries from regression analyses

Figure 3

Fig. 3 Referral reasons (a) percentage of cases with referral reasons from each domain and (b) percentages of cases with reasons from one or more different domain for each domain.

Figure 4

Fig. 4 Intervention domains (a) among cases with an intervention, percentage of cases belong to each domain and (b) percentages of cases receiving an intervention matched to referral reason in each referral reason domain.

Supplementary material: File

Bu et al. supplementary material

Bu et al. supplementary material
Download Bu et al. supplementary material(File)
File 3.5 MB

This journal is not currently accepting new eletters.

eLetters

No eLetters have been published for this article.