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Data · dataset · 2026

Referral routes to community support; exploring the impact of social prescribing

Listed in ZivaHub and Deakin Research Online and DMU Figshare — shown once because both records carry DOI 10.17034/32826083.v1

Social prescribing (SP) is a referral mechanism connecting individuals to non-medical, community-based support services, addressing social, emotional and practical needs to promote health and wellbeing.

Description

Increasingly recognised for its potential to reduce healthcare demand, tackle social isolation and address broader determinants of health, SP offers personalised, co-designed support. However, the evidence base remains limited, constrained by variations in provision, challenges in evaluation, small sample sizes, and inconsistencies in outcome reporting.

This PhD aimed to address these gaps through rigorous longitudinal research.<br><br>The study examined SP’s impact as a referral route to community-based support through three objectives:<br>1. Conduct a scoping review of literature to define the Social Prescribing Link Worker role.<br>2. Design, pre-test and implement a survey question to capture referral routes.<br>3.

Read the rest (3 more)

Examine associations across survey outcomes for those referred via SP compared to other routes.<br><br>Stage one, following the PRISMA-ScR framework, identified four SPLW themes: collaboration with participants to set goals and monitor progress; connection to community/statutory support; holistic views of health; and the importance of training to improve referrals. The review also highlighted inconsistencies in terminology and delivery across SP, informing the survey design.<br><br>Stage two, underpinned by a pragmatic approach, employing positivist methods, analysed longitudinal survey data at baseline, one, six and 12 months from 330 individuals engaging with community-led organisations in England, Northern Ireland and Scotland.

Health and wellbeing were assessed using ICECAP-A, EQ-5D-5L, SWEMWBS and SCS-R measures. Comparative analysis explored SP versus alternative referrals, and linear mixed models tested predictive strength.<br><br>Findings showed significant improvements across all participants, with greater gains for SP referrals, most evident at 12 months. Significant time–SP interactions were observed across all measures, with ICECAP-A showing the most consistent effects.

LMMs revealed demographic factors, including disability, income, employment, retirement, and setting, influenced outcomes more strongly than the specific CLO attended.<br><br><i>Thesis is embargoed until 31 December 2026.</i>

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Where it is published

Catalogue records · 1

Topics

Inferred from text
Longitudinal study 65%
Provenance · 3 source records, 18 field assertions
SourceKeyLast seenRaw
ZivaHuboai:figshare.com:article/328260835 d agoJSON v1
Deakin Research Onlineoai:figshare.com:article/328260835 d agoJSON v1
DMU Figshareoai:figshare.com:article/328260835 d agoJSON v1
FieldAssertionExtractorEvidence
access_levelsource · zivahub uct ac zaconnector:zivahub_uct_ac_za@1.0.0
concepts[field].anzsrc:group:4206mapping · figshare dmu ac ukvocabulary-mapper@1.0.0keywords['public health']
concepts[field].anzsrc:group:4206mapping · dro deakin edu auvocabulary-mapper@1.0.0keywords['public health']
concepts[field].anzsrc:group:4206mapping · zivahub uct ac zavocabulary-mapper@1.0.0keywords['public health']
concepts[field].local:field:earth-environmentalmapping · figshare dmu ac ukconnector:figshare_dmu_ac_uk@1.0.0
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concepts[field].local:field:earth-environmentalmapping · dro deakin edu auconnector:dro_deakin_edu_au@1.0.0
concepts[field].local:field:medicine-healthmapping · zivahub uct ac zaconnector:zivahub_uct_ac_za@1.0.0
concepts[field].local:field:medicine-healthmapping · figshare dmu ac ukconnector:figshare_dmu_ac_uk@1.0.0
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concepts[field].local:field:social-sciencemapping · dro deakin edu auconnector:dro_deakin_edu_au@1.0.0
concepts[field].local:field:social-sciencemapping · zivahub uct ac zaconnector:zivahub_uct_ac_za@1.0.0
concepts[method].local:method:longitudinal-studyenrichment · zivahub uct ac zakeyword-concept-rules@1.0.0title+description (65%)
descriptionsource · zivahub uct ac zaconnector:zivahub_uct_ac_za@1.0.0/metadata/dc/description
license_textsource · zivahub uct ac zaconnector:zivahub_uct_ac_za@1.0.0
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