An evaluation of the role of social identity processes for enhancing health outcomes within <scp>UK</scp>‐based social prescribing initiatives designed to increase social connection and reduce loneliness: A systematic review
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Abstract The UK's National Health Service has introduced Social Prescribing initiatives to tackle loneliness and ill‐health, yet it lacks a theoretical foundation and evidence base for Social Prescribing's effectiveness. Recent research applies the Social Identity Approach to Health (SIAH) to explain Social Prescribing's health benefits, emphasising how social connection unlocks health‐enhancing psychological mechanisms. This systematic review therefore aims to assess UK‐based Social Prescribing programmes designed to boost social connection and alleviate loneliness, examining programme efficacy and the role of SIAH processes in health outcomes. Following PRISMA guidelines, a narrative synthesis of articles published from May 5, 2006 (when social prescribing was first introduced in the NHS), to April 8, 2024, was conducted, and their quality assessed using CONSORT‐SPI (2018). Of these programmes, 10 employed a mixed‐methods design, 8 qualitative and 1 quantitative service evaluation, totalling 3,298 participants. Results indicate that Social Prescribing's psychological value lies in quality rather than quantity of social connections, with meaningful connections fostering shared identity, perceived support and self‐efficacy, the latter of which sustains social engagement post‐programme. The SIAH was a useful tool for mapping mixed‐methods findings onto a common theoretical framework to highlight these key proponents. Overall, this review underscores the importance of SIAH‐informed Social Prescribing interventions in enhancing social connectedness, reducing loneliness, and promoting overall health. Please refer to the Supplementary Material section to find this article's Community and Social Impact Statement .
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.010 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.003 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.002 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it