ArticleBMJ open2022
Evaluation of the mental health impacts of Universal Credit: protocol for a mixed methods study.
Article in BMJ open, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers, 1 of them a synthesis that pooled it.
What it found
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
4 citing papers in PubMed, 1 synthesis or guideline pooled it.
- Mental Health and Mental Wellbeing Impact Assessment Frameworks-A Systematic Review.International journal of environmental research and public health · 2022Pooled it
- Impacts of the Universal Credit welfare reform on well-being: a natural experiment study using UK population survey data.BMJ public health · 2026Article
- Using natural experiments to evaluate population health and health system interventions: new framework for producers and users of evidence.BMJ (Clinical research ed.) · 2025Article
- Exploring the health and sociodemographic characteristics of people seeking advice with claiming universal credit: a cross-sectional analysis of UK citizens advice data, 2017-2021.BMC public health · 2023Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
16 authors.
Funding
Abstract
introductionThe UK social security system is being transformed by the implementation of Universal Credit (UC), which combines six existing benefits and tax credits into a single payment for low-income households. Despite extensive reports of hardship associated with the introduction of UC, no previous studies have comprehensively evaluated its impact on mental health. Because payments are targeted at low-income households, impacts on mental health will have important consequences for health inequalities. METHODS AND ANALYSIS: We will conduct a mixed methods study. Work package (WP) 1 will compare health outcomes for new recipients of UC with outcomes for legacy benefit recipients in two large population surveys, using the phased rollout of UC as a natural experiment. We will also analyse the relationship between the proportion of UC claimants in small areas and a composite measure of mental health. WP2 will use data collected by Citizen's Advice to explore the sociodemographic and health characteristics of people who seek advice when claiming UC and identify features of the claim process that prompt advice-seeking. WP3 will conduct longitudinal in-depth interviews with up to 80 UC claimants in England and Scotland to explore reasons for claiming and experiences of the claim process. Up to 30 staff supporting claimants will also be interviewed. WP4 will use a dynamic microsimulation model to simulate the long-term health impacts of different implementation scenarios. WP5 will undertake cost-consequence analysis of the potential costs and outcomes of introducing UC and cost-benefit analyses of mitigating actions. ETHICS AND DISSEMINATION: We obtained ethical approval for the primary data gathering from the University of Glasgow, College of Social Sciences Research Ethics Committee, application number 400200244. We will use our networks to actively disseminate findings to UC claimants, the public, practitioners and policy-makers, using a range of methods and formats. TRIAL REGISTRATION NUMBER: The study is registered with the Research Registry: researchregistry6697.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.