Project description:BACKGROUND:Universal Credit, a welfare benefit reform in the UK, began to replace six existing benefit schemes in April, 2013, starting with the income-based Job Seekers Allowance. We aimed to determine the effects on mental health of the introduction of Universal Credit. METHODS:In this longitudinal controlled study, we linked 197 111 observations from 52 187 individuals of working age (16-64 years) in England, Wales, and Scotland who participated in the Understanding Society UK Longitudinal Household Panel Study between 2009 and 2018 with administrative data on the month when Universal Credit was introduced into the area in which each respondent lived. We included participants who had data on employment status, local authority area of residence, psychological distress, and confounding variables. We excluded individuals from Northern Ireland and people out of work with a disability. We used difference-in-differences analysis of this nationally representative, longitudinal, household survey and separated respondents into two groups: unemployed people who were eligible for Universal Credit (intervention group) and people who were not unemployed and therefore would not have generally been eligible for Universal Credit (comparison group). Using the phased roll-out of Universal Credit, we compared the change in psychological distress (self-reported via General Health Questionnaire-12) between the intervention group and the comparison group over time as the reform was introduced in the area in which each respondent lived. We defined clinically significant psychological distress as a score of greater than 3 on the General Health Questionnaire-12. We tested whether there were differential effects across subgroups (age, sex, and education). FINDINGS:The prevalence of psychological distress increased in the intervention group by 6·57 percentage points (95% CI 1·69-11·42) after the introduction of Universal Credit relative to the comparison group, after accounting for potential confounders. We estimate that between April 29, 2013, and Dec 31, 2018, an additional 63 674 (95% CI 10 042-117 307) unemployed people will have experienced levels of psychological distress that are clinically significant due to the introduction of Universal Credit; 21 760 of these individuals might reach the diagnostic threshold for depression. INTERPRETATION:Our findings suggest that the introduction of Universal Credit led to an increase in psychological distress, a measure of mental health difficulties, among those affected by the policy. Future changes to government welfare systems should be evaluated not only on a fiscal basis but on their potential to affect health and wellbeing. FUNDING:Wellcome Trust, UK National Institute for Health Research, and Medical Research Council.
Project description:Poverty has consistently been linked to poor mental health and risky health behaviors, yet few studies evaluate the effectiveness of programs and policies to address these outcomes by targeting poverty itself. We test the hypothesis that the earned income tax credit (EITC)-the largest U.S. poverty alleviation program-improves short-term mental health and health behaviors in the months immediately after income receipt. We conducted parallel analyses in two large longitudinal national data sets: the National Health Interview Survey (NHIS, 1997-2016, N = 379,603) and the Panel Study of Income Dynamics (PSID, 1985-2015, N = 29,808). Outcomes included self-rated health, psychological distress, tobacco use, and alcohol consumption. We employed difference-in-differences analysis, a quasi-experimental technique. We exploited seasonal variation in disbursement of the EITC, which is distributed as a tax refund every spring: we compared outcomes among EITC-eligible individuals interviewed immediately after refund receipt (Feb-Apr) with those interviewed in other months more distant from refund receipt (May-Jan), "differencing out" seasonal trends among non-eligible individuals. For most outcomes, we were unable to rule out the null hypothesis that there was no short-term effect of the EITC. Findings were cross-validated in both data sets. The exception was an increase in smoking in PSID, although this finding was not robust to sensitivity analyses. While we found no short-term "check effect" of the EITC on mental health and health behaviors, others have found long-term effects on these outcomes. This may be because recipients anticipate EITC receipt and smooth their income accordingly.
Project description:The US Congress temporarily expanded the Child Tax Credit (CTC) during the COVID-19 pandemic to provide economic assistance for families with children. Although formerly the CTC provided $2,000 per child for mostly middle-income parents, during July-December 2021 it provided up to $3,600 per child. Eligibility criteria were also expanded to reach more economically disadvantaged families. There has been little research evaluating the effect of the policy expansion on mental health. Using data from the Census Bureau's Household Pulse Survey and a quasi-experimental study design, we examined the effects of the expanded CTC on mental health and related outcomes among low-income adults with children, and by racial and ethnic subgroup. We found fewer depressive and anxiety symptoms among low-income adults. Adults of Black, Hispanic, and other racial and ethnic backgrounds demonstrated greater reductions in anxiety symptoms compared to non-Hispanic White adults with children. There were no changes in mental health care use. These findings are important for Congress and state legislators to weigh as they consider making the expanded CTC and other similar tax credits permanent to support economically disadvantaged families.
Project description:Background:Patient and Public Involvement (PPI) in research is a growing field of work, incorporating experiential knowledge within research processes. Co-production is a more recent PPI approach that emphasises the importance of power-sharing to promote inclusive research practices, valuing and respecting knowledge from different sources, and relationship building. Applying co-production principles in research trials can be difficult, and there are few detailed worked examples or toolkits. This paper explores the successes and challenges encountered by one research team. Methods:Our paper is written by a team of 21 people working on PARTNERS2, led by a smaller co-ordinating group. Using a co-operative style inquiry, the authors have reflected on and written about their experiences; analysis of the resulting 15 accounts provided examples of how PPI and co-production were delivered in practice. Results:We reveal varied and complicated experiences as we developed our collaborative approach across the entire research programme. Four main themes emerge from reflective accounts which describe aspects of this process: (1) recognising the importance of 'emotional work'; (2) developing safe spaces to create and share knowledge; (3) some challenges of using our personal identities in research work; and (4) acknowledging power-sharing within the research hierarchy. We also found continual relationship building, how different forms of expertise were valued, and stigma were central to shaping what work was possible together. Other important practices were transparency, particularly over decision making, and clear communication. Conclusions:Our work provides one example of the 'messy' nature of collaborative research in practice. The learning we surface was contextual, generated within a large-scale research programme, but applicable to other studies. We found for success there needs to be an acknowledgement of the importance of emotional work, creating safe spaces to co-produce, transparency in decision making and reflection on the difficulties of using personal identities in research work including for service user researchers. These elements are more important than existing guidelines suggest. Implementation of actions to support emotional work, will require changes within individual teams as well as institutions. Introducing reflective practice in teams may be helpful in identifying further improvements to inclusive research practice.
Project description:•Using migration of Venezuelans to Peru as a case example, we surveyed migrants on mental health and migration factors at the Ecuador-Peru border.•Pre-migration: No factors associated with anxiety; choosing Peru for safety or expected respect for Venezuelans increased odds of depression.•Migration: Walking and education increased odds of anxiety; choosing Peru decreased odds of anxiety; being pregnant increased odds of depression.•Link between migration factors and mental health is concerning, as the associated distress may influence post-migration mental health.•More work is needed to understand the influence of the journey on the mental health outcomes of migrants over time.
Project description:This conceptual paper describes the current state of mental health services, identifies critical problems, and suggests how to solve them. I focus on the potential contributions of artificial intelligence and precision mental health to improving mental health services. Toward that end, I draw upon my own research, which has changed over the last half century, to highlight the need to transform the way we conduct mental health services research. I identify exemplars from the emerging literature on artificial intelligence and precision approaches to treatment in which there is an attempt to personalize or fit the treatment to the client in order to produce more effective interventions.
Project description:People with lived experience of mental health challenges are extensively employed as peer workers within mental health and substance use services worldwide. Research shows that peer workers benefit individuals using such services and can have essential roles in developing recovery-oriented services. However, understanding how peer workers' contributions, by their role, functions, and input can be better used remains a critical challenge. Research on public sector innovation has focused on relevant actors collaborating to tackle complex demands. Co-production and co-creation are concepts used to describe this collaboration. Co-production refers to the collaboration between providers and users at the point of service delivery, whereas co-creation refers to collaboration starting in the early service cycle phases (e.g., in commissioning or design), including solution implementation. We overviewed research literature describing peer workers' involvement in mental health and substance use services. The research question is as follows: How are peer workers involved in co-production and co-creation in mental health and substance use services, and what are the described outcomes? A literature search was performed in 10 different databases, and 13,178 articles were screened, of which 172 research articles describing peer workers' roles or activities were included. The findings show that peer workers are involved in co-production and function as providers of pre-determined services or, most often, as providers of peer support. However, they are rarely engaged as partners in co-creation. We conclude that the identified peer worker roles have different potential to generate input and affect service delivery and development.
Project description:Background:People with mental disorders in low-income countries are at risk of being left behind during efforts to expand universal health coverage. Aims:To propose context-relevant strategies for moving towards universal health coverage for people with mental disorders in Ethiopia. Methods:We conducted a situational analysis to inform a SWOT analysis of coverage of mental health services and financial risk protection, health system characteristics and the macroeconomic and fiscal environment. In-depth interviews were conducted with five national experts on health financing and equity and analysed using a thematic approach. Findings from the situation analysis and qualitative study were used to develop recommended strategies for adequate, fair and sustainable financing of mental health care in Ethiopia. Results:Opportunities for improved financing of mental health care identified from the situation analysis included: a significant mental health burden with evidence from strong local epidemiological data; political commitment to address that burden; a health system with mechanisms for integrating mental health into primary care; and a favourable macro-fiscal environment for investment in human capabilities. Balanced against this were constraints of low current general government health expenditure, low numbers of mental health specialists, weak capacity to plan and implement mental health programmes and low population demand for mental health care. All key informants referred to the under-investment in mental health care in Ethiopia. Respondents emphasised opportunities afforded by positive rates of economic growth in the country and the expansion of community-based health insurance, as well as the need to ensure full implementation of existing task-sharing programmes for mental health care, integrate mental health into other priority programmes and strengthen advocacy to ensure mental health is given due attention. Conclusion:Expansion of public health insurance, leveraging resources from high-priority SDG-related programmes and implementing existing plans to support task-shared mental health care are key steps towards universal health coverage for mental disorders in Ethiopia. However, external donors also need to deliver on commitments to include mental health within development funding. Future researchers and planners can apply this approach to other countries of sub-Saharan Africa and identify common strategies for sustainable and equitable financing of mental health care.
Project description:Universal mental health screening in pediatric primary care is recommended, but studies report slow uptake and low rates of patient follow-through after referral to specialized services. This review examined possible explanations related to the process of screening, focusing on how parents and youth are engaged, and how providers evaluate and use screening results.A narrative synthesis was developed after a systematic review of 3 databases (plus follow-up of citations, expert recommendations, and checks for multiple publications about the same study). Searching identified 1,188 titles, and of these, 186 full-text articles were reviewed. Two authors extracted data from 45 articles meeting inclusion criteria.Published studies report few details about how mental health screens were administered, including how clinicians explain their purpose or confidentiality, or whether help was provided for language, literacy, or disability problems. Although they were not addressed directly in the studies reviewed, uptake and detection rates appeared to vary with means of administration. Screening framed as universal, confidential, and intended to optimize attention to patient concerns increased acceptability. Studies said little about how providers were taught to explore screen results. Screening increased referrals, but many still followed negative screens, in some cases because of parent concerns apparently not reflected by screen results but possibly stemming from screen-prompted discussions.Little research has addressed the process of engaging patients in mental health screening in pediatric primary care or how clinicians can best use screening results. The literature does offer suggestions for better clinical practice and research that may lead to improvements in uptake and outcome.
Project description:ObjectivePrevious research has demonstrated that individual risk of mental illness is associated with individual, co-resident, and household risk factors. However, modelling the overall effect of these risk factors presents several methodological challenges. In this study we apply a multilevel structural equation model (MSEM) to address some of these challenges and the impact of the different determinants when measuring mental health risk.Study design and settingTwo thousand, one hundred forty-three individuals aged 16 and over from 888 households were analysed based on the Household Survey for England-2014 dataset. We applied MSEM to simultaneously measure and identify psychiatric morbidity determinants while accounting for the dependency among individuals within the same household and the measurement errors.ResultsYounger age, female gender, non-working status, headship of the household, having no close relationship with other people, having history of mental illness and obesity were all significant (p < 0.01) individual risk factors for psychiatric morbidity. A previous history of mental illness in the co-residents, living in a deprived household, and a lack of closeness in relationships among residents were also significant predictors. Model fit indices showed a very good model specification (CFI = 0.987, TLI = 0.980, RMSEA = 0.023, GFI = 0.992).ConclusionMeasuring and addressing mental health determinants should consider not only an individual's characteristics but also the co-residents and the households in which they live.