Search

Within the context of scientific research, patient and public involvement (PPI) is defined as research performed "with" or "by" patients and members of the public, rather than "to," "about", or "for" them. When carried out systematically and thoughtfully, PPI has the potential to strengthen the quality and impact of research by fostering accountability, transparency, and relevance. There exist numerous guidelines, frameworks and tools for supporting PPI, however, these do not account for the unique challenges faced in psychedelic research. This paper describes the co-design of guidance intended to help build, evaluate and improve PPI in psychedelic research. A steering group was formed to design and run a co-design workshop alongside public collaborators. Insights from this workshop were analyzed and refined into a comprehensive and readily usable guide for planning PPI specific to the field of psychedelic research. Core values emerging from the process focused on the essential importance of trust, learning, purpose and inclusivity. It is hoped that this guidance will be a starting point for incorporating PPI in future psychedelic research, so that it can grow and adapt as this burgeoning field of research progresses.

Objectives: We undertook a national analysis to characterise and identify risk factors for acute respiratory infections (ARIs) resulting in hospitalisation during the winter period in Scotland. Design: A population-based retrospective cohort analysis. Setting: Scotland. Participants: The study involved 5.4 million residents in Scotland. Main outcome measures: Cox proportional hazard models were used to estimate adjusted hazard ratios (aHRs) and 95% confidence intervals (CIs) for the association between risk factors and ARI hospitalisation. Results: Between 1 September 2022 and 31 January 2023, there were 22,284 (10.9% of 203,549 with any emergency hospitalisation) ARI hospitalisations (1759 in children and 20,525 in adults) in Scotland. Compared with the reference group of children aged 6–17 years, the risk of ARI hospitalisation was higher in children aged 3–5 years (aHR = 4.55; 95% CI: 4.11–5.04). Compared with those aged 25–29 years, the risk of ARI hospitalisation was highest among the oldest adults aged ≥80 years (aHR = 7.86; 95% CI: 7.06–8.76). Adults from more deprived areas (most deprived vs. least deprived, aHR = 1.64; 95% CI: 1.57–1.72), with existing health conditions (≥5 vs. 0 health conditions, aHR = 4.84; 95% CI: 4.53–5.18) or with history of all-cause emergency admissions (≥6 vs. 0 previous emergency admissions, aHR = 7.53; 95% CI: 5.48–10.35) were at a higher risk of ARI hospitalisations. The risk increased by the number of existing health conditions and previous emergency admission. Similar associations were seen in children. Conclusions: Younger children, older adults, those from more deprived backgrounds and individuals with greater numbers of pre-existing conditions and previous emergency admission were at increased risk for winter hospitalisations for ARI. [ABSTRACT FROM AUTHOR]

Background We compared the quality of ethnicity coding within the Public Health Scotland Ethnicity Look-up (PHS-EL) dataset, and other National Health Service datasets, with the 2011 Scottish Census. Methods Measures of quality included the level of missingness and misclassification. We examined the impact of misclassification using Cox proportional hazards to compare the risk of severe coronavirus disease (COVID-19) (hospitalization & death) by ethnic group. Results Misclassification within PHS-EL was higher for all minority ethnic groups [12.5 to 69.1%] compared with the White Scottish majority [5.1%] and highest in the White Gypsy/Traveller group [69.1%]. Missingness in PHS-EL was highest among the White Other British group [39%] and lowest among the Pakistani group [17%]. PHS-EL data often underestimated severe COVID-19 risk compared with Census data. e.g. in the White Gypsy/Traveller group the Hazard Ratio (HR) was 1.68 [95% Confidence Intervals (CI): 1.03, 2.74] compared with the White Scottish majority using Census ethnicity data and 0.73 [95% CI: 0.10, 5.15] using PHS-EL data; and HR was 2.03 [95% CI: 1.20, 3.44] in the Census for the Bangladeshi group versus 1.45 [95% CI: 0.75, 2.78] in PHS-EL. Conclusions Poor quality ethnicity coding in health records can bias estimates, thereby threatening monitoring and understanding ethnic inequalities in health. [ABSTRACT FROM AUTHOR]

Introduction: Associations between structural inequalities and health are well established. However, there is limited work examining this link in relation to mental health, or that centres public perspectives. This study explores people's experience and sense‐making of inequality in their daily lives, with particular consideration of impacts on mental health. Methods: We conducted a peer research study. Participants had to live in one of two London Boroughs and have an interest in inequalities and mental health. Using social media, newsletters, local organisations and our peer researchers' contacts, we recruited 30 participants who took photos representing their experience of inequality and discussed them during semi‐structured interviews. Data were analysed using reflexive thematic analysis. Results: Three themes were identified in this study: (1) inequalities are unjust, multilayered and intertwined with mental health. Accounts demonstrated a deep understanding of inequalities and their link to mental health outcomes, describing inequalities as 'suffering' and 'not good for anyone'. Financial, housing, immigration and healthcare problems exacerbated poor mental health, with racism, gender‐based violence and job loss also contributing factors for both poor mental health and experiences of inequality; (2) inequalities exclude and have far‐reaching mental health consequences, impacting personal sense of belonging and perceived societal value and (3) moving forwards—addressing long‐standing inequality and poor public mental health necessitated coping and resilience strategies that are often unacknowledged and undervalued by support systems. Conclusion: Lived experience expertise was central in this study, creating an innovative methodological approach. To improve public mental health, we must address the everyday, painful structural inequalities experienced by many as commonplace and unfair. New policies and strategies must be found that involve communities, redistributing resources and power, building on a collective knowledge base, to coproduce actions combatting inequalities and improving population mental health. Patient or Public Contribution: This study was peer‐led, designed and carried out by researchers who had experiences of poor mental health. Six authors of the paper worked as peer researchers on this study. [ABSTRACT FROM AUTHOR]