Developing a toolkit for increasing the participation of black, Asian and minority ethnic communities in health and social care research.

BACKGROUND: It is recognised that Black, Asian and Minority Ethnic (BAME) populations are generally underrepresented in research studies. The key objective of this work was to develop an evidence based, practical toolkit to help researchers maximise recruitment of BAME groups in research. METHODS: Development of the toolkit was an iterative process overseen by an expert steering group. Key steps included a detailed literature review, feedback from focus groups (including researchers and BAME community members) and further workshops and communication with participants to review the draft and final versions. RESULTS: Poor recruitment of BAME populations in research is due to complex reasons, these include factors such as inadequate attention to recruitment strategies and planning, poor engagement with communities and individuals due to issues such as cultural competency of researchers, historical poor experience of participating in research, and lack of links with community networks. Other factors include language issues, relevant expertise in research team and a lack of adequate resources that might be required in recruitment of BAME populations. CONCLUSIONS: A toolkit was developed with key sections providing guidance on planning research and ensuring adequate engagement of communities and individuals. Together with sections suggesting how the research team can address training needs and adopt best practice. Researchers highlighted the issue of funding and how best to address BAME recruitment in grant applications, so a section on preparing a grant application was also included. The final toolkit document is practical, and includes examples of best practice and 'top tips' for researchers.

Lessons from the field: The role of agility in a coproduction project encompassing the COVID-19 pandemic.

AIM: We reflect on our experiences of coproducing a redesigned, COVID-safe priority-setting activity at a time of shifting priorities and upheaval to gain insight into good practice. METHOD: The project team documented the experience of adapting to COVID-19 through the reflective project evaluation. We reflect on how COVID disrupted coproduction through radically shifting personal and professional priorities and the implications for good practice. RESULTS: Our experiences highlighted the role of agility, management capacity, social capital and power in coproduction. CONCLUSIONS: COVID-19 disrupted and enabled coproduction, compounding tensions and serving as the basis to transcend them. The pandemic created new demands on institutions that initially prompted withdrawal to established power, and team members which redefined them in relation to each other. Shifting priorities and demands forced team members into new, and out of former, roles coming into conflict with enduring power dynamics articulating constructs of expertise and authority in the institutional structure. We consider how the tensions found expression: as governance and human resource concerns, problems with authorizing payments, challenges in institutionally accommodating community researchers and the exclusion of some from participation.

Predicting temporal trends in total absenteeism rates for civil service employees of a federal public health agency.

OBJECTIVE: This study evaluates the predictability in temporal absences trends due to all causes (total absenteeism) among employees at a federal agency. The objective is to determine how leave trends vary within the year, and determine whether trends are predictable. METHODS: Ten years of absenteeism data from an attendance system were analyzed for rates of total absence. RESULTS: Trends over a 10-year period followed predictable and regular patterns during a given year that correspond to major holiday periods. Temporal trends in leave among small, medium, and large facilities compared favorably with the agency as a whole. CONCLUSIONS: Temporal trends in total absenteeism rates for an organization can be determined using its attendance system. The ability to predict employee absenteeism rates can be extremely helpful for management in optimizing business performance and ensuring that an organization meets its mission.

Predicting temporal trends in sickness absence rates for civil service employees of a federal public health agency.

OBJECTIVE: To determine whether trends of sickness in employees at a federal agency are predictable, and whether the variance was minimal enough to detect unusual levels of employee illness for further investigation. METHODS: Ten years of absenteeism data from an attendance system were analyzed for rates of sickness absence. Specifically, week of year and day of week were used to describe temporal trends. RESULTS: This study evaluates the predictability in temporal absence trends due to sickness among employees at a federal agency. Trends follow regular patterns during a given year that correspond to seasonal illnesses. Temporal trends in sick leave have been proven to be very predictable. CONCLUSION: The minimal variance allows the detection of sick leave anomalies that may be ascribable to specific causes, allowing the business or agency to follow-up and develop interventions.