Count me in: an inclusive approach towards patient recruitment for clinical research studies in the NHS

Background: Participation in clinical research is associated with better patient outcomes and higher staff retention and satisfaction rates. Nevertheless, patient recruitment to mental health studies is challenging due to a reliance on clinician or patient referrals (standard approach). To empower patients and make healthcare research more equitable, we explored a novel researcher-led approach, called ‘Count Me In’ (CMI). Objective: To evaluate a 12-month implementation of CMI in a routine clinical setting. Methods: CMI was launched in August 2021 in a mental health National Health Service (NHS) Trust in England. Patients (aged 18+) learnt about CMI at their initial clinical appointment. Unless they opted out, they became contactable for research (via research informatics searches). Findings: After 12 months, 368 patients opted out and 22 741 became contactable through CMI, including 2716 through the standard approach and 20 025 through electronic searches (637% increase). Of those identified via electronic searches, 738 were contacted about specific studies and 270 consented to participate. Five themes were identified based on patient and staff experiences of CMI: ‘level of awareness and accessibility of CMI’, ‘perceptions of research and perceived engagement with CMI’, ‘inclusive research practice’, ‘engagement and incentives for research participation’, and ‘relationships between clinical and research settings’. Conclusions: CMI (vs standard) led to a larger and diverse patient cohort and was favoured by patients and staff. Yet a shift in the NHS research culture is needed to ensure that this diversity translates to actual research participation. Clinical implications: Through collaboration with other NHS Trusts and services, key funders (National Institute for Health and Care Research) and new national initiatives (Office for Life Sciences Mental Health Mission), CMI has the potential to address recruitment challenges through rapid patient recruitment into time-sensitive country-wide studies

Basic Income in the UK:Assessing Prospects for Reform in an Age of Austerity

Of all the European welfare states, the UK most clearly represents the liberal regime type - notwithstanding a shift towards 'social investment' under New Labour - as defined by its residual, targeted benefit structure and increasingly punitive activation regime. The idiosyncratic institutional characteristics of the UK welfare state give rise to challenges and opportunities with respect to prospects for the introduction of (some form of) basic income. Despite a large and growing population of 'disaffected' precarious and low-paid workers and widespread dissatisfaction with the increasingly punitive sanctions regime, significant barriers to the emergence of a sufficiently large and coherent constituency of support for basic income remain. Thus, while institutional inertia and political considerations may preclude anything more than marginal changes to the existing system, a number of policy options falling short of a 'full' basic income - but retaining some of its core features - appear relatively feasible.</p

Informing National Health Service patients about participation in clinical research: A comparison of opt-in and opt-out approaches across the United Kingdom

Objective: Recruitment to clinical research in the NHS remains challenging. One barrier is accessing patients to discuss research participation. Two general approaches are used in the UK to facilitate this: an ‘opt-in’ approach (when clinicians communicate research opportunities to patients) and an ‘opt-out’ approach (all patients have the right to be informed of relevant research opportunities). No evidence-based data are available, however, to inform the decision about which approach is preferable. This study aimed to collect information from ‘opt-in’ and ‘opt-out’ Trusts and identify which of the two approaches is optimal for ensuring NHS patients are given opportunities to discuss research participation. Method: This sequential mixed methods study comprised three phases: (1) an Appreciative Inquiry across UK Trusts, and (2) online surveys and (3) focus groups with NHS staff and patients at a representative mental health Trust. Results: The study was conducted between June and October 2019. Out of seven NHS Mental Health Trusts contacted (three ‘opt-out’ and four ‘opt-in’), only four took part in phase 1 of the study and three of them were ‘opt-out’ Trusts. Benefits of an ‘opt-out’ approach included greater inclusivity of patients and the removal of research gatekeepers, whilst the involvement of research-active clinicians and established patient-clinician relationships were cited as important to ‘opt-in’ success. Phase 2 and 3 were conducted at a different Trust (Oxford Health NHS Foundation Trust, OHNHSFT) which was using an ‘opt-in’ approach. Of 333 staff and member survey responders, 267 (80.2%) favoured moving to an ‘opt-out’ approach (phase 2). Nineteen staff and 16 patients and carers participated in focus groups (phase 3). Concern was raised by staff regarding the lack of time for clinical research, with clinical work taking precedence over research; patients were concerned about a lack of research activity; all considered research to be beneficial and were supportive of a move to ‘opt-out’. Conclusion: Findings suggest that ‘opt-out’ is more beneficial than ‘opt-in’, with the potential to vastly increase patient access to research opportunities and to enable greater equality of information provision for currently marginalised groups. This should ensure that healthcare research is more representative of the entire population, including those with a mental health diagnosis

Count me in : an inclusive approach towards patient recruitment for clinical research studies in the NHS

Background. Participation in clinical research is associated with better patient outcomes and higher staff retention and satisfaction rates. Nevertheless, patient recruitment to mental health studies is challenging due to a reliance on clinician or patient referrals (standard approach). To empower patients and make healthcare research more equitable, we explored a novel researcher-led approach, called ‘Count Me In’ (CMI). Objective. To evaluate a 12-month implementation of CMI in a routine clinical setting. Methods. CMI was launched in August 2021 in a mental health National Health Service (NHS) Trust in England. Patients (aged 18+) learnt about CMI at their initial clinical appointment. Unless they opted out, they became contactable for research (via research informatics searches). Findings. After 12 months, 368 patients opted out and 22 741 became contactable through CMI, including 2716 through the standard approach and 20 025 through electronic searches (637% increase). Of those identified via electronic searches, 738 were contacted about specific studies and 270 consented to participate. Five themes were identified based on patient and staff experiences of CMI: ‘level of awareness and accessibility of CMI’, ‘perceptions of research and perceived engagement with CMI’, ‘inclusive research practice’, ‘engagement and incentives for research participation’, and ‘relationships between clinical and research settings’. Conclusions. CMI (vs standard) led to a larger and diverse patient cohort and was favoured by patients and staff. Yet a shift in the NHS research culture is needed to ensure that this diversity translates to actual research participation. Clinical implications. Through collaboration with other NHS Trusts and services, key funders (National Institute for Health and Care Research) and new national initiatives (Office for Life Sciences Mental Health Mission), CMI has the potential to address recruitment challenges through rapid patient recruitment into time-sensitive country-wide studies

Impact of COVID-19 on telepsychiatry at the service and individual patient level across two UK NHS mental health trusts

Background. The effects of COVID-19 on the shift to remote consultations remain to be properly investigated. Objective. To quantify the extent, nature and clinical impact of the use of telepsychiatry during the COVID-19 pandemic and compare it with the data in the same period of the 2 years before the outbreak. Methods. We used deidentified electronic health records routinely collected from two UK mental health Foundation Trusts (Oxford Health (OHFT) and Southern Health (SHFT)) between January and September in 2018, 2019 and 2020. We considered three outcomes: (1) service activity, (2) in-person versus remote modalities of consultation and (3) clinical outcomes using Health of the Nation Outcome Scales (HoNOS) data. HoNOS data were collected from two cohorts of patients (cohort 1: patients with ≥1 HoNOS assessment each year in 2018, 2019 and 2020; cohort 2: patients with ≥1 HoNOS assessment each year in 2019 and 2020), and analysed in clusters using superclasses (namely, psychotic, non-psychotic and organic), which are used to assess overall healthcare complexity in the National Health Service. All statistical analyses were done in Python. Findings. Mental health service activity in 2020 increased in all scheduled community appointments (by 15.4% and 5.6% in OHFT and SHFT, respectively). Remote consultations registered a 3.5-fold to 6-fold increase from February to June 2020 (from 4685 to a peak of 26 245 appointments in OHFT and from 7117 to 24 987 appointments in SHFT), with post-lockdown monthly averages of 23 030 and 22 977 remote appointments/month in OHFT and SHFT, respectively. Video consultations comprised up to one-third of total telepsychiatric services per month from April to September 2020. For patients with dementia, non-attendance rates at in-person appointments were higher than remote appointments (17.2% vs 3.9%). The overall HoNOS cluster value increased only in the organic superclass (clusters 18–21, n=174; p<0.001) from 2019 to 2020, suggesting a specific impact of the COVID-19 pandemic on this population of patients. Conclusions and clinical implications. The rapid shift to remote service delivery has not reached some groups of patients who may require more tailored management with telepsychiatry

The Plankton Lifeform Extraction Tool: a digital tool to increase the discoverability and usability of plankton time-series data

Publication history: Accepted - 25 October 2021; Published online - 6 December 2021.Plankton form the base of the marine food web and are sensitive indicators of environmental change. Plankton time series are therefore an essential part of monitoring progress towards global biodiversity goals, such as the Convention on Biological Diversity Aichi Targets, and for informing ecosystem-based policy, such as the EU Marine Strategy Framework Directive. Multiple plankton monitoring programmes exist in Europe, but differences in sampling and analysis methods prevent the integration of their data, constraining their utility over large spatio-temporal scales. The Plankton Lifeform Extraction Tool brings together disparate European plankton datasets into a central database from which it extracts abundance time series of plankton functional groups, called “lifeforms”, according to shared biological traits. This tool has been designed to make complex plankton datasets accessible and meaningful for policy, public interest, and scientific discovery. It allows examination of large-scale shifts in lifeform abundance or distribution (for example, holoplankton being partially replaced by meroplankton), providing clues to how the marine environment is changing. The lifeform method enables datasets with different plankton sampling and taxonomic analysis methodologies to be used together to provide insights into the response to multiple stressors and robust policy evidence for decision making. Lifeform time series generated with the Plankton Lifeform Extraction Tool currently inform plankton and food web indicators for the UK's Marine Strategy, the EU's Marine Strategy Framework Directive, and for the Convention for the Protection of the Marine Environment of the North-East Atlantic (OSPAR) biodiversity assessments. The Plankton Lifeform Extraction Tool currently integrates 155 000 samples, containing over 44 million plankton records, from nine different plankton datasets within UK and European seas, collected between 1924 and 2017. Additional datasets can be added, and time series can be updated. The Plankton Lifeform Extraction Tool is hosted by The Archive for Marine Species and Habitats Data (DASSH) at https://www.dassh.ac.uk/lifeforms/ (last access: 22 November 2021, Ostle et al., 2021). The lifeform outputs are linked to specific, DOI-ed, versions of the Plankton Lifeform Traits Master List and each underlying dataset.Funding that supports this work and the data collected has come from the European Commission, European Union (EU) grant no. 11.0661/2015/712630/SUB/ENVC.2 OSPAR; UK Natural Environment Research Council (grant nos. NE/R002738/1 and NE/M007855/1); EMFF, Climate Linked Atlantic Sector Science (grant no. NE/R015953/1), Department for Environment, Food and Rural Affairs, UK Government (grant nos. ME-5308 and ME-414135), NSF USA OCE-1657887, DFO CA F5955150026/001/HAL, Natural Environment Research Council UK (grant no. NC-R8/H12/100); Horizon 2020 (MISSION ATLANTIC (grant no. 862428)); iCPR (grant no. SBFF-2019-36526), IMR Norway; DTU Aqua Denmark; and the French Ministry of Environment, Energy, and the Sea (MEEM). Recent funding for the development of PLET and the Pelagic Habitats Indicator has been provided by HBDSEG/Defra and MMO/EMFF. The MSS Scottish Coastal Observatory data and analyses are funded and maintained by the Scottish Government Schedules of Service (grant nos. ST05a and ST02H), MSS Stonehaven Samplers, North Atlantic Fisheries College, Shetland, Orkney Islands Harbour Council, and Isle Ewe Shellfish