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Introduction - Despite extensive debate surrounding mental health services in the UK, there is little empirical evidence regarding the views of those who use them. We therefore used data collected as part of a wider survey to examine satisfaction amongst those seeking treatment from mental and physical health services. Methods - An online survey designed with input from people with experience of mental illness was used to measure satisfaction with NHS mental and physical health services at first contact and in the previous 12 months. Results - A total of 2187 people responded. During the 12 months prior to the survey, 526 respondents had sought mental health care and 1379 had sought physical health care. Participants were significantly more satisfied with their most recent contact with mental health services (48.1% very/satisfied) than with their first contact (38.2% very/satisfied). More than 1 in 10 respondents who sought mental health care (11.4%) stated that they received no treatment/support from the NHS, compared to approximately 1 in 20 respondents who sought physical health care (4.6%). Of those who received the mental health treatment they requested (n = 424), most were satisfied or very satisfied with their care (54.7%), although this was lower than the corresponding figure (77.9%) for satisfaction with physical health care received (n = 1190). Conclusion -There was evidence that mental health services are satisfactory for a slim majority of users, but people were generally more satisfied with NHS physical health care. This survey was conducted in the year prior to the coronavirus disease 2019 pandemic. Future research could examine what influences satisfaction with care and whether this picture has changed following the emergence of the pandemic and consequent impact on health service delivery and daily life.
RESUMO
Background: Mental health research is commonly affected by difficulties in recruiting and retaining participants, resulting in findings which are based on a sub-sample of those actually living with mental illness. Increasing the use of Big Data for mental health research, especially routinely-collected data, could improve this situation. However, steps to facilitate this must be enacted in collaboration with those who would provide the data - people with mental health conditions. Methods: We used the Delphi method to create a best practice checklist for mental health data science. Twenty participants with both expertise in data science and personal experience of mental illness worked together over three phases. In Phase 1, participants rated a list of 63 statements and added any statements or topics that were missing. Statements receiving a mean score of 5 or more (out of 7) were retained. These were then combined with the results of a rapid thematic analysis of participants' comments to produce a 14-item draft checklist, with each item split into two components: best practice now and best practice in the future. In Phase 2, participants indicated whether or not each item should remain in the checklist, and items that scored more than 50% endorsement were retained. In Phase 3 participants rated their satisfaction with the final checklist. Results: The final checklist was made up of 14 "best practice" items, with each item covering best practice now and best practice in the future. At the end of the three phases, 85% of participants were (very) satisfied with the two best practice checklists, with no participants expressing dissatisfaction. Conclusions: Increased stakeholder involvement is essential at every stage of mental health data science. The checklist produced through this work represents the views of people with experience of mental illness, and it is hoped that it will be used to facilitate trustworthy and innovative research which is inclusive of a wider range of individuals.
RESUMO
Background: The UK hosts some of the world's longest-running longitudinal cohort studies, which make repeated observations of their participants and use these data to explore health outcomes. An alternative method for data collection is record linkage; the linking together of electronic health and administrative records. Applied nationally, this could provide unrivalled opportunities to follow a large number of people in perpetuity. However, public attitudes to the use of data in research are currently unclear. Here we report on an event where we collected attitudes towards recent opportunities and controversies within health data science. Methods: The event was attended by ~250 individuals (cohort members and their guests), who had been invited through the offices of their participating cohort studies. There were a series of presentations describing key research results and the audience participated in 15 multiple-choice questions using interactive voting pads. Results: Our participants showed a high level of trust in researchers (87% scoring them 4/5 or 5/5) and doctors (81%); but less trust in commercial companies (35%). They supported the idea of researchers using information from both neonatal blood spots (Guthrie spots) (97% yes) and from electronic health records (95% yes). Our respondents were willing to wear devices like a 'Fit-bit' (88% agreed) or take a brain scan that might predict later mental illness (73%). However, they were less willing to take a new drug for research purposes (45%). They were keen to encourage others to take part in research; whether that be offering the opportunity to pregnant mothers (97% agreed) or extending invitations to their own children and grandchildren (98%). Conclusions: Our participants were broadly supportive of research access to data, albeit less supportive when commercial interests were involved. Public engagement events that facilitate two-way interactions can influence and support future research and public engagement efforts.
