Effects of Actissist, a digital health intervention for early psychosis: A randomized clinical trial.

Schizophrenia affects 24 million people worldwide. Digital health interventions drawing on psychological principles have been developed, but their effectiveness remains unclear. This parallel, assessor-blinded, randomized clinical trial aimed to investigate whether a cognitive behaviour therapy-informed digital health intervention (Actissist app) confers added benefit on psychotic symptoms over and above remote symptom monitoring (ClinTouch app). Participants recruited from UK community health services were randomized 1:1 to receive either Actissist plus treatment as usual (TAU) or ClinTouch plus TAU. Eligible participants were adults with schizophrenia-spectrum psychosis within five years of first episode onset meeting a criterion level of positive symptoms severity. The primary outcome was Positive and Negative Syndrome Scale (PANSS) symptoms total score at 12 weeks post-randomization. Intention-to-treat analysis included 172 participants, with 149 participants (86.6 %) providing primary outcome data. Actissist plus TAU was not associated with greater reduction than an active control remote symptom monitoring app (ClinTouch) in PANSS total score at post-randomization. There were no significant effects between groups across secondary measures. There were no serious adverse reactions. Both groups improved on the primary psychotic symptoms measure at primary end-point and on secondary measures over time. The Actissist app is safe but not superior to digital symptom monitoring.

Digital Lifestyle Interventions for Young People With Mental Illness: A Qualitative Study Among Mental Health Care Professionals.

BACKGROUND: Given the physical health disparities associated with mental illness, targeted lifestyle interventions are required to reduce the risk of cardiometabolic disease. Integrating physical health early in mental health treatment among young people is essential for preventing physical comorbidities, reducing health disparities, managing medication side effects, and improving overall health outcomes. Digital technology is increasingly used to promote fitness, lifestyle, and physical health among the general population. However, using these interventions to promote physical health within mental health care requires a nuanced understanding of the factors that affect their adoption and implementation. OBJECTIVE: Using a qualitative design, we explored the attitudes of mental health care professionals (MHCPs) toward digital technologies for physical health with the goal of illuminating the opportunities, development, and implementation of the effective use of digital tools for promoting healthier lifestyles in mental health care. METHODS: Semistructured interviews were conducted with MHCPs (N=13) using reflexive thematic analysis to explore their experiences and perspectives on using digital health to promote physical health in youth mental health care settings. RESULTS: Three overarching themes from the qualitative analysis are reported: (1) motivation will affect implementation, (2) patients' readiness and capability, and (3) reallocation of staff roles and responsibilities. The subthemes within, and supporting quotes, are described. CONCLUSIONS: The use of digital means presents many opportunities for improving the provision of physical health interventions in mental health care settings. However, given the limited experience of many MHCPs with these technologies, formal training and additional support may improve the likelihood of implementation. Factors such as patient symptomatology, safety, and access to technology, as well as the readiness, acceptability, and capability of both MHCPs and patients to engage with digital tools, must also be considered. In addition, the potential benefits of data integration must be carefully weighed against the associated risks.

Experiences and Views of Young People and Health Care Professionals of Using Social Media to Self-Manage Type 1 Diabetes Mellitus: Thematic Synthesis of Qualitative Studies.

BACKGROUND: Social media have shown the potential to support type 1 diabetes self-management by providing informational, emotional, and peer-to-peer support. However, the perceptions of young people and health care professionals' (HCPs) toward the use of social media for type 1 diabetes self-management have not been systematically reviewed. OBJECTIVE: The aim of this study is to explore and summarize the experiences and views of young people with type 1 diabetes and their HCPs on using social media for self-management across qualitative findings. METHODS: We searched MEDLINE, Embase, PsycINFO, and CINAHL from 2012 to 2023 using Medical Subject Heading terms and text words related to type 1 diabetes and social media. We screened and selected the studies according to the inclusion and exclusion criteria. We quality appraised and characterized the included studies and conducted a thematic synthesis. RESULTS: We included 11 studies in our synthesis. A total of 9 of them were qualitative and 2 were mixed methods studies. Ten focused on young people with type 1 diabetes and 1 on HCPs. All used content analysis and were of moderate to high quality. Thirteen descriptive themes were yielded by our thematic synthesis, contributing to five analytic themes: (1) differences in how young people interact with social media, (2) characteristics of social media platforms that influence their use and uptake for type 1 diabetes self-management, (3) social media as a source of information, (4) impact on young people's coping and emotional well-being, and (5) impact on support from and relationships with HCPs and services. CONCLUSIONS: The synthesis suggests that we should consider leveraging social media's peer support capabilities to augment the traditional services for young people with type 1 diabetes. However, the patients may have privacy concerns about HCPs' involvement in their online activities. This warrants an update of existing guidelines to help young people use social media safely for self-managing their diabetes.

Clinical and cost-effectiveness of telemedicine among patients with type 2 diabetes in primary care: A systematic review and meta-analysis.

AIMS: Telemedicine has been promoted as an effective way of managing type-2 diabetes (T2DM) in primary care. However, the effectiveness of telemedicine is unclear. We investigated the clinical and cost-effectiveness of different telemedicine interventions for people with T2DM, compared to usual care. METHODS: We searched Medline, Embase, Cochrane, CINHAL, ProQuest and EconLit for randomized controlled trials (RCTs) that examined the effectiveness of telemedicine interventions on clinical outcomes (HbA1c, body mass index [BMI], weight, diastolic blood pressure [DBP], systolic blood pressure [SBP], fasting blood glucose, high-density lipoprotein [HDL] cholesterol, low-density lipoprotein [LDL] cholesterol, total cholesterol and triglyceride) in adults with T2DM, published in English from inception until 31 December 2022. Meta-analyses were conducted using random-effects models pooling mean differences, heterogeneity was quantified using the I2 statistic. Publication bias was assessed using funnel plots, Egger tests and trim and fill. Subgroup analyses included type of telemedicine intervention, telemedicine mode of delivery and type of healthcare professionals. This study was registered with PROSPERO, CRD 42022375128. RESULTS: Of the 4093 records identified, 21 RCTs, 10,732 participants from seven regions, were included. Reported interventions included telephone (k = 16 studies), internet-based (k = 2), videoconference (k = 2) and telephone and emails (k = 1). We observed no statistically significant differences between synchronous or asynchronous telemedicine interventions compared to usual care for HbA1c (-0.08% (-0.88 mmol/mol); 95% CI: -0.18, 0.02), BMI (0.51 kg/m2; 95% CI: -0.21, 1.22), SBP (-1.48 mmHg; 95% CI: -3.22, 0.26), DBP (3.23 mmHg; 95% CI: -0.89, 7.34), HDL-cholesterol (0.01 mmol/L; 95% CI: -0.03, 0.05), LDL-cholesterol (0.08 mmol/L; 95% CI: -0.22, 0.37), triglycerides (-0.08 mmol/L, 95% CI: -0.31, -0.15), total cholesterol (-0.10 mmol/L; 95% CI: -0.25, 0.04) and weight (-0.50 kg; 95% CI: -1.21, 0.21). CONCLUSIONS: Telemedicine was as effective as usual care in improving health outcomes of people with T2DM. They can provide a safe solution in times of rising demands for primary healthcare services, or in extreme events, like a global pandemic. More high-quality RCTs are needed on the cost evaluation of telemedicine.

Applying Team Science to Collaborative Digital Health Research: Learnings from the Wearable Clinic.

Collaboration across disciplinary boundaries is vital to address the complex challenges and opportunities in Digital Health. We present findings and experiences of applying the principles of Team Science to a digital health research project called 'The Wearable Clinic'. Challenges faced were a lack of shared understanding of key terminology and concepts, and differences in publication cultures between disciplines. We also encountered more profound discrepancies, relating to definitions of "success" in a research project. We recommend that collaborative digital health research projects select a formal Team Science methodology from the outset.

Using digital technology to promote physical health in mental healthcare: A sequential mixed-methods study of clinicians' views.

AIM: Recent years have seen innovation in 'mHealth' tools and health apps for the management/promotion of physical health and fitness across the general population. However, there is limited research on how this could be applied to mental healthcare. Therefore, we examined mental healthcare professionals' current uses and perceived roles of digital lifestyle interventions for promoting healthy lifestyles, physical health and fitness in youth mental healthcare. METHODS: A sequential, mixed-methods design was used, consisting of a quantitative online survey, followed by qualitative in-depth interviews. RESULTS: A total of 127 mental healthcare professionals participated in the online survey. Participants had limited mHealth experience, and the majority agreed that further training would be beneficial. Thirteen mental healthcare professionals were interviewed. Five themes were generated (i) digital technology's ability to enhance the physical healthcare; (ii) Conditions for the acceptability of apps; (iii) Limitations on staff capability and time; (iv) Motivation as the principal barrier; and (v) Practicalities around receiving lifestyle data. Systematic integration of data produced novel insights around: (i) staff involvement and needs; (ii) ideal focus and content of digital lifestyle interventions; and (iii) barriers towards implementation (including mental healthcare professionals own limited experience using digital lifestyle interventions, which aligned with the appeal of formal training). CONCLUSIONS: Overall, digital lifestyle interventions were positively received by mental healthcare professionals, particularly for health behaviour-tracking and mHealth support for exercise and nutrition. Practical suggestions for facilitating their uptake/implementation to improve availability of physical health interventions in mental healthcare are presented.

User engagement in a randomised controlled trial for a digital health intervention for early psychosis (Actissist 2.0 trial).

Digital Health Interventions (DHIs) can help support people with mental health problems. Achieving satisfactory levels of patient engagement is a crucial, yet often underexplored, pre-requisite for health improvement. Actissist is a co-produced DHI delivered via a smartphone app for people with early psychosis, based on Cognitive Behaviour Therapy principles. This study describes and compares engagement patterns among participants in the two arms of the Actissist 2.0 randomised controlled trial. Engagement frequency and duration were measured among participants using the Actissist app in the intervention arm (n = 87) and the ClinTouch symptom monitoring only app used as the control condition (n = 81). Overall, 47.1 % of Actissist and 45.7 % of ClinTouch users completed at least a third of scheduled alerts while active in the study. The mean frequency (77.1 versus 60.2 total responses) and the median duration (80 versus 75 days until last response) of engagement were not significantly higher among Actissist users compared to ClinTouch users. Older age, White ethnicity, using their own smartphone device and, among Actissist users, an increased sense of therapeutic alliance were significantly associated with increased engagement. Through exploiting detailed usage data, this study identifies possible participant-level and DHI-level predictors of engagement to inform the practical implementation of future DHIs.

Digital health behaviour change interventions in severe mental illness: a systematic review.

The use of digital technologies as a method of delivering health behaviour change (HBC) interventions is rapidly increasing across the general population. However, the role in severe mental illness (SMI) remains overlooked. In this study, we aimed to systematically identify and evaluate all of the existing evidence around digital HBC interventions in people with an SMI. A systematic search of online electronic databases was conducted. Data on adherence, feasibility, and outcomes of studies on digital HBC interventions in SMI were extracted. Our combined search identified 2196 titles and abstracts, of which 1934 remained after removing duplicates. Full-text screening was performed for 107 articles, leaving 36 studies to be included. From these, 14 focused on physical activity and/or cardio-metabolic health, 19 focused on smoking cessation, and three concerned other health behaviours. The outcomes measured varied considerably across studies. Although over 90% of studies measuring behavioural changes reported positive changes in behaviour/attitudes, there were too few studies collecting data on mental health to determine effects on psychiatric outcomes. Digital HBC interventions are acceptable to people with an SMI, and could present a promising option for addressing behavioural health in these populations. Feedback indicated that additional human support may be useful for promoting adherence/engagement, and the content of such interventions may benefit from more tailoring to specific needs. While the literature does not yet allow for conclusions regarding efficacy for mental health, the available evidence to date does support their potential to change behaviour across various domains.

Exploring engagement with the CBT-informed Actissist smartphone application for early psychosis.

BACKGROUND: Individuals with psychosis report favourable attitudes towards psychological interventions delivered via smartphone apps. Evidence for acceptability, safety, feasibility and efficacy is promising but in-depth reporting of app engagement in trials is sparse. AIMS: To examine how people with psychosis engaged with the cognitive behaviour therapy (CBT)-informed Actissist app over a 12-week intervention period, and to examine factors associated with app engagement. METHODS: Secondary data from participants in the intervention arm (n = 24) of a proof-of-concept randomised controlled trial of the Actissist app were analysed. The app prompted participants to engage with app-based CBT-informed material in five domains (voices, socialization, cannabis use, paranoia, perceived criticism) at pseudo-random intervals (three notifications per day, six days per week). Participants could self-initiate use any time. App use was financially incentivised. RESULTS: Participants responded to 47% of app notifications. Most app engagements (87%) were app-initiated rather than self-initiated. Participants engaged most with the voices domain, then paranoia. Age and employment status were significantly associated with overall app engagement. CONCLUSION: Individuals with psychosis engaged well with Actissist, particularly with areas focussing on voice-hearing and paranoia. App-generated reminders successfully prompted app engagement. As financial incentives may have increased app engagement, future studies of non-incentivized engagement in larger samples are needed.

Heightened COVID-19 Mortality in People With Severe Mental Illness Persists After Vaccination: A Cohort Study of Greater Manchester Residents.

BACKGROUND AND HYPOTHESIS: Previous studies show that people with severe mental illness (SMI) are at higher risk of COVID-19 mortality, however limited evidence exists regarding risk postvaccination. We investigated COVID-19 mortality among people with schizophrenia and other SMIs before, during and after the UK vaccine roll-out. STUDY DESIGN: Using the Greater Manchester (GM) Care Record to access routinely collected health data linked with death records, we plotted COVID-19 mortality rates over time in GM residents with schizophrenia/psychosis, bipolar disorder (BD), and/or recurrent major depressive disorder (MDD) from February 2020 to September 2021. Multivariable logistic regression was used to compare mortality risk (risk ratios; RRs) between people with SMI (N = 193 435) and age-sex matched controls (N = 773 734), adjusted for sociodemographic factors, preexisting comorbidities, and vaccination status. STUDY RESULTS: Mortality risks were significantly higher among people with SMI compared with matched controls, particularly among people with schizophrenia/psychosis (RR 3.18, CI 2.94-3.44) and/or BD (RR 2.69, CI 2.16-3.34). In adjusted models, the relative risk of COVID-19 mortality decreased, though remained significantly higher than matched controls for people with schizophrenia (RR 1.61, CI 1.45-1.79) and BD (RR 1.92, CI 1.47-2.50), but not recurrent MDD (RR 1.08, CI 0.99-1.17). People with SMI continued to show higher mortality rate ratios relative to controls throughout 2021, during vaccination roll-out. CONCLUSIONS: People with SMI, notably schizophrenia and BD, were at greater risk of COVID-19 mortality compared to matched controls. Despite population vaccination efforts that have prioritized people with SMI, disparities still remain in COVID-19 mortality for people with SMI.

Using discrete-choice experiments to elicit preferences for digital wearable health technology for self-management of chronic kidney disease.

OBJECTIVES: Wearable digital health technologies (DHTs) have the potential to improve chronic kidney disease (CKD) management through patient engagement. This study aimed to investigate and elicit preferences of individuals with CKD toward wearable DHTs designed to support self-management of their condition. METHODS: Using the results of our review of the published literature and after conducting qualitative patient interviews, five-choice attributes were identified and included in a discrete-choice experiment. The design consisted of 10-choice tasks, each comprising two hypothetical technologies and one opt-out scenario. We collected data from 113 adult patients with CKD stages 3-5 not on dialysis and analyzed their responses via a latent class model to explore preference heterogeneity. RESULTS: Two patient segments were identified. In all preference segments, the most important attributes were the device appearance, format, and type of information provided. Patients within the largest preference class (70 percent) favored information provided in any format except the audio, while individuals in the other class preferred information in text format. In terms of the style of engagement with the device, both classes wanted a device that provides options rather than telling them what to do. CONCLUSIONS: Our analysis indicates that user preferences differ between patient subgroups, supporting the case for offering a different design of the device for different patients' strata, thus moving away from a one-size-fits-all service provision. Furthermore, we showed how to leverage the information from user preferences early in the R&D process to inform and support the provision of nuanced person-centered wearable DHTs.

Smoking Cessation Apps for People with Schizophrenia: How Feasible Are m-Health Approaches?

Background: The large health disparities among those diagnosed with schizophrenia urgently need to be addressed. These disparities are partially caused by adverse health behaviours such as smoking. Smoking cessation apps vary in efficacy across various populations, and there are concerns regarding the accessibility and usability of apps for people with schizophrenia. Objective: This review identifies and examines the feasibility of using apps for smoking cessation in people with schizophrenia. Methods: A non-systematic narrative literature review of smoking cessation apps for individuals with schizophrenia was performed. Results: Eight studies were included in this review. Conclusion: Smoking cessation apps can be acceptable and feasible, but may need to be tailored to the needs of people with schizophrenia. Key messages: (1) Smoking cessation apps could be acceptable and feasible for use in people with schizophrenia; (2) Lack of motivation was perceived as the main potential barrier with regard to people with schizophrenia engaging with smoking cessation apps; (3) In order to improve motivation of people diagnosed with schizophrenia, apps could include games, rewards, and/or social support; (4) Smoking cessation apps with a simple interface seem to be beneficial for this population; (5) Apps may need to be tailored to consider this population's mental health needs.

Educating the Healthcare Workforce to Support Digital Transformation.

Digital transformation of the healthcare workforce is a priority if we are to leverage the potential of digital technologies, artificial intelligence in clinical decision support and the potential of data captured within electronic health records. Educational programmes need to be diverse and support the digital novices through to the champions whom will be responsible for procuring and implementing digital solutions. In order to professionalise the workforce in this area, digital competencies need to be built into training from early on and be underpinned by frameworks that help to guide regulators and professional bodies and support educational providers to deliver them. Here we describe Manchester's involvement in the development of digital competency frameworks and our digital transformation education programmes that we have created, including a Massive Online Open Course and a professional development course for England's Topol Digital Fellows.

Acceptability of reducing sedentariness using a mobile-phone application based on 'if then' plans for people with psychosis: A focus-group study conducted in North West England, UK.

OBJECTIVE: To understand the acceptability of (a) reducing sedentary-behaviour in people with psychosis using 'if-then' plans and (b) the proposed app content. DESIGN: Qualitative acceptability study. METHOD: Three structured focus-groups and an interview were conducted with eight participants who had experience of a psychotic episode. They discussed sedentary-behaviour, being more active, critical situations in which they may be tempted to be sedentary and solutions to these (the if-then plans), and a mock-up of the mobile application. The Theoretical Framework of Acceptability (TFA) was used to analyse qualitatively the transcripts. RESULTS: All TFA constructs were coded in each of the transcripts. The idea of reducing sedentary-behaviour was acceptable to people with psychosis, participants knew the importance of being more active, however it is not always their main priority. Likewise, the proposed content of the app was found to be acceptable, with participants already using some of the proposed solutions. CONCLUSION: This was the first study to use the TFA framework to assess the acceptability of an app that uses critical situations and solutions ('if-then plans') to help reduce sedentary behaviour for people with psychosis. In this sample (male, English speaking mainly white people), participants understood the benefits of being more active. However, reducing sedentary-behaviour is not the main priority of this population and being sedentary has benefits when their mental-health is bad.

Neurological, Psychiatric, and Psychological Implications of the COVID-19 Pandemic: Protocol for a Large-Scale Umbrella Review of Observational Studies.

The severe acute respiratory syndrome coronavirus 2 disease (SARS-CoV-2) is the most severe manifestation of the coronavirus disease 2019 (COVID-19) pandemic. Accruing evidence indicates that the COVID-19 pandemic may have profound deleterious neurological, psychiatric, and psychological outcomes. The number of systematic reviews (SRs) and meta-analyses (MAs) on this topic has grown exponentially. This protocol aims to synthesize all evidence from SRs and MAs on the associations between the COVID-19 pandemic and neuropsychiatric outcomes. The following electronic databases will be systematically searched from inception up to 15 January 2022: PubMed, Embase, APA PsycINFO, and Cochrane Reviews. An umbrella review (UR) of SRs and MAs of observational studies will be conducted. SRs and/or MAs of observational studies examining any direct or indirect association of COVID-19 with the neuropsychiatric outcomes will be deemed eligible for potential inclusion in this UR. The direct associations include the impact on the (1) prognosis of COVID-19 and (2) neuropsychiatric sequelae after COVID-19 infection. The indirect associations include the influence of the COVID-19 pandemic on the (1) treatments and (2) outcomes of neurological and psychiatric conditions associated with the COVID-19 pandemic.

Disparities in COVID-19 infection, hospitalisation and death in people with schizophrenia, bipolar disorder, and major depressive disorder: a cohort study of the UK Biobank.

People with severe mental illness (SMI; including schizophrenia/psychosis, bipolar disorder (BD), major depressive disorder (MDD)) experience large disparities in physical health. Emerging evidence suggests this group experiences higher risks of infection and death from COVID-19, although the full extent of these disparities are not yet established. We investigated COVID-19 related infection, hospitalisation and mortality among people with SMI in the UK Biobank (UKB) cohort study. Overall, 447,296 participants from UKB (schizophrenia/psychosis = 1925, BD = 1483 and MDD = 41,448, non-SMI = 402,440) were linked with healthcare and death records. Multivariable logistic regression analysis was used to examine differences in COVID-19 outcomes by diagnosis, controlling for sociodemographic factors and comorbidities. In unadjusted analyses, higher odds of COVID-19 mortality were seen among people with schizophrenia/psychosis (odds ratio [OR] 4.84, 95% confidence interval [CI] 3.00-7.34), BD (OR 3.76, 95% CI 2.00-6.35), and MDD (OR 1.99, 95% CI 1.69-2.33) compared to people with no SMI. Higher odds of infection and hospitalisation were also seen across all SMI groups, particularly among people with schizophrenia/psychosis (OR 1.61, 95% CI 1.32-1.96; OR 3.47, 95% CI 2.47-4.72) and BD (OR 1.48, 95% CI 1.16-1.85; OR 3.31, 95% CI 2.22-4.73). In fully adjusted models, mortality and hospitalisation odds remained significantly higher among all SMI groups, though infection odds remained significantly higher only for MDD. People with schizophrenia/psychosis, BD and MDD have higher risks of COVID-19 infection, hospitalisation and mortality. Only a proportion of these disparities were accounted for by pre-existing demographic characteristics or comorbidities. Vaccination and preventive measures should be prioritised in these particularly vulnerable groups.

Text mining tweets on e-cigarette risks and benefits using machine learning following a vaping related lung injury outbreak in the USA.

Electronic nicotine delivery systems (ENDS) (also known as 'e-cigarettes') can support smoking cessation, although the long-term health impacts are not yet known. In 2019, a cluster of lung injury cases in the USA emerged that were ostensibly associated with ENDS use. Subsequent investigations revealed a link with vitamin E acetate, an additive used in some ENDS liquid products containing tetrahydrocannabinol (THC). This became known as the EVALI (E-cigarette or Vaping product use Associated Lung Injury) outbreak. While few cases were reported in the UK, the EVALI outbreak intensified attention on ENDS in general worldwide. We aimed to describe and explore public commentary and discussion on Twitter immediately before, during and following the peak of the EVALI outbreak using text mining techniques. Specifically, topic modelling, operationalised using Latent Dirichlet Allocation (LDA) models, was used to discern discussion topics in 189,658 tweets about ENDS (collected April-December 2019). Individual tweets and Twitter users were assigned to their dominant topics and countries respectively to enable international comparisons. A 10-topic LDA model fit the data best. We organised the ten topics into three broad themes for the purposes of reporting: informal vaping discussion; vaping policy discussion and EVALI news; and vaping commerce. Following EVALI, there were signs that informal vaping discussion topics decreased while discussion topics about vaping policy and the relative health risks and benefits of ENDS increased, not limited to THC products. Though subsequently attributed to THC products, the EVALI outbreak disrupted online public discourses about ENDS generally, amplifying health and policy commentary. There was a relatively stronger presence of commercially oriented tweets among UK Twitter users compared to USA users.

Public Perspectives of Using Social Media Data to Improve Adverse Drug Reaction Reporting: A Mixed-Methods Study.

INTRODUCTION: Information on suspected adverse drug reactions (ADRs) voluntarily submitted by patients can be a valuable source of information for improving drug safety; however, public awareness of reporting mechanisms remains low. Whilst methods to automatically detect ADR mentions from social media posts using text mining techniques have been proposed to improve reporting rates, it is unclear how acceptable these would be to social media users. OBJECTIVE: The objective of this study was to explore public opinion about using automated methods to detect and report mentions of ADRs on social media to enhance pharmacovigilance efforts. METHODS: Users of the online health discussion forum HealthUnlocked participated in an online survey (N = 1359) about experiences with ADRs, knowledge of pharmacovigilance methods, and opinions about using automated data mining methods to detect and report ADRs. To further explore responses, five qualitative focus groups were conducted with 20 social media users with long-term health conditions. RESULTS: Participant responses indicated a low awareness of pharmacovigilance methods and ADR reporting. They showed a strong willingness to share health-related social media data about ADRs with researchers and regulators, but were cautious about automated text mining methods of detecting and reporting ADRs. CONCLUSIONS: Social media users value public-facing pharmacovigilance schemes, even if they do not understand the current framework of pharmacovigilance within the UK. Ongoing engagement with users is essential to understand views, share knowledge and respect users' privacy expectations to optimise future ADR reporting from online health communities.