Investigating mental health service user views of stigma on Twitter during COVID-19: a mixed-methods study.

Background: Mental health stigma on social media is well studied, but not from the perspective of mental health service users. Coronavirus disease-19 (COVID-19) increased mental health discussions and may have impacted stigma.Objectives: (1) to understand how service users perceive and define mental health stigma on social media; (2) how COVID-19 shaped mental health conversations and social media use.Methods: We collected 2,700 tweets related to seven mental health conditions: schizophrenia, depression, anxiety, autism, eating disorders, OCD, and addiction. Twenty-seven service users rated them as stigmatising or neutral, followed by focus group discussions. Focus group transcripts were thematically analysed.Results: Participants rated 1,101 tweets (40.8%) as stigmatising. Tweets related to schizophrenia were most frequently classed as stigmatising (411/534, 77%). Tweets related to depression or anxiety were least stigmatising (139/634, 21.9%). A stigmatising tweet depended on perceived intention and context but some words (e.g. "psycho") felt stigmatising irrespective of context.Discussion: The anonymity of social media seemingly increased stigma, but COVID-19 lockdowns improved mental health literacy. This is the first study to qualitatively investigate service users' views of stigma towards various mental health conditions on Twitter and we show stigma is common, particularly towards schizophrenia. Service user involvement is vital when designing solutions to stigma.

Keeping well in a COVID-19 crisis: a qualitative study formulating the perspectives of mental health service users and carers.

BACKGROUND: People with existing mental health conditions may be particularly vulnerable to the psychological effect of the COVID-19 pandemic. But their positive and negative appraisals, and coping behaviour could prevent or ameliorate future problems. OBJECTIVE: To explore the emotional experiences, thought processes and coping behaviours of people with existing mental health problems and carers living through the pandemic. METHODS: UK participants who identified as a mental health service user (N18), a carer (N5) or both (N8) participated in 30-minute semi-structured remote interviews (31 March 2020 to 9 April 2020). The interviews investigated the effects of social distancing and self-isolation on mental health and the ways in which people were coping. Data were analysed using a framework analysis. Three service user researchers charted data into a framework matrix (consisting of three broad categories: "emotional responses", "thoughts" and "behaviours") and then used an inductive process to capture other contextual themes. RESULTS: Common emotional responses were fear, sadness and anger but despite negative emotions and uncertainty appraisals, participants described efforts to cope and maintain their mental wellbeing. This emphasised an increased reliance on technology, which enabled social contact and occupational or leisure activities. Participants also spoke about the importance of continued and adapted mental health service provision, and the advantages and disadvantages associated with changes in their living environment, life schedule and social interactions. CONCLUSION: This study builds on a growing number of qualitative accounts of how mental health service users and carers experienced and coped with extreme social distancing measures early in the COVID-19 pandemic. Rather than a state of helplessness this study contains a clear message of resourcefulness and resilience in the context of fear and uncertainty.

Measuring attitudes towards mental health using social media: investigating stigma and trivialisation.

BACKGROUND: There are numerous campaigns targeting mental health stigma. However, evaluating how effective these are in changing perceptions is complex. Social media may be used to assess stigma levels and highlight new trends. This study uses a social media platform, Twitter, to investigate stigmatising and trivialising attitudes across a range of mental and physical health conditions. METHODS: Tweets (i.e. messages) associated with five mental and five physical health conditions were collected in ten 72-h windows over a 50-day period using automated software. A random selection of tweets per condition was considered for the analyses. Tweets were categorised according to their topic and presence of stigmatising and trivialising attitudes. Qualitative thematic analysis was performed on all stigmatising and trivialising tweets. RESULTS: A total of 1,059,258 tweets were collected, and from this sample 1300 tweets per condition were randomly selected for analysis. Overall, mental health conditions were found to be more stigmatised (12.9%) and trivialised (14.3%) compared to physical conditions (8.1 and 6.8%, respectively). Amongst mental health conditions the most stigmatised condition was schizophrenia (41%) while the most trivialised was obsessive compulsive disorder (33%). CONCLUSIONS: Our findings show that mental health stigma is common on social media. Trivialisation is also common, suggesting that while society may be more open to discussing mental health problems, care should be taken to ensure this is done appropriately. This study further demonstrates the potential for social media to be used to measure the general public's attitudes towards mental health conditions.

Serum insulin-like growth factor-I levels are associated with improved white matter recovery after traumatic brain injury.

OBJECTIVE: Traumatic brain injury (TBI) is a common disabling condition with limited treatment options. Diffusion tensor imaging measures recovery of axonal injury in white matter (WM) tracts after TBI. Growth hormone deficiency (GHD) after TBI may impair axonal and neuropsychological recovery, and serum insulin-like growth factor-I (IGF-I) may mediate this effect. We conducted a longitudinal study to determine the effects of baseline serum IGF-I concentrations on WM tract and neuropsychological recovery after TBI. METHODS: Thirty-nine adults after TBI (84.6% male, median age = 30.5 years, 87.2% moderate-severe, median time since TBI = 16.3 months, n = 4 with GHD) were scanned twice, 13.3 months (range = 12.1-14.9) apart, and 35 healthy controls were scanned once. Symptom and quality of life questionnaires and cognitive assessments were completed at both visits (n = 33). Our main outcome measure was fractional anisotropy (FA), a measure of WM tract integrity, in a priori regions of interest: splenium of corpus callosum (SPCC) and posterior limb of internal capsule (PLIC). RESULTS: At baseline, FA was reduced in many WM tracts including SPCC and PLIC following TBI compared to controls, indicating axonal injury, with longitudinal increases indicating axonal recovery. There was a significantly greater increase in SPCC FA over time in patients with serum IGF-I above versus below the median for age. Only the higher IGF-I group had significant improvements in immediate verbal memory recall over time. INTERPRETATION: WM recovery and memory improvements after TBI were greater in patients with higher serum IGF-I at baseline. These findings suggest that the growth hormone/IGF-I system may be a potential therapeutic target following TBI. Ann Neurol 2017;82:30-43.

Prevalence and correlates of vitamin D deficiency in adults after traumatic brain injury.

OBJECTIVES: Traumatic brain injury (TBI) is a major cause of long-term disability with variable recovery. Preclinical studies suggest that vitamin D status influences the recovery after TBI. However, there is no published clinical data on links between vitamin D status and TBI outcomes. The aim was to determine the (i) prevalence of vitamin D deficiency/insufficiency, and associations of vitamin D status with (ii) demographic factors and TBI severity, and with (iii) cognitive function, symptoms and quality of life, in adults after TBI. DESIGN: Retrospective audit of patients seen between July 2009 and March 2015. Serum vitamin D (25-hydroxy-cholecalciferol) was categorized as deficient (<40 nmol/l), insufficient (40-70 nmol/l) or replete (>70 nmol/l). PATIENTS: A total of 353 adults seen in tertiary hospital clinic (75·4% lighter skinned, 74·8% male, age median 35·1 year, range 26·6-48·3 year), 0·3-56·5 months after TBI (74·5% moderate-severe). MEASUREMENTS: Serum vitamin D concentrations; Addenbrooke's Cognitive Examination (ACE-R), Beck Depression Inventory-II (BDI-II), SF-36 Quality of Life, Pittsburgh Sleep Quality Index. RESULTS: In total, 46·5% of patients after TBI had vitamin D deficiency and 80·2% insufficiency/deficiency. Patients with vitamin D deficiency had lower ACE-R scores than those of vitamin D replete (mean effect size ± SEM 4·5 ± 2·1, P = 0·034), and higher BDI-II scores than those of vitamin D insufficient (4·5 ± 1·6, P = 0·003), correcting for age, gender, time since TBI and TBI severity. There was no association between vitamin D status and markers of TBI severity, sleep or quality of life. CONCLUSION: Vitamin D deficiency is common in patients after TBI and associated with impaired cognitive function and more severe depressive symptoms.

Damage to the Salience Network and interactions with the Default Mode Network.

Interactions between the Salience Network (SN) and the Default Mode Network (DMN) are thought to be important for cognitive control. However, evidence for a causal relationship between the networks is limited. Previously, we have reported that traumatic damage to white matter tracts within the SN predicts abnormal DMN function. Here we investigate the effect of this damage on network interactions that accompany changing motor control. We initially used fMRI of the Stop Signal Task to study response inhibition in humans. In healthy subjects, functional connectivity (FC) between the right anterior insula (rAI), a key node of the SN, and the DMN transiently increased during stopping. This change in FC was not seen in a group of traumatic brain injury (TBI) patients with impaired cognitive control. Furthermore, the amount of SN tract damage negatively correlated with FC between the networks. We confirmed these findings in a second group of TBI patients. Here, switching rather than inhibiting a motor response: (1) was accompanied by a similar increase in network FC in healthy controls; (2) was not seen in TBI patients; and (3) tract damage after TBI again correlated with FC breakdown. This shows that coupling between the rAI and DMN increases with cognitive control and that damage within the SN impairs this dynamic network interaction. This work provides compelling evidence for a model of cognitive control where the SN is involved in the attentional capture of salient external stimuli and signals the DMN to reduce its activity when attention is externally focused.

The neural basis of impaired self-awareness after traumatic brain injury.

Self-awareness is commonly impaired after traumatic brain injury. This is an important clinical issue as awareness affects long-term outcome and limits attempts at rehabilitation. It can be investigated by studying how patients respond to their errors and monitor their performance on tasks. As awareness is thought to be an emergent property of network activity, we tested the hypothesis that impaired self-awareness is associated with abnormal brain network function. We investigated a group of subjects with traumatic brain injury (n = 63) split into low and high performance-monitoring groups based on their ability to recognize and correct their own errors. Brain network function was assessed using resting-state and event-related functional magnetic resonance imaging. This allowed us to investigate baseline network function, as well as the evoked response of networks to specific events including errors. The low performance-monitoring group underestimated their disability and showed broad attentional deficits. Neural activity within what has been termed the fronto-parietal control network was abnormal in patients with impaired self-awareness. The dorsal anterior cingulate cortex is a key part of this network that is involved in performance-monitoring. This region showed reduced functional connectivity to the rest of the fronto-parietal control network at 'rest'. In addition, the anterior insulae, which are normally tightly linked to the dorsal anterior cingulate cortex, showed increased activity following errors in the impaired group. Interestingly, the traumatic brain injury patient group with normal performance-monitoring showed abnormally high activation of the right middle frontal gyrus, putamen and caudate in response to errors. The impairment of self-awareness was not explained either by the location of focal brain injury, or the amount of traumatic axonal injury as demonstrated by diffusion tensor imaging. The results suggest that impairments of self-awareness after traumatic brain injury result from breakdown of functional interactions between nodes within the fronto-parietal control network.

"Nothing About Me Without Me": An Interpretative Review of Patient Accessible Electronic Health Records.

BACKGROUND: Patient accessible electronic health records (PAEHRs) enable patients to access and manage personal clinical information that is made available to them by their health care providers (HCPs). It is thought that the shared management nature of medical record access improves patient outcomes and improves patient satisfaction. However, recent reviews have found that this is not the case. Furthermore, little research has focused on PAEHRs from the HCP viewpoint. HCPs include physicians, nurses, and service providers. OBJECTIVE: We provide a systematic review of reviews of the impact of giving patients record access from both a patient and HCP point of view. The review covers a broad range of outcome measures, including patient safety, patient satisfaction, privacy and security, self-efficacy, and health outcome. METHODS: A systematic search was conducted using Web of Science to identify review articles on the impact of PAEHRs. Our search was limited to English-language reviews published between January 2002 and November 2014. A total of 73 citations were retrieved from a series of Boolean search terms including "review*" with "patient access to records". These reviews went through a novel scoring system analysis whereby we calculated how many positive outcomes were reported per every outcome measure investigated. This provided a way to quantify the impact of PAEHRs. RESULTS: Ten reviews covering chronic patients (eg, diabetes and hypertension) and primary care patients, as well as HCPs were found but eight were included for the analysis of outcome measures. We found mixed outcomes across both patient and HCP groups, with approximately half of the reviews showing positive changes with record access. Patients believe that record access increases their perception of control; however, outcome measures thought to create psychological concerns (such as patient anxiety as a result of seeing their medical record) are still unanswered. Nurses are more likely than physicians to gain time efficiencies by using a PAEHR system with the main concern from physicians being the security of the PAEHRs. CONCLUSIONS: This review implements a novel scoring system, which shows there is a lack of rigorous empirical testing that separates the effect of record access from other existing disease management programs. Current research is too targeted within certain clinical groups' needs, and although there are positive signs for the adoption of PAEHRs, there is currently insufficient evidence about the effect of PAEHRs on health outcomes for patients or HCPs.

Pituitary dysfunction after blast traumatic brain injury: The UK BIOSAP study.

OBJECTIVE: Pituitary dysfunction is a recognized consequence of traumatic brain injury (TBI) that causes cognitive, psychological, and metabolic impairment. Hormone replacement offers a therapeutic opportunity. Blast TBI (bTBI) from improvised explosive devices is commonly seen in soldiers returning from recent conflicts. We investigated: (1) the prevalence and consequences of pituitary dysfunction following moderate to severe bTBI and (2) whether it is associated with particular patterns of brain injury. METHODS: Nineteen male soldiers with moderate to severe bTBI (median age = 28.3 years) and 39 male controls with moderate to severe nonblast TBI (nbTBI; median age = 32.3 years) underwent full dynamic endocrine assessment between 2 and 48 months after injury. In addition, soldiers had structural brain magnetic resonance imaging, including diffusion tensor imaging (DTI), and cognitive assessment. RESULTS: Six of 19 (32.0%) soldiers with bTBI, but only 1 of 39 (2.6%) nbTBI controls, had anterior pituitary dysfunction (p = 0.004). Two soldiers had hyperprolactinemia, 2 had growth hormone (GH) deficiency, 1 had adrenocorticotropic hormone (ACTH) deficiency, and 1 had combined GH/ACTH/gonadotrophin deficiency. DTI measures of white matter structure showed greater traumatic axonal injury in the cerebellum and corpus callosum in those soldiers with pituitary dysfunction than in those without. Soldiers with pituitary dysfunction after bTBI also had a higher prevalence of skull/facial fractures and worse cognitive function. Four soldiers (21.1%) commenced hormone replacement(s) for hypopituitarism. INTERPRETATION: We reveal a high prevalence of anterior pituitary dysfunction in soldiers suffering moderate to severe bTBI, which was more frequent than in a matched group of civilian moderate to severe nbTBI subjects. We recommend that all patients with moderate to severe bTBI should routinely have comprehensive assessment of endocrine function.

The impact of patient involvement on participant opinions of information sheets.

BACKGROUND: Patient and public involvement (PPI) groups can provide valuable input to create more accessible study documents with less jargon. However, we don't know whether this procedure improves accessibility for potential participants. AIMS: We assessed whether participant information sheets were rated as more accessible after PPI review and which aspects of information sheets and study design were important to mental health patients compared with a control group with no mental health service use. METHOD: This was a double-blind quasi-experimental study using a mixed-methods explanatory design. Patients and control participants quantitatively rated pre- and post-review documents. Semi-structured interviews were thematically analysed to gain qualitative feedback on opinions of information sheets and studies. Two-way multivariate analysis of variance was used to detect differences in ratings between pre- and post-review documents. RESULTS: We found no significant (P < 0.05) improvements in patient (n = 15) or control group (n = 21) ratings after PPI review. Patients and controls both rated PPI as of low importance in studies and considered the study rationale as most important. However, PPI was often misunderstood, with participants believing that it meant lay patients would take over the design and administration of the study. Qualitative findings highlight the importance of clear, friendly and visually appealing information sheets. CONCLUSIONS: Researchers should be aware of what participants want to know about so they can create information sheets addressing these priorities, for example, explaining why the research is necessary. PPI is poorly understood by the wider population and efforts must be made to increase diversity in participation.

Experiences of health tracking in mobile apps for multiple sclerosis: A qualitative content analysis of user reviews.

BACKGROUND: Mobile health applications (apps) are promising condition self-management tools for people living with multiple sclerosis (MS). However, most existing apps do not include health tracking features. This gap has been raised as a priority research topic, but the development of new self-management apps will require designers to understand the context and needs of those living with MS. Our aim was to conduct a content analysis of publicly available user reviews of existing MS self-management apps to understand desired features and guide the design of future apps. METHODS: We systematically reviewed MS self-management apps which were publicly available in English on the Google Play and iOS app stores. We then conducted sentiment and content analysis of recent user reviews which referenced health tracking and data visualization to understand self-reported experiences and feedback. RESULTS: Searches identified 75 unique apps, of which six met eligibility criteria and had reviews. One hundred and thirty-seven user reviews of these apps were eligible, though most were associated with a single app (n=108). Overall, ratings and sentiment scores skewed highly positive (Median [IQR]: Ratings - 5 [4-5], Sentiment scores - 0.70 [0.44-0.86]), though scores of individual apps varied. Content analysis revealed five themes: reasons for app usage, simple user experience, customization and flexibility, feature requests, and technical issues. Reviewers suggested that app customization, interconnectivity, and consolidated access to desired features should be considered in the design of future apps. User ratings weakly correlated with review sentiment scores (ρ = 0.27 [0.11-0.42]). CONCLUSIONS: Self-tracking options in MS apps are currently limited, though the apps that offer these functions are considered useful by individuals with MS. Additional qualitative research is required to understand how specific app features and opportunities for personalization should be incorporated into new self-management tools for this population.

Comparing Professional and Consumer Ratings of Mental Health Apps: Mixed Methods Study.

BACKGROUND: As the number of mental health apps has grown, increasing efforts have been focused on establishing quality tailored reviews. These reviews prioritize clinician and academic views rather than the views of those who use them, particularly those with lived experiences of mental health problems. Given that the COVID-19 pandemic has increased reliance on web-based and mobile mental health support, understanding the views of those with mental health conditions is of increasing importance. OBJECTIVE: This study aimed to understand the opinions of people with mental health problems on mental health apps and how they differ from established ratings by professionals. METHODS: A mixed methods study was conducted using a web-based survey administered between December 2020 and April 2021, assessing 11 mental health apps. We recruited individuals who had experienced mental health problems to download and use 3 apps for 3 days and complete a survey. The survey consisted of the One Mind PsyberGuide Consumer Review Questionnaire and 2 items from the Mobile App Rating Scale (star and recommendation ratings from 1 to 5). The consumer review questionnaire contained a series of open-ended questions, which were thematically analyzed and using a predefined protocol, converted into binary (positive or negative) ratings, and compared with app ratings by professionals and star ratings from app stores. RESULTS: We found low agreement between the participants' and professionals' ratings. More than half of the app ratings showed disagreement between participants and professionals (198/372, 53.2%). Compared with participants, professionals gave the apps higher star ratings (3.58 vs 4.56) and were more likely to recommend the apps to others (3.44 vs 4.39). Participants' star ratings were weakly positively correlated with app store ratings (r=0.32, P=.01). Thematic analysis found 11 themes, including issues of user experience, ease of use and interactivity, privacy concerns, customization, and integration with daily life. Participants particularly valued certain aspects of mental health apps, which appear to be overlooked by professional reviewers. These included functions such as the ability to track and measure mental health and providing general mental health education. The cost of apps was among the most important factors for participants. Although this is already considered by professionals, this information is not always easily accessible. CONCLUSIONS: As reviews on app stores and by professionals differ from those by people with lived experiences of mental health problems, these alone are not sufficient to provide people with mental health problems with the information they desire when choosing a mental health app. App rating measures must include the perspectives of mental health service users to ensure ratings represent their priorities. Additional work should be done to incorporate the features most important to mental health service users into mental health apps.

Identifying schizophrenia stigma on Twitter: a proof of principle model using service user supervised machine learning.

Stigma has negative effects on people with mental health problems by making them less likely to seek help. We develop a proof of principle service user supervised machine learning pipeline to identify stigmatising tweets reliably and understand the prevalence of public schizophrenia stigma on Twitter. A service user group advised on the machine learning model evaluation metric (fewest false negatives) and features for machine learning. We collected 13,313 public tweets on schizophrenia between January and May 2018. Two service user researchers manually identified stigma in 746 English tweets; 80% were used to train eight models, and 20% for testing. The two models with fewest false negatives were compared in two service user validation exercises, and the best model used to classify all extracted public English tweets. Tweets classed as stigmatising by service users were more negative in sentiment (t (744) = 12.02, p < 0.001 [95% CI: 0.196-0.273]). Our linear Support Vector Machine was the best performing model with fewest false negatives and higher service user validation. This model identified public stigma in 47% of English tweets (n5,676) which were more negative in sentiment (t (12,143) = 64.38, p < 0.001 [95% CI: 0.29-0.31]). Machine learning can identify stigmatising tweets at large scale, with service user involvement. Given the prevalence of stigma, there is an urgent need for education and online campaigns to reduce it. Machine learning can provide a real time metric on their success.

Health Tracking via Mobile Apps for Depression Self-management: Qualitative Content Analysis of User Reviews.

BACKGROUND: Tracking and visualizing health data using mobile apps can be an effective self-management strategy for mental health conditions. However, little evidence is available to guide the design of mental health-tracking mechanisms. OBJECTIVE: The aim of this study was to analyze the content of user reviews of depression self-management apps to guide the design of data tracking and visualization mechanisms for future apps. METHODS: We systematically reviewed depression self-management apps on Google Play and iOS App stores. English-language reviews of eligible apps published between January 1, 2018, and December 31, 2021, were extracted from the app stores. Reviews that referenced health tracking and data visualization were included in sentiment and qualitative framework analyses. RESULTS: The search identified 130 unique apps, 26 (20%) of which were eligible for inclusion. We included 783 reviews in the framework analysis, revealing 3 themes. Impact of app-based mental health tracking described how apps increased reviewers' self-awareness and ultimately enabled condition self-management. The theme designing impactful mental health-tracking apps described reviewers' feedback and requests for app features during data reporting, review, and visualization. It also described the desire for customization and contexts that moderated reviewer preference. Finally, implementing impactful mental health-tracking apps described considerations for integrating apps into a larger health ecosystem, as well as the influence of paywalls and technical issues on mental health tracking. CONCLUSIONS: App-based mental health tracking supports depression self-management when features align with users' individual needs and goals. Heterogeneous needs and preferences raise the need for flexibility in app design, posing challenges for app developers. Further research should prioritize the features based on their importance and impact on users.

Factors Influencing Increased Use of Technology to Communicate With Others During the COVID-19 Pandemic: Cross-sectional Web-Based Survey Study.

BACKGROUND: Communication via technology is regarded as an effective way of maintaining social connection and helping individuals to cope with the psychological impact of social distancing measures during a pandemic. However, there is little information about which factors have influenced increased use of technology to communicate with others during lockdowns and whether this has changed over time. OBJECTIVE: The aim of this study is to explore which psychosocial factors (eg, mental health and employment) and pandemic-related factors (eg, shielding and time) influenced an increase in communication via technology during the first lockdown in the United Kingdom. METHODS: A cross-sectional, web-based survey was conducted between April and July 2020, examining thoughts, feelings, and behaviors associated with the pandemic, including communicating more using technology (eg, via messaging, phone, or video). We collected sociodemographic information, employment status, mental health service user status, and depression symptoms. We used hierarchical logistic regression to test which factors were associated with communicating more using technology during the lockdown. RESULTS: Participants (N=1464) were on average 41.07 (SD 14.61) years old, and mostly women (n=1141; 77.9%), White (n=1265; 86.4%), and employed (n=1030; 70.4%). Participants reported a mild level of depression (mean 9.43, SD 7.02), and were communicating more using technology (n=1164; 79.5%). The hierarchical regression indicated that people who were employed and experiencing lower levels of depression were more likely to report increased communication using technology during a lockdown period of the COVID-19 pandemic, and over time, men communicated more using technology. Increased use of technology to communicate was related to greater communication and the inability to see others due to the social distancing measures enacted during the lockdown. It was not related to a general increase in technology use during the lockdown. CONCLUSIONS: Although most participants reported increased use of technology to communicate during a lockdown period of the COVID-19 pandemic, this was more apparent in the employed and those experiencing low levels of depression. Moving forward, we should continue to monitor groups who may have been excluded from the benefits of support and communication using technology.

Investigation of Carers' Perspectives of Dementia Misconceptions on Twitter: Focus Group Study.

BACKGROUND: Dementia misconceptions on social media are common, with negative effects on people with the condition, their carers, and those who know them. This study codeveloped a thematic framework with carers to understand the forms these misconceptions take on Twitter. OBJECTIVE: The aim of this study is to identify and analyze types of dementia conversations on Twitter using participatory methods. METHODS: A total of 3 focus groups with dementia carers were held to develop a framework of dementia misconceptions based on their experiences. Dementia-related tweets were collected from Twitter's official application programming interface using neutral and negative search terms defined by the literature and by carers (N=48,211). A sample of these tweets was selected with equal numbers of neutral and negative words (n=1497), which was validated in individual ratings by carers. We then used the framework to analyze, in detail, a sample of carer-rated negative tweets (n=863). RESULTS: A total of 25.94% (12,507/48,211) of our tweet corpus contained negative search terms about dementia. The carers' framework had 3 negative and 3 neutral categories. Our thematic analysis of carer-rated negative tweets found 9 themes, including the use of weaponizing language to insult politicians (469/863, 54.3%), using dehumanizing or outdated words or statements about members of the public (n=143, 16.6%), unfounded claims about the cures or causes of dementia (n=11, 1.3%), or providing armchair diagnoses of dementia (n=21, 2.4%). CONCLUSIONS: This is the first study to use participatory methods to develop a framework that identifies dementia misconceptions on Twitter. We show that misconceptions and stigmatizing language are not rare. They manifest through minimizing and underestimating language. Web-based campaigns aiming to reduce discrimination and stigma about dementia could target those who use negative vocabulary and reduce the misconceptions that are being propagated, thus improving general awareness.

Codeveloping and Evaluating a Campaign to Reduce Dementia Misconceptions on Twitter: Machine Learning Study.

Background: Dementia misconceptions on Twitter can have detrimental or harmful effects. Machine learning (ML) models codeveloped with carers provide a method to identify these and help in evaluating awareness campaigns. Objective: This study aimed to develop an ML model to distinguish between misconceptions and neutral tweets and to develop, deploy, and evaluate an awareness campaign to tackle dementia misconceptions. Methods: Taking 1414 tweets rated by carers from our previous work, we built 4 ML models. Using a 5-fold cross-validation, we evaluated them and performed a further blind validation with carers for the best 2 ML models; from this blind validation, we selected the best model overall. We codeveloped an awareness campaign and collected pre-post campaign tweets (N=4880), classifying them with our model as misconceptions or not. We analyzed dementia tweets from the United Kingdom across the campaign period (N=7124) to investigate how current events influenced misconception prevalence during this time. Results: A random forest model best identified misconceptions with an accuracy of 82% from blind validation and found that 37% of the UK tweets (N=7124) about dementia across the campaign period were misconceptions. From this, we could track how the prevalence of misconceptions changed in response to top news stories in the United Kingdom. Misconceptions significantly rose around political topics and were highest (22/28, 79% of the dementia tweets) when there was controversy over the UK government allowing to continue hunting during the COVID-19 pandemic. After our campaign, there was no significant change in the prevalence of misconceptions. Conclusions: Through codevelopment with carers, we developed an accurate ML model to predict misconceptions in dementia tweets. Our awareness campaign was ineffective, but similar campaigns could be enhanced through ML to respond to current events that affect misconceptions in real time.

Transforming access to care for serious mental disorders in slums (the TRANSFORM Project): rationale, design and protocol.

This paper introduces the TRANSFORM project, which aims to improve access to mental health services for people with serious and enduring mental disorders (SMDs - psychotic disorders and severe mood disorders, often with co-occurring substance misuse) living in urban slums in Dhaka (Bangladesh) and Ibadan (Nigeria). People living in slum communities have high rates of SMDs, limited access to mental health services and conditions of chronic hardship. Help is commonly sought from faith-based and traditional healers, but people with SMDs require medical treatment, support and follow-up. This multicentre, international mental health mixed-methods research project will (a) conduct community-based ethnographic assessment using participatory methods to explore community understandings of SMDs and help-seeking; (b) explore the role of traditional and faith-based healing for SMDs, from the perspectives of people with SMDs, caregivers, community members, healers, community health workers (CHWs) and health professionals; (c) co-design, with CHWs and healers, training packages for screening, early detection and referral to mental health services; and (d) implement and evaluate the training packages for clinical and cost-effectiveness in improving access to treatment for those with SMDs. TRANSFORM will develop and test a sustainable intervention that can be integrated into existing clinical care and inform priorities for healthcare providers and policy makers.

Investigating Mental Health Service User Opinions on Clinical Data Sharing: Qualitative Focus Group Study.

BACKGROUND: Sharing patient data can help drive scientific advances and improve patient care, but service users are concerned about how their data are used. When the National Health Service proposes to scrape general practitioner records, it is very important that we understand these concerns in some depth. OBJECTIVE: This study aims to investigate views of mental health service users on acceptable data sharing to provide clear recommendations for future data sharing systems. METHODS: A total of 4 focus groups with 4 member-checking groups were conducted via the internet between October 2020 and March 2021, with a total of 22 service users in the United Kingdom. Thematic analysis was used to identify the themes. RESULTS: Six main themes, with several subthemes were identified, such as the purpose of data sharing-for profit, public good, and continuation of care; discrimination through the misattribution of physical symptoms to mental health conditions (ie, diagnostic overshadowing) alongside the discrimination of individuals or groups within society (ie, institutional discrimination); safeguarding data by preserving anonymity and confidentiality, strengthening security measures, and holding organizations accountable; data accuracy and informed consent-increasing transparency about data use and choice; and incorporating service user involvement in system governance to provide insight and increase security. CONCLUSIONS: This study extends the limited research on the views and concerns of mental health service users regarding acceptable data sharing. If adopted, the recommendations should improve the confidence of service users in sharing their data. The five recommendations include screening to ensure that data sharing benefits the public, providing service users with information about how their data are shared and what for, highlighting the existing safeguarding procedures, incorporating service user involvement, and developing tailored training for health care professionals to address issues of diagnostic overshadowing and inaccurate health records. Adopting such systems would aid in data sharing for legitimate interests that will benefit patients and the National Health Service.