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.

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.

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.

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.

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.

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.

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

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. (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.

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.

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.

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.

Investigating Patient Acceptability of Stratified Medicine for Schizophrenia: A Mixed Methods Study.

Background: Health services have advocated a stratified medicine approach in mental health, but little is known about whether service users would accept this approach.

Aims: To explore service users' views of the acceptability of stratified medicine for treatment-resistant schizophrenia compared to the traditional "trial-and-error" approach.

Methods: A mixed methods observational study that explored questionnaire responses on acceptability and whether these responses were affected by demographic or clinical variables.

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.

Terms and conditions apply: Critical issues for readability and jargon in mental health depression apps.

Background: Mental health services are turning to technology to ease the resource burden, but privacy policies are hard to understand potentially compromising consent for people with mental health problems. The FDA recommends a reading grade of 8.

Objective: To investigate and improve the accessibility and acceptability of mental health depression app privacy policies.

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.

Ketamine treatment for depression: qualitative study exploring patient views.

Background: Ketamine is a new and promising treatment for depression but comes with challenges to implement because of its potential for abuse.

Aims: We sought the views of patients to inform policy and practical decisions about the clinical use of ketamine before large-scale roll-out is considered.

Method: This qualitative study used three focus groups and three validation sessions from 14 patients with prior diagnoses of depression but no experience of ketamine treatment.

Exploring patients' and carers' views about the clinical use of ketamine to inform policy and practical decisions: mixed-methods study.

Background: Only one-third of patients with major depressive disorder achieve remission. One new and promising treatment, ketamine, may prove challenging to implement because of its abuse potential. Although clinicians' views have been sought, we need patients' views before large scale roll-out is considered.

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.

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.

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.

"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.

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.

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.

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.