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

Designing Inclusive Qualitative Research with Carers of People Living with Dementia: Methodological Insights

The support provided by carers of people living with dementia results in savings for the UK economy; however, providing this care has a significant impact on carers. Supports are needed to ensure that carers can continue to provide care, and carers should be involved in the generation of the evidence necessary to develop such support. However, this relies on their ability to meaningfully engage with research, yet current data collection methods create obstacles to engagement. In this paper, we aim to provide a critical examination of approaches to qualitative data collection with carers and produce recommendations for the design of inclusive research. First, different approaches to qualitative data collection are discussed and appraised. Following this, a case study of inclusive research is presented, illustrating how carers can be facilitated to engage in research. Finally, recommendations for inclusive research are offered, including the collection of data without the cared-for person present, building additional care into a study design, providing 'incidental funds,' offering sustenance and remuneration, and undertaking research in a neutral space. These recommendations are designed to facilitate the involvement of carers in research and promote the use of more varied or multifaceted methods to develop the current evidence base.

Psychosocial Basis of Human Sufferings and Poverty in Patients with Neurological and Psychiatric Disorders

Neurological disorders and psychiatric ailments often lead to cognitive disabilities and low attainment of education, pivoting misconceptions, myths, and misbeliefs. Poverty and low educational attainment are intriguingly associated with poor awareness and perception of these diseases that add to the suffering. Poverty goes parallel with a low level of education and is intricately associated with neuropsychiatric ailments, which have the potential to spread transgenerationally. Robust education policies, proper government rules and regulations against the spread of disease-related myths and misconceptions, uplifting medical education in its true sense, voices against consanguinity, and programs to raise scientific perception about diseases can help to throw light at the end of this dark tunnel. In this article, the authors intend to 1) decipher the potential psychosocial basis of human suffering and poverty in patients with neurological and psychiatric disorders, and 2) discuss the apropos way-outs that would potentially mitigate suffering, and alleviate the economic burden and cognitive disabilities of families with neuropsychiatric diseases.

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.

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.

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.

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.