ABSTRACT
Many studies focus on problematic peer functioning in attention deficit/hyperactivity disorder (ADHD) but loneliness has been studied less. This paper examined (1) The loneliness level differences between young people (below 25 years old) with ADHD and those without ADHD, and (2) The association between loneliness and mental health difficulties in young people with ADHD. Six electronic databases were searched and 20 studies were included. A random effects meta-analysis was carried out in RStudio using the metafor package for the first question, while a narrative synthesis summarized the findings for the second question. The meta-analysis (n = 15) found that young people with ADHD reported significantly higher loneliness than those without ADHD, with a small-to-medium weighted pool effect (Hedges' g = 0.41) and high heterogeneity (I2 = 75.1%). For the second question (n = 8), associations between loneliness and mental health difficulties in ADHD was found (r = 0.05-0.68). Targeted research and interventions on loneliness in young people with ADHD is needed.
Subject(s)
Attention Deficit Disorder with Hyperactivity , Humans , Adolescent , Adult , Attention Deficit Disorder with Hyperactivity/psychology , Loneliness/psychology , Mental Health , Databases, FactualABSTRACT
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.
ABSTRACT
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. We also investigated whether treatment responsiveness or experience of invasive tests (brain scans and blood tests) affected participants' responses. Questionnaire generated qualitative data were analyzed thematically. Participants (N108) were aged 18-65, had a diagnosis of schizophrenia, and were adherent to antipsychotic medication. RESULTS: Acceptability of a stratified approach was high, even after participants had experienced invasive tests. Most rated it as safer (62% vs 43%; P < .01 [CI: -1.69 to 2.08]), less risky (77% vs 44%; P < .01 [CI: -1.75 to 1.10]), and less painful (90% vs 73%; P < 0.01 [CI: -0.84 to 0.5]) and this was not affected by treatment responsiveness or test experience. Although not statistically significant, treatment nonresponders were more willing to undergo invasive tests. Qualitatively, all participants raised concerns about the risks, discomfort, and potential side effects associated with the invasive tests. CONCLUSIONS: Service users were positive about a stratified approach for choosing treatments but were wary of devolving clinical decisions to purely data-driven algorithms. These results reinforce the value of service user perspectives in the development and evaluation of novel treatment approaches.
ABSTRACT
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. Focus groups explored their views about clinical use of ketamine and the best way for ketamine to be administered and monitored. The qualitative data were analysed by three service-user researchers using thematic analysis. RESULTS: Five themes were generated: changing public perceptions, risks, monitoring, privacy and data protection, and practical aspects. Participants were conscious of the stigma attached to ketamine as a street drug and wanted better public education, and evidence on the safety of ketamine after long-term use. They felt that monitoring was required to provide evidence for ketamine's safe use and administration, but there were concerns about the misuse of this information. Practical aspects included discussions about treatment duration, administration and accessibility (for example who would receive it, under what criteria and how). CONCLUSIONS: Patients are enthusiastic about ketamine treatment but need more information before national roll-out. The wider societal impact of ketamine treatment also needs to be considered and patients need to be part of any future roll-out to ensure its success.
