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This two day 50th anniversary event (18-19 March) will have a focus on the future of mental health. Sessions will be led by some of the leading experts in psychiatry and cover topics such as psychological treatments, epidemiology and data science, experimental medicine and neuroscience, psychiatry and Oxford medicine.
Effects of 28-day simvastatin administration on emotional processing, reward learning, working memory, and salivary cortisol in healthy participants at-risk for depression: OxSTEP, an online experimental medicine trial.
BACKGROUND: Statins are among the most prescribed medications worldwide. Both beneficial (e.g. antidepressant and pro-cognitive) and adverse (e.g. depressogenic and cognitive-impairing) mental health outcomes have been described in clinical studies. The underlying neuropsychological mechanisms, whether positive or negative, are, however, not established. Clarifying such activities has implications for the safe prescribing and repurposing potential of these drugs, especially in people with depression. METHODS: In this double-blind, randomized, placebo-controlled experimental medicine study, we investigated the effects of simvastatin on emotional processing, reward learning, working memory, and waking salivary cortisol (WSC) in 101 people at-risk for depression due to reported high loneliness scores (mean 7.3 ± 1.2 on the UCLA scale). This trial was largely conducted during periods of social distancing due to the COVID-19 pandemic (July 2021-February 2023), and we employed a fully remote design within a UK-wide sample. RESULTS: High retention rates, minimal outlier data, and typical main effects of task condition (e.g. emotion) were seen in all cognitive tasks, indicating this approach was comparable to in-person testing. After 28 days, we found no statistically significant differences (F's 0.20) for any of the measures of emotional processing, reward learning, working memory, and WSC. CONCLUSIONS: Study results do not substantiate concerns regarding adverse neuropsychiatric events due to statins and support the safety of their prescribing in at-risk populations. Although other unmeasured cognitive processes may be involved, our null findings are also in line with more recent clinical evidence suggesting statins do not show antidepressant or pro-cognitive efficacy.
Incentivising participation in mental health app research: lessons learned from a mixed methods randomised controlled trial
Background User engagement is recognised as a critical and pervasive challenge that has limited the potential evidence base being developed for mental health apps. Aim To understand young people’s motivations for participating in a randomised controlled trial for a mental health app and the role of intrinsic (e.g. improving well-being) and extrinsic (e.g. financial incentives) drivers in engagement. Method Emotional Competence for Well-Being (ECoWeB) was a superiority parallel three-arm randomised cohort trial recruiting a cohort of 16–22 year-olds across the UK, Germany, Spain and Belgium, who, depending on risk, were allocated respectively to the PREVENT (n = 1262) versus PROMOTE (n = 2532) trials. We conducted in-depth semi-structured interviews in the UK (n = 18, mean age = 17.7, s.d. = 1.5) and Spain (n = 11, mean age 20.6, s.d. = 1.7) to explore participants’ self-reported motivations and engagement. The trial was registered at ClinicalTrials.gov: NCT04148508. Results Across arms, 21% of participants never set up an account to access the app and approximately 50% did not complete the 3-month follow-up assessment. Engagement was not significantly higher in the intervention arm compared to the control arms across metrics. Qualitative findings demonstrated that although extrinsic factors alone may be enough to prompt someone to sign up to research, intrinsic drivers (e.g. finding the app useful) are needed to ensure longer-term engagement. Conclusions Incentivising participation in clinical trials needs to be consistent with incentives that might be utilised at the point of dissemination and implementation to ensure that findings are replicated if that intervention is adopted at scale.
Sociodemographic influences on substance use in psychosis in an African cohort.
BACKGROUND: Substance use is common among individuals with psychotic disorders, but limited research exists on the variations in substance use across countries in Africa. This study aims to investigate the frequency of alcohol, tobacco, cannabis, and khat consumption in individuals with bipolar disorder (BD) and schizophrenia (SCZ) across four African countries: South Africa, Ethiopia, Kenya, and Uganda. METHODS: We utilized data from the Neuropsychiatric Genetics of African Populations-Psychosis project, a large case-control study which will soon have genetic data on over 42,000 participants, half with psychosis. Information on substance use was collected using the Alcohol, Smoking and Substance Involvement Screening Test v3 (ASSIST). The outcome was categorized into never (lifetime usage, no), irregular usage (weekly or monthly) and regular (daily use) based on reported frequency in the past three months. Each substance was modeled individually as an outcome in ordinal regression model adjusting for demographic factors of sex, education and country. Stratified analyses were performed to assess country-specific effects. RESULTS: Individuals with BD had significantly higher odds of alcohol consumption compared to those with SCZ. Males showed higher odds of alcohol, tobacco, and khat consumption compared to females. Significant variations in alcohol, tobacco, and cannabis consumption were observed across different study countries. Education level was significantly associated with khat consumption, with higher education levels associated with lower odds of consumption. CONCLUSION: Country and sex-specific differences in substance use behaviors exist in a large-scale African case-control study of people with psychosis. The findings here are in line with previous work regarding sex and regional differences, though they differ from studies conducted in US populations in that minimal evidence was found to support a relationship between level of education and frequency of substance use for any of the substances studied. This suggests that there may be distinct sociodemographic correlates of substance use in Africa and highlights the critical need to consider individuals of diverse ancestry in large-scale studies while also taking into account regional differences when examining substance use behaviors.
Coming to terms with climate change: a glossary for climate change impacts on mental health and well-being.
Climate change is a major threat to global health. Its effects on physical health are increasingly recognised, but mental health impacts have received less attention. The mental health effects of climate change can be direct (resulting from personal exposure to acute and chronic climatic changes), indirect (via the impact on various socioeconomic, political and environmental determinants of mental health) and overarching (via knowledge, education and awareness of climate change). These impacts are unequally distributed according to long-standing structural inequities which are exacerbated by climate change. We outline key concepts and pathways through which climate change may affect mental health and explore the responses to climate change at different levels, from emotions to politics, to highlight the need for multilevel action. We provide a broad reference to help guide researchers, practitioners and policy-makers in the use and understanding of different terms in this rapidly growing interdisciplinary field.
Wasting coexisting with underweight and stunting among children aged 6‒59 months hospitalised in Garissa County Referral Hospital, Kenya.
Management of undernourished children depends only on wasting yet it can coexist with underweight and/or stunting. Among children admitted to hospital with acute illness, we determined the proportion with wasting coexisting with underweight and/or stunting and their risk factors. A retrospective review of hospital records of children 6‒59 months old admitted at Garissa County referral hospital, Kenya, from January 2017 to December 2019 was conducted. Using World Health Organization 2006 growth standards, undernutrition were defined: wasting as Weight-for-height Z-score
Evaluating the generalisability of region-naïve machine learning algorithms for the identification of epilepsy in low-resource settings.
OBJECTIVES: Approximately 80% of people with epilepsy live in low- and middle-income countries (LMICs), where limited resources and stigma hinder accurate diagnosis and treatment. Clinical machine learning models have demonstrated substantial promise in supporting the diagnostic process in LMICs by aiding in preliminary screening and detection of possible epilepsy cases without relying on specialised or trained personnel. How well these models generalise to naïve regions is, however, underexplored. Here, we use a novel approach to assess the suitability and applicability of such clinical tools to aid screening and diagnosis of active convulsive epilepsy in settings beyond their original training contexts. METHODS: We sourced data from the Study of Epidemiology of Epilepsy in Demographic Sites dataset, which includes demographic information and clinical variables related to diagnosing epilepsy across five sub-Saharan African sites. For each site, we developed a region-specific (single-site) predictive model for epilepsy and assessed its performance at other sites. We then iteratively added sites to a multi-site model and evaluated model performance on the omitted regions. Model performances and parameters were then compared across every permutation of sites. We used a leave-one-site-out cross-validation analysis to assess the impact of incorporating individual site data in the model. RESULTS: Single-site clinical models performed well within their own regions, but generally worse when evaluated in other regions (p<0.05). Model weights and optimal thresholds varied markedly across sites. When the models were trained using data from an increasing number of sites, mean internal performance decreased while external performance improved. CONCLUSIONS: Clinical models for epilepsy diagnosis in LMICs demonstrate characteristic traits of ML models, such as limited generalisability and a trade-off between internal and external performance. The relationship between predictors and model outcomes also varies across sites, suggesting the need to update specific model aspects with local data before broader implementation. Variations are likely to be particular to the cultural context of diagnosis. We recommend developing models adapted to the cultures and contexts of their intended deployment and caution against deploying region- and culture-naïve models without thorough prior evaluation.
Risk of epilepsy following first unprovoked and acute seizures: Cohort study.
OBJECTIVE: First unprovoked seizures and acute seizures are common and can develop into epilepsy. The risk of epilepsy following these seizures in community samples is not well established, and it is unclear whether the probability of subsequent unprovoked seizures following these seizures reaches the International League Against Epilepsy's threshold of 60%. METHODS: We followed participants initially classified as having first unprovoked seizures, having acute seizures, or without seizures in a community-based survey conducted in 2003 to estimate the subsequent risk of epilepsy in 2008 and 2021. The diagnosis of epilepsy in 2008 and 2021 was based on data from a community survey and health care visits to Kilifi County Hospital and the epilepsy clinic. Poisson regression models were used to compute incident risk ratios (IRRs) for epilepsy and population-attributable risk (PAR); population-attributable risk fractions (PAFs) were computed from contingency tables. RESULTS: In the 5-year follow-up (censored in 2008 survey), the IRR for epilepsy was 23.3 (95% confidence interval [CI] = 14.2-38.2) for first unprovoked seizures and 10.4 (95% CI = 5.6-19.5) for acute seizures compared to the no-seizure group. By 2021 (including 2008), the IRR was 18.4 (95% CI = 11.9-28.5) for first unprovoked seizures and 7.9 (95% CI = 4.3-14.5) for acute seizures compared to the no-seizure group. The PAR for first unprovoked seizures and acute seizures was 29.0 and 8.0/1000 persons in the long-term follow-up. The PAF was 56.3% for first unprovoked seizures and 26.3% for acute seizures in the long-term follow-up. There was a high probability that a person with acute seizures (72%) or first unprovoked seizures (92%) developed epilepsy earlier than a person from the comparison group. SIGNIFICANCE: First unprovoked seizures and acute seizures are associated with high risk for developing epilepsy. Neurological correlates for epilepsy risk following first unprovoked seizures should be investigated to inform epilepsy diagnosis and treatment.
Evaluation of the psychometric properties of the UBACC questionnaire in a multi-country psychiatric study in Africa.
BACKGROUND: The University of California, San Diego Brief Assessment of Capacity to Consent (UBACC) is a tool to assess the capacity of participants to consent in psychiatric research. However, little is known about the psychometric properties in low and middle-income countries. This study aimed to examine the psychometric properties of the UBACC. METHODS: We examined the reliability, latent factor structure, and item response of the first attempt of the UBACC items in a sample of 32,208 adults (16,467 individuals with psychosis and 15,741 controls) in Ethiopia, Kenya, South Africa, and Uganda; exploring these properties in the full sample and stratified by country, diagnostic status, sex, and ethnolinguistic language groups. RESULTS: Exploratory factor analysis (EFA) suggested a two-factor model for the overall sample. However, a three-factor model was more appropriate when examining the latent structure across country, language, and sex. Confirmatory factor analyses (CFA) revealed an adequately fitting three-factor model for the full sample and across country, sex, and language. A two-factor model, however, was more appropriate for English and Amharic languages. Across all groups, the internal consistency of the UBACC was low, indicating below-threshold reliability (Cronbach's α (95 % CI = 0.58 (0.57-0.59). Using a multidimensional item-response theory framework for the full sample revealed that UBACC item 8, measuring understanding of the benefits of study participation, was the most discriminating item. Many of the other items had below-threshold discriminating characteristics. CONCLUSION: EFA and CFA converged towards a two and three-dimensional structure for the UBACC, in line with the developers of the original scale. The differences in properties between populations and language groups, low internal consistency, and below-threshold item functioning suggest that investigations into the cultural and linguistic nuances are still warranted. Understanding the utility of consent tools, such as the UBACC, in underrepresented populations will be a part of the larger process which ensures that research participants are adequately protected.
Psychological Distress Among Ethnically Diverse Participants From Eastern and Southern Africa.
IMPORTANCE: Psychological distress is characterized by anxiety and depressive symptoms. Although prior research has investigated the occurrence and factors associated with psychological distress in low- and middle-income countries, including those in Africa, these studies' findings are not very generalizable and have focused on different kinds of population groups. OBJECTIVE: To investigate the prevalence and characteristics (sociodemographic, psychosocial, and clinical) associated with psychological distress among African participants. DESIGN, SETTING, AND PARTICIPANTS: This case-control study analyzed data of participants in the Neuropsychiatric Genetics in African Populations-Psychosis (NeuroGAP-Psychosis) study, which recruited from general outpatient clinics in Eastern (Uganda, Kenya, and Ethiopia) and Southern (South Africa) Africa. Individuals who participated in the control group of NeuroGAP-Psychosis from 2018 to 2023 were analyzed as part of this study. Data were analyzed from May 2023 to January 2024. MAIN OUTCOMES AND MEASURES: The prevalence of psychological distress was determined using the Kessler Psychological Distress Scale (K10), which measures distress on a scale of 10 to 50, with higher scores indicating more distress. Participants from the NeuroGAP-Psychosis study were categorized into cases as mild (score of 20-24), moderate (score of 25-29), and severe (score of 30-50), and participants with scores less than 20 were considered controls. Factors that were associated with psychological distress were examined using binomial logistic regression. RESULTS: From the data on 21 308 participants, the mean (SD) age was 36.5 (11.8) years, and 12 096 participants (56.8%) were male. The majority of the participants were married or cohabiting (10 279 participants [48.2%]), most had attained secondary education as their highest form of learning (9133 participants [42.9%]), and most lived with their families (17 231 participants [80.9%]). The prevalence of mild, moderate, and severe psychological distress was 4.2% (869 participants), 1.5% (308 participants), and 0.8% (170 participants), respectively. There were 19 961 participants (93.7%) who served as controls. Binomial logistic regression analyses indicated that the independent associations of psychological distress were experience of traumatic events, substance use (alcohol, tobacco, or cannabis), the physical comorbidity of arthritis, chronic neck or back pain, and frequent or severe headaches. CONCLUSIONS AND RELEVANCE: In this case-control study among ethnically diverse African participants, psychological distress was associated with traumatic stress, substance use, and physical symptoms. These findings were observed to be consistent with previous research that emphasizes the importance of traumatic events as a factor associated with risk for psychopathology and notes the frequent co-occurrence of conditions such as physical symptoms, depression, and anxiety.
Correction: Evaluating the generalisability of region-naïve machine learning algorithms for the identification of epilepsy in low-resource settings.
[This corrects the article DOI: 10.1371/journal.pdig.0000491.].
Integrating alternative and complementary medicine in the management of epilepsy and its comorbidities in low- and middle-income settings.
Traditional/alternative and complementary medicine (TCM) encompasses products, practices and practitioners that do not form part of conventional treatment and are not an integral part of the main health care systems. They are very common in the management of epilepsy and mental health conditions, particularly in low- and middle-income countries (LMIC). For instance, in a population-based survey in Africa, over 70% of people with epilepsy had visited a traditional health practitioner before the survey, with similarly high estimates reported in Asia and South America. Accessibility, cultural appropriateness/alignment, non-response to conventional (biomedical) medicine, and exercise of control over one's treatment were some of the reasons TCM was preferred over conventional medicine. There is also emerging evidence that TCM products administered alone or together with anti-seizure medications result in improvement in seizure control, psychiatric comorbidities, and quality of life. Most of the convincing evidence is from biological-based therapies for example, multivitamin supplementation, ketogenic diet and cannabidiol extracts. Mind-based therapies e.g. Yoga and whole-body systems therapies e.g. Ayurdelic and Traditional Chinese Medicine have also generated interest in epilepsy care. There is a paucity of effectiveness studies of these therapies in LMIC such as Africa, where capacity to take these products through clinical trials is limited. There are however serious concerns on reliability of reported findings because of inadequate randomization, and small sample sizes, and concerns on quality and safety owing to lack of standardization of bioactive compounds, accidental or intention botanical substitution of products and unhygienic handling. There is growing interest in TCM worldwide because of its economic potential, concerns on safety and quality and potential for integration into the health care systems. There is urgent need to develop and implement national TCM regulatory policies and programmes aimed at expanding the knowledge base and providing guidance on quality assurance standards. However, LMIC continue to lag in implementation of these policies and guidelines, especially in the areas of research and development and regulation of TCM practice. Working with stakeholders, countries are advised to assess their own national situations in relation to TCM, and then develop practical solutions to accommodate these approaches. For instance, conduct surveys on benefits and risks of TCM in the management of epilepsy in the local context and use this information to promote appreciation of a role for TCM, which will ease integration into the main health systems.