The global macroeconomic burden of Alzheimer's disease and other dementias: estimates and projections for 152 countries or territories.

BACKGROUND: Alzheimer's disease and other dementias (ADODs) severely threaten the wellbeing of older people, their families, and communities, especially with projected exponential growth. Understanding the macroeconomic implications of ADODs for policy making is essential but under-researched. METHODS: We used a health-augmented macroeconomic model to calculate the macroeconomic burden of ADODs for 152 countries or territories, accounting for: the effect on labour supply of reduced working hours of informal caregivers; the effect on labour supply of ADODs-related mortality and morbidity; age-sex-specific differences in education, work experience, labour market participations, and informal caregivers; and treatment and formal care costs diverting from savings and investments. FINDINGS: ADODs will cost the world economy 14 513 billion international dollars (INT$, measured in the base year 2020; 95% uncertainty interval [UI] 12 106-17 778) from 2020 to 2050, equivalent to 0·421% (95% UI 0·351-0·515) of annual global GDP. Japan incurs the largest annual GDP loss at 1·463% (1·225-1·790). China (INT$2961 billion [2507-3564]), the USA (INT$2331 billion [1989-2829]), and Japan (INT$1758 billion [1471-2150]) face the largest absolute economic burdens. The economic burden of informal care ranges from 60·97% in high-income countries to 85·45% in lower-middle-income countries, and treatment and formal care costs range from 10·50% in lower-middle-income countries to 30·80% in high-income countries. INTERPRETATION: The macroeconomic burden of ADODs is substantial and unequally distributed across countries and regions. Global efforts to reduce the burden, especially with regard to informal care, are urgently needed. FUNDING: National Institute on Aging, National Institutes of Health; Chinese Academy of Engineering; Chinese Academy of Medical Sciences; Bill & Melinda Gates Foundation; Davos Alzheimer's Collaborative through Data for Decisions.

Effectiveness of the Minder Mobile Mental Health and Substance Use Intervention for University Students: Randomized Controlled Trial.

BACKGROUND: University attendance represents a transition period for students that often coincides with the emergence of mental health and substance use challenges. Digital interventions have been identified as a promising means of supporting students due to their scalability, adaptability, and acceptability. Minder is a mental health and substance use mobile app that was codeveloped with university students. OBJECTIVE: This study aims to examine the effectiveness of the Minder mobile app in improving mental health and substance use outcomes in a general population of university students. METHODS: A 2-arm, parallel-assignment, single-blinded, 30-day randomized controlled trial was used to evaluate Minder using intention-to-treat analysis. In total, 1489 participants were recruited and randomly assigned to the intervention (n=743, 49.9%) or waitlist control (n=746, 50.1%) condition. The Minder app delivers evidence-based content through an automated chatbot and connects participants with services and university social groups. Participants are also assigned a trained peer coach to support them. The primary outcomes were measured through in-app self-assessments and included changes in general anxiety symptomology, depressive symptomology, and alcohol consumption risk measured using the 7-item General Anxiety Disorder scale, 9-item Patient Health Questionnaire, and US Alcohol Use Disorders Identification Test-Consumption Scale, respectively, from baseline to 30-day follow-up. Secondary outcomes included measures related to changes in the frequency of substance use (cannabis, alcohol, opioids, and nonmedical stimulants) and mental well-being. Generalized linear mixed-effects models were used to examine each outcome. RESULTS: In total, 79.3% (589/743) of participants in the intervention group and 83% (619/746) of participants in the control group completed the follow-up survey. The intervention group had significantly greater average reductions in anxiety symptoms measured using the 7-item General Anxiety Disorder scale (adjusted group mean difference=-0.85, 95% CI -1.27 to -0.42; P<.001; Cohen d=-0.17) and depressive symptoms measured using the 9-item Patient Health Questionnaire (adjusted group mean difference=-0.63, 95% CI -1.08 to -0.17; P=.007; Cohen d=-0.11). A reduction in the US Alcohol Use Disorders Identification Test-Consumption Scale score among intervention participants was also observed, but it was not significant (P=.23). Statistically significant differences in favor of the intervention group were found for mental well-being and reductions in the frequency of cannabis use and typical number of drinks consumed. A total of 77.1% (573/743) of participants in the intervention group accessed at least 1 app component during the study period. CONCLUSIONS: In a general population sample of university students, the Minder app was effective in reducing symptoms of anxiety and depression, with provisional support for increasing mental well-being and reducing the frequency of cannabis and alcohol use. These findings highlight the potential ability of e-tools focused on prevention and early intervention to be integrated into existing university systems to support students' needs. TRIAL REGISTRATION: ClinicalTrials.gov NCT05606601; https://clinicaltrials.gov/ct2/show/NCT05606601. INTERNATIONAL REGISTERED REPORT IDENTIFIER (IRRID): RR2-10.2196/49364.

Factors associated with satisfaction and perceived helpfulness of mental healthcare: a World Mental Health Surveys report.

BACKGROUND: Mental health service providers are increasingly interested in patient perspectives. We examined rates and predictors of patient-reported satisfaction and perceived helpfulness in a cross-national general population survey of adults with 12-month DSM-IV disorders who saw a provider for help with their mental health. METHODS: Data were obtained from epidemiological surveys in the World Mental Health Survey Initiative. Respondents were asked about satisfaction with treatments received from up to 11 different types of providers (very satisfied, satisfied, neither satisfied nor dissatisfied, somewhat dissatisfied, very dissatisfied) and helpfulness of the provider (a lot, some, a little, not at all). We modelled predictors of satisfaction and helpfulness using a dataset of patient-provider observations (n = 5,248). RESULTS: Most treatment was provided by general medical providers (37.4%), psychiatrists (18.4%) and psychologists (12.7%). Most patients were satisfied or very satisfied (65.9-87.5%, across provider) and helped a lot or some (64.4-90.3%). Spiritual advisors and healers were most often rated satisfactory and helpful. Social workers in human services settings were rated lowest on both dimensions. Patients also reported comparatively low satisfaction with general medical doctors and psychiatrists/psychologists and found general medical doctors less helpful than other providers. Men and students reported lower levels of satisfaction than women and nonstudents. Respondents with high education reported higher satisfaction and helpfulness than those with lower education. Type of mental disorder was unrelated to satisfaction but in some cases (depression, bipolar spectrum disorder, social phobia) was associated with low perceived helpfulness. Insurance was unrelated to either satisfaction or perceived helpfulness but in some cases was associated with elevated perceived helpfulness for a given level of satisfaction. CONCLUSIONS: Satisfaction with and perceived helpfulness of treatment varied as a function of type of provider, service setting, mental status, and socio-demographic variables. Invariably, caution is needed in combining data from multiple countries where there are cultural and service delivery variations. Even so, our findings underscore the utility of patient perspectives in treatment evaluation and may also be relevant in efforts to match patients to treatments.

Cost of care for Alzheimer's disease and related dementias in the United States: 2016 to 2060.

Medical and long-term care for Alzheimer's disease and related dementias (ADRDs) can impose a large economic burden on individuals and societies. We estimated the per capita cost of ADRDs care in the in the United States in 2016 and projected future aggregate care costs during 2020-2060. Based on a previously published methodology, we used U.S. Health and Retirement Survey (2010-2016) longitudinal data to estimate formal and informal care costs. In 2016, the estimated per patient cost of formal care was $28,078 (95% confidence interval [CI]: $25,893-$30,433), and informal care cost valued in terms of replacement cost and forgone wages was $36,667 ($34,025-$39,473) and $15,792 ($12,980-$18,713), respectively. Aggregate formal care cost and formal plus informal care cost using replacement cost and forgone wage methods were $196 billion (95% uncertainty range [UR]: $179-$213 billion), $450 billion ($424-$478 billion), and $305 billion ($278-$333 billion), respectively, in 2020. These were projected to increase to $1.4 trillion ($837 billion-$2.2 trillion), $3.3 trillion ($1.9-$5.1 trillion), and $2.2 trillion ($1.3-$3.5 trillion), respectively, in 2060.

Sociodemographic Correlates of Mental Health Treatment Seeking Among College Students: A Systematic Review and Meta-Analysis.

OBJECTIVE: College students have high rates of mental health problems and low rates of treatment. Although sociodemographic disparities in student mental health treatment seeking have been reported, findings have not been synthesized and quantified. The extent to which differences in perceived need for treatment contribute to overall disparities remains unclear. METHODS: A systematic search of PubMed, PsycInfo, and Embase was conducted. Studies published between 2007 and 2022 were included if they reported treatment rates among college students with mental health problems, stratified by sex, gender, race-ethnicity, sexual orientation, student type, student year, or student status. Random-effects models were used to calculate pooled prevalence ratios (PRs) of having a perceived need for treatment and of receiving treatment for each sociodemographic subgroup. RESULTS: Twenty-one studies qualified for inclusion. Among students experiencing mental health problems, consistent and significant sociodemographic differences were identified in perceived need for treatment and treatment receipt. Students from racial-ethnic minority groups (in particular, Asian students [PR=0.49]) and international students (PR=0.63) reported lower rates of treatment receipt than White students and domestic students, respectively. Students identifying as female (sex) or as women (gender) (combined PR=1.33) reported higher rates of treatment receipt than students identifying as male or as men. Differences in perceived need appeared to contribute to some disparities; in particular, students identifying as male or as men reported considerably lower rates of perceived need than students identifying as female or as women. CONCLUSIONS: Findings highlight the need for policy makers to address barriers throughout the treatment-seeking pathway and to tailor efforts to student subgroups to reduce treatment disparities.

A platform for connecting social media data to domain-specific topics using large language models: an application to student mental health.

Objectives: To design a novel artificial intelligence-based software platform that allows users to analyze text data by identifying various coherent topics and parts of the data related to a specific research theme-of-interest (TOI). Materials and Methods: Our platform uses state-of-the-art unsupervised natural language processing methods, building on top of a large language model, to analyze social media text data. At the center of the platform's functionality is BERTopic, which clusters social media posts, forming collections of words representing distinct topics. A key feature of our platform is its ability to identify whole sentences corresponding to topic words, vastly improving the platform's ability to perform downstream similarity operations with respect to a user-defined TOI. Results: Two case studies on mental health among university students are performed to demonstrate the utility of the platform, focusing on signals within social media (Reddit) data related to depression and their connection to various emergent themes within the data. Discussion and Conclusion: Our platform provides researchers with a readily available and inexpensive tool to parse large quantities of unstructured, noisy data into coherent themes, as well as identifying portions of the data related to the research TOI. While the development process for the platform was focused on mental health themes, we believe it to be generalizable to other domains of research as well.

Patterns, predictors, and patient-reported reasons for antidepressant discontinuation in the WHO World Mental Health Surveys.

BACKGROUND: Despite their documented efficacy, substantial proportions of patients discontinue antidepressant medication (ADM) without a doctor's recommendation. The current report integrates data on patient-reported reasons into an investigation of patterns and predictors of ADM discontinuation. METHODS: Face-to-face interviews with community samples from 13 countries (n = 30 697) in the World Mental Health (WMH) Surveys included n = 1890 respondents who used ADMs within the past 12 months. RESULTS: 10.9% of 12-month ADM users reported discontinuation-based on recommendation of the prescriber while 15.7% discontinued in the absence of prescriber recommendation. The main patient-reported reason for discontinuation was feeling better (46.6%), which was reported by a higher proportion of patients who discontinued within the first 2 weeks of treatment than later. Perceived ineffectiveness (18.5%), predisposing factors (e.g. fear of dependence) (20.0%), and enabling factors (e.g. inability to afford treatment cost) (5.0%) were much less commonly reported reasons. Discontinuation in the absence of prescriber recommendation was associated with low country income level, being employed, and having above average personal income. Age, prior history of psychotropic medication use, and being prescribed treatment from a psychiatrist rather than from a general medical practitioner, in comparison, were associated with a lower probability of this type of discontinuation. However, these predictors varied substantially depending on patient-reported reasons for discontinuation. CONCLUSION: Dropping out early is not necessarily negative with almost half of individuals noting they felt better. The study underscores the diverse reasons given for dropping out and the need to evaluate how and whether dropping out influences short- or long-term functioning.

Patterns of anxiety, depression, and substance use risk behaviors among university students in Canada.

Objective: To identify subgroups of students with distinct profiles of mental health symptoms (MH) and substance use risk (SU) and the extent to which MH history and socio-demographics predict subgroup membership. Participants: University students (N = 10,935: 63% female). Methods: Repeated cross-sectional survey administered weekly to stratified random samples. Latent class analysis (LCA) was used to identify subgroups and multinomial regression was used to examine associations with variables of interest. Results: LCA identified an optimal 4-latent class solution: High MH-Low SU (47%), Low MH-Low SU (22%), High MH-High SU (19%), and Low MH-High SU (12%). MH history, gender, and ethnicity were associated with membership in the classes with high risk of MH, SU, or both. Conclusion: A substantial proportion of students presented with MH, SU, or both. Gender, ethnicity and MH history is associated with specific patterns of MH and SU, offering potentially useful information to tailor early interventions.

"Multivariate analysis of the impact of sleep and working hours on medical errors: a MICE approach".

BACKGROUND: The main objective of this study was to describe the relationship between working conditions, sleep and psycho-affective variables and medical errors. METHODS: This was an observational, analytical and cross-sectional study in which 661 medical residents answered questionnaires about working conditions, sleep and psycho-affective variables. Actigraphic sleep parameters and peripheral temperature circadian rhythm were measured in a subgroup of 38 subjects. Bivariate and multivariate predictors of medical errors were assessed. RESULTS: Medical residents reported working 66.2 ± 21.9 weekly hours. The longest continuous shift was of 28.4 ± 10.9 h. They reported sleeping 6.1 ± 1.6 h per day, with a sleep debt of 94 ± 129 min in workdays. A high percentage of them reported symptoms related to psycho-affective disorders. The longest continuous shift duration (OR = 1.03 [95% CI, 1.00-1.05], p = 0.01), working more than six monthly on-call shifts (OR = 1.87 [95% CI, 1.16-3.02], p = 0.01) and sleeping less than six hours per working day (OR = 1.66 [95% CI, 1.10-2.51], p = 0.02) were independently associated with self-reported medical errors. The report of medical errors was associated with an increase in the percentage of diurnal sleep (2.2% [95% CI, 0.1-4.3] vs 14.5% [95% CI, 5.9-23.0]; p = 0.01) in the actigraphic recording. CONCLUSIONS: Medical residents have a high working hour load that affect their sleep opportunities, circadian rhythms and psycho-affective health, which are also related to the report of medical errors. These results highlight the importance of implementing multidimensional strategies to improve medical trainees' sleep and wellbeing, increasing in turn their own and patients' safety.

Evaluating the Effectiveness of a Codeveloped e-Mental Health Intervention for University Students: Protocol for a Randomized Controlled Trial.

BACKGROUND: University life typically occurs during a period of life transition, where the incidence of mental health and substance use problems and disorders peaks. However, relatively few students obtain effective treatment and support. e-Interventions have proven effective in improving the psychological outcomes of university students and have the potential to provide scalable services that can easily integrate into existing models of care. Minder is a mobile app codeveloped with university students that offers users a collection of evidence-based interventions tailored to help university students maintain their mental health and well-being and manage their substance use. OBJECTIVE: This paper describes the protocol for a randomized controlled trial (RCT) that aims to assess the effectiveness of the Minder app in improving the mental health and substance use outcomes of university students. METHODS: This study is a 2-arm, parallel assignment, single-blinded, 30-day RCT with 1 intervention group and 1 waitlist control group. Overall, 1496 (748 per trial arm) university students from the University of British Columbia Vancouver Campus (N=54,000) who are aged ≥17 years, have a smartphone with Wi-Fi or cellular data, and speak English will be recruited via a variety of web-based and offline strategies. Participants will be randomized into the intervention or control group after completing a baseline survey. Those randomized into the intervention group will gain immediate access to the Minder app and will be assessed at 2 weeks and 30 days. Those randomized into the control group will be given access to the app content after their follow-up assessment at 30 days. The primary outcomes are measured from baseline to follow-up at 30 days and include changes in general anxiety symptomology, depressive symptomology, and alcohol consumption risk measured by the General Anxiety Disorder 7-Item scale, Patient Health Questionnaire 9-Item scale, and US Alcohol Use Disorders Identification Test-Consumption Scale, respectively. Secondary outcomes include measures related to changes in the frequency of substance use, mental well-being, self-efficacy in managing mental health and substance use, readiness to change, and self-reported use of mental health services and supports (including referral) from baseline to follow-up at 30 days. RESULTS: Trial recruitment and data collection began in September 2022, and the completion of data collection for the trial is anticipated by June 2023. As of May 10, 2023, a total of 1425 participants have been enrolled. CONCLUSIONS: The RCT described in this protocol paper will assess whether the Minder app is effective in improving the mental health and substance use outcomes of a general population of Canadian university students. Additional secondary outcome research aims to explore additional outcomes of interest for further research and better understand how to support students' general mental well-being. TRIAL REGISTRATION: ClinicalTrials.gov NCT05606601; https://clinicaltrials.gov/ct2/show/NCT05606601. INTERNATIONAL REGISTERED REPORT IDENTIFIER (IRRID): DERR1-10.2196/49364.

Towards measuring effective coverage: critical bottlenecks in quality- and user-adjusted coverage for major depressive disorder in São Paulo metropolitan area, Brazil.

BACKGROUND: Major depressive disorder (MDD) contributes to a significant proportion of disease burden, disability, economic losses, and impact on need of treatment and health care in Brazil, but systematic information about its treatment coverage is scarce. This paper aims to estimate the gap in treatment coverage for MDD and identify key bottlenecks in obtaining adequate treatment among adult residents in the São Paulo Metropolitan area, Brazil. METHODS: A representative face-to-face household survey was conducted among 2942 respondents aged 18+ years to assess 12-month MDD, characteristics of 12-month treatment received, and bottlenecks to deliver care through the World Mental Health Composite International Diagnostic Interview. RESULTS: Among those with MDD (n = 491), 164 (33.3% [SE, 1.9]) were seen in health services, with an overall 66.7% treatment gap, and only 25.2% [SE, 4.2] received effective treatment coverage, which represents 8.5% of those in need, with a 91.5% gap in adequate care (66.4% due to lack of utilization and 25.1% due to inadequate quality and adherence). Critical service bottlenecks identified were: use of psychotropic medication (12.2 percentage points drop), use of antidepressants (6.5), adequate medication control (6.8), receiving psychotherapy (19.8). CONCLUSIONS: This is the first study demonstrating the huge treatment gaps for MDD in Brazil, considering not only overall coverage, but also identifying specific quality- and user-adjusted bottlenecks in delivering pharmacological and psychotherapeutic care. These results call for urgent combined actions focused in reducing effective treatment gaps within services utilization, as well as in reducing gaps in availability and accessibility of services, and acceptability of care for those in need.

An Exploratory Study of Sleep-Wake Differences of Autonomic Activity in Patients with Mild Cognitive Impairment: The Role of Melatonin as a Modulating Factor.

Purpose: The objective of the present study was to assess sleep-wake differences of autonomic activity in patients with mild cognitive impairment (MCI) compared to control subjects. As a post-hoc objective, we sought to evaluate the mediating effect of melatonin on this association. Patients and Methods: A total of 22 MCI patients (13 under melatonin treatment) and 12 control subjects were included in this study. Sleep-wake periods were identified by actigraphy and 24hr-heart rate variability measures were obtained to study sleep-wake autonomic activity. Results: MCI patients did not show any significant differences in sleep-wake autonomic activity when compared to control subjects. Post-hoc analyses revealed that MCI patients not taking melatonin displayed lower parasympathetic sleep-wake amplitude than controls not taking melatonin (RMSSD -7 ± 1 vs 4 ± 4, p = 0.004). In addition, we observed that melatonin treatment was associated with greater parasympathetic activity during sleep (VLF 15.5 ± 0.1 vs 15.1 ± 0.1, p = 0.010) and in sleep-wake differences in MCI patients (VLF 0.5 ± 0.1 vs 0.2 ± 0.0, p = 0.004). Conclusion: These preliminary findings hint at a possible sleep-related parasympathetic vulnerability in patients at prodromal stages of dementia as well as a potential protective effect of exogenous melatonin in this population.

Antidepressant use in low- middle- and high-income countries: a World Mental Health Surveys report.

BACKGROUND: The most common treatment for major depressive disorder (MDD) is antidepressant medication (ADM). Results are reported on frequency of ADM use, reasons for use, and perceived effectiveness of use in general population surveys across 20 countries. METHODS: Face-to-face interviews with community samples totaling n = 49 919 respondents in the World Health Organization (WHO) World Mental Health (WMH) Surveys asked about ADM use anytime in the prior 12 months in conjunction with validated fully structured diagnostic interviews. Treatment questions were administered independently of diagnoses and asked of all respondents. RESULTS: 3.1% of respondents reported ADM use within the past 12 months. In high-income countries (HICs), depression (49.2%) and anxiety (36.4%) were the most common reasons for use. In low- and middle-income countries (LMICs), depression (38.4%) and sleep problems (31.9%) were the most common reasons for use. Prevalence of use was 2-4 times as high in HICs as LMICs across all examined diagnoses. Newer ADMs were proportionally used more often in HICs than LMICs. Across all conditions, ADMs were reported as very effective by 58.8% of users and somewhat effective by an additional 28.3% of users, with both proportions higher in LMICs than HICs. Neither ADM class nor reason for use was a significant predictor of perceived effectiveness. CONCLUSION: ADMs are in widespread use and for a variety of conditions including but going beyond depression and anxiety. In a general population sample from multiple LMICs and HICs, ADMs were widely perceived to be either very or somewhat effective by the people who use them.

Determinants of effective treatment coverage for posttraumatic stress disorder: findings from the World Mental Health Surveys.

BACKGROUND: Posttraumatic stress disorder (PTSD) is associated with significant morbidity, but efficacious pharmacotherapy and psychotherapy are available. Data from the World Mental Health Surveys were used to investigate extent and predictors of treatment coverage for PTSD in high-income countries (HICs) as well as in low- and middle-income countries (LMICs). METHODS: Seventeen surveys were conducted across 15 countries (9 HICs, 6 LMICs) by the World Health Organization (WHO) World Mental Health Surveys. Of 35,012 respondents, 914 met DSM-IV criteria for 12-month PTSD. Components of treatment coverage analyzed were: (a) any mental health service utilization; (b) adequate pharmacotherapy; (c) adequate psychotherapy; and (d) effective treatment coverage. Regression models investigated predictors of treatment coverage. RESULTS: 12-month PTSD prevalence in trauma exposed individuals was 1.49 (S.E., 0.08). A total of 43.0% (S.E., 2.2) received any mental health services, with fewer receiving adequate pharmacotherapy (13.5%), adequate psychotherapy (17.2%), or effective treatment coverage (14.4%), and with all components of treatment coverage lower in LMICs than HICs. In a multivariable model having insurance (OR = 2.31, 95 CI 1.17, 4.57) and severity of symptoms (OR = .35, 95% CI 0.18, 0.70) were predictive of effective treatment coverage. CONCLUSION: There is a clear need to improve pharmacotherapy and psychotherapy coverage for PTSD, particularly in those with mild symptoms, and especially in LMICs. Universal health care insurance can be expected to increase effective treatment coverage and therefore improve outcomes.

Suicidal Ideation Amongst University Students During the COVID-19 Pandemic: Time Trends and Risk Factors.

OBJECTIVE: Examine time trends in suicidal ideation in post-secondary students over the first three waves of the COVID-19 pandemic in Canada and identify subpopulations of students with increased risk. METHOD: We analysed 14 months of data collected through repeated cross-sectional deployment of the World Health Organization (WHO) World Mental Health-International College Student (WMH-ICS) survey at the University of British Columbia. Estimated log odds weekly trends of 30-day suicidal ideation (yes/no) were plotted against time with adjustments for demographics using binary logistic generalized additive model (GAM). Risk factors for 30-day suicidal ideation frequency (four categories) were examined using the ordered logistic GAM, with a cubic smoothing spline for modelling time trend in obervation weeks and accounting for demographics. RESULTS: Nearly one-fifth (18.9%) of students experienced suicidal ideation in the previous 30 days. While the estimated log odds suggested that binary suicidal ideation was relatively stable across the course of the pandemic, an initial drop followed by an increasing trend was observed. Risk factors for suicidal ideation frequency during the pandemic included identifying as Chinese or as another non-Indigenous ethnic minority; experiencing current symptoms of depression or anxiety; having a history of suicidal planning or attempts; and feeling overwhelmed but unable to get help as a result of COVID-19. Older age was identified as a protective factor. CONCLUSIONS: The general university student population in our study was relatively resilient with respect to suicidal ideation during the first three waves of the pandemic, but trends indicate the possibility of delayed impact. Specific sub-populations were found to be at increased risk and should be considered for targeted support. Further analyses should be undertaken to continue monitoring suicidality trends throughout the remainder of the pandemic and beyond.

Using novel methodology to estimate the prevalence of mental disorders in British Columbia, Canada.

PURPOSE: A needs-based model of health systems planning uses a systematic estimate of service needs for a given population. Our objective was to derive annual prevalence estimates of specific mental disorders in the adult population of British Columbia, Canada and use a novel triangulation approach encompassing multiple data sources and stratifying these estimates by age, sex, and severity to inform Ministry partners, who commissioned this work. METHODS: We performed systematic literature reviews and subsequent meta-analyses to derive an annual prevalence estimate for each mental disorder. We then generated age- and sex-specific estimates by triangulating published epidemiological studies, routinely collected province-wide health administrative data, and nationally representative health survey data sources. The age- and sex-specific estimates were further stratified by severity using the Global Burden of Disease severity distributions and published literature. RESULTS: Anxiety disorders had the highest annual prevalence estimates (6.93%), followed by depressive disorders (6.42%). All other mental disorders had an annual prevalence of less than 1%. Prevalence estimates were consistently higher in younger age groups. Depressive disorders, anxiety disorders, and eating disorders were higher in women, while estimates for bipolar disorders, schizophrenia, and ADHD were slightly higher in men in younger age groups. CONCLUSION: We generated robust annual prevalence estimates stratified by age, sex, and severity using a triangulation approach. Variation by age, sex, and severity implies that these factors need to be considered when planning for mental health services. Our approach is replicable and can be used as a model for needs-based planning in other jurisdictions.

Psychiatric diagnosis and treatment in the 21st century: paradigm shifts versus incremental integration.

Psychiatry has always been characterized by a range of different models of and approaches to mental disorder, which have sometimes brought progress in clinical practice, but have often also been accompanied by critique from within and without the field. Psychiatric nosology has been a particular focus of debate in recent decades; successive editions of the DSM and ICD have strongly influenced both psychiatric practice and research, but have also led to assertions that psychiatry is in crisis, and to advocacy for entirely new paradigms for diagnosis and assessment. When thinking about etiology, many researchers currently refer to a biopsychosocial model, but this approach has received significant critique, being considered by some observers overly eclectic and vague. Despite the development of a range of evidence-based pharmacotherapies and psychotherapies, current evidence points to both a treatment gap and a research-practice gap in mental health. In this paper, after considering current clinical practice, we discuss some proposed novel perspectives that have recently achieved particular prominence and may significantly impact psychiatric practice and research in the future: clinical neuroscience and personalized pharmacotherapy; novel statistical approaches to psychiatric nosology, assessment and research; deinstitutionalization and community mental health care; the scale-up of evidence-based psychotherapy; digital phenotyping and digital therapies; and global mental health and task-sharing approaches. We consider the extent to which proposed transitions from current practices to novel approaches reflect hype or hope. Our review indicates that each of the novel perspectives contributes important insights that allow hope for the future, but also that each provides only a partial view, and that any promise of a paradigm shift for the field is not well grounded. We conclude that there have been crucial advances in psychiatric diagnosis and treatment in recent decades; that, despite this important progress, there is considerable need for further improvements in assessment and intervention; and that such improvements will likely not be achieved by any specific paradigm shifts in psychiatric practice and research, but rather by incremental progress and iterative integration.

Global and regional projections of the economic burden of Alzheimer's disease and related dementias from 2019 to 2050: A value of statistical life approach.

Background: The burden of Alzheimer's disease and related dementias (ADRDs) is expected to grow rapidly with population aging, especially in low- and middle-income countries, in the next few decades. We used a willingness-to-pay approach to project the global, regional, and national economic burden of ADRDs from 2019 to 2050 under status quo. Methods: We projected age group and country-specific disability-adjusted life years (DALYs) lost to ADRDs in future years based on historical growth in disease burden and available population projections. We used country-specific extrapolations of the value of a statistical life (VSL) year and its future projections based on historical income growth to estimate the economic burden - measured in terms of the value of lost DALYs - of ADRDs. A probabilistic uncertainty analysis was used to calculate point estimates and 95% uncertainty bounds of the economic burden. Findings: In 2019, the global VSL-based economic burden of ADRDs was an estimated $2.8 trillion. The burden was projected to increase to $4.7 trillion (95% uncertainty bound: $4 trillion-$5.5 trillion) in 2030, $8.5 trillion ($6.8 trillion-$10.8 trillion) in 2040, and $16.9 trillion ($11.3 trillion-$27.3 trillion) in 2050. Low- and middle-income countries (LMICs) would account for 65% of the global VSL-based economic burden in 2050, as compared with only 18% in 2019. Within LMICs, upper-middle income countries would carry the largest VSL-based economic burden by 2050 (92% of LMICs burden and 60% of global burden). Interpretation: ADRDs have a large and inequitable projected future VSL-based economic burden. Funding: The Davos Alzheimer's Collaborative.

Determinants of effective treatment coverage for major depressive disorder in the WHO World Mental Health Surveys.

BACKGROUND: Most individuals with major depressive disorder (MDD) receive either no care or inadequate care. The aims of this study is to investigate potential determinants of effective treatment coverage. METHODS: In order to examine obstacles to providing or receiving care, the type of care received, and the quality and use of that care in a representative sample of individuals with MDD, we analyzed data from 17 WHO World Mental Health Surveys conducted in 15 countries (9 high-income and 6 low/middle-income). Of 35,012 respondents, 3341 had 12-month MDD. We explored the association of socio-economic and demographic characteristics, insurance, and severity with effective treatment coverage and its components, including type of treatment, adequacy of treatment, dose, and adherence. RESULTS: High level of education (OR = 1.63; 1.19, 2.24), private insurance (OR = 1.62; 1.06, 2.48), and age (30-59yrs; OR = 1.58; 1.21, 2.07) predicted effective treatment coverage for depression in a multivariable logistic regression model. Exploratory bivariate models further indicate that education may follow a dose-response relation; that people with severe depression are more likely to receive any services, but less likely to receive adequate services; and that in low and middle-income countries, private insurance (the only significant predictor) increased the likelihood of receiving effective treatment coverage four times. CONCLUSIONS: In the regression models, specific social determinants predicted effective coverage for major depression. Knowing the factors that determine who does and does not receive treatment contributes to improve our understanding of unmet needs and our ability to develop targeted interventions.

The World Mental Health International College Student Survey in Canada: Protocol for a Mental Health and Substance Use Trend Study.

BACKGROUND: The World Health Organization World Mental Health International College Student (WMH-ICS) initiative aims to screen for mental health and substance use problems among postsecondary students on a global scale as well as to develop and evaluate evidence-based preventive and ameliorative interventions for this population. This protocol paper presents the Canadian version of the WMH-ICS survey, detailing the adapted survey instrument, the unique weekly cross-sectional administration, the multitiered recruitment strategy, and the associated risk mitigation protocols. OBJECTIVE: This paper aims to provide a methodological resource for researchers conducting cross-national comparisons of WMH-ICS data, as well as to serve as a useful guide for those interested in replicating the outlined cross-sectional methodology to better understand how mental health and substance use vary over time among university students. METHODS: The online survey is based on the WMH-ICS survey instrument, modified to the Canadian context by the addition of questions pertaining to Canadian-based guidelines and the translation of the survey to Canadian French. The survey is administered through the Qualtrics survey platform and is sent to an independent stratified random sample of 350 students per site weekly, followed by two reminder emails. Upon survey closure every week, a random subsample of 70 nonresponders are followed up with via phone or through a personal email in an effort to decrease nonresponder bias. The survey is accompanied by an extensive risk mitigation protocol that stratifies respondents by the level of need and provides tailored service recommendations, including a facilitated expedited appointment to student counseling services for those at increased risk of suicide. The anticipated sample size is approximately 5500 students per site per year. RESULTS: In February 2020, the Canadian survey was deployed at the University of British Columbia. This was followed by deployment at Simon Fraser University (November 2020), McMaster University (January 2021), and the University of Toronto (January 2022). Data collection at all 4 sites is ongoing. As of May 6, 2022, 29,503 responses have been collected. CONCLUSIONS: Based on international collaboration, the Canadian version of the WMH-ICS survey incorporates a novel methodological approach centered on the weekly administration of a comprehensive cross-sectional survey to independent stratified random samples of university students. After 27 months of consecutive survey administration, we have developed and refined a survey protocol that has proven effective in engaging students at four Canadian institutions, allowing us to track how mental health and substance use vary over time using an internationally developed university student survey based on the criteria from the Diagnostic and Statistical Manual of Mental Disorders (Fifth Edition). INTERNATIONAL REGISTERED REPORT IDENTIFIER (IRRID): RR1-10.2196/35168.