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Evidence about the impact of the COVID-19 pandemic on the mental health of specific subpopulations, such as university students, is needed as communities prepare for future waves.
To study the association of proximity of COVID-19 with symptoms of anxiety and depression in university students.
This trend study analysed weekly cross-sectional surveys of probabilistic samples of students from the University of British Columbia for 13 weeks, through the first wave of COVID-19. The main variable assessed was propinquity of COVID-19, defined as ‘knowing someone who tested positive for COVID-19’, which was specified at different levels: knowing someone anywhere globally, in Canada, in Vancouver, in their course or at home. Proximity was included in multivariable linear regressions to assess its association with primary outcomes, including 30-day symptoms of anxiety and/or depression.
Of 1388 respondents (adjusted response rate of 50%), 5.6% knew someone with COVID-19 in Vancouver, 0.8% in their course and 0.3% at home. Ten percent were overwhelmed and unable to access help. Knowing someone in Vancouver was associated with an 11-percentage-point increase in the probability of 30-day anxiety symptoms (s.e. 0.05, P ≤ 0.05), moderated by gender, with a significant interaction of the exposure and being female (coefficient −20, s.e. 0.09, P ≤ 0.05). No association was found with depressive symptoms.
Propinquity of COVID-19 cases may increase the likelihood of anxiety symptoms in students, particularly among men. Most students reported coping well, but additional support is needed for an emotionally overwhelmed minority who report being unable to access help.
Major depressive disorder (MDD) is a leading cause of morbidity and mortality. Shortfalls in treatment quantity and quality are well-established, but the specific gaps in pharmacotherapy and psychotherapy are poorly understood. This paper analyzes the gap in treatment coverage for MDD and identifies critical bottlenecks.
Seventeen surveys were conducted across 15 countries by the World Health Organization-World Mental Health Surveys Initiative. Of 35 012 respondents, 3341 met DSM-IV criteria for 12-month MDD. The following components of effective treatment coverage were analyzed: (a) any mental health service utilization; (b) adequate pharmacotherapy; (c) adequate psychotherapy; and (d) adequate severity-specific combination of both.
MDD prevalence was 4.8% (s.e., 0.2). A total of 41.8% (s.e., 1.1) received any mental health services, 23.2% (s.e., 1.5) of which was deemed effective. This 90% gap in effective treatment is due to lack of utilization (58%) and inadequate quality or adherence (32%). Critical bottlenecks are underutilization of psychotherapy (26 percentage-points reduction in coverage), underutilization of psychopharmacology (13-point reduction), inadequate physician monitoring (13-point reduction), and inadequate drug-type (10-point reduction). High-income countries double low-income countries in any mental health service utilization, adequate pharmacotherapy, adequate psychotherapy, and adequate combination of both. Severe cases are more likely than mild-moderate cases to receive either adequate pharmacotherapy or psychotherapy, but less likely to receive an adequate combination.
Decision-makers need to increase the utilization and quality of pharmacotherapy and psychotherapy. Innovations such as telehealth for training and supervision plus non-specialist or community resources to deliver pharmacotherapy and psychotherapy could address these bottlenecks.
There is a substantial proportion of patients who drop out of treatment before they receive minimally adequate care. They tend to have worse health outcomes than those who complete treatment. Our main goal is to describe the frequency and determinants of dropout from treatment for mental disorders in low-, middle-, and high-income countries.
Respondents from 13 low- or middle-income countries (N = 60 224) and 15 in high-income countries (N = 77 303) were screened for mental and substance use disorders. Cross-tabulations were used to examine the distribution of treatment and dropout rates for those who screened positive. The timing of dropout was examined using Kaplan–Meier curves. Predictors of dropout were examined with survival analysis using a logistic link function.
Dropout rates are high, both in high-income (30%) and low/middle-income (45%) countries. Dropout mostly occurs during the first two visits. It is higher in general medical rather than in specialist settings (nearly 60% v. 20% in lower income settings). It is also higher for mild and moderate than for severe presentations. The lack of financial protection for mental health services is associated with overall increased dropout from care.
Extending financial protection and coverage for mental disorders may reduce dropout. Efficiency can be improved by managing the milder clinical presentations at the entry point to the mental health system, providing adequate training, support and specialist supervision for non-specialists, and streamlining referral to psychiatrists for more severe cases.
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