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.

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.

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.

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.

Little is known about individual European countries or regional capacity to respond to animal welfare emergencies during natural disasters; therefore, it is important to establish baseline information (eg, types of disasters, training) to enable more focused and data-driven actionable support for future disasters.

A 55-question survey was distributed by an email link to the 53 World Organisation for Animal Health (WOAH) European Region Members plus 1 observer country.

Forty-nine countries (91%, n = 54) responded to the survey. Fifty-one percent (25/49) indicated they incorporated animal welfare into their national disaster regulatory framework, whereas 59% (29/49) indicated animal welfare was incorporated in the Veterinary Service National Disaster Management and Risk Reduction Plan. Thirty-nine percent (19/49) indicated they had “no” or “limited” legal authority to manage animal emergencies in natural disasters. Floods, forest fires, and snowstorm/extreme cold were the 3 most commonly reported disasters over the last 10 years with 79% (27/34) reporting Veterinary Services was involved in managing these disasters.

The survey results indicated a wide range in the capacity of WOAH European Member Countries to respond to animal welfare in natural disasters, highlighting the gaps and potential areas of improvement in this arena.

The study is aimed to identify brain functional connectomes predictive of depressed and elevated mood symptomatology in individuals with bipolar disorder (BD) using the machine learning approach Connectome-based Predictive Modeling (CPM).

Functional magnetic resonance imaging data were obtained from 81 adults with BD while they performed an emotion processing task. CPM with 5000 permutations of leave-one-out cross-validation was applied to identify functional connectomes predictive of depressed and elevated mood symptom scores on the Hamilton Depression and Young Mania rating scales. The predictive ability of the identified connectomes was tested in an independent sample of 43 adults with BD.

CPM predicted the severity of depressed [concordance between actual and predicted values (r = 0.23, pperm (permutation test) = 0.031) and elevated (r = 0.27, pperm = 0.01) mood. Functional connectivity of left dorsolateral prefrontal cortex and supplementary motor area nodes, with inter- and intra-hemispheric connections to other anterior and posterior cortical, limbic, motor, and cerebellar regions, predicted depressed mood severity. Connectivity of left fusiform and right visual association area nodes with inter- and intra-hemispheric connections to the motor, insular, limbic, and posterior cortices predicted elevated mood severity. These networks were predictive of mood symptomatology in the independent sample (r ⩾ 0.45, p = 0.002).

This study identified distributed functional connectomes predictive of depressed and elevated mood severity in BD. Connectomes subserving emotional, cognitive, and psychomotor control predicted depressed mood severity, while those subserving emotional and social perceptual functions predicted elevated mood severity. Identification of these connectome networks may help inform the development of targeted treatments for mood symptoms.

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.

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.

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.

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.

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.