Bibliographic record
Abstract
Back to table of contents Previous article Next article Community NewsFull AccessInvesting in Global Mental Health Care Could Save BillionsVabren WattsVabren WattsPublished Online:31 May 2016https://doi.org/10.1176/appi.pn.2016.5b4AbstractAccording to the World Health Organization, most low- and middle-income countries spend less than $2 per year per person on the treatment and prevention of mental disorders compared with an average of $50 in high-income countries.Scaling up treatment for people living with depression and anxiety disorders around the world can lead to billions of dollars in savings, according to a study published by the World Health Organization (WHO). The report appeared in the May issue of Lancet Psychiatry.Paul Summergrad, M.D., believes that achievement of significant and sustainable improvements in global mental health care requires major international organizations, governments, and foundations to be engaged."This study suggests that if mental health care was to be increased even to a moderate level of accessibility throughout the world, then not only would this increase be beneficial to the quality of [mental health] care, but it would have great returns on investments in terms of improved health, workforce productivity, and the economy in general," former APA President Paul Summergrad, M.D., chair of the Department of Psychiatry at Tufts University School of Medicine, told Psychiatric News.According to the World Economic Forum, an estimated $2.5 to $8.5 trillion in lost output was attributed to mental, neurological, and substance use disorders worldwide in 2010. While previous international economic studies of mental health have examined the economic effects of these disorders, including the cost-effectiveness of different intervention strategies and the cost of scaling up care, these studies did not evaluate the value of both economic and health benefits of intervention scale up.To estimate the global return on an investment in a scaled-up response to depression and anxiety disorders worldwide, Dan Chisholm, Ph.D., a health economist at WHO, and a team of international researchers calculated treatment costs and health outcomes in 36 countries between 2016 and 2030, assuming a linear increase in depression and anxiety treatment coverage. The analysis showed that the estimated cost for a modest increase in mental health care for depression and anxiety would amount to $147 billion ($91 billion for depression and $56 billion for anxiety disorders), a value of $399 billion in economic benefits and health returns."Notwithstanding the general limitations of any projection-modeling study, the analysis suggests that the investment needed to substantially scale up effective treatment coverage for depression and anxiety disorders in the 36 countries included in this analysis is substantial. Extending the scope to the 20 percent of the world's population not living in the 36 countries represented in the study would increase the cost by about 25 percent to $184 billion," the authors wrote. "However, the returns to this investment are also substantial, with benefit to cost ratios of 2.3 to 3.0 when economic benefits only are considered, and 3.3 to 5.7 when the value of health returns is also included."In an accompanying editorial in Lancet Psychiatry, Summergrad wrote, "the Chisholm study brings rigor to the economic case, but there are many other important reasons to consider enhanced investment in global mental health, not least of which are justice, equity, human rights, and the reduction of suffering." In his published comments, Summergrad went on to outline several actions to help advance the global mental health infrastructure, including more recognition of the burden of mental health disorders in terms of medical care cost, disability, lost life, and lost productivity, as well as an international campaign to destigmatize mental disorders that may lead to more people seeking mental health services. "It will require a collaborative effort from major international organizations, governments, and foundations to enhance the infrastructure for mental health care throughout the world," Summergrad told Psychiatric News.The study was funded by Grand Challenges Canada. ■An abstract of "Scaling-Up Treatment of Depression and Anxiety: A Global Return on Investment Analysis" can be accessed here. The accompanying editorial by Paul Summergrad, M.D., "Investing in Global Mental Health: The Time for Action Is Now," is available here. ISSUES NewArchived
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.001 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".