ReviewJournal of urban health : bulletin of the New York Academy of Medicine2021
Use of Data to Understand the Social Determinants of Depression in Two Middle-Income Countries: the 3-D Commission.
Review in Journal of urban health : bulletin of the New York Academy of Medicine, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
7 citing papers in PubMed, 14 citations in OpenAlex.
- The U-shape Association between Population Agglomeration and Individual Depression: the Role of Dialect Diversity.Journal of urban health : bulletin of the New York Academy of Medicine · 2024Article
- Explosion of research on psychopathology and social media use after COVID-19: A scientometric study.World journal of psychiatry · 2024Article
- Article
- Automating data collection methods in electronic health record systems: a Social Determinant of Health (SDOH) viewpoint.Health systems (Basingstoke, England) · 2023Review
- Association Between Single Nucleotide Polymorphisms Within lncRNA NONHSAT102891 and Depression Susceptibility in a Chinese Population.Neuropsychiatric disease and treatment · 2023Article
- Analyzing Discussions Around Rural Health on Twitter During the COVID-19 Pandemic: Social Network Analysis of Twitter Data.JMIR infodemiology · 2023Article
- The 3-D Commission: Forging a Transdisciplinary Synthesis at the Intersection of Social Determinants of Health, Data, and Decision-making.Journal of urban health : bulletin of the New York Academy of Medicine · 2021Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
13 authors at 5 institutions in 5 countries.
Funding
Abstract
Depression accounts for a large share of the global disease burden, with an estimated 264 million people globally suffering from depression. Despite being one of the most common kinds of mental health (MH) disorders, much about depression remains unknown. There are limited data about depression, in terms of its occurrence, distribution, and wider social determinants. This work examined the use of novel data sources for assessing the scope and social determinants of depression, with a view to informing the reduction of the global burden of depression.This study focused on new and traditional sources of data on depression and its social determinants in two middle-income countries (LMICs), namely, Brazil and India. We identified data sources using a combination of a targeted PubMed search, Google search, expert consultations, and snowball sampling of the relevant literature published between October 2010 and September 2020. Our search focused on data sources on the following HEALTHY subset of determinants: healthcare (H), education (E), access to healthy choices (A), labor/employment (L), transportation (T), housing (H), and income (Y).Despite the emergence of a variety of data sources, their use in the study of depression and its HEALTHY determinants in India and Brazil are still limited. Survey-based data are still the most widely used source. In instances where new data sources are used, the most commonly used data sources include social media (twitter data in particular), geographic information systems/global positioning systems (GIS/GPS), mobile phone, and satellite imagery. Often, the new data sources are used in conjunction with traditional sources of data. In Brazil, the limited use of new data sources to study depression and its HEALTHY determinants may be linked to (a) the government's outsized role in coordinating healthcare delivery and controlling the data system, thus limiting innovation that may be expected from the private sector; (b) the government routinely collecting data on depression and other MH disorders (and therefore, does not see the need for other data sources); and (c) insufficient prioritization of MH as a whole. In India, the limited use of new data sources to study depression and its HEALTHY determinants could be a function of (a) the lack of appropriate regulation and incentives to encourage data sharing by and within the private sector, (b) absence of purposeful data collection at subnational levels, and (c) inadequate prioritization of MH. There is a continuing gap in the collection and analysis of data on depression, possibly reflecting the limited priority accorded to mental health as a whole. The relatively limited use of data to inform our understanding of the HEALTHY determinants of depression suggests a substantial need for support of independent research using new data sources. Finally, there is a need to revisit the universal health coverage (UHC) frameworks, as these frameworks currently do not include depression and other mental health-related indicators so as to enable tracking of progress (or lack thereof) on such indicators.
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What OpenQuestion holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.