Psychotropic medication consumption before and after onset of COVID-19 pandemic in 91 countries and regions: a time-series analysis
Bibliographic record
Abstract
Background: The availability of psychotropic medications serves as a key indicator of global mental health status, underscoring the critical importance of continued monitoring. However, comprehensive studies assessing the global effect of the COVID-19 pandemic on such trends remain lacking. This study aimed to describe psychotropic consumption trends before and after the onset of the COVID-19 pandemic and investigate the pandemic's short- and long-term effects on psychotropic consumption across 91 countries and regions. Methods: This study used country-level sales data of psychotropic medications between Q1, 2012, and Q2, 2023 of 91 countries and regions from the IQVIA-Multinational Integrated Data Analysis System. Average annual sales trends were estimated and expressed as defined daily dose per 1000 inhabitants per day (DDD/TID) at the overall level and stratified by medication class and country income level. Relative average annual changes were assessed for the periods 2017-2019 and 2020-2022 both overall and within specific medication classes and income groups. The pandemic's short- and long-term effects on psychotropic medication sales were examined through interrupted time series analyses using quarterly data, conducted for each country and at overall level. Findings: Globally, the total consumption of psychotropic medications increased from 34.12 DDD/TID in 2020 to 36.15 DDD/TID in 2022, corresponding to a relative average increase of 2.94% [95% CI 0.97, 4.94] annually. The estimated relative change during 2020-2022 were 1.82% [1.02, 2.64] in Lower-Middle-Income-Countries (LMICs), 6.77% [-0.39, 14.45] in Upper-Middle-Income-Countries (UMICs), and 2.48% [0.72, 4.27] in High-Income-Countries (HICs). Overall psychotropic consumption showed an initial surge in Q1 2020 (level change: 1.94 DDD/TID [1.67, 2.21]), followed by a rapid decline during Q2 2020 (level change: -1.03 [-1.52, -0.54]). Most HICs exhibited a similar pattern. Following the pandemic onset, there was an increasing trend in overall psychotropic consumption (trend change: 0.13 [0.07, 0.19]). 70 of 91 countries showed an increasing slope change. Interpretation: Psychotropic medication consumption increased globally after the onset of the COVID-19 pandemic. During the pandemic, consumption rates in LMICs and UMICs appeared to slow down, however, patterns of change in psychotropic medication consumption following onset of the pandemic vary on a country level. To address these disparities, strategies for equitable psychotropic medication distribution and enhanced mental health care access in LMICs and UMICs are needed to improve global mental health. Funding: None.
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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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
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".