Adherence to Psychotropic Medication Before and During COVID-19
Bibliographic record
Abstract
BACKGROUND: The coronavirus disease 2019 (COVID-19) pandemic and associated public health measures have shifted the way people access health care. We aimed to study the effects of the COVID-19 pandemic on psychotropic medication adherence. METHODS: A retrospective cohort study using administrative data from the Manitoba Centre for Health Policy Manitoba Population Research Data Repository was conducted. Outpatients who received at least 1 prescription for an antidepressant, antipsychotic, anxiolytic/sedative-hypnotic, cannabinoid, lithium, or stimulants from 2015 to 2020 in Manitoba, Canada, were included. Adherence was measured using the proportion of individuals with a mean possession ratio of ≥0.8 over each quarter. Each quarter of 2020 after COVID-19-related health measures were implemented was compared with the expected trend using autoregression models for time series data plus indicator variables. Odds ratio of drug discontinuation among those previously adherent in 2020 was compared with each respective quarter of 2019. RESULTS: There were 1,394,885 individuals in the study population in the first quarter of 2020 (mean [SD] age, 38.9 [23.4] years; 50.3% female), with 36.1% having a psychiatric diagnosis in the preceding 5 years. Compared with the expected trend, increases in the proportions of individuals adherent to antidepressants and stimulants were observed in the fourth quarter (October-December) of 2020 (both P < 0.001). Increases in the proportions of individuals with anxiolytic and cannabinoid adherence were observed in the third quarter (July-September) of 2020 (both P < 0.05), whereas a decrease was seen with stimulants in the same quarter ( P < 0.0001). No significant changes were observed for antipsychotics. All drug classes except lithium had decreases in drug discontinuation in previously adherent patients during the pandemic compared with 2019. CONCLUSIONS: Improved adherence to most psychotropic medications in the 9 months after public health restrictions were enacted was observed. Patients who were already adherent to their psychotropic medications were less likely to discontinue them during the pandemic.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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 source (direct Gemma or distilled Codex), 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".