Patient visits and prescriptions for attention-deficit/hyperactivity disorder from 2017–2021: Impacts of COVID-19 pandemic in primary care
Bibliographic record
Abstract
OBJECTIVE: To determine whether more patients presented with Attention-deficit/hyperactivity disorder (ADHD)-related visits and/or sought care from family physicians more frequently during the COVID-19 pandemic. METHODS: Electronic medical records from the University of Toronto Practice-Based Research Network were used to characterize changes in family physician visits and prescriptions for ADHD medications. Annual patient prevalence and visit rates pre-pandemic (2017-2019) were used to calculate the expected rates in 2020 and 2021. The expected and observed rates were compared to identify any pandemic-related changes. RESULTS: The number of patients presenting for ADHD-related visits during the pandemic was consistent with pre-pandemic trends. However, observed ADHD-related visits in 2021 were 1.32 times higher than expected (95% CI: 1.05-1.75), suggesting that patients visited family physicians more frequently than before the pandemic. CONCLUSION: Demand for primary care services related to ADHD has continued to increase during the pandemic, with increased health service use among those accessing care.
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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 | 0.001 | 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 | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".