ADHD Symptoms Increased During the Covid-19 Pandemic: A Meta-Analysis
Bibliographic record
Abstract
OBJECTIVE: Emerging research suggests that the Covid-19 pandemic has disproportionately and adversely affected children with Attention-Deficit/Hyperactivity Disorder (ADHD). The purpose of this meta-analysis is to consolidate the findings from studies that examined changes in ADHD symptoms from before to during the pandemic. METHOD: Database searches of PsycINFO, ERIC, PubMed, and ProQuest were used to identify relevant studies, theses, and dissertations. RESULTS: A total of 18 studies met specific inclusion criteria and were coded based on various study characteristics. Twelve studies examined ADHD symptoms longitudinally and six studies assessed ADHD symptoms retroactively and during the pandemic. Data from 6,491 participants from 10 countries were included. Results indicated that many children and/or their caregivers reported an increase in child ADHD symptoms during the Covid-19 pandemic. CONCLUSIONS: This review points to a global increase in ADHD symptoms and has implications for the prevalence and management of ADHD during the post-pandemic recovery.
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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 | 0.009 | 0.025 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.009 | 0.028 |
| Bibliometrics | 0.004 | 0.005 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.004 | 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".