Mental health during the COVID-19 pandemic in children and adolescents with ADHD: A systematic review of controlled longitudinal cohort studies
Bibliographic record
Abstract
Prior studies reported mixed effects of the COVID-19 pandemic on the mental health of children and adolescents with ADHD, but they were mainly cross-sectional and without controls. To clarify the impact, we searched Web of Science, EMBASE, Medline, and PsychINFO until 18/11/2023 and conducted a systematic review of controlled longitudinal cohort studies (Prospero: CRD42022308166). The Newcastle-Ottawa scale was used to assess quality. We identified 6 studies. Worsening of mental health symptoms was more evident in ADHD or control group according to symptom considered and context. However, those with ADHD had more persistent elevated symptoms and remained an at-risk population. Sleep problems deteriorated more significantly in those with ADHD. Lower pre-COVID emotion regulation skills and greater rumination were associated with worse mental health outcomes, and longer screen time with poorer sleep. Quality was rated as low in most studies, mainly due to self-report outcome measures and no information on attrition rates. Despite these limitations, results suggest a predominantly negative impact on youths with ADHD and may guide clinical practice and policy.
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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 | 0.014 | 0.051 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.008 | 0.009 |
| Bibliometrics | 0.007 | 0.009 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.002 | 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".