Consequences of the Covid-19 pandemic in children and adolescents with attention deficit hyperactivity disorder - a systematic review
Bibliographic record
Abstract
OBJECTIVE: In this systematic review (SR), the authors aimed to identify the possible impact of the social restriction imposed by the Coronavirus Disease-19 (COVID-19) pandemic on children/adolescents with Attention Deficit Hyperactivity Disorder (ADHD). DATA SOURCES: This SR was registered on PROSPERO CRD42021255569. Eligible articles were selected from PubMed, Embase, and LILACS, according to the following characteristics: ADHD patients < 18 years old, exposed to the COVID-19 pandemic, and the outcomes, medications, relationships, sleep, media use, remote learning, and comorbidities such as depression/sadness, inattention, anxiety, and irritability/aggressiveness. Newcastle-Ottawa Scale (NOS) for cohort, cross-sectional and case-control studies was used to assess methodological quality and the risk of bias. SUMMARY OF FINDINGS: Of the 222 articles identified, 27 were included, with information on 7,235 patients. Most studies (n = 22) were cross-sectional and received a mean NOS 4.63/10 followed by longitudinal (n = 4) with 3.75/8 points and case-control (n = 1), with 3/9 points. The pandemic affected patients' access to treatment, behavior, and sleep. Difficulties in remote learning and increased use of social media were described, as well as significant and positive changes in relationships with family and peers. CONCLUSION: Although the studies were heterogeneous, they indicated that the pandemic-related issues experienced by patients with ADHD were mostly manifested affecting their behavior and sleep patterns.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.008 | 0.035 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.007 | 0.007 |
| Bibliometrics | 0.008 | 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) | 0.004 | 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".