Children's ADHD Symptoms and Friendship Patterns across a School Year.
Bibliographic record
Abstract
Symptoms of attention-deficit/hyperactivity disorder (ADHD) in elementary school-age children are associated with poor relationships with classroom peers, as indicated by poor social preference, low peer support, and peer victimization. Less is known about how friendship patterns relate to ADHD symptoms, or how friendships may buffer risk for negative peer experiences. Participants were 558 children in 34 classrooms (grades K-5). At the beginning (fall) and end (spring) of an academic year, children completed (a) sociometric interviews to index friendship patterns and social preference, and (b) self-report questionnaires about their support and victimization experiences from classmates. In fall, higher teacher-reported ADHD symptoms were associated with children having more classmates with no friendship ties (non-friends) and who the child nominated but did not receive a nomination in return (unreciprocated friends), and with having fewer classmates with mutual friendship ties (reciprocated friends) and who nominated the child but the child did not nominate in return (unchosen friends). Higher fall ADHD symptoms predicted more non-friend classmates, poorer social preference, and more victimization in the spring, after accounting for the same variables in fall. However, having many reciprocated friends (and to a lesser extent, many unchosen friends) in fall buffered against the trajectory between fall ADHD symptoms and poor peer functioning in spring. By contrast, having many unreciprocated friends in fall exacerbated the trajectory between fall ADHD symptoms and poor peer functioning in spring. Thus, elevated ADHD symptoms are associated with poorer friendship patterns, but reciprocated friendship may protect against negative classroom peer experiences over time.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.001 | 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) | 0.002 | 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".