Child ADHD and anxiety: Parent mental health literacy and information preferences
Bibliographic record
Abstract
Abstract This research explored parents' mental health literacy (MHL) skills (i.e., recognizing symptoms and identifying effective help‐seeking strategies) for child attention‐deficit/hyperactivity disorder (ADHD) and anxiety, factors associated with their MHL, and preferences for receiving information about each disorder. N = 128 parents were recruited from community organizations to participate in an online survey. Parents were randomly assigned to read one vignette depicting a child with symptoms of ADHD or anxiety. They were asked to identify the depicted problem and rate the helpfulness of potential help‐seeking strategies (i.e., different health professionals and medications). They also completed measures of parental self‐efficacy and parenting stress and indicated information preferences for learning about symptoms and treatment. Parents scored just above the mid‐range on a measure of their MHL skills, with no significant difference between parents responding to the ADHD and anxiety vignettes. Stronger MHL was associated with being a mother, having personal, family, or friend‐related mental health experience, and stronger parental self‐efficacy. Parents were interested in receiving more information about child ADHD and anxiety via health provider or written format. Results are valuable for informing future MHL intervention efforts to educate parents about symptoms and treatment for common child mental health problems such as ADHD and anxiety.
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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 | 0.002 | 0.009 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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".