Predicting family quality of life in parents of children with elevated symptoms of Attention-Deficit/Hyperactivity Disorder
Bibliographic record
Abstract
Parents of children with neurodevelopmental disorders, such as attention-deficit/hyperactivity disorder (ADHD), are at high risk for elevated levels of parenting stress. Given that parenting stress and family quality of life (FQOL) are inversely-related, it is surprising that research examining FQOL in ADHD populations is absent in the literature. In the present study, 145 parents of children (n =105 mothers and n = 40 fathers), ages 5 to 12 years, with elevated symptoms of ADHD from Canada and the United States completed an online survey. The current study compared FQOL among coupled mothers and fathers (n = 13), examined the relationship between FQOL and parenting stress in mothers and fathers, and examined child and parental factors that predict FQOL in mothers and fathers. A paired samples t-test failed to show differences in FQOL among coupled mothers and fathers. Pearson correlations revealed negative correlations between FQOL and parenting stress in both mothers and fathers, however this result was only significant for mothers. Parental social support was the strongest predictor of FQOL in both mothers and fathers. The results of this study suggest that social support should be considered in development of interventions for families of children with elevated symptoms of ADHD. Future research should continue to examine fathers and couples’ perspectives given the small sample size in this study.
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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 | 0.000 |
| 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 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".