The Parental Stress Scale: Psychometric Properties in Families of Children With Chronic Health Conditions
Bibliographic record
Abstract
Objective To confirm the factor structure of the Parental Stress Scale (PSS) and examine its validity in parents whose children have chronic health conditions. Background Parents who have a child with a chronic illness report more stress than parents of healthy children. However, information is lacking on whether the PSS demonstrates adequate psychometric properties in this population. Method Data came from a convenience sample of 50 parents whose children (aged 6–16 years) were newly diagnosed with asthma, diabetes, epilepsy, food allergy, or juvenile arthritis. Confirmatory factor analysis was used to replicate the factor structure of the PSS. Analyses were bootstrapped to reduce potential sample bias. Results The factor structure of the PSS was validated and demonstrated adequate internal consistency, α = .84. There was evidence of convergent validity with family functioning, r = –.51, parental anxiety, r = .44, and depression, r = .35. Discriminant analyses showed low, nonstatistical correlations with domains of child quality of life, r = –.07 to –.18. The PSS did not differentiate between those with and without psychiatric disorders. Conclusion The PSS is valid and reliable in parents of children with chronic health conditions. Implications Having established robust psychometric properties of the PSS, research is needed to extend its utility and routine use in clinical and public health settings.
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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 | 0.004 | 0.014 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 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".