Factor analysis of the Parenting Stress Index‐Short Form with parents of young children with autism spectrum disorders
Bibliographic record
Abstract
The primary purpose of this study was to examine the underlying factor structure of the Parenting Stress Index-Short Form (PSI-SF) in a large cohort of parents of young children with autism spectrum disorder (ASD). A secondary goal was to examine relationships between PSI-SF factors and autism severity, child behavior problems, and parental mental health variables that have been shown to be related to parental stress in previous research. A confirmatory factor analysis (CFA) was used to examine the three-factor structure described in the PSI-SF manual [Abidin, 1995]: parental distress, parent-child dysfunctional interaction, and difficult child. Results of the CFA indicated that the three-factor structure was unacceptable when applied to the study sample. Thus, an exploratory factor analysis was conducted and suggested a six-factor model as the best alternative for the PSI-SF index. Spearman's correlations revealed significant positive correlations with moderate to large effect sizes between the revised PSI-SF factors and autism severity, externalizing and internalizing child behaviors, and an index of parent mental health. The revised factors represent more narrowly defined aspects of the three original subscales of the PSI-SF and might prove to be advantageous in both research and clinical applications. Autism Res 2011,4:336-346. © 2011 International Society for Autism Research, Wiley Periodicals, Inc.
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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 | 0.005 | 0.012 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| 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".