The impact of a parent education workshop about children’s sensory processing differences on parental sense of competence
Bibliographic record
Abstract
Aims. This study aimed to: (1) examine the impact of a parent education workshop on the parental sense of competence (PSOC) of parents of children with sensory processing differences (SPD); and (2) explore parents’ perspectives regarding workshop content and delivery. Methods. This pilot study was a randomized waitlist-controlled trial. Parents were recruited from a neurodevelopmental assessment waitlist (for their children) and randomly selected to attend one of two identical workshops (two weeks apart). The workshops provided education about SPD and strategies for managing children’s behaviors related to SPD. The PSOC Scale and demographics and feedback questionnaires were administered to all parents before and after each workshop. Descriptive statistics and content analysis were used to analyze the quantitative and qualitative data, respectively. Results. Nine parents were recruited (six in the experimental group, three in the control group). PSOC Scale scores increased following workshop attendance. Three overarching themes of workshop components contributed to an enhanced PSOC: (1) learning specific strategies, (2) reframing children’s behavior, and (3) peer support. Conclusions. Parent education workshops showed promise for enhancing PSOC of parents of children with SPD. PSOC can promote positive mental health outcomes for parents, and help them to support their children’s occupational performance.
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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 | 0.007 | 0.020 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.001 | 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 | 0.002 |
| Insufficient payload (model declined to judge) | 0.009 | 0.001 |
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".