Exploring Effects of Sensory Garments on Participation of Children on the Autism Spectrum: A Pretest-Posttest Repeated Measure Design
Bibliographic record
Abstract
Objective: Autistic children experience sensory challenges that interfere with participation and increase parent stress. Sensory-based interventions are used to address children's behaviors affected by sensory processing difficulties, but research is limited regarding use of sensory garments to support participation of autistic children. This study explored sensory garment effects on participation, parental competence, and perceived stress of autistic children and their parents. Method: Twenty-one children were recruited and 17 males with ASD and atypical sensory processing patterns completed the 14-week study. The Canadian Occupational Performance (COPM) and Goal Attainment Scaling (GAS) were used to set and monitor participation goals. After a baseline period, children wore sensory garment(s) for 8 weeks. The COPM, GAS, Parent Stress Index-Short Form (PSI-SF), and Parent Sense of Competence Scale (PSOC) were administered four times (prebaseline, before and after the intervention, and three weeks postintervention). Results: There were moderate to large significant differences in both COPM and GAS scores after the intervention and from the beginning to the end of the study indicating sensory garments may improve participation of autistic children. There were no significant differences in PSI or PSOC at any timepoint. Two children rejected the garments. Conclusions: Parent- or child-selected sensory garments may improve participation in individually meaningful activities for children who can tolerate wearing them. Children's improvement in participation did not improve parent stress or competence, possibly due to the passive nature of the intervention. More research is needed explore the influence of heterogeneous sensory patterns on response to intervention.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.004 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| 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".