The development and usability testing of two arts-based knowledge translation tools for parents of children with functional constipation
Bibliographic record
Abstract
Abstract Pediatric functional constipation (FC) is a common childhood problem that involves difficult or painful defecation and can be caused by a variety of different factors. In children, FC is often unrecognized and poorly treated, and has potential to cause abdominal pain, appetite suppression, loss of control over defecation, and family disruption. A recent interpretive description qualitative study found that parents who care for children with FC often experience a myriad of negative sentiments, including isolation and self-doubt. Furthermore, parents often have unanswered questions about the condition, particularly regarding the cause, symptoms, and treatment options. As such, more effective knowledge translation (KT) tools are needed to satisfy parental information needs. The purpose of this research was to collaborate with parents to develop and test the usability of two animated KT tools (video and interactive infographic) on FC in children. Prototypes were co-developed with parents, and then evaluated by parents through usability testing in a large Alberta emergency department waiting room. Usability was assessed based on nine items with responses on a five-point Likert scale from 1=strongly disagree to 5=strongly agree. Overall, results were positive and the tools were highly rated across most usability items. Mean scores across usability items were 4.20 to 4.59 for the video and 3.73 to 4.30 for the infographic. The scores from the usability testing suggest arts-based digital tools are useful in sharing complex health information with parents about FC and provide meaningful guidance on how to improve KT tools to better reflect the needs of parents of children with FC.
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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 | 0.010 | 0.026 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 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".