Understanding Pediatric Patient Experiences with Urotherapy Tools: Qualitative Focus Group Study
Bibliographic record
Abstract
Background: Standard urotherapy for childhood incontinence involves traditional tools like paper bladder diaries, timer watches, wetting alarms, and uroflowmeters. However, little is known about how these tools are experienced by today's digitally native children. Objective: This study aimed to explore how children undergoing urotherapy perceive and experience these commonly used tools, with the goal of informing more engaging and child-centered design approaches. Methods: A qualitative focus group design was used with purposive sampling of children undergoing in-clinic urotherapy group training. In total, 19 participants (13 boys and 6 girls) aged 9-13 years took part in focus groups of 3 to 4 children, held at the hospital. A child-friendly focus group toolkit was used to facilitate discussion through creative and playful exercises. A total of 7 focus groups were conducted, including 2 repeated sessions, until thematic saturation was reached. All sessions were held in Dutch, video- and audio-recorded, and transcribed verbatim. An inductive conventional content analysis was conducted using a dual-coder approach to identify and iteratively refine emerging themes. Results: Four themes emerged: (1) attitudes and motivation: ranging from willingness to engage in urotherapy and use tools to reluctance or resistance; (2) social acceptance: highlighting the impact of peer perception, fear of being bullied, and opportunities to break the taboo and reframe tools as socially desirable; (3) contextual influences: including dissatisfaction with school toilets and limited child involvement at doctor visits, contrasted with the positive peer support experienced during group therapy; and (4) digital integration: children saw many traditional tools as outdated and suggested gamified, smart alternatives. The drawings created by children during the exercises served as a creative reflection of these thematic findings. Conclusions: Involving children in research and design is essential for creating interventions that are truly child-centered. Through creative, qualitative methods, this study uncovered rich insights into children's experiences with urotherapy tools, pointing to 4 key design priorities: personalization, stigma-free design, adaptability, and digital innovation.
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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 | 0.014 | 0.017 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.005 | 0.005 |
| Scholarly communication | 0.003 | 0.003 |
| Open science | 0.002 | 0.005 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.005 | 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".