Bridging the Communication Gap Between People With Cognitive Impairments and Their Caregivers Using mHealth Apps: User-Centered Design and Evaluation Study With People With 22q11 Deletion Syndrome
Bibliographic record
Abstract
BACKGROUND: In families with children with cognitive impairments, both parents and children experience tension and have questions because of a lack of communication and adequate information. Therefore, there is a great need to develop tools that can help bridge the communication gap between patients and caregivers by stimulating conversations and providing psychoeducational tools. mHealth apps show great potential in this context. OBJECTIVE: The objective of this research is to discover the specific ways young people with cognitive impairments and their families interact with mHealth apps in the context of bridging the communication gap. This newly discovered information leads to potentially more impactful mHealth interventions in the future. Therefore, this paper documents the design and development of a mHealth app for a specific group of people with cognitive impairments-people with 22q11 deletion syndrome (22q11 DS)-and their caregivers, as well as key learnings from the evaluation of this app. METHODS: An iterative, user-centered design approach is used to design and develop the app. Design and evaluation happens in 2 phases. During the design phase, feedback is gathered from 2 medical experts and 3 human computer interaction (HCI) experts using a low-fidelity paper prototype. During the evaluation phase, feedback is gathered from 8 families with a child with 22q11 DS using a fully working proof of concept. This phase consists of a semistructured interview, a 2-4-week trial period, and a concluding semistructured interview. RESULTS: The evaluation results of the fully working proof of concept led to design recommendations related to four different topics: (1) overcoming usage barriers, (2) stimulating conversation through a mHealth app, (3) providing information, and (4) bringing continual added value. Results are presented according to six different categories obtained in a thematic analysis: (1) feedback about the app "as is," (2) difficulties, (3) comparison between physical and digital tool, (4) extensions, (5) intention, and (6) other. CONCLUSIONS: In this research, the need for apps that help bridge the communication gap between a person with cognitive impairment and their caregiver is confirmed. All participating families express their gratitude and mention the added value for other families. Therefore, it is highly encouraged for clinics and institutions to take action and develop an app to be used in practice. Furthermore, considerations when developing for people with 22q11 DS, or more broadly, people with cognitive impairments, are proposed. First, one should keep design principles in mind to overcome usage barriers. Next, recognition is a key concept when stimulating conversations through mobile apps. Third, information should be provided by a trusted source, and more than just clinical information can be considered valuable. Finally, having the possibility of using a digital tool that can be personalized brings continual added value.
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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 | 0.023 | 0.026 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.002 | 0.002 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.002 |
| 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".