The Design Process of an mHealth Technology: The Communicative Constitution of Patient Engagement Through a Participatory Design Workshop
Bibliographic record
Abstract
The aim of this article is to allow for a better understanding of how patient engagement is progressively constituted through interactions during a participatory design workshop. We will present a research project (based on a Participatory Design Approach) with the objective of creating an mHealth technology to encourage post-myocardial infarction (MI) patients to manage their condition, and learn more about their sudden cardiac death risk. The analysis will allow us to reveal the communicative constitution of patient engagement during the design process. We will illustrate patient engagement “in-the-making” by revealing 3 interactional processes: (1) the collective constitution of “experiential knowledge”, (2) the enaction of a “mutual learning space”, and (3) the co-creation of a prototype that embedded the patients’ voices.
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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 | 0.114 | 0.081 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.009 | 0.019 |
| Scholarly communication | 0.010 | 0.007 |
| Open science | 0.003 | 0.011 |
| Research integrity | 0.003 | 0.004 |
| Insufficient payload (model declined to judge) | 0.004 | 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".