Co-design and Prototype Development of Medmanagesci: A Medication Self-Management Toolkit for Adults with Spinal Cord Injury/ Dysfunction 4228
Bibliographic record
Abstract
BACKGROUND: Medications are among the most common health interventions, with certain populations, such as individuals with spinal cord injury/dysfunction (SCI/D), commonly prescribed multiple medications. Consequently, adults with SCI/D often engage in activities related to medication self-management, but there are few comprehensive resources for this population. The objective of this study was to co-design the prototype of a toolkit to support medication self-management among adults with SCI/D. METHODS: We conducted a participatory multi-methods study, using the Good Things Foundation Pathfinder Model as a guide for the co-design process. Participants included adults with SCI/D, caregivers, and healthcare providers. Following the model's three stages, we: (1) understood and defined the problem by conducting a scoping review, concept mapping study, and working group sessions; (2) created a prototype of the toolkit through working group sessions and website development meetings; and (3) tested the prototype through working group sessions. RESULTS: The working group consisted of 19 individuals, including 9 adults with SCI/D, 1 caregiver, and 9 healthcare providers. In Stage 1, we identified the need for a comprehensive medication self-management resource through a scoping review, brainstormed content and delivery methods, and thematized and prioritized the content into eight categories through a concept mapping study. The concept mapping study included 44 participants, including 21 adults with SCI/D, 11 caregivers, and 12 healthcare providers. In Stage 2, feedback on the content mapped onto five categories: first impressions, message and purpose, visual elements, layout and flow, and graphics. The name, MedManageSCI, was selected by the working group. Through an iterative process with the website development company, an online version of the toolkit prototype was created ( www.medmanagesci.ca ). In Stage 3, participants provided recommendations to improve the website's functionality and navigation. CONCLUSIONS: The co-design of the MedManageSCI prototype is a significant step toward addressing the medication self-management needs of adults with SCI/D. The implications of this work extend beyond SCI/D, highlighting the importance of tailored digital health resources for populations with complex healthcare needs. Future work is needed to refine the content, assess the feasibility, acceptability, and appropriateness of the toolkit, and examine outcomes related to medication self-management.
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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 | 0.026 | 0.036 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.003 | 0.003 |
| Open science | 0.003 | 0.004 |
| Research integrity | 0.001 | 0.001 |
| 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".