Cocreation of a Video Feedback Tool for Managing Self-Care at Home With Pairs of Older Adults: Remote Experience-Based Co-Design Study
Bibliographic record
Abstract
BACKGROUND: Involving older adults in co-design processes is essential in developing digital technologies and health care solutions to enhance self-care management at home, especially for older adults with chronic illness and their companions. Remote co-design approaches could provide technologically sustainable solutions that address their personal needs. OBJECTIVE: This study aimed to cocreate and test the usability of a video feedback tool to facilitate self-care management at home. METHODS: This experience-based co-design approach involved collaboration between 4 pairs of older adults, 4 researchers, and 2 service designers in three steps: (1) six iterative workshops (5 remote and 1 in person) to cocreate self-care exercises within an existing video feedback tool by identifying factors influencing self-care management; (2) developing and refining the self-care exercises based on suggestions from the older adults; and (3) usability testing of the cocreated exercises with the 4 pairs of older adults in their homes. Among the older adults (68-78 years), 3 adults had heart failure and 1 adult had hypertension. Data were analyzed inductively through thematic analysis and deductively using the USABILITY (Use of Technology to Engage in Adaptation by Older Adults and/or Those With Low or Limited Literacy) framework. RESULTS: The identified influencing factors guiding the contents and format development of 2 new self-care exercises were that pairs of older adults support and learn from each other in performing self-care, which increases their motivation and engagement in practicing self-care at home. The usability test of the 2 new self-care exercises, "Breathing exercises" and "Picking up from the floor," revealed that the pairs found the exercises and the video feedback component valuable for learning and understanding, for example, by comparison of performances highlighting movement variability. However, they found it difficult to manage the video feedback tool on their own, and a support structure or tailored education or training was requested. CONCLUSIONS: This study emphasizes that the video feedback tool holds the potential to facilitate learning and understanding in self-care management, which may support motivation. The studied video feedback tool can be beneficial for pairs of older adults managing self-care at home as a complement to traditional health care services, but an accurate supporting structure is required. The effectiveness of the video feedback tool and its integration into existing health care services still need to be assessed and improved through careful design and structured support.
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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 | 0.028 | 0.036 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.003 | 0.002 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.002 | 0.004 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.003 | 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".