Acceptability and Impact of an Educational App (iCare) for Informal Carers Looking After People at Risk of Pressure Ulceration: Mixed Methods Pilot Study
Bibliographic record
Abstract
BACKGROUND: Pressure ulcers are areas of skin damage resulting from sustained pressure. Informal carers play a central role in preventing pressure ulcers among older and disabled people living at home. Studies highlight the paucity of pressure ulcer training for informal carers and suggest that pressure ulcer risk is linked to high levels of carer burden. OBJECTIVE: This pilot study evaluated a smartphone app with a specific focus on pressure ulcer prevention education for informal carers. The app was developed based on the principles of microlearning. The study aimed to explore carer perspectives on the acceptability of the app and determine whether the app increased knowledge and confidence in their caring role. METHODS: In this concurrent mixed methods study, participants completed quantitative questionnaires at baseline and at the end of weeks 2 and 6, which examined caregiving self-efficacy, preparedness for caregiving, caregiver strain, pressure ulcer knowledge, and app acceptability and usability. A subsample of participants participated in a "think aloud" interview in week 1 and semistructured interviews at the end of weeks 2 and 6. RESULTS: =21.624; P=.001) from baseline (mean 37.5; SE 2.926) to the second follow-up (mean 59.72, SE 3.985). Regarding the qualitative data, the theme "I'm more careful now and would react to signs of redness" captured participants' reflections on the new knowledge they had acquired, the changes they had made to their caring routines, their increased vigilance for signs of skin damage, and their intentions toward the app going forward. There were no significant results pertaining to improved preparedness for caregiving or caregiving self-efficacy or related to the Caregiver Strain Index. Participants reported above average usability scores on a scale of 0 to 100 (mean 69.94, SD 18.108). The app functionality and information quality were also rated relatively high on a scale of 0 to 5 (mean 3.84, SD 0.704 and mean 4.13, SD 0.452, respectively). Overall, 2 themes pertaining to acceptability and usability were identified: "When you're not used to these things, they take time to get the hang of" and "It's not a fun app but it is informative." All participants (n=32, 100%) liked the microlearning approach. CONCLUSIONS: The iCare app offers a promising way to improve informal carers' pressure ulcer knowledge. However, to better support carers, the findings may reflect the need for future iterations of the app to use more interactive elements and the introduction of gamification and customization based on user preferences.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.009 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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 teacher head, 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".