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Table 3 Feasibility score on a 5-point scale by item (N = 32)

From: The development of a web-based app employing machine learning for delirium prevention in long-term care facilities in South Korea

Item

 

N (%) or Mean ± SD

The app is suitable for caring for delirium patients in a long-term care facility

 

3.72 ± 0.63

The use of CAMa through the app makes it easier to assess delirium patients

 

3.81 ± 0.69

The delirium prediction result warned about the possibility of developing delirium patients, which led to caution

 

3.84 ± 0.72

Initiating care for delirium patients was achieved through the results of the app’s delirium prediction and delirium assessment

 

3.88 ± 0.61

The use of the app made it easy to apply delirium interventions

 

3.84 ± 0.63

The use of the app has improved the overall knowledge of delirium

 

3.88 ± 0.71

The app is useful for clinical use

 

3.78 ± 0.66

I will continue to use this app for delirium intervention in the future

 

3.66 ± 0.79

Average time taken for one use of the app (minute)

2 < 

18 (56.3)

Average number of times to get used to using the app (Count)

3–5

17 (53.1)

Total time it took to get used to using the app (minute)

60

13 (40.6)

  1. aConfusion Assessment Method