Diabetes
Conditions
Keywords
Diabetes, mobile application, artificial intelligence, self-care, hospitalization, cost
Brief summary
Aim: This study was conducted experimentally to examine the effect of artificial intelligence-based mobile virtual assistant developed for individuals with diabetes on cost, hospitalization rate, self-care and hypoglycemia. Methods: The research is multi-stage and designed as three stages in itself. According to this; development of the mobile application in the first and second stages and adding artificial intelligence to the application as a project; In the third stage, it was planned to examine the effect of the application on the variables and scales. The data of the study were collected between June 2022 and June 2023 in the Endocrinology Polyclinic of two private hospitals in Izmir and a diabetes association where individuals with diabetes were registered. Power 0.80 was determined by using NCSS PAS statistical software from the population of the research; The minimum number of samples to be included in the study was calculated as n:122 and they were divided into two as intervention and control groups by randomization. The research sample was carried out as intervention (n:60) and control (n:60) lastly due to death and cost. Five data collection tools were used, namely Individual Introduction Form, Diabetes Self-Care Scale, Hypoglycemia Confidence Scale, Mobile Application Opinion Form and Cost Table. An artificial intelligence-based mobile virtual assistant application was applied to the individuals with diabetes in the intervention group, and the data were collected three times, at the 0th, 6th and 12th months, and the costs were recorded. The standard outpatient trainings, which are currently applied, continued to be given to individuals with diabetes in the control group, the data were collected twice, at the beginning (0. month) and 12. months, and the costs were recorded. In the evaluation of the data, number, percentage, arithmetic mean, standard deviation, minimum and maximum median were calculated. Among the variables, chi-square, Kruskal Wallis, Mann Whitney U test and t test were used.
Interventions
OTHERartificial intelligence based mobile application
Artificial intelligence-based mobile application developed by me that includes diabetes education for individuals with diabetes.
Sponsors
Izmir Tinaztepe University
Study design
Observational model
OTHER
Time perspective
OTHER
Eligibility
Sex/Gender
FEMALE
Age
18 Years to 65 Years
Healthy volunteers
No
Inclusion criteria
* Having been diagnosed with Type 1 and Type 2 diabetes at least six months ago, according to the criteria of the American Diabetes Association (ADA), * Using insulin for at least six months, * Being between the ages of 18- 65, * Being able to read and write and speak Turkish, * Having an Android phone and being able to use mobile applications, * To volunteer to participate in the study.
Design outcomes
Primary
| Measure | Time frame | Description |
|---|---|---|
| Diabetes Self-Care Scale | 12 months | The score consists of 35 items and is a 4-point Likert type, the lowest acceptable score is 92 and the highest score is 140. As the score increases, self-care increases |
| Hypoglycemic Confidence Scale | 12 months | The scale consists of 9 items and is a 4-point Likert type. There is no cut-off value, the average score is used. |
Secondary
| Measure | Time frame | Description |
|---|---|---|
| hospitalization rate | 12 months | percentage |
Countries
Turkey (Türkiye)
Outcome results
None listed