Effect of Artıfıcıal Intellıgence Based Mobıle Vırtual Assıstant
Condition: Diabetes
MeSH terms: Diabetes Mellitus
Study type: Observational [Patient Registry]

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.
    


Intervention name(s): artificial intelligence based mobile application
Intervention type(s): Other
Intervention description(s): Artificial intelligence-based mobile application developed by me that includes diabetes education for individuals with diabetes.
Observational model: Other
Time perspective: Other
Sampling method: Probability Sample
Study population: 
        -  The patient has a perception disorder and psychiatric disorder that prevents
             communication,

          -  Desire to leave the research,

          -  His death during the research,

          -  Being pregnant,

          -  Individuals with severe retinopathy and neuropathy that prevent smartphone use were
             excluded from the study.
      
Keywords: Diabetes; mobile application; artificial intelligence; self-care; hospitalization; cost