The Influence of Personality Characteristics and Emotions on Blood Glucose Levels Among Type 1 Diabetes Mellitus Patients
Condition: Diabetes Mellitus, Type 1; Emotions; Personality; Sleep
MeSH terms: Diabetes Mellitus; Diabetes Mellitus, Type 1; Personality Disorders
Study type: Observational

Summary: 
      The research goal is to find a correlation between patient personality characteristics,
      patients' mood and glycemic control. Eventually, using this information may allow treating
      physicians the ability to better balance glucose blood levels in patients with T1DM, by
      recognizing influencing psychological parameters. The conclusion from this research will add
      to other physiological parameters that are being studied today, and in the future will be
      integrated into an artificial pancreas.

      The investigators believe that there is a correlation that hasn't been studied in the past
      between personality characteristics, daily emotions and the ability to balance glucose blood
      levels in patients with T1DM.
    

Detailed description: 
      Background:

      Type 1 diabetes mellitus (T1DM), is an autoimmune disease in which cells from the immune
      system attack the beta cells, that produce insulin, in the pancreas. As a result of the
      subsequent complete insulinopenia, glycemic levels rise, and the patient completely relies on
      exogenous administration of sub-cutaneous insulin injections. The patients must adjust the
      amount of insulin along the day in accordance with measured glucose blood levels and their
      activities (eating, physical activity, etc.) Recently patients diagnosed with T1DM, are
      eligible for a continuous glucose monitor with FLASH technology (Freestyle Libre glucose
      monitor), within the Israeli health medical basket services. As a result, nowadays treating
      physicians can better monitor glucose blood levels during the day. The Freestyle Libre
      constantly measures subcutaneous glucose levels, translating them using a specifically
      designed algorithm to projected blood glucose levels. This allows for improved glycemic
      control and more accurate insulin dosing decisions for the patient with a tool to assess
      disease severity and control for the treating physician.

      Using advanced algorithms, there is an enormous research effort in order to create an
      artificial pancreas- a glucose blood level monitor that informs an insulin pump regarding the
      amount of insulin that should be injected throughout the day. This will replace the patients
      ongoing burden of managing their glycemic levels and reduce patient dosing errors. In order
      to improve the already existing algorithms, inserting additional parameters into the equation
      may improve the predictive value of the algorithms, and thus improve the ability to balance
      glycemic levels in different situations. So far, most of the research in this area was
      performed using physiological parameters (heart rate, physical activity, nutrition, etc.).

      In the suggested study the researchers wish to examine the influence of character and
      emotions on glycemic levels during the day. Finding a correlation between the mental and mood
      status and glycemia may allow for the creation of a more accurate algorithm, to better
      predict and balance glycemic levels in patients with T1DM.

      Research hypothesis:

      The investigators' hypothesis is that there is a significant correlation between baseline
      personality characteristics, changing emotions throughout the day, and glycemic levels in
      patients with T1DM.

      Research goal:

      The research goal is to find a correlation between patient personality characteristics,
      patients' mood, and glycemic control. Eventually, using this information may allow treating
      physicians the ability to better balance glucose blood levels in patients with T1DM, by
      recognizing influencing psychological parameters. The conclusion from this research will add
      to other physiological parameters that are being studied today, and in the future will be
      integrated into an artificial pancreas.

      The investigators believe that there is a correlation that hasn't been studied in the past
      between personality characteristics, daily emotions, and the ability to balance glucose blood
      levels in patients with T1DM.

      Methods:

      During the first visit, participants will receive an explanation of nature, duration, and
      side effects required during the research period.

      After signing the informed consent, the following information will be collected:

        -  Demographic and socioeconomic background

        -  Personality characteristics questionnaire

        -  Medical history including the most recent blood tests During that visit, the participant
           will download a designated application for his mobile device and will receive
           instructions on using it.

      The duration of the follow-up period will be a week. During that period the patient will not
      change their current treatment or lifestyle. The patient will report their emotions,
      treatment, physical activity, behavior, and nutrition using a specifically designed
      smartphone application.

      At the end of the data collection week, and following their next visit to the clinic,
      glycemic information will be downloaded from the patients' CGM/FGM device.

      The mobile application: the designated application, will be built specifically for the study.
      The application is a questionnaire that is always available to the patient, in an accessible
      manner.

      Through the application, the patient will be able to fill out the questionnaire at any time,
      asking participants for details about their mood and emotions at the time. In addition, the
      app will collect data, if the participant will confirm it, which is collected by the smart
      device (steps, pulse, etc.) The data will be stored on a computer that is locked with a
      password, there will be complete separation between the patient's identifying data and the
      research related data. Data analysis will include correlation studies between the different
      parameters collected- specifically looking for emotional patterns/ events that affect
      glycemia.
    

Observational model: Cohort
Time perspective: Prospective
Sampling method: Non-Probability Sample
Study population: 
        Patients with a type 1 Diabetes Mellitus diagnosis