Clinical trial NCT03941652: Usability Study of the Sensors and eMOM GDM Application
Official title: Usability Study of the Sensors and the eMOM GDM Application eHealth in Treatment of Gestational Diabetes - eMOM GDM -Study
Study type: OBSERVATIONAL
Overall status: ACTIVE_NOT_RECRUITING
Conditions: Gestational Diabetes
Keywords: Gestational Diabetes
Continuous Glucose Values
Physical Activity
Nutrition
Behaviour Change
Stress
Recovery
Human-Computer Interaction (HCI)
Mobile Application
Diet
Self-tracking
User interface
Health care professionals
Lead sponsor: Helsinki University Central Hospital
Sponsor class: OTHER
Collaborators: name: Business Finland
name: Aalto University
name: University of Helsinki
name: Fujitsu Finland Oy
name: Elisa Oyj
name: CleverHealth Network
First posted: 2019-05-08
Enrollment: 54
Sex: FEMALE
Minimum age (years): 18
Maximum age (years): 68
Standard ages: ADULT
OLDER_ADULT
Accepts healthy volunteers: yes
Observational model: OTHER
Time perspective: PROSPECTIVE
Sampling method: NON_PROBABILITY_SAMPLE
Study population: * General population of pregnant women
* Pregnant women without gestational diabetes in previous pregnancy
* Pregnant women with or without gestational diabetes in previous pregnancies
* Health care professionals (nurses/midwives)

Brief summary: The principal aim of the eMOM GDM-project is to evaluate the effect of the eMOM GDM -application and the integrated service concept model on maternal and neonatal outcomes.

In the first phase of the project the investigators evaluate the usability, functionality and acceptability of developed eMOM GDM application and used sensors (continuous glucose meter, accelerometer, speech-enabled food record, optical pulse, beat-to-beat heart rate). Two different user interfaces (one for the women with GDM and one for the health care professionals) of the eMOM GDM application will we be developed and evaluated.

Detailed description: The first phase of the eMOM GDM -project consists of two parts.

Phase 1.1. the usability of the sensors will be evaluated by asking participants with GDM diagnosis (n = up to 10) to use the sensors (Garmin Vivosmart 3, Medtronic Guardian Connect, Firstbeat Bodyguard 2, and Exced) and by collecting participants' blood glucose values from glucose meter (Contour Next ONE) for one week. Participants fill out a logbook for physical activity and sleeping for seven days, and a logbook for diet for three days during the study period. For ensuring the quality of food record a researcher will phone interview the participant based on her diet recordings.

Before starting using the sensors, the participants will fill Background questionnaire and Technology acceptance questionnaire (UTAUT). After the usage period, the participants will fill the same Technology acceptance questionnaire (UTAUT) and take part in semi-structured interview. The interview has to parts. In the first part, participants will be interviewed about the acceptability of sensors. In the second part, researcher will show a non-functional prototype of eMoM GDM application to the participant and will ask predetermined questions. Interview will be recorded and data obtained from the interviews will be transcribed for analysis.

Phase 1.2. will define major usability issues with different versions of functional prototypes of eMOM GDM application developed in the project before moving to phase 2 of the study. General pregnant women (n = up to 30 in total) and GDM women (n=up to 10) will use the available version of the application for one week, and afterward the participants with GDM will take part in semi-structured interview. Interview will be recorded and data will be transcribed for analysis. General pregnant women will fill out a web form of usability of the application after application week. Based on the responses of the form, the participants may be contacted for further inquiries about the usability issues they have reported. For ensuring the quality of food record a researcher will phone interview all participants based on her diet recordings.

In Phase 1.3 user requirements for the professional eMOM GDM application will be collected. The first aim of this evaluation is to define what features the application should have. These user requirements are collected with a semi-structured interview. Before the interview, background of the 15-20 nurses/midwifes is asked with background questionnaire on profession. In the interviews, the questions are predetermined, but some flexibility is allowed. Interviews will be recorded and data obtained from the interviews will be transcribed for analysis.

Eligibility criteria: Inclusion Criteria:

* General pregnant women at gestational week \>=24
* GDM women without a prior GDM at gestational week \>=24
* GDM women with or without a prior GDM at gestational week \>=24

Exclusion Criteria:

* Type 1 Diabetes Mellitus
* Type 2 Diabetes Mellitus
* Use of medication that influences glucose metabolism in the beginning of the study (e.g. oral corticosteroids, metformin,insulin)
* Multiple Pregnancy
* Current substance abuse
* Severe psychiatric disorder
* Significant difficulty in cooperating (e.g. inadequate Finnish language skills)
* Significant physical disabilities

For health care professionals

Inclusion Criteria:

- Consult and treat women with GDM regularly

Exclusion Criteria:

- Inadequate Finnish language skills

Primary outcomes:
measure: Basic version of the eMOM GDM application has developed
timeFrame: 1 week
Secondary outcomes:
measure: Acceptability of sensors assessed by UTAUT questionnaire
timeFrame: 1 week
measure: Acceptability of sensors and eMOM GDM prototype application assessed by UTAUT questionnaire
timeFrame: 1 week
measure: Usability of sensors and their current applications
timeFrame: 1 week
measure: First impressions of a partially functional prototype of the eMOM GDM
timeFrame: 1 week
measure: Usability of eMOM GDM prototype application
timeFrame: 1 week
measure: Technical functionality of eMOM GDM application
timeFrame: 1 week
measure: User requirements for professional eMOM GDM application
timeFrame: 2 hours
Other outcomes:
measure: Continuous glucose levels dataset
timeFrame: 1 week
measure: Physical activity dataset
timeFrame: 1 week
measure: Sleep dataset
timeFrame: 1 week
measure: Recovery dataset
timeFrame: 1 week
measure: Stress dataset
timeFrame: 1 week
measure: Heart beat dataset
timeFrame: 1 week
measure: Nutrition dataset
timeFrame: 1 week
Locations:
city: Helsinki
country: Finland
facility: HUS
Study officials:
affiliation: Helsinki University Hospital, Women's Hospital
name: Seppo T Heinonen, prof
role: STUDY_DIRECTOR
References:
citation: Kyto M, Koivusalo S, Ruonala A, Stromberg L, Tuomonen H, Heinonen S, Jacucci G. Behavior Change App for Self-management of Gestational Diabetes: Design and Evaluation of Desirable Features. JMIR Hum Factors. 2022 Oct 12;9(4):e36987. doi: 10.2196/36987.