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Trial registered on ANZCTR


Registration number
ACTRN12618000065291
Ethics application status
Approved
Date submitted
18/12/2017
Date registered
17/01/2018
Date last updated
19/12/2018
Date data sharing statement initially provided
19/12/2018
Type of registration
Prospectively registered

Titles & IDs
Public title
Impact of Mobile Phone Diabetes Application on Diabetes Patients: a Randomized Controlled Trial
Scientific title
For an insulin requiring adult with either type 1 or type 2 diabetes, does using a diabetes mobile phone application combined with personalized and generalized educational messages improve glycaemic control as compared to usual care alone
Secondary ID [1] 293515 0
Nil
Universal Trial Number (UTN)
U1111-1205-7377
Trial acronym
Linked study record
Nil

Health condition
Health condition(s) or problem(s) studied:
Type 1 Diabetes Mellitus 305703 0
Type 2 Diabetes Mellitus 305704 0
Condition category
Condition code
Metabolic and Endocrine 304921 304921 0 0
Diabetes

Intervention/exposure
Study type
Interventional
Description of intervention(s) / exposure
Usual care visits to health care provider for 12 months duration of study. Plus the use of a mobile phone application (named ‘’My care Hub’’). The application is a software to be installed on participants mobile phones. It has both an android and i-phone versions with comprehensive functionalities which includes;
1. Capacity for users to log and track their blood glucose readings, food intake and physical activity habits over time.
2. Analytical functions which aid presentation of recorded data in a graphical form. This will help participants to set their health care targets and monitor trends in their self-care activities.
3. In response to the logged blood glucose reading, participants will receive automated personalized self-care educational messages. Additionally, participants will also receive through the application, general educational, behavioural and motivational messages twice weekly for 12 months. All messages will deliver information on the seven essential self-care behaviours in people with diabetes which predict good outcomes namely; lifestyle modifications (healthy eating and improved physical activity), monitoring of blood sugar, compliance with medications, good problem-solving skills, healthy coping skills, and risk-reduction behaviours (such as smoking caseation and reduction in alcohol intake). Compilation of both the personalized and general messages is by a Diabetes Educator and an Endocrinologist with over 7 years experience in the management of people with diabetes.
To access how best the application works for participants, they will be asked to input those self-care measurements at least twice a week; once on a weekend and once during the weekdays. The measurements inputted into the application will be automatically sent to the principal investigator through a secured web interface and stored onto a pass-worded protected computer system in an aggregated de-identified format. This will be used to monitor adherence to the use of the intervention.

Orientation and support for the use of the application will involve the following:
1. At the start of the trial, face to face training will be provided by the principal investigator to the participants.
2.. The principal investigator will contact the participants at least twice within the first month to inquire about any problem with the use of the application. We believe this period will be sufficient for them to get acquainted with the application.
3. At the start of the study, participants will be provided with the phone number and email address of the principal investigator whom they can contact for issues pertaining to the use of the application. This technical support will be available to participants throughout the study period.
Intervention code [1] 299747 0
Behaviour
Comparator / control treatment
Usual care visits to health care provider for the 12 months duration of study. Excluding emergency visits to the clinic, usual care treatments in diabetes management includes 3-4 monthly appointment with the doctor for the purpose of routine assessment of health parameters. This routine checkup is done to ensure good diabetes management.
Control group
Active

Outcomes
Primary outcome [1] 304114 0
Change in Glycosylated haemoglobin levels (HbA1c). HbA1c is an important measure of long-term glycemic control having the ability to reflect the cumulative glycemic history of the preceding 2-3 months (Khan & Weinstock, 2011). HbA1C test is done through a laboratory test of venous blood sample using the Siemens/Bayer DCA 2000 Analyser. This test is requested by the patient’s health care practitioner as part of usual care, so there will be a retrospective collection of this measure from the clinical records at each data collection point (baseline, 4,8 and 12 monthly).
Timepoint [1] 304114 0
Baseline, 4, 8 and 12 months (primary endpoint) after randomization
Primary outcome [2] 304115 0
Change in Lipids levels. A participant’s lipid profile is important because lipid abnormalities and diabetes often co-exist, so there will investigation of impact of variations in glycemic control on lipid schemes of participants. Lipid measurement is part of the usual care for diabetes patients and done through a laboratory procedure using a lipid profile Analyser.. Data collection will be through a retrospective check of the clinical records at each data collection point (baseline, 4, 8 and 12 monthly).
Timepoint [2] 304115 0
Baseline, 4, 8 and 12 months (primary endpoint) after randomization
Primary outcome [3] 304116 0
Change in Urine Albumin to Creatinine ratio (ACR): ACR is an accurate test to identify any abnormal amounts of albumin in urine and it plays a central role in monitoring the effectiveness of diabetes control and the progression of tissue damage. ACR is measured in the laboratory using the Siemens/Bayer DCA 2000 Analyser and is part of the routine care test requested by the patient’s health care practitioner. Data collection will be through a retrospective these measures from the clinical records at each data collection point (baseline, 4, 8 and 12 monthly).
Timepoint [3] 304116 0
Baseline, 4, 8 and 12 months (primary endpoint) after randomization
Secondary outcome [1] 341021 0
Change in Self Perceived Quality of Life will be measured using the Assessment of Quality of Life (AQoL-8D) questionnaire. AQol-8D is a 35 item instrument with domains to measure the physical, mental and social dimensions of health, as well as health utilities index and quality of well-being. AQol-8D is a comprehensive instrument with high validity and reliability (Richardson et al., 2013).
Timepoint [1] 341021 0
Baseline and 12 month after randomization
Secondary outcome [2] 341022 0
Change in knowledge of Diabetes management will be measured using the revised Michigan Diabetes Knowledge Scale (DKT).
DKT (comprises of 20 items) is designed to assess patient knowledge of diabetes concerning blood glucose levels and testing, diet, exercise, and self-care activities. DKT has been shown as a reliable and valid instrument to measure patient’s general knowledge of diabetes (Collins et al 2010).
Timepoint [2] 341022 0
Baseline and 12 month after randomization
Secondary outcome [3] 341023 0
The Diabetes Self-Management Questionnaire (DSMQ) will be used to assess change
in diabetes self-care activities associated with glycemic control. DSMQ is a 20 item questionnaire with four major subscales; Physical activity, dietary control, glucose management and health care use. Research has provided evidence that DSMQ is a reliable and valid measure for self-management in people with diabetes (Schmitt et al., 2013)
Timepoint [3] 341023 0
Baseline and 12 month after randomization
Secondary outcome [4] 341024 0
Change in medication adherence will be measured using the Medication Adherence Scale (MAQ). MAQ is a short 10 item questionnaire to study medication taking behaviour. It has been reported as an easy to score tool adaptable for various groups to identify barriers to adherence with medication intake (Culig & Leppee, 2014).
Timepoint [4] 341024 0
Baseline and 12 month after randomization
Secondary outcome [5] 341025 0
The family history of diabetes and co-morbidities that may be present in the participants or in their paternal and maternal side will be elucidated. This will be done through a questionnaire developed for the purpose of the study. This questionnaire was developed through extensive review of literature.
Timepoint [5] 341025 0
Baseline
Secondary outcome [6] 341026 0
Cost effectiveness of the intervention: Direct cost of implementing the intervention such as cost of personnel, operating cost, maintenance cost, and capital costs will be computed. As well as cost of hospital visits due to emergency (acute) complications (if any) as well as predicted long term health care cost incurred related to chronic complication development (if any). Indirect health cost will entail transportation to clinic appointments as a result of emergency complications and loss of productivity from being absent from work or usual activity due to such complication. Cost for standard care will also be elucidated for comparative cost analysis
Timepoint [6] 341026 0
12 months after intervention commencement
Secondary outcome [7] 341027 0
Engagement with intervention. This will be computed from the number of logs of blood glucose, diet and physical activity entered into the mobile application by the participants.
Timepoint [7] 341027 0
12 month after intervention commencement

Eligibility
Key inclusion criteria
- Diagnosed with Type 1 or Type 2 Diabetes
- Using insulin therapy with or without oral medication
- Own a smart phone (either android or IOS operation system)
- Consent from patient to participate
- Willing to return for follow up at 4, 8 and 12 months post intervention
Minimum age
18 Years
Maximum age
75 Years
Sex
Both males and females
Can healthy volunteers participate?
No
Key exclusion criteria
- Pregnant patients with type 1 or type 2 diabetes
- Having major diabetes complication such as kidney failure and lower limb amputation

Study design
Purpose of the study
Treatment
Allocation to intervention
Randomised controlled trial
Procedure for enrolling a subject and allocating the treatment (allocation concealment procedures)
Central randomization by computer
Methods used to generate the sequence in which subjects will be randomised (sequence generation)
Computerized sequence generation (i.e simple randomization using a random table created by computer software)
Masking / blinding
Open (masking not used)
Who is / are masked / blinded?



Intervention assignment
Parallel
Other design features
Not Applicable
Phase
Not Applicable
Type of endpoint/s
Efficacy
Statistical methods / analysis
Sample size determination
Estimation of sample size was based on glycated hemoglobin (HbA1c) level as the primary outcome. The sample size was estimated using a-priori power analysis in G-power computer software (Faul, Erdfelder, Lang, & Buchner, 2007). A statistical power of 80% will be achieved with a minimum sample size of 70 patients per study group, an effect size of 0.36 and p value set at 0.05. With the assumption of a drop out of approximately 10%, the sample size was increased to 150.
The calculated sample size and resulting effect size, significance level and statistical power are similar to previous studies (Ribu et al., 2013; Rossi et al., 2013). (Ribu et al., 2013; Rossi et al., 2013).

Statistical Methods and Analysis plan for Primary outcomes:
Primary outcomes will be analysed as continuous variables and dichotomised variables, and the mean values compared between the exposed and control groups using Bonferroni pair-wise comparison test from multivariate analysis. Furthermore, adjusted group comparisons using multilinear and logistic regressions will be performed. Goodness of fit model will be checked using graphical techniques and Hosmer-Lemeshow test will be performed for binary outcomes. The extent to which improvement in HbA1c, lipids levels and other clinical outcomes mediate reduction in complication development will be assessed by fitting two linear/logistic regression models, one including only group characteristics (such as age, sex, baseline HbA1c level) and the others incorporating both group effect and the intervention as covariates. The degree to which group characteristics are abated after adding the intervention into the model provides an indication of the mediating effect (Lin, Fleming, & De Gruttola, 1997).

Statistical methods and analysis plan for secondary outcomes:
Knowledge of diabetes management, medication intake and adherence, self-care practices, perceived ability to perform self-care and quality of life will be reported using descriptive statistics. Any changes in these parameters and socio-demographics will be assessed using Multivariate Analysis of Variance (MANOVA) while Pearson Correlation Coefficient will be utilized to assess the strength of the relationship between the continuous variables.

Cost-effectiveness will be expressed as an Incremental Cost-Effectiveness Ratio (ICER) and calculated as incremental costs divided by incremental effects. Results will be presented in cost-effectiveness planes and cost-effectiveness acceptability curves (CEACs). Prospective cost-savings from use of the intervention will be analysed using a one-way sensitivity to test the robustness of findings in net savings. Savings in this model will be attributed to: (a) avoiding travel by the patients and escorts to hospital due to emergency complication (b) avoiding overnight accommodation for patients and escorts in Townsville. Savings from avoiding travel by patients to hospitals will be calculated by multiplying return travel cost for two people (the patient and one escort) by the number of consultations as determined and fully reimbursed by the Queensland Health Patient Subsidy Scheme (PTSS).

Recruitment
Recruitment status
Recruiting
Date of first participant enrolment
Anticipated
Actual
Date of last participant enrolment
Anticipated
Actual
Date of last data collection
Anticipated
Actual
Sample size
Target
Accrual to date
Final
Recruitment in Australia
Recruitment state(s)
QLD
Recruitment hospital [1] 9479 0
The Townsville Hospital - Douglas
Recruitment postcode(s) [1] 18212 0
4814 - Douglas

Funding & Sponsors
Funding source category [1] 298132 0
University
Name [1] 298132 0
James Cook University
Country [1] 298132 0
Australia
Primary sponsor type
University
Name
James Cook University
Address
James Cook Drive, Townsville,
Queensland 4811
Country
Australia
Secondary sponsor category [1] 297500 0
None
Name [1] 297500 0
Address [1] 297500 0
Country [1] 297500 0

Ethics approval
Ethics application status
Approved
Ethics committee name [1] 299152 0
Townsville Hospital and Health Services Human Research Ethics Committee
Ethics committee address [1] 299152 0
Ethics committee country [1] 299152 0
Australia
Date submitted for ethics approval [1] 299152 0
05/08/2017
Approval date [1] 299152 0
18/12/2017
Ethics approval number [1] 299152 0
HREC/17/QTHS/148

Summary
Brief summary
Trial website
Trial related presentations / publications
Public notes
Attachments [1] 2278 2278 0 0
Attachments [2] 2279 2279 0 0
Attachments [3] 2280 2280 0 0
Attachments [4] 2281 2281 0 0
Attachments [5] 2282 2282 0 0

Contacts
Principal investigator
Name 79470 0
Mrs Mary Damilola Adu
Address 79470 0
College of Medicine and Dentistry, Building DB039, Room 202
James Cook University,
Townsville QLD 4811,
Country 79470 0
Australia
Phone 79470 0
+61469738375
Fax 79470 0
Email 79470 0
mary.adu@my.jcu.edu.au
Contact person for public queries
Name 79471 0
Mary Damilola Adu
Address 79471 0
College of Medicine and Dentistry, Building DB039, Room 202
James Cook University,
Townsville QLD 4811,
Country 79471 0
Australia
Phone 79471 0
+61469738375
Fax 79471 0
Email 79471 0
mary.adu@my.jcu.edu.au
Contact person for scientific queries
Name 79472 0
Mary Damilola Adu
Address 79472 0
College of Medicine and Dentistry, Building DB039, Room 202
James Cook University,
Townsville QLD 4811,
Country 79472 0
Australia
Phone 79472 0
+61469738375
Fax 79472 0
Email 79472 0
mary.adu@my.jcu.edu.au

Data sharing statement
Will individual participant data (IPD) for this trial be available (including data dictionaries)?
No
No/undecided IPD sharing reason/comment
All data collected will be analysed and results will be presented in scientific publications


What supporting documents are/will be available?

No Supporting Document Provided



Results publications and other study-related documents

Documents added manually
No documents have been uploaded by study researchers.

Documents added automatically
No additional documents have been identified.