Published on in Vol 7 , No 10 (2018) :October

Preprints (earlier versions) of this paper are available at, first published .
Using an mHealth App to Transition Care of Type 1 Diabetes from Parents to Teens: Protocol for a Pilot Study

Using an mHealth App to Transition Care of Type 1 Diabetes from Parents to Teens: Protocol for a Pilot Study

Using an mHealth App to Transition Care of Type 1 Diabetes from Parents to Teens: Protocol for a Pilot Study


1Department of Advertising and Public Relations, Michigan State University, East Lansing, MI, United States

2College of Nursing, Michigan State University, East Lansing, MI, United States

3Department of Media and Information, Michigan State University, East Lansing, MI, United States

4Department of Communication, Michigan State University, East Lansing, MI, United States

5Department of Surgery, University of Alabama-Birmingham, Birmingham, AL, United States

6Department of Pediatric Endocrinology, Sparrow Health System, Lansing, MI, United States

7Department of Pediatrics, University of Michigan, Ann Arbor, MI, United States

Corresponding Author:

Bree E Holtz, PhD

Department of Advertising and Public Relations

Michigan State University

404 Wilson Road, Room 309

East Lansing, MI,

United States

Phone: 1 5178844537


Background: Type 1 diabetes mellitus (T1DM) afflicts approximately 154,000 people under the age of 20 in the United States. Most people with T1DM are diagnosed at a young age, and parents have to take on the responsibility of T1DM management. Eventually, the child must begin to transition to self-management. Adolescents often struggle to take on responsibility for all the necessary tasks to successfully self-manage their T1DM. In fact, approximately three-quarters of adolescents are not achieving American Diabetes Association–recommended glycated hemoglobin (HbA1c) targets. This lack of adherence can lead to negative health outcomes.

Objective: The goals of this interdisciplinary proposal are as follows: (1) to develop a unique and theory-driven technology using a mobile phone app to promote self-management behaviors for adolescents aged 10-15 years with T1DM and their parents and (2) to explore the feasibility and impact of the self-management mobile app.

Methods: This study has two phases: app development and pilot testing. In the app development phase, the app will be conceptualized and a prototype will be tested. In Phase 2, the mobile app will undergo pilot testing to determine its feasibility and impact on diabetes self-management.

Results: The pilot test was launched in September 2017. Data collection for the final pilot test is underway, and results are forthcoming.

Conclusions: Adolescents with T1DM and their parents can have a difficult time managing the transition of diabetes care. It is hoped that this app can help. The focus groups and prototype testing have indicated promising outcomes of app use.

Trial Registration: NCT03436628; (Archived by WebCite at

International Registered Report Identifier (IRRID): RR1-10.2196/10803

JMIR Res Protoc 2018;7(10):e10803



Type 1 diabetes mellitus (T1DM) afflicts approximately 154,000 people under the age of 20 in the United States [1-3]. Most people with T1DM are diagnosed at a young age, and parents take on most of the responsibility for T1DM management. Optimal treatment requires the entire family to quickly learn about the disease and to oversee its management [4]. Starting in the early teen years, the child must begin to transition to self-management. During this transition, adolescents often struggle to take on responsibility for all the necessary tasks in order to successfully manage their T1DM [2,5]. Approximately three-quarters of adolescents are not achieving American Diabetes Association (ADA)–recommended glycated hemoglobin (HbA1c) targets. Achieving these targets requires consistent and dedicated management [6]. A lack of adherence to the prescribed treatment regimen can lead to negative health outcomes, such as the development of diabetic ketoacidosis, increased infections, and hospitalizations [7-9].

One reason for the lack of adherence is that as a child matures into an adolescent, communication between the child and his or her parent becomes increasingly difficult, and conflict often increases. There are data to suggest that improving communication between the adolescents and their parents facilitates a smoother transition to self-care and is one way to improve HbA1c [10]. Mobile health (mHealth) technologies can also ease this transition by facilitating trust-building and improving family communication, relationships, and health outcomes. Nearly three-quarters of American teens (13-17 years old) have access to a smartphone [11]. Our hypothesis is that a mobile phone-based intervention that focuses on improving family communication will be effective in providing both the adolescents and their parents with real-time, tailored information about their diabetes and tools for communicating effectively.

Easing transition difficulties in an effort to increase positive health outcomes is imperative to the well-being of adolescents with T1DM and their families, and studies have shown that participants using mobile phone interventions had higher adherence rates and more participation than those that did not use the intervention [12]. Therefore, this study will develop a mobile app that addresses the difficulties of the adolescent transition to self-management and pilot test the app to determine its feasibility and impact on diabetes self-management. Below, we discuss the methodology for developing the app as well as the theoretical foundations guiding this development.

Study Design

This study has two phases that correspond with the study aims (Textbox 1): app development and pilot testing. In the app development phase, the app will be conceptualized and a prototype will be tested. In Phase 2, the mobile app will undergo pilot testing to determine its feasibility and impact on diabetes self-management. We did not utilize a control group because this is a feasibility study [13].

Theoretical Foundation

The social cognitive theory will inform the development of the intervention. The use of this theory to guide interventions has demonstrated success in changing behaviors around disease management [14-17]. The social cognitive theory posits that a change in an individual’s environmental, personal, or behavioral factors will impact the other two factors [18-21]; thus, the relationship among these factors is reciprocal. The self-management mobile app is being developed to lead to changes in each of the three factors. For example, to change the adolescents’ environmental factors, we will provide social support through a forum feature [22-24]. We believe that receiving messages from their parents via the self-management mobile app will also be a part of the environmental change [25-28]. Personal factors will be modified by prompts sent to the adolescents to set small and achievable daily goals, blood sugar reminders, and educational tips about living with T1DM to improve the adolescents’ self-efficacy [29-34]. Behavioral change will result from reinforcement through reminders and awarding points for achieving goals and entering data. The points encourage use (behavior), which we predict will improve adolescent adherence [35]. As a result of all of these factors, children will have an improved HbA1c, a higher quality of life, and reduced conflict with their parents, which we believe will reinforce the use of the self-management mobile app, strengthening the links. Figure 1 shows the theoretical model for the intervention.

Specific aims.

Phase 1

Specific Aim 1: Develop a type 1 diabetes self-management mobile phone app intervention for parents and adolescents

  • Objective 1: Develop the self-management mobile app and finalize content
  • Objective 2: Prototype testing

Phase 2

Specific Aim 2: Conduct pilot testing of the self-management mobile app to determine its feasibility and impact on diabetes self-management

  • H1 (primary outcomes): Measures of app usage will be associated with increased adherence to self-management and lower glycosylated hemoglobin.
  • H2 (secondary outcomes): Measures of app usage will be associated with increased quality of life, self-efficacy, and social support and decreased conflict between the adolescents and their parents.
Textbox 1. Specific aims.
Figure 1. Theoretical model. HbA1c: glycated hemoglobin.
View this figure

Phase 1: Technical App Development

The technical app development (Phase 1) will take place over a 9-month period. This process will be monitored through set goals, and progress will be measured by achieving two objectives of developing the self-management mobile app and finalizing content. To complete these objectives, content development will be completed based on several sources, including Understanding Diabetes [36] and other literature from the ADA, in conjunction with an expert panel who will also advise on the project during implementation. This panel includes a pediatric endocrinologist, a pediatric diabetes nurse practitioner, a college student with T1DM, and a parent of an adolescent with T1DM (not part of the study).

Based upon best practices in app design principles [37], we will also conduct focus groups with participants recruited from our target population. We will invite 6 adolescents and their parents for concept-testing focus groups. We will present the app concept and mock screenshots to the participants and solicit feedback with regard to the app’s look and feel, message wording, and what would help the adolescents to log their values. The data from the focus groups will inform message content refinement, the timing of the messages, their appropriateness, and the ease of logging information. This information will inform the app’s technical development. The technology development (app interfaces, Web portal, and servers) will be informed by the focus groups, concept testing, and best practices literature. We have 10 benchmarks with deadlines for app development (Table 1).

Once the prototype is developed, the objective 2 will be met by prototype testing of the app. We will recruit 10 family dyads (each dyad includes a teen and his or her parent, n=20) to use the self-management mobile app prototype over a 4-week period. We will conduct usability interviews, measuring perceptions and satisfaction with the app. Additionally, server information will be used to quantify learning time, the efficiency of use, engagement, and user errors. All of the problems and issues identified in the usability interviews will inform app development and refinement.

The Mobile App
App Functionalities

The self-management mobile app will be an intervention mechanism to encourage adolescents aged 10 to 15 years to self-manage their diabetes by recording their values while allowing their parents seamless and unobtrusive access to the same blood glucose (BG) values, carbohydrate intake, and physical activity data, which will be time-stamped, encrypted, and sent to a remote server for storage.

Table 1. App development benchmarks.
StepTime (in days)
Server management13
User management13
Server side logic12
Data integration13
Push logic6
Cache logic6
Wireframe development8
User interface design & development33

The parent users will have a separate log-in and will be able to review their child's history of BG values, carbohydrate intake, and physical activity from their own phone to help their child make decisions about managing their diabetes. Parents may also send messages via the app to their child. However, the parent can still communicate outside of the app, and we will ask about this communication in the poststudy interviews.

Along with customizable test reminders and BG ranges, the app will also have an educational component and a moderated forum for the adolescents and the parents (separate forums) to post and discuss questions and comments to peers. The adolescents will be incentivized through the use of points accumulated based on usage. These points can be used by the adolescents to purchase accessories for a superhero avatar. As this is a feasibility study, we will have the adolescents manually input their BG readings into the app. While this may seem cumbersome, most meters and pumps do not have the ability to automatically send data through Bluetooth. Once we can determine the feasibility and other design requirements through this pilot, we will develop the app to be Bluetooth-enabled. The participants and their parents are responsible for notifying their medical providers regarding any issues with their diabetes. Our app will not cause an actual health concern, as it is just a monitoring and communication device.

Technical Details of the App.

The mobile app will be initially developed for the Android platform. Future iterations will include an iOS platform. Focusing on one operating system will allow us to develop a self-management mobile app using the highest-quality control standards. We have selected Android because it is the world’s most popular platform [38]. Mobile phones will be provided to any participant who does not have a phone or one compatible with the app. The app will feature separate and secure log-in mechanisms for the adolescent user and parent user. All data will be stored on a remote encrypted server rather than the phone itself. If the phone is lost or stolen, we will have the ability to remotely erase the phone’s contents and turn off the data plan associated with it. Technical specifications and functions of the app have been presented in Textboxes 2 and 3.

Phase 2: Intervention Study Methods

This portion of the intervention involves having the adolescents and their parents use the app over the course of 3 months.

Study Setting

Recruitment will take place in the Sparrow Hospital’s Pediatric Subspecialty Clinic in Lansing, Michigan, United States. The Sparrow Endocrinology Clinic team consists of 1 registered pediatric dietitian, 1 full-time nurse practitioner, 2 certified diabetes educators, and 2 endocrinologists, all of whom provide diabetes care 4 days per week within the larger subspecialty clinic. All patients are scheduled to come to the clinic every 3 months for care.

Sample and Recruitment of Participants.

The clinic nurse diabetes educator will act as the site coordinator. Participants for the pilot testing will be recruited from the hospital’s Pediatric Endocrinology Clinic. Invitations will be mailed three times over 2 months to all of the potential participant dyads, as identified by hospital providers. Additionally, the health care providers in the clinics will be given a presentation on the study by the researchers so they can offer it to the families who meet the inclusion criteria during any typical interactions they have with the adolescent and parent.

Technical specifications.
  • Operating system: Android
  • Data storage: Remote encrypted server
  • Log-in mechanisms: Separate and secure log-in mechanisms for the adolescent user and parent user
Textbox 2. Technical specifications.
App functions. BG: blood glucose.

Child functions:

  • Incentivized through the use of points accumulated based on usage
  • Send messages via the app to their parent
  • Customizable test reminders and BG ranges
  • An educational component
  • A moderated forum for the adolescents and the parents (separate forums) to post and discuss questions and comments to peers

Parent functions:

  • Review their child’s history of BG values, carbohydrate intake, and physical activity from their own phone
  • Send messages via the app to their child
  • Customizable test reminders and BG ranges
  • An educational component
  • A moderated forum for the adolescents and the parents (separate forums) to post and discuss questions and comments to peers
Textbox 3. App functions. BG: blood glucose.
Inclusion criteria.

Adolescents must:

  • Have a type 1 diabetes mellitus (T1DM) diagnosis according to the American Diabetes Association practice guidelines [34]
  • Be 10-15 years old
  • Have had a diagnosis of T1DM for at least 6 months; have glycated hemoglobin>7 [35]
  • Have had at least two outpatient visits in the past 2 years
  • Be treated at the local clinic for diabetes
  • Be fluent in English
  • Have a parent or guardian willing to participate
  • Be allowed to use a mobile phone for the study
  • Have permission from their care team

Parents must:

  • Have an adolescent with T1DM who is 10-15 years old
  • Be fluent in English
  • And have daily access to email and the internet (for appointment reminders and technical support)
Textbox 4. Inclusion criteria.
Exclusion criteria.


  • With a diagnosis of a major psychiatric or neurocognitive disorder (eg, traumatic brain injury, dementia, schizophrenia, bipolar disorder, borderline personality disorder, and intellectual disability)
  • With significant medical conditions other than type 1 diabetes
  • Being treated for thyroid disorders, celiac disease, or eating disorders
  • In foster care


  • With a diagnosis of a major psychiatric or neurocognitive disorder (eg, traumatic brain injury, dementia, schizophrenia, bipolar disorder, borderline personality disorder, and intellectual disability)

Textbox 5. Exclusion criteria.

If interested, the parent will contact the researchers to learn more about the study. A researcher will be in the waiting room of the pediatric endocrinologists, providing study information to possible participants. The researcher will explain the study and determine if the adolescent and parent are eligible through a brief screening questionnaire. We will recruit a total of 70 adolescent and parent dyads, which would correspond to similar past research studying T1DM and mobile phone interventions [12]. Inclusion and exclusion criteria have been presented in Textboxes 4 and 5, respectively.

Study Procedures.

During the study, there will be 4 contact points with the participants: the enrollment or baseline data collection visit (Visit 1), a midpoint review (Visit 2, 3 months after Visit 1), an end-of-study visit (Visit 3, 6 months after Visit 1), and a follow-up visit 3 months after app usage has stopped (Visit 4). Visit 1 (month 0) will be scheduled during the screening process. At Visit 1, a member of the research team will review and obtain informed consent (parent) and assent (adolescent) from the participants. The participants will then complete the baseline surveys to measure self-efficacy, quality of life, and social support and conflict; the laboratory will test the teens’ HbA1c, and we will download data from their glucometer or pump. If a participant does not have a mobile device that can download and operate the app, the research team will provide the participant with a device and data plan for the duration of the study. The researcher will demonstrate how to use the technology and have the participants use each of the functions. At Visit 2 (month 3), a research team member will test the adolescents’ HbA1c and download data from their glucometer or pump. The participants will also complete the survey at the midpoint. The midpoint data will be used to demonstrate whether any change at 6 months is part of an increasing trend, a plateau, or a waning trend. At Visit 3 (month 6), the participants will complete the survey and participate in interviews. Additionally, the adolescents’ HbA1c will be tested, and the meter or pump readings will be collected. Finally, any participant that has borrowed any equipment will need to return it at this time. Qualitative methods will also be used to better examine perceptions and intentions, whether participants were light users, or why participants dropped out of the study [39]. After Visit 3, the participants will not use the app for 3 months. At Visit 4 (month 9), all the participants will complete the survey. The researchers will test the adolescents’ HbA1c and download data from their glucometer or pump.

Outcome Measures

Specifically, the aim 2 seeks to determine the feasibility and impact on diabetes of the self-management mobile app among the adolescents and their parents. Demographic information will also be collected including current age, age at diagnosis, race, gender, parental status (ie, mom, dad, stepdad, etc), and method of diabetes treatment (eg, pump).

Hypothesis 1 seeks to demonstrate that adherence to self-management correlates with mobile app usage and a decrease in HbA1c. HbA1c data will be collected through the hospital laboratory system. The patient will be provided with a laboratory slip to obtain the baseline HbA1c value. The patient will be instructed to obtain the lab results within 1 week. Once the results are obtained, they will be faxed to the principal investigator via a secure fax line. Adherence will be measured in two ways. First, the participants will complete the Diabetes Behavior Rating Scale [40]. Second, we will use data from the server to determine if they are monitoring blood sugar on schedule and what mechanisms of the app helped the adolescents follow the medical recommendations. For example, we will use time-stamped log-ins, number of sections the user visited, number of individual logs, communication through the app, educational information accessed, and duration of use per log-on.

Hypothesis 2 states that through use of the app, the participants’ self-efficacy [29,41,42], quality of life [43-45], and perceptions of social support [46-48] will improve, and conflict [49] between the child and parent will be reduced from baseline to 3 months. These secondary outcomes are key in helping the adolescents maintain adherence and a normal HbA1c [50-52] and will be measured through surveys. The survey instruments, the participants who will complete them, and reliability for each measure can be found in Table 2.

Analysis and Statistical Power

This is a feasibility study, so all analyses will be exploratory, focusing on identifying temporal trends in the self-management mobile app usage and changes in study outcomes and identifying associations between outcomes. Preceding the analyses, we will calculate summary statistics for all measures as well as exploratory plots (histograms and box-plots) for all measures at each time point to identify outliers and potentially spurious values.

Trends over the 4 visits will be examined graphically as a function of time using nonparametrically smoothed plots to help identify when potential effects reach their maximum, plateau, and begin to decrease, which may indicate a time to target for additional interventions. At each time point, we will calculate pairwise correlations between the self-management mobile app usage measures and all study outcomes and examine bivariate scatter-plots with estimated trends for each pair. Distribution-appropriate correlations (Pearson or Spearman) will be calculated as appropriate for each measure and formally tested for statistical significance. These analyses will also be repeated using change from baseline as the outcome rather than the score itself, both as a simple bivariate analysis and using linear regression to model the change as a function of the app usage measures while controlling for baseline values. Analyses will also be repeated using paired t tests for differences in HbA1c values from baseline to posttest to measure self-management adherence.

Statistical power will be established based on a small pilot study. A 2010 report on a small randomized controlled trial (RCT) of an mHealth intervention for T1DM in teenagers showed a significant change in self-management adherence from a mean of 3.7 (SD 0.4) at baseline to 3.9 (SD 0.4) at the 12-week follow-up, at an effect size of d=0.64 [53]. Given our longer follow-up period (6 months), we expect to observe a larger effect size in our feasibility study because HbA1c has low variability in 3 months [54]. While using a small pilot study to calculate power may not be ideal, it provides a foundation for us to approximate this study’s sample size in order to estimate the critical parameters necessary for this study [55]. The 2010 study also reported no change in HbA1c for the intervention group, but there was an increase in the control group, with SDs ranging from 1.2 to 1.9. Considering that their groups were imbalanced with respect to HbA1c at baseline, it is difficult to project a difference for our study except to note that observing no change in HbA1c may be an improvement over a possible increase in adolescents with usual care. Despite our limited sample size, assuming the use of two-sided tests with a type 1 error rate of 0.05, with 70 participants we will have 80% power to detect relatively modest correlations of .29.

Table 2. Survey instruments.
OutcomeMeasureReliability (α)Participant
AdherenceDiabetes Behavior Rating Scale.86Child or parent
Glycated hemoglobinBlood test—HbA1cN/AaChild
Social supportMultidimensional Scale of Perceived Social Support.81Child or parent
Social supportDiabetes Family Behavior.79Child or parent
Self-efficacyDiabetes Empowerment Scale-Short Form.84Child
Quality of lifePediatric Quality of Life Inventory (general & diabetes specific).88Child
ConflictDiabetes Family Conflict Scale.91Child or parent

aN/A: not applicable.

In the event of unanticipated difficulties with recruitment or of attrition of up to 20%, leaving a final sample of 56, the correlation detectable with 80% power increases only slightly to .32. For t tests, N=70 provides 80% power to detect an effect size of 0.30, which is smaller than that reported in the RCT, while the effect size detectable with N=56 increases slightly to 0.34 [53].

Additionally, the primary foci of this study include assessment of the following: (1) the effect size of the intervention to power a larger study; (2) feasibility of the app; (3) practicality of data collection procedures; and (4) the ability to implement. We will also perform a post hoc analysis on personal characteristics and satisfaction related to use of the system. At the completion of the study (month 9), we will ask both those who completed the whole intervention and those who withdrew early about their experience with the intervention, including what worked well and what did not. Additionally, we will use the IBM computer usability satisfaction questionnaire to assess usability [56].

The interview data will be analyzed by developing broad code categories based upon perception themes and will serve as a preliminary sorting tool. The researchers will then use thematic analysis and create a list of common perceptions. Once a coding scheme is developed, two coders will perform a pretest by coding randomly selected interview transcripts in order to measure reliability. Coders will work together to reconcile any disagreements; this will allow us to achieve a high level of reliability.

The study has been approved by the Institutional Review Board of Michigan State University, United States. We conducted focus groups prior to app development in April 2016 [57]. Prototype testing of the app was conducted in February 2017, and it included feedback regarding usability and satisfaction of the app [58]. The final pilot test was launched in September 2017. Data collection is underway, and results are forthcoming.

Adolescents with T1DM and their parents often struggle during the transition from parent care to adolescent self-management [59,60]. This transition to young adulthood is challenging for all families, but families facing the added complexity of diabetes management often find this time especially challenging. The proposed intervention is innovative as it aims to shift diabetes management responsibility to the adolescent and increase their independence while encouraging parents to remain engaged and supportive of their adolescent in an effort to ease some difficulties of this challenging time.

To do this, a mobile app for adolescents and their parents is proposed. Previous mHealth research indicates that mobile apps provide an innovative approach to impact health [12,61] using technology that is frequently part of adolescents’ and parents’ daily life [62,63]. However, very few existing apps have shown significant or sustainable improvements in adolescent self-management and overall health outcomes,[64] and none have directly involved the parents in the use of the app. In some apps that are currently available, the parents can receive the BG value, but they are not given any prompts on how to positively address blood sugar results and plan for care with their child. Our app will include communication through the app that may allow for adolescents to ask for help and communicate more honestly with their parent than they would in face-to-face communication [65]. This improved communication between adolescents and their parents has been shown to facilitate a smoother transition to self-care by improving communication between parents and adolescents, providing adolescents with tangible self-management skills, and providing families with social support and has been shown to improve HbA1c [10,66,67].

One difficulty of using mobile app technology is keeping adolescents engaged with app use over long periods of time. This is also an issue when designing an intervention with outcomes that take 3 or more months to realize significant changes. Data suggests that the majority of user engagement begins to drop after 21 days of use [68,69]. To combat this difficulty, the app includes a points-based customizable avatar. However, it is important to note that researchers anticipate seeing a similar trend in engagement. Another difficulty seen in many studies is problems with recruitment and retention. To combat these difficulties, participants will be contacted frequently, flexible scheduling will be used for participant study meetings, and study newsletters will be sent to participants. In the event of unanticipated difficulties with recruitment or attrition, a final sample of 56 is acceptable [53].

After we have successfully completed this study, the data gathered will be integrated with machine learning in order to modify the app for a wider audience and better tailor the app to the individual user’s behavior and usage preferences. Once completed, we will design and conduct a full-scale RCT. We will also expand the project to iOS (Apple phones). Additionally, we will seek to integrate the data into the patient’s electronic health record.


We would like to recognize Bion Bilateral for help with app development. This research is supported by the ADA Innovative Clinical or Translational Science Award #1-16-ICTS-045.

Conflicts of Interest

None declared.

Multimedia Appendix 1

Peer-reviewer report from the American Diabetes Association's Research Program.

PDF File (Adobe PDF File), 509KB

  1. Writing Group for the SEARCH for Diabetes in Youth Study Group, Dabelea D, Bell RA, D'Agostino RB, Imperatore G, Johansen JM, et al. Incidence of diabetes in youth in the United States. JAMA 2007 Jun 27;297(24):2716-2724. [CrossRef] [Medline]
  2. Peters A, Laffel L, American Diabetes Association Transitions Working Group. Diabetes care for emerging adults: recommendations for transition from pediatric to adult diabetes care systems: a position statement of the American Diabetes Association, with representation by the American College of Osteopathic Family Physicians, the American Academy of Pediatrics, the American Association of Clinical Endocrinologists, the American Osteopathic Association, the Centers for Disease Control and Prevention, Children with Diabetes, The Endocrine Society, the International Society for Pediatric and Adolescent Diabetes, Juvenile Diabetes Research Foundation International, the National Diabetes Education Program, and the Pediatric Endocrine Society (formerly Lawson Wilkins Pediatric Endocrine Society). Diabetes Care 2011 Nov;34(11):2477-2485 [FREE Full text] [CrossRef] [Medline]
  3. SEARCH for Diabetes in Youth Study Group, Liese AD, D'Agostino RB, Hamman RF, Kilgo PD, Lawrence JM, et al. The burden of diabetes mellitus among US youth: prevalence estimates from the SEARCH for Diabetes in Youth Study. Pediatrics 2006 Oct;118(4):1510-1518. [CrossRef] [Medline]
  4. Wysocki T, Taylor A, Hough BS, Linscheid TR, Yeates KO, Naglieri JA. Deviation from developmentally appropriate self-care autonomy. Association with diabetes outcomes. Diabetes Care 1996 Feb;19(2):119-125. [Medline]
  5. Weissberg-Benchell J, Wolpert H, Anderson BJ. Transitioning from pediatric to adult care: a new approach to the post-adolescent young person with type 1 diabetes. Diabetes Care 2007 Oct;30(10):2441-2446. [CrossRef] [Medline]
  6. Petitti DB, Klingensmith GJ, Bell RA, Andrews JS, Dabelea D, Imperatore G, SEARCH for Diabetes in Youth Study Group. Glycemic control in youth with diabetes: the SEARCH for diabetes in Youth Study. J Pediatr 2009 Nov;155(5):668-72.e1 [FREE Full text] [CrossRef] [Medline]
  7. American Diabetes Association. Type 1 Diabetes. 2018.   URL: [accessed 2018-09-27] [WebCite Cache]
  8. JDRF. Type 1 Diabetes Resources and Support. 2018.   URL: [accessed 2018-09-27] [WebCite Cache]
  9. National Diabetes Information Clearinghouse. National Diabetes Statistics. 2011.   URL: [accessed 2018-09-27] [WebCite Cache]
  10. Hanberger L, Ludvigsson J, Nordfeldt S. Use of a web 2.0 portal to improve education and communication in young patients with families: randomized controlled trial. J Med Internet Res 2013 Aug 23;15(8):e175 [FREE Full text] [CrossRef] [Medline]
  11. Lenhart A. Pew Research Center: Teen, Social Media and Technology Overview 2015. 2015.   URL: [accessed 2018-09-27] [WebCite Cache]
  12. Holtz B, Lauckner C. Diabetes management via mobile phones: a systematic review. Telemed J E Health 2012 Apr;18(3):175-184. [CrossRef] [Medline]
  13. Eldridge S, Lancaster G, Campbell M, Thabane L, Hopewell S, Coleman CL, et al. Defining Feasibility and Pilot Studies in Preparation for Randomised Controlled Trials: Development of a Conceptual Framework. PLoS One 2016;11(3):e0150205 [FREE Full text] [CrossRef] [Medline]
  14. Huang J, Terrones L, Tompane T, Dillon L, Pian M, Gottschalk M, et al. Preparing adolescents with chronic disease for transition to adult care: a technology program. Pediatrics 2014 Jun;133(6):e1639-e1646 [FREE Full text] [CrossRef] [Medline]
  15. Anderson ES, Winett RA, Wojcik JR. Self-regulation, self-efficacy, outcome expectations, and social support: social cognitive theory and nutrition behavior. Ann Behav Med 2007;34(3):304-312. [CrossRef] [Medline]
  16. Lubans D, Morgan P, Okely A, Dewar D, Collins CE, Batterham M, et al. Preventing Obesity Among Adolescent Girls: One-Year Outcomes of the Nutrition and Enjoyable Activity for Teen Girls (NEAT Girls) Cluster Randomized Controlled Trial. Arch Pediatr Adolesc Med 2012 Sep 01;166(9):821-827. [CrossRef] [Medline]
  17. Martin JJ, McCaughtry N, Flory S, Murphy A, Wisdom K. Using social cognitive theory to predict physical activity and fitness in underserved middle school children. Res Q Exerc Sport 2011 Jun;82(2):247-255. [CrossRef] [Medline]
  18. Bandura A. Human agency in social cognitive theory. Am Psychol 1989 Sep;44(9):1175-1184. [Medline]
  19. Bandura A. Social cognitive theory: an agentic perspective. Annu Rev Psychol 2001;52:1-26. [CrossRef] [Medline]
  20. Bandura A. Health promotion by social cognitive means. Health Educ Behav 2004 Apr;31(2):143-164. [CrossRef] [Medline]
  21. Glanz K, Rimer B, Lewis F, editors. Health Behavior and Health Education: Theory, Research and Practice. San Fransisco, CA: John Wiley & Sons; 2002.
  22. Greco P, Pendley JS, McDonell K, Reeves G. A peer group intervention for adolescents with type 1 diabetes and their best friends. J Pediatr Psychol 2001 Dec;26(8):485-490. [Medline]
  23. Pendley JS, Kasmen LJ, Miller DL, Donze J, Swenson C, Reeves G. Peer and family support in children and adolescents with type 1 diabetes. J Pediatr Psychol 2002;27(5):429-438. [Medline]
  24. Ravert R, Hancock M, Ingersoll G. Online forum messages posted by adolescents with type 1 diabetes. Diabetes Educ 2004;30(5):827-834. [CrossRef] [Medline]
  25. Hanna KM, Guthrie D. Adolescents' behavioral autonomy related to diabetes management and adolescent activities/rules. Diabetes Educ 2003;29(2):283-291. [CrossRef] [Medline]
  26. Hanna K, Weaver M, Stump T, Guthrie D, Oruche U. Emerging Adults with Type 1 Diabetes during the First Year Post-High School: Perceptions of Parental Behaviors. Emerg Adulthood 2014 Jun 01;2(2):128-137 [FREE Full text] [CrossRef] [Medline]
  27. Skinner TC, Hampson SE. Social support and personal models of diabetesin relation to self-care and well-being inadolescents with type I diabetes mellitus. J Adolesc 1998 Dec;21(6):703-715. [CrossRef] [Medline]
  28. Skinner TC, John M, Hampson SE. Social support and personal models of diabetes as predictors of self-care and well-being: a longitudinal study of adolescents with diabetes. J Pediatr Psychol 2000 Jun;25(4):257-267. [Medline]
  29. Anderson RM, Funnell MM, Fitzgerald JT, Marrero DG. The Diabetes Empowerment Scale: a measure of psychosocial self-efficacy. Diabetes Care 2000 Jun;23(6):739-743 [FREE Full text] [Medline]
  30. Iannotti RJ, Schneider S, Nansel TR, Haynie DL, Plotnick LP, Clark LM, et al. Self-efficacy, outcome expectations, and diabetes self-management in adolescents with type 1 diabetes. J Dev Behav Pediatr 2006 Apr;27(2):98-105. [Medline]
  31. Law GU, Walsh J, Queralt V, Nouwen A. Adolescent and parent diabetes distress in type 1 diabetes: the role of self-efficacy, perceived consequences, family responsibility and adolescent-parent discrepancies. J Psychosom Res 2013 Apr;74(4):334-339. [CrossRef] [Medline]
  32. Nouwen A, Urquhart LG, Hussain S, McGovern S, Napier H. Comparison of the role of self-efficacy and illness representations in relation to dietary self-care and diabetes distress in adolescents with type 1 diabetes. Psychol Health 2009 Nov;24(9):1071-1084. [CrossRef] [Medline]
  33. Stupiansky NW, Hanna KM, Slaven JE, Weaver MT, Fortenberry JD. Impulse control, diabetes-specific self-efficacy, and diabetes management among emerging adults with type 1 diabetes. J Pediatr Psychol 2013 Apr;38(3):247-254 [FREE Full text] [CrossRef] [Medline]
  34. Viner RM, Christie D, Taylor V, Hey S. Motivational/solution-focused intervention improves HbA1c in adolescents with Type 1 diabetes: a pilot study. Diabet Med 2003 Sep;20(9):739-742. [Medline]
  35. Cafazzo JA, Casselman M, Hamming N, Katzman DK, Palmert MR. Design of an mHealth app for the self-management of adolescent type 1 diabetes: a pilot study. J Med Internet Res 2012 May 08;14(3):e70 [FREE Full text] [CrossRef] [Medline]
  36. Chase HP, Maahs DM. A first book for understanding diabetes. Denver, Colorado: Children's Diabetes Foundation; 2011.
  37. Godwin-Jones R. Mobile apps for language learning. Language Learning & Technology 2011;15(2):2-11 [FREE Full text]
  38. Google Inc. Android, the world's most popular mobile platform. 2014.   URL: [accessed 2018-09-27] [WebCite Cache]
  39. Ritholz MD, Beverly EA, Weinger K. Digging deeper: the role of qualitative research in behavioral diabetes. Curr Diab Rep 2011 Dec;11(6):494-502. [CrossRef] [Medline]
  40. Iannotti RJ, Nansel TR, Schneider S, Haynie DL, Simons-Morton B, Sobel DO, et al. Assessing regimen adherence of adolescents with type 1 diabetes. Diabetes Care 2006 Oct;29(10):2263-2267. [CrossRef] [Medline]
  41. Anderson RM, Fitzgerald JT, Gruppen LD, Funnell MM, Oh MS. The Diabetes Empowerment Scale-Short Form (DES-SF). Diabetes Care 2003 May;26(5):1641-1642. [Medline]
  42. Anderson RM, Funnell MM, Fitzgerald JT, Marrero DG. The Diabetes Empowerment Scale: a measure of psychosocial self-efficacy. Diabetes Care 2000 Jun;23(6):739-743 [FREE Full text] [Medline]
  43. Varni JW, Burwinkle TM, Jacobs JR, Gottschalk M, Kaufman F, Jones KL. The PedsQL in type 1 and type 2 diabetes: reliability and validity of the Pediatric Quality of Life Inventory Generic Core Scales and type 1 Diabetes Module. Diabetes Care 2003 Mar;26(3):631-637. [Medline]
  44. Varni JW, Seid M, Kurtin PS. PedsQL 4.0: reliability and validity of the Pediatric Quality of Life Inventory version 4.0 generic core scales in healthy and patient populations. Med Care 2001 Aug;39(8):800-812. [Medline]
  45. Varni JW, Seid M, Rode CA. The PedsQL: measurement model for the pediatric quality of life inventory. Med Care 1999 Feb;37(2):126-139. [Medline]
  46. Zimet G, Dahlem N, Zimet S, Farley G. The Multidimensional Scale of Perceived Social Support. Journal of Personality Assessment 1988 Mar;52(1):30-41. [CrossRef]
  47. Zimet GD, Powell SS, Farley GK, Werkman S, Berkoff KA. Psychometric characteristics of the Multidimensional Scale of Perceived Social Support. J Pers Assess 1990;55(3-4):610-617. [CrossRef] [Medline]
  48. McKelvey J, Waller DA, North AJ, Marks JF, Schreiner B, Travis LB, et al. Reliability and validity of the Diabetes Family Behavior Scale (DFBS). Diabetes Educ 1993;19(2):125-132. [CrossRef] [Medline]
  49. Hood KK, Butler DA, Anderson BJ, Laffel LMB. Updated and revised Diabetes Family Conflict Scale. Diabetes Care 2007 Jul;30(7):1764-1769 [FREE Full text] [CrossRef] [Medline]
  50. Hirose M, Beverly EA, Weinger K. Quality of life and technology: impact on children and families with diabetes. Curr Diab Rep 2012 Dec;12(6):711-720 [FREE Full text] [CrossRef] [Medline]
  51. Ruiz J, Prather C, Kauffman E. Social Support. In: Gellman MD, Turner JR, editors. Encylopedia of Behavioral Medicine. New York, NY: Springer; 2013.
  52. Jensen MP, Smith AE, Bombardier CH, Yorkston KM, Miró J, Molton IR. Social support, depression, and physical disability: age and diagnostic group effects. Disabil Health J 2014 Apr;7(2):164-172. [CrossRef] [Medline]
  53. Mulvaney SA, Rothman RL, Wallston KA, Lybarger C, Dietrich MS. An internet-based program to improve self-management in adolescents with type 1 diabetes. Diabetes Care 2010 Mar;33(3):602-604 [FREE Full text] [CrossRef] [Medline]
  54. Nathan DM, Kuenen J, Borg R, Zheng H, Schoenfeld D, Heine RJ, A1c-Derived Average Glucose Study Group. Translating the A1C assay into estimated average glucose values. Diabetes Care 2008 Aug;31(8):1473-1478 [FREE Full text] [CrossRef] [Medline]
  55. Arain M, Campbell MJ, Cooper CL, Lancaster GA. What is a pilot or feasibility study? A review of current practice and editorial policy. BMC Med Res Methodol 2010 Jul 16;10:67 [FREE Full text] [CrossRef] [Medline]
  56. Lewis J. IBM computer usability satisfaction questionnaires: Psychometric evaluation and instructions for use. International Journal of Human-Computer Interaction 1995 Jan;7(1):57-78. [CrossRef]
  57. Holtz BE, Murray KM, Hershey DD, Dunneback JK, Cotten SR, Holmstrom AJ, et al. Developing a Patient-Centered mHealth App: A Tool for Adolescents With Type 1 Diabetes and Their Parents. JMIR Mhealth Uhealth 2017 Apr 19;5(4):e53 [FREE Full text] [CrossRef] [Medline]
  58. Holtz B, Murray K, Hershey D. The Development and Prototype Testing of a Patient-Centered mHealth App for Diabetes. 2017 Presented at: American Diabetes Association; June 2017; San Diego, CA.
  59. American Diabetes Association. Standards of Medical Care in Diabetes-2016: Summary of Revisions. Diabetes Care 2016 Jan;39 Suppl 1:S4-S5. [CrossRef] [Medline]
  60. Castenøe-Seidenfaden P, Teilmann G, Kensing F, Hommel E, Olsen BS, Husted GR. Isolated thoughts and feelings and unsolved concerns: adolescents' and parents' perspectives on living with type 1 diabetes - a qualitative study using visual storytelling. J Clin Nurs 2017 Oct;26(19-20):3018-3030. [CrossRef] [Medline]
  61. Hamine S, Gerth-Guyette E, Faulx D, Green BB, Ginsburg AS. Impact of mHealth chronic disease management on treatment adherence and patient outcomes: a systematic review. J Med Internet Res 2015 Feb 24;17(2):e52 [FREE Full text] [CrossRef] [Medline]
  62. Anderson M, Singh A, Page D. Parents, teens and digital monitoring. Pew Research Center: Internet, Science & Technology 2016 [FREE Full text]
  63. Lenhart A, Duggan M, Perrin A, Stepler R, Rainie H, Parker K. Teens, social media & technology overview. Pew Research Center Internet & American Life Project 2015 [FREE Full text]
  64. Veazie SW, Gilbert J, Paynter R, Ivlev I, Eden K, Nussbaum K, et al. Mobile applications for self-management of diabetes: technical brief no. 31. Agency for Healthcare Research and Quality 2018;18-EHC010-EF [FREE Full text]
  65. Tidwell L, Walther J. Computer-Mediated Communication Effects on Disclosure, Impressions, and Interpersonal Evaluations: Getting to Know One Another a Bit at a Time. Human Comm Res 2002 Jul;28(3):317-348. [CrossRef]
  66. Hanna KM, Juarez B, Lenss SS, Guthrie D. Parent-adolescent communication and support for diabetes management as reported by adolescents with type 1 diabetes. Issues Compr Pediatr Nurs 2003;26(3):145-158. [CrossRef] [Medline]
  67. Wiebe DJ, Berg CA, Korbel C, Palmer DL, Beveridge RM, Upchurch R, et al. Children's appraisals of maternal involvement in coping with diabetes: enhancing our understanding of adherence, metabolic control, and quality of life across adolescence. J Pediatr Psychol 2005 Mar;30(2):167-178. [Medline]
  68. Eysenbach G. The law of attrition. J Med Internet Res 2005 Mar 31;7(1):e11 [FREE Full text] [CrossRef] [Medline]
  69. Wu RC, Delgado D, Costigan J, Maciver J, Ross H. Pilot study of an Internet patient-physician communication tool for heart failure disease management. J Med Internet Res 2005 Mar 26;7(1):e8 [FREE Full text] [CrossRef] [Medline]

ADA: American Diabetes Association
BG: blood glucose
HbA1c: glycated hemoglobin
mHealth: mobile health
RCT: randomized controlled trial
T1DM: type 1 diabetes mellitus

Edited by G Eysenbach; submitted 17.04.18; peer-reviewed by F Calvo, V Hagger; comments to author 07.06.18; revised version received 20.07.18; accepted 14.08.18; published 30.10.18


©Bree E Holtz, Katharine M Mitchell, Denise D Hershey, Shelia R Cotten, Amanda J Holmstrom, Joshua Richman, Julie K Dunneback, Michael A Wood. Originally published in JMIR Research Protocols (, 30.10.2018.

This is an open-access article distributed under the terms of the Creative Commons Attribution License (, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work, first published in JMIR Research Protocols, is properly cited. The complete bibliographic information, a link to the original publication on, as well as this copyright and license information must be included.