Telemedicine for adolescents with type 1 diabetes.

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Telemedicine for Adolescents With Type 1 Diabetes Jennifer P. Dougherty, Terri H. Lipman, Sandra Hyams and Kathleen A. Montgomery West J Nurs Res 2014 36: 1199 originally published online 1 April 2014 DOI: 10.1177/0193945914528387 The online version of this article can be found at: http://wjn.sagepub.com/content/36/9/1199

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Article

Telemedicine for Adolescents With Type 1 Diabetes

Western Journal of Nursing Research 2014, Vol. 36(9) 1199–1221 © The Author(s) 2014 Reprints and permissions: sagepub.com/journalsPermissions.nav DOI: 10.1177/0193945914528387 wjn.sagepub.com

Jennifer P. Dougherty1, Terri H. Lipman2, Sandra Hyams3, and Kathleen A. Montgomery1

Abstract Diabetes is the third most common chronic disease in the pediatric population and diabetes management in adolescents presents a unique challenge for health care providers. The purpose of this article is to define telemedicine, review a variety of telemedicine intervention studies in the adolescent population, and interpret those results in the context of the current health care climate. Clinicians and researchers will be provided with education related to adolescent needs and telemedicine interventions so that telemedicine can be used effectively to promote the health of adolescents with diabetes. Because telemedicine has yet to demonstrate consistent and significant positive outcomes in this population, further research and continued development of technology are essential to improve diabetes control in adolescents and prevent the long-term complications of this disease. Keywords diabetes mellitus, type 1; telecommunications; adolescen; self-care; chronic disease

1The

Children’s Hospital of Philadelphia, PA, USA of Pennsylvania School of Nursing, Philadelphia, PA, USA 3Cook Children’s Medical Center, Fort Worth, TX, USA 2University

Corresponding Author: Jennifer P. Dougherty, MSN, CRNP, CPNP-AC, Pediatric Nurse Practitioner, The Children’s Hospital of Philadelphia, 3400 Civic Center Blvd., Philadelphia, PA 19104, USA. Email: [email protected]

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Western Journal of Nursing Research 36(9)

Diabetes is one of the most common chronic diseases in pediatrics in the United States, affecting more than 151,000 youth under 20 years of age in 2011 (Centers for Disease Control and Prevention [CDC], 2012). According to the CDC (2012), complications from diabetes are more common or more severe in those whose diabetes is poorly controlled. Therefore, improving diabetes control through the use of better management and prevention practices can improve the health of youth with diabetes (CDC, 2012). Because diabetes control in adolescence is significantly poorer than in other age groups, it is vital to develop interventions that resonate with adolescents and maximize good diabetes control prior to adulthood (Harris, Hood, & Mulvaney, 2012). Optimal diabetes management during adolescence can prolong life expectancy and lead to improved health outcomes (The National Diabetes Information Clearinghouse, 2011).

Background What Is Telemedicine? According to the American Telemedicine Association (ATA; 2012), telemedicine is defined as “the use of medical information exchanged from one site to another via electronic communications to improve a patient’s clinical health status”. The World Health Organization (WHO; 2010) describes telemedicine as health care services that are delivered remotely using technology to assess and diagnose problems, deliver treatments, and promote the health of individuals and entire communities. Others have further defined telemedicine in diabetes as “the scheduled remote transmission of blood glucose data by means such as telephone, fax, mobile phone, or internet with unsolicited clinician feedback” (Shulman, O’Gorman, & Palmert, 2010, p. 1). For the purposes of this article, the term telemedicine will be used to describe any remote communication of health care information and services between patients and health care providers using telecommunication, a definition consistent with the ATA (2012) and WHO (2010). Monitoring patients remotely using technology such as mobile phones and other wireless devices has been described as an “accessible, affordable method[s] for self-managing diabetes and adhering to exercise and diet regimens” (Russell-Minda et al., 2009, p. 1469). Telemedicine has the potential to help relieve the burden placed on many patients due to lack of access to health care, limited financial resources, and shortages of qualified providers (Franc et al., 2011). If used effectively, telemedicine can successfully improve the quality of care and eliminate barriers such as geographical proximity to appropriate providers (Franc et al., 2011; Harris et al., 2012).


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Diabetes in Adolescence Diabetes in adolescence is challenging to manage and is further complicated by the social, emotional, and psychological demands of the disease (Harris et al., 2012). From a health care perspective, the hormonal changes during puberty can result in insulin resistance that can further complicate insulin regimens, increase the number of daily interruptions to manage diabetes, and frustrate both the adolescent and family (Borus & Laffel, 2010). Periods of accelerated physical growth, and lack of attention to diet and exercise, change insulin requirements. Sporadic blood glucose monitoring and insulin administration results in poor diabetes control as evidenced by elevated hemoglobin A1C (HbA1C) values, the standard measure of diabetes control over a 3-month period. This can lead to adverse short- and long-term health complications that include hypoglycemia and diabetic ketoacidosis, retinopathy, peripheral neuropathy, hypertension and cardiovascular disease, gastroparesis, nephropathy, and sexual dysfunction (Farrell & Holmes-Walker, 2011; Shulman et al., 2010). Interventions that improve diabetes management and decrease chronic hyperglycemia can prevent these serious consequences (American Diabetes Association, n.d.). Emotional factors, such as family relationships and mental health issues, can result in numerous factors contributing to poor glycemic control during these years (Carroll, DiMeglio, Stein, & Marrero, 2011a; Iannotti et al., 2006; Lehmkuhl et al., 2010). Adolescents have competing academic and social demands and may not be motivated to attend appointments, particularly if their diabetes is in poor control and they predict potentially unpleasant interactions with their parents and/or diabetes health care providers. This lack of effective follow-up is one of the most important factors leading to the decline in diabetes management in adolescents and emphasizes the importance of interventions that increase interactions with health care providers to improve control and decrease complications of diabetes (Borus & Laffel, 2010; Farrell & Holmes-Walker, 2011; Russell-Minda et al., 2009). Adolescents of color, or of low income, also face issues of racial/ethnic and socioeconomic disparities and limited access to health care (Shulman et al., 2010). Racial and ethnic disparities have been demonstrated in the diagnosis, treatment, and outcomes of children and adolescents with diabetes (Lehmkuhl et al., 2010). Adolescents in underserved or rural areas may not have access to diabetes specialists or primary care providers trained in diabetes management, or the transportation to these appointments may place a significant strain on family resources (Lehmkuhl et al., 2010). Current and future shortages in health care providers may exacerbate this problem for this vulnerable group of patients (Russell-Minda et al., 2009).


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The interplay of all of these factors creates a unique challenge for health care providers who care for adolescents with diabetes. Adolescence provides an opportunity to establish lifelong habits for diabetes management as adolescents transition to self-care and adult health care providers. Therefore, this developmental stage should be targeted to ensure long-term success (Farrell & Holmes-Walker, 2011).

Technology and Adolescents Technology can be utilized to help adolescents manage diabetes. Research has demonstrated that adolescents have significant exposure to technology on a daily basis. The Kaiser Family Foundation found that adolescents use on average 7 hr and 38 min of social media per day (Rideout, Foehr, & Roberts, 2010). A 2011 survey by the Pew Internet and American Life Project showed that 95% of American adolescents use the Internet, as many as 70% on a daily basis, and 74% of adolescents have their own computers (Lenhart, 2012), demonstrating that “the likelihood of dissemination of interventions to adolescents via the internet is quite high” (Harris et al., 2012, p. 970). More than 77% of adolescents have mobile phones and the majority use text messaging daily (Lenhart, 2012). Therefore, mobile technology has become an accessible and essential component of adolescent culture and daily life worldwide. Low income, urban, and minority adolescents have access to this technology as well, with more than 90% using the Internet and 94% sending text messages on a daily basis (Lindstrom Johnson, Tandon, Trent, Jones, & Cheng, 2012). Because of this intense usage, technology in this age group has great potential for health promotion interventions. Technology for health care must be feasible for long-term use, able to reach a wide variety of patients, and not impose significant time demands on health care providers (Shulman et al., 2010). There also must be maximum return for minimal input and effort required, as adolescents are less likely than adults and children to utilize technology when it is cumbersome and time-demanding (Borus, Blood, Volkening, Laffel, & Shrier, 2013). Technology may be particularly effective in providing access to health care for minority and low income adolescents. Underserved populations may benefit from accessing diabetes health care through telemedicine interventions (George, Hamilton, & Baker, 2012). The perception of telemedicine in African American and Latino urban communities was evaluated and participants believed that telemedicine was helpful for providing efficient access to care in underserved areas and eliminating barriers such as location and transportation (George et al., 2012). Tailoring interventions to align


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with community needs and values is important for the success of telemedicine (George et al., 2012).

Method The data on the use of telemedicine for diabetes management in adults have been strongly positive with high rates of patient and provider satisfaction, better disease control, and reduced need for hospitalizations (Harris et al., 2012). However, telemedicine in adolescents has not been studied as extensively in general, or in adolescents with diabetes. Several varieties of telemedicine have been used in diabetes including social media, websites, Internet applications, remote disease monitoring, text messaging, and phone or video consultations. A review of websites and social media related to diabetes management can be found in the article by Ho and colleagues and will not be discussed in this article (Ho, O’Connor, & Mulvaney, 2014). The types of telemedicine interventions for diabetes that will be reviewed include text messaging, phone and video consultation, remote blood glucose and disease monitoring, mobile phone applications, and computer software. A literature search of Pubmed and CINAHL was conducted using the terms type 1 diabetes and telecommunications to identify studies published from January 1, 2006, to December 31, 2013. The MeSH search term telecommunications was used because it encompasses the terms: electronic bulletin boards, electronic mail, instant messaging, interactive voice response systems, internet, social media, social networking, radio, telecommuting, teleconferencing, telefacsimile, telehealth, telemedicine, telenursing, telepsychiatry, telephone, television, text messaging, videoconferencing, voice mail, and wireless communications. When these results were limited to include only studies published in English, available online, and studying adolescents (ages 13-18), a total of 90 studies were identified. Studies were excluded if they included patients with type 2 diabetes, a majority of participants are older or younger than the adolescent age group, or if an intervention other than the telemedicine interventions of interest stated above was evaluated. In addition, only studies where hemoglobin A1C (HbA1C) values were measured were included. Duplicate articles describing the same study were also excluded. References from pertinent review articles were examined to find additional studies on telemedicine and diabetes meeting our inclusion criteria that were not identified in our initial literature search. One study was included that falls outside our specified time period because to our knowledge, it is a classic study that evaluated the use of telemedicine in place of the traditional provider visit in adolescents with diabetes (Chase et al., 2003). A total of 15 studies were identified using these methods.


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Results Automated Systems: Mobile Phone Communication Using the SuperEgo system, adolescents were sent weekly text messages of encouragement based on their self-identified top three barriers to diabetes self-management and could alter the frequency, type, and topic of the text messages during the program via a website. The participants believed that the website and text messages helped them remember to complete diabetes tasks such as checking blood glucoses and bringing supplies, and reduced their feelings of isolation and embarrassment related to diabetes. While the intervention group had no change from their baseline HbA1C at the completion of the study, a matched historical control group had a significant worsening of glycemic control (Mulvaney, Anders, Smith, Pittel, & Johnson, 2012). The Computerized Automated Reminder Diabetes System (CARDS) study evaluated the impact of automated text messages on blood glucose monitoring in adolescents with diabetes (Hanauer, Wentzell, Laffel, & Laffel, 2009). Adolescents self-selected a schedule for reminders via text message or email and could “opt in” to receive informational messages. Users received a follow-up message after 15 min if they failed to respond to the reminder message with blood glucose data. Although the text message group was initially more interactive with the system, the level of participation after 3 months diminished for both groups. At the conclusion of the study, average HbA1C improved slightly for the text message users and worsened slightly for the email users, but neither change was statistically significant (Hanauer et al., 2009).

Interactive Systems: Remote Disease Monitoring The “Sweet Talk” study evaluated the use of a text messaging support system to help manage diabetes and provide education for insulin therapy (Franklin, Waller, Pagliari, & Greene, 2006). Adolescents were randomized to either conventional or intensive insulin regimens and received regular text messages based on their diabetes goals and personal demographics, a weekly text message reminding them of their goal, and “newsletter” texts asking for information on self-management. Adolescents were encouraged to send in information or ask questions related to selfmanagement and received responses from their diabetes team members. Overall, adolescents were highly satisfied with the system and 90% cited they wanted to continue the program. HbA1C values improved for adolescents using the intervention in conjunction with intensive insulin therapy (Franklin et al., 2006).


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Text messaging was utilized as a method for adolescents to receive support from their nurse practitioner (NP) in a study where diabetes self-management was monitored remotely (Carroll et al., 2011a). A behavioral contract was developed between parents and adolescent related to helping these families navigate the transition of diabetes care from parental to adolescent responsibility and address points of conflict and this contract was used in conjunction with telemedicine. The study aimed to prevent crises related to diabetes by helping the adolescent gain independence and specifically reduce conflict related to blood glucose monitoring. A mobile device, GlucoPack, monitored the frequency of blood glucose testing and prompted the NP to intervene with either a text message or phone call if a breach in contract had occurred (e.g., the results or frequency of blood glucose testing were not consistent with the behavioral contract). After an additional breach in the contract, the NP spoke with the parents and adolescent together about expected behaviors, and after a third breach, a meeting was held to discuss divisions of responsibility, the contract, and appropriate boundaries for diabetes management. This approach helped adolescents gain responsibility and limited the need for the parents to prod the adolescent to test blood sugars. The study found a significant increase in Diabetes Self-Management Profile results and a statistically significant decrease in HbA1C values (Carroll et al., 2011a). These results were not seen in previous studies of adolescents who used the GlucoPack alone without a behavioral contract, and highlights the effect of a behavioral agreement in conjunction with technology to help adolescents better manage their diabetes (Carroll, DiMeglio, Stein, & Marrero, 2011b). A study of remote blood glucose transmission in adolescents showed a similar improvement in diabetes control and a significant cost savings to adolescents when compared with the traditional care regimen of diabetes clinic visits every 3 months (Chase et al., 2003). Adolescents in the intervention group transmitted blood glucose data to their diabetes providers via their glucometers and a modem. They then received follow-up phone calls from their providers to discuss blood glucose data and any treatment changes, but only attended a clinic visit every 6 months. The control group attended all regular clinic visits at 3-month intervals and had the option of communicating blood glucose data to their provider via telephone or fax but could not use electronic transmission. At the conclusion of the study, both groups had significantly improved glycemic control and high satisfaction with their diabetes care. The modem intervention saved adolescents an average of US$142 when compared with the control group, even when the cost of the technology and time for provider phone calls was included (Chase et al., 2003). While clinic visits every 6 months may not be ideal for all adolescents, this


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intervention demonstrated that for this group, remote blood glucose monitoring was a cost-saving acceptable alternative and could be used in place of clinic visits in certain situations to combat appointment shortages and barriers such as transportation and time off work (Chase et al., 2003). In another study of remote blood glucose data transmission, glucose data were shared with the diabetes team via the Internet from the adolescents’ glucometers by uploading to the Carelink website. Adolescents received reminder phone calls if they failed to upload their data or parents received calls if treatment modifications were required. Study adherence was very poor though the adolescents rated the modality was useful. Only 33% of participants regularly sent in data and of these, only 54% of adolescents sent in the data themselves. A small improvement was seen in the adherent group with a 0.45% average, but not significant, decrease in HbA1C. However, satisfaction with the system was high and increased communication with the diabetes health care providers was valued (Landau et al., 2012). The effect of transmitting blood glucose data via fax with the help of the local pharmacist on diabetes management was studied (Gay et al., 2006). Adolescents used software either at home or their pharmacy to send glucose meter data to their diabetes team and received a follow-up phone call with any treatment changes. Adherence to the intervention was very poor for all adolescents, with diabetes providers only receiving 30% of the expected faxes and adolescents receiving responses to less than 70% of their submitted data. The study had numerous technical difficulties which contributed to these low rates of participation. At the conclusion of the study, no significant changes in glycemic control were observed between the intervention and control groups, and there was no increase in blood glucose monitoring for adolescents in the intervention group (Gay et al., 2006). The difference in glycemic control for adolescents using telemedicine remote disease monitoring and conventional paper record keeping was studied (Rami, Popow, Horn, Waldhoer, & Schober, 2006). Participants were randomized to start in the telemedicine phase or the conventional phase and switched halfway through the study period. Blood glucose values and diabetes management data were submitted to the diabetes team via mobile phone software and adolescents received a weekly follow-up text message during the telemedicine phase. Adolescents kept paper records and had no additional contact with their diabetes provider during the conventional phase of the study. It was found in both groups that adolescents had higher HbA1C values during the conventional phase of the study and lower HbA1C values during the telemedicine phase. Thus, it was concluded that the telemedicine intervention resulted in improved glycemic control for all adolescents. Clinicians spent a minimal amount of time reviewing the submitted data and overall satisfaction with the intervention was high (Rami et al., 2006). Downloaded from wjn.sagepub.com at Ondokuz Mayis Universitesi on November 6, 2014

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Interactive Systems: Phone and Video Communication Access to mobile phone support for sick day management was evaluated to determine whether it was associated with reduced hospital admissions due to diabetic ketoacidosis (Farrell & Holmes-Walker, 2011). Adolescents in four groups were compared to examine the relationship between diabetes control and the effectiveness of a phone support system for sick day management— defined as the presence of ketonuria. The interactive voice and text message support system was designed to augment the education adolescents received at clinic appointments and allow real-time support from providers to prevent hospital admission when sick. HbA1C values were not associated with frequency of system access and 94% of the adolescents who used the system for ketone management successfully avoided hospital admission regardless of their diabetes control (Farrell & Holmes-Walker, 2011). The study also found that adolescents who were more recently diagnosed with diabetes were less likely to use the mobile support system, suggesting a need for targeting education in this group (Farrell & Holmes-Walker, 2011). The effect of telemedicine behavioral therapy for children and parents on diabetes self-management, family functioning, and glycemic control was studied (Lehmkuhl et al., 2010). Adolescents discussed topics such as selfcare activities, potential barriers to diabetes management, education, problem solving, responsibility, family functioning, and communication with trained researchers during scheduled phone calls. All participants had an average 0.75% decrease in HbA1C values and demonstrated an improvement in diabetes self-management scores. Participants who began therapy immediately demonstrated a nonsignificant greater improvement in their glycemic control when compared with participants who were waitlisted for a month prior to starting therapy. The immediate treatment group also showed improvements on the Clinical Global Improvement scale during the study in 4 times as many adolescents when compared with the waitlist group. Adolescents were receptive to the intervention and this method has significant promise for reaching adolescents in areas with limited access to diabetes care (Lehmkuhl et al., 2010). Bimonthly phone calls were studied to determine the effect on glycemic control and diabetes knowledge (Nunn, King, Smart, & Anderson, 2006). Adolescents discussed diabetes care and received education and support from a diabetes educator during scheduled phone sessions and continued their regular clinical care. After the intervention period, glycemic control worsened for adolescents in both the intervention and control groups with an average 0.6% increase in HbA1C and no improvements in diabetes knowledge, self-management, or rate of hospitalization were observed. In addition,


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glycemic control was worse for adolescents with more parental involvement with the intervention. Despite the lack of diabetes care improvement, adolescents and families reported the phone calls as helpful (Nunn et al., 2006). Phone and video communication were used in a telemedicine intervention to improve family functioning and diabetes management for adolescents with repeated hospitalizations for diabetic ketoacidosis or poor glycemic control (Heidgerken et al., 2006). Adolescents communicated with a therapist several times weekly via phone calls or videoconferencing for several months and discussed family processes, diabetes knowledge, and barriers to treatment. Adolescents had significantly improved glycemic control with an average 0.7% decrease in HbA1C at the conclusion of the study, and no adolescents required hospitalization during the treatment period (Heidgerken et al., 2006). Videoconferencing via Skype was used in a school-based setting to improve diabetes care (Izquierdo et al., 2009). Using the telemedicine system, an intervention group had a prescheduled regular monthly meeting with the school nurse, student, diabetes NP, and possibly the students’ parents, to exchange diabetes information. This was in addition to their regular diabetes clinic care. An added component of the intervention was a collection of online educational modules for the school nurse and other educators to complete to increase their knowledge of diabetes and disease management. Improvement in diabetes control for the intervention group was seen during the first 6 months of the study but was not statistically significant. There were fewer urgent school nurse visits and acute events such as hospitalizations and emergency department visits for the students in the intervention group. Students in the intervention group performed significantly better on emotional measures in the diabetes surveys, felt less embarrassed about their disease, felt better equipped to manage their diabetes, and especially improved in the quality of life areas of diabetes tasks such as giving insulin and checking blood sugars (Izquierdo et al., 2009).

Smartphone Applications Although hundreds of smartphone applications (apps) for diabetes are available for health information tracking, medication management, device teaching, and social networking, there are minimal data on the effectiveness of these devices on diabetes management (Eng & Lee, 2013). Visual learning for diabetes care was evaluated through a study combining a “Diamob” mobile phone diary app and the Diabetes Message System, a mobile messaging app (Frøisland, Arsand, & Skårderud, 2012). Adolescents used Diamob to track correct food portions, grams of carbohydrates, blood glucose data, insulin doses, and activity levels. The Diabetes Messaging System allowed


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adolescents to contact their diabetes health care provider and receive a prompt response as well as educational messages. Adolescents enjoyed having quick access to the apps and felt the visual representation of their diet was helpful for reviewing dietary trends and discussing diabetes management with their parents. Diamob was particularly helpful in assisting adolescents to integrate the different components of their diabetes care into one system and was easier to use than traditional paper logs. Adolescents reported they benefited from the information they received from the messaging app and enjoyed the ability to contact their providers, but there was no significant change in glycemic control or scores on diabetes knowledge testing despite high satisfaction ratings (Frøisland et al., 2012). A mobile app called bant was studied to evaluate the impact of automatic transfer of blood glucose readings to an iPhone or iPod to help users manage their diabetes care. Based on the data received, the app would prompt the user to review their blood glucose trends and make a treatment decision accordingly. The app also provided incentives via a points system, the ability to communicate via a peer network, and an online portal for parents and providers to view input data. While glycemic control did not change significantly over the study period, the frequency of blood glucose testing increased significantly and users were highly satisfied with the app (Cafazzo, Casselman, Hamming, Katzman, & Palmert, 2012). Overall, this review of telemedicine interventions for adolescents with diabetes produced mixed results. A summary of the studies can be found in Table 1. We evaluated studies using both automated and interactive systems with interventions lasting from 3 months to 3 years with varying outcome measures and clinical impact. Telemedicine interventions involving a text messaging component were the most common, with 7 of 15 studies including some type of mobile messaging. The vast majority of the studies were interactive, with only 2 interventions not requiring provider participation. All of the studies were safe with a low prevalence of severe hypoglycemia or ketoacidosis during the intervention.

Discussion Effective technology for disease management in adolescents needs to be simple, reliable, relevant, and interactive. Various modes of technology can reach a majority of adolescents, reduce the daily burden of chronic illness, promote self-efficacy, and allow for extensive learning and interaction to take place. Therefore, the use of telemedicine for diabetes management in adolescents has significant promise but has yet to demonstrate consistent results.


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Remote Internet transmission of blood glucose data with follow-up phone calls. Mobile phone support system for ketone management.

N = 63 participants ages 15 to 20 years, 100% non-Hispanic Caucasian. Randomized to intervention (N = 30) or control group (N = 33). 6-month study. N = 350 participants ages 15 to 25 years. Four groups: Clinic patients with ketoacidosis using (N = 31) or not using the intervention (N = 15), patients without ketosis (N = 285), or nonclinic patients hospitalized for ketoacidosis (N = 15). No data on race/ethnicity. 3-year study.

Mobile Phone Support Is Associated With Reduced Ketoacidosis in Young Adults.

Farrell and HolmesWalker (2011)

Chase et al. (2003)

GlucoPack, a cell phone blood sugar monitoring system.

N = 10 participants ages 14 to 18 years. No data on race/ethnicity. 3-month study.

Contracting and Monitoring Relationships for Adolescents With Type 1 Diabetes: A Pilot Study. Modem Transmission of Glucose Values Reduces the Costs and Need for Clinic Visits.

Carroll, DiMeglio, Stein, and Marrero (2011a)

Bant app

N = 20 participants ages 12 to 16 years. Control group was the same patients in the previous 3 months. No data on race/ethnicity 3-month study.

Design of an mHealth App for the SelfManagement of Adolescent Type 1 Diabetes: A Pilot Study.

Cafazzo, Casselman, Hamming, Katzman, and Palmert (2012)

Telemedicine intervention

Sample, characteristics, and duration of study

Study name

Authors and publication year

Table 1. Description of Studies.

Use of behavioral intervention in conjunction with telemedicine had better results than telemedicine alone. Telemedicine can save time and money.

Telemedicine can effectively help manage acute situations.

No EHR integration of data.

Many subgroups of patients need more frequent contact with diabetes team.

Observational study only, no randomization. Number of clinic patients with ketosis but no system use or hospital presentation not measured.

Significant average 0.3% decrease in HbA1C in both groups.

Hospital admission rate of patients with ketosis who used the system was 6% compared with 120% for clinic patients with ketosis who did not use the system.

(continued)

Decision-making prompts help adolescents manage their disease. Integration with already existing technology is important.

Lack of communication between app and insulin pump.

Nonsignificant 0.4% average increase in HbA1C. 50% increase in daily average frequency of blood glucose measurement. Significant average 0.5% decrease in HbA1C values.

Implications

Challenges

Results


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Improving Diabetes Care for Young People With Type 1 Diabetes Through Visual Learning on Mobile Phones: Mixed-Methods Study. Reinforced Follow-Up for Children and Adolescents With Type 1 Diabetes and Inadequate Glycaemic Control: A Randomized Controlled Trial Intervention via the Local Pharmacist and Telecare.

Frøisland, Arsand, and Skårderud (2012)

Gay et al. (2006)

A Randomized Controlled Trial of Sweet Talk, a Text Messaging System to Support Young People With Diabetes.

Study name

Franklin, Waller, Pagliari, and Greene (2006)


Table 1. (continued)

Usability of technology is important. Telemedicine interventions are not successful without the participation of patients and diabetes team. Multiple problems with data transmission and software malfunction. Poor participation. Nonsignificant average 0.1% HbA1C decrease in intervention group and 0.1% increase in control group.

Fax transmission of blood glucose data and phone communication with diabetes provider.

(continued)

Visual memory aids are helpful for diabetes management. Apps are helpful for integrating different aspects of diabetes care. Need to access from a web browser instead of phone messaging function and use specific study phone were barriers.

No significant changes or adverse events. High satisfaction rates with the apps.

“Diamob,” a mobile phone diary and message system.

N = 100 participants ages 8 to 17 years. 2 groups— intervention (N = 50) and control (N = 50). 57% European, 41% North African. 6-month study

System was a helpful adjunct to treatment but not effective alone.

No comparison group for intensive insulin therapy without intervention.

Nonsignificant average 1% decrease in HbA1C only for patients with intensive insulin therapy and intervention.

Implications

Interactive text messaging system—“Sweet Talk.”

Challenges

N = 92 participants ages 8 to 18 years, 4% non-White. Randomized to three groups—control group (N = 28), intervention group (N = 33), and intervention group with intensive insulin therapy (N = 31). 12-month study. N = 12 participants ages 13 to 19 years. No data on race/ethnicity. 3-month study.

Results



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School-Centered Telemedicine for Children With Type 1 Diabetes Mellitus.

Izquierdo et al. (2009)

Heidgerken et al. (2006)

Computerized Automated Reminder Diabetes System (CARDS): Email and SMS Cell Phone Text Messaging Reminders to Support Diabetes Management. Telehealth Intervention for Adolescents With Type 1 Diabetes.

Study name

Hanauer, Wentzell, Laffel, and Laffel (2009)



Patients in poor control are receptive to this type of intervention. No control group, varied length of intervention, and no measures of knowledge or diabetes management. School break schedule impacted intervention. Technology problems during beginning of study.

Significant average 0.7% decrease in HbA1C at end of intervention.

Nonsignificant decrease in HbA1C from 0 to 6 months for intervention group and increase for control group.

Phone or video therapy sessions.

Video conference meetings and online education.

N = 27 participants ages 9 to 18 years, 22% non-White. Telephone (N = 19) or video (N = 8) groups. Study not time-limited; average duration 5.7 months.

N = 41 participants ages 5 to 14 years, 10% non-White. Intervention (N = 23) and control group (N = 18). 12-month study.

(continued)

Intervention group maintained improved diabetes control during the study. Reduced acute events in intervention group saved time, money, and stress.

SMS reminders were preferable to email.

Interaction with the system decreased over the study for both groups.

Nonsignificant average 0.2% HbA1C decrease in SMS group and increase in email group. More interaction with system for SMS group.

Daily automated SMS message or email reminder system.

N = 40 participants ages 14 to 20 years Email (N = 18) or SMS (N = 22) groups. No data on race/ethnicity. 3-month study

Implications

Challenges

Results




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Phone calls Waitlist group was delayed for 1 month before starting.

Text messaging via “SuperEgo” system.

N = 32 participants ages 9 to 17 years, 12% African American, 3.1% Hispanic. Immediate treatment (N = 18) and waitlist (N = 14) groups. 12 weeks.

N = 23 participants ages 13 to 17 years. Intervention and historical matched control group. No data on race/ethnicity. 3-month study.

Telehealth Behavior Therapy for the Management of Type 1 Diabetes in Adolescents.

A Pilot Test of a Tailored Mobile and Web-Based Diabetes Messaging System for Adolescents.

Mulvaney, Anders, Smith, Pittel, and Johnson (2012)

Online transmission of blood glucose data with follow-up phone calls.

N = 70 participants ages 12 to 17 years Intervention group (N = 36) or control (N = 34) groups. No data on race/ethnicity. 6-month study.

Lehmkuhl et al. (2010)



The Effectiveness of Internet-Based Blood Glucose Monitoring System on Improving Diabetes Control in Adolescents With Type 1 Diabetes.

Study name

Landau et al. (2012)



Nonsignificant 0.3% average decrease in HbA1C for compliant intervention group. Nonsignificant 0.2% increase in HbA1C for control group. Nonsignificant average 0.74% decrease in HbA1C for immediate treatment group and average 0.09% increase in waitlist group. Significant 1% average increase in A1C in control group while intervention group maintained baseline A1C.

Results

Small sample size. Historical control group used instead of intervention and control group.

Behavioral therapy via phone reached many patients without the capacity for videoconferencing.

Poor compliance (67%) from intervention group.

Challenges

(continued)

Most participants wanted social networking component. HbA1C was maintained using an intervention that did not require direct clinician involvement.

Intervention lacked interactivity or reward system and poor compliance was seen. No correlation between HbA1C improvement and frequency of interaction with the system. Hispanic and African American, low socioeconomic status, and underinsured participants included in study.

Implications

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Phone calls from diabetes educators.

Remote disease monitoring via VIE-DIAB system.

N = 36 participants ages 10 to 19 years. No data on race/ethnicity. 6-month study.

Telemedical Support to Improve Glycemic Control in Adolescents With Type 1 Diabetes Mellitus.

Rami, Popow, Horn, Waldhoer, and Schober (2006)


N = 123 participants ages 3 to 16 years, 100% non-Hispanic Caucasian. Intervention (N = 63) and control (N = 60) groups. 7-month study.


A Randomized Controlled Trial of Telephone Calls to Young Patients With Poorly Controlled Type 1 Diabetes

Study name

Nunn, King, Smart, and Anderson (2006)



Implications More frequent contact may be more required to see improvement.

Manual data entry into telemedicine system is time-consuming and may limit interaction with intervention.

Challenges Study included younger patients but mean age 11.9. No motivation or goal setting techniques were included.

Numerous technical problems.

Results Significant average 0.6% increase in HbA1C in both groups. More parental involvement with intervention associated with decreased glycemic control. Nonsignificant average 0.25% HbA1C decrease during telemedicine phase and 0.35% increase during conventional phase.

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Benefits of Telemedicine Although clinical improvements HbA1C were observed in 10 studies (Carroll et al., 2011a; Chase et al., 2003; Franklin et al., 2006; Gay et al., 2006; Hanauer et al., 2009; Heidgerken et al., 2006; Izquierdo et al., 2009; Landau et al., 2012; Lehmkuhl et al., 2010; Rami et al., 2006), improvement in diabetes control was statistically significant in only 3 studies (Carroll et al., 2011a; Chase et al., 2003; Heidgerken et al., 2006). No studies reported adverse effects from telemedicine use such as increased episodes of hypoglycemia and mobile phone support for sick days was associated with lower hospital admission rates for diabetes complications (Farrell & HolmesWalker, 2011). Users reported high levels of satisfaction with telemedicine and most wanted to continue using telemedicine after the conclusion of the studies even if no clinical improvements were demonstrated. The ability of the interventions, especially mobile diaries and apps, to provide real-time support and guidance to adolescents supported their self-efficacy and disease management. The use of communication methods relevant to the target age group enhanced the transfer of responsibility from the parent to the adolescent. The burden of chronic illness was reduced through remote disease monitoring and transmission of blood glucose values to providers for review and guidance between clinic visits (Carroll et al., 2011a; Chase et al., 2003; Franklin et al., 2006; Frøisland et al., 2012; Izquierdo et al., 2009; Lehmkuhl et al., 2010). Access to health care providers was increased through the use of telemedicine. Communication with diabetes providers via telemedicine was trusted and useful as a safety net and for education in between clinic visits. The option of some programs to alert providers when an adolescent had missed diabetes management tasks allowed for accountability and timely interventions by the clinicians. Adolescents demonstrated their interest in using technology, especially text messaging, and appreciated the increased contact with their provider that was provided. The use of visual imagery, a modality available on mobile apps such as Diamob, was particularly useful for adolescents because it allowed adolescents learn about and properly manage their disease using visual technology and reminders rather than traditional learning methods of reading or discussions (Frøisland et al., 2012). Perhaps one of the most important uses of telemedicine in chronic disease management lies in the ability to reach underserved or rural areas where access to qualified health care providers is limited or nonexistent. Four studies specifically included minority or non-White adolescents and each demonstrated an improvement in diabetes control for adolescents in the intervention groups (Franklin et al., 2006; Heidgerken et al., 2006; Izquierdo et al., 2009;


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Lehmkuhl et al., 2010). The use of telemedicine in a school setting integrated the involvement of the school nurse, a key member of the diabetes team, and was associated with better disease management and reduced complications such as hospital visits (Izquierdo et al., 2009). It was demonstrated that the use of telemedicine in place of a clinic visit was equally effective and resulted in less time missed from work and school. Underserved adolescents in poor glycemic control benefitted from the increased contact with their providers that remote disease monitoring interventions provided, which is crucial as increased provider contact is associated with improved disease control and fewer complications (Heidgerken et al., 2006; Lehmkuhl et al., 2010). Finally, the cost benefit of telemedicine for the management of chronic diseases such as diabetes is important. Interventions that use common technology, such as mobile phones and computers, can reach a broad population and were preferred by adolescents. Similar glycemic control was seen in adolescents using telemedicine for blood glucose monitoring in lieu of a clinic visit, demonstrating the potential savings of time and money over a 6-month period without a decrease in disease control or increase in complications. Even systems that require initial equipment purchases were found to be costeffective due to reduced hospital admissions rates and emergency room visits due to the minimal cost per use over time. Better disease management can result in significant long-term savings by reducing the rate of complications and comorbidities, rendering effective telemedicine interventions a costeffective solution.

Challenges to Clinical Use While these telemedicine interventions were largely satisfactory, challenges were identified that require attention and future improvement. Programs compatible with personal mobile phones (instead of separate devices) were found to be easier for adolescents to use. Users reported better results when they could transmit information using their personal devices rather than having to log into a website or other device to communicate with or send information to their provider. No telemedicine systems we reviewed were able to automatically integrate into the Electronic Health Record (EHR), an essential component for efficiency and to enable providers to document their telemedicine encounters. Interventions that were cumbersome and required multiple log-ons or manual data entry demonstrated less participation and had waning compliance over time due to the additional effort required (Frøisland et al., 2012; Gay et al., 2006; Rami et al., 2006). Interventions that lacked incentives also demonstrated decreased interaction over time (Hanauer et al., 2009; Landau et al., 2012; Nunn et al., 2006). Adolescents wanted to be able to


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personalize their technology and appreciated being able to select the frequency and content of messages they received, demonstrating that adolescents need technology that is individualized, stimulating, and engaging for maximum success and sustained interest over time. Telemedicine was shown to improve social support and connectedness and participants appreciated interventions that increased a sense of community. However, this raises the issue of sharing health information via the Internet, websites, and online networks. Providers need to be diligent in promoting secure telemedicine interventions, educating their patients about trustworthy sources of information, and advocate for telemedicine regulations to protect their patients from the loss of health privacy. In addition, social networking features, a component requested by many adolescents using these interventions, raise the threat of loss of privacy. As peers are an important resource for sharing of information, guidelines for promoting peer interaction and mutual education in a safe and secure environment are needed. In general, interventions combining technology with clinician and parental involvement were found to be the most successful. This requires any telemedicine intervention to have clinician oversight rather than be fully automated, which can decrease the cost-effectiveness of telemedicine programs. In addition, third-party payers may not provide reimbursement for time spent developing and testing more effective programs in the future. Billing and reimbursement for telemedicine is an important issue for providers as these interventions may require a significant time commitment. Currently, the Centers for Medicare and Medicaid Services (n.d.) recognize telemedicine as a cost-effective alternative to the more traditional face-toface way of providing medical care but allow individual states to set guidelines for billing and reimbursement of interventions or visits. In general, telemedicine services are covered when they meet a certain set of criteria, commonly the synchronous interaction of provider and patient, across a significant distance, involve audio or videoconferencing, and in place of a standard clinic visit (ATA, 2013). Other forms of telemedicine, such as remote disease monitoring (commonly referred to as “store-and-forward” services), which may not take place in real time, involve communication via SMS messaging or email, or be in addition to standard clinical care, are only currently covered in a few states (ATA, 2013). A comprehensive understanding of telemedicine interventions is essential for today’s health care providers in our rapidly advancing health care market. Nurses can help adolescents with diabetes improve their disease control by providing education on the use of telemedicine, promoting their involvement in the development and evaluation of different types of technology, and stressing the importance of privacy and security when using this technology.


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The role of telemedicine as an adjunct—not a replacement—for personal, parental, and provider input should be stressed for optimal diabetes control. In addition, nurses can promote self-efficacy in adolescents by emphasizing the use of telemedicine as a tool to supplement their own problem-solving strategies for proper disease management. Because the laws regarding telemedicine differ greatly from state to state, it is vital for health care providers to be well-versed in the policies of their states regarding telemedicine. Providers must function within their scope of practice and advocate for telemedicine access and expanded legislation regarding reimbursement (Center for Connected Health Policy, 2013). The impact of telemedicine interventions on diabetes control is variable. Comparison of telemedicine interventions is limited by varying sample sizes, inconsistent outcome measures, and type and duration of interventions. Larger studies need to be conducted over longer periods of time to determine the lasting effects of various interventions as well as how to best tailor interventions over time and keep users engaged. Standardization of blood glucose meters, Internet platforms, and communication software is needed for better comparison of different interventions. The integration of telemedicine into the EHR is essential for seamless and safe delivery of care via telemedicine. Mobile apps, especially those providing clinical decision making support or dose calculations, need to be closely evaluated and monitored as medical devices to prevent potentially adverse patient outcomes. Involvement of adolescents, especially urban and underserved adolescents, is critical for the development of telemedicine interventions in the future to explore needed features, maximize utilization by eliminating privacy concerns, and encourage ownership of personal health status in these populations. Future research with minority adolescents is imperative as the majority of participants included in these studies were non-Hispanic whites. Finally, telemedicine research must demonstrate consistent and positive health outcomes for these interventions to be reimbursable. All of these factors are necessary for telemedicine to be a feasible and cost-effective option in today’s health care market. Declaration of Conflicting Interests The author(s) declared no potential conflicts of interest with respect to the research, authorship, and/or publication of this article.

Funding The author(s) received no financial support for the research, authorship, and/or publication of this article.


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References American Diabetes Association. (n.d.). Living with diabetes: Complications. Retrieved from http://www.diabetes.org/living-with-diabetes/complications/ American Telemedicine Association. (2012). What is telemedicine? Retrieved from http://www.americantelemed.org/about-telemedicine/what-is-telemedicine American Telemedicine Association. (2013). State Medicaid best practice: Storeand-forward telemedicine. Retrieved from http://www.americantelemed.org/ docs/default-source/policy/state-medicaid-best-practice—store-and-forwardtelemedicine.pdf Borus, J. S., Blood, E., Volkening, L. K., Laffel, L., & Shrier, L. A. (2013). Momentary assessment of social context and glucose monitoring adherence in adolescents with type 1 diabetes. Journal of Adolescent Health, 52, 578-583. doi:10.1016/j. jadohealth.2012.10.003 Borus, J. S., & Laffel, L. (2010). Adherence challenges in the management of type 1 diabetes in adolescents: Prevention and intervention. Current Opinion in Pediatrics, 22, 405-411. doi:10.1097/MOP.0b013e32833a46a7 Cafazzo, J. A., Casselman, M., Hamming, N., Katzman, D. K., & Palmert, M. R. (2012). Design of an mHealth app for the self-management of adolescent type 1 diabetes: A pilot study. Journal of Medical Internet Research, 14(3), e70. doi:10.2196/jmir.2058; 10.2196/jmir.2058 Carroll, A. E., DiMeglio, L. A., Stein, S., & Marrero, D. G. (2011a). Contracting and monitoring relationships for adolescents with type 1 diabetes: A pilot study. Diabetes Technology & Therapeutics, 13, 543-549. doi:10.1089/dia.2010.0181 Carroll, A. E., DiMeglio, L. A., Stein, S., & Marrero, D. G. (2011b). Using a cell phone-based glucose monitoring system for adolescent diabetes management. Diabetes Educator, 37, 59-66. doi:10.1177/0145721710387163 Center for Connected Health Policy. (2013). State telehealth laws and reimbursement policies: A comprehensive scan of the 50 states and the District of Columbia. Retrieved from http://www.americantelemed.org/news-landing/2013/02/06/50state-telehealth-medicaid-policy-report-released Centers for Disease Control and Prevention. (2012). Diabetes report card 2012. Atlanta, GA: Author. Centers for Medicare and Medicaid Services. (n.d.). Telemedicine. Retrieved from http://www.medicaid.gov/Medicaid-CHIP-Program-Information/By-Topics/ Delivery-Systems/Telemedicine.html Chase, H. P., Pearson, J. A., Wightman, C., Roberts, M. D., Oderberg, A. D., & Garg, S. K. (2003). Modem transmission of glucose values reduces the costs and need for clinic visits. Diabetes Care, 26, 1475-1479. Eng, D. S., & Lee, J. M. (2013). The promise and peril of mobile health applications for diabetes and endocrinology. Pediatric Diabetes, 14, 231-238. doi:10.1111/ pedi.12034; 10.1111/pedi.12034 Farrell, K., & Holmes-Walker, D. J. (2011). Mobile phone support is associated with reduced ketoacidosis in young adults. Diabetic Medicine: A Journal of the British Diabetic Association, 28, 1001-1004. doi:10.1111/j.1464-5491.2011.03302.x


1220


Franc, S., Daoudi, A., Mounier, S., Boucherie, B., Dardari, D., Laroye, H., . . . Charpentier, G. (2011). Telemedicine and diabetes: Achievements and prospects. Diabetes & Metabolism, 37, 463-476. doi:10.1016/j.diabet.2011.06.006 Franklin, V. L., Waller, A., Pagliari, C., & Greene, S. A. (2006). A randomized controlled trial of Sweet Talk, a text-messaging system to support young people with diabetes. Diabetic Medicine, 23, 1332-1338. doi:10.1111/j.14645491.2006.01989.x Frøisland, D. H., Arsand, E., & Skårderud, F. (2012). Improving diabetes care for young people with type 1 diabetes through visual learning on mobile phones: Mixed-methods study. Journal of Medical Internet Research, 14(4), e111. doi:10.2196/jmir.2155 Gay, C. L., Chapuis, F., Bendelac, N., Tixier, F., Treppoz, S., & Nicolino, M. (2006). Reinforced follow-up for children and adolescents with type 1 diabetes and inadequate glycaemic control: A randomized controlled trial intervention via the local pharmacist and telecare. Diabetes & Metabolism, 32, 159-165. George, S., Hamilton, A., & Baker, R. S. (2012). How do low-income urban African Americans and Latinos feel about telemedicine? A diffusion of innovation analysis. International Journal of Telemedicine and Applications, 2012, 715194. doi:10.1155/2012/715194 Hanauer, D. A., Wentzell, K., Laffel, N., & Laffel, L. M. (2009). Computerized automated reminder diabetes system (CARDS): E-mail and SMS cell phone text messaging reminders to support diabetes management. Diabetes Technology & Therapeutics, 11, 99-106. doi:10.1089/dia.2008.0022 Harris, M. A., Hood, K. K., & Mulvaney, S. A. (2012). Pumpers, skypers, surfers and texters: Technology to improve the management of diabetes in teenagers. Diabetes, Obesity & Metabolism, 14, 967-972. doi:10.1111/j.1463-1326.2012.01599.x Heidgerken, A. D., Adkins, J., Storch, E. A., Williams, L., Lewin, A. B., Silverstein, J. H., . . . Geffken, G. R. (2006). Telehealth intervention for adolescents with type 1 diabetes. Journal of Pediatrics, 148, 707-708. doi:10.1016/j.jpeds.2006.01.001 Ho, Y.-X., O’Connor, B., & Mulvaney, S. A. (2014). Features of online health communities for adolescents with type 1 diabetes. Western Journal of Nursing Research. Advance online publication. doi:10.1177/0193945913520414 Iannotti, R. J., Schneider, S., Nansel, T. R., Haynie, D. L., Plotnick, L. P., Clark, L. M., . . . Simons-Morton, B. (2006). Self-efficacy, outcome expectations, and diabetes self-management in adolescents with type 1 diabetes. Journal of Developmental and Behavioral Pediatrics, 27, 98-105. Izquierdo, R., Morin, P. C., Bratt, K., Moreau, Z., Meyer, S., Ploutz-Snyder, R., & Weinstock, R. S. (2009). School-centered telemedicine for children with type 1 diabetes mellitus. Journal of Pediatrics, 155, 374-379. doi:10.1016/j. jpeds.2009.03.014 Landau, Z., Mazor-Aronovitch, K., Boaz, M., Blaychfeld-Magnazi, M., GraphBarel, C., Levek-Motola, N., & Pinhas-Hamiel, O. (2012). The effectiveness of internet-based blood glucose monitoring system on improving diabetes control in adolescents with type 1 diabetes. Pediatric Diabetes, 13, 203-207. doi:10.1111/ j.1399-5448.2011.00800.x


Dougherty et al.

1221

Lehmkuhl, H. D., Storch, E. A., Cammarata, C., Meyer, K., Rahman, O., Silverstein, J., . . . Geffken, G. (2010). Telehealth behavior therapy for the management of type 1 diabetes in adolescents. Journal of Diabetes Science and Technology, 4, 199-208. Lenhart, A. (2012). Teens, smartphones and texting. Retrieved from http://pewinternet.org/~/media//Files/Reports/2012/PIP_Teens_Smartphones_and_Texting.pdf Lindstrom Johnson, S., Tandon, S. D., Trent, M., Jones, V., & Cheng, T. L. (2012). Use of technology with health care providers: Perspectives from urban youth. Journal of Pediatrics, 160, 997-1002. doi:10.1016/j.jpeds.2011.11.059 Mulvaney, S. A., Anders, S., Smith, A. K., Pittel, E. J., & Johnson, K. B. (2012). A pilot test of a tailored mobile and web-based diabetes messaging system for adolescents. Journal of Telemedicine and Telecare, 18, 115-118. The National Diabetes Information Clearinghouse. (2011). National diabetes statistics, 2011. Retrieved from http://diabetes.niddk.nih.gov/dm/pubs/ statistics/#NewCasesDD Nunn, E., King, B., Smart, C., & Anderson, D. (2006). A randomized controlled trial of telephone calls to young patients with poorly controlled type 1 diabetes. Pediatric Diabetes, 7, 254-259. doi:10.1111/j.1399-5448.2006.00200.x Rami, B., Popow, C., Horn, W., Waldhoer, T., & Schober, E. (2006). Telemedical support to improve glycemic control in adolescents with type 1 diabetes mellitus. European Journal of Pediatrics, 165, 701-705. doi:10.1007/s00431-006-0156-6 Rideout, J. V., Foehr, U. G., & Roberts, D. F. (2010). Generation M2: Media in the lives of 8- to 18-year-olds. Retrieved from http://www.kff.org/entmedia/ upload/8010.pdf Russell-Minda, E., Jutai, J., Speechley, M., Bradley, K., Chudyk, A., & Petrella, R. (2009). Health technologies for monitoring and managing diabetes: A systematic review. Journal of Diabetes Science and Technology, 3, 1460-1471. Shulman, R. M., O’Gorman, C. S., & Palmert, M. R. (2010). The impact of telemedicine interventions involving routine transmission of blood glucose data with clinician feedback on metabolic control in youth with type 1 diabetes: A systematic review and meta-analysis. International Journal of Pediatric Endocrinology, 2010. doi:10.1155/2010/536957 World Health Organization. (2010). Telemedicine: Opportunities and developments in member states: Report on the second global survey on eHealth 2009 (Global Observatory for eHealth Series, Vol. 2). Retrieved from http://www.who.int/goe/ publications/goe_telemedicine_2010.pdf


Telemedicine in US Army soldiers with type 1 diabetes.

CoYoT1 Clinic: Innovative Telemedicine Care Model for Young Adults with Type 1 Diabetes.

Quality of life of adolescents with type 1 diabetes.

Correction: Quality of life of adolescents with type 1 diabetes.

Glycemic variability predicts inflammation in adolescents with type 1 diabetes.

Hyperfiltration and uricosuria in adolescents with type 1 diabetes.

[Insulin-induced edema in adolescents with type 1 diabetes mellitus].

Online Resources for Pediatric Type 1 Diabetes: What Adolescents Want.

Technology Use for Diabetes Problem Solving in Adolescents with Type 1 Diabetes: Relationship to Glycemic Control.

Diabetes-Specific Quality of Life of Korean Children and Adolescents With Type 1 Diabetes.

Overweight adolescents with type 2 diabetes have significantly higher lipoprotein abnormalities than those with type 1 diabetes.

Adherence in adolescents with Type 1 diabetes: strategies and considerations for assessment in research and practice.

Peer Interaction and Group Education for Adaptation to Disease in Adolescents with Type 1 Diabetes Mellitus.

Metformin for the treatment of hyperandrogenism in adolescents with type 1 diabetes mellitus.

Pilot study of a web-based intervention for adolescents with type 1 diabetes.

Feasibility of the SMART Project: A Text Message Program for Adolescents With Type 1 Diabetes.

Teaming up: feasibility of an online treatment environment for adolescents with type 1 diabetes.

Camp for Youth With Type 1 Diabetes.

Adolescents with clinical type 1 diabetes display reduced red blood cell glucose transporter isoform 1 (GLUT1).

Opportunities and Challenges of Telemedicine: Observations from the Wild West in Pediatric Type 1 Diabetes.

A Pilot Randomized Trial of Text-Messaging for Symptom Awareness and Diabetes Knowledge in Adolescents With Type 1 Diabetes.

Factors associated with nocturnal hypoglycemia in at-risk adolescents and young adults with type 1 diabetes.

The efficiency of telemedicine to optimize metabolic control in patients with type 1 diabetes mellitus: Telemed study.

Overnight glucose control with an automated, unified safety system in children and adolescents with type 1 diabetes at diabetes camp.