The result of this study show that the time spent in hyperglycaemia (%TAR) was significantly reduced in the intervention group compared with the comparison group. Furthermore, the intervention group empowerment score was significantly increased over time during the 1-year intervention period. However, other glycaemic control metrics did not differ significantly between the intervention group and the comparison group.
The adolescents with a high % TAR at baseline were those who benefited most from this intervention. This finding could be due to the greater collaboration that took place in our intervention between the adolescent and a diabetes nurse to achieve the planned goal, since adolescents with unsatisfactory glycaemic control required frequent follow-up and greater collaboration with a diabetes nurse (30, 31). The higher % TAR at the time of enrolment and the use of real-time blood glucose information may also have contributed to the observed outcome. This has also been observed in other studies done in Greece and Australia, which showed a significant reduction in TAR among the intervention group having unsatisfactory metabolic control at baseline. In both studies, participants with high TAR at baseline benefitted most from the intervention (41, 42).
The observed lowering of TAR is clinically important, as it could reduce hyperglycaemia-associated complications and healthcare costs related to hyperglycaemia (2, 43, 44). This is significant because hyperglycaemia increases the development of micro and macrovascular complications, which lead to long-term diabetes complications and patient vulnerability to various infectious diseases (2, 44). Furthermore, studies have revealed that hyperglycaemia is the most significant factor in neurodevelopmental problems among children and adolescents with T1D as well as being the main risk factor for neurocognitive complications (45–47). Hence, our intervention could be used for support in the prevention of short- and long-term complications among adolescents with suboptimal glycaemic control.
Our results show no significant differences in other glycaemic control metrics during the 1-year study period between the two study groups. These findings are supported by a study conducted in Spain on the impact of telemedicine on metabolic control among adults with T1D having suboptimal glycaemic control which showed that telemedicine intervention had no significant difference as compared with face-to-face visits (48). In contrast to our findings and those of the study mentioned above, a study done by Alharthi et al. (49) among adults with T1D revealed that telemedicine visits resulted in a significant improvement in all glycaemic control metrics, as compared with usual care. Similarly, other retrospective observational studies assessing the effect of telemedicine among different age groups with T1D have revealed that telemedicine visits result in significant improvement in all glycaemic control metrics. (50–52). These studies enrolled participants who used a data-sharing platform and actively shared their blood glucose information with the diabetes clinic. During telemedicine consultations, the diabetes team evaluated the blood glucose information and provided advice to the patient (50–52).
The above-mentioned studies (49–52) have shown that the use of telemedicine consultation may have contributed to improved glycaemic control. This might be due to the accessibility and user-friendliness of technology-based interventions for adolescents. Our study involved a unique eHealth intervention that included the use of real-time CGM ( rt-CGM) data to support adolescents based on their need for support, as well as the involvement of a diabetes nurse to support the adolescents in making informed decisions and actively participating in self-management activities. However, only % TAR showed a significant change while the other glycaemic control metric did not show a significant difference. This might be due to the small sample size of our study.
In this study, we also investigated the effect of the eHealth care programme on adolescent empowerment. Our results revealed, a significant effect of the eHealth care programme on adolescent empowerment. This might be a result of the involvement of a diabetes nurse in our intervention, who understood the developmental changes of the adolescents, explore their emotions, and boosts their motivation to address their difficulties and engage in self-management. This has been supported by a study done by James (53), which showed that due to their expertise and experience, involving diabetic nurses in the care empowered patients to manage their own health. Similarly, other studies have revealed that diabetes nurse involvement, nurse-aided web-based intervention, and telenursing empowerment intervention programme can play vital roles in empowering patients to manage their health and significantly increase patients’ self-efficacy (54–56).
Our intervention was an individualized care programme provided based on the need of the adolescents. Shared decisions made between the diabetes nurse and the adolescent regarding the need for support to reach the goal might also contribute to the observed empowerment. A study conducted by Fraenkel (57) revealed that including patients’ preferences in care enable them to choose the type of support they needed and set their own goals to achieve the desired outcome.
Our intervention promotes adolescents’ involvement and active participation in the care which may have contributed to the observed improvement in empowerment scores. A study conducted by Anderson and Funnell (58) showed that individuals’ active participation in their diabetes care enabled them to be more autonomous and make informed decisions.
Moreover, the use of technology in our study may have contributed to the observed improvement in the adolescents’ empowerment scores. This could be that technology-based interventions increase the accessibility and availability of evidence-based services and support the self-management behaviours of adolescents, which has been reported in a study done by Blake et al. (59). Similarly, other evidence has shown that technology-based (i.e., telemedicine) intervention programmes significantly increase diabetes self-efficacy and adolescents’ ability to interact with each other (60, 61). In contrast, other studies have indicated that technology-based intervention had no significant effect on participants’ empowerment. Studies carried out by Kirwan et al. (42) and Markowitz et.al (62) revealed that technology-based text-message intervention had no significant effect on participants’ empowerment scores. Some of the above-mentioned interventions included theory-based content and were delivered via text message or online follow-up. The duration of the intervention and the characteristics of the study participants could explain the disparity in the effects of the interventions.
Strength Of The Study
In Sweden, healthcare is accessible to all adolescents and is (almost) free; thus, our intervention was open to all adolescents who met the inclusion criteria. The study participants were included regardless of sex and ethnicity and the study was conducted for a relatively longer time under real-life conditions. Our intervention used the CGM cloud platform, which provides remote access to blood glucose values in real-time. Moreover, we followed strict inclusion criteria, and only adolescents using specific real-time CGM (Dexcom G6 and flash glucose monitoring) systems were included in the study to avoid discrepancies in values between different sensor types. Our intervention provided individualized care, ensuring that the intervention received by each adolescent was relevant to his/her health condition. The findings of this study can be used as a baseline for further eHealth programmatic intervention development. However, our study does have limitations: the small sample size which might underpower the study to detect differences between the two care programmes and lack of random assignment to each group might also another limitation of the study.