JMIR Diabetes最新文献

Background: Inequity in diabetes technology use persists among Black and Hispanic youth with type 1 diabetes (T1D). Community health workers (CHWs) can address social and clinical barriers to diabetes device use. However, more information is needed on clinicians' perceptions to inform the development of a CHW model for youth with T1D.

Objective: This study aimed to identify barriers to diabetes technology use and cocreate solutions in collaboration with diabetes and school-based clinicians serving Black and Hispanic youth with T1D.

Methods: Using human-centered design, the study team conducted 2-hour web-based workshops with clinicians from a diabetes clinic or school-based clinics at a safety net hospital in the Bronx, New York. The workshops promoted active ideation of barriers and co-design of a CHW intervention prototype to address self-reported challenges. Workshops were analyzed using a qualitative inductive approach.

Results: A total of 17 participants completed the human-centered design workshops and surveys. Of these, 11 (65%) were clinicians from the diabetes clinic and 6 (35%) were school-based clinicians from elementary, middle, and high schools in the Bronx. A total of 4 workshops were conducted. The perceived diabetes device barriers for youth with T1D and their families by participants were general health-related social needs (HRSNs) and diabetes technology-specific HRSNs that interfered with technology uptake, such as housing and financial insecurity, as well as digital social needs; and difficulty navigating health care systems, insurance, and pharmacy benefits due to the high level of care coordination required by caregivers. In addition, the participants identified barriers that interfered with their ability to support youth with T1D with diabetes technology, such as limited support for using diabetes technology in school and lack of time and technology support to troubleshoot problems in diabetes clinics. Ways in which a CHW could help mitigate these barriers include (1) identifying and addressing HRSNs by directing patients to appropriate resources; (2) providing peer support for caregivers to navigate diabetes device logistics; (3) acting as a school liaison to improve communication and coordination between caregivers, schools, and diabetes clinicians; and (4) offering administrative support to offload the logistical burden of clinicians.

Conclusions: Important needs related to specialized technology support, enhanced care coordination, family-clinician communication, and administrative task shifting were identified by clinicians to inform a CHW model for youth with T1D. Continued co-design and pilot testing are needed to refine the model.

Background: A novel mobile health (mHealth) app "acT1ve," developed using a co-design model, provides real-time support during exercise for young people with type 1 diabetes (T1D).

Objective: This study aimed to demonstrate the noninferiority of acT1ve compared with "treatment as usual" with regard to hypoglycemic events.

Methods: Thirty-nine participants living with T1D (age: 17.2, SD 3.3 years; HbA1c: 64, SD 6.0 mmol/mol) completed a 12-week single-arm, pre-post noninferiority study with a follow-up qualitative component. During the intervention, continuous glucose monitoring (CGM) and physical activity were monitored while participants used acT1ve to manage exercise. CGM data were used to assess the number of hypoglycemic events (<3.9 mmol/L for ≥15 minutes) in each phase. Using a mixed effects negative binomial regression, the difference in the rates of hypoglycemia between the preapp and app-use phases was analyzed. Participants completed both a semistructured interview and the user Mobile Application Rating Scale (uMARS) questionnaire postintervention. All interviews were audio-recorded for transcription, and a deductive content analysis approach was used to analyze the participant interviews. The uMARS Likert scores for each subscale (engagement, functionality, esthetics, and information) were calculated and reported as medians with IQRs.

Results: The rates of hypoglycemia were similar for both the preapp and app-use phases (0.79 and 0.83 hypoglycemia events per day, respectively). The upper bound of the CI of the hypoglycemia rate ratio met the prespecified criteria for noninferiority (rate ratio=1.06; 95% CI 0.91-1.22). The uMARS analysis showed a high rating (≥4 out of 5) of acT1ve by 80% of participants for both functionality and information, 72% for esthetics, and 63% for overall uMARS rating. Content analysis of the interview transcripts identified 3 main themes: "Provision of information," "Exercising with the App," and "Targeted Population."

Conclusions: The mHealth app "acT1ve," which was developed in collaboration with young people with T1D, is functional, acceptable, and safe for diabetes management around exercise. The study supports the noninferiority of acT1ve compared with "treatment as usual" with regards to hypoglycemic events.

Background: Insulin therapy is crucial for type 2 diabetes mellitus management, with increasing usage in Indonesia, and its effectiveness is well-established. However, prescribing insulin poses various challenges that can impact the effectiveness of insulin. Patient education is crucial for the successful implementation of insulin therapy. Proper insulin use remains insufficient in Indonesia.

Objective: This study seeks to investigate physicians' knowledge and practice in providing education on insulin use to type 2 diabetes mellitus patients in Indonesia.

Methods: This study recruited potential participants (all physicians in Indonesia) through the Internet using a convenience sampling method. The participants were asked to fill out a questionnaire. The questionnaire had 32 questions divided into 4 sections, comprising demographics and clinical practice, practice of insulin education, Indonesian insulin injection technique guideline, and knowledge of insulin injection technique. The instrument used in this study was developed based on the Pedoman Teknik Menyuntik Insulin Indonesia (PTMII), which was adapted from the international consensus by the Forum for Injection Technique and Therapy Expert Recommendations (FITTER). The survey lasted from February to March 2021. Data was analysed using Kruskal-Wallis tests.

Results: A total of 823 participants were included in the analysis. A total of 680 out of 823 participants (82.6%) had given insulin education to patients at least once during the last 30 days. However, only 479 out of 823 participants (58.2%) used specific guidelines in their practice, with only 280 out of 823 participants (34.0%) aware of the Indonesian guidelines. Eight hundred and fifteen out of 823 participants (99.0%) agreed that insulin injection techniques would affect clinical results. The median score of knowledge about insulin injection techniques was 7 (interquartile range 2) among the study participants, indicating good knowledge. The profession was the only statistically significant variable associated with knowledge scores, with the highest median score held by consultants in endocrinology, metabolism & diabetes, and the lowest by other doctors (P <.001).

Conclusions: Most physicians in this study had given education to their patients. However, there was still a gap between the guidelines and the practice of insulin education, as shown by the lack of awareness and a fair level of knowledge about the Indonesian guidelines.

Clinicaltrial:

Background: Diabetes mellitus (DM) is a chronic condition requiring effective self-management to maintain glycemic control and prevent complications. Mobile health (mHealth) apps offer potential solutions by providing real-time monitoring, personalized feedback, and educational resources. However, their long-term adoption is hindered by a lack of user involvement in the development process and insufficient cultural adaptation. This study aims to explore the perspectives of patients with DM in Hong Kong on the functionalities and features of mHealth apps, highlighting the importance of tailoring these apps to meet local cultural needs.

Objective: The objective of this study is to understand the views of patients with DM on the development of mHealth apps and the demand for app functions in order to provide a basis for the development of DM prevention apps.

Methods: This descriptive qualitative study conducted semi-structured interviews with 10 patients with DM attending a District Health Centre in Hong Kong in May 2024, using a purposive sampling strategy. The transcribed data were analyzed by the inductive content analytical method, and themes were extracted with the aid of NVivo (version 15.0; QSR International) software.

Results: In total, 7 key themes were identified: accurate information resources, automatic tracking and monitoring of health metrics, reminders, personalized customization options, intuitive usability, efficient data-sharing capabilities, and interactive design. Additionally, the study emphasizes the importance of cultural adaptation and the potential of artificial intelligence-enabled mHealth apps to enhance personalized information delivery. Ensuring the credibility and professionalism of information sources is also essential.

Conclusions: The results provide valuable insights for enhancing the self-management capabilities of patients with DM and inform the future development of mHealth apps focused on DM prevention.

Background: Gestational diabetes mellitus (GDM), a type of blood glucose intolerance or hyperglycemia that occurs during pregnancy, is a common condition increasing in prevalence both globally and in Australia. Mobile health apps have been shown to be a useful resource for women with type 1 diabetes and could successfully contribute to GDM management by facilitating healthy behaviors.

Objective: This study aimed to seek the perspectives of health care consumers (HCCs) and health professionals (HPs) regarding the development of a smartphone app for women living with GDM.

Methods: A co-design process with 4 distinct phases underpinned the development of SugarMumma. Phase 1 involved a nonsystematic literature search followed by the creation of an app functions wish list. In phase 2, semistructured interviews with HCCs and HPs were undertaken and then thematically analyzed. In phase 3, a prototype was designed based on social cognitive theory and stakeholder recommendations. Agile project management methodology was used, followed by "user acceptance testing." During phase 4, a second round of individual interviews was undertaken with HCCs and HPs. The same qualitative methods outlined in phase 2 were used.

Results: In phase 2, individual and didactic interviews were undertaken with HCCs (n=2) and HPs (n=6). Two overarching themes encompassing recommendations for app development emerged: (1) functionality and (2) individualized care. SugarMumma was created in phase 3. Phase 4 involved a second round of individual interviews with HCCs (n=1) and HPs (n=5), resulting in the final theme (3) future directions.

Conclusions: With increasing numbers of people using smartphones, mobile health apps can help manage chronic conditions such as GDM. SugarMumma was designed following extensive stakeholder input. Good functionality, regular notifications, appealing visual aids, positive feedback, relevant dietary advice, and exporting information to HPs are important features to include.

Background: The utility of a nurse-led telemonitoring approach (NLTA) is yet to be firmly established in diabetes management.

Objective: This study aims to examine the effect of a 12-month proactive NLTA on metabolic and psychological health indices in individuals with diabetes during the COVID-19 pandemic, and to evaluate it as a new diabetes model of care.

Methods: The telemonitoring study group (TSG; n=91) comprised adults who had attended an Australian tertiary hospital diabetes center between January 2019 and March 2020. Telehealth surveillance contact with a diabetes nurse educator was subsequently maintained at approximately 3-month intervals over 12 months. Prospective surveillance measures included glycated hemoglobin A1c (HbA1c%), weight, adherence to healthy behaviors, and patient-reported outcomes of diabetes distress, anxiety, and depression using validated instruments. Metabolic changes were compared retrospectively with a comparison group who had not received telemonitoring contact during the study period (non-TSG; n=115).

Results: The average participant age was 57.2 (SD 15) years; 63% (129/206) were male, 48% (99/206) had type 1 diabetes, 50% (104/206) had type 2 diabetes, and the mean HbA1c% was 8.1% (SD 1.4%). At the end of the 12-month study, the relative percentage reduction in unadjusted HbA1c% for the TSG cohort was significantly greater than that observed in the non-TSG cohort (4% vs 1%; P=.04). Following adjustment for baseline HbA1c%, a significant improvement in HbA1c% was observed in the TSG (P=.048) but not in the non-TSG (P=.61). TSG participants were 40% less likely (odds ratio 0.6, 95% CI 0.5-0.7) to experience an unfavorable rise in HbA1c% compared to non-TSG participants, after adjusting for sex, age, prepandemic HbA1c%, ethnicity, diabetes type, and diabetes duration. The NLTA facilitated assessments of psychological risk, with elevated depression, anxiety and diabetes distress scores significantly increased in women and youth <30 years of age (P<.001). Increasing anxiety measures were observed in those with high baseline anxiety scores (P<.001).

Conclusions: A proactive diabetes NLTA is feasible with positive effects on glycemia and the potential to identify those at psychological risk for targeted intervention. In the context of increasing demand for diabetes-related resources, further study of an NLTA model of care is warranted.

Background: Pneumonia is the most common respiratory tract infection among patients with diabetes, affecting individuals across all age groups and sexes.

Objective: This study aims to examine demographic trends in mortality among patients diagnosed with both diabetes mellitus (DM) and pneumonia.

Methods: Deidentified death certificate data for DM- and pneumonia-related deaths in adults aged 25 years and older from 1999 to 2022 were obtained from the Centers for Disease Control and Prevention Wide-ranging Online Data for Epidemiologic Research (CDC WONDER) database. Age-adjusted mortality rates (AAMRs) per 1,000,000 population were calculated. The Joinpoint Regression Program was used to evaluate annual percentage changes (APCs) in mortality trends, with statistical significance set at P<.05. This study adhered to the STROBE (Strengthening the Reporting of Observational Studies in Epidemiology) guidelines for reporting.

Results: Between 1999 and 2022, a total of 425,777 deaths were recorded from DM and pneumonia. The overall AAMR declined significantly (P=.001) from 98.73 in 1999 to 49.17 in 2016 (APC -4.68), and then surged to 97.66 by 2022 (APC 23.55). Men consistently experienced higher mortality than women throughout the study period. Male AAMR rose from 62.61 in 2016 to 127.05 in 2022 (APC 24.88), while female AAMR increased from 41.05 in 2017 to 75.25 in 2022 (APC 27.60). Race-based analysis demonstrated that American Indian or Alaska Native populations had the highest mortality rates among racial groups. Non-Hispanic White individuals exhibited a significant decline in AAMR (P=.002) from 89.76 in 1999 to 44.19 in 2017 (APC -4.58), followed by an increase to 83.11 by 2022 (APC 25.25). Adults aged 65 years or older bore the highest mortality burden, with rates declining steadily to 206.9 in 2017 (APC -5.15) before rising sharply to 371.3 in 2022 (APC 20.01). Nonmetropolitan areas consistently exhibited higher mortality than metropolitan areas, with particularly steep increases after 2018 (APC 64.42). Type-specific mortality revealed that type 1 DM AAMRs declined from 9.2 in 1999 to 1.4 in 2015 (APC -11.94) before rising again. By contrast, type 2 DM AAMRs surged drastically after 2017, peaking at 62.2 in 2020 (APC 58.74) before partially declining to 41.6 by 2022.

Conclusions: DM is associated with an increased risk of mortality following pneumonia, particularly among men, older adults, and American Indian populations. Strengthening health care interventions and policies is essential to curb the rising mortality trend in these at-risk groups.

Background: Artificial intelligence (AI) chatbots have shown competency in a range of areas, including clinical note taking, diagnosis, research, and emotional support. An obesity epidemic, alongside a growth in novel injectable pharmacological solutions, has put a strain on limited resources.

Objective: This study aimed to investigate the use of a chatbot integrated with a digital avatar to create a "digital clinician." This was used to provide mandatory patient education for those beginning semaglutide once-weekly self-administered injections for the treatment of overweight and obesity at a national center.

Methods: A "digital clinician" with facial and vocal recognition technology was generated with a bespoke 10- to 15-minute clinician-validated tutorial. A feasibility randomized controlled noninferiority trial compared knowledge test scores, self-efficacy, consultation satisfaction, and trust levels between those using the AI-powered clinician avatar onsite and those receiving conventional semaglutide education from nursing staff. Attitudes were recorded immediately after the intervention and again at 2 weeks after the education session.

Results: A total of 43 participants were recruited, 27 to the intervention group and 16 to the control group. Patients in the "digital clinician" group were significantly more knowledgeable postconsultation (median 10, IQR 10-11 vs median 8, IQR 7-9.3; P<.001). Patients in the control group were more satisfied with their consultation (median 7, IQR 6-7 vs median 7, IQR 7-7; P<.001) and had more trust in their education provider (median 7, IQR 4.8-7 vs median 7, IQR 7-7; P<.001). There was no significant difference in reported levels of self-efficacy (P=.57). 81% (22/27) participants in the intervention group said they would use the resource in their own time.

Conclusions: Bespoke AI chatbots integrated with digital avatars to create a "digital clinician" may perform health care education in a clinical environment. They can ensure higher levels of knowledge transfer yet are not as trusted as their human counterparts. "Digital clinicians" may have the potential to aid the redistribution of resources, alleviating pressure on bariatric services and health care systems, the extent to which remains to be determined in future studies.