Background: There is growing evidence that apps and digital interventions have a positive impact on diabetes self-management. Standard self-management for patients with diabetes could therefore be supplemented by apps and digital interventions to increase patients’ skills. Several initiatives, models, and frameworks suggest how health apps and digital interventions could be evaluated, but there are few standards for this. And although there are many methods for evaluating apps and digital interventions, a more specific approach might be needed for assessing digital diabetes self-management interventions. Objective: This review aims to identify which methods and criteria are used to evaluate apps and digital interventions for diabetes self-management, and to describe how patients were involved in these evaluations. Methods: We searched CINAHL, EMBASE, MEDLINE, and Web of Science for articles published from 2015 that referred to the evaluation of apps and digital interventions for diabetes self-management and involved patients in the evaluation. We then conducted a narrative qualitative synthesis of the findings, structured around the included studies’ quality, methods of evaluation, and evaluation criteria. Results: Of 1681 articles identified, 31 fulfilled the inclusion criteria. A total of 7 articles were considered of high confidence in the evidence. Apps were the most commonly used platform for diabetes self-management (18/31, 58%), and type 2 diabetes (T2D) was the targeted health condition most studies focused on (12/31, 38%). Questionnaires, interviews, and user-group meetings were the most common methods of evaluation. Furthermore, the most evaluated criteria for apps and digital diabetes self-management interventions were cognitive impact, clinical impact, and usability. Feasibility and security and privacy were not evaluated by studies considered of high confidence in the evidence. Conclusions: There were few studies with high confidence in the evidence that involved patients in the evaluation of apps and digital interventions for diabetes self-management. Additional evaluation criteria, such as sustainability and interoperability, should be focused on more in future studies to provide a better understanding of the effects and potential of apps and digital interventions for diabetes self-management.

Background: Diabetes patient associations and diabetes-specific patient groups around the world are present on social media. Although active participation and engagement in these diabetes social media groups has been mostly linked to positive effects, very little is known about the content that is shared on these channels or the post features that engage their users the most. Objective: The objective of this study was to analyze (1) the content and features of posts shared over a 3-year period on 3 diabetes social media channels (Facebook, Twitter, and Instagram) of a diabetes association, and (2) users’ engagement with these posts (likes, comments, and shares). Methods: All social media posts published from the Norwegian Diabetes Association between January 1, 2017, and December 31, 2019, were extracted. Two independent reviewers classified the posts into 7 categories based on their content. The interrater reliability was calculated using Cohen kappa. Regression analyses were carried out to analyze the effects of content topic, social media channel, and post features on users’ engagement (likes, comments, and shares). Results: A total of 1449 messages were posted. Posts of interviews and personal stories received 111% more likes, 106% more comments, and 112% more shares than miscellaneous posts (all P<.001). Messages posted about awareness days and other celebrations were 41% more likely to receive likes than miscellaneous posts (P<.001). Conversely, posts on research and innovation received 31% less likes (P<.001), 35% less comments (P=.02), and 25% less shares (P=.03) than miscellaneous posts. Health education posts received 38% less comments (P=.003) but were shared 39% more than miscellaneous posts (P=.007). With regard to social media channel, Facebook and Instagram posts were both 35 times more likely than Twitter posts to receive likes, and 60 times and almost 10 times more likely to receive comments, respectively (P<.001). Compared to text-only posts, those with videos had 3 times greater chance of receiving likes, almost 4 times greater chance of receiving comments, and 2.5 times greater chance of being shared (all P<.001). Including both videos and emoji in posts increased the chances of receiving likes by almost 7 times (P<.001). Adding an emoji to posts increased their chances of receiving likes and being shared by 71% and 144%, respectively (P<.001). Conclusions: Diabetes social media users seem to be least engaged in posts with content topics that a priori could be linked to greater empowerment: research and innovation on diabetes, and health education. Diabetes social media groups, public health authorities, and other stakeholders interested in sharing research and innovation content and promoting health education on social media should consider including videos and emoji in their posts, and publish on popular and visual-based social media channels, such as Facebook and Instagram, to increase user engagement. International Registered Report Identifier (IRRID): RR2-10.1186/s12913-018-3178-7

Background: Artificial intelligence (AI) has the potential to enhance physical activity (PA) interventions. However, human factors (HFs) play a pivotal role in the successful integration of AI into mobile health (mHealth) solutions for promoting PA. Understanding and optimizing the interaction between individuals and AI-driven mHealth apps is essential for achieving the desired outcomes. Objective: This study aims to review and describe the current evidence on the HFs in AI-driven digital solutions for increasing PA. Methods: We conducted a scoping review by searching for publications containing terms related to PA, HFs, and AI in the titles and abstracts across 3 databases—PubMed, Embase, and IEEE Xplore—and Google Scholar. Studies were included if they were primary studies describing an AI-based solution aimed at increasing PA, and results from testing the solution were reported. Studies that did not meet these criteria were excluded. Additionally, we searched the references in the included articles for relevant research. The following data were extracted from included studies and incorporated into a qualitative synthesis: bibliographic information, study characteristics, population, intervention, comparison, outcomes, and AI-related information. The certainty of the evidence in the included studies was evaluated using GRADE (Grading of Recommendations Assessment, Development, and Evaluation). Results: A total of 15 studies published between 2015 and 2023 involving 899 participants aged approximately between 19 and 84 years, 60.7% (546/899) of whom were female participants, were included in this review. The interventions lasted between 2 and 26 weeks in the included studies. Recommender systems were the most commonly used AI technology in digital solutions for PA (10/15 studies), followed by conversational agents (4/15 studies). User acceptability and satisfaction were the HFs most frequently evaluated (5/15 studies each), followed by usability (4/15 studies). Regarding automated data collection for personalization and recommendation, most systems involved fitness trackers (5/15 studies). The certainty of the evidence analysis indicates moderate certainty of the effectiveness of AI-driven digital technologies in increasing PA (eg, number of steps, distance walked, or time spent on PA). Furthermore, AI-driven technology, particularly recommender systems, seems to positively influence changes in PA behavior, although with very low certainty evidence. Conclusions: Current research highlights the potential of AI-driven technologies to enhance PA, though the evidence remains limited. Longer-term studies are necessary to assess the sustained impact of AI-driven technologies on behavior change and habit formation. While AI-driven digital solutions for PA hold significant promise, further exploration into optimizing AI’s impact on PA and effectively integrating AI and HFs is crucial for broader benefits. Thus, the implications for innovation management involve conducting long-term studies, prioritizing diversity, ensuring research quality, focusing on user experience, and understanding the evolving role of AI in PA promotion.

Digital interventions for increasing physical activity behavior have shown great potential, especially those with social media. Chatbots, also known as conversational agents, have emerged in healthcare in relation to digital interventions and have proven effective in promoting physical activity among adults. The study’s objective is to explore users’ experiences with a social media chatbot. The concept and the prototype development of the social media chatbot MYA were realized in three steps: requirement analysis, concept development, and implementation. MYA’s design includes behavior change techniques effective in increasing physical activity through digital interventions. Participants in a usability study answered a survey with the Chatbot Usability Questionnaire (CUQ), which is comparable to the Systems Usability Scale. The mean CUQ score was below 68, the benchmark for average usability. The highest mean CUQ score was 64.5 for participants who thought MYA could help increase their physical activity behavior. The lowest mean CUQ score was 40.6 for participants aged between 50 and 69 years. Generally, MYA was considered to be welcoming, very easy to use, realistic, engaging, and informative. However, some technical issues were identified. A good and diversified user experience promotes prolonged chatbot use. Addressing identified issues will enhance users’ interaction with MYA.

The COVID-19 pandemic sent shock waves through societies, economies, and health systems of Member States in the WHO European Region and beyond. During the pandemic, most countries transitioned from a slow to a rapid adoption of telehealth solutions, to accommodate the public health and social measures introduced to mitigate the spread of the disease. As countries shift to a post-pandemic world, the question remains whether telehealth's importance as a mode of care provision in Europe continues to be significant. This paper aims to present, synthesize, and interpret results from the Telehealth Programmes section of the 2022 WHO Survey on Digital Health (2022 WHO/Europe DH Survey). We specifically analyze the implementation and use of teleradiology, telemedicine, and telepsychiatry. Norwegian telehealth experiences will be used to illustrate survey findings, and we discuss some of the relevant barriers and facilitators that impact the use of telehealth services. The survey tool was revised from the 2015 WHO Global Survey on eHealth, updated to reflect recent progress and policy priorities.The 2022 WHO/Europe DH Survey was conducted by WHO and circulated to Member States in its European Region from April to October 2022. The data analysis revealed that teleradiology, telemedicine, and telepsychiatry are the telehealth services most commonly used in the WHO European Region in 2022. Funding remains the most significant barrier to the implementation of telehealth in the Region, followed by infrastructure and capacity/human resources. The survey results highlighted in this study are presented in the following sections: (1) telehealth strategies and financing, (2) telehealth programmes and services offered by Member States of the WHO European Region, (3) barriers to implementing telehealth services, and (4) monitoring and evaluation of telehealth. Based on WHO's 2022 survey, the use of telehealth in the WHO European Region is on the rise. However, merely having telehealth in place is not sufficient for its successful and sustained use for care provision. Responses also uncovered regional differences and barriers that need to be overcome. Successful implementation and scaling of telehealth requires rethinking the design of health and social care systems to create robust, trustworthy, and person-centred digital health and care services.

Background: There is a need to deliver smoking cessation support at a population level, both in developed and developing countries. Studies on internet-based and mobile phone–based smoking cessation interventions have shown that these methods can be as effective as other methods of support, and they can have a wider reach at a lower cost. Objective: This randomized controlled trial (RCT) aimed to compare, on a population level, the efficacy of an identical, tailored smoking cessation intervention delivered by mobile text messaging versus email. Methods: We conducted a nationwide 2-arm, double-blinded, fully automated RCT, close to a real-world setting, in Norway. We did not offer incentives to increase participation and adherence or to decrease loss to follow-up. We recruited users of the website, slutta.no, an open, free, multi-component Norwegian internet-based smoking cessation program, from May 2010 until October 2012. Enrolled smokers were considered as having completed a time point regardless of their response status if it was 1, 3, 6, or 12 months post cessation. We assessed 7315 participants using the following inclusion criteria: knowledge of the Norwegian language, age 16 years or older, ownership of a Norwegian cell phone, having an email account, current cigarette smoker, willingness to set a cessation date within 14 days (mandatory), and completion of a baseline questionnaire for tailoring algorithms. Altogether, 6137 participants were eligible for the study and 4378 participants (71.33%) provided informed consent to participate in the smoking cessation trial. We calculated the response rates for participants at the completed 1, 3, 6, and 12 months post cessation. For each arm, we conducted an intention-to-treat (ITT) analysis for each completed time point. The main outcome was 7-day self-reported point prevalence abstinence (PPA) at the completed 6 months post cessation. We calculated effect size of the 7-day self-reported PPA in the text message arm compared with the email arm as odds ratios (ORs) with 95% CIs for the 4 time points post cessation. Results: At 6 months follow-up, 21.06% (384/1823) of participants in the text message arm and 18.62% (333/1788) in the email arm responded (P=.07) to the surveys. In the ITT analysis, 11.46% (209/1823) of participants in the text message arm compared with 10.96% (196/1788) in the email arm (OR 1.05, 95% CI 0.86-1.30) reported to have achieved 7 days PPA. Conclusions: This nationwide, double-blinded, large, fully automated RCT found that 1 in 9 enrolled smokers reported 7-day PPA in both arms, 6 months post cessation. Our study found that identical smoking cessation interventions delivered by mobile text messaging and email may be equally successful at a population level. Trial Registration: ClinicalTrials.gov NCT01103427; https://clinicaltrials.gov/ct2/show/NCT01103427