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IntroductionThe prevalence of non-adherence to antidiabetic treatment remains high despite various efforts. Thus, the positive effects of the antidiabetic treatment cannot be optimised and th

Using AI to Interpret Medical Images The authors examine the advantages and limitations of current clinical radiologic AI systems, new clinical workflows, and the potential effect of generative A

Anxiety and depressive symptoms are prevalent in the elderly and lead to loss of functionality and increased mortality.

Telemedicine interventions can be an alternative for the treatment o

The COVID-19 pandemic necessitated remote cancer care delivery via the internet and telephone, rapidly accelerating an already growing care delivery m…

Background: The use of digital technologies within health care rapidly increased as services transferred to web-based platforms during the COVID-19 pandemic. Inequalities in digital health across the domains of equity are not routinely examined; yet, the long-term integration of digitally delivered services needs to consider such inequalities to ensure equitable benefits.
Objective: This scoping review aimed to map inequities in access, use, and engagement with digital health technologies across equity domains.
Methods: We searched 4 electronic databases (MEDLINE, ASSIA, PsycINFO, and Scopus) for quantitative and mixed methods reviews and meta-analyses published between January 2016 and May 2022. Reviews were limited to those that included studies from the World Health Organization’s European region. Extracted data were mapped against Cochrane’s PROGRESS PLUS (place of residence, race, ethnicity, culture, and language, occupation, gender and sex, religion, education, socioeconomic status, social capital, and other characteristics) dimensions of equity.
Results: In total, 404 unique citations were identified from the searches, and 2 citations were identified from other sources. After eligibility assessment, 22 reviews were included. Consistent evidence was found showing higher access to digital health technologies among patients who were of White ethnicity, were English speaking, and had no disability. There were no reviews that explored differences in access to digital health care by age, gender and sex, occupation, education, or homeless or substance misuse. Higher use of digital health technologies was observed among populations that were White, English speaking, younger, with a higher level of education, of higher economic status, and residents in urban areas. No clear evidence of differences in the use of digital technologies by occupation, gender and sex, disability, or homeless or substance misuse was found, nor was clear evidence found in the included reviews on inequalities in the engagement with digital technologies. Finally, no reviews were identified that explored differences by place of residence.
Conclusions: Despite awareness of the potential impact of inequalities in digital health, there are important evidence gaps across multiple equity domains. The development of a common framework for evaluating digital health equity in new health initiatives and consistency in reporting findings is needed.

Background: Long-term daily health monitoring and management play a more significant role in telehealth management systems nowadays, which require evaluation indicators to present patients’ general health conditions and become applicable to multiple chronic diseases.
Objective: This study aims to evaluate the effectiveness of subjective indicators of telehealth chronic disease management system (TCDMS).
Methods: We selected Web of Science, ScienceDirect, Scopus, Cochrane library, IEEE, and Chinese National Knowledge Infrastructure and Wanfang, a Chinese medical database, and searched papers published from January 1, 2015, to July 1, 2022, regarding randomized controlled trials on the effectiveness of the telehealth system on patients with chronic diseases. The narrative review summarized the questionnaire indicators presented in the selected studies. In the meta-analysis, Mean Difference (MD) and Standardized Mean Difference (SMD) with a 95% CI were pooled depending on whether the measurements were the same. Subgroup analysis was conducted if the heterogeneity was significant, and the number of studies was sufficient.
Results: Twenty RCTs with 4153 patients were included in the qualitative review. Seventeen different questionnaire-based outcomes were found, within which quality of life, psychological well-being (including depression, anxiety, and fatigue), self-management, self-efficacy, and medical adherence were most frequently used. Ten RCTs with 2095 patients remained in meta-analysis. Compared to usual care, telehealth system can significantly improve the quality of life (SMD 0.44; 95% CI 0.16-0.73; P=.002), whereas no significant effects were found on depression (SMD −0.25; 95% CI −0.72 to 0.23; P=.30), anxiety (SMD −0.10; 95% CI −0.27 to 0.07; P=.71), fatigue (SMD −0.36; 95% CI −1.06 to 0.34; P<.001), and self-care (SMD 0.77; 95% CI −0.28-1.81; P<.001). In the subdomains of quality of life, telehealth statistically significantly improved physical functioning (SMD 0.15; 95% CI 0.02 to 0.29; P=.03), mental functioning (SMD 0.37; 95% CI 0.13-0.60; P=.002), and social functioning (SMD 0.64; 95% CI 0.00-1.29; P=.05), while there was no difference on cognitive functioning (MD 8.31; 95% CI −7.33 to 23.95; P=.30) and role functioning (MD 5.30; 95% CI −7.80 to 18.39; P=.43).
Conclusions: TCDMS positively affected patients’ physical, mental, and social quality of life across multiple chronic diseases. However, no significant difference was found in depression, anxiety, fatigue, and self-care. Subjective questionnaires had the potential ability to evaluate the effectiveness of long-term telehealth monitoring and management. However, further well-designed experiments are warranted to validate TCDMS’s effects on subjective outcomes, especially when tested among different chronically ill groups.

Background: Rapid proliferation of mental health interventions delivered through conversational agents (CAs) calls for high-quality evidence to support their implementation and adoption. Selecting appropriate outcomes, instruments for measuring outcomes, and assessment methods are crucial for ensuring that interventions are evaluated effectively and with a high level of quality.
Objective: We aimed to identify the types of outcomes, outcome measurement instruments, and assessment methods used to assess the clinical, user experience, and technical outcomes in studies that evaluated the effectiveness of CA interventions for mental health.
Conclusions: The diversity of outcomes and the choice of outcome measurement instruments employed in studies on CAs for mental health point to the need for an established minimum core outcome set and greater use of validated instruments. Future studies should also capitalize on the affordances made available by CAs and smartphones to streamline the evaluation and reduce participants’ input burden inherent to self-reporting.

The objective of the study is to identify challenges and associated factors for privacy and security related to telehealth visits during the COVID-19 pandemic. The systematic search strategy used the databases of PubMed, ScienceDirect, ProQuest, Embase

Background: Health systems globally need to rapidly set and achieve targets for reaching net zero carbon emissions. Virtual consulting (including video- and telephone-based consulting) is regarded as one means by which this might be achieved, largely through reduced patient travel. Little is currently known about the ways in which forms of virtual consulting might contribute to the net zero agenda or how countries may develop and implement programs at scale that can support increased environmental sustainability.
Objective: In this paper, we asked, What is the impact of virtual consulting on environmental sustainability in health care? and What can we learn from current evaluations that can inform future reductions in carbon emissions?
Methods: We conducted a systematic review of published literature according to PRISMA (Preferred Reporting Item for Systematic Reviews and Meta-Analyses) guidelines. We searched the MEDLINE, PubMed, and Scopus databases using key terms relating to “carbon footprint,” “environmental impact,” “telemedicine,” and “remote consulting,” using citation tracking to identify additional articles. The articles were screened, and full texts that met the inclusion criteria were obtained. Data on the approach to carbon footprinting reported reductions in emissions, and the opportunities and challenges associated with the environmental sustainability of virtual consultations were extracted into a spreadsheet, analyzed thematically, and theorized using the Planning and Evaluating Remote Consultation Services framework to consider the various interacting influences, including environmental sustainability, that shape the adoption of virtual consulting services.
Results: A total of 1672 papers were identified. After removing duplicates and screening for eligibility, 23 papers that focused on a range of virtual consulting equipment and platforms across different clinical conditions and services were included. The focus on the environmental sustainability potential of virtual consulting was unanimously reported through carbon savings achieved by a reduction in travel related to face-to-face appointments. The shortlisted papers used a range of methods and assumptions to determine carbon savings, reporting these using different units and across varied sample sizes. This limited the potential for comparison. Despite methodological inconsistencies, all papers concluded that virtual consulting significantly reduced carbon emissions. However, there was limited consideration of wider factors (eg, patient suitability, clinical indication, and organizational infrastructure) influencing the adoption, use, and spread of virtual consultations and the carbon footprint of the entire clinical pathway in which the virtual consultation was provided (eg, risk of missed diagnoses from virtual consultations that result in the need for subsequent in-person consultations or admissions).
Conclusions: There is overwhelming evidence that virtual consulting can reduce health care carbon emissions, largely through reducing travel related to in-person appointments. However, the current evidence fails to look at system factors associated with implementing virtual health care delivery and wider research into carbon emissions across the entire clinical pathway.
Trial Registration:

Background: The prevalence of mental health problems in children and adolescents is high. As these problems can impact this population’s developmental trajectories, they constitute a public health concern. This situation is accentuated by the fact that children and adolescents infrequently seek help. Digital health interventions (DHIs) offer an opportunity to bridge the treatment gap between health care needs and patient engagement in care. Additional detailed research is needed to identify how children and adolescents can be empowered to access help through DHIs. In this context, an understanding of their attitudes toward digital health appears to be a necessary first step in facilitating the effective implementation of DHIs.
Objective: This study aimed to establish an inventory of children’s, adolescents’, and their parents’ attitudes toward DHIs.
Methods: A scoping review following PRISMA-ScR (Preferred Reporting Items for Systematic reviews and Meta-Analyses extension for Scoping Reviews) recommendations was performed using the MEDLINE, Embase, and PsycINFO databases. This research was conducted using 3 key concepts: “child and adolescent mental health service users,” “digital health interventions,” and “attitudes.” Data extracted included the name of the publishing journal, the methodology used, the target population, the DHI studied, and the principal results.
Results: Of 1548 studies found, 30 (1.94%) were included in our analysis. Among these, 13 concerned satisfaction, 24 concerned preferences, 22 concerned the use of DHI, 11 concerned perception, and 10 concerned needs.
Conclusions: The results of this study provide a better understanding of the factors influencing children’s and adolescents’ attitudes toward digital health and DHIs. The continued growth of DHIs can help reduce barriers to mental health care. Future research on these interventions should investigate the needs of the targeted populations to increase their engagement in care.

Background: Mental health problems are a crucial global public health concern. Owing to their cost-effectiveness and accessibility, conversational agent interventions (CAIs) are promising in the field of mental health care.
Objective: This study aims to present a thorough summary of the traits of CAIs available for a range of mental health problems, find evidence of efficacy, and analyze the statistically significant moderators of efficacy via a meta-analysis of randomized controlled trial.
Methods: Web-based databases (Embase, MEDLINE, PsycINFO, CINAHL, Web of Science, and Cochrane) were systematically searched dated from the establishment of the database to October 30, 2021, and updated to May 1, 2022. Randomized controlled trials comparing CAIs with any other type of control condition in improving depressive symptoms, generalized anxiety symptoms, specific anxiety symptoms, quality of life or well-being, general distress, stress, mental disorder symptoms, psychosomatic disease symptoms, and positive and negative affect were considered eligible. This study followed the PRISMA (Preferred Reporting Items for Systematic Reviews and Meta-Analyses) guidelines. Data were extracted by 2 independent reviewers, checked by a third reviewer, and pooled using both random effect models and fixed effects models. Hedges g was chosen as the effect size.
Results: Of the 6900 identified records, a total of 32 studies were included, involving 6089 participants. CAIs showed statistically significant short-term effects compared with control conditions in improving depressive symptoms (g=0.29, 95% CI 0.20-0.38), generalized anxiety symptoms (g=0.29, 95% CI 0.21-0.36), specific anxiety symptoms (g=0.47, 95% CI 0.07-0.86), quality of life or well-being (g=0.27, 95% CI 0.16-0.39), general distress (g=0.33, 95% CI 0.20-0.45), stress (g=0.24, 95% CI 0.08-0.41), mental disorder symptoms (g=0.36, 95% CI 0.17-0.54), psychosomatic disease symptoms (g=0.62, 95% CI 0.14-1.11), and negative affect (g=0.28, 95% CI 0.05-0.51). However, the long-term effects of CAIs for the most mental health outcomes were not statistically significant (g=−0.04 to 0.39). Personalization and empathic response were 2 critical facilitators of efficacy. The longer duration of interaction with conversational agents was associated with the larger pooled effect sizes.
Conclusions: The findings show that CAIs are research-proven interventions that ought to be implemented more widely in mental health care. CAIs are effective and easily acceptable for those with mental health problems. The clinical application of this novel digital technology will conserve human health resources and optimize the allocation of mental health services.
Trial Registration: PROSPERO CRD42022350130; https://tinyurl.com/mvhk6w9p