Background: Recent meta-analyses suggest the use of technology-based interventions as a treatment option for obesity in adulthood. Similar meta-analytic approaches for children are scarce. Objective: The aim of this meta-analysis is to examine the effect of technology-based interventions on overweight and obesity treatment in children and adolescents. Methods: A systematic literature search was performed using MEDLINE (PubMed), Scopus, and Cochrane Library for randomized clinical trials to identify interventional studies published between January 2000 and February 2021. Results: In total, 9 manuscripts from 8 clinical trials of 582 children or adolescents were considered eligible. BMI, BMI z-score, and other BMI-related baseline metrics during and after intervention were considered as primary outcomes. In 7 of 8 studies, a technology-based intervention was applied in addition to conventional care. Of the 8 studies, 6 studies were conducted in the United States, 1 in Australia, and 1 in northwestern Europe. In total, 5 studies included adolescents, whereas the rest addressed children aged 9 to 12 years. Intervention duration ranged from 3 to 24 months. Significant differences between groups in BMI metric changes were reported by 5 of the 8 studies. Pooled analysis revealed an overall significant decrease in BMI metrics in the intervention group (standardized mean difference –0.61, 95% CI –1.10 to –0.13; P=.01). Subgroup analysis revealed that significance was lost in case of no parental involvement (standardized mean difference –0.36, 95% CI –0.83 to 0.11; P=.14). The small number of clinical trials found, the varying study quality, and the study heterogeneity are some limitations of this review. Conclusions: The studies reported herein describe functional and acceptable technology-based approaches, in addition to conventional treatments, to enhance weight loss in young populations.

Cardiovascular diseases (CVDs) remain a leading cause of global mortality and morbidity. Traditional risk prediction models, while foundational, often fail to capture the multifaceted nature of risk factors or leverage the expanding pool of healthcare data. Machine learning (ML) and artificial intelligence (AI) approaches represent a paradigm shift in risk prediction, offering dynamic, scalable solutions that integrate diverse data types. This review examines advancements in AI/ML for CVD risk prediction, analyzing their strengths, limitations, and the challenges associated with their clinical integration. Recommendations for standardization, validation, and future research directions are provided to unlock the potential of these technologies in transforming precision cardiovascular medicine.

It is well acknowledged that most of the modifiable risk factors for Cardiovascular Diseases (CVDs) can be averted through lifestyle modifications beyond medication adherence. This review aims to critically evaluate the cardiometabolic (CM) patient-related factors that influence the adherence to lifestyle changes studied alone and/or in combination with medication. A comprehensive literature search of PubMed articles from 2000 to 2023 retrieved 379 articles. After removing the articles which were not relevant, a total of 28 cross-sectional studies was chosen (12 qualitative, and 16 quantitative). The findings confirmed that five groups of factors influence patients’ adherence to overall treatment: (1) health beliefs, knowledge, and perceptions regarding the risks and challenges of disease and medication intake along with adherence process perceptions; (2) self-concept; (3) emotions; (4) patient–healthcare providers relationship/communication and (5) social and cultural interactions. It is worth mentioning that cultural issues, such as culinary particularities, ethnic identity, social life as well as patients’ skills and abilities, play a profound role in the effectiveness of the recommended lifestyle modifications beyond the aforementioned common factors. The need for clear-cut culturally adapted guidelines along with personalized advice from physicians is imperative as it could improve patients’ self-efficacy. These socio-psychological factors should be seriously considered as a means to increase the effectiveness of future community prevention programs.

(1) Background: Cardiometabolic disease progression can be delayed if patients engage in healthy lifestyle behaviors, adherence to which is highly influenced by psychosocial factors. The present study aimed at investigating the association of self-efficacy with the adherence level to healthy lifestyle behaviors among patients with cardiometabolic diseases in Greece. (2) Methods: 1988 patients (1180 females) with cardiometabolic diseases participated. Anthropometric, demographic, socioeconomic, clinical, and lifestyle characteristics were recorded. Patients were also asked to evaluate their efficacy to comply with healthy lifestyle behaviors. (3) Results: The majority exhibited unhealthy lifestyle behaviors. A subgroup demonstrated elevated self-efficacy in maintaining healthy habits despite facing diverse psychosocial challenges. Individuals with higher educational attainment, socioeconomic status, and rural/semi-urban residency had significantly elevated self-efficacy. Those with heightened self-efficacy exhibited significantly lower BMI and reduced prevalence of certain health conditions. Self-efficacy significantly influenced adherence to the Mediterranean diet, physical activity engagement, and smoking cessation, even in challenging circumstances. (4) Conclusions: This study represented an innovative approach in examining the role of self-efficacy in shaping health behaviors and outcomes within a Greek population. By integrating specific psychosocial circumstances into the analysis, valuable insights were provided into the contextual factors influencing self-efficacy and adherence to healthy lifestyle behaviors.

This study aimed to evaluate the association between adherence to the Mediterranean diet and the 20-year incidence of type II diabetes mellitus (T2DM) among adults from the ATTICA study. This study involved a prospective cohort of 3042 men and women recruited at baseline from the Attica region in Greece. Sociodemographic, anthropometric, lifestyle, and clinical characteristics were evaluated at baseline and follow-up examinations; adherence to the Mediterranean diet was assessed through the MedDietScore (range 0–55); four Mediterranean diet trajectories were identified (i.e., increasing, decreasing, and sustained high and sustained low adherence levels). For the present analysis, data from 2000 individuals with complete information were used (age 43 ± 13 years; 49% men). Over the 20-year period, 26.3% (95%CI 24.4%, 28.3%) of participants developed T2DM; men exhibited a 1.5-times higher incidence compared to women (p < 0.001). Individuals consistently close to the Mediterranean diet throughout the studied period had an improved glycemic and lipidemic profile (at baseline and at 10-y follow-up) (all p-values < 0.001) and showed a 21% reduction in their 20-year risk of developing T2DM compared to those who were consistently away (RR = 0.79, 95%CI 0.47, 0.86). A long-term adherence to the Mediterranean diet is protective against the onset of T2DM and, therefore, could be incorporated in public health actions for the prevention of the disease.