Background/Objectives: Dental erosion occurs due to repeated contact between the teeth and acidic substances along with mechanical stress. Athletes are exposed to acids through the consumption of sports drinks, energy drinks, and isotonic solutions; they also undergo mechanical stress during training and competition, making them prone to a higher prevalence of dental erosion. Therefore, our aim was to determine the erosive potential of beverages consumed by athletes. Methods: We conducted a systematic review of 1466 articles found on nine search engines between 1997 and 2021. We included observational studies and clinical trials in English, Portuguese, and Spanish on beverage consumption in athletes of both genders. Results: A total of four studies involving 567 athletes from four countries were identified. The prevalence of dental erosion ranged from 19.4% to 100%, and the severity assessments showed that between 52.4% and 75.2% of athletes had enamel affected, and 24% to 57.1% had both enamel and dentin affected. Only one study found that the consumption of sports drinks by swimmers practicing in chlorinated pools doubles the risk of developing dental erosion. Bias was low in half of the studies. Conclusions: The available evidence suggests that the consumption of sports drinks alone is not associated with dental erosion. However, to establish more conclusive evidence on the erosive potential of sports drinks, energy drinks, and isotonic solutions on the oral health of athletes, more prospective cohort studies are needed. These studies should include a standardization of indices and variables to which athletes are subjected, including dietary and healthcare habits, oral conditions, and protective factors. Furthermore, a larger number of athletes must be included to establish more conclusive evidence on the erosive potential of sports drinks, energy drinks, and isotonic solutions on athletes’ oral health.

Background: Older adults in rural or underserved settings face persistent access barriers. Digital and remote health interventions may mitigate these gaps. Objective: The aim of this study is to assess technologies, effectiveness, and implementation challenges of digital or remote health interventions for adults ≥60 years old in rural or underserved contexts. Methods: A systematic search was conducted in 4 electronic databases, such as PubMed, Scopus, Web of Science, and Embase (inception: April 2025), under dual screening by 2 reviewers. The tool Cochrane Risk of Bias 2.0 was used to assess the risk of bias for randomized trials, and Risk Of Bias In Non-randomized Studies–of Interventions (ROBINS-I) was used for nonrandomized trials. For observational studies, we used the National Institutes of Health quality assessment tool, and a narrative synthesis was performed. Results: Fourteen studies met the inclusion criteria (randomized and nonrandomized designs; median follow-up ~12 mo). Ten of 14 (71%) reported significant improvements in at least 1 clinical end point (eg, hemoglobin A _1c , blood pressure, and weight), 11 of 14 (79%) improved behavioral or psychosocial outcomes, and 5 of 9 (56%) reduced hospitalizations or acute episodes. Risk-of-bias concerns most frequently related to missing data and selective reporting. Digital literacy and broadband access were the most consistent barriers, while multicomponent, nurse-supported models achieved higher adherence. Equity-related dimensions (place, gender, and socioeconomic status) were variably reported, with limited attention to language, cultural tailoring, or social capital. No study included a formal cost-effectiveness analysis. Conclusions: Digital and remote health interventions can benefit older adults in rural and underserved settings by improving selected clinical and behavioral outcomes. However, heterogeneity, small sample sizes, and the absence of economic evaluations temper certainty. Importantly, gaps in equity reporting and persistent barriers to digital inclusion highlight the need for future trials to integrate PROGRESS-Plus (place of residence, race/ethnicity, occupation, gender, religion, education, socioeconomic status, social capital, plus other context-specific determinants of health equity) dimensions, embed cost-effectiveness assessments, and design interventions that are both sustainable and accessible to the most underserved populations.