Background: Chronic low back pain (CLBP) is a leading cause of disability, impacting quality of life (QoL), function, and work productivity. Traditional rehabilitation faces challenges in accessibility and adherence. Remote rehabilitation and virtual reality (VR) interventions using motion sensors offer real-time movement tracking, biofeedback, and personalized exercises. This systematic review evaluates their effectiveness in pain reduction, functional improvement, adherence, and QoL. Methods: A systematic search was performed across PubMed, Scopus, Web of Science, and PEDro (2015–2025), including randomized controlled trials, observational, and feasibility studies on adults with CLBP undergoing sensor-based digital rehabilitation. The primary outcomes included pain, functional mobility, and movement biomechanics; secondary outcomes included adherence, QoL, and cost-effectiveness. Eight studies involving 7166 participants were included. Overall, sensor-based remote rehabilitation and VR interventions demonstrated positive effects on pain, function, and adherence. Pain reductions ranged from modest short-term decreases to over 60% in long-term programs (e.g., −68.5% in VAS). Functional improvements included lumbar ROM gains up to +9.9° and better movement control. Adherence was consistently high, with some programs reporting completion rates between 73% and 90%, particularly those incorporating gamification or real-time feedback. Selected studies also showed QoL improvements (e.g., +9.10 points on SF-36) and reductions in work impairment by over 60%. A few trials reported significant decreases in inflammatory markers (e.g., CRP −1.16 mg/L, TNF-α −8.9 pg/mL). Conclusions: Motion sensor-based remote rehabilitation and VR interventions show promising results in pain management, mobility, and adherence for individuals with CLBP. Gamification and biofeedback features enhance engagement, addressing a key challenge of conventional rehabilitation. However, more long-term RCTs and economic evaluations are needed to confirm their effectiveness and cost-efficiency.

Background: Prostate cancer is one of the most common malignancies in men and a leading cause of cancer-related mortality. Early detection is essential to ensure curative treatment and favorable outcomes, but traditional diagnostic approaches—such as serum prostate-specific antigen (PSA) testing, digital rectal examination (DRE), and histopathological confirmation following biopsy—are limited by suboptimal accuracy and variability. Multiparametric magnetic resonance imaging (mpMRI) has improved diagnostic performance but remains highly dependent on reader expertise. Artificial intelligence (AI) offers promising opportunities to enhance diagnostic accuracy, reproducibility, and efficiency in prostate cancer detection. Objective: To evaluate the diagnostic accuracy and reporting timeliness of AI-based technologies compared with conventional diagnostic methods in the early detection of prostate cancer. Methods: Following PRISMA 2020 guidelines, PubMed, Scopus, Web of Science, and Cochrane Library were searched for studies published between January 2015 and April 2025. Eligible designs included randomized controlled trials, cohort, case–control, and pilot studies applying AI-based technologies to early prostate cancer diagnosis. Data on AUC-ROC, sensitivity, specificity, predictive values, diagnostic odds ratio (DOR), and time-to-reporting were narratively synthesized due to heterogeneity. Risk of bias was assessed using the QUADAS-AI tool. Results: Twenty-three studies involving 23,270 patients were included. AI-based technologies achieved a median AUC-ROC of 0.88 (range 0.70–0.93), with median sensitivity and specificity of 0.86 and 0.83, respectively. Compared with radiologists, AI or AI-assisted readings improved or matched diagnostic accuracy, reduced inter-reader variability, and decreased reporting time by up to 56%. Conclusions: AI-based technologies show strong diagnostic performance in early prostate cancer detection. However, methodological heterogeneity and limited standardization restrict generalizability. Large-scale prospective trials are required to validate clinical integration.

Background: Smoking cessation has a crucial public health role. To overcome non-technological and technology-based smoking cessation intervention limitations, technology-supported programs were developed. Objectives: The present umbrella review aimed to evaluate the long-term effectiveness (≥6 months) of pharmacological vs. non-pharmacological technology-supported smoking cessation interventions on adult daily smokers and the related human health benefits. Methods: Following PRISMA guidelines, the protocol was registered on PROSPERO (CRD42024601824). Fifty systematic reviews were included, evaluated through AMSTAR-2, and qualitatively synthesized. Results: A total of 69,269 smokers underwent pharmacological (39,367) and non-pharmacological (29,902) technology-supported interventions. The biochemically-verified effectiveness assessed as continuous abstinence rates (CARs) and seven-day point prevalence abstinence (PPA) of pharmacological vs. non-pharmacological at 6 and 12 months were, respectively, CARs 9.06% vs. 14.85%, 7-day PPA 17.37% vs. 17.15%; CARs 8.51% vs. 9.08%, 7-day PPA 14.00% vs. 5.63%. The 6-month adherence rates were higher in the non-pharmacological group (41.37% vs. 83.43%). Conclusions: Non-pharmacological technology-supported interventions showed similar effectiveness and higher adherence at 6 months. At 12 months, the CARs were similar despite lower adherence. Adherence quality and consistency may be important for sustained success, probably due to the “reverse causality”. Non-pharmacological interventions showed similar effectiveness, lower costs, and shorter durations than pharmacological interventions.

Background: Non-communicable diseases (NCDs) represent a leading cause of global mortality, demanding innovative approaches to management. Voice assistants (VAs) have emerged as promising tools in healthcare, offering support for self-management, behavioral engagement, and patient care. This systematic review evaluates the role of VAs in NCD management, analyzing their impact on clinical and behavioral outcomes, quality of life, usability, and user experiences while identifying barriers to their adoption. Methods: A systematic search was conducted in PubMed, Scopus, and Web of Science from January 2014 to October 2024. Studies were selected based on predefined inclusion and exclusion criteria using the PRISMA guidelines. Data extraction focused on outcomes such as usability, acceptability, adherence, clinical metrics, and quality of life. The risk of bias was assessed using the Cochrane Risk of Bias (RoB) 2 and ROBINS-I tools. Results: Eight studies involving 541 participants were included, examining VAs across various NCD contexts such as diabetes, cardiovascular diseases, and mental health. While VAs demonstrated good usability and moderate adherence, their clinical and quality-of-life outcomes were modest. Behavioral improvements, such as increased physical activity and problem-solving skills, were noted in some interventions. Key challenges included privacy concerns, speech recognition errors, and accessibility issues. Conclusions: VAs show potential as supportive tools in NCD management, especially for enhancing patient engagement and self-management, and their impact on clinical outcomes and long-term usability requires further investigation. Future research should focus on diverse populations, standardized metrics, and comparative studies with alternative technologies.

Background/Objectives: Chronic Obstructive Pulmonary Disease (COPD) is frequently associated with dyspnea, impaired health-related quality of life (HRQoL), and cognitive dysfunction. Although pulmonary rehabilitation (PR) is considered a core therapeutic strategy, its specific effects on cognitive function, dyspnea, and dysphonia remain unclear. This systematic review aimed to evaluate the impact of PR and respiratory or cognitive-focused rehabilitative interventions on dyspnea, quality of life, cognitive performance, and voice outcomes in adults with COPD. Methods: This review was conducted in accordance with PRISMA 2020 guidelines and registered in PROSPERO (CRD420251131325). A systematic search of PubMed, Scopus and Web of Science identified studies published between 2010 and 21 August 2025. Eligible designs included randomized and non-randomized controlled studies, cohort, and mixed-method studies involving adults with COPD undergoing rehabilitative interventions targeting dyspnea, cognition, dysphonia, or swallowing. Outcomes included cognitive measures, dyspnea scales, voice parameters, and HRQoL indices. Results: Twelve studies (n ≈ 810 participants) met inclusion criteria. Most PR and exercise-based programs showed improvements in global cognition and executive functions, particularly when combined with cognitive training or high-intensity exercise modalities. Dyspnea improved consistently following short- to medium-term PR or respiratory muscle training, whereas low-frequency long-term programs yielded limited benefit. HRQoL improved across structured PR programs, especially in multidimensional interventions. Only one study assessed dysphonia, reporting transient improvements in maximum phonation time following inspiratory muscle training. No included study evaluated dysphagia-related outcomes. Conclusions: PR and respiratory muscle training can enhance cognition, dyspnea, and HRQoL in COPD, although evidence for dysphonia remains scarce and dysphagia is entirely unaddressed. Future high-quality trials should adopt standardized outcome measures, include long-term follow-up, and integrate voice and swallowing assessments within PR pathways.

Background: The World Health Organization defined specific recommendations about digital tobacco cessation modalities as a self-management tool or as an adjunct to other support for adults. Objectives: The present umbrella review primarily aimed to assess the long-term (≥6 months) effectiveness and adherence of the different standalone digital tobacco cessation modalities (mobile text messaging, smartphone apps, Internet-based websites and programs, AI-based), administered individually or in combination; secondarily, the study aimed to assess the effect on smokers’ health. Methods: The present study (PROSPERO number: CRD42024601824) followed the PRISMA guidelines. The included studies were qualitatively synthesized and evaluated through the AMSTAR-2 tool. Results: Forty-five systematic reviews were included, encompassing 164,010 adult daily smokers of combustible tobacco. At 6 months, highly interactive or human-centered digital tools showed higher effectiveness (biochemically verified continuous abstinence rates (CARs) were 11.48% for smartphone apps and 11.76% for video/telephone counseling). In contrast, at 12 months, simpler, less interactive tools demonstrated higher effectiveness (self-reported CARs was 24.38% for mobile text messaging and 18.98% for Internet-based). Adherence rates were generally high, particularly with human-centered digital tools, amounting to 94.12% at 6 months and 64.08% at 12 months. Compared with individually administered digital tobacco cessation modalities, at 12 months, combined ones registered slightly higher effectiveness (self-reported CARs were 13.12% vs. 13.94%) and adherence (62.36% vs. 63.70%), potentially attributed to the multi-component nature and longer durations. Conclusions: Clinicians should prioritize combined digital tobacco cessation interventions that incorporate human-centered engagement initially, alongside simpler, sustained digital support to enhance long-term effectiveness and adherence. Future research should explore long-term medical and oral health benefits to assess the impact on overall health and well-being.