Search Results (1,040)

Background/Objectives: Physical activity and sedentary behaviour are important components of adolescent lifestyle, but favourable movement behaviour may not correspond to favourable behaviours across other health-related domains. This study aimed to identify empirical physical activity–sedentary behaviour profiles among adolescents and examine their co-occurring dietary, sleep, digital, and general health behaviours. Methods: This cross-sectional, school-based study used data from 3307 Polish adolescents aged 15–17 years. Following final processing of the International Physical Activity Questionnaire–Long Form, 1932 participants had complete and analytically eligible data for sedentary time, walking, moderate-intensity physical activity, and vigorous-intensity physical activity and were included in profile derivation. The four variables were Z-standardised before k-means clustering. Solutions from k = 2 to k = 6 were evaluated using the silhouette coefficient, Calinski–Harabasz index, Davies–Bouldin index, and Adjusted Rand Index (ARI). Co-occurring behaviours were compared using chi-square and Mann–Whitney U tests with effect-size estimates. Results: Cluster assignments were almost identical across repeated k-means runs initiated from different random starting centroids (ARI = 0.999). Because all runs were performed on the same set of participants, this result reflects low dependence on the initial centroid configuration rather than robustness to changes in sample composition. Separation between the two groups was limited (silhouette coefficient = 0.294), while the correspondence between classifications obtained from unstandardised and Z-standardised variables was minimal (ARI = 0.008), demonstrating a strong influence of scaling on cluster membership. The final classification included 1070 adolescents (55.4%) in the Higher Physical Activity profile and 862 (44.6%) in the Lower Physical Activity profile. The profiles showed no clear differences in school-day sleep duration, television/computer use, or internet-related risk. Weekend sleep duration differed between profiles (V = 0.120, p = 0.001). The Higher Physical Activity profile had higher Pro-Healthy Diet Index (r = 0.100, p < 0.001) and Non-Healthy Diet Index scores (r = 0.090, p < 0.001), slightly higher energy-drink intake (r = 0.080, p = 0.001), and more frequent out-of-home meal consumption (V = 0.079, p = 0.002). Effect sizes for co-occurring behaviours were generally small. Conclusions: Empirically distinct movement-behaviour profiles showed only partial correspondence with broader lifestyle characteristics. Higher physical activity coexisted with both more and less favourable dietary characteristics, whereas the Lower Physical Activity profile did not show a consistently adverse sleep or digital-behaviour pattern. These findings indicate that physical activity level alone should not be treated as a proxy for overall adolescent lifestyle quality. Given the exploratory, cross-sectional design and method-dependent nature of the profiles, the findings should be interpreted as hypothesis-generating rather than as evidence for fixed lifestyle types or profile-specific interventions. Full article

Introduction: Rapid technological development requires continuous learning and adaptation, yet many older adults (OAs) face difficulties using digital technologies. The AGAPE project (Active aGeing And Personalised service Ecosystem) aimed to promote active and healthy ageing (AHA) among adults aged 65+ by supporting independent functioning reducing caregiver burden, and improving eHealth literacy through personalized, user-friendly digital services co-created and tested in Italy, Portugal, and Romania. Objective: AGAPE pilot phase evaluated the effectiveness and usability of innovation adoption strategies designed to improve technology acceptance, digital literacy, and behavioural change among older adults and caregivers. This study examined participants’ perceptions of digital technologies and self-reported digital efficacy during a multicomponent intervention combining repeated technology use, personalized coaching, digital literacy and health education, technical assistance, and support from informal and formal caregivers. Material and Methods: The multiple-sites uncontrolled pilot study combined home-based use of the AGAPE digital technologies with long-term combined personalized support. Data were collected at baseline (T0), intermediate (T1), and final (T2) assessments using the System Usability Scale (SUS), technostress questionnaire, digital adoption questionnaire (TAM-derived), EQ-5D-5L, CarerQoL-7D, and the UCLA Loneliness Scale, complemented by participant feedback, technology usage, and activity data. Results: The study included 217 participants, of whom 146 were OAs. Over the course of the intervention, participants showed reductions in technostress and improvements in perceived digital efficacy, although the magnitude and direction of change varied across pilot sites. The findings also indicated that contextual and social factors contributed to technology adoption and engagement. Conclusions: Participation in the multicomponent AGAPE intervention was associated with positive longitudinal changes in technology-related perceptions, technostress, and digital self-efficacy. The findings support the feasibility and potential of combining digital technologies with personalized coaching and broader interpersonal support to facilitate technology adoption among older adults. However, given the uncontrolled study design and the integrated nature of the intervention, the observed changes cannot be attributed independently to coaching or to any single intervention component. Full article

Individuals with post-stroke hemiplegia may experience difficulty performing independent nail care because conventional nail clippers require bilateral hand function, grip strength, and fine motor control. Despite its relevance to personal hygiene and independence, nail care remains underexplored in rehabilitation engineering. The aim of this study was to design and develop a user-centered electric nail clipper for individuals with post-stroke hemiplegia and evaluate the preliminary functional suitability of the finalized prototype under supervised conditions. A sequential mixed-methods, user-centered device-development study was conducted following ISO 9241-210 principles. Phase I involved 10 healthy volunteers who participated in semi-structured interviews and controlled prototype testing to identify preliminary operational, ergonomic, and safety considerations. Stroke-specific functional requirements were additionally informed by the clinical context, relevant literature, and subsequent evaluation in the intended user population. These inputs were translated into engineering requirements and four iterative prototype configurations, which were independently evaluated by a five-member multidisciplinary expert panel. In Phase II, the finalized prototype underwent supervised participant-based evaluation in 20 individuals with post-stroke hemiplegia. These participants constituted the same cohort previously reported in a randomized controlled trial; previously published comparative clinical outcomes were not analyzed as new findings in the present study. Five principal functional considerations informed prototype development: one-handed stabilization, reduced operating effort, controlled nail reduction, operational safety, and practical device handling and debris management. The finalized design incorporated a stabilized triangular tabletop structure, silicone suction base, motor-driven rotary filing mechanism, adjustable operating speed, removable buffing head, debris-collection compartment, LED illumination, and rechargeable power. Prototype 4 received the highest overall expert rating (mean = 4.43, SD = 0.48) and was selected for participant-based evaluation. Under short-term supervised conditions, participants with post-stroke hemiplegia were able to perform one-handed nail care using the finalized prototype, with no device-related adverse events or malfunctions observed. The study demonstrates a structured user-centered pathway for translating functional and contextual requirements into an assistive nail-care device for individuals with post-stroke hemiplegia. The finalized prototype showed preliminary functional suitability during short-term supervised use; however, these findings do not establish comparative clinical effectiveness, long-term safety, or performance during unsupervised use. Larger, longitudinal, and home-based studies incorporating objective performance measures and validated user-reported instruments are warranted. Full article

Background/Objectives: The objective of this study was to test the accuracy of two sound-based voided volume measurement applications compared to voided volume based on the measurement of pre- and post-void weight using a high-resolution scale. Methods: Seven male and four female volunteers participated. Male and female volunteers used the proudP and Healthy Bladder-Voiding Diary mobile apps, respectively, to measure sound-based voided volume (SVV). The difference between pre- and post-void weight was calculated and converted to mL to be the true voided volume (TVV) using a high-resolution scale. Pearson correlation coefficients were calculated, and paired t-tests were completed. Results: Eighty-one voids were recorded (42M/39F). The median male participant age was 25 years. Male SVV ranged from 42 to 790 mL, and TVV ranged from 61 to 880 mL. The mean difference was 39 mL (95% CI, 18–59 mL). SVV and TVV comparison revealed a strong correlation (r = 0.977, p < 0.0001). Bland–Altman analysis revealed a mean bias of 39 mL. The median female participant age was 25 years. Female SVV ranged from 32 to 440 mL, and TVV ranged from 20 to 682 mL. The mean difference was 55 mL (95% CI, 23–88 mL). SVV and TVV comparison revealed a correlation (r = 0.882, p < 0.0001). Bland–Altman analysis demonstrated a mean bias of 55 mL. Conclusions: In this pilot study, we found that the male and female apps have a strong correlation to true voided volume (male > female app) and can be used by patients to track voided volume at home. The male app accurately measures voided volume within 60 mL from the TVV; however, the female app is less accurate. These preliminary findings warrant validation in larger prospective cohorts. Full article

Background: Exercise is a cornerstone of axial spondyloarthritis (axSpA) management, yet real-world adherence to physical activity (PA) recommendations and patient preferences for exercise delivery remain insufficiently characterized. This study aimed to compare PA levels, World Health Organization (WHO) aerobic PA guideline compliance, and exercise preferences between patients with axSpA and age and sex-matched healthy controls. Methods: A total of 153 patients with axSpA and 153 age- and sex-matched healthy controls were recruited from a tertiary rheumatology clinic. PA was assessed using the International Physical Activity Questionnaire-Short Form. Compliance with WHO aerobic PA recommendations was defined as achieving ≥150 min/week of moderate-intensity PA including walking, ≥75 min/week of vigorous-intensity PA, or an equivalent combination. Disease activity, function, quality of life, kinesiophobia, fibromyalgia, neuropathic pain, psychological status, and exercise preferences (adapted from the Personalized Exercise Questionnaire) were also recorded, and logistic regression identified factors associated with compliance among axSpA patients. Results: Total IPAQ-SF MET-min/week scores were comparable between groups, but vigorous-intensity activity was lower in axSpA (p = 0.012). Fewer patients with axSpA met WHO aerobic PA recommendations than controls (60.1% vs. 71.2%, p = 0.041) and this gap was most evident among women (43.4% vs. 75.5%, p = 0.002) but not among men, with a significant axSpA status × sex interaction (p = 0.008). Among patients with axSpA, female sex and higher kinesiophobia scores were independently associated with lower odds of meeting the WHO aerobic PA recommendations. Patients with axSpA also showed distinct exercise preferences including greater preference for health-professional supervision, home-based exercise, and regular feedback. Conclusions: Patients with axSpA had lower adherence to WHO aerobic PA recommendations than healthy controls. Among patients with axSpA, female sex and higher kinesiophobia were associated with lower adherence. These findings highlight the importance of considering sex-related differences, kinesiophobia, and individual exercise preferences when developing personalized strategies to promote PA in axSpA. Full article

Parkinson’s disease (PD) is associated with motor impairment and altered cortical dynamics. Although resting-state electroencephalography (EEG) has been widely studied for PD classification, walking EEG remains comparatively underexplored despite its relevance to gait dysfunction. This study developed an EEG-only, leakage-free framework for participant-level classification of PD and healthy controls (HCs) using resting- and walking-state EEG data from the OpenNeuro ds007526 dataset. Following selection, preprocessing, and quality control, 132 participants were retained, including 109 individuals with PD and 23 HCs. EEG recordings were resampled to 128 Hz, filtered between 0.5 and 40 Hz, screened for artifacts, harmonized across conditions, and segmented into overlapping 6 s windows. Classical machine-learning (ML) models used participant-level engineered features, whereas deep-learning (DL) models classified pooled resting-state and walking windows. Extra Trees achieved the highest balanced accuracy (0.71) among the ML, while ShallowConvNet-Lite was the strongest standard DL baseline (0.82). The proposed NeuroAtten-PD model achieved an accuracy of 0.86, a balanced accuracy of 0.84, an F1-score of 0.91, an ROC-AUC of 0.90, and a sensitivity of 0.88. After Holm correction, participant-level paired comparisons indicated significant differences from DeepConvNet-Lite and EEGNet-Lite. These findings demonstrate the feasibility of participant-level PD classification using a pooled collection of resting-state and walking EEG windows. With validation in larger, independent, and more balanced clinical cohorts, the proposed framework could support objective EEG-based decision support and provide a foundation for portable or wearable systems for longitudinal monitoring of PD-related cortical changes in clinical and home-based settings. Full article

Background: Human milk sodium (Na) concentration is a biomarker of lactation physiology and secretory activation, but conventional measurement methods are impractical for routine breastfeeding support. Portable Na analyzers may enable real-time home monitoring. Objective: The purpose of this study was to characterize longitudinal changes in human milk Na concentrations during the first 3 postpartum months and to evaluate the feasibility of longitudinal home Na monitoring throughout established lactation. Methods: Nine healthy lactating mothers intending to breastfeed were recruited at a breastfeeding management clinic in Tokyo, Japan, between August 2025 and December 2025. Participants performed home-based Na measurements from both breasts from birth through approximately 100 days postpartum, with the planned monitoring schedule defined as 90 postpartum days for adherence assessment. Each measurement required 2–3 drops of milk and was completed within 1 min. Longitudinal Na trajectories and Na elevation episodes were evaluated. Results: Na concentrations were highest immediately after birth and declined rapidly during the first postpartum week. Six of nine participants (66.7%) reached concentrations below 413.8 ppm within the first 7 postpartum days, and five of nine (55.6%) reached concentrations below 220 ppm by postpartum day 8. During established lactation, 62 breast-level Na elevation episodes were identified, with substantial interindividual variation in frequency and duration. Some episodes occurred without overt breast symptoms. Frequent home monitoring detected transient physiological fluctuations that would likely have been missed by conventional intermittent sampling. Conclusions: Longitudinal home milk Na monitoring was feasible in this small pilot cohort and enabled characterization of Na fluctuations from secretory activation through established lactation. These findings are preliminary and hypothesis-generating, and larger prospective studies are required to determine the clinical utility of longitudinal Na monitoring for breastfeeding assessment. Full article

Smartphone accelerometry could enable longitudinal home-based balance testing, yet its reliability across tasks and outcome measures must be established. We assessed the test–retest reliability and measurement precision of a custom smartphone balance application. Sixty-nine healthy, community-dwelling middle-aged and older adults (ages 41–76 years) performed a 5 s home-based balance assessment weekly for 3 weeks. The assessment was directed by the application, which generated accelerometer-based sway metrics. Participants performed two 30 s trials each of feet together and tandem stance (eyes open, eyes closed) and single leg stance (eyes open only). Intraclass correlation coefficients (ICCs) and relative standard error of measurement (SEM%) were calculated for time-domain and frequency-domain measures. Outcomes achieved good-to-excellent reliability when averaged across three weekly assessments (ICC = 0.59–0.95), particularly mediolaterally. Time-domain measures, particularly mean acceleration (ICC = 0.84–0.92; SEM% = 11.1–23.5%), were the most reliable and precise outcomes overall, while frequency-domain measures showed lower reliability and precision at higher spectral bands (ICC as low as 0.59; SEM% up to 41.5%). As standing tasks became more difficult, reliability and precision declined correspondingly. We conclude that minimally supervised, home-based balance assessment can produce reliable, precise sway measures in healthy, screened, iPhone-owning middle-aged and older adults. This application carries potential for large-scale, remote balance monitoring for research purposes, though validation in more diverse and higher-risk populations will be needed before clinical application can be recommended. Full article

Wrist accelerometers are widely used in clinical trials for continuous assessment of participants’ day-to-day physical activity and function, through derivation of metrics such as time spent in sedentary, non-sedentary, light, and moderate-to-vigorous physical activity (MVPA). Multiple algorithms have been proposed to derive these physical activity endpoints; however, the agreement across the endpoints derived from these algorithms has not been thoroughly explored. In this work, we leverage a publicly available dataset, CAPTURE-24, including wrist accelerometer data and experts’ annotations of various physical activities for 151 healthy adults, monitored at-home for one day, to compare three literature algorithms: Algorithm #1, SciKit Digital Health (SKDH), from Adamowicz et al., Algorithm #2 from Staudenmayer et al., and Algorithm #3 from Montoye et al. Algorithms’ outputs were assessed against experts’ annotations via paired t-tests, Pearson’s correlation (R), Bland–Altman analysis, accuracy, sensitivity, specificity, and F1-score. Algorithm #1 and Algorithm #2 showed stronger correlation and lower bias with experts’ annotations for time in sedentary (Algorithm #1: R = 0.91), and MVPA (Algorithm #1: R = 0.63), compared to Algorithm #3. In addition, Algorithm #1 and Algorithm #3 outperformed Algorithm #2 for time in light activity. Future work using longer monitoring periods and reference calorimetry devices should be performed to confirm the reproducibility of these findings. Full article

Tuberculosis (TB) remains one of the most burdensome infectious diseases in Indonesia. One contributing factor is the environment, particularly issues related to household ventilation and lighting. TB control efforts do not solely rely on medical interventions but also require a community-based approach that emphasizes active community involvement in preventing and controlling environmental risks to TB transmission. This study aims to analyze risk factors, distribution patterns, and their implications for environmentally based TB transmission risk control strategies. A mixed-methods design was conducted in two stages: first, risk factor analysis (with a case–control approach) and disease distribution pattern determination on environmental variables were performed, followed by a multidimensional scaling model (by using the Rapid Appraisal for Fisheries (RAPFISH) method) according to sustainability dimensions (ecological, economic, social, institutional, and technological) based on the resulting significant variables/indicators. This research was conducted in 2024, in four villages/nagari in West Sumatra of Indonesia. For quantitative analysis, data were collected through interviews, physical measurements of the environment, and determination of the coordinates of the residences of people with TB. Data were analyzed using bivariate and multivariate analyses. For the distribution pattern, Nearest Neighbor Analysis (NNA) in the ArcView program version 3.1 was used. Meanwhile, for qualitative data collection, focus group discussion (FGD) was performed. This study found that poor ventilation, minimal lighting, and a lack of stigma competency significantly increased the risk of TB transmission. Varied distribution patterns between regions demand adaptive and locally based strategies. The community-triggering approach is key to building community awareness and participation in creating a healthy and TB-free home environment. Full article

Parkinson’s disease (PD) diagnosis and severity assessment increasingly rely on gait analysis. To capture complex gait dynamics from limited sensor data, we propose a novel multi-branch framework integrating a one-dimensional convolutional neural network (1D-CNN), a bidirectional gated recurrent unit (Bi-GRU), and Kolmogorov–Arnold networks (KANs) (CNN-GRU-KAN) utilizing 18-channel vertical ground reaction force (VGRF) signals. Each module serves a distinct clinical purpose: the 1D-CNN branch with squeeze-and-excitation (SE) attention extracts localized spatial plantar pressure patterns, while the Bi-GRU branch with temporal attention captures long-range rhythm abnormalities. Crucially, the KAN serves as the classification head. By utilizing learnable B-spline functions instead of traditional fixed activations, KAN adaptively models the highly non-linear boundaries between healthy controls and varying PD severities, effectively mitigating overfitting. Under rigorous subject-independent cross-validation, our model achieves 98.43% accuracy for binary PD detection and 93.46% for five-class UPDRS severity grading. These results highlight the framework’s strong potential for low-cost, unobtrusive clinical tracking and home monitoring. Full article

Neurological disorders drive demand for prolonged upper-limb rehabilitation, yet specialist access is uneven and assessment stays subjective. Marker-based and inertial measurement unit (IMU) systems are accurate but costly and impractical at home, while pose estimation pipelines mostly stop at keypoints, and many process video server-side, raising privacy concerns. We present a markerless pipeline that analyzes monocular RGB video entirely on-device in the browser, so it never leaves the machine. From 33 BlazePose keypoints, it derives five geometric metrics designed to limit body-size dependence—incomplete elbow extension, inter-limb asymmetry, shoulder girdle elevation, lateral trunk lean, and head tilt—compared against empirically calibrated, preliminary thresholds; a finite-state machine segments repetitions, and the flags are pooled into an unvalidated, exploratory quality score. Against an IMU reference over the 0–${62}^{\circ }$ range that the recordings cover, the image-plane angle showed a mean absolute error of ${2.18}^{\circ }$, below the pre-specified $5^{\circ }$ tolerance, a trajectory-averaged bias within $\pm 2^{\circ }$, and Lin’s concordance correlation coefficient of $0.956$; the difference is, however, proportional to the angle—about $4\%$ of the measured value—so the accuracy should not be extrapolated to larger elevations, and because that comparison was made offline, it does not include the timing error of the causal real-time path. On a single seated frontal-plane abduction task, with 18 healthy volunteers simulating the compensations and annotated by two independent clinicians blind to the instructed condition, compensation detection reached a macro-averaged $F_1$ of $0.75$ and $0.72$ against the individual raters. The five signs differ in maturity: near-expert for trunk lean and head tilt, moderate for incomplete elbow extension and inter-limb asymmetry, and weakest for shoulder elevation, which a single frontal view cannot fully disentangle from the abduction motion. Running at 22–30 frames per second on consumer laptops without relying on a discrete GPU, it offers an accessible, privacy-preserving proof-of-concept foundation for home telerehabilitation; generalization beyond this one exercise and effectiveness on genuine post-stroke compensations remain to be established. Full article

Background: Ultra-processed food (UPF) consumption may be associated not only with nutrition knowledge but also with individuals’ practical food-related competencies and overall dietary patterns. Aim: This study investigated how cooking and food skills, dietary literacy, and adherence to the Mediterranean diet were related to UPF consumption among adults in İstanbul, Türkiye. Methods: This descriptive cross-sectional study included 293 (85.7% female, mean age of 22.63 ± 4.66 years) adults residing in Istanbul, Türkiye between 1 January 2026 and 30 June 2026. Data were collected through an online questionnaire comprising sociodemographic and food-related characteristics, the Cooking Skills and Food Skills Measure, the e-Healthy Diet Literacy Scale (e-HDL), the Mediterranean Diet Adherence Screener (MEDAS), and the Short Screening Questionnaire of Highly Processed Food Consumption (sQ-HPF). Validated Turkish versions of all instruments were used; no measurement tool was developed specifically for this study. Results: 57.0% of participants were classified as having a high level of UPF consumption. The high level of UPF consumption group was younger, cooked at home less frequently, ordered food more frequently, and had lower cooking skills, food skills, and MEDAS scores compared to the low level of UPF consumption group (all p < 0.05). UPF consumption was negatively correlated with food skills (r: −0.33), MEDAS (r = −0.28), cooking skills (r = −0.27), age (r = −0.21), and home-cooking frequency (r = −0.18) and positively correlated with food-ordering frequency (r = 0.18). In the final regression model, younger age (β = −0.144, p = 0.009), lower food skills (β = −0.325, p < 0.001), and lower MEDAS scores (β = −0.252, p < 0.001) were independently associated with higher UPF consumption. E-HDL was not independently associated with UPF consumption. The final model explained 18.4% of the adjusted variance. Conclusions: Among this predominantly young and female sample of adults residing in Istanbul, lower food skills and lower Mediterranean diet adherence co-occurred with higher UPF consumption. Although the direction of these associations cannot be determined, the findings may inform future strategies that integrate nutrition education with practical food preparation support and the promotion of Mediterranean-style food choices. Full article

Artificial intelligence-enabled technologies offer new opportunities to support healthy aging and the long-term care needs of older adults. However, inclusive practices are paramount to ensuring that accessibility, usability, privacy, and equitable use are factored into the design and deployment of these emerging technologies. This article explores the role of co-design in health technology development and highlights the application of three methodological tools—the NIH Stage Model for Behavioral Intervention Development, the Unified Theory of Acceptance and Use of Technology, and Goal Attainment Scaling—to create a smart-home-based socially assistive robot (SAR) for the care of individuals living with Alzheimer’s disease and related dementias (ADRD). Ten participants (five caregiver–care recipient dyads) from an ongoing mixed-methods pilot feasibility study trialed the SAR in their homes for 1–6 months, with the robot personalized to their daily functioning, home layout, and caregiving needs. Qualitative analysis of monthly interviews derived themes pertaining to technical design, care protocol design, training management, and complementary care. These themes, combined with goal attainment analysis, offered several insights that allowed us to iteratively scale and refine the technology tailored to ADRD care. The study offers a practical framework for future co-design efforts aimed at enhancing the adoption of AI-enabled health technologies among older adults. Full article

Background/Objectives: This study evaluated the effects of a five-day intensive intervention aboard the Italian Navy sailing vessel Nave Italia for both cognitively healthy older adults and individuals with Alzheimer’s disease, focusing on autonomy, depressive symptoms, quality of life, and mobility. Given the limited sample size, the study is framed as a proof-of-concept investigation of a multidimensional intervention that can be experienced jointly by older adults and, in the case of dementia, within a supportive relational context. Methods: The program integrated the “Nave Italia Method” developed by the Tender to Nave Italia Foundation with cognitive stimulation, physical exercise, social engagement, and emotional support within a highly immersive outdoor experiential context. A total of 30 participants were involved: 10 healthy older adults and 20 individuals with Alzheimer’s disease (10 embarked and 10 remained at home). Because of the small, non-randomized cohorts, the analyses focused primarily on within-group pre–post changes rather than formal between-group efficacy comparisons. Results: Autonomy and depressive symptoms showed no significant changes, while quality of life improved in embarked individuals with Alzheimer’s disease for the timeframe participants were directly in the intervention and showed a positive trend in cognitively healthy older adults. Balance and gait improved in the healthy older adult group for the same intervention timeframe, likely reflecting the combined effects of structured exercise and physically engaging shipboard activities. The program strongly stimulated motivation, perceived self-efficacy, and active participation, highlighting the importance of experiential learning in facilitating the transfer of skills to daily life. Findings suggest that brief, intensive, and immersive interventions can act as a motivational catalyst by enhancing emotional, social, and cognitive engagement and supporting adherence to more structured programs to be continued on land. Conclusions: Due to the lack of literature on integrated and multidimensional outdoor experiences designed for both cognitively healthy older adults and those living with dementia, the study addresses this gap by exploring the potential of unconventional and immersive interventions to promote the well-being and quality of life of older adults. These findings support the feasibility and short-term promise of the intervention as a proof of concept rather than as definitive evidence of efficacy. Full article