Specific Demands Research Articles

Integrating CLSP and GLSP models for optimizing production batch sizes in vulcanized component manufacturing

This study addresses the complex issue of optimizing production batch sizes within a company specializing in manufacturing rubber, thermoplastic, and polyurethane components, all of which undergo vulcanization prior to sale. Through meticulous analysis of the production planning process, it was observed that certain activities could be logically grouped into two sequential stages without compromising information integrity or detail. The initial stage encompasses press activities involving vulcanization and curing, while the next one involves greenhouse operations for post-curing. The commencement of the second stage is contingent upon the completion of all activities in the first stage. Consequently, an effective production plan must concurrently consider both stages. To tackle this, a mathematical model is proposed to address the batch sizing problem within the company, integrating both stages and drawing inspiration from the CLSP (Capacitated Lot Sizing Problem) for the first stage and the subperiod approach derived from GLSP (General Lot-sizing and Scheduling Problem) models for the second stage. The model is solved utilizing the CPLEX solver version 12.8. It incorporates 74 items, spans 20 periods, each with specific demands, and delineates 16 sub-periods within each planning horizon period. Experimentation involving a hypothetical example and subsequent tests utilizing real data from the case study company demonstrate the successful resolution of the problem, yielding enhanced production plans, particularly in terms of cost reduction objectives.

Development and Characterization of Lime-Based Mortars Modified with Graphene Nanoplatelets

Materials for the conservation of cultural heritage must meet specific demands, such as high durability, service life, and compatibility with other materials used in the original building structures. Due to their low permeability to water and water vapor and their high rigidity, the use of Portland cement (PC) mortars, despite their high mechanical resistance and durability, does not represent an appropriate solution for the repair of historic masonry and structures. Their incompatibility with the original materials used in the past, often on a lime basis, is therefore a serious deficiency for their application. On the other hand, lime-based mortars, compared to PC-based materials, are more susceptible to mechanical stress, but they possess high porosity, a high water vapor transmission rate, and moderate liquid water transport. This study aims at the development of two types of lime-based mortars, calcium lime (CL) and hydraulic lime (HL). The modification of mortars was conducted with a carbon-based nanoadditive and graphene nanoplatelets (GNs) in three dosages: 0.1%, 0.3%, and 0.5% of the binder weight. The enhancement of CL mortars by GNs greatly increased mechanical strength and affected heat transport characteristics, while other characteristics such as porosity, water absorption, and drying rate remained almost similar. The application of GNs to HL not only enhanced the strength of mortars but also decreased their porosity, influenced pore size distribution, and other dependent characteristics. It can be concluded that the use of graphene nanoplatelets as an additive of lime-based composites can be considered a promising method to reinforce and functionalize these composite materials. The improved mechanical resistance while maintaining other properties may be favorable in view of the increasing requirements of building materials and may prolong the life span of building constructions.

Impact of various fairness-based distribution models on supply chain networks from the perspective of customer satisfaction

AbstractThis study investigates the effectiveness of two fairness-based distribution approaches—type I and type II—in enhancing the resilience of supply chain networks (SCNs) during disruptions. The research contributes to the growing body of knowledge on supply chain management by offering insights into how fairness principles can be applied to improve the restoration of disrupted networks. A mixed-integer programming model was developed to simulate these fairness-based distribution strategies, focusing on a water supply chain network of a privet company in Saudi Arabia. The SCN consists of a single supplier and ten demand nodes, each requiring multiple commodities. The model was tested under 100 random disruption scenarios, each reducing the capacity of randomly selected network segments. The performance of each fairness-based distribution approach was evaluated based on how quickly and effectively the SCN returned to its required service levels (SLs) across all demand nodes. Results indicate that Fairness Distribution Type I, which aims to minimize unmet demand across the entire network, generally outperformed Type II in terms of speed and efficiency. Type I was more effective at restoring SLs quickly at most nodes, while Type II showed localized advantages, particularly in restoring SLs for specific commodities at select nodes. The study concludes that while Type I is more suited for overall supply chain recovery, Type II may be beneficial in scenarios requiring focused recovery at specific demand nodes. These findings provide actionable insights for supply chain managers seeking to enhance network resilience through fairness-based distribution strategies, and suggest avenues for future research on hybrid and context-specific approaches.

Formulation-Property Effects in Novel Injectable and Resilient Natural Polymer-Based Hydrogels for Soft Tissue Regeneration

The development of injectable hydrogels for soft tissue regeneration has gained significant attention due to their minimally invasive application and ability to conform precisely to the shape of irregular tissue cavities. This study presents a novel injectable porous scaffold based on natural polymers that undergoes in situ crosslinking, forming a highly resilient hydrogel with tailorable mechanical and physical properties to meet the specific demands of soft tissue repair. By adjusting the formulation, we achieved a range of stiffness values that closely mimic the mechanical characteristics of native tissues while maintaining very high resilience (>90%). The effects of gelatin, alginate, and crosslinker concentrations, as well as porosity, on the hydrogel’s properties were elucidated. The main results indicated a compression modulus range of 2.7–89 kPa, which fits all soft tissues, and gelation times ranging from 5 to 30 s, which enable the scaffold to be successfully used in various operations. An increase in gelatin and crosslinker concentrations results in a higher modulus and lower gelation time, i.e., a stiffer hydrogel that is created in a shorter time. In vitro cell viability tests on human fibroblasts were performed and indicated high biocompatibility. Our findings demonstrate that these injectable hydrogel scaffolds offer a promising solution for enhancing soft tissue repair and regeneration, providing a customizable and resilient framework that is expected to support tissue integration and healing with minimal surgical intervention.

Barriers to care for dependent older adults: Brazilian Primary Health Care managers' perspective.

This study analyzes the perspective of 16 managers from different Brazilian regions about the barriers to adequate care for dependent older adults in Brazilian PHC. This qualitative approach is anchored in the hermeneutic-dialectic theoretical framework. It builds on the principle that aging has different epidemiological rhythms and multiple specific demands from older adults' biopsychosocial changes. We highlighted several challenges to health services, since family, educational, organizational, and social contexts are fragmented. The 16 managers were selected by convenience from June to September 2019. They interacted individually in a semi-structured interview lasting approximately 30 minutes. The interviews were transcribed in full, and data were organized into four empirically selected themes: barriers due to dependent older adults' family care problems; lack of priority in PHC scheduling; failure in recruiting and training professionals; and lack of a specific public policy. The results indicated weakened families regarding lack of training and overload, especially female caregivers in care routine. Managers recognize the repeated comings and goings and searching for PHC access, highlighting insufficient primary services to organize care. Noteworthy is that high population demand exacerbates inadequate coverage, since lack of professionals with adequate training, priority on the agenda of services, and a public support policy to meet this population's needs fragment healthcare. Thus, it is essential to remedy the barriers recognized by managers by training more experts and qualifying professionals in the service. Society must recognize the stages of aging and support families, especially those most socially needy. The health sector at the Primary Care level has much to contribute to ensuring social protection and healthy longevity for Brazilians.

Don't Throw Away Your Notebook: Effects of Task Difficulty and Presentation Medium on Memory Performance.

People are increasingly reliant on various electrical devices for learning and memory, yet the implications and consequences of this dependence remain poorly understood. The present study aimed to investigate how learning through electrical media impacts recall under varying task difficulties. During this study, participants encoded information related to daily life situations (low difficulty), academic conceptual knowledge (middle difficulty), or associative word pairs (high difficulty), presented on smartphones, computers, or paper. At test, they recalled the omitted content based on the provided cue information. A significant screen-inferiority effect was observed for both computers and smartphones. However, the impairment related to computers disappeared in the retrieval of daily life situations and academic conceptual knowledge, whereas the impairment associated with smartphones was consistently present across all tasks. These results suggest that memory performance is modulated by the interaction between the presentation medium and the specific demands of the task, highlighting a more pronounced screen-inferiority memory effect when the media restrict the depth of processing or when the memory tasks pose greater external challenges. A deeper understanding of these factors can guide the optimization of electrical devices to enhance human memory abilities and functions.

Drowning in emails: investigating email classes and work stressors as antecedents of high email load and implications for well-being.

High email load has been associated with impaired well-being because emails impose specific demands, disturb the workflow, and thereby overtax individuals' action regulation toward prioritized goals. However, the causes and well-being-related consequences of email load are not yet well understood, as previous studies have neglected the interaction type and function of emails as well as co-occurring stressors as antecedents of high email load and have relied predominantly on cross-sectional designs. In two studies, we aimed to clarify the nature of email load through the lens of action regulation theory. The first study, a two-wave investigation with a fortnightly interval, examined the lagged relationships among email load, work stressors, strain, and affective well-being. The sample included 444 individuals across various occupations and organizations, with 196 of them working from home or remotely at least part of the time. In the second cross-sectional study, we surveyed 257 individuals using a convenience sampling approach, 108 of whom worked from home or remotely at least partially. This study focused on evaluating how different email classes-distinguished by email interaction type (received vs. processed) and email function (communication vs. task)-serve as predictors of high email load. In Study 1, we found a positive lagged effect of high email load on strain, even when controlling for the co-occurring stressors time pressure and work interruptions. In addition, lagged effects of email load on time pressure and interruptions were identified, while no evidence was found for the reverse direction. The results of Study 2 suggest that only the number of communication-related emails received, but not the number of task-related emails received, or the number of all emails processed contribute to high email load. Findings suggest that email load can be considered a unique stressor and that different classes of email need to be distinguished to understand its nature. Clarifying the sources of email load can help develop effective strategies to address it.

Reshaping sport performers' careers: Lessons from the 2023–2024 war in Israel

The war experience (WE) presents a highly troublesome period for sport performers, with severe effects on their lives and career trajectories. In this article, we initially conceptualize the WE through the scheme of change for sport psychology practice (Samuel & Tenenbaum, 2011a). The WE is considered a longitudinal, multifaceted, unpredicted, noncontrolled, negative change-event, developed over four distinct stages with specific demands and responses: (a) a pre-war stage, (b) War stage-A accompanied by instability and confusion, (c) War stage-B characterized by active coping or regression, and (d) War stage-C; return to sport activity, modification of activity, or retirement. The development of this change process in sport performers’ careers is discussed within the context of the 2023 Israel-Hamas war. Thereafter, we discuss applied practice efforts to support sport performers through the WE. The conclusions offer future avenues for researchers and practitioners when attempting to evaluate and cope with this unique change-event.

Water Demand Forecasting in Multiple District Metered Areas Based on a Multi-Scale Correction Module Neural Network Architecture

Short-term water demand forecasting (STWDF) for multiple spatially and temporally correlated District Metering Areas (DMAs) is an essential foundation for achieving more refined management of urban water supply networks. However, due to the greater uncertainty associated with specific DMA demand compared to overall water usage, accurately predicting STWDF poses significant challenges. This study introduces an innovative network architecture—the multi-scale correction module neural network, built upon Long Short-Term Memory (LSTM) networks and Convolutional Neural Networks (CNN) enhanced with Attention mechanisms—for simultaneous STWDF with a temporal resolution of one hour over a week for 10 DMAs located in a single city in northern Italy. This framework utilizes multivariate corrections to refine and enhance the output accuracy. The results reveal that, in comparison to traditional Gated Recurrent Unit or LSTM models, the proposed model with integrated correction modules, particularly those that leverage inter-DMA correlations, improves performance across all evaluation metrics by an average of 5%-20% per DMA. Additionally, it consistently delivers superior accuracy across three scenarios: single DMA forecasting, total water demand, and extreme conditions, while maintaining stable performance throughout. Furthermore, the interpretability analysis underscores the feasibility of this innovative structure and highlights the contribution of meteorological features to the predictive model in some DMA-level STWDF. The unified input-output framework elegantly simplifies the STWDF process across multiple DMAs, providing new insights and methodologies for future research in this domain.

The considerations on selecting the appropriate decellularized ECM for specific regeneration demands

The considerations on selecting the appropriate decellularized ECM for specific regeneration demands

Relationship between Physical Demands and Player Performance in Professional Female Basketball Players Using Inertial Movement Units

Load monitoring has been identified as a valuable tool for optimizing training planning and minimizing injury risk. This study’s aim was divided into two main objectives: (1) to describe the physical demands during official competition through IMU (inertial movement unit) metrics and (2) to investigate the relationship between basketball statistics and these physical demands. Twelve female highly trained basketballers (26.5 ± 5.3 years, 180 ± 7.1 cm, and 73.6 ± 10.3 kg) were monitored during four official games. Our results indicate that games with more frequent possession changes, particularly those driven by steals and turnovers, exhibit higher physical demands. Additionally, longer game durations were associated with longer recovery time while maintaining similar active time and physical load. Players who assume prominent shooting roles face greater conditional demands, such as increased jumps and impacts, even with equal playing time. These findings suggest that IMUs provide valuable insights into high-intensity actions and patterns, indicating a direct association between physical load and player performance in professional female basketball. This study also highlights the potential for professionals to better manage workload and understand player demands using these insights, even in the absence of in-game sensor data. Our research underscores the importance of contextual analysis in sports performance studies, encouraging future investigations into game phases and their specific physical demands.

Perspectives on Intelligence in Soft Robotics

Engineers frequently aim to streamline environmental factors to facilitate the effective operation of robots. However, in nature, environmental considerations play a crucial role in shaping the embodiment of organisms. To comply robots with the complexity of real‐world environments, embedding similar intelligence is key. In the field of soft robotics, various approaches offer insight into how intelligence can be integrated into artificial agents. A discussed topic is the intricate relationship between the brain and the body at the core of intelligence in robots. The goal of this article is, therefore, to unravel the strategies to implement different types of intelligence currently adopted in soft robots. A classification is made by making a distinction between agents that adapt to their environment by 1) their adaptive shape, 2) their adaptive functionality, and 3) their adaptive mechanics. Additionally, the perspectives on intelligence based on their computational approach are distinguished: centralized computation, decentralized computation, or embedded computation. It is concluded that a tailored robotic design approach attuned to specific environmental demands is needed. To unlock the full potential of soft robots, a fresh perspective on embodied intelligence is described, so‐called mechanical intelligence, emphasizing the robot's responsiveness to changing external conditions of a real‐world environment.

Depth of Cure, Surface Characteristics, Hardness, and Brushing Wear of 4 Direct Restorative Materials in Paediatric Dentistry

Aim: The study aimed to compare the depth of cure, hardness, surface roughness, and wear resistance of four restorative materials used in pediatric dentistry: FUJI IX GP FAST, RivaSilver, SDR flow+, and Vertise Flow. Materials and Methods: The depth of cure was measured per ISO 4049 standards using a digital caliper, with 15 samples of each material. Hardness was evaluated using a Vickers indenter under a 10 N load for 20 s. Surface roughness was assessed before and after acid exposure using an optical profilometer according to ISO 4288. Brushing wear resistance was analyzed by subjecting samples to 20 and 60 min of brushing, followed by roughness measurements. Statistical analysis was performed using independent sample t-tests to determine the significance of differences between the materials, with p-values < 0.05 considered significant. Results: SDR flow+ exhibited the highest depth of cure with an average of 3.5 mm (±0.2 mm), significantly higher than Vertise Flow at 2.8 mm (±0.3 mm) (p < 0.001). Hardness testing revealed SDR flow+ had the highest average hardness (85 HV ± 4 HV), while Vertise Flow had the lowest (72 HV ± 5 HV) (p < 0.001). Surface roughness increased significantly after acid exposure for RivaSilver (from 1.2 μm ± 0.12 μm to 1.6 μm ± 0.15 μm, p = 0.007) and for SDR flow+ (from 0.85 μm ± 0.08 μm to 1.3 μm ± 0.14 μm, p = 0.001). Brushing wear resistance was highest in RivaSilver (Ra increase from 1.2 μm to 1.4 μm ± 0.11 μm) and lowest in FUJI IX GP FAST (Ra increase from 1.5 μm to 1.9 μm ± 0.15 μm, p < 0.001). Conclusions: The study demonstrates significant differences in performance among the tested materials. SDR flow+ showed a superior depth of cure and hardness, making it suitable for high-stress applications. However, all materials displayed increased surface roughness following acid exposure and brushing, with FUJI IX GP FAST showing the highest wear. These findings highlight the need to select restorative materials based on the specific clinical demands of pediatric patients, considering both their mechanical properties and resistance to wear and acid.

Do oil market shocks affect financial distress? Evidence from firm-level global data

This study investigates the impact of three oil price shocks on financial distress of global firms using a dataset of 8130 firms across 48 countries from 2002 to 2022. It also analyses the role of energy diversification in the relationship between oil shocks and firm distress. The findings reveal that aggregate demand and specific demand shocks increase firm distress risk, while supply shocks reduce it. Furthermore, the results suggest that energy diversification mitigates the impact of specific demand shocks on firm distress. The study also implements several robustness checks, and the results remain consistent. Potential policy implications are also discussed.

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Digitalization has significantly influenced the challenges facing the media industry. The very process of media transformations "is no longer a technical need, but is already a social reflection and need, a need for communication, a need for solving political and technological problems in the society of this time" (Bebić & Volarević, 2016). Therefore, the attention of users is increasingly difficult to capture, thanks to the diversity of media publications, and in this sense traditional media often fail to respond to specific audience demands (Trattner, et al., 2022).Today, users are exposed to a large amount of information on a daily basis, their content is increasing, so media content cannot be imposed on users, but they choose only what they are interested in for consumption. However, traditional electronic media have understood the importance of the new multidimensional environment, therefore they are using a multiplatform through the Internet that use digital technology both to place the content and to personalize the offers against the user (Ćitić, 2020).

Reverse periodization in ultratrail: The road to the 2023 World Mountain and Trail Running Championships of an elite female ultrarunner

Introduction and Purpose Traditionally, linear periodization has been widely applied to endurance training programs, whereas reverse periodization has been often used for shorter endurance events (Clemente-Suárez et al., 2015; Clemente-Suárez et al., 2018; Clemente-Suárez & Ramos-Campo, 2019) and fitness (Prestes et al., 2009). The aim of this study was to describe the training characteristics of a Spanish high-level female ultrarunner in her preparation to the 2023 World Mountain and Trail Running Championships using a reverse linear periodization model. Methods Day-by-day data training of 1 study subject for 29 weeks (from November 2022 to June 2023) was retrospectively analyzed. Training form (endurance, strength or complementary sessions), intensity (low-, moderate-, and high-intensity training), intensity distribution, exercise endurance mode (cycling, elliptical, running or trail running) and specific exercise mode goal session (running uphill, running flat, running downhill, hiking or mixed) were considered. Specific sessions, key competitions, tapering, hypoxia period and periodization were also analyzed. Results An average training of 8 hr and 53 min per week, covering 87.2 km and 3,755 m of altitude gain, was completed. The hardest week consisted of 14 hr and 58 min, 145 km, and 7,552 m of altitude gain. Distribution percentage of the training form of total training time was ~60% of running, ~17% cross training (mainly road cycling) and ~11% of strength training. Intensity distribution varied considering specificity and characteristics of the main races, progressing from more polarized to pyramidal pattern distribution. Moreover, running volume increased during the preparation period and more specific sessions and with mixed specific exercise modes was realized close to the main races, with the longest trail run of 4 hr 18 min of duration. Training in hypoxia was also completed, and tapering started 12 days before the world championship. In addition to the World Championship, National Championship races were held during the preparation period, where a 4th and a 3rd place in the Marathon (February 2023) and Ultratrail (April 2023) National Championships, respectively, was achieved. Discussion Reverse periodization has been successfully implemented in an elite female ultrarunner, finishing 11th in the 2023 World Mountain and Trail Running Championships. Reverse periodization was planned and completed, mainly considering volume and tendency of distribution, going from a polarized pattern to a pyramidal one. Moreover, overall planning and key sessions progressed in specificity, developing more rolling-hill trail runs, longer trail runs, longer longest trail run of the week, and more specific exercise modes (i.e. more hiking and mixed sessions vs flats runs) along the macrocycle. Conclusion Training specificity in trail running, considering race intensity, exercise mode and race characteristics (i.e., elevation gain and distance) progressed during the macrocycle. Reverse periodization can be successfully implemented in ultratrail running by focusing on specific training and race demands, especially close to the main races.

Physical demands of collegiate basketball practice: a preliminary report on novel methods and metrics.

Knowing the specific physical demands of basketball players can provide useful information for clinical decision making when rehabilitating athletes following injury. The purpose of this observational study was to describe the physical demands of basketball play at the Division I collegiate level using video-based time-motion analysis and introduce a time-efficient alternative method of quantifying demands. Eleven NCAA Division I basketball players (6M, 5F; 4 guards, 4 centers, 3 forwards) participated in the study. Video footage was collected from four practices (2 men's, 2 women's) and used to quantify the types and frequencies of player movements based on definitions from seminal work. A second and simpler method was also used to classify movement. A two-way ANOVA was used to assess significant differences in movement by team (men's, women's) and position (guard, forward, center). There were significant differences in counts of stand/walk (p < 0.001), jog (p = 0.012), run (p = 0.001), stride/sprint (p = 0.04), and medium-intensity shuffling (p < 0.001) per minute and proportion of practice time spent in bodyweight (p < 0.001) or above-bodyweight (p < 0.001) loading between teams. There were significant differences for jog (p = 0.001) and transition (p = 0.07) rates across positions. Position and team are important considerations for rehabilitation and return-to-sport clearance. Quantification of these demands can be reliably acquired through video analysis using a simplified method (estimated foot load) or using traditional methods of movement classification and counts, particularly when applying descriptors that better capture the current style of play.

G20 systemic risk: Are structural oil price shocks driving factors?

Investigating systemic risk and its driving factors has always been a hot topic. Based on this, we combine the tail-event driven network (TENET) and structural vector autoregression (SVAR) model to study characteristics of G20 systemic risk and the impact of structural oil price shocks on it. The results of TENET model are as follows: From a systemic perspective, G20 systemic risk is high and exhibits significant time-varying characteristics. It can reflect periods of economic stress. From a group perspective, systemic risk in developing countries is often higher than developed countries and is more susceptible to extreme events. The systemic risk in developing countries mainly transmits and receives within the group. The systemic risk in developed countries is more balanced in its sources and mainly releases risk to developing countries. From an individual perspective, the risk spillover in G20 stock markets shows significant regional characteristics. Additionally, Argentina is most sensitive to G20 systemic risk, while India exhibits the strongest risk spillover to other G20 members. The results of SVAR model are as follows: Oil price shocks are important factors in explaining changes in G20 systemic risk, with the most significant being specific demand shock. The supply shock exacerbates systemic risk. The aggregate demand shock increases systemic risk in the short term but reduce it in the long term. The specific demand shock significantly reduces systemic risk. Against the backdrop of increasing uncertainty and economic globalization, these findings are of great significance for accurately identifying key points in regulatory frameworks and mitigating systemic risk.

Role of Adjuvants in Enhancing the Efficacy and Duration of Anesthesia Blocks: A Comprehensive Review.

Anesthesia blocks are integral to modern pain management, offering targeted and effective relief for various surgical and procedural interventions. These techniques, including regional and peripheral nerve blocks (PNBs), involve the administration of local anesthetics to specific body areas, either through epidural, spinal, or direct nerve injections. While effective, incorporating adjuvants, substances added to local anesthetics, can significantly enhance their efficacy and prolong their duration. Adjuvants such as opioids, corticosteroids, alpha-2 agonists, and nonsteroidal anti-inflammatory drugs (NSAIDs) are used to amplify analgesic effects, reduce the need for general anesthesia, and improve postoperative outcomes. This review explores the role of adjuvants in optimizing anesthesia blocks, examining their mechanisms of action, clinical benefits, and safety considerations. Adding adjuvants can lead to enhanced pain control, reduced dosage of local anesthetics, and fewer systemic side effects. By integrating adjuvants into anesthesia practice, clinicians can achieve more precise and sustained pain management, tailoring approaches to individual patient needs and specific procedural demands. This comprehensive review highlights current evidence on using adjuvants, their impact on anesthesia block effectiveness, and future research directions. Understanding the role of adjuvants is crucial for improving patient outcomes and advancing pain management techniques in various surgical settings.

Perceptions and Satisfaction With the Use of Digital Medical Services in Urban Older Adults of China: Mixed Methods Study.

In an aging and information-driven society, older adults have distinct perceptions of and specific demands for digital medical services. It is essential for society to understand these needs and develop a more thoughtful approach to digital health care. This study aims to evaluate the behavioral intention and satisfaction of older adults with digital medical services by identifying the perceived factors and the pathways through which these factors influence their behavior. This study used a mixed methods approach, combining qualitative and quantitative analyses. A focus group interview was conducted with 30 randomly selected older adults, and the interviews were transcribed verbatim and coded using grounded theory. In addition, 876 valid questionnaires were collected to describe older adults' perceptions of and satisfaction with digital medical care. Then, t tests and ANOVA were used to explore differences among various demographic groups, while hierarchical multiple regression was conducted to identify the factors most closely related to satisfaction. Structural equation modeling was used to identify multiple mediating effects. The qualitative study identified the core category of "medical service relief and transformation paths for older adults in the context of digital reform." Quantitative analysis revealed that more than half of the older adults were satisfied with digital medical services, and behavioral intentions were higher among those with higher incomes and education levels. Structural equation modeling confirmed that external variables, such as digital skills training, positively influenced perceived ease of use (β=.594, P<.001), perceived usefulness (β=.544, P<.001), and promoted digital medical behavioral intentions (β=.256, P<.001), while also reducing perceived risk (β=-.295, P<.001). Additionally, perceived ease of use (β=.168, P<.001) and perceived usefulness (β=.508, P<.001) positively impacted behavioral intention, whereas perceived risk (β=-.05, P=.037) exerted a negative influence. Furthermore, behavioral intention (β=.641, P<.001) significantly and positively affected older adults' satisfaction with digital medical care. The mediation test identified 4 significant paths: (1) external variables → perceived ease of use → behavioral intention (effect size of 13.9%); (2) external variables → perceived usefulness → behavioral intention (effect size of 38.4%); (3) external variables → perceived ease of use → perceived usefulness → behavioral intention (effect size of 10.1%); and (4) a direct effect (35.5%) from external variables to behavioral intention. Based on the study's findings, addressing the needs of older adults and enhancing perceived usefulness are the most effective ways to encourage the use of digital health care devices. Community support plays a crucial role in helping older adults integrate into digital health care, and adapting the design of services and products to suit their needs improves their perceptions of digital health care. This, in turn, promotes usage behavior and satisfaction, while the negative impact of perceived risk remains minimal.