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The patient healthcare experience is a complex phenomenon, as is encouraging patient compliance with medical advice. To address this multifaceted relationship, the purpose of this paper is to explore the ways resident physicians verbally encourage patient compliance and the relationship between these compliance-seeking strategies and patient satisfaction.

A total of 40 medical interviews between resident physicians and patients were audio-recorded, transcribed, coded, and analysed. Patient questionnaires were also administered and analysed.

It was found that resident physicians used indirect orders most frequently, followed by motivation, persuasion, scheduling, and direct orders. It was also found that female patients received (marginally) more messages than male patients; female residents used more messages with female patients than with male patients; female residents used more persuasion messages with female patients than with male patients; male residents were less likely than female residents to use motivational messages with female patients; and compliance was significantly correlated with expertise satisfaction, overall satisfaction, and communication satisfaction.

This study advances existing research by examining various ways in which residents verbally encourage patient compliance and the relationship between these messages and patient satisfaction. Findings can be used to inform physicians on strategies to encourage patient adherence to medication regimen, appointments, and lifestyle changes.

The purpose of this paper is to examine interruption patterns between residents and patients as well as the correlations between three categories of interruptions and patient satisfaction.

A total of 40 resident/patient consultations in a Canadian clinic were audiotaped, transcribed and analyzed for intrusive, cooperative and unsuccessful interruptions.

Residents made significantly more interruptions than patients, especially in the categories of intrusive interruptions. These findings provide support for situated identity theory. High correlations were found between residents and patients on all three categories of interruptions, providing unequivocal support for communication accommodation theory. Patient satisfaction was negatively correlated with residents' intrusive interruptions and positively correlated with residents' cooperative interruptions. Patient satisfaction was higher among patients those who inserted more cooperative interruptions; to increase patient satisfaction, it is necessary to raise patient participation in the medical consultation. In comparison with healthier patients, sicker patients were interrupted more frequently and were less satisfied with the way they were treated.

The negative correlations between residents' intrusive interruption and patient satisfaction, as well as the positive correlation between patient satisfaction and residents' cooperative interruption provides evidence that patients' perception of the medical consultation is shaped by the nature of interruptions.

The purpose of this paper is to study the condensation flow of wet steam in the last stage of a steam turbine and to obtain the distribution of condensation parameters such as nucleation rate, Mach number and wetness.

Because of the sensitivity of the condensation parameter distribution, a double fluid numerical model and a realizable k-ε-k_d turbulence model were applied in this study, and the numerical solution for the non-equilibrium condensation flow is provided.

The simulation results are consistent with the experimental results of the Bakhtar test. The calculation results indicate that the degree of departure from saturation has a significant impact on the wet steam transonic condensation flow. When the inlet steam deviates from the saturation state, shock wave interference and vortex mixing also have a great influence on the distribution of water droplets.

The research results can provide reference for steam turbine wetness losses evaluation and flow passage structure optimization design.

The purpose of this paper is to find out the anti‐smoking counselling frequency and its correlates in a sample of Chinese physicians.

In this paper, 268 physicians in Baoding, a city near Beijing, filled out a questionnaire asking about their own smoking status, their anti‐smoking behaviors as well as their opinions on how to reduce cigarette smoking in China.

The paper finds that 54 percent of the male and 8.4 percent of the female physicians were current cigarette smokers. When asked whether they had counselled their patients about cigarette smoking in the past year, 43.7 percent answered “always”; 38.1 percent “often”; 13.1 percent “sometimes”; 2.6 percent “occasionally”, and 2.6 percent said: “not much”. However, only 9.0 percent said that they were “very successful”. Physicians' anti‐smoking counselling practices were highly correlated with their own smoking status; whether they perceived their past anti‐smoking activities as successful; whether they thought that they should set examples by not smoking; whether they felt that they had the responsibility to help patients and whether they perceived themselves as influential in persuading patients to quit smoking.

The paper shows that messages aimed at increasing Chinese physicians' anti‐smoking counselling should appeal to their responsibility, exemplary role, and unique influence on patients' health‐related behaviors.

The paper adds to the few studies on Chinese physicians' cigarette smoking behavior and their anti‐smoking activities. In a country where cigarette smoking is a way of life among males, and few people are aware of the health consequences of cigarette smoking, physicians' efforts can be a spearhead to a cessation campaign.

Human behavior recognition poses a pivotal challenge in intelligent computing and cybernetics, significantly impacting engineering and management systems. With the rapid advancement of autonomous systems and intelligent manufacturing, there is an increasing demand for precise and efficient human behavior recognition technologies. However, traditional methods often suffer from insufficient accuracy and limited generalization ability when dealing with complex and diverse human actions. Therefore, this study aims to enhance the precision of human behavior recognition by proposing an innovative framework, dynamic graph convolutional networks with multi-scale position attention (DGCN-MPA) to sup.

The primary applications are in autonomous systems and intelligent manufacturing. The main objective of this study is to develop an efficient human behavior recognition framework that leverages advanced techniques to improve the prediction and interpretation of human actions. This framework aims to address the shortcomings of existing methods in handling the complexity and variability of human actions, providing more reliable and precise solutions for practical applications. The proposed DGCN-MPA framework integrates the strengths of convolutional neural networks and graph-based models. It innovatively incorporates wavelet packet transform to extract time-frequency characteristics and a MPA module to enhance the representation of skeletal node positions. The core innovation lies in the fusion of dynamic graph convolution with hierarchical attention mechanisms, which selectively attend to relevant features and spatial relationships, adjusting their importance across scales to address the variability in human actions.

To validate the effectiveness of the DGCN-MPA framework, rigorous evaluations were conducted on benchmark datasets such as NTU-RGB + D and Kinetics-Skeleton. The results demonstrate that the framework achieves an F1 score of 62.18% and an accuracy of 75.93% on NTU-RGB + D and an F1 score of 69.34% and an accuracy of 76.86% on Kinetics-Skeleton, outperforming existing models. These findings underscore the framework’s capability to capture complex behavior patterns with high precision.

By introducing a dynamic graph convolutional approach combined with multi-scale position attention mechanisms, this study represents a significant advancement in human behavior recognition technologies. The innovative design and superior performance of the DGCN-MPA framework contribute to its potential for real-world applications, particularly in integrating behavior recognition into engineering and autonomous systems. In the future, this framework has the potential to further propel the development of intelligent computing, cybernetics and related fields.

This study aims to investigate the basic public service level in the Beijing-Tianjin-Hebei region under the impact of COVID-19.

This study constructed a basic public service-level evaluation system from the five dimensions of education, culture, health, social security and infrastructure and environment, and measures the basic public service level in 13 cities in Beijing, Tianjin and Hebei using the entropy method. The spatial pattern and dynamic evolution of the public service level are analysed from the perspective of dynamic trends in time series and spatial distribution, along with the reasons for the evolution of spatial distribution.

(1) The basic public service level in the 13 cities is generally on the rise, but the trend is unstable. (2) The basic public service level in space shows a general trend of attenuation from northeast to southwest, with significant spatial imbalance and orientation. (3) The regional differences first increase and then decrease. (4) The inter-group mobility of different basic public service levels is low, and cities with lower initial levels find it difficult to achieve leapfrog development. Moreover, the health service level of the region is still at a low stage, which is not conducive to effectively preventing and controlling the epidemic.

From the perspective of this research, the spatial pattern and dynamic evolution of basic public service were adopted to analyse the coordinated development of the Beijing-Tianjin-Hebei region. Furthermore, this study discusses how to improve the basic public service level to ensure sustainable operation in the region under the impact of COVID-19.

The main problem addressed by this research is the current debate between the negative and positive effects of industrial clusters. This debate is a result of gaps between theoretical implications and empirical evidence in both the classical agglomeration theory and the agglomeration lifecycle theory. The purpose of this study is to propose a framework for developing an index measuring both organizational cluster involvement and organizational supply chain including the three pillars (economic, social, and environmental). Furthermore, the index acts as a quantitative predictor of the stages of the life cycle of industrial clusters. Adopting a case study methodology, the applicability of the index development framework is demonstrated. First, cross-sectional exploratory interviews are performed to locate items measuring the three pillars of organizational sustainability within Egyptian communication industry. Second, an explanatory, cross-sectional approach is applied gathering data from eight professionals related to involvement and supply chain sustainability of their organizations. Analytical hierarchical process is used for weighting and aggregating individual item metrics into two indicators (Saaty, 1980). Measuring, managing, and controlling capabilities of organization's supply chains outweighs the need to manage risks. The proposed framework aids firms within a cluster in making timely decisions about what needs addressing to improve supply chain sustainability performance. Hence, all environmental, social, and economic capabilities can be effectively monitored and controlled.

The main purpose of the paper was to examine whether a short patient training session on various ways of requesting physicians to clarify a piece of previously elicited information during medical consultation would improve information communication, thus increasing patient satisfaction.

A total of 114 adult patients voluntarily participated in the study which was carried out at a clinic in Canada. Half of the participants were randomly assigned to the experimental group and half to the control group. Males and females were evenly distributed in both experimental and control groups. Prior to their medical visits, participants in the experimental group received 10‐15‐minute face‐to‐face training, whereas the control group did not receive any training. The purpose of the training was to facilitate information transmission, with the intention to increase communication effectiveness and patient satisfaction. Immediately after their medical visits, all participants filled out a patient satisfaction questionnaire.

On all four dimensions of patient satisfaction (i.e. overall satisfaction, relationship satisfaction, communication satisfaction and expertise satisfaction), patients who received training scored significantly higher (were more satisfied) than patients who received no training. No consistent gender differences were found in patient satisfaction in both experimental and control groups.

This study applied a psycholinguistics theory, conversational grounding, to the field of patient education and achieved positive results.

The success of the short training session provides health practitioners with a new method to help patients communicate more effectively, thus increasing satisfaction in medical interviews.

Focuses on a means to elicit information from patients in medical consultations.