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BACKGROUND Hypertension is a significant global disease burden. Mobile health (mHealth) offers a promising means to provide hypertensive patients with easy access to healthcare services. Yet, its effectiveness needs to be validated, especially in less developed areas with a high-salt diet. OBJECTIVE This study aims to assess the effectiveness of the mHealth app-based intervention in supporting patient self-management of hypertension. METHODS A two-arm randomized controlled clinical trial was conducted on 448 patients with hypertension at the General Hospital of Ningxia Medical University, Ningxia Hui Autonomous Region, P.R.China. The participants selected via convenience sampling were randomly allocated into two groups: the intervention and control groups. Participants in the intervention group were trained and asked to use a mHealth app named Blood Pressure Assistant for six months. They can use the app to record and upload vital signs, access educational materials, and receive self-management reminders and feedback from healthcare providers based on the analysis of the uploaded data. Participants in the control group received the usual care. Blood pressure and two questionnaire surveys about hypertension knowledge and lifestyle behavior were used to assess all participants at baseline and six months. Data analysis was performed in SPSS software, using t-test and Chi-square test. RESULTS There were no differences in baseline characteristics between the two groups. After six months, although both groups show a significant pre-post improvement (P CONCLUSIONS This research demonstrated that the mHealth app-based intervention could effectively improve patient health knowledge and support them to self-manage towards a healthier lifestyle, including medication adherence, low-salt diets, and physical exercises, thereby achieving optimal blood pressure control. CLINICALTRIAL ChiCTR1900026437

Background Mobile health services are gradually being introduced to support patients’ self-management of chronic conditions. The success of these services is contingent upon patients’ continuous use of them. Objective This study aims to develop a model to measure the success of patients’ continuous use of mobile health services for the self-management of chronic conditions. Methods The proposed model was derived from the information systems continuance model and the information systems success model. This model contains 7 theoretical constructs: information quality, system quality, service quality, perceived usefulness, user satisfaction, perceived health status, and continuous use intention. A web-based questionnaire survey instrument was developed to test the model. The survey was conducted to collect data from 129 patients who used a mobile health app for hypertension management from 2017 to 2019. The questionnaire items were derived from validated instruments and were measured using a 5-point Likert scale. The partial least squares modelling method was used to test the theoretical model. Results The model accounted for 58.5% of the variance in perceived usefulness (R2=0.585), 52.3% of the variance in user satisfaction (R2=0.523), and 41.4% of the variance in patients’ intention to make continuous use of mobile health services (R2=0.414). The continuous use intention was significantly influenced by their perceived health status (β=.195, P=.03), perceived usefulness (β=.307, P=.004), and user satisfaction (β=.254, P=.04) with the mobile health service. Information quality (β=.235, P=.005), system quality (β=.192, P=.02), and service quality (β=.494, P Conclusions This study developed a theoretical model to predict and explain patients’ continuous use of mobile health services for self-management of chronic conditions and empirically tested the model. Perceived usefulness, user satisfaction, and health status contributed to patients’ intention to make continuous use of mobile health services for self-managing their chronic conditions.

BACKGROUND Mobile health services are gradually being introduced to support patients’ self-management of chronic conditions. The success of these services is contingent upon patients’ continuous use of them. OBJECTIVE This study aims to develop a model to measure the success of patients’ continuous use of mobile health services for the self-management of chronic conditions. METHODS The proposed model was derived from the information systems continuance model and the information systems success model. This model contains 7 theoretical constructs: information quality, system quality, service quality, perceived usefulness, user satisfaction, perceived health status, and continuous use intention. A web-based questionnaire survey instrument was developed to test the model. The survey was conducted to collect data from 129 patients who used a mobile health app for hypertension management from 2017 to 2019. The questionnaire items were derived from validated instruments and were measured using a 5-point Likert scale. The partial least squares modelling method was used to test the theoretical model. RESULTS The model accounted for 58.5% of the variance in perceived usefulness (R2=0.585), 52.3% of the variance in user satisfaction (R2=0.523), and 41.4% of the variance in patients’ intention to make continuous use of mobile health services (R2=0.414). The continuous use intention was significantly influenced by their perceived health status (β=.195, P=.03), perceived usefulness (β=.307, P=.004), and user satisfaction (β=.254, P=.04) with the mobile health service. Information quality (β=.235, P=.005), system quality (β=.192, P=.02), and service quality (β=.494, PP CONCLUSIONS This study developed a theoretical model to predict and explain patients’ continuous use of mobile health services for self-management of chronic conditions and empirically tested the model. Perceived usefulness, user satisfaction, and health status contributed to patients’ intention to make continuous use of mobile health services for self-managing their chronic conditions.

BACKGROUND Hypertension affects over 15% of the world’s population and is a significant global public health and socioeconomic challenge. Mobile health (mHealth) services have been increasingly introduced to support hypertensive patients to improve their self-management behaviors, such as adherence to pharmacotherapy and lifestyle modifications. OBJECTIVE This study aims to explore patients’ perceptions of mHealth services and the mechanisms by which the services support them to self-manage their hypertension. METHODS A semistructured, in-depth interview study was conducted with 22 outpatients of the General Hospital of Ningxia Medical University from March to May 2019. In 2015, the hospital introduced an mHealth service to support community-dwelling outpatients with self-management of hypertension. Content analysis was conducted by following a grounded theory approach for inductive thematic extraction. Constant comparison and categorization classified the first-level codes with similar meanings into higher-level themes. RESULTS The patient-perceived mechanisms by which the mHealth service supported their self-management of hypertension were summarized as 6A: access, assessment, assistance, awareness, ability, and activation. With the portability of mobile phones and digitization of information, the mHealth service provided outpatients with easy access to assess their vital signs and self-management behaviors. The assessment results gave the patients real-time awareness of their health conditions and self-management performance, which activated their self-management behaviors. The mHealth service also gave outpatients access to assistance, which included health education and self-management reminders. Both types of assistance could also be activated by abnormal assessment results, that is, uncontrolled or deteriorating blood pressure values, discomfort symptoms, or not using the service for a long period. With its scalable use to handle any possible information and services, the mHealth service provided outpatients with educational materials to learn at their own pace. This led to an improvement in self-management awareness and ability, again activating their self-management behaviors. The patients would like to see further improvements in the service to provide more useful, personalized information and reliable services. CONCLUSIONS The mHealth service extended the traditional hypertension care model beyond the hospital and clinician’s office. It provided outpatients with easy access to otherwise inaccessible hypertension management services. This led to process improvement for outpatients to access health assessment and health care assistance and improved their awareness and self-management ability, which activated their hypertension self-management behaviors. Future studies can apply the 6A framework to guide the design, implementation, and evaluation of mHealth services for outpatients to self-manage chronic conditions.

In order to solve the problem of isolated design in multi-process using multi-assistant software, a through-software radial fatigue life prediction model was established, the effects of shrinkage cavity, SDAS and mean stress on fatigue life were considered. The casting process of the aluminum alloy wheel was simulated based on ProCast, and the data of SDAS and porosity of different parts were predicted based on the solidification process; The data mapping algorithm between tetrahedral mesh elements was developed to realize the unidirectional transformation of microcosmic data from a cast model to a static mechanical model, the radial loading mechanical analysis model of a wheel containing microcosmic information was established; The fatigue life prediction model was established by Fesafe based on the specific mechanical and fatigue parameters of each node. Based on the self-developed TCD software, the integrated coupling method of the three software prediction models was realized. The application of this method on the virtual fatigue prediction experiment of unidirectional tensile specimen reduce the result dispersion between virtual and physical experiment, and the predicted life result error is reduced from 51% to 16%. The proposed method lays a solid foundation of the optimization design and lightweight design of aluminum alloy wheels.

Background Hypertension affects over 15% of the world’s population and is a significant global public health and socioeconomic challenge. Mobile health (mHealth) services have been increasingly introduced to support hypertensive patients to improve their self-management behaviors, such as adherence to pharmacotherapy and lifestyle modifications. Objective This study aims to explore patients’ perceptions of mHealth services and the mechanisms by which the services support them to self-manage their hypertension. Methods A semistructured, in-depth interview study was conducted with 22 outpatients of the General Hospital of Ningxia Medical University from March to May 2019. In 2015, the hospital introduced an mHealth service to support community-dwelling outpatients with self-management of hypertension. Content analysis was conducted by following a grounded theory approach for inductive thematic extraction. Constant comparison and categorization classified the first-level codes with similar meanings into higher-level themes. Results The patient-perceived mechanisms by which the mHealth service supported their self-management of hypertension were summarized as 6A: access, assessment, assistance, awareness, ability, and activation. With the portability of mobile phones and digitization of information, the mHealth service provided outpatients with easy access to assess their vital signs and self-management behaviors. The assessment results gave the patients real-time awareness of their health conditions and self-management performance, which activated their self-management behaviors. The mHealth service also gave outpatients access to assistance, which included health education and self-management reminders. Both types of assistance could also be activated by abnormal assessment results, that is, uncontrolled or deteriorating blood pressure values, discomfort symptoms, or not using the service for a long period. With its scalable use to handle any possible information and services, the mHealth service provided outpatients with educational materials to learn at their own pace. This led to an improvement in self-management awareness and ability, again activating their self-management behaviors. The patients would like to see further improvements in the service to provide more useful, personalized information and reliable services. Conclusions The mHealth service extended the traditional hypertension care model beyond the hospital and clinician’s office. It provided outpatients with easy access to otherwise inaccessible hypertension management services. This led to process improvement for outpatients to access health assessment and health care assistance and improved their awareness and self-management ability, which activated their hypertension self-management behaviors. Future studies can apply the 6A framework to guide the design, implementation, and evaluation of mHealth services for outpatients to self-manage chronic conditions.

The elastoplastic mechanical properties of the weld and heat affected zone metals have comparatively major impact on the forming process of tailor-welded blanks. A few scholars investigated the elastoplastic mechanical properties of the weld and heat affected zone, but they only simply assumed that it was a uniform distribution elastoplastic material different from the base materials. Four types of tailor-welded blanks which consist of ST12 and 304 stainless steel plates are selected as the research objects, the elastoplastic mechanical properties of the tailor-welded blanks weld and heat affected zone metals are obtained based on the nanoindentation tests, and the Erichsen cupping tests are conducted by combining numerical simulation with physical experiment. The nanoindentation tests results demonstrate that the elastoplastic mechanical properties of the weld and heat affected zone metals are not only different from the base materials, but also varying between the weld metals and the heat affected zone metals. Comparing the Erichsen cupping test resulted from numerical with that from experimental method, it is found that the numerical value of Erichsen cupping test which consider the elastoplastic mechanical properties of the weld and heat affected zone metals have a good agreement with the experimental result, and the relative error is only 4.8%. The proposed research provides good solutions for the inhomogeneous elastoplastic mechanical properties of the tailor-welded blanks weld and heat affected zone metals, and improves the control performance of tailor-welded blanks forming accuracy.

Background: Chronic disease patients often face multiple challenges from difficult comorbidities. Smartphone health technology can be used to help them manage their conditions only if they accept and use the technology. Objective: The aim of this study was to develop and test a theoretical model to predict and explain the factors influencing patients’ acceptance of smartphone health technology for chronic disease management. Methods: Multiple theories and factors that may influence patients’ acceptance of smartphone health technology have been reviewed. A hybrid theoretical model was built based on the technology acceptance model, dual-factor model, health belief model, and the factors identified from interviews that might influence patients’ acceptance of smartphone health technology for chronic disease management. Data were collected from patient questionnaire surveys and computer log records about 157 hypertensive patients’ actual use of a smartphone health app. The partial least square method was used to test the theoretical model. Results: The model accounted for .412 of the variance in patients’ intention to adopt the smartphone health technology. Intention to use accounted for .111 of the variance in actual use and had a significant weak relationship with the latter. Perceived ease of use was affected by patients’ smartphone usage experience, relationship with doctor, and self-efficacy. Although without a significant effect on intention to use, perceived ease of use had a significant positive influence on perceived usefulness. Relationship with doctor and perceived health threat had significant positive effects on perceived usefulness, countering the negative influence of resistance to change. Perceived usefulness, perceived health threat, and resistance to change significantly predicted patients’ intentions to use the technology. Age and gender had no significant influence on patients’ acceptance of smartphone technology. The study also confirmed the positive relationship between intention to use and actual use of smartphone health apps for chronic disease management. Conclusions: This study developed a theoretical model to predict patients’ acceptance of smartphone health technology for chronic disease management. Although resistance to change is a significant barrier to technology acceptance, careful management of doctor-patient relationship, and raising patients’ awareness of the negative effect of chronic disease can negate the effect of resistance and encourage acceptance and use of smartphone health technology to support chronic disease management for patients in the community. [JMIR Mhealth Uhealth 2017;5(12):e177]

BACKGROUND Chronic disease patients often face multiple challenges from difficult comorbidities. Smartphone health technology can be used to help them manage their conditions only if they accept and use the technology. OBJECTIVE The aim of this study was to develop and test a theoretical model to predict and explain the factors influencing patients’ acceptance of smartphone health technology for chronic disease management. METHODS Multiple theories and factors that may influence patients’ acceptance of smartphone health technology have been reviewed. A hybrid theoretical model was built based on the technology acceptance model, dual-factor model, health belief model, and the factors identified from interviews that might influence patients’ acceptance of smartphone health technology for chronic disease management. Data were collected from patient questionnaire surveys and computer log records about 157 hypertensive patients’ actual use of a smartphone health app. The partial least square method was used to test the theoretical model. RESULTS The model accounted for .412 of the variance in patients’ intention to adopt the smartphone health technology. Intention to use accounted for .111 of the variance in actual use and had a significant weak relationship with the latter. Perceived ease of use was affected by patients’ smartphone usage experience, relationship with doctor, and self-efficacy. Although without a significant effect on intention to use, perceived ease of use had a significant positive influence on perceived usefulness. Relationship with doctor and perceived health threat had significant positive effects on perceived usefulness, countering the negative influence of resistance to change. Perceived usefulness, perceived health threat, and resistance to change significantly predicted patients’ intentions to use the technology. Age and gender had no significant influence on patients’ acceptance of smartphone technology. The study also confirmed the positive relationship between intention to use and actual use of smartphone health apps for chronic disease management. CONCLUSIONS This study developed a theoretical model to predict patients’ acceptance of smartphone health technology for chronic disease management. Although resistance to change is a significant barrier to technology acceptance, careful management of doctor-patient relationship, and raising patients’ awareness of the negative effect of chronic disease can negate the effect of resistance and encourage acceptance and use of smartphone health technology to support chronic disease management for patients in the community.