Publications by authors named "Yiqiang Guo"

Background: Smoking is a leading cause of premature death globally. Quitting smoking reduces the risk of all-cause mortality by 11%-34%. Smartphone app-based smoking cessation (SASC) interventions have been developed and are widely used.

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Objective: This study aimed to assess the level of depression, anxiety and stress among metastatic breast cancer (MBC) patients undergoing chemotherapy (CT) in Beijing, China.

Methods: A cross-sectional study was conducted on 176 MBC women receiving CT, selected by purposive sampling. Data were collected using self-administered questionnaires that included participants' socio-demographic status, DASS-21 and Brief COPE.

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Objectives: Women who underwent chemotherapy (CT) for metastatic breast cancer (MBC) used both adaptive and maladaptive coping strategies but had low implementation levels. The present study explores the qualitative experience of coping strategies for women with MBC undergoing CT in Beijing.

Methods: A hermeneutic phenomenological approach was employed on twenty Chinese MBC women undergoing CT.

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Developing sustainable environmental policies in ecologically fragile and deeply impoverished areas is a global challenge. Desertification has caused serious environmental and socioeconomic issues. It is important to reveal the mechanisms of environmental policies when balancing desertification control and poverty alleviation.

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Background: Death and disability from coronary heart disease (CHD) can be largely reduced by improving risk factor management. However, adhering to evidence-based recommendations is challenging and requires interventions at the level of the patient, provider, and health system.

Objective: The aim of this study was to develop an Intelligent Individualized Cardiovascular App for Risk Elimination (iCARE) to facilitate adherence to health behaviors and preventive medications, and to test the usability of iCARE.

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To examine the method for estimating the spatial patterns of soil respiration (Rs) in agricultural ecosystems using remote sensing and geographical information system (GIS), Rs rates were measured at 53 sites during the peak growing season of maize in three counties in North China. Through Pearson's correlation analysis, leaf area index (LAI), canopy chlorophyll content, aboveground biomass, soil organic carbon (SOC) content, and soil total nitrogen content were selected as the factors that affected spatial variability in Rs during the peak growing season of maize. The use of a structural equation modeling approach revealed that only LAI and SOC content directly affected Rs.

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