[Applying Extended Theory of Planned Behavior for Lung Cancer Patients Undergone Pulmonary Resection: Effects on Self-Efficacy for Exercise, Physical Activities, Physical Function, and Quality of Life]

Study on influence factors of public participation willingness in substation project based on integrated TPB-NAM model

Public infrastructure, such as substations, is crucial for the advancement of the economy and society. However, the “not in my backyard” phenomenon is causing concern among the population, and these two things are at odds with one another. This study aims to investigate the driving mechanism that influences participation willingness of the public in order to promote the construction of substations, so the study proposes an integration model based on the planned behavior theory and the normative activation theory. Moreover, a structural equation model is created using the two dimensions, namely, social altruism and personal egoism, while data of 568 questionnaires are used for empirical research in combination with the “Decision-Making Trial and Evaluation Laboratory” method; these data are collected in the surrounding areas of three 110kV substations in Jiaozuo city, China. The key factors that affect participation willingness of the public are discussed, and the study demonstrates that the model is most significantly impacted by public trust, which is an a priori variable. Furthermore, the direct path coefficient of personal norms on participation willingness is the largest, which confirms that increased moral responsibility has a beneficial effect on project execution, and subjective norms contribute to the improvement of the assessment model overall since they are the main variables with the largest centrality degree in the system. The findings of this research better our understandings about the mechanism of “not in my backyard” and offer practical implications for its dissolution. On the basis of this, we present pertinent policy proposals for the “not in my backyard” effect that develops during the construction of public infrastructure.

Dynamic Changes and Influencing Factors for the Quality of Life in Nursing Care after Lung Cancer Resection

To investigate the dynamic changes and influencing factors for the quality of life in nursing care in patients with lung cancer after resection. Totally, 136 patients undergoing lung cancer resection in our hospital from January 2019 to January 2022 were prospectively enrolled as subjects. The quality of life was measured before and 1 and 2 weeks and 1, 3, 6, and 12 months after the operation to analyze the dynamic changes in the quality of life in nursing care. Clinical data of patients were collected at the time of discharge. The patients were divided into high-quality and low-quality groups according to the median level of quality of life in nursing care at the final follow-up. The logistic regression equation was applied to analyze the influencing factors for the quality of life in nursing care after lung cancer resection. Of 136 patients receiving lung cancer resection, 32 were lost to follow-up until the final follow-up, so 104 patients were finally included. According to the median level of quality of life in nursing care at the final follow-up, the patients were divided into high-quality and low-quality groups (n = 52 per group). The quality of life in nursing care first decreased, then increased, and then stabilized after lung cancer resection. The comparison of clinical data between the two groups exhibited that albumin level was higher in the high-quality group than that in the control group. The age, proportion of living alone, S-AI score, and FoP-Q-SF score were lower in the high-quality group than those in the low-quality group ( $P<0.05$ ). Univariate logistic regression analysis demonstrated that high albumin (OR = 0.884) was a protective factor for the quality of life in nursing care after lung cancer resection ( $P<0.05$ ). Living alone (OR = 1.333), high S-AI score (OR = 1.211), high FoP-Q-SF score (OR = 1.221), and advanced age (OR = 1.209) were the risk factors for the quality of life in nursing care after lung cancer resection ( $P<0.05$ ). Multivariate logistic regression analysis demonstrated that high albumin (OR = 0.861) was a protective factor for the quality of life in nursing care after lung cancer resection ( $P<0.05$ ). Living alone (OR = 1.144), high S-AI score (OR = 1.170), high FoP-Q-SF score (OR = 1.161), and advanced age (OR = 1.181) were the risk factors for the quality of life after lung cancer resection ( $P<0.05$ ). The quality of life in nursing care first decreased, then increased, and then stabilized after lung cancer resection. Albumin, age, living alone, and S-AI and FoP-Q-SF scores were the influencing factors for the quality of life in nursing care after lung cancer resection. In the nursing care process after lung cancer resection, we should focus on elderly patients living alone who are affected by anxiety and fear of recurrence to improve the quality of life of these patients.