Objective: To investigate the effects of a mobile health smartphone application to support self-management programmes on quality of life, self-management behaviour and exercise and smoking cessation behaviour in patients with chronic obstructive pulmonary disease (COPD). Design: A randomised controlled, single-blind trial, was carried out from November 2017 to February 2019, which included 78 participants admitted with COPD to the Affiliated Hospital of Zunyi Medical University in Guizhou. The study participants were randomised into intervention ( n = 39) and control groups ( n = 39). Methods: Participants in the intervention group undertook a mobile medical application-based programme in addition to routine care, and participants in the control group received only routine care. The outcome measures were health-related quality of life evaluated by the COPD Assessment-Test, self-management behaviour using the COPD Self-Management Scale and physical activity and smoking behaviour were measured using a self-designed questionnaire. Data collection was conducted at baseline, third month, sixth month and 12th months. Results: Thirty-five participants in the intervention group and 33 in the control group completed the study. Compared to the control group, participants in the intervention group showed statistically significant improvement in the COPD -Assessment -Test scores ( P < 0.01) and in all domains of the COPD Self-Management Scale scores ( P < 0.01) at 12th 12 months. Improvements in the COPD -Assessment -Test scores by 4.3 and 0.3 units, and in the total scores of the COPD Self-Management Scale total score by 23.01 and 2.28 units, respectively, were observed in the intervention and control groups, respectively over the 12-month study period. Meanwhile, the mobile health application programme also improved participants’ exercise and smoking cessation behaviour. Conclusions: The mobile health smartphone application to support self-management programmes was effective in improving health-related quality of life and self-management behaviour in patients with COPD. Trial registration: This study was registered in Chinese clinicaltrials.gov

Purpose To evaluate the efficacy of a deep‐learning model to segment the lung and thorax regions in pediatric chest X‐rays (CXRs). Validating the diagnosis of bacterial or viral pneumonia could be improved after lung segmentation. Materials and methods A clinical‐pediatric CXR set including 1351 patients was proposed to develop a deep‐learning model for the pulmonary‐thoracic segmentations. Model performance was evaluated by Jaccard's similarity coefficient (JSC) and Dice's coefficient (DC). Two adult CXR sets were used to assess the model's generalizability. According to the pulmonary‐thoracic ratio, Pearson's correlation coefficient and the Bland‐Altman plot were generated to demonstrate the correlation and agreement between manual and automatic segmentations. The receiver operating characteristic curves and areas under the curve (AUCs) were used to compare the pneumonia classification performance based on the lung‐extracted images with that based on the original images. Results The model achieved JSCs of 0.910 and 0.950, DCs of 0.948 and 0.974 for lung and thorax segmentations, respectively. Pearson's r = 0.96, P < .0001. In the Bland‐Altman plot, the mean difference was 0.0025 with a 95% confidence interval of (−0.0451, 0.0501). For testing with two adult CXR sets, the JSCs were 0.903 and 0.888, respectively, while the DCs were 0.948 and 0.937, respectively. After lung segmentation, the AUC of a classifier to identify bacterial or viral pneumonia increased from 0.815 to 0.879. Conclusion We built a pediatric CXR dataset and exploited a deep‐learning model for accurate pulmonary‐thoracic segmentations. Lung segmentation can notably improve the diagnosis of bacterial or viral pneumonia.

ObjectiveTo confirm the effects of a transtheoretical model (TTM) based on multidimensional life management on healthy behavior in patients with polycystic ovary syndrome (PCOS).MethodsIn total, eighty eligible patients were recruited from March 2021 to June 2021 and randomly assigned to either the intervention (n = 40) or control (n = 40) groups. Outcome measures include health-promoting behavior, self-efficacy, anthropometrics, and the number of unplanned outpatient admissions. Data were collected at baseline, 3, and 6 months after the intervention. The chi-square test, rank-sum test, t-test, and repeated measurement analysis of variance (ANOVA) were used to analyze the data.ResultsIn total, sixty-six participants completed the study: 35 participants in the intervention group and 31 participants in the control group. After 6 months of intervention, the healthy behavior level of patients with PCOS increased from moderate [health-promoting lifestyle profile (HPLP)-II score of 105.37 ± 12.57] to good (156.94 ± 19.36) in the intervention group; and there was no change observed in the control group. In addition, the total self-efficacy score (p &lt; 0.001), PCOS-related unplanned outpatient admissions (p = 0.008), waist circumference (WC) (p = 0.016), and body mass index (BMI) (p = 0.011) were found to have a significant difference in the intervention group at 6 months. Meanwhile, repeated measures analysis of variance showed a significantly greater improvement in health-promoting behavior and self-efficacy over time in the intervention group than in the control group (p &lt; 0.001).ConclusionThe transtheoretical model based on multidimensional life management positively affected healthy behavior, self-efficacy, the number of unplanned outpatient admissions, and anthropometrics in patients with PCOS.Clinical Trial Registrationwww.chictr.org.cn, ChiCTR2000034572.

ObjectiveThis study aimed to investigate health-promoting lifestyle status and associated risk factors in patients with polycystic ovary syndrome (PCOS).DesignCross-sectional study.SettingThis study was conducted at a tertiary hospital in Guizhou, China from December 2020 to June 2021.ParticipantsA total of 366 participants (18–45 years) diagnosed with PCOS were recruited from the outpatient departments.MeasuresSociodemographic characteristics were collected, and health-promoting behaviours were measured using the Health-Promoting Lifestyle Profile scale. Anxiety status was measured using the Zung’s Self-Rating Anxiety Scale, depression status using the Zung’s Self-Rating Depression Scale and self-efficacy using the Managing Chronic Disease 6-Item Scale. Multiple stepwise linear regression was conducted to assess the risk factors associated with the health-promoting behaviours of the study participants.ResultsThe participants had a poor health-promoting behaviours (88.54±17.44). The highest score in all dimensions was spiritual growth (16.68±4.98), while physical activity (12.71±2.68) was the lowest. Multiple regression analysis revealed that the main factors influencing the development and maintenance of health-promoting behaviours among participants were education (B=10.788, p<0.001), depression (B=−0.377, p<0.001), anxiety (B=−0.333, p<0.001) and self-efficacy (B=0.938, p=0.002). The model showed 74.40% variance shared between the dependent and independent variables (R2=74.40, F=264.633, p<0.001).ConclusionHealth-promoting behaviours are minimal among patients with PCOS, and improving negative emotions and enhancing behavioural awareness and self-efficacy are necessary to increase the adoption of health-promoting behaviours among patients with PCOS.Trial registration numberChiCTR2000034572.

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