A Latent Class Analysis of Perceived Neighborhood Conditions Associated with Mental Disorders Among Children in the United States.

The current study examined the association between perceived neighborhood conditions and common childhood mental disorders in a nationally representative sample of children in the U.S. The data were derived from the 2017 National Survey of Children's Health, including American children aged 6-17 years (N = 15,438). Latent class analysis was used to identify subtypes of perceived neighborhood conditions regarding neighborhood physical environment, social capital, and violence. Three classes were identified: Ideal Neighborhood (55.99%); Insufficient Assets (27.38%), and Broken and Unsafe Neighborhood (16.63%). The effects of latent classes on psychiatric outcomes (i.e. attention deficit hyperactivity disorder, depression, anxiety, conduct problem, and any of these four disorders) were examined. Class membership was differentially associated with the mental disorders after adjustment for demographic variables, food insufficiency, and guardian's mental health. The Broken and Unsafe Neighborhood class was associated with greater odds of all childhood psychiatric disorders than the Ideal Neighborhood and Insufficient Assets class. Insufficient Assets class was associated with greater odds of all childhood psychiatric disorders than the Ideal Neighborhood class. The findings suggest that neighborhood-level interventions to decrease children's mental health burdens are critically needed.

A temporal relationship between nonmedical opioid Use and major depression in the U.S.: A Prospective study from the National Epidemiological Survey on Alcohol and Related Conditions.

BACKGROUND: Given the existing strong cross-sectional relationship between nonmedical opioid use (NMOU) and major depressive disorder (MDD), this study focused on the temporal relationship between NMOU and major depression. METHODS: Data sources were derived from Wave 1 and Wave 2 of the National Epidemiological Survey on Alcohol and Related Conditions. Logistic regression was applied to predicted NMOU at the follow-up survey based on baseline MDD diagnosis and symptoms of MDD among the sample without lifetime NMOU at baseline (N=32,982). In parallel, we examined the relationship between past year NMOU at baseline and new onset of MDD diagnosis (N=28,649) and between past year NMOU at baseline and new onset of symptoms of MDD (N=23,214) among people without major depression diagnosis or symptoms at baseline. RESULTS: MDD diagnosis (aOR=1.68, 95% CI=1.43, 1.98) and symptoms of major depression (aOR=1.25, 95% CI=1.14, 1.38) at baseline were associated with higher odds of incident NMOU. The baseline NMOU was associated with lower odds incident MDD diagnosis (aOR=0.79, 95%CI=0.66, 0.94) in the adjusted model. However, the baseline NMOU was associated with higher odds of new onset of major depressive symptoms at wave 2 in the sample without baseline symptoms of MDD (aOR=1.42, 95%CI=1.23, 1.63). CONCLUSION: Symptoms of MDD and MDD diagnosis increased the new onset of NMOU, while NMOU only increased the risks of new onset of symptoms of MDD.

The Use of Mobile Health Applications to Improve Patient Experience: Cross-Sectional Study in Chinese Public Hospitals.

BACKGROUND: The proliferation of mobile health apps has greatly changed the way society accesses the health care industry. However, despite the widespread use of mobile health apps by patients in China, there has been little research that evaluates the effect of mobile health apps on patient experience during hospital visits. OBJECTIVE: The purpose of our study was to examine whether the use of mobile health apps improves patient experience and to find out the difference in patient experience between users and nonusers and the characteristics associated with the users of these apps. METHODS: We used the Chinese Outpatient Experience Questionnaire to survey patient experience. A sample of 300 outpatients was randomly selected from 3 comprehensive public hospitals (3 tertiary hospitals) in Hubei province, China. Each hospital randomly selected 50 respondents from mobile health app users and 50 from nonusers. A chi-square test was employed to compare the different categorical characteristics between mobile health app users and nonusers. A t test was used to test the significance in continuous variables between user scores and nonuser scores. Multiple linear regression was conducted to determine whether the use of mobile health apps during hospital visits was associated with patient experience. RESULTS: The users and nonusers differed in age (χ22=12.2, P=.002), education (χ23=9.3, P=.03), living place (χ21=7.7, P=.006), and the need for specialists (χ24=11.0, P=.03). Compared with nonusers, mobile health app users in China were younger, better educated, living in urban areas, and had higher demands for specialists. In addition, mobile health app users gave significantly higher scores than nonusers in total patient experience scores (t298=3.919, P<.001), the 18 items and the 5 dimensions of physician-patient communication (t298=2.93, P=.004), health information (t298=3.556, P<.001), medical service fees (t298=3.991, P<.001), short-term outcome (t298=4.533, P<.001), and general satisfaction (t298=4.304, P<.001). Multiple linear regression results showed that the use of mobile health apps during hospital visits influenced patient experience (t289=3.143, P=.002). After controlling for other factors, it was shown that the use of mobile health apps increased the outpatient experience scores by 17.7%. Additional results from the study found that the self-rated health status (t289=3.746, P<.001) and monthly income of patients (t289=2.416, P=.02) influenced the patient experience as well. CONCLUSIONS: The use of mobile health apps could improve patient experience, especially with regard to accessing health information, making physician-patient communication more convenient, ensuring transparency in medical charge, and ameliorating short-term outcomes. All of these may contribute to positive health outcomes. Therefore, we should encourage the adoption of mobile health apps in health care settings so as to improve patient experience.