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In 2021, New York City passed some of the most progressive nuclear disarmament legislation of any major city in the United States, supported by local activists from the New York Campaign to Abolish Nuclear Weapons (NYCAN). In this essay, two of the people behind this effort share some details of their success with local government as an example of what others can do to bring nuclear abolitionist activism home. They also give a sense of New York's long history as a nuclear city—and as a locus of action for disarmament. [ABSTRACT FROM AUTHOR]

This study examined the differences in mental health service use, barriers, and service preferences among 393 low-income housing (LIH) and market-rate housing (MRH) Harlem residents in New York City. One-third (34.6%) endorsed the need for professional support for psychological issues, 27.2% and 15.8% reported using counseling services and psychotropic medication, with no differences between housing types. LIH residents (21.6–38.8%) reported significantly higher use of all types of mental health resources (e.g., websites, anonymous hotlines, self-help tools) compared with MRH residents (16.1–26.4%). Eighty-six percent reported barriers to mental health access, with LIH residents reporting more than double the barriers. Particularly, LIH residents reported greater difficulty getting time off work (34.1% vs. 14%), lack of health insurance (18.7% vs. 9.8%), lack of trust in mental health providers (14.6% vs. 4.7%), and stigma (12.2% vs. 5.1%) compared with MRH residents. Residents most preferred places of services were health clinics and houses of worship; provided by healthcare and mental health providers; and services delivered in-person and phone-based counseling. In contrast, residents least preferred getting support at mental health clinics; from family/friends; and by the Internet. No differences were found between service preferences by housing type. LIH residents reported higher use of mental health services and resources, but they face significantly more barriers to mental health care, suggesting a need to address specific barriers. Preferences for mental health services suggest a need for expanding mental health services to different settings given the low preference for services to be delivered at mental health clinics. [ABSTRACT FROM AUTHOR]

Objective: This study aimed to identify characteristics surrounding COVID-19 vaccine hesitancy and trust in home health workers (HHWs) in New York City. Methods Data were collected from HHWs through focus group sessions conducted via Zoom. We developed a facilitator guide using the 5C Scale, a validated psychometric tool for assessing vaccine hesitancy. We performed qualitative thematic analysis using a combined inductive and deductive approach. Results: Major themes that emerged included the following: conflicting information decreased vaccine confidence; individualized outreach is valued when information gathering; mandates and financial incentives may increase skepticism; low health literacy and conflict in personal relationships are barriers to acceptance; and experiencing a severe infection and fear of exposure at work increase acceptance. Conclusions: Based on our study, personalized yet consistent messaging may be key to reaching hesitant HHWs. [ABSTRACT FROM AUTHOR]

Air pollution has a significant impact on human health and influences housing choices. Existing studies on determinant factors affecting property prices, including air pollution, mainly employed hedonic and spatial regression models that have limitations in capturing non-linear relationships and local interactions. Neglecting the non-linear relationships can lead to incomplete estimation impacts between explainable features and prices. To fill these gaps, this study used machine learning algorithms and SHAP (SHapley Additive exPlanations) to identify the relative importance of air pollutant variables on land values and their non-linear mechanism. The results showed that the Extreme Gradient Boosting (XGBoost) outperformed Ordinary Least Squares (OLS), Gradient Boosting Decision Tree (GBDT), Random Forest (RF), K-Nearest Neighbors (K-NN), and Extra Tree Regression (ETR) models in price prediction and capturing the non-linear relationship between air pollution and land values. Notably, Ozone (O 3) and Nitric Oxide (NO) concentrations contribute 1.64% and 1.47% to land value variation, respectively. The results confirmed the non-linear relationship and identified that the threshold effect between air pollution and land values is at mean concentration values. Furthermore, we observed that the negative influence of O 3 and NO on land values appears as their concentration level is higher than 29.3 and 13 ppb, respectively. This paper contributes valuable insights by advancing our understanding of the non-linear mechanism impact of air pollution on house and land values, informing environmental policymaking, and shedding light on housing decisions. [ABSTRACT FROM AUTHOR]