Reducing Loneliness Among Aging Adults: The Roles of Personal Voice Assistants and Anthropomorphic Interactions

The perception of feeling lonely is an influential factor in determining quality of life among aging adults. As the US Census Bureau projects that the number of Americans ages 65 and older will double by 2060, reducing loneliness is imperative. Personal voice assistants (PVAs) such as Amazon's Echo offer the ease-of-use of voice control with a friendly, helpful artificial intelligence. This study aimed to understand the influence of a PVA on loneliness reduction among adults of advanced ages, i.e., 75+, and explore anthropomorphism as a potential underlying mechanism. Participants (N = 16) ages 75 or older used an Amazon Echo PVA for 8 weeks in an independent living facility in the Midwest. Surveys were used to collect information about perceived loneliness, and PVA interaction data was recorded and analyzed. Participants consistently exceeded the required daily interactions. As hypothesized, after the first 4 weeks of the intervention, aging adults reported significantly lower loneliness (baseline mean = 2.22, SD = 0.42; week 4 mean = 1.99, SD = 0.45, Z = −2.45, and p = 0.01). Four dominant anthropomorphic themes emerged after thematic analysis of the entire 8 weeks' PVA interaction data (Cohen's Kappa = 0.92): (1) greetings (user-initiated, friendly phrases); (2) comments/questions (user-initiated, second-person pronoun), (3) polite interactions (user-initiated, direct-name friendly requests), (4) reaction (user response to Alexa). Relational greetings predicted loneliness reductions in the first 4 weeks and baseline loneliness predicted relational greetings with the PVA during the entire 8 weeks, suggesting that anthropomorphization of PVAs may play a role in mitigating loneliness in aging adults.

What a difference a year makes: A snapshot of the trends in vaccinations, hospitalizations, and mortality rates for SARS- CoV-2 across the state of Indiana

Background: Many efforts both scientifically and politically helped reduced the spread of SARS-CoV-2. In December of 2020, vaccinations were authorized for distribution. It is important to understand demographical correlations to COVID-19 acute illness rates and whether COVID-19 vaccinations significantly reduced these rates. Project Methods: This study focused on data from seventeen counties in Indiana. This information was used to determine if there were correlations between demographics and COVID-19 illness rates. County demographics were obtained from the United States Census Bureau. COVID-19 hospitalization and mortality were collected from the Regenstrief Institute and the Indiana State Department of Health respectively. Linear regression analyses were performed to determine if there were significant correlations between demographics and rates COVID-19 illness. T-test analyses assuming unequal variances were performed in order to determine if there has been a significant reduction in COVID-19 illness. Results: The results of this study revealed that the percentage of the population over the age of 65, with a bachelor’s degree, disabled under age 65, and the median income (r values: 0.729, 0.701, 0.661, and 0.533 respectively) are significantly correlated to the mortality rate. The percentage of the population over the age of 65 and with a bachelor’s degree (r values: 0.565 and 0.524 respectively) are significantly correlated to the hospitalization rate. When comparing the COVID-19 acute illness rates for each county from 07/27/20 until 02/01/21 to the rates after 02/01/21 until late- June of 2021, each county had significant decrease in the hospitalization and mortality rate after February 1, 2021. Potential Impact: The result of this study suggests that vaccinating residents was a significant factor in the 50% or higher reduction in COVID-19 hospitalization and mortality rates. These findings emphasize the importance of COVID-19 vaccinations to protect Americans from COVID-19 severe illness.

Frequent mask-wearing during the COVID-19 pandemic and acne: an infodemiology study from Google research trends (Preprint)

BACKGROUND Researchers have been increasingly using the internet as a major source of health-related information and infodemiological methods have provided new approaches for studying the impact of coronavirus disease (COVID-19). OBJECTIVE To verify whether frequent mask-wearing during the COVID-19 pandemic was associated with an increase in acne search popularity. METHODS Data for mask-wearing were obtained from a NYT survey, with 250,000 responses between July 2 and 14, 2020, and from Google COVID-19 symptoms dataset for weekly acne and anxiety search popularity. All data in the study were presented in relation to US county levels. Each county was classified in the frequent mask-wearing group if the proportion of frequent users was above the third quartile. To make search trends comparable from one week to another and from one county to another, search trends were normalized on a relative 100-point scale, with the maximum value corresponding to the highest search popularity for a particular term in a specific week and a specific county. Other sources of data included the US census bureau datasets. Acne search popularity outcome was analyzed using a logistic regression, with COVID-19 incidence, metropolitan status of the county and anxiety search popularity as covariates, and mask-wearing status as the exposure variable. 2019 data, no mask-wearing, was used as a calibration control for acne search weight. RESULTS The final dataset consisted of 2893 counties with complete cases. Frequent mask-wearing was associated with an important increase in acne search popularity (OR=1.69; 95% CI (1.30-2.21); P<.001). A high relative incidence of COVID-19 was associated with an even greater acne search popularity (OR=8.42; 95% CI (6.48-10.96); P<.001). CONCLUSIONS Despite various biases, the use of infodemiology will keep increasing. Observational statistical methods need to be adapted to manage the large amounts of bias concerning web-based information more efficiently.

Telehealth Use By Persons with Disabilities During the COVID-19 Pandemic

Telehealth use rapidly expanded during the COVID-19 pandemic. Understanding if, and how, people from disabilities used telehealth during the pandemic is vital to assuring this evolving and increasingly common form of health care is equitably developed and delivered to avoid reproducing the health disparities people with disabilities already face. Our aim was to explore the use of telehealth among people with disabilities during the pandemic. We conducted a weighted secondary analysis of United States Census Bureau data (April-July 2021) from 38,512 (unweighted) people with disabilities. Our findings revealed 39.8% of people with disabilities used telehealth during the second year of the pandemic, ranging from 34.5% of people with hearing disabilities to 43.3% of people with mobility disabilities. There were also differences in telehealth use based on sociodemographics. Telehealth promises to open doors to more equitable health care access for many people with disabilities, but only if access barriers are removed.

Immigrant Essential Workers During the COVID-19 Pandemic

The COVID-19 pandemic affected everyone in the United States, and essential workers across industries like health care, agriculture, retail, transportation and food supply were key to our survival. Immigrants, overrepresented in essential industries but largely invisible in the public eye, were critical to our ability to weather the pandemic and recover from it. But who are they? How did they do the riskiest of jobs in the riskiest of times? And how were both U.S.-born and foreign-born residents affected? This report explores the crucial contributions of immigrant essential workers, their impact on the lives of those around them, and how they were affected by the pandemic, public sentiment and policies. It further explores the contradiction of immigrants being essential to all of our well-being yet denied benefits, protections and rights given to most others. The pandemic revealed the significant value of immigrant essential workers to the health of all Americans. This report places renewed emphasis on their importance to national well-being. The report first provides a demographic picture of foreign-born workers in key industries during the pandemic using U.S. Census Bureau American Community Survey (ACS) data. Part I then gives a detailed narrative of immigrants’ experiences and contributions to the country’s perseverance during the pandemic based on interviews with immigrant essential workers in California, Minnesota and Texas, as well as with policy experts and community organizers from across the country. Interviewees include: ■ A food packing worker from Mexico who saw posters thanking doctors and grocery workers but not those like her working in the fields. ■ A retail worker from Argentina who refused the vaccine due to mistrust of the government. ■ A worker in a check cashing store from Eritrea who felt a “responsibility to be able to take care of people” lining up to pay their bills. Part II examines how federal and state policies, as well as increased public recognition of the value of essential workers, failed to address the needs and concerns of immigrants and their families. Both foreign-born and U.S.-born people felt the consequences. Policies kept foreign-trained health care workers out of hospitals when intensive care units were full. They created food and household supply shortages resulting in empty grocery shelves. They denied workplace protections to those doing the riskiest jobs during a crisis. While legislation and programs made some COVID-19 relief money available, much of it failed to reach the immigrant essential workers most in need. Part II also offers several examples of local and state initiatives that stepped in to remedy this. By looking more deeply at the crucial role of immigrant essential workers and the policies that affect them, this report offers insight into how the nation can better respond to the next public health crisis.

Moving Toward an Age-Friendly University: Survey Process of GSU 50+ Students

The proportion of Georgia’s population that is 60 years and older is growing rapidly. The 2010 U.S. Census Bureau predicted a growth of more than 20% of older adults by the year 2030. Georgia residents who are 62 and older are eligible to take courses at no or little cost at public state colleges. Due to the expected increase in Georgia’s aging population, access to a free university education, and the large number of currently enrolled 62+ students at Georgia State University (GSU), it is crucial that GSU become an Age-Friendly University. During Fall 2019, a survey was distributed to 1046 students aged 50 years plus; 411 completed the survey (39% response rate). This presentation describes the process involved in designing and distributing the survey. Unique aspects of the survey’s development include the cross-generational and interdisciplinary contributions of the student, faculty, affiliates, and staff from GSU’s Gerontology Institute. The goal was to learn more about GSU students 50 years and older by assessing their motivation for attending school, challenges on campus, perceptions of how the university is currently addressing their needs, factors/resources that have helped/are helping them to adjust to school, and the extent to which they experience age discrimination on campus. The long-term goal of the survey is to use this information to direct GSU in becoming an Age-Friendly University.

Do Smart Cities Technologies Contribute to Local Economic Development?

Governments around the world are exploring strategies that contribute to increased government performance and economic development that enable them to meet the service-tax expectations of their citizens. Within the framework of technology use in public management, this sudy examines the effects of smart cities technologies on the importance that chief administrative officers attach to local economic development. Drawing on the Digital Era Governance (DEG) model for theoretical context, this study uses logistic regressions derived from the 2016 International City/County Management Association survey on smart cities and the U.S. Census Bureau. The results show that the level of commitment to, the extent of engagement with, and the barriers faced in implementing smart cities technologies are associated with the importance of local economic development. Among other variables, poverty and education were also found to be significant predictors of the importance of local economic development.

To determine the effect of healthcare policy implementation on the COVID-19 pandemic.

As the Delta variant of SARS-CoV-2 has spread across the USA, some states have been impacted in different ways than others. This is due to factors such as the implementation of public health guidelines, primarily mask usage, and vaccination rates. With the Delta variant already causing much damage and with newer variants mutating, it is imperative to understand the spread of the Delta variant of SARS-CoV-2. The study examined five states - Minnesota, Iowa, Missouri, Arkansas, and Louisiana - and their respective COVID-19 cases. Data on these states were collected from the US Census Bureau and the CDC. The data was then compared between each state as well as to the USA. Finally, the data were analyzed and visualized using statistics software. First, COVID-19 cases were normalized by dividing by population in millions to get a standard measure, Daily Cases Per Million (DPCM), to compare the five states. Next, we used the CDC data to create a timeline, which was used to compare case data between states. Additionally, the CDC data was used to compare states concerning non-communicable disorders. Our analysis showed that the vaccination rate reduced while the masking mandates were interrupted for more than two months, with a rapid rise in delta variant of COVID-19 virus. Thus, from the study, it can be concluded that vaccines and mask usage are the most critical factors in preventing COVID-19 transmission.

Exploring the Patterns and Drivers of Urban Expansion in the Texas Triangle Megaregion

As the world becomes increasingly urbanized, it is vital for planners and policy-makers to understand the patterns of urban expansion and the underlying driving forces. This study examines the spatiotemporal patterns of urban expansion in the Texas Triangle megaregion and explores the drivers behind the expansion. The study used data from multiple sources, including land cover and imperviousness data from the National Land Cover Database (NLCD) 2001–2016, transportation data from the Texas Department of Transportation (TxDOT), and ancillary socio-demographic data from the U.S. Census Bureau. We conducted spatial cluster analysis and mixed-effect regression analysis. The results show that: (1) urban expansion in the Texas Triangle between 2001 and 2016 showed a decreasing trend, and 95% of the newly urbanized land was in metropolitan areas, especially at the periphery of the central cities; (2) urban expansion in non-metropolitan areas displayed a scattered pattern, comparing to the clustered form in metro areas; (3) the expansion process in the Texas Triangle exhibited a pattern of increased development compactness and intensity; and (4) population and economic growth played a definitive role in driving the urban expansion in the Texas Triangle while highway density also mattered. These results suggest a megaregion-wide emerging trend deviating from the sprawling development course known in Texas’ urban growth history. The changing trend can be attributed to the pro-sustainability initiatives taken by several anchor cities and metropolitan planning agencies in the Texas Triangle.