The role of financial security in loneliness or sadness among medicare-enrolled cancer survivors during the COVID-19 pandemic

Introduction This study aims to estimate the relative decreased rate of financial security and increased rate of loneliness or sadness during the COVID-19 pandemic and investigate the association between financial security and loneliness or sadness among Medicare beneficiaries with a cancer history. Material and Methods We examined population-based, cross-sectional data from the Medicare Current Beneficiary Survey COVID-19 Winter 2021 survey. The study cohort included 1632 Medicare beneficiaries (aged ≥65 years) with self-reported cancer history. The outcome was feelings of loneliness or sadness, and the independent variable was financial security during the 2020–2021 winter surge of COVID-19. We conducted weighted descriptive statistics, a cross-tabulation analysis, and multivariable logistic regression analyses. Results Overall, 18.8% of cancer survivors reported increased feelings of loneliness or sadness and 11.2% reported decreased financial security during the 2020–2021 winter surge of COVID-19. Cancer survivors who reported decreased financial security had 93% higher odds of increased feelings of loneliness or sadness compared to those who reported feeling more or about the same financial security (Adjusted odds ratio [AOR] = 1.93;95% Confidence Interval [CI] 1.25–3.01;p < 0.004). Discussion Decreased financial security and increased feelings of loneliness or sadness were prevalent among cancer survivors. Additional screenings and interventions beyond what are currently available are needed to ease the socioeconomic vulnerabilities experienced by cancer survivors.

Cannabis use among cancer survivors before and during the COVID-19 pandemic, 2019-2021.

We estimated the prevalence of past 30-day cannabis use, evaluated reasons for use, and identified individual-level factors associated with cannabis use among cancer survivors before (2019) and during (2020 and 2021) the COVID-19 pandemic. Cancer survivors, aged 18 years and older, were identified from the 2019 (n = 8185), 2020 (n = 11 084), and 2021 (n = 12 248) Behavioral Risk Factor Surveillance System. Prevalence of past 30-day cannabis use among survivors held steady through the pandemic (8.7%, 7.4%, and 8.4% in 2019, 2020 and 2021, respectively). Of those who used cannabis, 48.7% used it for medical reasons in 2019, 54.5% in 2020, and 43.5% in 2021. Survivors were more likely to report past 30-day cannabis use if they were younger, male, current or former tobacco smokers, and binge alcohol consumers and if they experienced poor mental health in the past 30-days. Our study identified subpopulations of cancer survivors that need to be targeted for evidence-informed discussions about cannabis use.

Topical analysis of migration coverage during lockdown in India by mainstream print media.

Implementing countrywide lockdown measures in India, from March 2020 to May 2020 was a major step to deal with the COVID -19 pandemic crisis. The decision of country lockdown adversely affected the urban migrant population, and a large section of them was compelled to move out of the urban areas to their native places. The reverse migration garnered widespread media attention and coverage in electronic as well as print media. The present study focuses on the coverage of the issue by print media using descriptive natural language text mining. The study uses topic modelling, clustering, and sentiment analysis to examine the articles on migration issues during the lockdown period published in two leading English newspapers in India- The Times of India and The Hindu. The sentiment analysis results indicate that the majority of articles have neutral sentiment while very few articles show high negative or positive polarity. Descriptive topic modelling results show that transport, food security, special services, and employment with migration and migrants are the majorly covered topics after employing Bag of Words and TF-IDF models. Clustering is performed to group the article titles based on similar traits using agglomerative hierarchical clustering.