Faculty Bibliography

INTRODUCTION:The COVID-19 pandemic had clear impacts on mental health. Social media presents an opportunity for assessing mental health at the population level. OBJECTIVES:1) Identify and describe language used on social media that is associated with discourse about depression. 2) Describe the associations between identified language and COVID-19 incidence over time across several geographies. METHODS:We create a word embedding based on the posts in Reddit's /r/Depression and use this word embedding to train representations of active authors. We contrast these authors against a control group and extract keywords that capture differences between the two groups. We filter these keywords for face validity and to match character limits of an information retrieval system, Elasticsearch. We retrieve all geo-tagged posts on Twitter from April 2019 to June 2021 from Seattle, Sydney, Mumbai, and Toronto. The tweets are scored with BM25 using the keywords. We call this score rDD. We compare changes in average score over time with case counts from the pandemic's beginning through June 2021. RESULTS:We observe a pattern in rDD across all cities analyzed: There is an increase in rDD near the start of the pandemic which levels off over time. However, in Mumbai we also see an increase aligned with a second wave of cases. CONCLUSIONS:Our results are concordant with other studies which indicate that the impact of the pandemic on mental health was highest initially and was followed by recovery, largely unchanged by subsequent waves. However, in the Mumbai data we observed a substantial rise in rDD with a large second wave. Our results indicate possible un-captured heterogeneity across geographies, and point to a need for a better understanding of this differential impact on mental health.

Considering that the world population is rapidly aging and disability is a very frequent event in older adults, there is an increasing interest in studying their determinants, such as the neighborhood characteristics. Thus, this study aimed to explore the association between the social environment of the neighborhood and disability in older adults. A cohort study was assembled using waves 1 and 2 from the Study of Global Ageing and Adults Health (SAGE) in Mexico, which included adults with 55+ years old. Neighborhood characteristics - such as social participation, trust and safety - and individual covariates were measured only in wave 1 (baseline), while disability was measured in both waves to adjust for the score of wave 1. Multilevel negative binomial models with random intercepts at the municipality level were constructed for the disability score in wave 2, using each of the social environment variables as the main exposure and adjusting for the sociodemographic and health-related variables. Finally, interaction terms with sex, age, and socioeconomic quintiles were tested. Results showed that neighborhoods with a medium (IRR: 0.68; 95%CI: 0.53-0.87) or high (IRR: 0.67; 95%CI: 0.52-0.86) safety level were associated with a significant reduction in the disability score of adults older than 75 years, although there was no association between other characteristics of the social environment and disability in the general sample. Consequently, actions to improve safety in the neighborhoods should be carried out to help reduce the disability score in vulnerable older adults, especially in a context where safety is a critical issue, as in Mexico.

Objectives/UNASSIGNED:Skip-logic is commonly used on electronic surveys in which programs provide follow-up questions to affirmative responses and skip to the next topic in response to non-affirmative responses. While skip-logic helps produce data without contradictory responses, erroneous non-affirmative reports can lead to loss of accurate information. We examined the extent to which type-in drug use responses contradict unreported use in a survey of a high-risk population-electronic dance music (EDM) party attendees. Design/UNASSIGNED:We surveyed 1029 EDM party-attending adults (ages 18-40) using time-spacing sampling in 2018. We examined the extent to which reporting of recent drug use via type-in responses occurred after past-year use of the same drugs were unreported earlier on the same survey. Changes in prevalence of use and predictors of providing discordant responses were examined. Results/UNASSIGNED:< .001) were at higher odds of providing a discordant response. Conclusions/UNASSIGNED:Electronic surveys that query drug use can benefit from follow-up (e.g. open-ended) questions not dependent on previous responses, as they may elicit affirmative responses underreported earlier in the survey.

Low-dose computed tomography (LDCT), an accepted U.S. screening tool for early lung cancer detection, is not widely-used in Puerto Rico. We investigated knowledge and attitudes about LDCT in focus groups of primary care physicians (PCP) and individuals at high risk for lung cancer (HRI) in Puerto Rico. Transcribed/translated audio-recorded discussions were analyzed with the constant comparison method. Both groups had limited knowledge about LDCT and concerns regarding insurance coverage. Most HRIs had never had a provider recommend LDCT and believed that having symptoms was necessary to obtain LDCT screening. Perceived barriers included fears about results and the procedure; a perceived benefit was having early detection and possibly being cured. Few PCPs had ever recommended LDCT to a patient, with those who had basing their decision on symptoms/smoking history but having challenges with insurance. More education on LDCT is needed among HRIs, and U.S. Preventive Services Task Force guidelines should be widely distributed to encourage physician recommendations.