research
2022
- JGIMThe Impact of COVID-19 on Routine Medical Care and Cancer ScreeningWenger, Neil S, Stanton, Annette L, Baxter-King, Ryan, Sepucha, Karen, Vavreck, Lynn, and Naeim, ArashJournal of general internal medicine 2022
Background COVID-19 restrictions and fear dramatically changed the use of medical care. Understanding the magnitude of cancelled and postponed appointments and associated factors can help identify approaches to mitigate unmet need.
Objective To determine the proportion of medical visits cancelled or postponed and for whom. We hypothesized that adults with serious medical conditions and those with higher anxiety, depressive symptoms, and avoidance-oriented coping would have more cancellations/postponements.
Design Four nationally representative cross-sectional surveys conducted online in May, July, October, and December 2020.
Participants 59,747 US adults who completed 15-min online surveys. 69% cooperation rate.
Measures Physical and mental health visits and cancer screening cancelled or postponed over prior 2 months. Plan to cancel or postpone visits over the next 2 months. Relationship with demographics, medical conditions, local COVID-19 death rate, anxiety, depressive symptoms, coping, intolerance of uncertainty, and perceived COVID-19 risk.
Key Results Of the 58% (N = 34,868) with a medical appointment during the 2 months before the survey, 64% had an appointment cancelled or postponed in May, decreasing to 37% in December. Of the 41% of respondents with scheduled cancer screening, 20% cancelled/postponed, which was stable May to December. People with more medical conditions were more likely to cancel or postpone medical visits (OR 1.19 per condition, 95% CI 1.16, 1.22) and cancer screening (OR 1.20, 95% CI 1.15, 1.24). Race, ethnicity, and income had weak associations with cancelled/postponed visits, local death rate was unrelated, but anxiety and depressive symptoms were strongly related to cancellations, and this grew between May and December.
Conclusions Cancelled medical care and cancer screening were more common among persons with medical conditions, anxiety and depression, even after accounting for COVID-19 deaths. Outreach and support to ensure that patients are not avoiding needed care due to anxiety, depression and inaccurate perceptions of risk will be important. - JMIR MHDepressive Symptoms and Anxiety During the COVID-19 Pandemic: Large, Longitudinal, Cross-sectional SurveyMacDonald, James J, Baxter-King, Ryan, Vavreck, Lynn, Naeim, Arash, Wenger, Neil, Sepucha, Karen, and Stanton, Annette LJMIR Mental Health 2022
Background: The COVID-19 pandemic has influenced the mental health of millions across the globe. Understanding factors associated with depressive symptoms and anxiety across 12 months of the pandemic can help identify groups at higher risk and psychological processes that can be targeted to mitigate the long-term mental health impact of the pandemic.
Objective: This study aims to determine sociodemographic features, COVID-19-specific factors, and general psychological variables associated with depressive symptoms and anxiety over 12 months of the pandemic.
Methods: Nationwide, cross-sectional electronic surveys were implemented in May (n=14,636), July (n=14,936), October (n=14,946), and December (n=15,265) 2020 and March/April 2021 (n=14,557) in the United States. Survey results were weighted to be representative of the US population. The samples were drawn from a market research platform, with a 69% cooperation rate. Surveys assessed depressive symptoms in the past 2 weeks and anxiety in the past week, as well as sociodemographic features; COVID-19 restriction stress, worry, perceived risk, coping strategies, and exposure; intolerance of uncertainty; and loneliness.
Results: Across 12 months, an average of 24% of respondents reported moderate-to-severe depressive symptoms and 32% reported moderate-to-severe anxiety. Of the sociodemographic variables, age was most consistently associated with depressive symptoms and anxiety, with younger adults more likely to report higher levels of those outcomes. Intolerance of uncertainty and loneliness were consistently and strongly associated with the outcomes. Of the COVID-19-specific variables, stress from COVID-19 restrictions, worry about COVID-19, coping behaviors, and having COVID-19 were associated with a higher likelihood of depressive symptoms and anxiety.
Conclusions: Depressive symptoms and anxiety were high in younger adults, adults who reported restriction stress or worry about COVID-19 or who had had COVID-19, and those with intolerance of uncertainty and loneliness. Symptom monitoring as well as early and accessible intervention are recommended. - PNASHow local partisan context conditions prosocial behaviors: Mask wearing during COVID-19Baxter-King, Ryan, Brown, Jacob R., Enos, Ryan D., Naeim, Arash, and Vavreck, LynnProceedings of the National Academy of Sciences 2022
Differences between Democrats and Republicans in rates of wearing a mask to stop the spread of COVID-19 are associated with the partisan balance of a neighborhood. The difference in rates grew larger as the share of Republicans in a neighborhood increased. This finding appears to be driven by decreased rates of mask wearing by Republicans who live among increasing numbers of Republicans (and not by Democrats in the same neighborhood). Theories about social pressure suggest these findings may be driven by the politicized and publicly observable nature of wearing a mask relative to other COVID-19 mitigation strategies, like vaccination. Neighborhood partisan composition was only weakly related to uptake of the COVID-19 vaccine and unrelated to uptake of flu vaccines. Does local partisan context influence the adoption of prosocial behavior? Using a nationwide survey of 60,000 adults and geographic data on over 180 million registered voters, we investigate whether neighborhood partisan composition affects a publicly observable and politicized behavior: wearing a mask. We find that Republicans are less likely to wear masks in public as the share of Republicans in their zip codes increases. Democratic mask wearing, however, is unaffected by local partisan context. Consequently, the partisan gap in mask wearing is largest in Republican neighborhoods, and less apparent in Democratic areas. These effects are distinct from other contextual effects such as variations in neighborhood race, income, or education. In contrast, partisan context has significantly reduced influence on unobservable public health recommendations like COVID-19 vaccination and no influence on nonpoliticized behaviors like flu vaccination, suggesting that differences in mask wearing reflect the publicly observable and politicized nature of the behavior instead of underlying differences in dispositions toward medical care.
2021
- JAMA SurgeryEffect of a Predictive Model on Planned Surgical Duration Accuracy, Patient Wait Time, and Use of Presurgical Resources: A Randomized Clinical TrialStrömblad, Christopher T., Baxter-King, Ryan G., Meisami, Amirhossein, Yee, Shok-Jean, Levine, Marcia R., Ostrovsky, Aaron, Stein, Daniel, Iasonos, Alexia, Weiser, Martin R., Garcia-Aguilar, Julio, Abu-Rustum, Nadeem R., and Wilson, Roger S.JAMA Surgery 2021
Accurate surgical scheduling affects patients, clinical staff, and use of physical resources. Although numerous retrospective analyses have suggested a potential for improvement, the real-world outcome of implementing a machine learning model to predict surgical case duration appears not to have been studied. To assess accuracy and real-world outcome from implementation of a machine learning model that predicts surgical case duration. Cases were assigned to machine learning–assisted surgical predictions 1 day before surgery and compared with a control group. The primary outcome measure was accurate prediction of the duration of each scheduled surgery, measured by (arithmetic) mean (SD) error and mean absolute error. Effects on patients and systems were measured by start time delay of following cases, the time between cases, and the time patients spent in presurgical area. The overall mean (SD) reduction of wait time was 33.1 minutes per patient (from 49.4 minutes to 16.3 minutes per patient). Improved accuracy did not adversely inflate time between cases (surgeon wait time). There was marginal improvement (1.5 minutes, from a mean of 70.6 to 69.1 minutes) in time between the end of cases and start of to-follow cases using the predictive model, compared with the control group. Patients spent a mean of 25.2 fewer minutes in the facility before surgery (173.3 minutes vs 148.1 minutes), indicating a potential benefit vis-à-vis available resources for other patients before and after surgery. Implementing machine learning–generated predictions for surgical case durations may improve case duration accuracy, presurgical resource use, and patient wait time, without increasing surgeon wait time between cases.
- JMIR PH & SEffects of age, gender, health status, and political party on COVID-19–related concerns and prevention behaviors: Results of a large, longitudinal cross-sectional surveyNaeim, Arash, Baxter-King, Ryan, Wenger, Neil, Stanton, Annette L, Sepucha, Karen, Vavreck, Lynn, and others,JMIR public health and surveillance 2021
Background: With conflicting information about COVID-19, the general public may be uncertain about how to proceed in terms of precautionary behavior and decisions about whether to return to activity.
Objective: The aim of this study is to determine the factors associated with COVID-19–related concerns, precautionary behaviors, and willingness to return to activity.
Methods: National survey data were obtained from the Democracy Fund + UCLA Nationscape Project, an ongoing cross-sectional weekly survey. The sample was provided by Lucid, a web-based market research platform. Three outcomes were evaluated: (1) COVID-19–related concerns, (2) precautionary behaviors, and (3) willingness to return to activity. Key independent variables included age, gender, race or ethnicity, education, household income, political party support, religion, news consumption, number of medication prescriptions, perceived COVID-19 status, and timing of peak COVID-19 infections by state.
Results: The data included 125,508 responses from web-based surveys conducted over 20 consecutive weeks during the COVID-19 pandemic (comprising approximately 6250 adults per week), between March 19 and August 5, 2020, approved by the University of California, Los Angeles (UCLA) Institutional Review Board for analysis. A substantial number of participants were not willing to return to activity even after the restrictions were lifted. Weighted multivariate logistic regressions indicated the following groups had different outcomes (all P<.001): individuals aged ≥65 years (COVID-19–related concerns: OR 2.05, 95% CI 1.93-2.18; precautionary behaviors: OR 2.38, 95% CI 2.02-2.80; return to activity: OR 0.41, 95% CI 0.37-0.46 vs 18-40 years); men (COVID-19–related concerns: OR 0.73, 95% CI 0.70-0.75; precautionary behaviors: OR 0.74, 95% CI 0.67-0.81; return to activity: OR 2.00, 95% CI 1.88-2.12 vs women); taking ≥4 medications (COVID-19–related concerns: OR 1.47, 95% CI 1.40-1.54; precautionary behaviors: OR 1.36, 95% CI 1.20-1.555; return to activity: OR 0.75, 95% CI 0.69-0.81 vs <3 medications); Republicans (COVID-19–related concerns: OR 0.40, 95% CI 0.38-0.42; precautionary behaviors: OR 0.45, 95% CI 0.40-0.50; return to activity: OR 2.22, 95% CI 2.09-2.36 vs Democrats); and adults who reported having COVID-19 (COVID-19–related concerns: OR 1.24, 95% CI 1.12-1.39; precautionary behaviors: OR 0.65, 95% CI 0.52-0.81; return to activity: OR 3.99, 95% CI 3.48-4.58 vs those who did not).
Conclusions: Participants’ age, party affiliation, and perceived COVID-19 status were strongly associated with their COVID-19–related concerns, precautionary behaviors, and willingness to return to activity. Future studies need to develop and test targeted messaging approaches and consider political partisanship to encourage preventative behaviors and willingness to return to activities.
2020
- Sci. Adv.Fatalities from COVID-19 are reducing Americans’ support for Republicans at every level of federal officeWarshaw, Christopher, Vavreck, Lynn, and Baxter-King, RyanScience Advances 2020
Between early March and 1 August 2020, COVID-19 took the lives of more than 150,000 Americans. Here, we examine the political consequences of the COVID-19 epidemic using granular data on COVID-19 fatalities and the attitudes of the American public. We find that COVID-19 has led to substantial damage for President Trump and other Republican candidates. States and local areas with higher levels of COVID-19 fatalities are less likely to support President Trump and Republican candidates for House and Senate. Our results show that President Trump and other Republican candidates would benefit electorally from a reduction in COVID-19 fatalities. This implies that a greater emphasis on social distancing, masks, and other mitigation strategies would benefit the president and his allies.