All Publications


  • Descriptive Study of Employee Engagement With Workplace Wellness Interventions in the UK. Journal of occupational and environmental medicine Mulaney, B., Bromley-Dulfano, R., McShane, E. K., Stepanek, M., Singer, S. J. 2021; 63 (9): 719-730

    Abstract

    OBJECTIVE: To explore sequential steps of employee engagement in wellness interventions and the impact of wellness interventions on employee health.METHODS: Using previously collected survey data from 23,667 UK employees, we tabulated intervention availability, awareness, participation, and associated health improvement and compared engagement by participation and risk status.RESULTS: Employees' awareness of wellness interventions at their workplaces was often low (mean 43.3%, range 11.6%-82.3%). Participation was highest in diet/nutrition initiatives (94.2%) and lowest in alcohol counseling and smoking cessation interventions (2.1%). Employees with health risks were less likely than lower-risk employees to report awareness, participation, and health improvements from wellness interventions addressing the relevant health concern.CONCLUSION: Employers and policymakers should consider variation in intervention engagement as they plan and implement wellness interventions. Engaging employee populations with higher health risks requires a more targeted approach.

    View details for DOI 10.1097/JOM.0000000000002219

    View details for PubMedID 34491963

  • COVID-19 antibody seroprevalence in Santa Clara County, California. International journal of epidemiology Bendavid, E., Mulaney, B., Sood, N., Shah, S., Bromley-Dulfano, R., Lai, C., Weissberg, Z., Saavedra-Walker, R., Tedrow, J., Bogan, A., Kupiec, T., Eichner, D., Gupta, R., Ioannidis, J. P., Bhattacharya, J. 2021

    Abstract

    BACKGROUND: Measuring the seroprevalence of antibodies to Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2) is central to understanding infection risk and fatality rates. We studied Coronavirus Disease 2019 (COVID-19)-antibody seroprevalence in a community sample drawn from Santa Clara County.METHODS: On 3 and 4 April 2020, we tested 3328 county residents for immunoglobulin G (IgG) and immunoglobulin M (IgM) antibodies to SARS-CoV-2 using a rapid lateral-flow assay (Premier Biotech). Participants were recruited using advertisements that were targeted to reach county residents that matched the county population by gender, race/ethnicity and zip code of residence. We estimate weights to match our sample to the county by zip, age, sex and race/ethnicity. We report the weighted and unweighted prevalence of antibodies to SARS-CoV-2. We adjust for test-performance characteristics by combining data from 18 independent test-kit assessments: 14 for specificity and 4 for sensitivity.RESULTS: The raw prevalence of antibodies in our sample was 1.5% [exact binomial 95% confidence interval (CI) 1.1-2.0%]. Test-performance specificity in our data was 99.5% (95% CI 99.2-99.7%) and sensitivity was 82.8% (95% CI 76.0-88.4%). The unweighted prevalence adjusted for test-performance characteristics was 1.2% (95% CI 0.7-1.8%). After weighting for population demographics, the prevalence was 2.8% (95% CI 1.3-4.2%), using bootstrap to estimate confidence bounds. These prevalence point estimates imply that 53000 [95% CI 26000 to 82000 using weighted prevalence; 23000 (95% CI 14000-35000) using unweighted prevalence] people were infected in Santa Clara County by late March-many more than the 1200 confirmed cases at the time.CONCLUSION: The estimated prevalence of SARS-CoV-2 antibodies in Santa Clara County implies that COVID-19 was likely more widespread than indicated by the number of cases in late March, 2020. At the time, low-burden contexts such as Santa Clara County were far from herd-immunity thresholds.

    View details for DOI 10.1093/ije/dyab010

    View details for PubMedID 33615345

  • Prospectively Assigned AAST Grade versus Modified Hinchey Class and Acute Diverticulitis Outcomes. The Journal of surgical research Choi, J. n., Bessoff, K. n., Bromley-Dulfano, R. n., Li, Z. n., Gupta, A. n., Taylor, K. n., Wadhwa, H. n., Seltzer, R. n., Spain, D. A., Knowlton, L. M. 2020

    Abstract

    The American Association for the Surgery of Trauma (AAST) recently developed a classification system to standardize outcomes analyses for several emergency general surgery conditions. To highlight this system's full potential, we conducted a study integrating prospective AAST grade assignment within the electronic medical record.Our institution integrated AAST grade assignment into our clinical workflow in July 2018. Patients with acute diverticulitis were prospectively assigned AAST grades and modified Hinchey classes at the time of surgical consultation. Support vector machine-a machine learning algorithm attuned for small sample sizes-was used to compare the associations between the two classification systems and decision to operate and incidence of complications.67 patients were included (median age of 62 y, 40% male) for analysis. The decision for operative management, hospital length of stay, intensive care unit admission, and intensive care unit length of stay were associated with both increasing AAST grade and increasing modified Hinchey class (all P < 0.001). AAST grade additionally showed a correlation with complication severity (P = 0.02). Compared with modified Hinchey class, AAST grade better predicted decision to operate (88.2% versus 82.4%).This study showed the feasibility of electronic medical record integration to support the full potential of AAST classification system's utility as a clinical decision-making tool. Prospectively assigned AAST grade may be an accurate and pragmatic method to find associations with outcomes, yet validation requires further study.

    View details for DOI 10.1016/j.jss.2020.10.016

    View details for PubMedID 33248670

  • COVID-19 Solutions Are Climate Solutions: Lessons From Reusable Gowns Frontiers in Public Health Baker, N. M., Bromley-Dulfano, R., Chan, J., Gupta, A., Herman, L., Jain, N., Taylor, A. L., Lu, J., Pannu, J., Patel, L., Prunicki, M. 2020