Factors Affecting Burnout Among Medical Assistants.

EXECUTIVE SUMMARY: Medical assistants-key professionals supporting physician practices-have not been studied with regard to burnout and professional fulfillment, which may affect other healthcare professionals. This study examined the factors associated with burnout among medical assistants in an academic healthcare organization while validating the use of a tool previously used to assess burnout in physicians. Using portions of the Professional Fulfillment Index (PFI) and questions designed for this mixed methods study, medical assistants employed across Stanford Health Care were surveyed. The authors assessed demographic characteristics and the impact of control, organizational culture, team knowledge, self-efficacy, and professional fulfillment/meaningfulness on burnout. Of the 505 eligible participants, 261 (52%) completed the survey; 76% were women. The study validated the PFI for use with this population and validated three additional scales. Burnout was found to be low among medical assistants (M = 2.32); professional fulfillment/meaningfulness of work was found to be high (M = 4.08). Organizational culture, professional fulfillment, and self-efficacy were found to be predictors of burnout (R2 = 0.438), with negative perceptions of organizational culture as the strongest predictor of burnout among medical assistants (ß = -0.34). These results indicate that a survey tool is useful in understanding components of burnout and professional fulfillment in this population. Although limited to one site, this study could be replicated in other organizations.

Likelihood of Unemployed Smokers vs Nonsmokers Attaining Reemployment in a One-Year Observational Study.

IMPORTANCE: Studies in the United States and Europe have found higher smoking prevalence among unemployed job seekers relative to employed workers. While consistent, the extant epidemiologic investigations of smoking and work status have been cross-sectional, leaving it underdetermined whether tobacco use is a cause or effect of unemployment. OBJECTIVE: To examine differences in reemployment by smoking status in a 12-month period. DESIGN, SETTING, AND PARTICIPANTS: An observational 2-group study was conducted from September 10, 2013, to August 15, 2015, in employment service settings in the San Francisco Bay Area (California). Participants were 131 daily smokers and 120 nonsmokers, all of whom were unemployed job seekers. Owing to the study's observational design, a propensity score analysis was conducted using inverse probability weighting with trimmed observations. Including covariates of time out of work, age, education, race/ethnicity, and perceived health status as predictors of smoking status. MAIN OUTCOMES AND MEASURES: Reemployment at 12-month follow-up. RESULTS: Of the 251 study participants, 165 (65.7) were men, with a mean (SD) age of 48 (11) years; 96 participants were white (38.2%), 90 were black (35.9%), 24 were Hispanic (9.6%), 18 were Asian (7.2%), and 23 were multiracial or other race (9.2%); 78 had a college degree (31.1%), 99 were unstably housed (39.4%), 70 lacked reliable transportation (27.9%), 52 had a criminal history (20.7%), and 72 had received prior treatment for alcohol or drug use (28.7%). Smokers consumed a mean (SD) of 13.5 (8.2) cigarettes per day at baseline. At 12-month follow-up (217 participants retained [86.5%]), 60 of 108 nonsmokers (55.6%) were reemployed compared with 29 of 109 smokers (26.6%) (unadjusted risk difference, 0.29; 95% CI, 0.15-0.42). With 6% of analysis sample observations trimmed, the estimated risk difference indicated that nonsmokers were 30% (95% CI, 12%-48%) more likely on average to be reemployed at 1 year relative to smokers. Results of a sensitivity analysis with additional covariates of sex, stable housing, reliable transportation, criminal history, and prior treatment for alcohol or drug use (25.3% of observations trimmed) reduced the difference in employment attributed to smoking status to 24% (95% CI, 7%-39%), which was still a significant difference. Among those reemployed at 1 year, the average hourly wage for smokers was significantly lower (mean [SD], $15.10 [$4.68]) than for nonsmokers (mean [SD], $20.27 [$10.54]; F(1,86) = 6.50, P = .01). CONCLUSIONS AND RELEVANCE: To our knowledge, this is the first study to prospectively track reemployment success by smoking status. Smokers had a lower likelihood of reemployment at 1 year and were paid significantly less than nonsmokers when reemployed. Treatment of tobacco use in unemployment service settings is worth testing for increasing reemployment success and financial well-being.