Local media burnout report (page 7)

Appendix: Method

Study population and sampling

Study population and sampling:

The target population in this study was local journalists across the U.S. Past studies of burnout in journalism have surveyed journalists by collecting their email information from their employers.

In this study, we aimed to measure burnout in journalists throughout the country, across print, digital, radio and television media. To get a better idea of how journalists are experiencing burnout, regardless of outlet or employer’s ability to send contact information, we decided to use a different method.

At the time of this study, Twitter was used by journalists to promote their reporting and look for sources, so many journalists put email addresses in their bios. Following Elon Musk’s purchase of Twitter and the exodus of outlets such as NPR from the website, this may no longer be a viable method for collecting contact information.

We compiled Twitter lists of local journalists by reviewing relevant local journalism Twitter accounts, such as prominent news organizations and news workers active on social media, in every U.S. state to find Twitter lists of reporters in each state.

We then ran a collection of these lists using a Python scraping tool we constructed and sorted out journalist emails, resulting in 4,573 usable emails. We sent our survey to journalists whose contact information we retrieved.

Data collection

Data collection

We constructed our survey questionnaire in Qualtrics and used the Qualtrics platform to send the survey to journalists via email.

The survey first asked questions from the Copenhagen Burnout Inventory, followed by questions related to job satisfaction, whether they were considering applying to other jobs including jobs outside journalism. We did this in order to ascertain if there is a correlation between high levels of burnout and looking for outside work, or if journalists are looking for work outside of journalism for reasons other than burnout.

Finally, we asked questions related to respondent demographics in order to ascertain whether there is a difference in responses across age, race as well as in type of role and beat. Questions relating to demographics were optional for respondents in case they did not feel comfortable sharing that information.

Methods of Analysis

Methods of Analysis

Analysis of variance (ANOVA) was used to identify factors contributing to personal, work-related, and source-related burnout, starting with the relationship among the three types of burnout. The results of this model indicate that personal burnout and work-related burnout indicated that both personal burnout (p < .0001) and work-related burnout (p < .0001) were statistically significant predictors of source-related burnout. This means that there is a statistically significant relationship between both personal and work-related burnout and source-related burnout.

The results of ANOVA for personal, work-related, and source-related burnout indicate that age and gender are statistically significant predictors of all types of burnout. Race was not a statistically significant predictor of any type of burnout. The tables below detail these analyses.

The results of a multiple regression model indicate a strong statistical relationship between work-related burnout and respondents thinking about leaving their job (p < .001). There was not a statistically significant relationship between source-related burnout or personal burnout and respondents thinking about leaving their jobs.

Due to the small number of respondents who identified as non-binary or other, we combined nonbinary respondents with those identifying as women for a joint category of “women and non-binary” for purposes of analysis. Due to the small size of racial groups other than white, we created a “BIPOC” group that contains all respondents who identified as non-white for purposes of analysis.

It is difficult to situate these demographics within industry diversity statistics. The News Leaders Association has not released data from its diversity survey since 2019 due to low response rates; however, the 2019 survey indicated that people of color made up about 22% of print and digital staff. The 2022 Radio Television Digital News Association survey found that people of color made up approximately 26% of TV staff and 18% of radio staff.

The lack of diversity among survey respondents is a limitation of this study. Burnout among journalists of color is an understudied but vital topic for further research, since those journalists must also navigate predominantly white newsroom structures and colleagues in addition to their jobs. Previous studies of burnout in journalism have attracted a less diverse group of respondents, in which 91% of respondents were Caucasian.


The authors would like to acknowledge the following for their support in data collection, number checking, and design:

Jessica Mahone, CISLM research director
Sarah Vassello, CISLM project manager
Callan Hazeldine, CISLM graduate student researcher
Clay Williams CISLM graduate student researcher
Jordan Davis, CISLM graduate student researcher
Caitlyn Yaede, CISLM intern

"Local media burnout report" table of contents

  1. Local media burnout report
  2. Who responded?
  3. Burnout in U.S. local journalists
  4. Burnout demographics
  5. Changes and leaving journalism
  6. Conclusion
  7. Appendix: Method