Chapter 4: Data Collection

Sreevarenya J -

Good Morning Everyone!

This week’s blog post will be about how I am doing my data collection. Although for my research project I am studying a specific population: nurses who work with Neonatal Abstinence Syndrome, I am looking into burnout specifically. 

After reading current literature on how burnout was studied in general in various populations, demographics, and countries, I came across a survey called the Maslach Burnout Inventory a.k.a the MBI. This questionnaire allows for the quantification of burnout and has been in use for more than 35 years in various countries. 

The MBI was my initial way of measuring burnout, however, later on I found out that this questionnaire required payment to be accessed. So in order for me to legally use this for my data collection, I would have to purchase some number of digital tests from the official page. This led to pursuing other options; I read multiple articles that detailed the pros and cons of different burnout measurement surveys currently in use, however, either they were paid or were not tested enough to be fully accurate. 

However, a friend of mine was doing a similar study with burnout and when she ran into the same exact problem she came across a survey known as the burnout assessment tool a.k.a the BAT and told me to check it out. 

Although the BAT is more recent in the scientific world, it is said to be an updated version of the MBI. The authors said that it was specifically developed to address some of the shortcomings of the Maslach Burnout Inventory. Even better is that the survey is completely free and can be accessed and used by anyone. 

It has 23 main questions and 10 secondary questions that are not necessary but could be included. It measures exhaustion, mental distance, cognitive impairment, and emotional impairment. All of the statements are about someone’s day to day situation and each statement applies to them. They are given five options: never, rarely, sometimes, often, and always. I am currently in the process of understanding how data analysis works. Stay tuned for next week!

Thank you for reading!

 

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