Anonymous Source of Data

Academic writers have the ethical responsibility to protect their sources of data, to inform participants of how personal information will be secured, and to inform participants when anonymity cannot be safeguarded. The informed consent document, reviewed prior to data collection, conveys the appropriate information to potential participants. In this way, participants understand whether or not they will be identifiable and how this affects their decision to participate. This entry elaborates on these three points.

Responsibility to protect sources coincides with the principles of respect for persons, beneficence, and justice as set forth in the National Commission for the Protection of Human Subjects of Biomedical and Behavioral Research’s 1979 report Ethical Principles and Guidelines for the Protection of Human Subjects of Research, commonly called the Belmont Report. These protections were designed to eliminate or minimize negative consequences to participants for engaging in the research process. These procedures are reviewed by Institutional Review Boards at organizations that conduct research. Researchers carefully evaluate how they will inform participants of how their information will be kept anonymous. Several procedures are listed here:

• 1.
  Do not ask for name, address, date of birth, Social Security number, or phone number. If names are needed to link data to their sources, ask the participant to provide a pseudonym. If an age is needed, ask for the age (not date of birth).
• 2.
  Have participants acknowledge acceptance of an informed consent document without providing a name. In online surveys, participants can read an informed consent document and click on the I Agree or I Disagree button. In this way, the researcher has a record of respondents’ consent, but cannot link individuals’ data to any identifying information.
• 3.
  When a signed informed consent form is collected, separate the form from the participants’ data as soon as possible or collect the consent forms separately from or prior to distribution of the data collection instrument or outset of an experiment.
• 4.
  If an e-mail address is requested for a follow-up interview or compensation, make sure the information is separated from the data as soon as possible. Two electronic surveys can be sequenced such that a second survey can capture identifying information without connecting individuals to data in the first survey. Data reports often appear in spreadsheet form. Thus, if identifiable information is connected to the data, a column can be selected, cut, and pasted into a new data file, separating the information from the data.

Researchers also have the responsibility to inform participants of how personal information will be secured. A common practice to protect sources of data is to use pseudonyms. Writing an excerpt from an interview can be challenging without using names, places, or other identifiers mentioned by the participants. Some of these clues, such as names of employers, companies employed, relational partners, or street names, for example, could help the sleuth reader detect who participants are. For example, David McMahan wrote an ethnographic essay about his experience working as a bartender/bouncer in a rural tavern. At the time of publication, McMahan worked at Missouri Western State University in St. Joseph, Missouri, a small city less than one hour from where I was raised. As I read the article, the setting was clearly a typical, small, Midwest community. As I read more details, I began to picture a local tavern I was familiar with in a community close to St. Joseph. Upon meeting McMahan at a conference, I asked if he had worked at the tavern I was [Page 40]thinking of. Whether the answer was yes or no, McMahan protected his source by replying that it was not. The description could apply to any number of establishments, but I couldn’t help but ponder the challenges to the ethnographer and qualitative researcher of trying to create the setting for the reader while simultaneously protecting the source of the data.

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