Difference between revisions of "Research Ethics"

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<onlyinclude>Impact evaluations often entail direct manipulation of people's personal or economic situations, collection of [[De-identification#Personally-Identifying Information | personal and/or sensitive data]], and publication of results that have direct implications for political or economic governance. Research designers must ensure that these tasks are undertaken in an ethical manner that protects the study population. This page outlines guidelines for ethical research before, during, and after data collection.
'''Research ethics''' make up the first pillar of the [https://github.com/worldbank/dime-standards/tree/master/dime-research-standards DIME Research Standards] compiled by [https://www.worldbank.org/en/research/dime/data-and-analytics DIME Analytics].
Impact evaluations often directly involve [[Protecting Human Subjects|human subjects]], and the [[Impact Evaluation Team|research team]] often [[Primary Data Collection|collects]] sensitive or [[Personally Identifiable Information (PII)|personal identifiable information (PII)]]. There are several ethical concerns related to handling personal data, and [[Data Publication|publishing]] results from a field study. The '''research team''' must ensure complete [[De-Identification|confidentiality]] of [[Survey Pilot Participants|respondents]], and respondents must be required to provide [[Informed Consent|informed consent]] which they can revoke at any time. This page outlines guidelines for ethical research before, during, and after data collection.


== Read First ==
== Read First ==

Revision as of 20:46, 14 May 2020

Research ethics make up the first pillar of the DIME Research Standards compiled by DIME Analytics. Impact evaluations often directly involve human subjects, and the research team often collects sensitive or personal identifiable information (PII). There are several ethical concerns related to handling personal data, and publishing results from a field study. The research team must ensure complete confidentiality of respondents, and respondents must be required to provide informed consent which they can revoke at any time. This page outlines guidelines for ethical research before, during, and after data collection.

Read First

Guidelines

Ethics Before Data Collection

Any research that involves economic intervention or data collection on specific individuals is almost certainly subject to human subjects ethics rules, including pre-approval by an institutional review board, as well as a human subjects education certificate from the NIH or other body for each researcher or assistant handling implementation or data.

In practice, ethics rules may or may not require informed consent from individual research participants, depending on the design and purpose of the study. For example, an IRB may grant approval to collect administrative data or health care provider data for public health reasons, given written consent from the appropriate government ministry or office. Similarly, when the information to be collected is not especially sensitive and affirmative consent might endanger the feasibility of the study, individualized consent may be possible to waive.

Ethics During Data Collection

Whether or not individualized informed consent is required, research that involves the collection of sensitive information – including but not limited to names, addresses, mobile phone numbers, bank or credit accounts, or location information – should be handled from collection to publication in a way that ensures the privacy of research participants. This means using appropriately secure electronic methods to collect and store data, appropriate data encryption on devices like laptops or hard drives, and anonymization of data before any public release.

Ethics After Data Collection

Once common concern in research is the possibility of manipulating results. Political factors, publication bias and other circumstances may pressure researchers to target findings, for example through P-hacking and selective reporting. To avoid this concern, researchers often choose to develop pre-analysis plans and pre-register studies. Sharing data and codes improves research reproducibility.

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