Research Integrity & Ethical Considerations in Research Research Integrity Flashcards
what is research integrity?
- Involves conducting research in ways that allow others to have trust and confidence in the methods used and the findings that result.
- Also requires researchers meet professional standards.
Five principles:
- honesty,
- rigour,
- transparency,
- independence,
- Responsibility
What does being honest mean?
being accurate, being open, refraining from fabricating/untruth claims
what does being rigour mean
using scientific methods, exercising the best possible care in designing, undertaking, and reporting research
what does being transparent mean
be clear on how the research was based on, data were obtained, results were achieved
what does being independent mean
not allowing the research to be guided by nonscientific considerations, impartiality
how can they be responsible?
a researcher does not operate in isolation, conducting research scientifically and/or societally relevant.
Role description of research ethics committee (REC)?
- A research ethics committee is a group of people appointed to review
research proposals to assess formally if the research is ethical.- This means the research must conform to recognised ethical standards, which includes respecting the dignity, rights, safety and well-being of the people who take part.
why is research important?
- Research is a core part of the NHS and other care services.
- Research enables these services to improve the current and future health and wellbeing of the people they serve.
- However, research sometimes involves a degree of risk because researchers cannot predict the outcome with certainty.
- It may also involve additional burdens or intrusions exceeding those involved in normal care.
Common types of ethical issues
- voluntary participation
2.informed consent
3.anonmity
4.confidentialilty - potential for harm
- results communication
voluntary participation ?
Your participants are free to opt in or out of the study at any point in time.
informed consent?
Participants know the purpose, benefits, risks, and funding behind the
study before they agree or decline to join.
Anomity?
You don’t know the identities of the participants. Personally identifiable
confidentiality?
You know who the participants are but keep that information hidden from
everyone else. You anonymise personally identifiable data so that it can’t be linked to other data by anyone else.
potential for harm?
Physical, social, psychological, and all other types of harm are kept to an
absolute minimum.
Results communication?
You ensure your work is free of plagiarism or research misconduct, and
you accurately represent your results.
Data pseudonymisation?
- Data pseudonymisation is an alternative method where you replace identifiable information of participants with fake (pseudonymous) identifiers.
- The data can still be linked to the participants, but it’s harder to do so because you separate personal information from the study data.
How do you keep data confidentley?
- You store all signed consent forms in a locked file drawer and encrypt all files with data.
- Only other researchers directly involved in the study are allowed to access the study data, and you make sure that everyone knows and follows your institution’s data protection protocols.
- In a focus group study, you invite five people to give their opinions on a new student service in a group setting.
Before beginning the study, you ask everyone to agree to keep what’s discussed confidential and to respect each other’s privacy. You also note that you cannot completely guarantee confidentiality or anonymity so that participants are aware of the risks involved.
Psychological harm:
Sensitive questions or tasks may trigger negative emotions such as shame or anxiety.
Social harm
Participation can involve social risks, public embarrassment, or stigma.
Physical harm
Pain or injury can result from the study procedures.
Legal harm?
Reporting sensitive data could lead to legal risks or a breach of privacy.
Qualitive subject matter?
-experiences
-perception
-motivations
-intentions
Quantitive subject matter?
numerical data
