Inclusive Research Collective
Designing Your Experiment
in vitro
In vitro research investigates an isolated system in a controlled environment, for example cells in a petri dish or molecules in a blood sample. It can be easy to forget that the biological samples used in in vitro work are taken from a living subject and have an attached identity and set of characteristics, which themselves may affect your experimental outcomes.
Recommendations for in vitro study design:
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Find out the background of your sample. This might include characteristics such as the ancestry or age of the donor. Consider the implications of conducting your experiments on one identity, and whether you can run your experiment with multiple, diverse samples.
See also:
- The Need for Cell Lines from Diverse Ethnic Backgrounds for Prostate Cancer Research (Badal et al)
- 'Inclusive Basic Research': IRC Seminar with Dr Simone Badal
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Represent all sex expressions available for your sample- e.g. in a study investigating blood biomarkers for humans, use samples from men, women and if possible intersex variations. For research to be generalisable and representative we must represent all sex expressions in our work.
See also:
- Sex and Gender in Biomedical Research (CIHR online training course)
in vivo
(animal)
In vivo research investigates phenomena inside a living organism: in this case, inside animals. Like in vitro work, in vivo animal work is often conducted under the assumption that the results are broadly generalisable across species. Stringent controlling for confounding variables can violate this assumption.
Recommendations for in vivo animal study design:
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Represent all sex expressions available for your chosen animal model. For example, in C. elegans this would involve conducting your experiments on both hermaphrodite and male animals, whereas in mice both male and female sexes should be used. Preference for studying only one sex expression is largely due to infrastructure limitations (costs, space) and historical attitudes. However, for research to be truly generalisable we must represent all sex expressions in our work.
See also:
- Prevalence of sexual dimorphism in mammalian phenotypic traits (Karp et al)
- 'Inclusive Basic Research': IRC Seminar with Dr Natasha Karp
- Meta-Research: A 10-year follow-up study of sex inclusion in the biological sciences (Woitowich et al)
General resources for in vivo experimental design:
- Experimental Design Assistant (NC3Rs)
- ARRIVE Guidelines for Experimental Design (ARRIVE)
- Best Practice in Experimental Design (Video by NC3Rs)
The recommendations below specifically deal with improving inclusivity in your experimental design. Beyond these recommendations, you should be designing your experiments to be adequately powered, controlled for confounding variables/biases and able to answer your research question.
in vivo
(human)
In vivo human research investigates phenomena inside living human beings. There are many ways human participant research can be biased or exclusionary.
Recommendations for in vivo human study design:
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Involve Patient & Public Involvement (PPI) groups as early on as possible. PPI groups are an invaluable resource and can advise on many study aspects such as recruitment and study design.
See also:
- PPI Resources for Researchers (People in Health West of England)
- Public Involvement (Health Research Authority)
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Think about the ideal and probable demographics of your study participants. Minoritised identities are often under-represented in research, and you should do all that you can to make sure your study population is diverse. This includes thinking about your inclusion/exclusion criteria, recruitment methods, identifying existing databases of potential participants and identifying existing community relationships. Discuss participant demographics with your supervisors early on to make sure you are aware of all of the resources available for diverse recruitment.
See also:
- Improving inclusion of under-served groups in clinical research: INCLUDE Guidance (NIHR)
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Carefully consider your inclusion and exclusion criteria. Many studies use inappropriate blanket exclusion criteria to reduce cost, cut corners or because of tradition. Respective examples include the exclusion of participants who require language interpreters, exclusion of people with disabilities and the exclusion of women from clinical trials. Your inclusion and exclusion criteria should be kept to a minimum, must have clear justification and be as inclusive as possible.
See also:
- Designing Inclusion and Exclusion Criteria (Hornberger & Rangu)
- Ensuring that COVID-19 research is inclusive: guidance from the NIHR INCLUDE project (NIHR)
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Think about the equipment and techniques you will use for your data collection. Are they suitable for a diverse group of participants, or are there accessibility or technological limitations which could lead to you rejecting potential participants from taking part in the study?
See also:
- 'Inclusive Human Participant Research' (IRC Seminar) with Arnelle Etienne
- Racial Bias in Pulse Oximetry Measurement (Sjoding et al)
- Universal Design for Inclusive Research (article by N. Heydarian)
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Make sure your participant-facing documents and communication methods are accessible.
See also:
- Improve accessibility with the Accessibility Checker (for Microsoft Office applications)
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Collect good data on your participant demographics. It is important to know whether your study population are representative of your target population, and good practice for acknowledging and recording representation of minoritised groups in research. When designing your demographics surveys, also consider the diversity of identities you might encounter and move beyond the traditional categories (e.g. Sexuality defined as Heterosexual or Homosexual).
See also:
- Inclusive Demographic Data Collection (Harvard University)
- Social determinants of health in mental health care and research: a case for greater inclusion (Deferio et al)