Inclusive and Intersectional Literature Searching
This guide is designed to provide a starting point to advance evidence-based practice toward health equity and justice for all patients and communities.
This guide is created in response to how racism, homophobia and transphobia, settler colonialism, and other systems of inequity are present not only in the personal spheres of our lives, such as prejudice and behavioral patterns of hate, but also in the routines and policies of institutions, including healthcare. Systemic health disparities are one such manifestation of this inequity at the institutional level. Examples exist and pervade medical research and clinical practices, as black, indigenous, and people of color (BIPOC), LGTBQI+ communities, women, and people in poverty experience among the highest health disparities, with poor health outcomes and healthcare barriers often linked to socioeconomic and educational disparities as well as discrimination. Perhaps more importantly, it is important to consider how race, class, gender, sexuality, and more intersect to reproduce these systemic disparities. Kimberlé Crenshaw coined the concept of intersectionality in 1989, addressing the oppression of black women, and it has developed to encompass how justice as well as injustices often engage across race, gender, class, and sexuality simultaneously. Intersectionality reveals that systems of inequity such as racism and sexism cannot be easily detangled and isolated from each other.
"Intersectionality is a lens through which you can see where power comes and collides, where it interlocks and intersects. It’s not simply that there’s a race problem here, a gender problem here, and a class or LBGTQ problem there. Many times that framework erases what happens to people who are subject to all of these things." - Kimberlé Crenshaw (2017)
You will find resources and techniques available through the Library and elsewhere to support the journeys of USAHS students, staff, and faculty in their commitment to healthcare justice and intersectional medicine. You can find recommended eBooks, scholarly literature, and other resources on the topics of topics ranging from racism in medicine to LGBTQI+ health disparities, search strategies for finding relevant literature for your evidence-based practice, and ways to contextualize your research approach under an intersectional and inclusive framework.
While the biases listed below are not necessarily equivalent to racism, transphobia, and other forms of systems of inequity, they can certainly play a role in reproducing discriminatory research practices and work against cultural competence.
- Search satisficing - This bias occurs when the researcher concludes the literature search as soon as they find any information that meets the criteria of their topic or question. While the information might be relevant, it may not constitute the best possible answer to the question. For example, a researcher might only consider the first few sources listed on the first page of the search results.
- Premature closure - This bias occurs when the researcher concludes the literature search when they find very little information or no information at all. The researcher assumes that if they did not readily find the information, then it must not exist. This bias is particularly likely if the researcher is hurried or inexperienced, or if they are only familiar with using one database.
- Confirmation bias - The tendency to search for, focus on, and remember information in a way that affirms and reinforces the researcher's prior beliefs and attitudes. If the researcher has particularly strong feelings toward an issue (e.g., vaccination, alternative and complimentary medicine, reproductive matters), they may overlook evidence that contradicts their approach.
- Attribute substitution - This bias essentially results from the researcher simplifying a complex topic or question in a way that leaves out important information. While simplification can be very useful in literature search, as demonstrated by the PICO technique, it becomes problematic when the simplification alters the topic or question. For example, the researcher may not consider the patient's cultural or ethnic background as they generalize their literature search.
- Focusing effect - The bias in which the researcher over-prioritizes one aspect of the topic or question at the expense of considering other relevant facets such as the patient's history or background.
- "Not-invented-here" bias - This bias manifests when the researcher places more value on information written and published in their own country. Yet the researcher may be missing out on crucial evidence that exists in another part of the world where there is a higher incidence of the given disease or they offer alternative interventions and approaches, and where more published evidence would likely be found as a result. Particularly for U.S. researchers, it is important to realize that several countries are farther ahead in the domains of evidence-based medicine and practice.
- Overconfidence - A very common bias in which the researcher believes they know more than what they actually do. When we assume that we know the potential answer to the topic or question, then we are likely to fail to conduct a comprehensive and systematic search for evidence. Overconfidence can make it more difficult to address other biases as the researcher may proceed in their search unheeded, only finding evidence that matches exactly what they put into their search query and only what they found from their preferred database.
- Automation bias - This bias is demonstrated when the researcher places too much faith in their tools, or databases and search engines in this case. The strong faith in the reliability of internet search engines is one example of this bias. The researcher would do well to remember and acknowledge that each resource comes with limitations and biases.
- Preconceived notions - The bias in which the researcher informs their search with their own prior beliefs and attitudes, thereby limiting the success of their search. A researcher, for example, might believe that they will find all the information they require in one perfect peer-reviewed article in PubMed, published in English in a highly regarded journal within the last 3 years. This "unicorn" article rarely exists, as the information might be found in the gray literature or perhaps parts of the answer can be found across several different articles.
- Blindspot bias - A very problematic bias in which the researcher believes they are somehow less susceptible than others to experiencing any of the above cognitive biases, placing too much faith in their own ways of thinking.
While it could be argued that it is impossible to debias your own thinking, as you are trying to do so with the very same brain making the mistakes, there are a number of available techniques to help mitigate the impact of cognitive bias.
- Awareness of bias - The first step for a researcher to work toward debiasing a literature search is to acknowledge that everyone is prone to bias, including themselves.
- Metacognition - The technique that essentially involves thinking about thinking. The researcher should reflect on their search, considering the query itself as well as the strategies and resources being used (and not used). Ask themselves: Are they not considering the patient's specific needs and if so, what are those needs? It may require the researcher to take a step back from the search, for a few hours or over a good night's sleep, returning with refreshed clarity.
- Minimize obstacles - Make the tasks of the literature search easier. Perhaps look up concepts and terminology by referring to general sources such as a reference book or an online summary to develop a better understanding. If you are a clinician, ask the patient clarifying questions to consider for factors across race, gender, etc.
- Mental simulation - This technique engages the researcher to imagine themselves in the place of the patient. Think critically about the topic or question and its intended use. This technique is key to practicing cultural competence and conducting inclusive research.
- Consider the alternatives - The researcher should not limit themselves to using only preferred resources. There are likely other tools to consider for conducting a comprehensive search of the literature. The researcher and the clinician will serve themselves well by looking outside the self-referential worlds of filter bubbles and discipline-specific databases.
- Self-work - It is important for the researcher to address areas for improvement. Seek out specific, targeted training. Perhaps the researcher or clinician is not familiar with finding evidence about marginalized patients and populations, either through avoidance or a lack of awareness. Reviewing and applying lessons from guides such as this one, as well as consulting with your librarian, can help your practice of this technique.
- Feedback - Because the brain is inherently biased as discussed in this guide, it can be incredibly difficult to debias our own thinking. Seeking out feedback from colleagues and experts can be crucial. It might even be essential to involve the community under study in the research process from the very beginning to ensure respectful research practices.
- Self-care - The act of taking care of oneself is certainly relevant here. Sleep deprivation and even mild dehydration can affect our mental acuity, leaving us more prone to cognitive biases.
Many clinicians and other health providers utilize internet search engines such as Google and Bing to conduct searches for primary evidence. These search engines will often imbue a sense that the internet is an essential part of their cognitive toolbelt, with users feeling more confident in their knowledge. This ease of access and convenient retrieval of information can lead users, including clinicians, to depend on the evidence provided by internet search engines. The main issue with relying upon the results of an internet search is that these search engines are not typically designed in mind for a systematic or structured way to curate and assess the quality of available evidence, posing a risk for clinical decision-making errors.
Internet search engines are enabled with algorithms that will adapt to a user's search behavior. Internet search engines will respond to your search behavior by changing the search results based on your personal preferences. Internet search engines are in part designed to satisfy your search inquiries with information that is familiar or agreeable to you, which can lead the results to omit evidence (particularly contradicting information) that the search engine designates as less likely to be of interest to you.
This personalization of search information is compounded as our Internet search behavior can be highly prejudiced. We often have a strong faith in the evidence that is retrieved and shown by internet search engines, preferring the top-ranked search results even when they are not as relevant to our topics or questions. We are more likely to choose positive or affirming information over negative or contradicting information.
The proclivity for internet search engines to curate information based on our preferences and behavior ultimately produces a personal selection bias known as the filter bubble, in which the information available to a user is structured according to their beliefs and attitudes. There is a lack of transparency regarding under what criteria these search engines personalize information. While some internet search engines will allow users to use advanced searching techniques such as Boolean logic, they are not adequately comparable to the robust features offered by scholarly research databases. Google and other internet search engines heavily depend on personalized algorithms for the evaluation and prioritizing of search results. For example, a user will be directed to utilize the country-specific version of a search engine. The search engine will typically include variations and synonymous terms in a user's search query, independent of the user's control or awareness.
Systematic searching of evidence is not feasible using internet search engines as a result. Not only are the personalized algorithms constantly being modified, preventing the user from reproducing the same search despite using the same keywords, but the content of the internet is inherently unstable and ever-changing.
There are a few techniques to mitigating the impact of filter bubbles and personalized algorithms. However, it is important to realize that it is impossible to completely eliminate the problems embedded in internet search engines.
- Use internet search engines to find general background information about the topic or question, to develop a better understanding of relevant concepts and terminology to apply in searching scholarly research databases. Internet search engines, particularly Google Scholar, can still be useful when it comes to finding open-access full-text content.
- Do not rely solely on the results of internet search engines, diversifying your search by using scholarly research databases like PubMed.
- You can minimize the effects of personalized algorithms by doing the following:
- Logging out of your personal browser accounts.
- Automatically or manually clearing your internet search history.
- Disabling internet history options.
- Using anonymous browser options.
- Using advanced search features when available.
Scholarly research databases may have their own biases. For example, PubMed and Ovid MEDLINE have a bias toward pathology, which mirrors the bias in U.S. healthcare and medicine, in that something must be wrong in order to fix it. Looking at PubMed's journal selection, the predominant focus of the database is biomedical topics and life sciences. Topics positioned further away from these fields are less likely to be included and therefore findable in PubMed. While you may find some literature concerning education-related concepts as they relate to the health and medical sciences, but more generalized publications on education would be better discovered in other databases like ProQuest.
As emerging and experienced clinicians, the need for evidence-based practice often calls for searching through scholarly databases to find evidence to substantiate good clinical decision-making. PubMed among other databases are among the more popular databases of this caliber, and for good reason as they focus on topics and issues of health and medicine. It is essential to develop knowledge and skills to maximize your search, finding the literature that includes the experiences and needs of marginalized patients and populations.
Medical Subject Headings (MeSH) are subject categories and labels assigned to each article in PubMed to best describe what the given article is about. These terms are assigned by the National Library of Medicine. The terms come from the National Library of Medicine’s official thesaurus of words and phrases to represent different concepts and elements of the scholarly literature. For example, an article about tumors would be assigned the official MeSH term, Neoplasms. While MeSH is the default vocabulary in PubMed, you can also use MeSH terms when searching ProQuest, CINAHL, and several other databases.
New MeSH terms can be introduced to replace older, outdated subject terminology. The process to introduce new MeSH terms can be slow and may not be able to reflect the changing landscape of terminology, especially when it comes to topics like race and other population or society related concepts. So you may find yourself having to use outdated and sometimes even offensive terms to find older literature. You may also find that using more current terminology limits your results to only recently published literature.
This guide provides a list of recommended MeSH terms to consider when searching for marginalized communities in the medical literature. However, you may realize that some of these MeSH may be too broad or do not exactly pertain to your population. For example, you might miss out on specific nuances in certain groups and communities. Take the generational terms for Japanese Americans, for example, such as Issei (referring to first-generation Japanese Americans) and Nisei (referring to second-generation Japanese Americans). The MeSH vocabulary does not have terms for either generation, let alone for Japanese Americans. Asian Americans would be preferred MeSH term in this case. You can use keywords such as Nisei, Issei, and even Japanese American as search terms in combination with appropriate MeSH terms to narrow the scope of your results.
Through the Library, you have comprehensive access to a wide variety of ebooks that focus on systemic health disparities among marginalized patients and communities as well as culturally competent research practices and ethics.
This selection of eBooks available through the Library is certainly not exhaustive, but these eBooks highlight the growing wealth of research and knowledge sustained by BIPOC and LGBTQI+ communities, women, and people in poverty in addition to ally researchers and clinicians that is often left overlooked or neglected in the face of mounting health disparities.
To access one of these eBooks on display:
1) Click on the display you want to explore. This will open a PDF.
2) Use that PDF to click on the specific title you would like to find in our eBook collections.
3) Log in with your USAHS credentials and start reading.
Do you have a resource to recommend? Let us know by emailing your library staff at [email protected].
AHRQ Health Care: Minority Health - The Agency for Healthcare Research and Quality (AHRQ) is the leading federal agency charged with improving the safety and quality of the U.S. health care system. They provide minority health fact sheets that cover activities for participatory research as well as other research activities relevant to indigenous peoples in the United States.
DiversityRx - DiversityRx informs, educates, and supports health care providers, policymakers, researchers, and advocates who share our goals. They facilitate the exchange of knowledge and information among professional colleagues. They provide professional development opportunities and resources on key practice and policy issues. They also spearhead research and policy development, and advocate for culturally responsive care. They have a comprehensive database of cultural resources available for researchers and clinicians to use for culturally responsive care.
Ethnomed - The objective of the website is to make information about culture, language, health, illness and community resources directly accessible to health care providers who see patients from different ethnic groups. EthnoMed was designed to be used in clinics by care providers in the few minutes before seeing a patient in clinic. For instance, before seeing a Cambodian patient with asthma, a provider might access the website to learn how the concept of asthma is translated and about common cultural and interpretive issues in the Cambodian community that might complicate asthma management. A practitioner could also download a patient education pamphlet in Khmer (Cambodian language) to give to the patient.
GASP Measures Database - A free public resource that basically provides "one-stop shopping" for researchers seeking measures designed for lesbian/gay/bisexual issues or populations. You can browse the entire list, or you can search for measures focusing on particular topics, such as internalized homophobia or identity development. Information about each measure can include its general intent, length, original citation, detailed psychometric information, contact information for the author, etc. The scale itself is included, when possible.
ICPSR - The Inter-university Consortium for Political and Social Research maintains a data archive of more than 250,000 files of research in the social and behavioral sciences. It hosts 21 specialized collections of data in education, aging, criminal justice, substance abuse, and other fields. You can access and download datasets regarding LGBTQI+ health, race and ethnicity information, and more. Users of ICPSR data are required to send them bibliographic citations for each completed manuscript or thesis abstract. This allows them to provide funding agencies with essential information about use of archival resources and facilitates the exchange of information about the research activities of principal investigators.
LGBTData.com - An open-access clearinghouse for the collection of sexual orientation & gender identity data and measures. This site also provides knowledgeable analysis, commentary and expert "how to" information on gathering such data effectively in scientific surveys, questionnaires and studies. You will find numerous datasets and links to rich data sources that are essential to LGBT health research, researchers, students, advocates and anyone interested in scientific-based information about LGBT people and populations.
MedEdPortal Diversity, Inclusion, and Health Equity Collection - Features peer-reviewed educational resources for educators to advance institutional efforts in creating a diverse and inclusive culture and climate for all in order to drive clinical, educational, research and service excellence.
MedlinePlus for Population Groups - Presents high-quality, relevant health and wellness information that is trusted, easy to understand. Of particular note, you can gain access to information about cultural, racial, and ethnic groups in addition to other populations. These population profiles include encyclopedic information, statistics, research, and other relevant information.
Native Health Database - Contains bibliographic information and abstracts of health-related articles, reports, surveys, and other resource documents pertaining to the health and health care of American Indians, Alaska Natives, and Canadian First Nations. The database provides information for the benefit, use, and education of organizations and individuals with an interest in health-related issues, programs, and initiatives regarding North American indigenous peoples. Does not necessarily give free full text access. Please check Search USA for USAHS's access to a particular article.
Native Voices: Native Peoples' Concepts of Health and Illness - An online exhibition that explores the interconnectedness of wellness, illness, and cultural life for Native Americans, Alaska Natives, and Native Hawaiians. You can discover how Native concepts of health and illness are closely tied to the concepts of community, spirit, and the land.
Racial Equity Tools - Designed to support individuals and groups working to achieve racial equity. This site offers tools, research, tips, curricula and ideas for people who want to increase their own understanding and to help those working toward justice at every level – in systems, organizations, communities and the culture at large, and that also include healthcare and health disparities. You can find population and issues statistics, research, and teaching materials.
Finding Answers Intervention Research (FAIR) Database - A searchable tool containing 388 journal article summaries, distilled from 11 systematic reviews of the published health disparities literature. The database allows individuals to find targeted research that applies to their area of interest, and specific to their patient population, disease, and intervention. Use this database to generate ideas for disparities reduction interventions, and to collect ideas of research questions and interventions that have already been explored. Does not necessarily give free full text access. Please check Search USA for USA's access to a particular article.