Exploring Representation of Diverse Samples in fMRI Studies Conducted in Patients With Cardiac-Related Chronic Illness: A Focused Systematic Review
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Identification of Disease-related Spatial Covariance Patterns using Neuroimaging Data
Published on: June 26, 2013
Lenette M Jones1, Emily Ginier2, Joseph Debbs1
1School of Nursing, University of Michigan, Ann Arbor, MI, United States.
Insights
Functional magnetic resonance imaging (fMRI) studies on cardiovascular disease (CVD) often lack diverse participants, primarily including older men and underrepresenting women and minority groups. Future research should prioritize inclusivity to improve tailored CVD self-management interventions.
Area of Science:
- Neuroscience and Medical Research
- Cardiovascular Health and Brain Function
Background:
- Cardiovascular disease (CVD) is a leading global cause of mortality, necessitating effective self-management strategies.
- Functional magnetic resonance imaging (fMRI) is utilized to explore brain-behavior connections relevant to CVD self-management.
Conclusions:
- Current fMRI research on CVD is characterized by a lack of diversity, particularly concerning gender, ethnicity, and age.
- There is a critical need for studies to include underrepresented populations to enhance the generalizability of findings.
- Future research should purposefully sample diverse groups to enable the development of tailored and equitable CVD interventions.
Abstract:
Introduction/Purpose: Cardiovascular disease (CVD) is the leading cause of death worldwide, and in the United States alone, CVD causes nearly 840,000 deaths annually. Using functional magnetic resonance imaging (fMRI), a tool to assess brain activity, researchers have identified some brain-behavior connections and predicted several self-management behaviors. The purpose of this study was to examine the sample characteristics of individuals with CVD who participated in fMRI studies. Methods: A literature search was conducted in PubMed, CINAHL, and Scopus. No date or language restrictions were applied and research methodology filters were used. In October 2017, 1659 titles and abstracts were identified. Inclusion criteria were: (1) utilized an empirical study design, (2) used fMRI to assess brain activity, and (3) focused on patients with CVD-related chronic illness. Articles were excluded if they: were theory or opinion articles, focused on mental or neuropathic illness, included non-human samples, or were not written in English. After duplicates were removed (230), 1,429 titles and abstracts were reviewed based on inclusion criteria; 1,243 abstracts were then excluded. A total of 186 studies were reviewed in their entirety; after additional review, 142 were further excluded for not meeting the inclusion criteria. Forty-four articles met criteria and were included in the final review. An evidence table was created to capture the demographics of each study sample. Results: Ninety eight percent of the studies did not report the racial or ethnic composition of their sample. Most studies (66%) contained more men than women. Mean age ranged from 38 to 78 years; 77% reported mean age ≥50 years. The most frequently studied CVD was stroke (86%), while hypertension was studied the least (2%). Conclusion: Understanding brain-behavior relationships can help researchers and practitioners tailor interventions to meet specific patient needs. These findings suggest that additional studies are needed that focus on populations historically underrepresented in fMRI research. Researchers should thoughtfully consider diversity and purposefully sample groups by including individuals that are: women, from diverse backgrounds, younger, and diagnosed with a variety of CVD-related illnesses. Identifying and addressing these gaps by studying more representative samples will help healthcare providers reduce disparities and tailor interventions for all CVD populations.
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