Call for Abstracts
TechQuity Volume: Call for Abstracts
IBM, Brigham and Women’s Hospital (BWH), and Vanderbilt University Medical Center (VUMC) invite you to submit abstracts for papers to be included in a supplemental issue of the Journal of Health Care for the Poor and Underserved (JHCPU). This issue will focus on what has been termed “TechQuity”, or the consideration, design, development, and implementation of technology solutions that promote, assure and potentially enhance health equity.
The deadline for submission of abstracts is midnight Pacific time on August 20, 2020.
All abstracts should be submitted through REDCap using this link: https://redcap.vanderbilt.edu/surveys/?s=ED79938LRH
The purpose of the supplemental issue is to describe how technology can transform health, public health, and healthcare to promote health equity (aka, “TechQuity”).
Process: Submitted abstracts will be scored by the sponsoring organizations. Of those received, no more than 50 will result in an invitation to submit completed papers to the Journal. Invited papers need to be submitted no later than October 15, 2020 for consideration. We anticipate accepting approximately 20 of the submitted papers to be published.
Criteria: Abstracts will be scored on the following criteria:
- Relevance for underserved populations
- Relevance to the topics suggested by the overview below
- Quality of research
- Implications for techquity research or its application
- New insights for techquity research or its application
- Clarity and completeness of abstract
- Evidence that the authors are knowledgeable about existing scholarship on the topic they address
Overview of Issue:
The topics we hope to see addressed in submitted abstracts include the following:
- The design and use of technology to promote and assure health equity (aka, “TechQuity”).
- People of technology, health, public health, and healthcare (e.g., Workforce Diversity)
- Data (e.g., data collection, data integration, data diversity)
- Design and/or usability considerations for non-majority populations
- Analytics (i.e., equity dashboards, racism/discrimination measures, etc.)
- Artificial intelligence (e.g., transparent, ethical, and equitable AI; reducing bias/racism through humans + AI solutions)
- System issues (e.g., structural racism, stress/psychosocial factors, and their impact on health, public health, and healthcare delivery and workforce)
- We invite authors with relevant work to submit abstracts. Achieving health equity through technology requires the use of interdisciplinary methods, stakeholders, data, and policies.
Abstracts must be in English, no more than 250 words long, and sufficiently detailed for the scorers to evaluate the proposed paper in a fully informed way.
The authors should include, in addition to the abstract, a list of no fewer than five key words or phrases important for the proposed paper. For more information on the types of papers JHCPU accepts, please click the link below to view the author guidelines.
The authors must also include a cover letter, in which they supply the names, degrees, and affiliations of the authors, as well as any information they think it is important for the Guest Editors to know.
For paper types, please consult the Journal’s Information for Authors: https://www.press.jhu.edu/journals/journal-health-care-poor-and-underserved/author-guidelines
To develop a topic, choosing among (or combining several of) the following population parameters may prove helpful. While the supplement will be organized in terms of race/ethnicity, we also welcome work that — while including information about race/ethnicity — also bear on other characteristics of underserved populations, including sexual orientation [LGBTQIA], mental health and cognitive development, disability, and others. Work framing identities in terms of intersectionality are welcome, but this approach is not required.
African American (or Black)
Latino (or Hispanic) broken down by subgroups
Non-Hispanic White (or White)
American Indian/Alaska Native, broken down by subgroups
Pacific Islander, broken down by subgroups
Asian Americans, broken down by subgroups
Children (pre-school, school age, or combined)
Reproductive-aged women (including pregnancy, post-partum, gestational influences, and infancy)
Other demographic characteristics
Groups with low socioeconomic status