Dataset Information

Selection biases in technology-based intervention research: patients' technology use relates to both demographic and health-related inequities.

ABSTRACT:

Objective

Researchers conduct studies with selection biases, which may limit generalizability and outcomes of intervention research. In this methodological reflection, we examined demographic and health characteristics of implantable cardioverter defibrillator patients who were excluded from an informatics intervention due to lack of access to a computer and/or the internet.

Materials and methods

Using information gathered from surveys and electronic health records, we compared the intervention group to excluded patients on demographic factors, computer skills, patient activation, and medical history.

Results

Excluded patients were older, less educated, less engaged and activated in their health, and had worse health (ie, more medical comorbidities) than nonexcluded patients.

Discussion

Although excluded from the intervention based solely on lack of access to a computer and/or internet, excluded patients may have needed the intervention more because they were sicker with more comorbidities.

Conclusion

Researchers must be mindful of enrollment biases and demographic and health-related inequities that may exist during recruitment for technology-based interventions.

SUBMITTER: Toscos T

PROVIDER: S-EPMC7647239 | biostudies-literature | 2019 Aug

REPOSITORIES: biostudies-literature

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Publications

Selection biases in technology-based intervention research: patients' technology use relates to both demographic and health-related inequities.

Toscos Tammy T Drouin Michelle M Pater Jessica J Flanagan Mindy M Pfafman Rachel R Mirro Michael J MJ

Journal of the American Medical Informatics Association : JAMIA 20190801 8-9

<h4>Objective</h4>Researchers conduct studies with selection biases, which may limit generalizability and outcomes of intervention research. In this methodological reflection, we examined demographic and health characteristics of implantable cardioverter defibrillator patients who were excluded from an informatics intervention due to lack of access to a computer and/or the internet.<h4>Materials and methods</h4>Using information gathered from surveys and electronic health records, we compared th ...[more]

PMID: 31172193

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Project description:BackgroundTo support equity focussed public health policy in low and middle income countries, more evidence and analysis of the social determinants of health inequalities is needed. This requires specific know how among researchers. The INDEPTH Training and Research Centres of Excellence (INTREC) collaboration will develop and provide training on the social determinants of health approach for health researchers from the International Network for the Demographic Evaluation of Populations and Their Health in Low- and Middle-Income Countries (INDEPTH) in Africa and Asia. To identify learning needs among the potential target group, this qualitative study explored what INDEPTH researchers from Ghana, Tanzania, South Africa, Kenya, Indonesia, India, Vietnam, and Bangladesh feel that they want to learn to be able to conduct research on the causes of health inequalities in their country.MethodsUsing an inductive method, online concept-mapping, participants were asked to generate statements in response to the question what background knowledge they would need to conduct research on the causes of health inequalities in their country, to sort those statements into thematic groups, and to rate them in terms of how important it would be for the INTREC program to offer instruction on each of the statements. Statistical techniques were used to structure statements into a thematic cluster map and average importance ratings of statements/clusters were calculated.ResultsOf the 150 invited researchers, 82 participated in the study: 54 from Africa; 28 from Asia. Participants generated 59 statements and sorted them into 6 broader thematic clusters: "assessing health inequalities"; "research design and methods"; "research and policy"; "demography and health inequalities"; "social determinants of health" and "interventions". African participants assigned the highest importance to further training on methods for assessing health inequalities. Asian participants assigned the highest importance to training on research and policy.ConclusionThe identified thematic clusters and statements provide a detailed understanding of what INDEPTH researchers want to learn in order to be able to conduct research on the social determinants of health inequalities. This offers a framework for developing capacity building programs in this emerging field of public health research.

Project description:PurposeThe analysis of existing institutional research proposal databases can provide novel insights into science funding parity. The purpose of this study was to analyze the relationship between race/ethnicity and extramural research proposal and award rates across a medical school faculty and to determine whether there was evidence that researchers changed their submission strategies because of differential inequities across submission categories.MethodThe authors performed an analysis of 14,263 biomedical research proposals with proposed start dates between 2010-2022 from the University of Michigan Medical School, measuring the proposal submission and award rates for each racial/ethnic group across 4 possible submission categories (R01 & Equivalent programs, other federal, industry, and non-profit).ResultsResearchers from each self-identified racial/ethnic group (Asian, Black/African American, Hispanic/Latino) pursued a different proposal submission strategy than the majority group (White). The authors found that Black/African American researchers experienced negative award rate differentials across all submission categories, which resulted in the lowest R01 & Equivalent and Other Federal submission rates of any racial/ethnic group and the highest submission rate to non-profit sources. The authors did not find support for the hypothesis that researchers changed submission strategies in response to award rate inequalities across submission categories.ConclusionsBiomedical researchers from different racial/ethnic groups follow markedly different proposal submission strategies within the University of Michigan Medical School. There is also a clear relationship between race/ethnicity and rates of proposal award. Black/African American and Asian researchers appear disadvantaged across all submission categories relative to White researchers. This study can be easily replicated by other academic research institutions, revealing opportunities for positive intervention.

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Dataset Information

Selection biases in technology-based intervention research: patients' technology use relates to both demographic and health-related inequities.

Objective

Materials and methods

Results

Discussion

Conclusion

Publications

Selection biases in technology-based intervention research: patients' technology use relates to both demographic and health-related inequities.

Similar Datasets

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