Reporting of Demographic Variables in Neuropsychological Research: An Update of O’Bryant et al.’s Trends in the Current Literature

Abstract

Objective: Demographic trends and the globalization of neuropsychology have led to a push toward inclusivity and diversity in neuropsychological research in order to maintain relevance in the healthcare marketplace. However, in a review of neuropsychological journals, O’Bryant et al. found systematic under-reporting of sample characteristics vital for understanding the generalizability of research findings. We sought to update and expand the findings reported by O’Bryant et al. Method: We evaluated 1648 journal articles published between 2016 and 2019 from 7 neuropsychological journals. Of these, 1277 were original research or secondary analyses and were examined further. Articles were coded for reporting of age, sex/gender, years of education, ethnicity/race, socioeconomic status (SES), language, and acculturation. Additionally, we recorded information related to sample size, country, and whether the article focused on a pediatric or adult sample. Results: Key variables such as age and sex/gender (both over 95%) as well as education (71%) were frequently reported. Language (20%) and race/ethnicity (36%) were modestly reported, and SES (13%), and acculturation (<1%) were more rarely reported. SES was more commonly reported in pediatric than adult samples, and the opposite was true for education. There were differences between the present results and those of O’Bryant et al., though the same general trends remained. Conclusions: Reporting of demographic data in neuropsychological research appears to be slowly changing toward greater comprehensiveness, though clearly more work is needed. Greater systematic reporting of such data is likely to be beneficial for the generalizability and contextualization of neurocognitive function.

Representativeness of samples enrolled in Alzheimer's disease research centers

“…Prospective standardized collection and reporting of key sociodemographic factors 49 across sites would further help characterize selection factors and improve generalizability of results from large datasets like NACC. Future studies should also consider leveraging transportability methods such as weighting and outcome modeling aimed at generalizing findings to external populations 50–53 . These methods have important assumptions that limit their applicability, but there is some recent work in aging samples 53 .…”

“…Each site is per- Future studies should also consider leveraging transportability methods such as weighting and outcome modeling aimed at generalizing findings to external populations. [50][51][52][53] These methods have important assumptions that limit their applicability, but there is some recent work in aging samples. 53 Last, future work evaluating updated recruitment strategies will also want to consider the impact of major historic events on research recruitment and enrollment, like the COVID-19 pandemic.…”

Recommendations for Defining and Reporting Adherence Measured by Biometric Monitoring Technologies: Systematic Review

“…Moreover, we found that the software name or version (or both) used for data processing was reported for only 30.9% (34/110) of the BioMeTs, indicating that the data cannot be reproduced even if the hardware details are known. We also noted key gaps in the descriptive data; most notably, only 41% (41/100) reported the ethnicity or race of participants, which is a persistent problem in clinical research [22,23]. Even among the 46 studies performed in the United States, for which there are clear guidelines for collecting and reporting race and ethnicity [24], 30% (14/46) of the studies did not provide these data.…”

Introduction to the special issue on cross-cultural neuropsychology

“…O’Bryant et al (2004) noted that information on race, ethnicity, native language and acculturation are often not reported in research articles, which likely limits progress in cross-cultural neuropsychology. Medina et al (2021) provided a recent update on these trends, and while reporting of these variables in research papers is slowly improving, greater systematic reporting of these variables is needed. They present specific recommendations by Rad et al (2018) as a possible path forward.…”