Potential Misinterpretation of Data on Racial Representation

In an article in Perspectives on Psychological Science, Roberts et al. (2020) analyzed racial representation among publications and authors within three fields of psychology. This commentary points to two aspects of that article that may inhibit proper interpretation of the findings. First, Roberts et al. do not present population base rates in U.S. demographics when drawing inferences. Specifically, they interpret their bibliometric analysis as indicating an over-representation of White authors in social and developmental psychology with no consideration of base rates. I demonstrate that when base rates are considered, the data show equal representation in the 1980s, 1990s, and 2000s, and White under-representation in the 2010s in both subfields. They also report a correlation between non-White editorship, non-White authorship, and non-White participant recruitment, and then suggest that editorship causes an increase in authorship and participant recruitment. They do not consider that demographic change—an overall increase in the proportion of non-Whites in the U.S.—is an alternative explanation for this phenomenon. Lastly, they claim that race is an unpopular topic but a comparative PsycInfo analysis shows race may be one of the most popular topics in psychology. Thus, there are alternative ways to interpret their data.

Cyberbullying Text-messages: Iterative Qualitative Methods for Intervention Design with Adolescents (Preprint)

BACKGROUND Effective, acceptable programs to reduce consequences of cyberbullying are needed. OBJECTIVE This study used “Agile” qualitative methods to refine and evaluate the acceptability of a mixed-modality intervention, initiated within the context of usual pediatric care, for adolescents with a history of cyber-harassment and cyberbullying victimization. METHODS Adolescents were recruited from an urban primary care clinic to participate in three consecutive iterations of the program. All participants completed a brief in-clinic intervention followed by 8 weeks of daily, automated text messaging. After 2 weeks (iteration1 and iteration2) or 8 weeks (iteration3) of messaging, participants completed semi-structured interviews that sought feedback on intervention experiences. Framework matrix analysis expeditiously summarized participant feedback and guided changes in each iteration. Daily response rates assessed participant engagement, and satisfaction questionnaires assessed acceptability. RESULTS Nineteen adolescents (age 13-17) reporting past-year cyber-victimization enrolled: 7 took part in iteration1, 4 in iteration2, and 8 in iteration3. Participants were an average age of 15 years, 58% were female, 63% Hispanic, and 21% White. Participant feedback was used to adjust intervention content and design. Participant satisfaction (from 0% excellent to 80% excellent) and engagement (from 60% of daily assessments completed to 80% completed) improved from the first to the third iteration. CONCLUSIONS This study shows the value of structured participant feedback gathered in an Agile intervention refinement methodology for development of a technology-based intervention targeting adolescents.

Equal Representation is Inequality, and Other Fallacies: A Commentary on Roberts et al. (2020)

In an article in Perspectives on Psychological Science, Roberts et al. (2020) claimed there is significant racial inequality in the publication process within psychology. Roberts et al. raise important questions, but some of their conclusions are inadequately supported. Among other things, they claim to have demonstrated that there is racial inequality in psychological research but do not define a threshold to separate inequality from equality. In addition, Roberts et al. fail to account for population base rates in U.S. demographics when drawing inferences. Specifically, they interpret their bibliometric analysis as indicating an over-representation of White authors in social and developmental psychology with no consideration of base rates. I demonstrate that when base rates are considered, the data actually show equal representation in the 1980s, 1990s, and 2000s, and White under-representation in the 2010s in both subfields. They also report a correlation between non-White editorship, non-White authorship, and non-White participant recruitment, and then suggest that editorship causes an increase in authorship and participant recruitment. They do not consider that demographic change—an overall increase in the proportion of non-Whites in the U.S.—is a better explanation than psychological bias for this association. They claim that race is an unpopular topic but a comparative PsycInfo analysis shows race may be one of the most popular topics in psychology. Their method for assessing a focus on race is also downward biased.

Location-specific risk factors for intracerebral hemorrhage

ObjectiveTo conduct a systematic review and meta-analysis of studies reporting on risk factors according to location of the intracerebral hemorrhage.MethodsWe searched PubMed and Embase for cohort and case-control studies reporting ≥100 patients with spontaneous intracerebral hemorrhage that specified the location of the hematoma and reported associations with risk factors published until June 27, 2019. Two authors independently extracted data on risk factors. Estimates were pooled with the generic variance-based random-effects method.ResultsAfter screening 10,013 articles, we included 42 studies totaling 26,174 patients with intracerebral hemorrhage (9,141 lobar and 17,033 nonlobar). Risk factors for nonlobar intracerebral hemorrhage were hypertension (risk ratio [RR] 4.25, 95% confidence interval [CI] 3.05–5.91, I2 = 92%), diabetes mellitus (RR 1.35, 95% CI 1.11–1.64, I2 = 37%), male sex (RR 1.63, 95% CI 1.25–2.14, I2 = 61%), alcohol overuse (RR 1.48, 95% CI 1.21–1.81, I2 = 19%), underweight (RR 2.12, 95% CI 1.12–4.01, I2 = 31%), and being a Black (RR 2.83, 95% CI 1.02-7.84, I2 = 96%) or Hispanic (RR 2.95, 95% CI 1.69-5.14, I2 = 71%) participant compared with being a White participant. Hypertension, but not any of the other risk factors, was also a risk factor for lobar intracerebral hemorrhage (RR 1.83, 95% CI 1.39–2.42, I2 = 76%). Smoking, hypercholesterolemia, and obesity were associated with neither nonlobar nor lobar intracerebral hemorrhage.ConclusionsHypertension is a risk factor for both nonlobar and lobar intracerebral hemorrhage, although with double the effect for nonlobar intracerebral hemorrhage. Diabetes mellitus, male sex, alcohol overuse, underweight, and being a Black or Hispanic person are risk factors for nonlobar intracerebral hemorrhage only. Hence, the term hypertensive intracerebral hemorrhage for nonlobar intracerebral hemorrhage is not appropriate.

How Ethnicity, Expression, and Study Design Influence First Impressions of Approachability

Over two studies, participants (total N = 642) rated a community sample of photographs of Black, East Asian, and White males who were smiling or portraying a neutral expression to see how participant ethnicity, target ethnicity, and target expression influence judgments of approachability (i.e., trustworthiness, friendliness, and threat). We also examined how a commonly used study design, in which each participant is asked to evaluate different groups of people, may motivate participants to adjust their ratings in an effort to avoid appearing biased. Results showed that the White participant group tended to rate smiling targets as friendlier (Studies 1 and 2) and more trustworthy (Study 1) than did the non-White participant group, which could be due to cultural differences based on majority versus minority status among the participants. In addition, the White participant group tended to rate White targets more positively than did the non-White participant group, suggesting an in-group bias. Finally, differences in results between Studies 1 and 2 suggest that study design can influence the degree of bias responding, highlighting the importance of incorporating a diversity of methods to better understand first impression judgments.

Abstract P198: Does Neighborhood Poverty Account for Race/Ethnic Differences in Sleep Duration?

Introduction: Shorter sleep duration and poorer quality sleep are commonly observed in non-white vs. white racial/ethnic groups. Reasons for these racial/ethnic differences are unknown. Our objective is to determine whether neighborhood poverty, which may reflect more noise exposure, crowding and social stress, explains racial/ethnic differences in sleep. Methods: The Chicago Area Sleep Study identified men and women 35-64 years old without sleep apnea via commercially available telephone listings (N=510; 31% Black, 22% Asian, 21% Hispanic, and 26% White). Participant addresses were geocoded, and residence in a census tract with >20% poverty based on American Community Survey data was classified as “high poverty”. Participants wore wrist actigraphs for 7 days (Actiwatch TM ) to determine sleep duration and sleep percentage (percentage of time during the primary sleep interval spent sleeping). Multivariable regression analysis was used to test whether race remained significantly associated with sleep following adjustment for neighborhood poverty. Results: Black (86%) and Hispanic (66%) participants were more likely to live in high poverty areas as compared with Whites (33%) and Asians (6%). In unadjusted analyses, living in a high poverty census tract was associated with a significantly lower mean sleep percentage (β= -1.80, SE=0.42, p<0.01) and a higher odds of sleeping <6 hrs/night (OR=1.65, 95% CI: 1.02, 2.67). However, these associations were attenuated in adjusted models, and they did not account for race differences in sleep (Table). Conclusions: Neighborhood poverty was unassociated with a lower sleep percentage or shorter sleep in adjusted models, and it did not account for racial/ethnic differences in sleep. Further investigation of specific features of neighborhood poverty (e.g., crime, crowding) and household environment factors that may explain racial/ethnic differences in sleep is warranted.