Factors associated with contact tracing compliance among communities of color in the first year of the COVID-19 pandemic.

RATIONALE: The disproportionate impact of COVID-19 on communities of color has raised questions about the unique experiences within these communities not only in terms of becoming infected with COVID-19 but also mitigating its spread. The utility of contact tracing for managing community spread and supporting economic reopening is contingent upon, in part, compliance with contact tracer requests. OBJECTIVE: We investigated how trust in and knowledge of contact tracers influence intentions to comply with tracing requests and whether or not these relationships and associated antecedent factors differ between communities of color. METHOD: Data were collected from a U.S. sample of 533 survey respondents from Fall (2020) to Spring 2021. Multi-group SEM tested quantitative study hypotheses separately for Black, AAPI, Latinx, and White sub-samples. Qualitative data were collected via open-ended questions to inform the roles of trust and knowledge in contact tracing compliance. RESULTS: Trust in contact tracers was associated with increased intentions to comply with tracing requests and significantly mediated the positive relationship between trust in healthcare professionals and government health officials with compliance intentions. Yet, the indirect effects of trust in government health officials on compliance intentions were significantly weaker for the Black, Latinx, and AAPI samples compared to Whites, suggesting this strategy for increasing compliance may not be as effective among communities of color. Health literacy and contact tracing knowledge played a more limited role in predicting compliance intentions directly or indirectly, and one that was inconsistent across racial groups. Qualitative results reinforce the importance of trust relative to knowledge for increasing tracing compliance intentions. CONCLUSIONS: Building trust in contact tracers, more so than increasing knowledge, may be key to encouraging contact tracing compliance. Differences among communities of color and between these communities and Whites inform the policy recommendations provided for improving contact tracing success.

Cannabis's Link to Schizotypy: Phenomenon, Measurement Bias, or Delusion?

Links between cannabis use and psychosis generate research and media attention. Cannabis users have outscored non-users on the Schizotypal Personality Questionnaire-Brief (SPQ-B) in multiple studies, but previous work suggests that groups do not differ if biased items are removed. The present study examined links between schizotypal personality and cannabis use in a large sample recruited from Amazon's MTurk platform (N = 705). Over 500 participants reported lifetime cannabis exposure. Of those, 259 participants reported current cannabis use, and on average, used 4.53 days per week. Users and non-users failed to differ significantly on total SPQ-B scores or any of the three established subscales. The null results inspired a re-examination of the SPQ-B's factor structure, which identified a novel 3-factor solution (difficulty opening up to others, hyperawareness, and odd or unusual behavior). Only the "odd or unusual behavior" factor showed cannabis-related differences, but a differential item functioning test revealed that one subscale item showed potential bias against users. Removing this item diminished group differences. These results suggest that links between schizotypy and cannabis use require cautious interpretation with careful attention to potential measurement bias. In addition, the SPQ-B might have an alternative factor structure that could help answer important questions in psychopathology.

Item response theory scoring and the detection of curvilinear relationships.

Psychologists are increasingly positing theories of behavior that suggest psychological constructs are curvilinearly related to outcomes. However, results from empirical tests for such curvilinear relations have been mixed. We propose that correctly identifying the response process underlying responses to measures is important for the accuracy of these tests. Indeed, past research has indicated that item responses to many self-report measures follow an ideal point response process-wherein respondents agree only to items that reflect their own standing on the measured variable-as opposed to a dominance process, wherein stronger agreement, regardless of item content, is always indicative of higher standing on the construct. We test whether item response theory (IRT) scoring appropriate for the underlying response process to self-report measures results in more accurate tests for curvilinearity. In 2 simulation studies, we show that, regardless of the underlying response process used to generate the data, using the traditional sum-score generally results in high Type 1 error rates or low power for detecting curvilinearity, depending on the distribution of item locations. With few exceptions, appropriate power and Type 1 error rates are achieved when dominance-based and ideal point-based IRT scoring are correctly used to score dominance and ideal point response data, respectively. We conclude that (a) researchers should be theory-guided when hypothesizing and testing for curvilinear relations; (b) correctly identifying whether responses follow an ideal point versus dominance process, particularly when items are not extreme is critical; and (c) IRT model-based scoring is crucial for accurate tests of curvilinearity. (PsycINFO Database Record

Are common language effect sizes easier to understand than traditional effect sizes?

Communicating the results of research to nonscientists presents many challenges. Among these challenges is communicating the effectiveness of an intervention in a way that people untrained in statistics can understand. Use of traditional effect size metrics (e.g., r, r²) has been criticized as being confusing to general audiences. In response, researchers have developed nontraditional effect size indicators (e.g., binomial effect size display, common language effect size indicator) with the goal of presenting information in a more understandable manner. The studies described here present the first empirical test of these claims of understandability. Results show that nontraditional effect size indicators are perceived as more understandable and useful than traditional indicators for communicating the effectiveness of an intervention. People also rated training programs as more effective and were willing to pay more for programs whose effectiveness was described using the nontraditional effect size metrics.

Uncovering curvilinear relationships between conscientiousness and job performance: how theoretically appropriate measurement makes an empirical difference.

The personality trait of conscientiousness has seen considerable attention from applied psychologists due to its efficacy for predicting job performance across performance dimensions and occupations. However, recent theoretical and empirical developments have questioned the assumption that more conscientiousness always results in better job performance, suggesting a curvilinear link between the 2. Despite these developments, the results of studies directly testing the idea have been mixed. Here, we propose this link has been obscured by another pervasive assumption known as the dominance model of measurement: that higher scores on traditional personality measures always indicate higher levels of conscientiousness. Recent research suggests dominance models show inferior fit to personality test scores as compared to ideal point models that allow for curvilinear relationships between traits and scores. Using data from 2 different samples of job incumbents, we show the rank-order changes that result from using an ideal point model expose a curvilinear link between conscientiousness and job performance 100% of the time, whereas results using dominance models show mixed results, similar to the current state of the literature. Finally, with an independent cross-validation sample, we show that selection based on predicted performance using ideal point scores results in more favorable objective hiring outcomes. Implications for practice and future research are discussed.