Identifying Invalid Responders in a Campus Climate Survey: Types, Impact on Data, and Best Indicators

Mitigating invalid and mischievous survey responses: A registered report examining risk disparities between heterosexual and lesbian, gay, bisexual, or questioning youth

In a Registered Report, the authors propose a new survey-bias-mitigation method-incorporating inverse probability weighting via boosted regression-to better understand lesbian, gay, bisexual, or questioning (LGBQ)-heterosexual youth risk disparities. This method is tested using the 2019 US Centers for Disease Control and Prevention-collected Youth Risk Behavior Survey (YRBS) national data, which contain 12,847 observations (ages 12-18 [M = 16, SD = 1.25]; 49.1% male [8.7% LGBQ] and 50.9% female [22.4% LGBQ]; nationally representative regarding race and ethnicity). Looking across 44 outcomes, the authors found that the YRBS contains responses that are potentially biased against LGBQ youth in systematic ways, inflating perceived risk for this group in some outcomes. This potential bias is more pronounced among reported males than among reported females, and it is more pronounced for low-incidence outcomes. For example, the steroid-use disparity estimate among reported males reduced by 67%, while the reduction in bullying victimization was small and not statistically significant. The authors discuss robustness of results, the new method, and data policy implications.

Why Do Students Participate in Campus Sexual Assault Climate Surveys?

The purpose of the current study is to explore students' reasons for participating in a campus sexual assault climate survey to determine if patterns exist based on various identities and experiences. More specifically, we were interested in the most frequently reported reasons for participating, and whether they differed by key demographic variables. As part of a campus climate survey administration at two campuses, 4,020 students responded to survey questions asking why they participated in the survey (Sample 1, n = 2,937 and Sample 2, n = 1,083). To examine which demographic variables predicted reasons for taking the survey while controlling for other potential correlates, we conducted logistic regression analyses. The reasons provided by students as to why they completed the campus climate survey differed by identity characteristics, suggesting that researchers must consider the demographic makeup of their institutions when designing sampling and recruitment plans and tailoring them to their student populations. For example, while gender emerged as salient for differing reasons for participation (e.g., women more likely to participate because of the issue's importance and wanting their opinions heard more), intersectional analysis by race and gender indicates that White men (and Asian men, in Sample 1) most consistently indicated different reasons for participation, with significantly greater odds than their White and Asian women counterparts to participate for the cash incentives. This information could help improve the recruitment of representative samples for campus sexual assault surveys and therefore provide more accurate data that can be used to deliver effective intervention and prevention efforts.

Syndromes associated with frontotemporal lobar degeneration change response patterns on visual analogue scales

Self-report scales are widely used in cognitive neuroscience and psychology. However, they rest on the central assumption that respondents engage meaningfully. We hypothesise that this assumption does not hold for many patients, especially those with syndromes associated with frontotemporal lobar degeneration. In this study we investigated differences in response patterns on a visual analogue scale between people with frontotemporal degeneration and controls. We found that people with syndromes associated with frontotemporal lobar degeneration respond with more invariance and less internal consistency than controls, with Bayes Factors = 15.2 and 14.5 respectively indicating strong evidence for a group difference. There was also evidence that patient responses feature lower entropy. These results have important implications for the interpretation of self-report data in clinical populations. Meta-response markers related to response patterns, rather than the values reported on individual items, may be an informative addition to future research and clinical practise.