Kevin M. Cummins

Comparisons of online recruitment sources are rarely conducted under a unified protocol; literature-based comparisons confound recruitment mode with variation in eligibility criteria, survey instruments, incentives, and data-quality controls. We compared four concurrently fielded recruitment modes (text-message invitations, targeted digital advertising, social media advertising, and a commercial nonprobability panel) using a common screener, instrument, incentive, and quality-flagging system to establish a large cohort of a minority subpopulation: young adults (aged 18-25) in California who use electronic nicotine delivery systems. Screener completion per invitation/impression ranged from 0.8% to 11.1% with 12,547 completed screeners. Two quality-flagging systems were applied with 806 retained respondents. Screener fraud flags were 4 to 9 times more frequent for social media advertising than for any other mode (p < .001). Across all recruitment modes except social media, endorsing eligibility items was associated with a higher likelihood of screener flags, with one exception (ps < .008), a pattern consistent with eligibility fraud. Baseline assessment insufficient effort responding (IER) flags were most frequent among panel respondents (p < .001) and least frequent among respondents recruited via text-message and targeted digital advertising, the two probabilistic sampling modes. Paradata-based and content-based screening were complementary rather than interchangeable data-quality tools with weak overlap (Jaccard index = .20); most respondents exceeding the baseline threshold were already excluded via screener flags, whereas most screener-flagged respondents produced internally consistent reports, indicating the screenings captured distinct validity threats. Recruitment mode systematically shaped both fraudulent responding and response effort. Social media advertising yielded the largest and most demographically diverse sample but also the highest screener fraud rates; the commercial panel showed little evidence of fraud but the highest IER. Multi-modal recruitment of minority subpopulations into large longitudinal studies is feasible and, with layered quality controls, can yield cohorts with acceptable fraud and IER profiles.

Substantial increases in depression at the outset of the pandemic were previously reported in NCANDA, a longitudinal sample of adolescents and young adults. The current NCANDA study examined depression symptoms before and during the COVID-19 pandemic. It evaluated the influence of stressors and social behavior (e.g., in-person and online socializing) with linear mixed effects models. A strong, positive association between COVID-19-related stressors and depression symptoms was observed. The frequency of in-person socializing did not account for the totality of the changes in depression observed during the early COVID-19 pandemic. It may be that pandemic-related stressors counteracted the benefits of in-person interactions during the early stages of the COVID-19 pandemic. Future studies can continue to elucidate the interactions among psychosocial, genetic, and behavioral factors contributing to depression symptoms in the unprecedented context of the COVID-19 pandemic.

Early vaping research often did not differentiate between substances vaped. The present study investigates risk perceptions for vaped nicotine and vaped cannabis. A school-based census of 9th and 11th graders yielded 431 responses to the California Healthy Kids Survey. Differences in harm perceptions were evaluated using multilevel mixed-effects models. Students were more likely to report nicotine vaping as great-moderate risk in comparison to cannabis vaping. Additionally, vaped cannabis was viewed as riskier than traditional administration. These results indicate that differences in harm perceptions may need to be addressed when targeting specific classes of substance use in investigations and interventions.

Persuasive arguments for using theory have been influential in health behavior and health promotion research. The use of theory is expected to improve intervention outcomes and facilitate scientific advancement. However, current empirical evaluations of the benefits of theory have not consistently demonstrated strong effects. A lack of resolution on this matter can be attributed to several features of the current body of evidence. First, the use of theory may be confounded with other features that impact health-related outcomes. Second, measurement of theory use has not been reliable. Third, the field conflates models and theories. Lastly, the evidentiary status and applicability of theories are not considered. Addressing these challenges during the execution of meta-analyses and designing original research specifically to estimate the benefits of theory could improve research and practice.

We examined whether the often-reported protective association of alcohol with cardiovascular disease (CVD) risk could arise from confounding. Our sample comprised 908 men (56–67 years), free of prevalent CVD. Participants were categorized into 6 groups: never drinkers, former drinkers, and very light (1–4 drinks in past 14 days), light (5–14 drinks), moderate (15–28 drinks), and at-risk (>28 drinks) drinkers. Generalized linear mixed effect models examined the associations of alcohol use with three established CVD risk scores: The Framingham Risk Score (FRS); the atherosclerotic CVD (ASCVD) risk score; and the Metabolic Syndrome (MetS) Severity score, adjusting for group differences in demographics, body size, and health-related behaviors. In separate models we additionally adjusted for several groups of potentially explanatory factors including socioeconomic status, social support, physical and mental health status, childhood factors, and prior history of alcohol misuse. Results showed lower CVD risk among light and moderate alcohol drinkers, relative to very light drinkers, for all CVD risk scores, independent of demographics, body size, and health-related behaviors. Alcohol-CVD risk associations were robust to further adjustment for several groups of potential explanatory factors. Study limitations include the all-male sample with limited racial and ethnic diversity, and the inability to adjust for sugar consumption and for patterns of alcohol consumption. Although this observational study does not address causation, results show that middle-aged men who consume alcohol in moderation have lower CVD risk and better cardiometabolic health than men who consume little or no alcohol, independent of a variety of health, behavioral, psychosocial, and earlier life factors.

The factor structure of neuropsychological functioning among a large sample (N = 831) of American youth (ages 12–21 at baseline) was investigated in order to identify an optimal model. Candidate models were selected based on their potential to provide service to the study of adolescent development and the effects of heavy episodic alcohol consumption. Data on neuropsychological functioning were obtained from the NCANDA study. This is a longitudinal community study of the effects of alcohol exposure on neurodevelopment. Three conceptually motivated and one empirically motivated factor analysis model of neuropsychological domains were compared based on penalized-likelihood selection criteria and model fit statistics. Two conceptually-motivated models were found to have adequate fit and pattern invariance to function as a measurement model for the Penn Computerized Neurocognitive Battery (Penn CNB) anchored neuropsychological battery in NCANDA. Corroboration of previous factor analysis models was obtained, in addition to the identification of an alternative factor model that has higher discriminant capacity for neuropsychological domains hypothesized to be most sensitive to alcohol exposure in human adolescents. The findings support the use of a factor model developed originally for the Penn CNB and a model developed specifically for the NCANDA project. The NCANDA 8-Factor Model has conceptual and empirical advantages that were identified in the current and prior studies. These advantages are particularly valuable when applied in alcohol research settings.