Turning to smoking, researchers surveyed 916 junior high school students in Grade 7 and two years later in Grade 9.54 7th graders who smoked thought that relatively more people smoke, and 7th graders who did not smoke thought that relatively fewer people smoked.Specifically, adolescents who were most involved with smoking believed that half or more than half of all adults or peers smoked, while those least involved believed that fewer than half of adults or peers smoked. Projection bias could explain this data. Students in 9th grade were more likely to smoke than in 7th grade. The study showed which 7th grade non-smokers were likely to become 9th grade smokers. Specifically, non-smokers in the 7th grade who thought that others smoke were relatively likely to smoke became smokers in the 9th grade. Thus the non-smokers who failed to project their behavior onto were likely to become smokers. In contrast, 7th graders who thought that others do not smoke were relatively unlikely to smoke themselves in the 9th grade. Thus non-smokers who projected their behavior onto others were unlikely to become smokers. These facts are consistent with our conclusion that projection bias stabilizes behavior. From these facts, the authors of the study concluded that projection bias caused the increase in smoking. If our model is correct, their conclusion is mistaken. According to our model, projection bias does not change the number of wrongdoers, but it increases the stability of behavior. We predict that providing accurate information about actual smoking to 7th grader non-smokers would reduce their resistance to smoking,cannabis indoor growing and providing accurate information to 7th grade smokers would reduce their resistance to quitting.As soon as the ban was lifted, other students were seen as taking fewer showers than implied by self-reports — 70% versus 77% on day 4, 72% versus 84% on day 5.
This fact is consistent with the theory that moral pessimism only applies to morally relevant behavior. Not showering ceased to be altruistic after the ban was lifted. In another study on altruism, subjects were asked whether or not they would perform hypothetical acts to help others, such as aiding an aging couple stranded in a storm with a flat tire, and whether or not they thought that other people would perform those acts.The study found a gap suggesting moral pessimism. Pessimism was greatest for people who reported that they would not help others, which suggests social projection. Similarly, in the context of blood donations, Goethals found that 60% of a student sample said they would be willing to donate blood but estimated that only 39% of heir peers would do so.In contexts like these, people have difficulty getting information about actual behavior, so bias is likely too have long-term effects. These studies would be more valuable if they predicted the effect of bias on actual behavior and tested their predictions. Advent of the coronavirus 2019 disease pandemic was associated with changes in drinking and drug use among young adults. For alcohol, most studies found increases in the number of days drinking and decreases in the number of drinks consumed per occasion , though other studies have found no significant change or a decrease in the number of days drinking. Studies found no change in the number of days using nicotine and no change or increases in the number of days using cannabis during the pandemic. The emergent literature has three key limitations. First, it is unclear whether the initial effects of the pandemic on drinking and nicotine use in the Spring-Summer of 2020 persisted over time. Most published work has focused on the immediate impact of public health policies to reduce the impact of the pandemic in March 2020. Second, those studies with more extended follow-up have not been designed to distinguish pandemic effects from maturation effects , leaving it unclear to what extent the observed changes in drinking or nicotine use are specifically due to the COVID-19 pandemic. Developmental increases in drinking and drug use are expected as young adults mature, even absent a pandemic.
Thus, characterizing the effects of the pandemic in the medium- and long-term requires a design that can subtract out the developmental change that would be expected outside the pandemic context. Third, initial evidence regarding an important potential moderator of the pandemic’s impact—its impact on financial security—has been mixed. One study found financial strain was linked to greater pandemic-related increases in nicotine use during March and April 2020 while another study found loss of income did not moderate pandemic-related changes in drinking during June 2020. The financial impact of the pandemic on U.S. adults has been heterogenous and time-varying , so both replication and extension of these findings with a longer period follow up is warranted. Procedures were approved by Institutional Review Boards at each study site. The NCANDA Study was designed to investigate the impact of heavy alcohol use on neurodevelopment. 831 participants ages 12–21 years old were recruited into NCANDA in 2012–2014 and have been followed prospectively at five study sites across the U.S: Duke University, University of Pittsburgh Medical Center , Oregon Health & Science University , University of California San Diego , and SRI International. Exclusion criteria were intentionally minimized: participants lived within 50 miles of the study site, had no MRI contraindications, had no reported prenatal or perinatal exposures or complications, had no pervasive developmental disorder, had no current or persistent major psychiatric disorder that would interfere with the protocol, and were not taking medications known to affect brain function or blood flow. Each site aimed to recruit a community sample representative of the racial/ethnic distributions of their county. Participants were recruited through announcements at local schools and colleges, public notices, and targeted catchment-area calling. The current study draws data from 348 participants ages 12–15 years old at study entry—older participants were excluded to minimize the potential for cohort effects on drinking and nicotine use. 49% of participants were female. 13% identified as Hispanic; 68% as White, 12% as Black, 7% as Asian, and 8% as Alaskan Native or Pacific Islander. 84% of participants had 1 + parent who completed a Bachelor’s degree.
After completing their baseline assessment at study entry, participants were assessed every six months going forward with a combination of in-person assessments and phone interviews. The timing of follow-up visits was anchored to the date of the participant’s baseline assessment. “Pre-pandemic” observations were any assessment occurring between study entry and March 19, 2020, the date of the first state-issued stay-at-home order, so each youth could contribute multiple assessments. Among youth contributing pre-pandemic data to analyses ,cannabis grow racks there were an average of 3.0 pre-pandemic assessments. During the COVID-19 pandemic, participants were invited to complete three web-based surveys in June 2020 , December 2020 , and June 2021. Of the 348 participants included in analyses, 237 completed the June 2020 survey, 213 completed the December 2020 survey, and 195 completed the June 2021 survey. Completers of the pre pandemic and during-pandemic assessments were sociodemo graphically similar. Among the youth contributing during pandemic data to analyses , there were an average of 2.2 during-pandemic observations. Altogether, 60 youth contributed only pre-pandemic data, 67 youth contributed only during pandemic data, and 221 youth contributed both pre- and during pandemic data. Analyses were conducted in R v4.1.2. We estimated the impact of the COVID-19 pandemic by comparing obser vations of same-age youth assessed at four different timepoints: pre pandemic , June 2020, December 2020, and June 2021. Conceptually, we used the pre pandemic data to construct a reference curve for the expected drinking or nicotine use as a function of age, then compared that reference curve to the observed drinking and nicotine use as a function of age at each survey wave during the pandemic. In this way, we sought to distinguish the effects of the pandemic from age-related changes in drinking or nicotine use that would have occurred even outside the pandemic context. We restricted the sample to participants ≤ age 15.8 years at study entry to reduce potential cohort effects on drinking and nicotine use introduced by study entry criteria or by secular changes in drinking or nicotine use among U.S. young adults between 2016 and 2021. If cohort effects were present, they would be confounded with the effect of the COVID-19 pandemic. Preliminary analyses showed date of birth was not predictive of drinking or nicotine use in the restricted sample after controlling for age, suggesting any remaining cohort effects were minimal. In addition, we restricted observations to those of participants ages 18.8–22.4 years old at each time point, to ensure we had observations covering the same age span at each of the four assessment time points and avoid extrapolation beyond the common region of support. Outcomes included the proportion of young adults drinking or using nicotine, the number of days drinking or using nicotine among those reporting any use, and the typical number of drinks per drinking day.Regressions were fit in the geepack package , clustering observations on participant, specifying an exchangeable cor relation structure, and using robust standard errors. For dichotomous dependent variables, a logistic link function was used.
Model specification included fixed effects for sex, race, ethnicity, study site, age at observation, age-at-observation-squared, and time point of assessment. Participant sex, race, ethnicity, and study site were included as covariates given previous work has established they predict alcohol and nicotine use. Age at observation was included to implement our age-based identification strategy ; both linear and quadratic effects were included to account for nonlinear developmental changes in alcohol and nicotine use across this age range. Time point of assessment was a four-level categorical variable , represented by dummy variables with pre pandemic as the reference level. Follow-up models investigated whether the effect of the COVID-19 pandemic varied as a function the impact of the pandemic on participants’ financial security. We expanded the primary model described above by adding the main effect of financial impact and terms capturing the interaction of financial impact with time point. We then tested the statistical significance of the interaction via a Wald test. Regression models compared drinking and nicotine use at the three during-pandemic time points to drinking and nicotine use pre-pandemic. Fig. 1, Panel A graphs the model-estimated means for a 20-year-old participant across time points, which are inter preted next. Compared to pre-pandemic , significantly fewer participants reported any past-month drinking in June 2020 and December 2020 , with the difference no longer being statistically significant in June 2021. Compared to pre-pandemic, those reporting any past-month drinking drank on 1.83 more days in June 2020 , with the difference no longer being statistically significant in December 2020 or June 2021. Compared to pre-pandemic, there were no significant differences at any of the three during-pandemic time points in the number of drinks on a typical drinking day or the binge drinking or nicotine use outcomes. Tables 2 and 3 reports the corresponding effect sizes. Compared to pre-pandemic, 4–5% fewer participants engaged in past month binge drinking in June 2020 and December 2020, though neither difference was statistically significant. We did not find evidence that the degree to which the pandemic impacted participants’ financial security moderated the pandemic’s impact on drinking outcomes. We found evidence that the degree to which the pandemic impacted participants’ financial security moderated the pandemic’s impact on the number of days using nicotine among past-month users but not the prevalence of past-month nicotine use. Fig. 1, Panel B graphs the interactions for the nicotine use outcomes. Among those reporting any past-month nicotine use, participants who experienced moderate-to-extreme financial impact increased the number of days using nicotine while those with no financial impact decreased the number of days using nicotine in June 2020. We investigated changes in drinking and nicotine use from pre pandemic baseline over the first 15 months of the COVID-19 pandemic in a sample of 348 emerging adults ages 18–22 years old. Compared to pre-pandemic, in June 2020, fewer young adults reported past-month drinking, but those who did were drinking on more days. Compared to pre-pandemic, in December 2020, fewer young adults re ported past-month drinking, but those who did were no longer drinking on significantly more days.