Tuesday, January 31, 2023

A growing literature points to children’s influence on parents’ behavior, including parental investments in children; this study finds an earlier predictor of investment, offspring genotype

Child-Driven Parenting: Differential Early Childhood Investment by Offspring Genotype. Asta Breinholt, Dalton Conley. Social Forces, soac155, January 18 2023. https://doi.org/10.1093/sf/soac155

Abstract: A growing literature points to children’s influence on parents’ behavior, including parental investments in children. Further, previous research has shown differential parental response by socioeconomic status to children’s birth weight, cognitive ability, and school outcomes—all early life predictors of later socioeconomic success. This study considers an even earlier, more exogenous predictor of parental investments: offspring genotype. Specifically, we analyze (1) whether children’s genetic propensity toward educational success affects parenting during early childhood and (2) whether parenting in response to children’s genetic propensity toward educational success is socially stratified. Using data from the Avon Longitudinal Survey of Parents and Children (N = 6,247), we construct polygenic indexes (PGIs) for educational attainment (EA) and regress cognitively stimulating parenting behavior during early childhood on these PGIs. We apply Mendelian imputation to construct the missing parental genotype. This approach allows us to control for both parents’ PGIs for EA and thereby achieve a natural experiment: Conditional on parental genotype, the offspring genotype is randomly assigned. In this way, we eliminate the possibility that child’s genotype may be proxying unmeasured parent characteristics. Results differ by parenting behavior: (1) parents’ singing to the child is not affected by the child’s EA PGI, (2) parents play more with children with higher EA PGIs, and (3) non-college-educated parents read more to children with higher education PGIs, while college-educated parents respond less to children’s EA PGI.

Compared to those who have had a COVID-19 infection, those who have not yet experienced infection anticipate they will experience greater negative emotion, and this may have implications for preventive behaviors

Getting COVID-19: Anticipated negative emotions are worse than experienced negative emotions. Amanda J.Dillard, Brian P.Meier. Social Science & Medicine, Volume 320, March 2023, 115723. https://doi.org/10.1016/j.socscimed.2023.115723


Anticipated and recalled negative emotions for COVID-19 infection were compared.

People who have never had COVID may overestimate their negative emotion for infection.

More negative emotion, particularly when anticipated, relates to vaccination and intentions.


Objective: When people think about negative events that may occur in the future, they tend to overestimate their emotional reactions, and these “affective forecasts” can influence their present behavior (Wilson and Gilbert, 2003). The present research examined affective forecasting for COVID-19 infection including the associations between emotions and preventive intentions and behavior.

Methods: In two studies, we compared individuals’ anticipated emotions and recalled emotions for COVID-19 infection. Study 1 asked college students (N = 219) and Study 2 asked general adults (N = 401) to either predict their emotions in response to a future COVID-19 infection or to recall their emotions associated with a previous infection.

Results: In both studies, reliable differences in negative emotions emerged. Those who were predicting their feelings associated with a future infection anticipated more negative emotion than those who were recalling their feelings associated with a past infection reported. Greater negative emotion in both studies was significantly associated with being more likely to have been vaccinated as well as higher intentions to get the booster vaccine.

Conclusions: These findings suggest that compared to those who have had a COVID-19 infection, those who have not yet experienced infection anticipate they will experience greater negative emotion, and this may have implications for preventive behaviors. In general, these findings suggest that people may have an impact bias for COVID-19 infection.

Keywords: COVID-19Affective forecasting theoryAnticipated emotionVaccine behaviorBehavior intentions

9. General discussion

In two studies with college students and general adults, we compared affective forecasts to affective experiences of a COVID-19 infection. In both studies, when individuals thought about the prospect of contracting COVID-19, they anticipated more regret, guilt, anger, and fear than individuals who had the virus recalled experiencing. Higher negative emotion was meaningful in that it was related to greater likelihood of having been vaccinated as well as higher intentions to get the booster.

Although similar differences in anticipated versus recalled negative emotions were observed in both the college students and general adults, the negative emotions were overall higher in the latter group. In the sample of general adults, perceived severity of COVID-19 also significantly differed among those anticipating versus recalling infection, a finding which was not observed in the college students. Together, these findings may suggest that relative to college students, the general adults felt more threatened by COVID-19. On one hand, this notion of greater perceived threat among an older sample is reasonable given that age is a risk factor for more severe disease. On the other hand, the anticipation of greater negative emotion among the older sample does not fit with recent studies finding that older individuals, compared to younger, are faring better emotionally during the pandemic (including some of the same emotions we tested; Carstensen et al., 2020Knepple Carney, Graf, Hudson and Wilson, 2021) or that older adults are more optimistic about COVID-19 (Bruine de Bruin, 2021). However, this distinction may relate to emotions about how one would fare with COVID-19 infection (as measured in our research) versus how one is coping emotionally with the pandemic. In fact, although several studies have examined people's emotions during the pandemic, none that we know of have examined people's anticipated or recalled emotional reactions to contracting COVID-19.

Our findings are in line with affective forecasting theory, and the specific error known as the impact bias. The impact bias occurs when people overestimate the intensity and duration of their future emotions (Gilbert and Wilson, 2007; for a review, see Wilson and Gilbert, 2003). Early research on the impact bias showed it for outcomes such as breaking up with a romantic partner or failing to get a job promotion, but it has since been found for many diverse events and outcomes (Dunn et al., 2003Finkenauer et al., 2007Gilbert et al., 1998Hoerger, 2012Hoerger et al., 2009Kermer et al., 2006Sieff et al., 1999Van Dijk, 2009). Researchers have argued that the impact bias likely underpins many health decisions, but relatively few studies have tested the bias and its behavioral implications (Halpern and Arnold, 2008Rhodes and Strain, 2008). Given our findings that anticipated emotions were more intense than recalled experienced emotions, our data are suggestive of an impact bias for COVID-19 infection. These data are among the first to apply affective forecasting ideas to this unusually novel and severe virus.

Although our research is an important first step in highlighting the potential of an impact bias for COVID-19, our studies do not provide definitive evidence. This is because we assessed recalled emotions which may differ from actual experienced emotions. For example, it could be that participants who were recalling their emotions from a past infection experienced just as much negative emotion as those who were anticipating an infection, but they remember the emotions as less intense. This idea would be supported by research suggesting that recalled emotions are susceptible to various cognitive biases and processes (for a review see Levine and Safer, 2002). For example, one's expectations about how they should have felt, one's coping or adaptation since the event, and even personality factors may influence recalled emotions (Hoerger et al., 2009Ottenstein and Lischetzke, 2020Wilson et al., 2003). Arguably, some of these factors could influence one's anticipated emotions too. However, a future study that uses a within-subjects, longitudinal design, assessing the same individuals before, during and after they experience COVID-19, can provide definitive evidence of an impact bias (see more discussion of this idea in the Limitations section).

One question raised by our findings is, would it benefit people to learn that individuals who contract a virus like COVID-19 may experience less negative emotion than others predict? On one hand, reducing negative emotion in those who have never experienced infection could have the undesired effect of discouraging preventive behavior like getting vaccinated. Indeed, our data would support this notion. On the other hand, many people have experienced high distress due to the pandemic (Belen, 2022Shafran et al., 2013). While emotions associated with infection may play only a small role in this distress, learning that these emotions may be overestimated (and that people may do better than they anticipate) could be helpful information. Related to this, one strategy to reduce negative emotions surrounding the COVID-19 pandemic is to encourage mindfulness (Dillard and Meier, 2021Emanuel et al., 2010). Mindfulness is about focusing one's attention on the ongoing, present moment (Brown and Ryan, 2003). People who practice mindfulness may be less inclined to think about future outcomes, or anticipate strong negative emotions associated with these outcomes.

The question above relates to a broad dilemma, faced by researchers in psychology, medicine and other fields, about using emotions to promote health behaviors. That is, to what extent is it acceptable to use, or to increase, people's existing negative emotions to motivate health behaviors? For example, to encourage women to get mammograms, is it appropriate to use interventions to increase their fear (or other negative emotions), or to not correct their existing strong negative emotions about breast cancer? Although some women may hold stronger negative emotions than warranted (e.g., they may be of lower-than-average risk), correcting them could have the unfortunate consequence of reducing their likelihood of getting screened. The answer to this dilemma may well depend on factors such as context (e.g., whether there is a ‘right’ preventive action that is appropriate for most people) or emotion threshold (e.g., when is a negative emotion too much, leading to additional distress, and when is it just enough to motivate behavior). In general, more research should be devoted to determining the conditions relating to this dilemma and affective forecasting is a ripe context for investigating them.

In both studies, we found that individuals who anticipated or recalled greater negative emotion associated with COVID-19 infection were more likely to have been vaccinated and they also reported higher intentions to get the booster. Although our data were correlational, they fit with the broad literature that show emotions, including anticipated ones, can be a powerful influence on heath behaviors (e.g., see Williams and Evans, 2014 for a review), including vaccine behavior (Brewer et al., 2016Chapman and Coups, 2006Wilson et al., 2003). Our findings also fit with recent research finding that emotions like fear and regret are positively associated with COVID-19 vaccination and other preventive behaviors (Coifman et al., 2021Reuken et al., 2020Wolff, 2021). More research is needed on associations between different types of emotions and health behaviors. For example, are experienced emotions as important as recalled or anticipated emotions in motivating health behavior? And does accuracy of recalled or anticipated emotions matter in this context? Testing associations between these emotions and health behavior may be difficult as the emotions likely share overlap especially for health threats people are familiar with and have prior experience.

It is important to consider the timing of this research which occurred during Fall 2021. In a recent large-scale longitudinal investigation, researchers examined both American and Chinese adults’ emotions and behavior over the course of the pandemic (Li et al., 2021). They found that negative emotions like fear, anxiety, and worry were heightened in the beginning of the pandemic, but later, during phases of ongoing risk, returned to baseline levels. Their research also showed that while emotions were predictive of preventive behaviors like wearing a mask early in the pandemic, they were not predictive later. In the present research, we observed meaningful differences between anticipated and recalled emotions associated with COVID-19 infection, and both were associated with vaccine behavior. Thus, although emotional reactions have apparently lessened, our findings may speak to the power of affective forecasting and its implications for present behavior.

10. Limitations

This research is not without limitations. Most importantly, both studies used a between-subjects design in which participants were not randomly assigned yet were asked different questions depending on their experience with COVID-19 infection. Although we believe their negative emotion differences related to affective forecasting errors, the differences may have been due to other factors. For example, people who have contracted COVID-19 and people who have not may differ in various ways. Notably, we did not find differences for demographics like age or gender, or various psychosocial variables that were measured in the surveys (see supplementary material for details). Given that an experimental design would be impossible as one cannot randomly assign people to have a COVID-19 infection or not, future studies might incorporate additional baseline measures (e.g., COVID exposure, self-protective behaviors) when assessing these groups. A second related limitation is that although our method of comparing anticipated to recalled emotions is an approach that has been used to test affective forecasting errors (e.g., Dillard et al., 2021Gilbert et al., 1998Sieff et al., 1999), the preferred method is to use a within-subjects, longitudinal design (e.g., Smith et al., 2008Wilson et al., 2003Wilson et al., 2000). For example, people would be measured before and after a COVID-19 infection occurs, and their anticipated and experienced emotions can be directly compared. Of course, this design presents logistical challenges such as the difficulty in assessing people as they are experiencing an infection or having to follow people until an infection occurs (not knowing if it will occur). Following people over time may also allow researchers to examine prospective, actual behavior as opposed to the present studies’ approach which examined retroactive vaccine behavior and booster intentions. Although intentions may be a reliable predictor of behavior (Webb and Sheeran, 2006), finding associations between negative emotion and actual behavior would provide more direct support for the notion that the impact bias has behavioral implications. This may be particularly relevant if COVID vaccines become a yearly recommendation.

Finally, another limitation relates to the biases inherent in recalled emotions. First, individuals who were recalling their infection could have experienced it days, weeks, or even months before being in the study. Length of time since an outcome occurred can bias one's memory for the emotions they experienced during the outcome – in the direction of over or underestimating emotions (Wilson et al., 2003). However, others have found that people are relatively accurate in recalling past emotional experiences, especially in the short-term (Hoerger, 2012). At the time of our study, COVID-19 diagnosis was a new, recent phenomenon, having been around for a little over one year, and all participants' infections would have fallen in that same time frame. Nonetheless to resolve this issue, future studies might assess another group of individuals – those who are currently experiencing COVID-19 infection. However, as mentioned above, this assessment presents logistical challenges.