Findings show that the sample at hand is similar to the population in Norway regarding Covid-19 vaccination status, in that 95.6% of participants and 91% of the general population above the age of 18 are fully vaccinated (FHI 2022). These rates are among the best in the world (WHO 2023a). They are also higher than findings reported in a meta-analysis by Brewer et al. (2007) who found vaccination uptake for infectious diseases to vary between 6 and 86% (with a median uptake of 51%). The rate of vaccination both in the sample and in the Norwegian population also exceeds the 61% of participants who in 2020 stated the intent to get vaccinated once a vaccine became available (Wolff 2021).

The variance explained in intentions assessed in 2020 (Wolff 2021) was higher than the variance explained in vaccination status in the present investigation, 69 and 41%, respectively. This is in line with previous research showing that the theory of planned behavior predicts behavioral intentions better than behavior (Armitage and Conner 2001; Rich et al. 2015). This is to be expected as the theory of planned behavior proposes that predictor variables, i.e., attitudes, norms, and perceived control, are the immediate precursors of intentions which in turn predict behavior.

The predictors of vaccination intent (2020) and of vaccination uptake (2022) are very similar. Both are predicted by positive attitudes toward vaccination, favorable social norms within one’s family, perceived capability (one measure of perceived behavioral control), and high anticipated regret for not getting vaccinated. Vaccination intent (2020) was additionally predicted by low anticipated regret for getting vaccinated, and vaccination uptake (2022) was also predicted by older age (which is a risk factor for a serious prognosis), and somewhat surprisingly by lack of perceived autonomy (another measure of perceived behavioral control).

These findings are also similar to previous research that has used the theory of planned behavior to predict Covid-19 vaccination intentions and found the following predictors: age, positive attitudes, and increased perceived risk for others (Sherman et al. 2020); attitudes, but neither social norms nor perceived behavioral control (Fan et al. 2021), perceived severity, subjective norms and perceived behavioral control (Shmueli 2021); and attitudes, social norms, and perceived behavioral control (Servidio et al. 2022).

The fact that perceived autonomy correlates negatively with being vaccinated is contradictory to the theory of planned behavior which claims that perceived behavioral control, including perceived autonomy, correlates positively with behavioral intentions and behavior (Ajzen 1985, 1991). In hindsight, however, it seems plausible that respondents who disagree with the statement It is up to me whether I get vaccinated or not might be the ones who feel obligated to get vaccinated. Such an obligation may be caused by a feeling of responsibility for protecting others, or from the fact that certain restrictions applied to people who were not vaccinated. Still, Norway had hardly any differential restrictions for vaccinated and unvaccinated citizens, only some differences in quarantine length and travel restrictions (Government.no 2023). This supports the fact that a perceived obligation may stem from altruistic motives.

Optimistic bias, assessed as lower perceived susceptibility and less serious prognosis compared to others, did neither predict intention to vaccinate nor vaccination uptake. These findings contradict other research showing that increased perceived risk and vulnerability predict protective heath behaviors, including vaccination (Brewer et al. 2007). However, the results are in line with Sherman et al. (2020) who found that participants were more willing to vaccinate against COVID-19 when they perceived greater risk for others but not for themselves. Results also fit with the finding discussed above, that people may feel obligated to vaccinate against Covid-19 to protect others. As discussed by Wolff (2021), Covid-19 may not pose a serious risk for most participants and vaccination may therefore be motivated by protecting others rather than oneself. This altruistic motivation may also contribute to vaccination uptake for other diseases. It has for example been shown that appealing to altruistic motives, i.e., the protection of sex partners, may increase men’s willingness to vaccinate against HPV (Bonafide and Vanable 2015). For diseases where the main motivation of vaccination is self-protection, increased perceived personal risk and vulnerability are likely to be predictors of vaccination uptake (Brewer et al. 2007). Optimistic bias might still influence vaccination uptake for those diseases even though it did not influence vaccination intention and uptake in the present study.

Anticipated regret for not getting vaccinated correlated with vaccination uptake in the present investigation. This is in line with Wolff (2021) who found that Covid-19 vaccination intentions were predicted by high anticipated regret for not getting vaccinated and low anticipated regret for vaccination. Findings also correspond with Brewer et al. 2016 who found that anticipated regret was lower for vaccination than for non-vaccination, and with Zeelenberg & Pieters (2007) who showed easily justifiable choices (virtues, health promotion) to be associated with less anticipated regret than choices that are hard to justify (vices, risk behaviors).

As in Wolff (2021), it is interesting to note a negative correlation of anticipated regret for getting vaccinated and for not getting vaccinated. As anticipated regret is determined by the probability of negative outcomes of an alternative, this finding is somewhat paradoxical. This is because the more negative the consequences of not being vaccinated are, the more willing one should be to accept negative consequences (i.e., side effects) of a vaccine. This would imply a positive correlation of anticipated regret for getting vaccinated and for not getting vaccinated. See Wolff (2021) for a discussion of possible explanations.

The present investigation has several limitations. First and foremost, it did not actually predict vaccination behavior but rather post-dicted it. All measures were obtained after most participants were vaccinated. It is therefore not possible to conclude whether attitudes influenced vaccination behavior or whether getting vaccinated leads people to form positive attitudes toward vaccination. Possibly, both processes are at work. The current approach also implies that participants had to assess the potential of regret for different alternatives after they had made an irreversible choice (at least the vaccinated ones). This may lead participants to exaggerate the difference in anticipated regret between chosen and not chosen alternative. All of this could of course have been circumvented with a longitudinal design following the same participants over time, which would have been preferable. It is still interesting to observe that participants report not regretting their choice. Also, the observed relations between the predictor variables and vaccination status are very similar to the ones observed in the data obtained before vaccination became available.

Also perceived susceptibility and seriousness of prognosis were measured in relative terms, i.e., compared to others. It is therefore not possible to conclude whether susceptibility and seriousness of the prognosis are perceived to be high or low in absolute terms. This way of assessment was chosen to construct a measure of optimistic bias.

Furthermore, several constructs have been assessed with single-item measures. This holds true for perceived capability and autonomy, relative susceptibility and seriousness of prognosis, and anticipated regret for getting vaccinated and for not getting vaccinated. However, for simple constructs, single-item measures may outperform multi-item measures (Bergkvist and Rossiter 2007).

Another limitation of this research concerns the operationalization of vaccination status as a continuous variable (from zero to three doses of vaccine), since it could be argued that vaccination status is a dichotomous variable (one either is or is not vaccinated). This was done for two reasons: to overcome statistical problems that arise from a very low number of participants with zero vaccination doses, and to allow for a direct comparison to the data collected in 2020. It seems reasonable to assume that participants with fewer doses are more skeptical toward vaccination, as vaccines had been fully available for all for at least 6 months by the time of data collection. The similarity of the results from 2020 and 2022 also underline that the conceptualization of vaccination status as a continuous variable is not nonsensical.

In conclusion, results support the use of the theory of planned behavior (Ajzen 1985, 1991) as a theoretical model to predict vaccination intentions and vaccination uptake for Covid-19. The theory explains 70% of the variance in intentions and 41% of the variance in vaccination uptake and all proposed predictor variables (attitudes, norms, and perceived control) turned out to be significant. However, the model’s predictive power was further increased by including measures of anticipated regret.

Interventions designed to increase vaccination uptake should focus on the variables found to correlate with intentions and vaccination uptake. These were positive attitudes, favorable subjective norms within one’s family, perceived capability, and anticipated regret for not getting vaccinated. Interventions could focus on increasing positive attitudes through informing about vaccination benefits; however, it might be equally effective to focus on the disadvantages and possible negative consequences of not being vaccinated to increase non-vaccination regret.

Focusing on the risk of Covid-19 for others, rather than individual risk might be another way to increase vaccination uptake. This is supported by the finding that relative perceived susceptibility and seriousness of prognosis (i.e., optimistic bias) did not correlate with vaccination intentions and uptake. This may be because Covid-19 does not pose a grave risk for most of the population, at least not in Norway (FHI 2020). However, optimistic bias might still influence vaccination uptake for diseases that are riskier for most individuals.

Another finding supporting focusing on the risk or others is that vaccinated participants reported less autonomy over the decision than unvaccinated participants. This may indicate that vaccinated participants might have felt obligated to get vaccinated, possibly to protect others. Appealing to altruistic norms and the obligation to protect others, for example older family members, may therefore be one way to increase vaccination rates. This approach is also supported by the fact that norms within the family seem to influence vaccination uptake.

Finally, while this research focused on vaccination uptake for Covid-19, hopefully some directions for future research and some generalizable finding may be gained from it. Those may include the following: The theory of planned behavior is a useful model for explaining vaccination behavior, but its predictive power may be increased by including measures of anticipated regret (also see Sandberg and Conner 2008). Future research should look at whether vaccination uptake for diseases that are not threatening for many individuals can be increased by focusing on the risk for others and altruistic norms, rather than individual risk.