Discussion
The present study aimed to identify the determinants of social distancing behavior in the context of COVID-19 through the application of an integrated social cognition model. The integrated model was based on the theory of planned behavior [13] augmented to include additional predictors relating to normative (moral norm), anticipated affect (anticipated regret), volitional (action planning), and nonconscious (habit) determinants of health behavior. The model was tested in data from a correlational prospective survey study in two samples of Australian and U.S. residents subject to national or local “shelter-in-place” orders. Results indicated that intention and habit were significant predictors of social distancing behavior in both samples. Subjective norm, moral norm, and PBC were significant predictors of social distancing intention. In addition, intention-mediated effects of these social cognition constructs on social distancing behavior in the U.S. sample, but did so only for moral norm in the Australian sample. Action planning did not mediate effects of intention on behavior in either samples but moderated the intention–behavior relationship in the Australia sample. Inclusion of past behavior attenuated effects of social cognition constructs in the models in both samples, although habit and intention remained significant determinants of social distancing behavior in both samples. Excluding participants in the U.S. sample not subject to formal “shelter-in-place” orders, or had the orders lifted during the study, did not affect the pattern or size of the effects in the model, providing evidence that formal orders did not have a substantive bearing on the determinants of social distancing behavior in this sample.
Current findings provide qualified support for some, but not all, predictions of the integrated social cognition model for social distancing behavior. A key assumption of the model, derived from the social cognition theories on which it is based, is that social distancing behavior is reasoned action and, therefore, determined predominantly by intention and the belief-based constructs that underpin them. Effects of intention on social distancing behavior and its mediation of constructs reflecting social reasons for acting, particularly beliefs relating to significant others and moral obligations to perform the behavior, and PBC is consistent with this assumption. This is unsurprising in this context, considering the widely publicized details of the relatively mild effects of the virus in the majority of the population. It is likely that the majority of individuals do not view themselves as at serious risk from COVID-19 but have internalized the view that significant others want them to engage in social distancing and feel a moral obligation to perform the behavior to protect the health of those most at risk. Such a finding is consistent with research on similar health behaviors, such as blood donation, where behavioral performance is likely to promote the health of others rather than the self [34]. Similarly, the impact of PBC indicates the importance of perceived personal agency in maintaining social distancing behavior, consistent with previous research on health behaviors [14]. Individuals that see fewer barriers to maintaining social distancing and have the confidence to do so are more likely to intend to perform these behaviors.
The effects of subjective and moral norms and PBC suggests that these should be viable targets for behavioral interventions aimed at promoting social distancing behavior based on the model. For example, messages promoting moral obligation (e.g., highlighting social responsibility for preventing transmission of the virus to vulnerable others through social distancing) and perceived control (e.g., demonstrating how to easily and successfully maintain appropriate social distance) may facilitate greater intention to socially distance. However, the intention–behavior relationship in the present study was relatively modest in size, particularly in the Australian sample, indicative of a substantive intention–behavior “gap” [15]. This suggests that interventions targeting change in intention determinants, such as moral norms and PBC, may have only small effects on social distancing behavior. It may be of value to explore how properties of intention may affect intention–behavior relations in the context of social distancing behavior [35]. Such properties may signal potential intervention strategies that may strengthen intention–behavior relations in conjunction with messaging targeting moral norms and PBC.
Current findings also indicated consistent effects of self-reported habits on social distancing behavior. Importantly, the effects of habit were direct and independent of intentions, consistent with the theory that suggests that effects of habits reflect nonconscious, automatic processes developed through consistent experience with the behavior in stable contexts over time. Habits also partially mediated the effects of past behavior on social distancing behavior, suggesting that past behavior effects, at least in part, reflect habits [27]. An implication of these findings is that facilitating habit development in behavioral interventions may be effective in promoting social distancing. Research suggests that strategies, such as providing successful experiences of the desired behavior consistently over time and creating environment conditions that facilitate the behavior (e.g., consistent reminders and environmental restructuring) are effective in inducing habits [36], but the efficacy of such strategies in the context of social distancing behavior need to be verified empirically. Furthermore, legislation restricting or mandating behavior change facilitates habit formation over time. This suggests that the introduction of “shelter-in-place” and other government-mandated restrictions may facilitate social distancing habits.
Inclusion of past behavior as a predictor of social distancing behavior at follow-up reduced the effects of intention on behavior to a trivial size in both samples and also attenuated the effects of the social cognition constructs on intention. Such effects are consistent with previous research [22] and raise questions over the sufficiency of the model in identifying the determinants of social distancing behavior. However, such findings must be interpreted in light of the current study design and how the effects of past behavior can provide important information on the determinants of social distancing behavior. The 1 week time lag means that past behavior was always likely to have a large effect because individuals’ behavior tends to be relatively stable over short periods [22]. A more complete evaluation of model sufficiency would be afforded by testing its long-range prediction, which has often been cited as a goal of social cognition theories [14], and should be considered a future research priority for research on social distancing behavior. However, past behavior effects can be informative on the determinants of social distancing behavior as it may reflect the effects of other unmeasured behavioral determinants. In particular, past behavior will likely reflect determinants that bypass the reasoned, intention-mediated processes that lead to behaviors, such as implicit attitudes and motives, personality traits, and variables reflecting the social and physical environment. The effects of such constructs are speculative and future tests of the integrated model that incorporate such factors alongside those from the current model may assist in resolving these effects.
Consistent with dual-phase models [18, 19], we also tested the extent to which action planning was implicated in the process by which individuals act on their intention. Two patterns of effects were tested: mediation and moderation effects of action planning on the intention–behavior relationship. The mediation effect was significant in the U.S. sample but not the Australia sample, while the moderation effect was significant in the Australia sample only. However, in both cases, the effects were small in size. The small size of the mediation effects suggests that action planning is a relatively trivial component of the link between social distancing intention and behavior, particularly when past behavior was taken into account. The moderation of the intention–behavior relationship by action planning in the Australian sample was negative in sign, which is contrary to predictions [18]. However, probing this interaction indicated that individuals with stronger intention were more likely to follow through on their social distancing behavior at both high and low levels of action planning, but the rate of increase was much steeper for low planning, which supports the prediction. However, when the intention–behavior relationship was strongest, planning had little effect, so planning may only be effective for those with lower intentions. As with the mediation effect, the moderation effect was no longer present once past behavior was included in the model. Taken together, current results do not provide strong evidence for the role of action planning in mediating and moderating the intention–behavior relationship for social distancing.

Limitations and Avenues for Future Research
Current findings should be interpreted in light of some notable limitations. First, attrition rates in both samples were relatively high given the relatively brief time between the baseline survey and follow-up. High attrition could lead to selection bias with those who are more motivated or engaged overrepresented in the sample. While participants were reminded multiple times to complete follow-up measures, we acknowledge that more intensive recruitment and incentivization of nonresponders may have minimized drop out. Attrition also affected the demographic profile of the sample, particularly among underrepresented groups. Although the effect sizes of these differences were small, they were not trivial. This is particularly pertinent in the current context given emerging data indicating that COVID-19 infection and mortality rates are significantly higher in underrepresented minority and socioeconomic groups [37]. A potential solution would be to oversample in underrepresented groups likely to have low retention rates and is a recommendation for future research. It is also important to note that, although our sampling strategy ensured that the distribution of participants in our samples matched those of the national population according to gender and state, we did not stratify the sample by key demographic or socioeconomic factors. The samples, therefore, should not be considered representative of the national populations of Australia or the USA. Taken together, the bias linked to attrition rates and nonrepresentativeness of the samples places limits on the extent to which current findings can be generalized to the broader population.
Second, the intention–behavior “gap” in the current study resulted in small indirect effects of intention determinants, such as subjective and moral norms and PBC on social distancing behavior. This is a limitation of the current model and means that intervention strategies aimed at changing intention determinants may have relatively modest effects on behavior change. However, small effects may still translate to large numbers of people changing if interventions targeting change in these constructs are administered at the population level. Future intervention research is, nevertheless, needed to verify the effects of targeting change in model constructs on behavior. Research should also adopt behavioral measures that can be converted to meaningful metrics that demonstrate practically significant changes in social distancing behavior (e.g., numbers of people complying with social distancing guidelines when venturing outside the home).
Third, the current study observed social distancing over a relatively brief time frame. Short-range prediction has value as it helps identify potential determinants of social distancing behavior. However, consistency in performing social distancing over time is important for the effective prevention of virus transmission, so research on the determinants of social distancing in the long term is a priority. The relatively short time lag is also likely to be the reason why past behavior had such a pervasive effect in predicting behavior and other constructs in the model. The relevance of past behavior is likely to wane over time, so examining prediction over time may be more revealing as to the social cognition predictors of this behavior and the processes involved.
Fourth, the correlational design precludes the inference of causal effects among the constructs in the current model, so the proposed direction of effects are inferred from theory alone, not the data. Causal sequencing among variables would necessitate experimental or controlled intervention designs. Verification of such effects will highlight the value of the model in informing interventions to promote changes in social distancing behavior. In addition, the inclusion of past behavior in the current analysis modeled change in behavior over time. Past behavior also had the effect of modeling residual effects of unmeasured constructs on behavior, such as past measures of the model constructs. However, the adoption of a cross-lagged panel design would better facilitate the examination of how the change in specific model constructs over time affects social distancing behavior and permit tests of reciprocal effects. It is also important that the effects of past behavior do not provide definitive evidence that affecting change in model constructs, such as intentions or habit, through intervention will lead to a concomitant change in social distancing behavior. This highlights the imperative of intervention research that tests the efficacy of manipulating constructs from the current model in promoting social distancing behavior and illustrates the extent to which model constructs can be modified.
Finally, the current research relies exclusively on self-report measures. While self-reported behavior has exhibited concurrent validity when evaluated against non-self-report measures, such as behavior measured using devices or direct observation, the potential for recall bias or inaccurate reporting likely introduces additional measurement error in the behavioral measure, which would affect model relations. Further, self-reported data are also at risk of self-presentation bias and socially desirable responding. Health behaviors, particularly social distancing behavior in the context of a pandemic, are likely to be considered desirable, which may have compelled respondents to provide positive responses, without even being aware of such biases. Although we stressed anonymity to participants to make it clear that they had license to report their behavior without prejudice, this is unlikely to have fully eliminated such biases. Current data should, therefore, be interpreted in light of these potential biases and their potential to contribute to error variance in observed effects. Future research may consider the use of devices, such as GPS tracking of cellular phones, as alternative means to measure social distancing behavior that do not rely on self-report.