| Literature DB >> 35892351 |
Allison C Drody1, Lydia J Hicks2, James Danckert1.
Abstract
Research conducted within the first year of the pandemic demonstrated that boredom prone individuals were more likely to break rules (e.g., social distancing) aimed at preventing the spread of COVID-19. It is of interest whether this relation persisted deeper into the pandemic, given that initial results may have reflected the extraordinary nature of the early stages of the pandemic on one hand, or more stable dispositions on the other. Therefore, in the Summer of 2021, we administered an online survey to investigate whether boredom proneness predicted COVID-19 rule-breaking over one year into the pandemic (and approximately one year after the earlier studies). We found that boredom prone individuals remained more likely to engage in COVID-19 rule-breaking. Our results suggest that a trait disposition towards boredom exerts a persistent, long-term influence on behaviour, one that is detrimental to personal well-being during the pandemic. Adherence to public health measures might be improved by encouraging individuals to find adaptive ways of coping with boredom.Entities:
Keywords: COVID-19; boredom proneness; pandemic; rule-breaking; self-control
Year: 2022 PMID: 35892351 PMCID: PMC9394241 DOI: 10.3390/bs12080251
Source DB: PubMed Journal: Behav Sci (Basel) ISSN: 2076-328X
Participants’ self-reported ethnicities.
| Ethnicity | Frequency | Percentage |
|---|---|---|
| Caucasian | 304 | 80.85 |
| First Nations (North American Indian) | 5 | 1.33 |
| Métis | 1 | 0.27 |
| Other European Origins | 1 | 0.27 |
| Black or African American | 31 | 8.24 |
| Carribbean Origins | 2 | 0.53 |
| Latin, Central or South American Origins | 12 | 3.19 |
| West Central Asian and Middle Eastern Origins | 3 | 0.80 |
| South Asian Origins | 14 | 3.72 |
| East and South Eastern Origins | 20 | 5.32 |
| Other Asian Origins | 2 | 0.53 |
| Oceania Origins | 1 | 0.27 |
| Other/Prefer to Self-Identify | 3 | 0.80 |
Note. Participants could select multiple categories to indicate which race(s) they identified with. This table presents the number of participants who endorsed each option. Therefore, the sum of the numbers presented in this table will not correspond to 100%. N = 376.
Rule-breaking questions and accompanying factor loadings.
| Rule-Breaking Questions | Response Options | Factor Loadings |
|---|---|---|
| On average, how many hours of the day are you spending in your household (including your garage or yard but not going into the neighbourhood or other public spaces)? | 1–24 | −0.79 |
| How frequently have you gone out for in-person social visits? | 1 (not at all)–5 (constantly) | 0.86 |
| How frequently do you go out to shop in-person? | 1 (not at all)–5 (constantly) | 0.78 |
| In the past week, how many social gatherings have you had at your home (i.e., gatherings with people other than those with whom you live)? | Free numerical entry | 0.57 |
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| To what extent are you practicing social distancing over the past week? | 1 (not at all)–4 (very much) | −0.16 ** |
| How many people have come within 6ft of you over the last week (best guess, other than people who live with you in your household)? | Free numerical entry | −0.08 |
| How many days have you spent in isolation over the past week? | 1–7 | −0.19 *** |
| To what extent are you washing your hands with soap and water in response to the COVID-19 pandemic? | 1 (not at all)–4 (very much) | 0.03 |
Note. Principal components analysis was conducted with N = 382 since outlier removal based on mahalanobis distances had to be conducted after the rule-breaking composite score was calculated for each participant. ** p < 0.01, *** p < 0.001.
Bivariate correlations involving age, self-control, boredom proneness and COVID-19 rule-breaking.
| Age | Self- | Boredom | |
|---|---|---|---|
| Self-Control | 0.18 *** | ||
| Boredom | −0.29 *** | −0.71 *** | |
| COVID-19 Rule-Breaking | −0.15 ** | −0.34 *** | 0.51 *** |
Note. ** p < 0.01, *** p < 0.001. N = 376.
Hierarchical regression predicting COVID-19 rule-breaking.
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| Age | −0.01 | 0.00 | −0.15 | −3.02 | 0.003 | ||
| 0.02 | 0.003 | ||||||
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| Age | −0.02 | 0.00 | −0.18 | −3.36 | <0.001 | ||
| Gender | 0.19 | 0.10 | 0.10 | 1.87 | 0.063 | ||
| 0.01 | 0.063 | ||||||
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| Age | −0.00 | 0.00 | −0.03 | −0.61 | 0.544 | ||
| Gender | 0.19 | 0.09 | 0.10 | 2.13 | 0.034 | ||
| BPS | 0.04 | 0.00 | 0.51 | 10.91 | <0.001 | ||
| 0.23 | <0.001 | ||||||
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| Age | −0.00 | 0.00 | −0.03 | −0.59 | 0.553 | ||
| Gender | 0.20 | 0.09 | 0.10 | 2.16 | 0.031 | ||
| BPS | 0.04 | 0.00 | 0.54 | 8.28 | <0.001 | ||
| BSCS | 0.00 | 0.01 | 0.04 | 0.71 | 0.480 | ||
| 0.00 | 0.480 |
N = 376.