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Looking out for myself: Exploring the relationship between conspiracy mentality, perceived personal risk, and COVID-19 prevention measures.

ABSTRACT: OBJECTIVES:This research examined how conspiracy mentality may affect compliance with preventive health measures necessary to fight the COVID-19 pandemic, and the underlying motivations to comply. DESIGN AND METHOD:We conducted two cross-sectional studies (Study 1 N = 762, Study 2 N = 229) on a French population, measuring conspiracy mentality, compliance with preventive health measures, and perceived risks related to COVID-19. We also measured motivations to comply with preventive measures in Study 2. RESULTS:We show that people high in conspiracy mentality are likely to engage in non-normative prevention behaviours (Study 1), but are less willing to comply with extreme preventive behaviours that are government-driven (Study 2). However, we demonstrate that a perceived risk to oneself (risk of death) and a motivation to protect oneself can act as a suppressor: Conspiracy mentality is linked with an increase in the perception of risk to oneself, which, in turn, is associated with normative compliance. We also find that perceived risk of death explains the relationship between conspiracy mentality and non-normative prevention behaviours. CONCLUSIONS:Our studies showcase how people high in conspiracy theorizing may (dis)engage with prevention behaviours, but that perceived risk and motivation to protect oneself could increase these individuals' compliance.

SUBMITTER: Marinthe G

PROVIDER: S-EPMC7361332 | biostudies-literature | 2020 Jun

REPOSITORIES: biostudies-literature

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Looking out for myself: Exploring the relationship between conspiracy mentality, perceived personal risk, and COVID-19 prevention measures.

Marinthe Gaëlle G Brown Genavee G Delouvée Sylvain S Jolley Daniel D

British journal of health psychology 20200625 4

<h4>Objectives</h4>This research examined how conspiracy mentality may affect compliance with preventive health measures necessary to fight the COVID-19 pandemic, and the underlying motivations to comply.<h4>Design and method</h4>We conducted two cross-sectional studies (Study 1 N = 762, Study 2 N = 229) on a French population, measuring conspiracy mentality, compliance with preventive health measures, and perceived risks related to COVID-19. We also measured motivations to comply with preventiv ...[more]

PMID: 32583540

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Project description:AimCalculating a modelled workload based on objective measures. Exploring the relation between this modelled workload and workload as perceived by nurses, including the effects of specific job demands, job resources and personal resources on the relation.DesignAcademic hospital in the Netherlands. Six surgical wards, capacity 15-30 beds. Data collected over 15 consecutive day shifts.MethodsModelled workload is calculated as a ratio of required care time, based on patient characteristics, baseline care time and time for non-patient related activities, and allocated care time, based on the amount of available nurses. Both required and allocated care time are corrected for nurse proficiency. Five dimensions of perceived workload were determined by questionnaires. Both the modelled and the perceived workloads were measured on a daily basis. Linear mixed effects models study the longitudinal relation between this modelled and workload as perceived by nurses and the effects of personal resources, job resources and job demands. ANOVA and post-hoc tests were used to identify differences in modelled workload between wards.ResultsModelled workload varies roughly between 70 and 170%. Significant differences in modelled workload between wards were found but confidence intervals were wide. Modelled workload is positively associated with all five perceived workload measures (work pace, amount of work, mental load, emotional load, physical load). In addition to modelled workload, the job resource support of colleagues and job demands time spent on direct patient care and time spent on registration had the biggest significant effects on perceived workload.ConclusionsThe modelled workload does not exactly predict perceived workload, however there is a correlation between the two. The modelled workload can be used to detect differences in workload between wards, which may be useful in distributing workload more evenly in order prevent issues of over- and understaffing and organizational justice. Extra effort to promote team work is likely to have a positive effect on perceived workload. Nurse management can stimulate team cohesion, especially when workload is high. Registered nurses perceive a higher workload than other nurses. When the proportion of direct patient care in a workday is higher, the perceived workload is also higher. Further research is recommended. The findings of this research can help nursing management in allocating resources and directing their attention to the most relevant factors for balancing workload.

Dataset Information

Looking out for myself: Exploring the relationship between conspiracy mentality, perceived personal risk, and COVID-19 prevention measures.

Publications

Looking out for myself: Exploring the relationship between conspiracy mentality, perceived personal risk, and COVID-19 prevention measures.

Similar Datasets

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