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Soares, P. Factors Associated with Patient's Decision to Avoid Healthcare. Encyclopedia. Available online: (accessed on 18 June 2024).
Soares P. Factors Associated with Patient's Decision to Avoid Healthcare. Encyclopedia. Available at: Accessed June 18, 2024.
Soares, Patrícia. "Factors Associated with Patient's Decision to Avoid Healthcare" Encyclopedia, (accessed June 18, 2024).
Soares, P. (2021, December 28). Factors Associated with Patient's Decision to Avoid Healthcare. In Encyclopedia.
Soares, Patrícia. "Factors Associated with Patient's Decision to Avoid Healthcare." Encyclopedia. Web. 28 December, 2021.
Factors Associated with Patient's Decision to Avoid Healthcare

The COVID-19 pandemic has resulted in changes in healthcare use. This study aimed to identify factors associated with a patient’s decision to avoid and/or delay healthcare during the COVID-19 pandemic. A data from a community-based survey in Portugal from July 2020 to August 2021, “COVID-19 Barometer: Social Opinion”, which included data regarding health services use, risk perception and confidence in health services, was used. The analysis was framed under Andersen’s Behavioural Model of Health Services Use and utilised Poisson regression to identify healthcare avoidance associated factors. Healthcare avoidance was high (44%). Higher prevalence of healthcare avoidance was found among women; participants who reported lower confidence in the healthcare system response to COVID-19 and non-COVID-19; lost income during the pandemic; experienced negative emotions due to physical distancing measures; answered the questionnaire before middle June 2021; and perceived having worse health, the measures implemented by the Government as inadequate, the information conveyed as unclear and confusing, a higher risk of getting COVID-19, a higher risk of complications and a higher risk of getting infected in a health institution. It is crucial to reassure the population that health services are safe. Health services should plan their recovery since delays in healthcare delivery can lead to increased or worsening morbidity, yielding economic and societal costs.

healthcare avoidance health services COVID-19 risk perception

1. Introduction

The World Health Organization (WHO) declared the novel coronavirus disease 2019 (COVID-19) a global pandemic on 11 March 2020 [1]. Restrictive measures were implemented to contain the pandemic, such as lockdowns, stay-at-home orders, movement restriction and closure of schools and non-essential businesses [2][3]. Additionally, several countries temporarily cancelled non-urgent medical activity to ensure the best care for COVID-19 cases, diverting attention from non-COVID-19 care and a reduction in care for these conditions [2][3][4][5]. The health services reorganisation might partially explain this reduction to respond to COVID-19, but the reduction might also be explained by the patient’s avoidance or delay regarding attending healthcare due to the fear of getting COVID-19. The latter phenomenon is known as healthcare avoidance and was previously described in response to a traumatic or threatening situation like this pandemic [6][7]. Healthcare avoidance can be characterised as cancelling appointments, nonadherence to treatment and delaying or avoiding medical care due to fear or denial of symptoms and diagnosis, among other factors [6][8][9]. The impact of COVID-19 is yet to be fully determined, but existing evidence suggests that changes in healthcare utilisation are in the pathway of COVID-19 indirect effects [3].
The frequency of healthcare avoidance during the pandemic and potential drivers were analysed in previous studies [4][7][8][10][11][12]. The impact of healthcare avoidance on health outcomes has not yet been fully described, although excess non-COVID-19 mortality was observed in the past few months, which could be explained by healthcare avoidance [13][14][15]. Findling et al. [10] reported that more than half of those avoiding healthcare in the USA experienced negative health consequences, underlining the importance of understanding which factors may be associated with healthcare avoidance. Reasons to avoid healthcare included the closure of medical offices, fear of contracting COVID-19 and financial difficulties resulting from the pandemic [7][10]. Other factors related to healthcare avoidance are poor health perception, the number of comorbidities and living in highly COVID-19-affected residential areas [8][11][12]. In addition, healthcare avoidance was linked to risk perception, a subjective psychological construct influenced by cognitive, emotional and cultural factors [16]. Risk perceptions are frequently subject to bias. While unrealistic optimism about health risks may result in false feelings of security and lack of precaution, pessimistic bias may lead to excessive mass scares and dissuade people from seeking healthcare [17]. Other factors, such as age, household income, education and having health insurance, were described inconsistently across the literature, suggesting that context and cultural differences in healthcare might explain these differences.
Studies on previous epidemics found that individuals who avoided healthcare due to fearing infection exacerbated the severity of the disease and indirectly increased mortality through reduced access to treatment [18][19]. Furthermore, return to pre-pandemic activity levels might take a few years [19][20]. Thus, understanding the extent and factors associated with avoidance could be useful to support the development of interventions to address it [17].

2. Predisposing Factors

The prevalence of avoiding healthcare was higher for women than men (aPR: 1.27, 95% CI: 1.20–1.35) (Figure 1). A higher prevalence of healthcare avoidance was also found for individuals with low confidence in the responses of health services to COVID-19 and non-COVID-19 compared with individuals reporting higher trust in the health services (aPR: 1.19, 95% CI: 1.13–1.25 and aPR: 1.24, 95% CI: 1.18–1.30, respectively) (Figure 1). Young adults and individuals who reported living in the North, Center or Azores had a lower prevalence of healthcare avoidance than working-age adults and individuals who reported living in Lisbon and Tagus Valley (Figure 1).
Figure 1. Forest plot of healthcare avoidance for predisposing and enabling factors. Adjusted prevalence ratio (adjusted for gender, age group, region, education, health perception and period of the questionnaire) and the respective 95% confidence intervals are denoted by black dots and black lines, respectively.

3. Enabling Factors

The prevalence of healthcare avoidance was higher for participants who lost income during the pandemic than individuals who did not (aPR: 1.10, 95% CI: 1.04–1.15) (Figure 1).

4. Need for Care

Participants who perceived their health status as reasonable or bad had a higher prevalence of healthcare avoidance than participants who perceived their health as good (aPR: 1.25, 95% CI: 1.19–1.31 and aPR: 1.38, 95% CI: 1.23–1.54, respectively) (Figure 2). Similarly, participants with one disease had a higher prevalence of healthcare avoidance than participants without diseases (aPR: 1.06, 95% CI: 1.01–1.12) (Figure 2).
Figure 2. Forest plot of healthcare avoidance for the need for care and COVID-19-specific factors. Adjusted prevalence ratio (adjusted for gender, age group, region, education, health perception and period of the questionnaire) and the respective 95% confidence intervals are denoted by black dots and black lines, respectively.

5. COVID-19-Specific Factors

Participants who perceived their risk of getting COVID-19 as low or non-existent had a lower prevalence of healthcare avoidance than those who perceived a high risk (aPR: 0.88, 95% CI: 0.82–0.95) (Figure 2). Similarly, participants who perceived their risk of having complications following a diagnosis of COVID-19 as low or non-existent or were unsure had a lower prevalence of healthcare avoidance than those who perceived their risk as high (aPR: 0.82, 95% CI: 0.77–0.88 and aPR: 0.91, 95% CI: 0.84–0.99, respectively) (Figure 2). 

6. Research on  Why the Patient’s  Avoided Healthcare during the COVID-19 Pandemic

A higher prevalence of healthcare avoidance in women and participants with low confidence were found in the health response to COVID-19 and non-COVID-19 conditions. Likewise, a higher prevalence of healthcare avoidance was reported by those who lost income during the pandemic; did not perceive their health as good; and experienced sadness, anxiety or agitation due to physical distancing measures.

The prevalence of healthcare avoidance is widely variable within and between countries, with studies in the United States, Australia and South Korea reporting estimates between 15 and 73%, and 10 to 12% avoiding urgent care and around 32% avoiding routine care [8][10][11][12][21]. Studies exploring the factors associated with healthcare avoidance during the COVID-19 pandemic are still scarce. However, some factors seem consistent across the literature. It is found that the prevalence of healthcare avoidance was higher for participants who did not perceive their health as good; had one disease; and experienced frequent feelings of anxiety, sadness and agitation. These results are in agreement with the literature, with a higher prevalence of healthcare avoidance for individuals with poor health perception, comorbidities, disabilities and symptoms of anxiety and depression [11][12][21][22]. A higher prevalence of healthcare avoidance in women was also found in the literature [8][11][21]. Behavioural differences might explain this finding since previous studies found that women perceived themselves as more vulnerable to illnesses, were more likely to use health services during pain episodes and, in general, visited general practitioners more often than men [23][24]. Higher odds of healthcare avoidance were found for individuals who lived in highly COVID-19-affected areas [8].

Participants who perceived their risk of getting COVID-19 and complications as low or non-existent had a lower prevalence of healthcare avoidance than those who perceived their risk as high. However, this finding was not replicated in one study that dichotomised the self-perceived risk of having severe COVID-19 [12], suggesting that the different results obtained among different studies might be due to methodological differences.


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