key: cord-0929050-r9hgqdfy
authors: Hawkins, Maren M.; Lopez, Alexa A.; Schmitt, Marin E.; Tamkin, Vivian L.; Dressel, Anne E.; Kako, Peninnah; Mkandawire‐Valhmu, Lucy; Weinhardt, Lance S.
title: A qualitative analysis of perceptions of and reactions to COVID‐19
date: 2022-02-05
journal: Public Health Nurs
DOI: 10.1111/phn.13052
sha: 3fae78886d316b4e47f0db5887586f74da85fc14
doc_id: 929050
cord_uid: r9hgqdfy

OBJECTIVE: To understand communities’ perceptions, beliefs, and health‐related behavior choices related to COVID‐19 in order to guide public health nursing communication and interaction with patients and the community. DESIGN: A qualitative study, guided by the Health Belief Model (HBM), strove to comprehend the perceptions and reactions to COVID‐19 among Wisconsinites. SAMPLE: Twenty‐five diverse Wisconsin residents aged 18 or older. MEASUREMENTS: Semi‐structured interviews provided information about individuals’ attitudes, perceptions, and reactions to COVID‐19. Interviews were audio‐recorded, transcribed, and thematic analysis was conducted to identify themes. RESULTS: We identified three major themes: (1) “health care starts way before you ever enter the doors of a healthcare facility”; (2) “to live in a society is to help each other”; and (3) mental health as impacted by COVID‐19. CONCLUSIONS: This study demonstrated the need for greater public health support, as well as the role of Social Determinants of Health. Understanding perceptions and reactions to COVID‐19 can help public health nurses understand and better respond to future pandemics.

As of December 2021, over 10,000 people have died from in Wisconsin (COVID-19, 2021a ) and over one million cases have been reported (COVID-19, 2021b) . Early in the pandemic, Wisconsin received national attention due to the implementation and then striking down of public health orders designed to curb the spread of COVID-19. For example, the Wisconsin Supreme Court blocked an attempt by Governor Tony Evers to delay the April 2020 election and extend the absentee ballot deadline due to health and safety concerns (Liptak, 2020) . Republican members of Wisconsin's legislature also challenged the Governor's Safer-at-Home order. The Safer-at-Home order was then ended by the Wisconsin Supreme Court in mid-May 2020, leaving Wisconsin with no unified plan for addressing the pandemic. Each of Wisconsin's 72 counties was left to make different, independent decisions about how to curb the spread of COVID-19 (Johnson, 2020) .

It is against the backdrop of this political climate in Wisconsin that we conducted our qualitative study to examine Wisconsinite's perceptions of and reactions to the COVID-19 pandemic. Conducted early in the pandemic (March-June 2020), we asked participants what they thought about COVID-19, their sentiments about quarantine, and how COVID-19 was impacting them, individually and in their communities.

Wisconsin, a state in the upper Midwest of the United States (U.S.), is home to 5,822,434 people (U.S. Census Bureau QuickFacts, V2019).

Moreover, Wisconsin is 46th out of 50 U.S. states for its public health spending (Wisconsin Department of Health Services, 2019), meaning that Wisconsin's public health sector was strained and underfunded well before the COVID-19 pandemic. Additionally, political decisions made before the pandemic impeded Wisconsin's COVID-19 response.

Specifically, in 2018 after former Governor Scott Walker lost his reelection campaign to current Governor Tony Evers, Walker, along with the Republican-controlled legislature, passed a series of laws which were later upheld by the Wisconsin Supreme Court in 2020 (White, 2020) . These laws limited some of the Governor's power (White, 2020) , and gave "lawmakers more power to intervene in lawsuits involving the state, to approve legal settlements involving the state, and to block administrative rules written by the Evers administration" (White, 2020) . In essence, the lack of public health funding and such political actions meant that Wisconsin was in a precarious situation to handle any health emergency prior to COVID-19.

This lack of funding and overturning of rules meant to protect the public's health had harsh consequences for Wisconsin residents. By

October 2020, Wisconsin had one of the worst COVID-19 outbreaks in the U.S. (Burakoff, 2020; COVID-19, 2020b context, not only did we interview Wisconsinites, but we also applied a theoretical framework to inform our study.

The Health Belief Model (HBM) guided our study, as it has commonly been used to examine reluctance to participate in various public health programs or initiatives (Champion & Skinner, 2008) . The HBM posits that one's health-related behavior is largely impacted by perceived threats, benefits, and barriers to engaging in a particular behavior, as well as relevant cues to action and self-efficacy (Champion & Skinner, 2008) . Perceived threats include perceptions of susceptibility to and severity of health problems. This framework provided structural direction for the development of interview questions.

IRB approval from the University of Wisconsin-Milwaukee was obtained prior to beginning our study. Participants were 18 years of age or older, Wisconsin residents, English-speaking, and provided informed consent as explained in further detail below.

We employed a single-series cross-sectional qualitative design to conduct our observational research (Salazar et al., 2015) .

Between March and June 2020, we conducted semi-structured interviews with 25 residents of Wisconsin. Purposive snowball sampling was used to ensure a diverse sample of Wisconsinites over the age of 18, and also to ensure we reached "hard-to-reach populations and their networks" (Salazar et al., 2015, p. 168) . Recruitment was a challenge due to COVID-19 and the Safer-at-Home order. As a result, many organizations were closed (Radcliffe & Caughey, 2021) , and organiza-

tions that were open, such as healthcare organizations, were too busy to respond. For this reason, we contacted community stakeholders for recruitment purposes, who were identified through a discussion among the lead authors, all of whom have lived or worked in Wisconsin for a minimum of 10 years. We contacted the stakeholders and either interviewed them directly and/or asked for referrals of who to contact. A standardized referral script was emailed to organizations and individuals so that each participant received the same introductory information about the study.

Stakeholder engagement was crucial in this study to establish trust.

Many of the community stakeholders were religious or non-profit leaders. This was an important step because some participants would not speak with the research team until after they had spoken with their community leader (the community stakeholder) about the trustworthiness of us and our study. The community stakeholders were thus considered community gatekeepers (Joseph et al., 2016) . We sought out community stakeholders and those within their network of different ages, race/ethnicities, and occupations, to reach saturation. Hence, snow-ball sampling was ideal for this study due to the challenges presented by COVID-19 and because we were able to reach a broad range of people (Tolley et al., 2016) . Figure one illustrates our recruitment ( Figure 1 ). Those listed at the beginning of each web are stakeholders. However, if they are listed as participants, it means they are stakeholders who were also interviewed. If it simply says stakeholder, they referred others without being interviewed themselves.

We e-mailed all participants the consent form approximately 24 h ahead of time to review, and we obtained verbal consent for this study.

This was to allow time for thorough review of the consent form and for answering any questions. Participants consented to the interview and its recording. All interviews were conducted over the phone, recorded, and transcribed, deidentified, and checked for accuracy.

Once accuracy was confirmed, the original recording was destroyed to ensure confidentiality.

The semi-structured interview guide was developed based on Aday and Cornelius's (2006) and Blair et al.'s (2013) recommendations for interview guide creation. Thus, the interview guide started with more general questions and then transitioned to more specific questions.

We did not ask any "double-barreled" questions (Blair et al., 2013) , meaning, we asked one question about one specific issue at a time.

We also avoided leading questions about COVID-19, and instead, we asked questions such as, "what are your thoughts about COVID-19?"

"When did you first hear about COVID-19?," "Who did you hear this information from?," and "What do you think of COVID-19?" Moreover, every participant was asked identical questions in the same order.

While the HBM did inform our study, to avoid leading questions we did not ask any specific questions on perceived threat of susceptibility to COVID-19.

Finally, we did not ask demographic questions until the very end of the interview. These questions were: "How old are you? How do you self-identify your race or ethnicity? How do you self-identify your gender?" While asking for county of residence was not explicitly in the interview guide, it did come up in most interviews. Therefore, we were able to determine that all participants resided in southeastern Wiscon-sin and 76% (n = 19) of the participants resided in Milwaukee County.

In total, we asked 20 questions, and the interviews took an average of 30 min to complete.

Wisconsin's Safer-at-Home order began on March 25, 2020, and required all residents to stay home as much as possible; all nonessential businesses and operations were stopped, drawn down to a minimum, or remote (work from home) (WI DHS, 2020, p. 19). While the study began on March 30, the Safer-at-Home order was ended by the Wisconsin Supreme Court on May 13, 2020. There had originally been a planned, slow reopening based on certain criteria for COVID-19 case numbers (WI DHS, 2020). However, after the Safer-at-Home order was struck down, openings varied in Wisconsin by city and by county. We conducted 19 of our 25 interviews before the Safer-at-Home order was prematurely struck down. We conducted six more interviews between May 13 and June 29. In a sub-sample analysis, the themes identified in those six interviews did not differ from the initial 19 interviews; therefore, we chose to include all 25 interviews in our final analysis. We conducted interviews until we reached data saturation (Morse, 2014; Tolley et al., 2016) . All interviews were conducted over the phone and recorded using a Yeti microphone and Presonus software (Blue-Yeti, n.d.; Studio One, |PreSonus, n.d.). Interviews took an average of 30 min, although some lasted up to one hour. MH, who completed all the interviews, also took notes during each interview.

Data analysis consisted of a qualitative thematic analysis (Tolley et al., 2016) and was carried out by two co-authors. The analyses were further reviewed by a third co-author to ensure the verifiability and dependability of our findings (Morse, 2014; Tolley et al., 2016) . Working with multiple coders aids to "offset the subjective bias of any one researcher" (Tolley et al., 2016, p. 213 ) thereby enhancing dependability. To ensure credibility, we examined negative cases, possible differing explanations, and incorporated investigator triangulation, and theoretical triangulation, as evident in our design and discussion (Flick, 2008; Morse, 2014; Tolley et al., 2016) .

As discussed previously, each participant was asked the same questions in the same order, thereby improving validation (Morse, 2014) .

The authors developed a codebook and kept record of their audit trail during the analysis, which included process notes, data reduction notes, data reconstruction notes, and detailed materials about the study (Morse, 2014) . Moreover, in the development of our inclusive codebook, we included, both definitions and example responses, and we also had regular meetings among the coders to order to ensure consistency (Morse, 2014) . All of these actions helped us ensure validity.

Participants ranged in age, 36% were between the ages of 20 and 29, 16% were between the ages of 30 and 39, 8% were between the ages of 40 and 49, 24% were between the ages of 50 and 59, and 16%

were between the ages of 60 and 69 (Table 1) . Additionally, 36% of participants were White, 20% were Black/African American, 16% were South-East Asian, 4% were Central Asian, 4% were Southern Asian, 8%

were Latinx, and 12% were biracial (Table 1) . Moreover, 60% of participants identified as female, 36% identified as male, and 4% as Gender Queer (Table 1) . Finally, 28% of participants had children under the age of 18, 28% of participants were unable to work from home, and 20% of participants worked in healthcare (Table 1) .

Based on the interviews, we identified the following three themes:

(1) "Health care starts way before you ever enter the doors of a healthcare facility"; (2) "To live in a society is to help each other"; and (3) mental health as impacted by COVID-19. 

The theme of mental health included three sub-categories: mental health generally, mental health and routine, and mental health among parents with young children.

For some participants COVID-19 disrupted planned events they had been were looking forward to, which they perceived negatively impacted them. One participant in their 30s who was working from Another participant in their 30s, working in the non-profit sector, describe the challenge of suddenly managing everything online and from home, saying: "I have no concept of the days or the time anymore." -Participant 11

Importantly, a participant noted that the impacts of COVID-19, and specifically the impacts of COVID-19 on routine, would have impacts both during and after the pandemic is over. They said:

"And so I think there's a, you know, both the, the concern of the disease itself on the physical side, but then also just Importantly, public health nurses are in a unique and advantageous position regarding the intersection between public prevention and clinical care. For example, it has been recommended that nurses conduct a SDOH screening with patients (Bradywood et al., 2021) , yet currently, only one-third of hospitals conduct SDOH screenings (Bradywood et al., 2021) . Implementing this screening more widely may provide a more illuminating picture of the factors intersecting with COVID-19 risk, and its implications. Additionally, as noted by the Council of Public Health Nursing Organizations, "[Public health nurses] are uniquely prepared with the knowledge, skills and experience to partner across all components of the health system and within various community sectors" (Levin et al., 2016, p. 3), and thus public health nurses are in a position to navigate the juncture between COVID-19 and SDOH.

Notably, however, SDOH requires attention prior to an emergency, because the COVID-19 emergency may simply be one emergency on top of several others. In essence, these emergencies may exacerbate one another. For example, Milwaukee was and is still facing a lead crisis (Martinez, 2021) . SDOH needs to be addressed before we are encountering emergencies on multiple fronts.

Regarding theme two, the support for public health responses to the pandemic (i.e., the Safer-at-Home order) is based on a sense of community cohesion and support. By community cohesion we draw on Beider's (2012) definition. According to Beider (2012) , community cohesion involves a sense of community, relationships among community members, and a sense of one's rights and responsibilities to and in a community. Participants stated that due to a sense of responsibility in their communities, they would engage in safer behaviors.

Moreover, public health nursing and public health, in general, need more support. Public health in Wisconsin is extremely underfunded, which impacts every part of dedicated public health officials' ability to do their jobs. For example, other researchers have found that early clear and consistent messaging from officials, particularly in the media, could "proactively address public perception" (Al-Ramahi et al., 2021) . Greater support for public health could enhance messaging and other health campaigns, building upon the strengths of communities, such as strong community cohesion, to improve future pandemic responses. Understanding and addressing public perception is important in creating programs, guidelines, mandates, etc. that are effective and adhered to.

There are several limitations to our study. First, there is the threat of selection bias given that we used a form of convenience sampling (Salazar et al., 2015) . Second, all participants were from southeastern

Wisconsin. Hence, we sampled a predominantly urban populace which may differ in perceptions from a more rural populace. For example, Milwaukee maintained mask mandates while representatives from more rural counties such as Racine, Dodge, and Jefferson counties fought the Safer-at-Home order (Gerlach, 2020). Third, interviews were conducted over the phone, thus we may have missed non-verbal cues.

Finally, interviews were only conducted with English speakers, hence we lacked the perspectives of non-English speakers.

Understanding perceptions and reactions to COVID-19 can help inform public health nurses, healthcare professionals, and policymakers in improving communication, compliance, and understanding of pandemic response. We conducted our study in Wisconsin, against the backdrop of political turmoil impacting the public health response, to examine Wisconsinite's perceptions and reactions to COVID-19 within this context. Participants noted that many factors-besides health care-such as employment, employer requirements, and living arrangements impacted their health, and especially their mental health. They also recognized how their health behaviors impacted others; hence while some expressed frustration with public health mandates, they also expressed support. Our findings demonstrate that public health needs greater support to fulfill its goal of preventing disease. Understanding perceptions and reactions to COVID-19 can help public health nurses and other healthcare professionals understand and better react to future pandemics.

This study was approved by the University of Wisconsin-Milwaukee Institutional Review Board.

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The authors elect not to share data. 

Peninnah Kako PhD, RN https://orcid.org/0000-0002-1071-5785