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. 2025 Jul 23:13:1597941.
doi: 10.3389/fpubh.2025.1597941. eCollection 2025.

Insights from the front line: uplifting stories of the COVID-19 pandemic through the eyes of the public health workforce in Iowa

Heidi Haines  1 , Amanda Sursely  1 , Hanh Pham  1 , Rylee Beltran  1 , Daniel K Sewell  1 , Lina Tucker Reinders  2 , Natoshia Askelson  1 , Sarah Dixon  3 , Kaitlin Emrich  4 , Christine Estle  5 , Michelle Lewis  6 , Edith Parker  1 , Jimmy Reyes  7 , Laurie Walkner  1 , Kelly Wells Sittig  8 , Rima A Afifi  1
Affiliations

Insights from the front line: uplifting stories of the COVID-19 pandemic through the eyes of the public health workforce in Iowa

Heidi Haines et al. Front Public Health. .

Abstract

Introduction: SARS-CoV-2 was declared a pandemic in March 2020. Studies have characterized some of the negative impact of the pandemic on public health workers (PHW), but few have explored the strength and coping strategies used. Our study documents the experiences of PHW in Iowa during the pandemic.

Methods: We used an innovative mixed methods data collection tool, SenseMaker® to gather stories from PHW in Iowa between March and July 2022. Participants provided additional data about their story via structured follow-up questions. We conducted descriptive analyses of the quantitative questions. A qualitative thematic and sentiment analysis was applied to all stories.

Results: The final sample size was 163 stories. PHW who submitted stories identified as mostly white (93.9%), and women (83.4%). Respondents were most likely to feel that in the story they told: the ability to act was out of their control; the strongest influence was from political considerations; decisions were made out of necessity; they wished for more focus on evidence-based public health. PHW were most likely to describe their emotional state at the height of the pandemic as frustration (61%), uncertainty (55%), and helplessness (50%). Those who felt in control were more likely to express positive emotions. Qualitative thematic analysis of these stories revealed 8 themes, highlighting facilitators (e.g., strong partnerships and collaborations) and barriers (e.g., politicization and controversial government response) to effective pandemic response.

Discussion: The stories PHW shared powerfully illustrate the context of the pandemic in Iowa, a state that spent the least time under high stringency policies.

Keywords: COVID-19; SenseMaker; mental health; mixed-methods; public health workforce; rural health.

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Conflict of interest statement

The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.

Figures

Ternary plot showing distribution of PHW perspectives on factor driving decisions in their stories, across three axes: Organizational Values, Need, and Evidence. Each dot represents one participant's response. Dots are least likely to cluster on the evidence apex of the triangle.
Figure 1
Ternary plot showing PHW perspectives on factor driving decisions in their stories. Respondents were able to place their cursor anywhere in the triangle. This plot shows that many placed their cursor at one of the corners indicating that variable to account for the majority of the decision. Others placed their cursor in between the line linking need and organizational values, indicating that both those variables equally accounted for the decision.
Bar chart showing frequency distribution for responses from PHW workers for all submitted stories on a dyadic simplex question related to whether their story indicated actions that “used tried and tested approaches” or “Took a risk on something entirely new.” Respondents were able to pick a point anywhere between those two options. Frequencies peak in the middle suggesting that both strategies were used most often.
Figure 2
Dyadic bar chart showing PHW perspectives on whether the story they described included the use of tried and tested approaches, or took a risk on something entirely new. PHW were able to place their cursor anywhere along the 2-dimensional line. This graph shows the frequency with which PHW chose various positions on that line.
This figure combines (1) the ternary plot for PHW perspectives on whether their story was influenced by Social, cultural, and economic factors, Political decisions, and/or The way things are done around here; with (2) qualitative responses provided by respondents who selected various points in the triangle.
Figure 3
Ternary plot showing PHW perspectives on factor driving the experience of their stories. Stories were linked to quotations drawn from datapoints at the axes, with two examples shown here.
Bar graphs comparing emotional status of PHW during the pandemic at two points in time: at the height of the pandemic, and at the time of the survey (current). Frustration, uncertainty, and helplessness as the highest emotions, with confidence and hope as the lowest, at the height of the pandemic. Frustration and uncertainty are still highest at the time of the survey, while hope and confidence have increased, and fear has decreased significantly.
Figure 4
Percentage of PHW that selected these respective feelings as best describing their emotional status related to the pandemic's impact of their work in public health (A) at the height of the pandemic—in Winter 2020-Spring 2021, and (B) at the time of the survey—in Spring/Summer 2022. PHW could pick up to 3 feelings.
This figure presents five ternary scatter plots that compare answers of PHW to whether their story indicated they had control over the action, or it was out of their control, or they were able to act - for the overall sample, as well as for those who chose the following key emotion: Hope, Confidence, Anger, and Helplessness.
Figure 5
The relationship between public health workers' (PHW) perceived control in responding to the pandemic and their current pandemic-related emotions; each ternary point represents a unique story. The “Overall” central plot aggregates data from all participants, while the surrounding plots represent subsets of respondents who expressed certain emotions.
Ternary plot showing sentiment analysis distribution of all the stories submitted by positive, neutral, and negative categories. The size of each circle corresponds to the number of sentences in a story. Data points vary in size and color, with most points clustering toward the positive vertex.
Figure 6
Compositions of neutral, positive, and negative sentences in each story. The size of each circle corresponds to the number of sentences in a story.
See this image and copyright information in PMC

References

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