Abstract
Objective:
The purpose of this study is to describe individual and organizational characteristics among those who report working remotely and examine how concordance between public health employees’ work preferences and their actual work situations relates to burnout, satisfaction, and intention to leave.
Design:
This cross-sectional study utilizes the 2024 Public Health Workforce Interests and Needs Survey (PH WINS). Bivariate relationships were analyzed by conducting chi-squared tests of individual and organizational characteristics by respondents’ reported work situation, work preference, and concordance between work situation and work preference. Multivariate logistic regression models of workforce outcomes were performed holding race/ethnicity, gender, age, education level, public health degree attainment, role classification, tenure at current agency, current employer, current employment status, full-time employee, supervisory status, setting, and governance constant.
Setting:
A nationally representative sample of government public health employees.
Participants:
55 742 government public health employees.
Main Outcome Measures:
Job satisfaction, burnout, and intention to leave.
Results:
Among respondents, most worked in-person, and 52.2% reported that their work situation matched their preference. Job satisfaction was high for the majority of respondents. Nearly 20% reported burnout, and 24.8% reported that they intended to leave their organization within a year. Work situation and preference varied significantly by age, education, tenure, employment status, and organizational setting. Older and less educated staff were more likely to work in their preferred setting (in-person). Multivariate models showed that concordance between work situation and preference was significantly associated with higher satisfaction and lower burnout and intent to leave.
Conclusions:
Findings show that employees whose work situations align with their work preferences report higher job satisfaction, lower burnout, and decreased intention to leave their organizations. These effects are most pronounced among younger and highly educated workers, who experience more difficulty in achieving this alignment.
Keywords: burnout, intention to leave, job satisfaction, public health workforce, remote work
Introduction
The public health workforce has faced mounting challenges in recent years, with concerns over burnout, recruitment, and retention becoming increasingly urgent.1-4 These issues have been exacerbated by the demands of the COVID-19 pandemic, which intensified workloads and stretched the workforce.5-8 As a result, recent studies suggest that many public health professionals are leaving the field or considering career changes, raising concerns about government public health’s capacity to respond to both current and future public health needs.5,7
One avenue for addressing these workforce issues lies in improving the workplace environment, an area over which public health organizations have considerable influence. A study using 2017 Public Health Workforce Interest and Needs Survey (PH WINS) data found that the workplace environment is a significant reason that individuals working in a State Health Agency Central Office (SHA-CO) considered leaving their job.4 The COVID-19 pandemic created a shift in workplace norms, forcing many employees to work remotely. The prolonged pandemic eventually changed employer and employee expectations and preferences around remote work. A study using 2021 PH WINS data to look at trends in intention to stay in one’s current job before and after the COVID-19 pandemic found that flexibility (eg, flex hours/telework) was a leading reason for employees’ intention to stay.5 Another study using qualitative data from PH WINS 2021 found that the majority of comments around telework were predominantly positive.9 However, some workers reported that there were inequities in who was given the opportunity to telework, highlighting variation within and across settings.9
Across the US workforce, preferences and options for remote work have evolved following the pandemic.10,11 While the 2021 PH WINS data hint at the perceived value of “telework” for the public health workforce, the 2024 iteration of PH WINS is the first to explicitly ask about work preferences and experiences between different work settings. It would be valuable to know both preferences for remote work and experiences with remote work within government public health settings. Additionally, understanding whether there is a match or concordance between preferences and options for work setting relates to key workforce outcomes such as recruitment, retention, and overall job satisfaction. Specifically, it would be of value to know whether employees who are able to work in their preferred setting experience lower burnout, greater satisfaction, or decreased intent to leave compared to those whose preferences are not met. However, there is currently limited empirical research on how remote work preferences and experiences align in government public health and how this alignment affects workforce outcomes. This lack of evidence limits the ability of public health agencies to make informed decisions about work arrangements that could stabilize and strengthen the workforce.
The purpose of this study is to first describe individual and organizational characteristics among those who report working remotely using the PH WINS 2024 survey. Additionally, we will examine how concordance between public health employees’ work preferences and their actual work situations relates to burnout, satisfaction, and intention to leave. By exploring these relationships, this research aims to inform organizational policies that better support the public health workforce in the post-pandemic era.
Methods
Data
PH WINS is a nationally representative survey of government public health employees in the United States. Administered and supported by the de Beaumont Foundation and the Association of State and Territorial Health Officials (ASTHO), PH WINS is conducted every 3 to 4 years, providing longitudinal information about the public health workforce since 2014. Detailed survey design and sampling methods have been described by Robin and colleagues.12
Inclusion/exclusion criteria
This study included government public health workers whose job roles could feasibly allow them flexibility in work situations and preferences. Thus, respondents whose job roles were “custodial” (n = 67, 0.1%), “other” (n = 123, 1.3%), or undefined (n = 63, 0.1%) were excluded from analyses.
Dependent variables
Three dependent variables were examined: job satisfaction, burnout, and intention to leave.
Job satisfaction
Four individual PH WINS questions were included about job satisfaction broadly. These questions asked about job, organization, pay, and benefits satisfaction. Each type of satisfaction was measured using a 4-point Likert scale with the prompt, “I am satisfied with my [variable].” Following prior approaches for working with these variables,3,13 all 4 satisfaction variables were dichotomized, where “Agree” and “Strongly Agree” were coded together as satisfied, and “Disagree” and “Strongly Disagree” were coded together as not satisfied.
Burnout
Burnout was measured by asking respondents to describe their current level of burnout. Respondents could choose 1 of 4 answers: “I have no symptoms of burnout,” “I have one or more symptoms of burnout that come and go away,” “I have one or more symptoms of burnout that won’t go away,” or “I am completely burnout, my symptoms won’t go away.” To create a binary indicator for burnout (ie, “burnout” vs “no burnout”), we categorized “I have no symptoms of burnout” and “I have one or more symptoms of burnout that come and go away” as no burnout and “I have one or more symptoms of burnout that won’t go away” and “I am completely burnout, my symptoms won’t go away” as burnout.
Intention to leave
Respondents were asked to indicate whether they were considering leaving their organization within the next year and, if so, why. We dichotomized this variable to “yes” for those who reported any reason for leaving other than retirement, and “no” for those who reported they were not considering leaving.1,14
Independent variable
Concordance between work situation and work preference
Concordance between work situation and work preference was defined as the degree of similarity or agreement between remote work preference and actual work situation. Respondents were asked to describe (1) their current work situations and (2) current work preferences. Both questions offered the following options: “completely in-person,” “mostly in-person, with some remote work,” “mostly remote, with some in-person,” or “completely remote.” A binary work concordance variable was created to indicate where there was agreement between the respondent’s current work situation and their reported work preference (coded as 1 = concordant, 0 = discordant).
Analysis
Unweighted and weighted descriptive statistics were calculated for all respondents included in this study. Bivariate relationships were analyzed by conducting chi-squared tests of individual and organizational characteristics by respondents’ reported work situation, work preference, and concordance between work situation and work preference. Next, we used multivariate logistic regression models to examine the association between work situation/work preference concordance and satisfaction (job, organization, pay, and benefits), burnout, and intention. We controlled for individual characteristics, race/ethnicity, gender, age, education level, public health degree attainment, role classification, tenure at current agency, current employer (state or local government), current employment status (contractor, permanent, intern, federal, temporary, or AmeriCorps), full-time equivalent (full-time or part-time), and supervisory status (non-supervisor, supervisor/manager, executive). Additionally, we included setting and governance as organizational control variables. We accounted for the complex sampling design of PH WINS by using the survey and balanced repeated replication weights provided by the de Beaumont Foundation. Because of our study’s large number of comparisons, our α value of significance was adjusted according to the Bonferroni correction and set at .02 for all bivariate and multivariate analyses. Findings were considered marginally significant if P values were between .05 and .02. All data were analyzed using Stata, Version 19 (College Station, Texas). This study was deemed exempt by the Indiana University Institutional Review Board (#27091).
Results
Demographics
The study sample included 55 742 respondents (234 583 weighted responses). Demographic characteristics of this sample are displayed in Table 1. Of the respondents, the majority worked only in-person (n = 108 286, 46.2%) or mostly in-person with some remote work (n = 70 387, 30.1%). About half of the respondents (n = 122 095, 52.2%) reported concordance between their work situation and preference.
TABLE 1.
Unweighted and Weighted Descriptive Statistics Among Respondents to PH WINS 2024
| N (%) | Weighted N (%) | |
|---|---|---|
| Total | 55 742 | 234 583 |
| Variables of interest | ||
| Work situation | ||
| In-person only | 24 676 (44.3) | 108 286 (46.2) |
| Mostly in-person, some remote | 17 264 (31.0) | 70 387 (30.1) |
| Mostly remote, some in-person | 11 056 (19.9) | 45 277 (19.3) |
| Remote only | 2665 (4.8) | 10 283 (4.4) |
| Work preference | ||
| In-person only | 10 578 (19.0) | 47 755 (20.4) |
| Mostly in-person, some remote | 20 700 (37.2) | 86 638 (37.0) |
| Mostly remote, some in-person | 17 465 (31.4) | 71 516 (30.6) |
| Remote Only | 6885 (12.4) | 28 208 (12.1) |
| Concordance between work situation and work preferencea | ||
| Concordant | 29 163 (52.4) | 122 095 (52.2) |
| Discordant | 26 445 (47.6) | 111 893 (47.8) |
| Job satisfactionb | ||
| Satisfied | 48 057 (86.6) | 200 745 (86.0) |
| Not satisfied | 7411 (13.4) | 32 625 (14.0) |
| Organization satisfactionb | ||
| Satisfied | 40 358 (78.1) | 167 283 (77.1) |
| Not satisfied | 11 295 (21.9) | 49 573 (22.9) |
| Pay satisfactionb | ||
| Satisfied | 29 170 (57.2) | 120 058 (56.1) |
| Not satisfied | 21 796 (42.8) | 93 835 (43.9) |
| Benefits satisfactionb | ||
| Satisfied | 42 568 (83.6) | 176 252 (82.3) |
| Not satisfied | 8359 (16.4) | 37 465 (17.5) |
| Burnoutc | ||
| Yes | 10 798 (19.4) | 46 080 (19.7) |
| No | 44 840 (80.6) | 188 067 (80.3) |
| Intention to leaved | ||
| Yes | 13 569 (24.3) | 58 177 (24.8) |
| No | 42 173 (75.7) | 176 407 (75.2) |
| Individual characteristics | ||
| Race/ethnicity | ||
| White | 34 490 (63.3) | 141 773 (61.8) |
| Black/African American | 7381 (13.6) | 33 006 (14.4) |
| Hispanic or LatinX | 4986 (9.2) | 21 331 (9.3) |
| Other | 7611 (14.0) | 33 259 (14.5) |
| Gender | ||
| Female | 43 734 (79.7) | 184 011 (79.6) |
| Male/other | 11 163 (20.3) | 47 043 (20.4) |
| Age | ||
| ≤35 years | 14 566 (26.2) | 59 436 (25.4) |
| 36-45 years | 14 254 (25.6) | 59 506 (25.4) |
| 46-55 years | 14 226 (25.6) | 60 278 (25.8) |
| ≥56 years | 12 556 (22.6) | 54 779 (23.4) |
| Education level | ||
| No college degree | 8159 (14.7) | 33 936 (14.6) |
| Associate’s degree | 6559 (11.8) | 29 555 (12.7) |
| Bachelor’s degree | 21 261 (38.4) | 88 337 (38.0) |
| Master’s degree | 16 578 (30.0) | 69 528 (29.8) |
| Doctoral degree | 2838 (5.1) | 11 724 (5.0) |
| PH Degree | ||
| Yes | 12 117 (21.9) | 181 756 (22.0) |
| No | 43 278 (78.1) | 51 324 (78.0) |
| Role | ||
| Administrative Staff & Leadership | 15 287 (27.6) | 65 910 (28.2) |
| Clinical, Behavioral, & Social Services | 15 786 (28.5) | 69 061 (29.6) |
| Public Health Programs, Research, Assessment, & Surveillance | 24 305 (43.8) | 98 002 (42.0) |
| Other | 93 (0.2) | 397 (0.2) |
| Tenure in current agency | ||
| 0-5 years | 29 362 (54.4) | 123 032 (54.2) |
| 6-15 years | 14 275 (26.5) | 60 291 (26.6) |
| ≥16 years | 10 296 (19.1) | 43 506 (19.2) |
| Current employer | ||
| State government | 26 618 (49.9) | 105 461 (47.1) |
| Local government | 26 673 (50.1) | 118 495 (52.9) |
| Employment status | ||
| Contractor providing services to the health department | 2214 (4.0) | 9564 (4.1) |
| Permanent staff employed by the health department | 50 850 (91.7) | 213 970 (91.7) |
| Intern employed by the health department | 123 (0.2) | 630 (0.3) |
| Federal employee detailed to the health department | 1904 (3.4) | 7698 (3.3) |
| Temporary staff employed by the health department | 303 (0.6) | 1213 (0.5) |
| AmeriCorps member serving at the health department | 45 (0.1) | 185 (0.1) |
| FTE | ||
| Full-time | 51 965 (93.2) | 217 435 (92.7) |
| Part-time | 3777 (6.7) | 17 148 (7.3) |
| Supervisory level | ||
| Non-supervisor | 40 148 (72.0) | 167 751 (71.5) |
| Supervisor/manager | 13 859 (24.9) | 59 209 (25.2) |
| Executive | 1735 (3.1) | 7624 (3.6) |
| Organizational characteristics | ||
| Setting | ||
| SHA-CO | 17 912 (32.1) | 62 751 (26.8) |
| Large LHD | 23 725 (42.6) | 106 219 (45.3) |
| Medium LHD | 11 505 (20.6) | 44 618 (19.0) |
| Small LHD | 2600 (4.7) | 20 995 (9.0) |
| Governance | ||
| Centralized | 6726 (12.2) | 31 126 (13.4) |
| Decentralized | 37 457 (67.8) | 160 144 (68.8) |
| Mixed | 4419 (8.0) | 19 960 (8.6) |
| Shared | 6682 (12.1) | 21 402 (9.2) |
Abbreviations: FTE, full-time equivalent; LHD, local health department; SHA-CO, State Health Agency Central Office.
Source: Public Workforce Interests and Needs Survey, 2024. National survey and replication weights provided by the de Beaumont Foundation.
Notes: National survey and replication weights provided by the de Beaumont Foundation.
Concordance is a binary indicator of whether there was agreement between the respondent’s report of work situation and the respondent’s report of work preference.
Satisfaction is a binary indicator of whether the respondent reports satisfaction (agree or strongly agree) or not (disagree or strongly disagree).
Burnout is a binary indicator of whether the respondent reports burnout (“I have one or more symptoms of burnout that won’t go away” or “I am completely burnt out, my symptoms won’t go away”) or not (“I have no symptoms of burnout” or “I have one or more symptoms of burnout that come and go away”).
Intention to Leave is a binary indicator of whether the respondent reports considering leaving their organization within the next year or not excluding those who reported they were planning to retire.
Overall, 86.0% of respondents (n = 200 745) were satisfied with their jobs, although satisfaction was lower for pay (n = 120 058, 56.1%) compared to benefits (n = 176 252, 82.3%). A total of 19.7% of respondents (n = 46 080) reported symptoms of burnout, and roughly a quarter of respondents (n = 58 177, 24.8%) considered leaving their organization within the next year for any reason besides retirement.
Respondents were predominantly female (n = 184 011, 79.6%) and White (n = 141 773, 61.8%), with most holding at least a bachelor’s degree (n = 88 337, 72.8%). Over half (n = 123 023, 54.2%) had been with their agency for 5 years or less. The majority of respondents worked full-time (n = 217 435, 92.7%) as permanent staff (n = 213 970, 91.7%) in local health departments (n = 171 832, 73.3%) and in decentralized governance settings (n = 160 144, 68.8%).
Bivariate analyses
Work situation
Table 2 illustrates the bivariate relationship between sample characteristics and work situations. Bivariate analyses revealed significant differences in work situation by most individual and organizational characteristics (P < .02). Workers who were older, had lower educational attainment, or lacked a public health degree were more likely to work entirely in-person with 51.4% (n = 28 102) of those aged 56 and older working only in-person, compared to 44.5% (n = 26 417) of those aged 35 or younger. In terms of education, 65.1% (n = 22 052) of individuals without a college degree worked fully in-person, compared to 29.4% (n = 3446) of those with a doctoral degree. Similarly, 50.4% (n = 91 456) of workers without a public health degree worked entirely in-person, compared to 31.5% (n = 16 130) of those with a public health degree. Permanent staff and interns were more likely to be only in-person (n = 101 479, 47.5% and n = 301, 48.6%, respectively), while contractors (n = 4367, 45.7%) and federal employees (n = 2894, 37.7%) worked in a mostly or only remote setting.
TABLE 2.
| In-Person Only | Mostly In-Person, Some Remote | Mostly Remote, Some In-Person | Remote Only | P Valuec | |
|---|---|---|---|---|---|
| Characteristic | (n = 87 315; 69.4%) N (%) | (n = 87 315; 69.4%) N (%) | (n = 87 315; 69.4%) N (%) | (n = 87 315; 69.4%) N (%) | |
| Race/ethnicity | <.001d | ||||
| White | 66 734 (47.1) | 40 937 (28.9) | 37 380 (19.3) | 6657 (4.7) | |
| Black/African American | 16 411 (49.8) | 10 525 (31.9) | 4997 (15.2) | 1032 (3.1) | |
| Hispanic or LatinX | 10 171 (47.8) | 6816 (32.0) | 3616 (17.0) | 692 (3.3) | |
| Other | 12 857 (38.7) | 10 596 (31.9) | 8151 (24.5) | 1640 (4.9) | |
| Gender | .06 | ||||
| Female | 86 065 (46.8) | 54 692 (29.7) | 35 055 (19.1) | 8064 (4.4) | |
| Male/Other | 20 956 (44.6) | 14 679 (31.2) | 9331 (19.8) | 2045(4.4) | |
| Age | <.001d | ||||
| ≤ 35 years | 26 417 (44.5) | 18 626 (31.4) | 11 820 (19.9) | 2500 (4.2) | |
| 36-45 years | 24 741 (41.7) | 18 949 (31.9) | 12 751 (21.5) | 2957 (5.0) | |
| 46-55 years | 28 822 (47.9) | 17 835 (29.6) | 11 383 (18.9) | 2190 (3.6) | |
| ≥56 years | 28 102 (51.4) | 14 739 (27.0) | 9209 (16.8) | 2614 (4.8) | |
| Education level | <.001d | ||||
| No college degree | 22 052 (65.1) | 7109 (21.0) | 3685 (10.9) | 1040 (3.1) | |
| Associate’s degree | 18 645 (63.2) | 6838 (23.2) | 3226 (10.9) | 795 (2.7) | |
| Bachelor’s degree | 41 539 (47.1) | 27 425 (31.1) | 15 794 (17.9) | 3526 (4.0) | |
| Master’s degree | 21 904 (31.5) | 24 698 (35.6) | 18 786 (27.0) | 4071 (5.9) | |
| Doctoral degree | 3446 (29.4) | 4025 (34.3) | 3470 (29.6) | 776 (6.6) | |
| PH degree | <.001d | ||||
| Yes | 16 130 (31.5) | 17 715 (34.5) | 14 363 (28.0) | 3071 (6.0) | |
| No | 91 456 (50.4) | 52 380 (28.8) | 30 599 (16.9) | 7137 (3.9) | |
| Role | <.001d | ||||
| Administrative Staff & Leadership | 31 732 (48.2) | 18 408 (28.0) | 12 405 (18.8) | 3315 (5.0) | |
| Clinical, Behavioral, & Social Services | 39 497 (57.3) | 20 175 (29.3) | 8050 (11.7) | 1244 (1.8) | |
| Public Health Programs, Research, Assessment, & Surveillance | 36 685 (37.5) | 31 199 (31.9) | 24 418 (25.0) | 5545 (5.7) | |
| Other | 102 (25.0) | 122 (30.0) | 154 (38.1) | 28 (7.0) | |
| Tenure in current agency | <.001d | ||||
| 0-5 years | 54 850 (44.6) | 37 290 (30.3) | 24 606 (20.0) | 6175 (5.0) | |
| 6-15 years | 26 497 (44.0) | 18 480 (30.7) | 12 632 (21.0) | 2544 (4.2) | |
| ≥16 years | 22 595 (52.0) | 12 448 (29.2) | 6899 (15.9) | 1302 (3.0) | |
| Current Employer | <.001d | ||||
| State Government | 42 177 (40.0) | 26 599 (25.2) | 28 685 (27.2) | 7888 (7.5) | |
| Local Government | 60 525 (51.2) | 40 670 (34.4) | 15 266 (12.9) | 1857 (1.6) | |
| Employment Status | <.001d | ||||
| Contractor providing services to the health department | 2352 (24.7) | 2822 (29.6) | 2509 (26.2) | 1858 (19.5) | |
| Permanent staff employed by the health department | 101 479 (47.5) | 64 949 (30.4) | 40 131 (18.8) | 7149 (3.3) | |
| Intern employed by the health department | 301 (48.6) | 173 (28.0) | 125 (20.1) | 20 (3.3) | |
| Federal employee detailed to the health department | 3105 (40.4) | 1689 (22.0) | 1843 (24.0) | 1051 (13.7) | |
| Temporary staff employed by the health department | 487 (39.7) | 392 (32.0) | 247 (20.2) | 99 (8.1) | |
| AmeriCorps member serving at the health department | 66 (34.2) | 81 (42.1) | 31 (16.0) | 15 (7.8) | |
| FTE | <.001d | ||||
| Full-time | 100 068 (46.1) | 66 141 (30.5) | 42 095 (19.4) | 8819 (4.1) | |
| Part-time | 8216 (48.0) | 4249 (24.8) | 3176 (18.6) | 1468 (8.6) | |
| Supervisory Level | <.001d | ||||
| Non-supervisor | 79 434 (47.4) | 46 886 (28.0) | 32 461 (19.4) | 8653 (5.2) | |
| Supervisory/Manager | 25 522 (43.1) | 20 156 (34.1) | 11 899 (20.1) | 1600 (2.7) | |
| Executive | 3324 (43.6) | 3348 (44.0) | 910 (12.0) | 34 (0.4) | |
| Setting | <.001d | ||||
| SHA-CO | 13 782 (22.0) | 16 371 (26.1) | 25 131 (40.1) | 7405 (11.8) | |
| Large LHD | 50 655 (47.8) | 36 795 (34.7) | 16 209 (15.3) | 2325 (2.2) | |
| Medium LHD | 29 745 (66.7) | 12 023 (27.0) | 2456 (5.5) | 345 (0.8) | |
| Small LHD | 14 101 (67.2) | 5200 (24.8) | 1475 (7.0) | 211 (1.0) | |
| Governance | <.001d | ||||
| Centralized | 18 873 (60.7) | 7900 (25.4) | 3574 (40.1) | 733 (2.4) | |
| Decentralized | 64 445 (40.3) | 51 382 (32.1) | 35 893 (15.3) | 8138 (5.1) | |
| Mixed | 11 757 (58.9) | 4261 (21.4) | 3110 (5.5) | 821 (4.1) | |
| Shared | 12 503 (58.4) | 5711 (26.7) | 2594 (7.0) | 584 (2.7) |
Abbreviations: FTE, full-time equivalent; LHD, local health department; SHA-CO, State Health Agency Central Office.
Differences by supervisory level were calculated using χ2 tests.
Public Health Workforce Interests and Needs Survey, 2024.
Bonferroni correction adjustment (significance level set at P ≤ .02).
Significance P ≤ .02.
Marginal significance P ≤ .05. National survey and replication weights provided the de Beaumont Foundation.
Organizational factors also mattered in terms of work situations (P < .001). Employees in state government (n = 32 536, 51.9%) reported working mostly or only in a remote setting, whereas the majority of those in small LHDs (n = 14 101, 67.2%) reported working only in in-person settings. Employees in decentralized governance structures had the lowest rates of in-person work situations (n = 64 445, 40.3%), in contrast to the 60.7% (n = 18 873) of employees in centralized governance structures reported only in-person work situations.
Work preference
Table 3 presents the bivariate relationship betw-een sample characteristics and work preferences. Individuals under 55 were significantly more inclined toward a hybrid work model, with 73% (n = 43 366) of those aged ≤35, 69.7% (n = 41 376) of those aged 36 to 45, and 67.5% (n = 40 590) of those aged 36 to 55 preferring a mix between in-person and remote work. In contrast, employees ≥56 years were more likely to prefer in-person only work (n = 17 171, 31.5%). Education level was strongly associated with remote work preference (P < .001). Individuals without a college degree preferred in-person only work (n = 13 059, 38.5%), whereas those with graduate degrees leaned toward remote or hybrid models. Among workers with a master’s degree, 39.1% (n = 27 126) preferred mostly remote and 15.3% (n = 10 654) fully remote work, while only 10.0% (n = 6964) favored in-person only. A similar trend was seen among those with a public health degree (P < .001), where over half (n = 28 801, 56.2%) preferred mostly or fully remote arrangements. Employees with shorter tenure (0-5 years) were more likely to prefer some sort of remote work model (n = 57 174, 46.6%) compared to those with longer tenure (≥16 years). Employment status also played a role in work preferences (P < .001). Contractors and federal employees were among the most likely to favor remote arrangements (n = 6167, 64.7% and n = 4152, 54.1%, respectively, preferred mostly or fully remote work). In contrast, interns overwhelmingly preferred some form of in-person work, with 77.6% opting for either mostly in-person (n = 384, 62.0%) or an only in-person model (n = 96, 15.6%).
TABLE 3.
| In-Person Only | Mostly In-Person, Some Remote | Mostly Remote, Some In-Person | Remote Only | P Valuec | |
|---|---|---|---|---|---|
| Characteristic | (n = 87 315; 69.4%) N (%) | (n = 87 315; 69.4%) N (%) | (n = 87 315; 69.4%) N (%) | (n = 87 315; 69.4%) N (%) | |
| Race/ethnicity | <.001d | ||||
| White | 30 191 (21.3) | 55 466 (39.2) | 40 111 (28.3) | 15 845 (11.2) | |
| Black/African American | 7330 (22.2) | 11 434 (34.7) | 10 640 (32.3) | 3552 (10.8) | |
| Hispanic or LatinX | 4231 (19.9) | 7558 (35.5) | 6911 (32.4) | 2606 (12.2) | |
| Other | 5216 (15.7) | 10 652 (32.1) | 12 061 (36.3) | 5307 (16.0) | |
| Gender | <.001d | ||||
| Female | 36 797 (20.0) | 68 209 (37.1) | 57 126 (31.1) | 21 635 (11.8) | |
| Male/other | 10 432 (22.2) | 17 466 (37.2) | 13 173 (28.0) | 5937 (12.6) | |
| Age | <.001d | ||||
| ≤35 years | 7709 (13.0) | 22 461 (37.8) | 20 905 (35.2) | 8279 (13.9) | |
| 36-45 years | 9528 (16.0) | 21 656 (36.5) | 19 720 (33.2) | 8465 (14.3) | |
| 46-55 years | 13 248 (22.0) | 22 851 (38.0) | 17 739 (29.5) | 6364 (10.6) | |
| ≥56 years | 17 171 (31.5) | 19 493 (35.7) | 12 955 (23.7) | 4973 (9.1) | |
| Education level | <.001d | ||||
| No college degree | 13059 (38.5) | 10700 (31.6) | 7004 (20.7) | 3124 (9.2) | |
| Associate’s degree | 9834 (33.3) | 10 616 (36.0) | 6518 (22.1) | 2531 (8.6) | |
| Bachelor’s degree | 16 178 (18.2) | 36 015 (40.8) | 26 150 (29.6) | 9868 (11.2) | |
| Master’s degree | 6964 (10.0) | 24 703 (35.6) | 27 126 (39.1) | 10 654 (15.3) | |
| Doctoral degree | 1384 (11.8) | 4205 (36.0) | 4313 (36.9) | 1792 (15.3) | |
| PH degree | <.001d | ||||
| Yes | 5086 (9.9) | 17 380 (33.9) | 20 814 (40.6) | 7987 (15.6) | |
| No | 42 333 (23.3) | 68 860 (37.9) | 50 297 (27.7) | 19 982 (11.0) | |
| Role | <.001d | ||||
| Administrative Staff & Leadership | 15 428 (23.4) | 22 456 (34.1) | 18 562 (28.2) | 9403 (14.3) | |
| Clinical, Behavioral, & Social Services | 18 329 (26.6) | 29 359 (42.6) | 16 784 (24.4) | 4414 (6.4) | |
| Public Health Programs, Research, Assessment, & Surveillance | 13 779 (14.1) | 34 359 (35.1) | 35 579 (36.4) | 14 082 (14.4) | |
| Other | 46 (11.5) | 196 (48.3) | 125 (30.7) | 38 (9.5) | |
| Tenure in current agency | <.001d | ||||
| 0-5 years | 21 364 (17.4) | 44 311 (36.1) | 40 738 (33.2) | 16 436 (13.4) | |
| 6-15 years | 12 178 (20.3) | 22 233 (37.0) | 18 144 (30.2) | 7577 (12.6) | |
| ≥16 years | 12 425 (28.6) | 17 139 (39.5) | 10 425 (24.0) | 3452 (7.9) | |
| Current employer | <.001d | ||||
| State government | 20 112 (19.1) | 31 509 (29.9) | 34 829 (33.1) | 18 825 (17.9) | |
| Local government | 24 709 (20.9) | 51 295 (43.4) | 34 055 (28.8) | 8223 (7.0) | |
| Employment status | <.001d | ||||
| Contractor providing services to the health department | 1055 (11.1) | 2312 (24.3) | 3678 (38.6) | 2489 (26.1) | |
| Permanent staff employed by the health department | 44 587 (20.9) | 81 068 (28.0) | 64 159 (30.0) | 23 778 (11.1) | |
| Intern employed by the health department | 96 (15.6) | 384 (62.0) | 124 (20.1) | 15 (2.4) | |
| Federal employee detailed to the health department | 1502 (19.6) | 2017 (26.3) | 2615 (34.1) | 1537 (20.0) | |
| Temporary staff employed by the health department | 167 (13.6) | 419 (34.3) | 431 (35.3) | 205 (16.8) | |
| AmeriCorps member serving at the health department | 29 (15.1) | 80 (41.6) | 62 (32.1) | 21 (11.2) | |
| FTE | <.001d | ||||
| Full-time | 42 969 (19.8) | 80 836 (37.3) | 67 167 (31.0) | 25 992 (12.0) | |
| Part-time | 4785 (27.9) | 5796 (33.8) | 4339 (25.3) | 2209 (12.9) | |
| Supervisory level | <.001d | ||||
| Non-supervisor | 35 672 (21.3) | 57 415 (34.3) | 51 821 (31.0) | 22 406 (13.4) | |
| Supervisor/Manager | 10 636 (18.0) | 24 981 (42.2) | 17 960 (30.4) | 5588 (9.4) | |
| Executive | 1446 (19.0) | 4237 (55.6) | 1724 (22.6) | 207 (2.7) | |
| Setting | <.001d | ||||
| SHA-CO | 5927 (9.5) | 14 522 (23.2) | 25 555 (40.8) | 16 657 (26.6) | |
| Large LHD | 21 188 (20.0) | 41 773 (39.4) | 33 485 (31.6) | 9490 (9.0) | |
| Medium LHD | 13 989 (31.4) | 20 696 (46.5) | 8395 (18.9) | 1451 (3.3) | |
| Small LHD | 6649 (31.7) | 9642 (46.0) | 4070 (19.4) | 603 (2.9) | |
| Governance | <.001d | ||||
| Centralized | 8262 (26.6) | 12 411 (39.9) | 8203 (26.4) | 2193 (7.1) | |
| Decentralized | 27 657 (17.3) | 57 641 (36.1) | 52 537 (32.9) | 21 956 (13.7) | |
| Mixed | 5025 (25.2) | 7420 (37.2) | 5404 (27.1) | 2074 (10.4) | |
| Shared | 6431 (30.1) | 8254 (39.1) | 4705 (22.0) | 1881 (8.8) |
Abbreviations: FTE, full-time equivalent; LHD, local health department; SHA-CO, State Health Agency Central Office.
Differences by supervisory level were calculated using χ2 tests.
Public Health Workforce Interests and Needs Survey, 2024.
Bonferroni correction adjustment (significance level set at P ≤ .02).
Significance P ≤ .02.
Marginal Significance P ≤ .05. National survey and replication weights provided the de Beaumont Foundation.
Organizational factors, such as setting and governance, further shaped preferences (P < .001). Staff in SHA-CO had the highest remote preference, with 40.8% (n = 25 555) choosing mostly remote and 26.6% (n = 16 657) fully remote. Conversely, workers in small local health departments (LHDs) had the strongest preference for in-person work (n = 6649, 31.7%), with only 2.9% (n = 603) preferring fully remote. Decentralized agencies had the highest proportion of staff preferring remote arrangements (n = 74 493, 46.6%), compared to centralized agencies where only 33.5% (n = 10 396) preferred a remote arrangement.
Concordance between work situation and work preference
Table 4 illustrates the bivariate relationship between sample characteristics and the concordance between work situation and work preference. Workers aged 56 or older were the most likely to have a concordant work arrangement, with 63.1% (n = 34 412) reporting that their work situation matched their preference. In contrast, only 43.2% (n = 25 645) of workers under 35 reported a concordant work situation. In terms of educational attainment, those with no college degrees had the highest concordance rate (n = 19 832, 58.6%), while those with a master’s degree had the lowest (n = 34 472, 49.7%). In terms of tenure, employees with 16 or more years at their agency were most likely to have a concordant arrangement, with 59.4% (n = 25 773) reporting their work situation aligned with their preferences, compared to 49.5% (n = 60 736) for those with fewer than 5 years. Concordance was also more common among part-time employees (n = 10 817, 63.3%), compared to full-time employees (n = 111 269, 51.3%). Federal employees and contractors were among those with the highest concordance, with 56.8% (n = 4355) and 57.5% (n = 5478), respectively, indicating their work situation aligned with their preferences. In contrast, interns had the highest discordance, with 58.0% (n = 360) reporting that their work situation did not match their preference.
TABLE 4.
Bivariate Relationship Between Sample Characteristics and Concordance Between Work Situation and Work Preference (N = 234 583)a,b
| Concordant | Discordant | P Valuec | |
|---|---|---|---|
| Characteristic | (n = 87 315; 69.4%) N (%) | (n = 87 315; 69.4%) N (%) | |
| Race/ethnicity | <.001d | ||
| White | 77 564 (54.8) | 63 996 (45.2) | |
| Black/African American | 16 171 (49.1) | 16 754 (50.9) | |
| Hispanic or LatinX | 9897 (46.5) | 11 395 (53.5) | |
| Other | 16 139 (48.6) | 17 089 (51.4) | |
| Gender | <.001d | ||
| Female | 94 244 (51.3) | 89 434 (48.7) | |
| Male/other | 26 197 (55.8) | 20 790 (44.2) | |
| Age | <.001d | ||
| ≤35 years | 25 645 (43.2) | 33 703 (56.8) | |
| 36-45 years | 29 193 (49.2) | 30 143 (50.8) | |
| 46-55 years | 32 548 (54.1) | 27 640 (45.9) | |
| ≥56 years | 34 412 (63.1) | 20 125 (36.9) | |
| Education level | <.001d | ||
| No college degree | 19 832 (58.6) | 14 034 (41.4) | |
| Associate’s degree | 16 111 (54.7) | 13 347 (45.3) | |
| Bachelor’s degree | 44 413 (50.4) | 43 788 (49.6) | |
| Master’s degree | 34 472 (49.7) | 34 941 (50.3) | |
| Doctoral degree | 6540 (55.9) | 5154 (44.1) | |
| PH degree | <.001d | ||
| Yes | 25 692 (50.1) | 25 552 (49.9) | |
| No | 95 676 (52.7) | 85 711 (47.3) | |
| Role | .02e | ||
| Administrative Staff & Leadership | 35 019 (53.2) | 30 806 (46.8) | |
| Clinical, Behavioral, & Social Services | 36 207 (52.6) | 32 633 (47.4) | |
| Public Health Programs, Research, Assessment, & Surveillance | 50 004 (51.1) | 47 760 (48.9) | |
| Other | 226 (55.6) | 180 (44.4) | |
| Tenure in current agency | <.001d | ||
| 0-5 years | 60 736 (49.5) | 62 073 (50.5) | |
| 6-15 years | 31 817 (53.0) | 28 268 (47.0) | |
| ≥16 years | 25 773 (59.4) | 17 650 (40.6) | |
| Current employer | <.001d | ||
| State government | 57 483 (54.6) | 47 746 (45.4) | |
| Local government | 58 657 (49.6) | 59 567 (50.4) | |
| Employment status | <.001d | ||
| Contractor providing services to the health department | 5478 (57.5) | 4046 (42.5) | |
| Permanent staff employed by the health department | 110 370 (51.7) | 103 135 (48.3) | |
| Intern employed by the health department | 260 (42.0) | 360 (58.0) | |
| Federal employee detailed to the health department | 4355 (56.8) | 3314 (43.2) | |
| Temporary staff employed by the health department | 622 (50.9) | 601 (49.1) | |
| AmeriCorps member serving at the health department | 105 (55.0) | 86 (45.0) | |
| FTE | <.001d | ||
| Full-time | 111 269 (51.3) | 105 620 (48.7) | |
| Part-time | 10 817 (63.3) | 6282 (36.7) | |
| Supervisory level | <.001d | ||
| Non-supervisor | 86 747 (51.9) | 80 478 (48.1) | |
| Supervisor/Manager | 30 946 (52.3) | 28 203 (47.7) | |
| Executive | 4393 (57.7) | 3221 (42.3) | |
| Setting | <.001d | ||
| SHA-CO | 35 194 (56.2) | 27 433 (43.8) | |
| Large LHD | 51 991 (49.1) | 53 880 (50.9) | |
| Medium LHD | 23 538 (52.9) | 20 993 (47.1) | |
| Small LHD | 11 362 (54.2) | 9596 (45.8) | |
| Governance | <.001d | ||
| Centralized | 15 612 (50.3) | 15 440 (49.7) | |
| Decentralized | 83 829 (52.5) | 75 883 (47.5) | |
| Mixed | 9887 (49.6) | 10 037 (50.4) | |
| Shared | 11 784 (55.2) | 9577 (44.8) |
Abbreviations: FTE, full-time equivalent; LHD, local health department; SHA-CO, State Health Agency Central Office.
Differences by supervisory level were calculated using χ2 tests.
Public Health Workforce Interests and Needs Survey, 2024.
Bonferroni correction adjustment (significance level set at P ≤ .02).
Significance P ≤ .02.
Marginal Significance P ≤ .05.
National survey and replication weights provided the de Beaumont Foundation.
Organizational factors played a significant role as well (P < .001). Employees in decentralized agencies had the highest concordance rate (n = 83 829, 52.5%), while those in mixed settings had the lowest concordance (n = 9887, 49.6%). Among health department settings, employees in small local health departments had the highest concordance (n = 11 362, 54.2%), while those in large local health departments had less concordance (n = 51 991, 49.1%).
Multivariate analyses
Satisfaction
Employees whose work situation was concordant with their work preferences reported significantly higher levels of job satisfaction, organizational satisfaction, pay satisfaction, and benefits satisfaction compared to those whose work situation was discordant with their work preferences (Table 5). Specifically, employees with work concordance were 2.07 times more likely to report higher job satisfaction (AOR = 2.07, 95% CI = 1.94-2.20, P < .001), 1.74 times more likely to report higher organizational satisfaction (AOR = 1.74, 95% CI = 1.66-1.83, P < .001), 1.62 times more likely to report higher pay satisfaction (AOR = 1.62, 95% CI = 1.56-1.68, P < .001), and 1.59 times more likely to report higher benefits satisfaction (AOR = 1.60, 95% CI = 1.47-1.74, P < .001).
TABLE 5.
Multivariate Analysis of Reported Satisfaction, Burnout, and Intention to Leave Among Public Health Employees With/Without Work Concordancee in 2024a,b
| OR | AOR | CI | P Valuec | |
|---|---|---|---|---|
| Satisfactionf | ||||
| Job satisfaction | 2.112 | 2.065 | 1.936-2.203 | <.001d |
| Organization satisfaction | 1.751 | 1.741 | 1.655-1.832 | <.001d |
| Pay satisfaction | 1.698 | 1.621 | 1.561-1.682 | <.001d |
| Benefits satisfaction | 1.597 | 1.594 | 1.465-1.735 | <.001d |
| Burnoutg | 0.545 | 0.566 | 0.537-0.596 | <.001d |
| Intention to leaveh | 0.548 | 0.561 | 0.531-0.592 | <.001d |
Data source: Public Workforce Interests and Needs Survey, 2024.
Results are individual logistic regressions holding constant race/ethnicity, gender, age, education level, public health education, role type, tenure at current agency, employer, employment status, full-time status, supervisory level, and organization size. National survey and replication weights provided by the de Beaumont Foundation.
Bonferroni correction adjustment (significance level set at P ≤ .02).
Significance (P ≤ .02).
Concordance is a binary indicator of whether there was agreement between the respondent’s report of work situation and the respondent’s report of work preference.
Satisfaction is a binary indicator of whether the respondent reports satisfaction (agree or strongly agree) or not (disagree or strongly disagree).
Burnout is a binary indicator of whether the respondent reports burnout (“I have one or more symptoms of burnout that won’t go away” or “I am completely burnt out, my symptoms won’t go away”) or not (“I have no symptoms of burnout” or “I have one or more symptoms of burnout that come and go away”).
Intention to Leave is a binary indicator of whether the respondent reports considering leaving their organization within the next year or not excluding those who reported they were planning to retire.
Burnout
Employees whose work situation was concordant with their work preferences reported significantly less burnout compared to those whose work situation was discordant with their work preferences (Table 5). Specifically, individuals who experienced work concordance were 0.57 times less likely to experience burnout (AOR = 0.57, 95% CI = 0.54-0.60, P < .001) compared to those who experienced discordance.
Intention to leave
Employees whose work situation was concordant with their work preferences were significantly less likely to report intentions to leave compared to those whose work situation was discordant with their work preferences (Table 5). Individuals who experienced work concordance were 0.56 times less likely to report an intention to leave their organization in the next year (AOR = 0.56, 95% CI = 0.53-0.59, P < .001) compared to those who experienced discordance.
Discussion
The public health workforce has faced significant strain in recent years, particularly due to recruitment and retention challenges. Studies suggest that improving workplace environments, specifically through flexible work arrangements, could help address these issues.10,11 Data from PH WINS highlights the importance of telework and flexibility in employee satisfaction and retention.5,9 Despite a growing preference for telework, there is limited evidence on how alignment between employees’ work preferences and their actual work situations impacts burnout, job satisfaction, and intention to leave. This study aims to describe characteristics of those working remotely and examine how the match between preferred and actual work settings influences key workforce outcomes in the post-pandemic era.
Our findings demonstrate that employees whose work situations were concordant with their work preferences reported significantly higher satisfaction with their jobs, organizations, pay, and benefits. They were also substantially less likely to report symptoms of burnout or intentions to leave their organization in the next year. These associations suggest that ensuring concordance between work preference and work situation is a viable strategy for improving recruitment and retention among the government public health workforce. These findings are particularly important for younger individuals, who are often more difficult to recruit and retain in the public health workforce due to lower salaries compared to the private sector and limited career advancement opportunities.15 Employees under 35 were among the least likely to experience concordance between their work preferences and actual work situations, with many preferring hybrid or remote arrangements but more often working in-person. Given that early-career professionals represent the future of government public health, this finding provides important insight for organizational leaders. Public health agencies that offer flexible work options aligned with younger employees’ preferences may be better positioned to attract and retain this critical segment of the workforce.
Highly educated workers, particularly those with graduate and public health degrees, bring essential expertise to the field; however, they were less likely to experience alignment between their preferred and actual work situations. These individuals expressed a stronger preference for hybrid or remote work but were disproportionately working in-person. Recruiting and retaining these individuals is critical to maintaining a skilled and adaptive public health workforce. Without offering flexible work options that match their expectations, agencies risk losing individuals whose skills are important.
Interns represent a key pathway for the future public health workforce, yet findings suggest they face a notable mismatch between their work preferences and current work situations. A majority of interns reported discordance, with most preferring in-person or mostly in-person work while being placed in a range of different work situations. This group is at a formative stage in their careers, and their early experiences can strongly influence whether they choose to remain in public health. They also typically rely on internships for connecting and building relationships that may help them eventually find a full-time position, which may explain some of the preference for in-person arrangements. Ensuring in-person or mostly in-person opportunities for interns would align with work preferences and experiences. It may also strengthen their engagement, reinforce interest in government public health careers, and support long-term workforce development.
Findings from this study are especially relevant in the context of the current environment. The COVID-19 pandemic normalized remote work across numerous sectors, including government public health. Many organizations have since attempted to retain flexible work arrangements; however, a January 20, 2025, presidential action mandated a return to in-person work for federal government employees, prompting a rapid shift back to the office.16 Similar changes are occurring in individual state governments as well. For example, Indiana’s new governor issued a state executive order mandating a return to in-person work for state government employees.17 It is likely too early to predict how the work environment will eventually settle after these recent changes, but understanding the preferences of government public health employees and the current work environment allows governmental decision makers to proactively shape policies that support employee satisfaction, improve retention, and ensure operational effectiveness in a changing workforce landscape.
Strengths and Limitations
This study has several strengths and limitations worth noting. First, this study is the first of its kind to examine alignment between work situations and work preferences among government public health employees and how this alignment relates to key workforce outcomes such as burnout and job satisfaction. Additionally, this study utilized a representative national sample of government public health employees at both the state and local levels. It provides new insights that will be useful to government leaders and policymakers tasked with leading workforce recruitment and retention initiatives. However, while this study accounts for various individual and organizational characteristics, unmeasured factors such as job type complexity or organizational culture may also influence the outcomes, and we were unable to control for these factors. Additionally, as it is a cross-sectional study, this analysis does not consider the long-term effects of remote work or concordance between work preferences. Although this cross-sectional study offers valuable new findings, we are unable to establish causal relationships between work concordance and self-reported outcomes (satisfaction, burnout, and intention to leave). Lastly, given the number of multivariate models, it is possible that we may have identified spurious relationships between work concordance and reporting outcomes; however, to mitigate this risk, we applied a more conservative significance level using the Bonferroni correction.
Conclusion
This study highlights the importance of aligning government public health employees’ work preferences with their actual work situations, particularly in the context of post-pandemic workplace changes. Findings show that employees whose work situations align with their work preferences report higher job satisfaction, lower burnout, and decreased intention to leave their organizations. These effects are most pronounced among younger and highly educated workers, who experience more difficulty in achieving this alignment. Offering flexible work arrangements that match employees’ preferences, particularly for hybrid or remote options, can serve as a key strategy for improving recruitment, retention, and overall workforce well-being. As government public health agencies navigate what has been, for some, a shift back to in-person work, these insights should be considered in the bigger picture of employee satisfaction and efforts to ensure a resilient, sustainable workforce.
Implications for Policy & Practice
By understanding employees’ work preferences and aligning job roles and work environments accordingly, organizations can improve employee satisfaction and reduce turnover.
While preferences for remote work vary across the government public health workforce, policies that broadly remove the option for remote work may be detrimental to employee recruitment and retention.
If internships are meant to be used as a recruitment tool, organizations should prioritize some in-person work for interns.
Footnotes
PH WINS was developed by the de Beaumont Foundation and the Association of State and Territorial Health Officials to understand the interests and needs of the state and local governmental public health workforce in the US, and was fielded in 2014, 2017, 2021, and 2024. For more information, visit phwins.org.
Human participant compliance statement: The requirement of ethical approval for PH WINS 2024 was waived by the WCG Institutional Review Board (Western-Copernicus Group IRB) for studies involving humans.
The authors declare that they have no conflicts of interest.
This work is supported by funds made available from the Centers for Disease Control and Prevention (CDC) of the U.S. Department of Health and Human Services (HHS), National Center for STLT Public Health Infrastructure and Workforce, through OE22-2203: Strengthening U.S. Public Health Infrastructure, Workforce, and Data Systems grant. The contents are those of the author(s) and do not necessarily represent the official views of, nor an endorsement, by CDC/HHS, or the U.S. Government.
The lead author of this work was supported by the National Library of Medicine of the National Institutes of Health under award number T15LM012502. The content of this article is solely the responsibility of the authors and does not represent the official views of the National Institutes of Health or the National Library of Medicine.
Ethical approval for this research was obtained from Indiana University on April 10, 2025 (Decision No 27091).
Contributor Information
MaKenzie Gee, Email: makgee@iu.edu, makenzie-gee@yahoo.com.
Valerie A. Yeager, Email: vyeager@iu.edu.
References
- 1.Liss-Levinson R, Bharthapudi K, Leider JP, Sellers K. Loving and leaving public health: predictors of intentions to quit among state health agency workers. J Public Health Manage Pract. 2015;21(Supplement 6):S91–S101. doi: 10.1097/PHH.0000000000000317 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 2.Yeager VA, Wisniewski JM, Amos K, Bialek R. Why do people work in public health? Exploring recruitment and retention among public health workers. J Public Health Manage Pract. 2016;22(6):559-566. doi: 10.1097/PHH.0000000000000380 [DOI] [PubMed] [Google Scholar]
- 3.Yeager VA, Balio CP, Kronstadt J, Beitsch LM. The relationship between health department accreditation and workforce satisfaction, retention, and training needs. J Public Health Manage Pract. 2019;25(2):S113–S123. doi: 10.1097/PHH.0000000000000920 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 4.Bogaert K, Castrucci BC, Gould E, et al. The public health workforce interests and needs survey (PH WINS 2017): an expanded perspective on the state health agency workforce. J Public Health Manage Pract. 2019;25(2):S16–S25. doi: 10.1097/PHH.0000000000000932 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 5.Leider JP, Shah GH, Yeager VA, Yin J, Madamala K. Turnover, COVID-19, and reasons for leaving and staying within governmental public health. J Public Health Manage Pract. 2023;29(Supplement 1):S54–S63. doi: 10.1097/PHH.0000000000001634 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 6.Bogaert K, Papillon G, Etheridge KW, et al. Seven years, 3 surveys, a changed world: the state public health workforce 2014-2021. J Public Health Manage Pract. 2023;29(Supplement 1):S14–S21. doi: 10.1097/PHH.0000000000001645 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 7.Orr JM, Leider JP. Voluntary separations and COVID-19: a snapshot of turnover intention in the federal workforce in the first year of the pandemic. J Public Health Manage Pract. 2023;29(4):442-445. doi: 10.1097/PHH.0000000000001720 [DOI] [PubMed] [Google Scholar]
- 8.Spencer-Hwang R, Cruz A, Ong M, et al. Prevalence of burnout among public health professionals: a systematic review. J Public Health Manage Pract. 2024;30(3):384-393. doi: 10.1097/PHH.0000000000001887 [DOI] [PubMed] [Google Scholar]
- 9.Yeager VA, Madsen ER, Schaffer K. Qualitative insights from governmental public health employees about experiences serving during the COVID-19 pandemic, PH WINS 2021. J Public Health Manage Pract. 2023;29(Supplement 1):S73–S86. doi: 10.1097/PHH.0000000000001644 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 10.Valdez ID, Ramirez CE, Khansari A, et al. Leading past COVID-19: an analysis of remote work now and beyond. Med Dosim. 2023;48(3):161-164. doi: 10.1016/j.meddos.2023.03.003 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 11.Asgari H, Gupta R, Jin X. Impacts of COVID-19 on future preferences toward telework. Transp Res Rec. 2023;2677(4):611-628. doi: 10.1177/03611981221115078 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 12.Robins M, et al. Surveying the State and Local Government Public Health Workforce: The Design and Evolution of PH WINS 2024. J Public Health Manag Pract. 2026;32(Suppl 1):S29-S40. doi: 10.1097/PHH.0000000000002248 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 13.Bogaert K, Castrucci BC, Gould E, Sellers K, Leider JP. Changes in the state governmental public health workforce: demographics and perceptions, 2014-2017. J Public Health Manage Pract. 2019;25(2):S58–S66. doi: 10.1097/PHH.0000000000000933 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 14.Mitchell AK, Apenteng BA, Boakye KG. Examining factors associated with minority turnover intention in state and local public health organizations: the moderating role of race in the relationship among supervisory support, job satisfaction, and turnover intention. J Public Health Manage Pract. 2022;28(5):E768–E777. doi: 10.1097/PHH.0000000000001571 [DOI] [PubMed] [Google Scholar]
- 15.Sellers K, Leider JP, Lamprecht L, Liss-Levinson R, Castrucci BC. Using public health workforce surveillance data to prioritize retention efforts for younger staff. Am J Prev Med. 2020;59(4):562-569. doi: 10.1016/j.amepre.2020.03.017 [DOI] [PubMed] [Google Scholar]
- 16.The White House. Return to in-person work. Presidential Actions. https://www.whitehouse.gov/presidential-actions/2025/01/return-to-in-person-work/. Accessed September 13, 2025.
- 17.State of Indiana Executive Order 25-16. Bringing the public servant workforce back to the office. https://www.in.gov/gov/files/EO-25-16.pdf. Accessed September 13, 2025.