Appendix A
Literature Review Terms and Survey Methodology for “Boundaryless Work: The Impact of COVID-19 on Work-Life Boundary Management, Integration, and Gendered Divisions of Labor for Academic Women in STEMM,” by Ellen Ernst Kossek, Tammy D. Allen, and Tracy L. Dumas
SURVEY METHODOLOGY
We1 designed a survey to ask women faculty in science, technology, engineering, mathematics, and medicine (STEMM) to compare how the COVID-19 pandemic has affected them between March 2020 and October 2020. Using a mixed-methods approach including qualitative and quantitative formats, the survey asked respondents to indicate their work-location preferences and boundary control; changes in work-life coping strategies, childcare and eldercare, and other domestic demands; and preferences for university support. The survey was publicized on the ADVANCE grant listserv and listservs of academic women in scientific specialties (see Table A-1).
We presented the results of 933 faculty who identified themselves as STEMM faculty and provided usable data. The final sample included 763 respondents; other respondents who were omitted were not women (25), not in STEMM (190), did not indicate STEMM status (286), or had other incomplete data. We focused our report on the results from 733 tenured or tenure-stream faculty, since these individuals, in addition to teaching and service roles, were juggling research demands that may have results in significant career setbacks that could harm tenure, research funding and implementation, and promotion. We have also included some data from the 170 non-tenure-stream respondents. Many of their concerns mirrored those of tenure-stream faculty. Table A-2 shows sample demographic breakouts.
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1 In this appendix, Kossek, Allen, and Dumas use the first person plural.
TABLE A-1 Listservs that Posted the Anonymous Survey Link for the Work-Life Boundaries Paper
American Society for Engineering Education (ASEE) list of Engineering Deans |
Big Ten+ Associate Deans of Engineering for Academic Affairs |
ASEE Women in Engineering Division |
Women in Engineering Pro-Active Network |
Computing Research Association Committee on Widening Participation |
Association for Computing Machinery (ACM) website |
ACM Council on Women in Computing |
National Academy of Engineering list of women members |
Purdue Women Faculty in Engineering (1) mailing list; (2) Dean of Engineering Thursday Memo; and (3) Deans of the Colleges of (a) Agriculture, (b) Pharmacy, (c) Purdue Polytechnic Institute, and (d) Veterinary Medicine & Purdue American Association of University Professor Twitter |
Survey Sample Data and Analytical Approach
Nearly all (98 percent) of the 763 tenure-track or tenured women faculty in STEMM fields were from 202 U.S. institutions, and a small number (a little more than 2 percent or n = 20) of participants were from non-U.S. institutions. The survey was distributed on U.S. listservs. About half the respondents, or 326 people, were from 77 R1 institutions. The sample had representation from many disciplines as follows: industrial, material, and general engineering (n = 129, 16.9 percent); chemistry, chemical engineering, biology, and biochemistry (n = 102, 13.9 percent); health sciences (n = 56, 7.3 percent); electrical and mechanical engineering (n = 48, 6.3 percent); mathematics and statistics (n = 27, 3.5 percent); atmospheric, Earth, and ocean sciences (n = 25, 3.3 percent); agriculture and natural resources (n = 17, 2.2 percent); physics (n = 9, 1.2 percent); and other disciplines. For rank, the sample was evenly distributed with about one-third (34.1 percent) untenured assistant professors, one-third associate professors (31.2 percent), and one-third (34.7 percent) full professors. Approximately three-fourths of the sample was white (72.9 percent) and married or living with a romantic partner (86.5 percent). A little less than one-tenth (7.3 percent) of married women faculty lived apart from their spouse or one of the spouses lived far from work because of the other’s work. More than half (58.2 percent) provided care for children under the age of 18, 10.4 percent provided eldercare, 3.9 percent provided sandwiched care (i.e., both child care and eldercare). Nearly one-fifth, or 17.8 percent, provided care for family members who do not live with them.
The sample of women faculty in STEMM fields who are not on the tenure track included 170 participants predominantly from 62 U.S. institutions. The survey population was composed of faculty (91.2 percent), researchers (5.9 percent),
TABLE A-2 Sample Description for October 2020 Survey of Women in Academic STEMM Faculty
Tenured or on the Tenure Track (n = 763) N (%) |
Non-Tenure-Track (n = 170) N (%) |
Study Sample |
||||||||
---|---|---|---|---|---|---|---|---|---|---|
Characteristics | Assistant (n = 258, 34.1) | Associate (n = 236, 31.2) | Full (n = 263, 34.7) | Total (n = 763) | Faculty (n = 155, 91.2) | Researcher (n = 10, 5.9) | Postdocs (n = 5, 2.9) | Total (n = 170) | Total (n = 933) | |
Ethnicity | White | 172 (66.7) | 171 (72.5) | 209 (88.9) | 556 (72.9) | 116 (74.8) | 10 (100) | 2 (40.0) | 128 (75.3) | 684 (73.3) |
Hispanic | 20 (7.8) | 17 (7.2) | 13 (4.9) | 50 (6.6) | 12 (7.7) | 0 | 1 (20.0) | 13 (7.6) | 63 (6.8) | |
Black | 6 (2.3) | 4 (1.7) | 1 (0.4) | 11 (1.4) | 7 (4.5) | 0 | 0 | 7 (4.1) | 18 (109) | |
Asian/Pacific Is. | 31 (12.0) | 23 (9.7) | 16 (6.1) | 70 (9.2) | 7 (4.5) | 0 | 1 (20.0) | 8 (4.7) | 78 (8.4) | |
Multi-Racial/Other | 11 (4.3) | 8 (3.4) | 9 (3.4) | 28 (3.7) | 7 (4.5) | 0 | 1 (20.0) | 8 (4.7) | 36 (3.9) | |
Relationship | Married | 198 (76.7) | 183 (77.5) | 215 (81.7) | 601 (80.2) | 120 (77.4) | 7 (70.0) | 3 (60.0) | 130 (76.5) | 731 (78.3) |
Living with a Romantic Partner | 23 (8.9) | 16 (6.8) | 9 (3.4) | 49 (6.3) | 9 (5.8) | 0 | 1 (20.0) | 10 (5.9) | 59 (6.3) | |
Single | 28 (10.9) | 34 (14.4) | 33 (12.5) | 95 (12.9) | 24 (15.5) | 3 (30.0) | 1 (20.0) | 28 (16.5) | 123 (13.2) | |
Widowed | 1 (0.4) | 1 (0.4) | 3 (1.1) | 5 (0.7) | 1 (0.6) | 0 | 0 | 1 (0.6) | 6 (0.6) | |
Long-Distance Married Relationship | 18 (7.0) | 14 (5.9) | 12 (4.6) | 44 (5.8) | 8 (5.2) | 2 (20.0) | 0 | 10 (5.9) | 54 (5.8) | |
Long-Distance Romantic Relationship | 5 (1.9) | 1 (0.4) | 0 | 6 (0.7) | 1 (0.6) | 0 | 0 | 1 (0.6) | 7 (0.8) | |
Care | Childcare | 148 (57.4) | 168 (71.2) | 124 (47.1) | 444 (58.2) | 89 (41.3) | 5 (50.0) | 3 (60.0) | 97 (57.1) | 541 (58.0) |
Eldercare | 23 (8.9) | 24 (10.2) | 32 (12.2) | 79 (10.4) | 14 (9.0) | 3 (30.0) | 0 | 17 (10.0) | 96 (10.3) | |
Sandwiched Care | 10 (3.9) | 12 (5.1) | 9 (3.4) | 31 (3.9) | 5 (3.2) | 2 (20.0) | 0 | 7 (4.1) | 38 (4.1) | |
Long-Distance Care | 39 (15.1) | 36 (15.3) | 60 (22.8) | 136 (17.8) | 28 (18.1) | 3 (30.0) | 1 (20.0) | 3 (18.8) | 139 (14.9) |
and postdocs (2.9 percent). Three-fourths were white (76.3 percent), and most (82.4 percent) were married or living with a romantic partner. A little less than one-tenth (7.7 percent) of married women faculty lived apart from their spouse or one of the spouses lived far from work because of the other’s work. More than half (57.1 percent) provided care for children under the age of 18, 10 percent provided eldercare, and 7 percent provided sandwiched care (i.e., both childcare and eldercare). Nearly one-fifth, or 18.8 percent, provided care for family members who do not live with them. While most of the concerns of non-tenure-track faculty mirrored those of tenured and tenure-track faculty, we did notice some unique challenges, which we focus on here.
Most of the survey responses were qualitative and were analyzed using a content analysis method developed by Schreier (2012). First, we created our main coding frame, challenges and coping strategies, for each topic (e.g., childcare, eldercare, boundary management, work and nonwork, and effects) based on the literature review. Next, subcategories were created under each main category. They were defined to make sure each category was mutually exclusive and were continuously reexamined through discussion. After the coding was completed, we obtained final counts for each category. The full list of survey topics is provided in Table A-3.
The several quantitative items from the survey were analyzed using IBM SPSS Statistics 26 (IBM Corp., 2019). Means and standard deviations were obtained for the boundary-control measure to assess changes in boundary control. Using paired t tests, we also compared changes in prepandemic and postpandemic location preferences assessing the number of preferred and actual days working on and off campus over a 5-day week. For example, paired t-tests results revealed that, across the sample of women STEMM faculty, all reported significantly lower levels of boundary control after the pandemic than before the pandemic (t = 33.42, p < .001; 3.98 and 2.33 respectively). In order to examine the impacts of care responsibilities on the changes in the numbers of days working at home and boundary management, we used a general linear mixed model (Cnaan, et al., 1997; Krueger and Tian, 2004) approach. For example, a general linear mixed-model analysis was conducted to examine whether the magnitude of the increase in the number of days working at home post-COVID-19 was different between faculty with and without children. The result revealed that the increase in the number of days working at home post-COVID-19 pandemic was significantly greater for faculty with children than faculty without children (F (1, 753) = 11.58).
Literature Review Search Terms
To inform the literature review summarized in the commissioned paper, “Boundaryless Work: The Impact of COVID-19 on Work-Life Boundary Management, Integration, and Gendered Divisions of Labor for Academic Women in STEMM,” We used the search criteria and obtained the number of results presented in Table A-4. To note, we found that, at the time of writing, few empirical papers focused specifically on COVID-19 and women in STEMM.
TABLE A-3 Topics for the October 2020 Survey
Quantitative Questions | |
---|---|
Work location | |
The number of days of working at home (out of 3 working days) before and after the pandemic | The preferred number of days of working at home |
Boundary control | |
The actual and preferred levels of boundary control before and after the pandemic, using a boundary control measure by Kossek et al. (2012) |
Qualitative Questions | |||
---|---|---|---|
The positive and negative impact of COVID-19 on personal and career well-being | |||
Boundary management | |||
The challenges of boundary management between work and family due to COVID-19 | Examples of boundary-setting practices (physical, temporal, mental, and technological) | Differences in boundary management between work and family after the pandemic | |
Support from the university | |||
Examples of university support for work-life integration | What needs to be improved | ||
Housework demands | |||
The positive and negative impact of COVID-19 on nonwork responsibilities | The negotiation of nonwork responsibilities during the pandemic |
Care Demands | ||||
---|---|---|---|---|
The positive and negative impact of COVID-19 on the following: | ||||
Childcare | Eldercare | Sandwiched care | Long-distance care | Long-distance romantic relationship |
Background Information | ||||
---|---|---|---|---|
Gender | Race/ethnicity | Academic affiliation (university/department) | Tenure status (tenured, tenure-track but not yet tenured, non-tenure-track) | Rank |
Kossek Search | Psychinfo | Academic Search Complete | |||
---|---|---|---|---|---|
1. | COVID-19 and Leadership | 51 | 367 | ||
2. | COVID-19 and HR | 6 | 72 | ||
3. | COVID-19 and organizational support | 2 | 3 | ||
4. | COVID-19 and faculty | 148 | 21 | ||
5. | COVID-19 and women faculty | 2 | 4 | ||
6. | COVID-19 and university | 1,175 | 108 | ||
7. | COVID-19 and higher education | 22 | 24 | ||
8. | COVID-19 and professors | 11 | 0 | ||
9. | COVID-19 and coping | 108 | 1 | ||
10. | COVID-19 and faculty stress | 1 | 0 | ||
11. | COVID-19 and faculty well-being | 0 | 0 | ||
12. | COVID-19 and faculty coping | 0 | 0 | ||
13. | COVID-19 and faculty eldercare | 0 | 0 | ||
14. | COVID-19 and faculty childcare | 2 | 0 | ||
15. | COVID-19 and faculty parenting | 0 | 0 | ||
16. | COVID-19 and faculty sandwiched care | 0 | 0 | ||
17. | COVID-19 and eldercare | 5 | 0 | ||
18. | COVID-19 and childcare | 20 | 21 | ||
19. | COVID-19 and STEM | 10 | 122 | ||
20. | COVID-19 and STEMM | 0 | 0 | ||
Subtotal | 1,563 | 743 | |||
Chronicle of Higher Education COVID 19 used as search term | 769 | ||||
Total (Kossek) | 3,075 | ||||
Dumas Search | |||||
1. | “COVID-19” “women” “faculty’ “stem” | 3,290 | |||
2. | “COVID-19” “women” “faculty” “stem” “U.S.” | 2,890 | |||
Allen Search | |||||
USF library | |||||
1. | COVID-19 AND academic women | 1,149 | |||
2. | COVID-19 AND academic women AND division of labor | 108 | |||
3. | COVID-19 AND STEM | 138,794 | |||
4. | COVID-19 AND STEMM | 105 | |||
SocArXIC Papers website | |||||
1. | COVID academic women | 74 |