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There are a variety of urgent calls for institutional initiatives and actions to transform engineering education. For a transformational change to occur, the initiatives must alter the culture of the institutions (Eckel, Hill, and Green, 1998). In this work in progress, we detail the methods used to conduct a scoping literature review (ScR) concerning the current state of the literature surrounding institutional culture and transformational change in engineering education at institutions of higher learning in the United States. As institutional culture and transformational change are currently underexplored topics in the engineering education literature, we investigated the larger body of computer science and engineering literature in the United States. Once completed, this study aims to reveal the current trends, theories, and potential gaps in the literature regarding these topics. Arksey and O’Malley’s methodology for conducting scoping reviews informed the development of our scoping review protocol, which similarly includes five stages: (1) identify the research questions, (2) identify relevant studies, (3) select relevant studies, (4) chart the data, and (5) collate, summarize, and report results (Arksey and O’Malley, 2005). University librarians who specialize in conducting systematic reviews aided in the refinement of this protocol. From the research question and aim of the study, three main inclusion criteria were created: (1) the literature must discuss both organizational culture and transformational change, (2) discussion of transformational change must describe the institution where the change happened, and (3) the literature must emphasize the agents of transformational change. Additional inclusion and exclusion criteria were created in collaboration with both the librarians and reviewers. These criteria guided the search for existing literature in the following online databases: Elsevier (Engineering Village – Compendex and Engineering Village – INSPEC), ProQuest (ERIC and Education Database), Scopus, and Web of Science. These six databases were selected as they often include publications relevant to the field of engineering education. After the search was conducted, the inclusion and exclusion criteria were turned into questions to inform a three-step screening process (title, abstract, and full text) used by reviewers to determine whether a publication was eligible for the study. Reviewers were assigned to review papers through Covidence, a cloud-based systematic literature review management platform. There are currently two primary reviewers and a third additional reviewer to resolve any conflicts or disagreements if they should arise. Before each review cycle, the inclusion and exclusion criteria are revisited, revised, and agreed upon by the three reviewers. This screening process is performed iteratively, allowing for critical reflection at each stage to drive the resulting findings by the reviewers in consultation with content matter experts. We are currently conducting our first round of screening in the study selection (third stage) of the scoping review protocol. After the removal of duplicates, 999 publications were found by searching in the six selected databases. This number is expected to be further reduced with each step of the screening process. When this scoping review is complete, the resulting publication will contain an analysis of the literature and synthesis of our findings, and present the prominent themes, theories, and potential gaps in the literature. This publication is expected to unite disparate lines of research on institutional culture and transformational change, challenge the assumptions in the field, and change the way engineering education views transformational change.more » « less
Abstract Introduction Digital twins, a form of artificial intelligence, are virtual representations of the physical world. In the past 20 years, digital twins have been utilized to track wind turbines' operations, monitor spacecraft's status, and even create a model of the Earth for climate research. While digital twins hold much promise for the neurocritical care unit, the question remains on how to best establish the rules that govern these models. This model will expand on our group’s existing digital twin model for the treatment of sepsis. Methods The authors of this project collaborated to create a Direct Acyclic Graph (DAG) and an initial series of 20 DELPHI statements, each with six accompanying sub-statements that captured the pathophysiology surrounding the management of acute ischemic strokes in the practice of Neurocritical Care (NCC). Agreement from a panel of 18 experts in the field of NCC was collected through a 7-point Likert scale with consensus defined a-priori by ≥ 80% selection of a 6 (“agree”) or 7 (“strongly agree”). The endpoint of the study was defined as the completion of three separate rounds of DELPHI consensus. DELPHI statements that had met consensus would not be included in subsequent rounds of DELPHI consensus. The authors refined DELPHI statements that did not reach consensus with the guidance of de-identified expert comments for subsequent rounds of DELPHI. All DELPHI statements that reached consensus by the end of three rounds of DELPHI consensus would go on to be used to inform the construction of the digital twin model. Results After the completion of three rounds of DELPHI, 93 (77.5%) statements reached consensus, 11 (9.2%) statements were excluded, and 16 (13.3%) statements did not reach a consensus of the original 120 DELPHI statements. Conclusion This descriptive study demonstrates the use of the DELPHI process to generate consensus among experts and establish a set of rules for the development of a digital twin model for use in the neurologic ICU. Compared to associative models of AI, which develop rules based on finding associations in datasets, digital twin AI created by the DELPHI process are easily interpretable models based on a current understanding of underlying physiology.more » « less
The COVID-19 pandemic has dramatically altered family life in the United States. Over the long duration of the pandemic, parents had to adapt to shifting work conditions, virtual schooling, the closure of daycare facilities, and the stress of not only managing households without domestic and care supports but also worrying that family members may contract the novel coronavirus. Reports early in the pandemic suggest that these burdens have fallen disproportionately on mothers, creating concerns about the long-term implications of the pandemic for gender inequality and mothers’ well-being. Nevertheless, less is known about how parents’ engagement in domestic labor and paid work has changed throughout the pandemic, what factors may be driving these changes, and what the long-term consequences of the pandemic may be for the gendered division of labor and gender inequality more generally.more » « less
The Study on U.S. Parents’ Divisions of Labor During COVID-19 (SPDLC) collects longitudinal survey data from partnered U.S. parents that can be used to assess changes in parents’ divisions of domestic labor, divisions of paid labor, and well-being throughout and after the COVID-19 pandemic. The goal of SPDLC is to understand both the short- and long-term impacts of the pandemic for the gendered division of labor, work-family issues, and broader patterns of gender inequality.
Survey data for this study is collected using Prolifc (www.prolific.co), an opt-in online platform designed to facilitate scientific research. The sample is comprised U.S. adults who were residing with a romantic partner and at least one biological child (at the time of entry into the study). In each survey, parents answer questions about both themselves and their partners. Wave 1 of SPDLC was conducted in April 2020, and parents who participated in Wave 1 were asked about their division of labor both prior to (i.e., early March 2020) and one month after the pandemic began. Wave 2 of SPDLC was collected in November 2020. Parents who participated in Wave 1 were invited to participate again in Wave 2, and a new cohort of parents was also recruited to participate in the Wave 2 survey. Wave 3 of SPDLC was collected in October 2021. Parents who participated in either of the first two waves were invited to participate again in Wave 3, and another new cohort of parents was also recruited to participate in the Wave 3 survey. This research design (follow-up survey of panelists and new cross-section of parents at each wave) will continue through 2024, culminating in six waves of data spanning the period from March 2020 through October 2024. An estimated total of approximately 6,500 parents will be surveyed at least once throughout the duration of the study.
SPDLC data will be released to the public two years after data is collected; Waves 1 and 2 are currently publicly available. Wave 3 will be publicly available in October 2023, with subsequent waves becoming available yearly. Data will be available to download in both SPSS (.sav) and Stata (.dta) formats, and the following data files will be available: (1) a data file for each individual wave, which contains responses from all participants in that wave of data collection, (2) a longitudinal panel data file, which contains longitudinal follow-up data from all available waves, and (3) a repeated cross-section data file, which contains the repeated cross-section data (from new respondents at each wave) from all available waves. Codebooks for each survey wave and a detailed user guide describing the data are also available. Response Rates: Of the 1,157 parents who participated in Wave 1, 828 (72%) also participated in the Wave 2 study. Presence of Common Scales: The following established scales are included in the survey:
- Self-Efficacy, adapted from Pearlin's mastery scale (Pearlin et al., 1981) and the Rosenberg self-esteem scale (Rosenberg, 2015) and taken from the American Changing Lives Survey
- Communication with Partner, taken from the Marriage and Relationship Survey (Lichter & Carmalt, 2009)
- Gender Attitudes, taken from the National Survey of Families and Households (Sweet & Bumpass, 1996)
- Depressive Symptoms (CES-D-10)
- Stress, measured using Cohen's Perceived Stress Scale (Cohen, Kamarck, & Mermelstein, 1983)
The second wave of the SPDLC was fielded in November 2020 in two stages. In the first stage, all parents who participated in W1 of the SPDLC and who continued to reside in the United States were re-contacted and asked to participate in a follow-up survey. The W2 survey was posted on Prolific, and messages were sent via Prolific’s messaging system to all previous participants. Multiple follow-up messages were sent in an attempt to increase response rates to the follow-up survey. Of the 1,157 respondents who completed the W1 survey, 873 at least started the W2 survey. Data quality checks were employed in line with best practices for online surveys (e.g., removing respondents who did not complete most of the survey or who did not pass the attention filters). After data quality checks, 5.2% of respondents were removed from the sample, resulting in a final sample size of 828 parents (a response rate of 72%).
In the second stage, a new sample of parents was recruited. New parents had to meet the same sampling criteria as in W1 (be at least 18 years old, reside in the United States, reside with a romantic partner, and be a parent living with at least one biological child). Also similar to the W1 procedures, we oversampled men, Black individuals, individuals who did not complete college, and individuals who identified as politically conservative to increase sample diversity. A total of 1,207 parents participated in the W2 survey. Data quality checks led to the removal of 5.7% of the respondents, resulting in a final sample size of new respondents at Wave 2 of 1,138 parents.
In both stages, participants were informed that the survey would take approximately 20 minutes to complete. All panelists were provided monetary compensation in line with Prolific’s compensation guidelines, which require that all participants earn above minimum wage for their time participating in studies.
To be included in SPDLC, respondents had to meet the following sampling criteria at the time they enter the study: (a) be at least 18 years old, (b) reside in the United States, (c) reside with a romantic partner (i.e., be married or cohabiting), and (d) be a parent living with at least one biological child. Follow-up respondents must be at least 18 years old and reside in the United States, but may experience changes in relationship and resident parent statuses. Smallest Geographic Unit: U.S. State
This work is licensed under the Creative Commons Attribution 4.0 International License. To view a copy of this license, visit http://creativecommons.org/licenses/by/4.0/. In accordance with this license, all users of these data must give appropriate credit to the authors in any papers, presentations, books, or other works that use the data. A suggested citation to provide attribution for these data is included below:To help provide estimates that are more representative of U.S. partnered parents, the SPDLC includes sampling weights. Weights can be included in statistical analyses to make estimates from the SPDLC sample representative of U.S. parents who reside with a romantic partner (married or cohabiting) and a child aged 18 or younger based on age, race/ethnicity, and gender. National estimates for the age, racial/ethnic, and gender profile of U.S. partnered parents were obtained using data from the 2020 Current Population Survey (CPS). Weights were calculated using an iterative raking method, such that the full sample in each data file matches the nationally representative CPS data in regard to the gender, age, and racial/ethnic distributions within the data. This variable is labeled CPSweightW2 in the Wave 2 dataset, and CPSweightLW2 in the longitudinal dataset (which includes Waves 1 and 2). There is not a weight variable included in the W1-W2 repeated cross-section data file.
Carlson, Daniel L. and Richard J. Petts. 2022. Study on U.S. Parents’ Divisions of Labor During COVID-19 User Guide: Waves 1-2.
null (Ed.)The COVID-19 pandemic has caused financial stress and disrupted daily life more quickly than any prior economic downturn and on a scale beyond any prior natural disaster. This study aimed to assess the impact of the pandemic on psychological distress and identify vulnerable groups using longitudinal data to account for pre-pandemic mental health status. Clinically significant psychological distress was assessed with the Kessler-6 in a national probability sample of adults in the United States at two time points, February 2019 (T1) and May 2020 (T2). To identify increases in distress, psychological distress during the worst month of the past year at T1 was compared with psychological distress over the past 30-days at T2. Survey adjusted logistic regression was used to estimate associations of demographic characteristics at T1 (gender, age, race, and income) and census region at T2 with within-person increases in psychological distress. The past-month prevalence of serious psychological distress at T2 was as high as the past-year prevalence at T1 (10.9% vs. 10.2%). Psychological distress was strongly associated across assessments (X2(4) = 174.6, p < .0001). Increase in psychological distress above T1 was associated with gender, age, household income, and census region. Equal numbers of people experienced serious psychological distress in 30-days during the pandemic as did over an entire year prior to the pandemic. Mental health services and research efforts should be targeted to those with a history of mental health conditions and groups identified as at high risk for increases in distress above pre-pandemic levels.more » « less
Few studies have used longitudinal approaches to consider the cumulative impact of COVID-19-related stressors (CRSs) on the psychological adjustment of mothers and children. In the current study, we tracked changes in maternal depressive symptoms and children’s behavioral problems from approximately 2 years before the pandemic (T1) to May through August 2020 (T2). Second, we explored maternal hair cortisol and dehydroepiandrosterone as predictors of change in maternal depressive symptoms. Mothers (N = 120) reported on maternal and child psychological adjustment at both time points. Hair hormone data were collected in the lab at T1. Results suggest increases in children’s internalizing symptoms from T1 to T2 and that higher levels of CRSs were associated with increased maternal depressive symptoms. Maternal and child adjustment were correlated. Maternal hair cortisol, but not dehydroepiandrosterone, was associated with significant increases in depressive symptoms. Findings underscore the importance of considering the family system and cumulative risk exposure on maternal and child mental health.more » « less