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1. Study on U.S. Parents' Divisions of Labor During COVID-19, Waves 1-2

   https://doi.org/10.3886/E183142V2  

   Carlson, Daniel L. ; Petts, Richard J. ( January 2022 , ICPSR - Interuniversity Consortium for Political and Social Research)

   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.
   
   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)
     

   Full details about these scales and all other items included in the survey can be found in the user guide and codebook
   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:            
   
   Carlson, Daniel L. and Richard J. Petts. 2022. Study on U.S. Parents’ Divisions of Labor During COVID-19 User Guide: Waves 1-2.  

   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.
    

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2. Perceptions, Experiences, and Priorities Supporting Agroecosystem Management Decisions Differ among Agricultural Producers, Consultants, and Researchers

   https://doi.org/10.3390/su10114096  

   McKenzie, Sean ; Parkinson, Hilary ; Mangold, Jane ; Burrows, Mary ; Ahmed, Selena ; Menalled, Fabian ( November 2018 , Sustainability)

   The sustainability of agriculture depends as much on the natural resources required for production as it does on the stakeholders that manage those resources. It is thus essential to understand the variables that influence the decision-making process of agricultural stakeholders to design educational programs, interventions, and policies geared towards their specific needs, a required step to enhance agricultural sustainability. This study employed a survey of multiple-choice and open-ended questions to examine the perceptions, experiences, and priorities that influence management decisions of agricultural stakeholders across Montana, United States. A total of 272 respondents completed a survey, representing five distinct agricultural stakeholder groups: 103 (34.9%) conventional producers, 78 (28.7%) consultants, 37 (13.6%) researchers, 33 (12.1%) organic grain producers, and 21 (7.7%) organic vegetable producers. The results revealed that, while stakeholder groups have distinct perceptions, experiences, and priorities, there were similarities across groups (pseudo-F = 22.92, p = 0.001). Specifically, organic vegetable and organic small-grain producers showed similar responses that were, in turn, divergent from those of conventional producers, researchers, and crop consultants. Conventional small-grain producers and researchers showed overlapping response patterns, while crop consultants formed an isolated group. Six clusters resulting from the classification of the multiple-choice response dataset associated with specific agricultural professions (χ2 = 549.72, p = 0.001). The classification of open-ended questions that assessed agronomic challenges and research needs resulted in six distinctive clusters, with specific associations between clusters and agricultural stakeholder groups (χ2 = 164.41, p = 0.001). These results reinforce the need for agricultural education and programs that address unique and shared experiences, priorities, and concerns of multiple stakeholder groups. This study endorses the call for a paradigm shift from the traditional top-down agricultural extension model to one that accounts for participants’ socio-ecological contexts to facilitate the adoption of sustainable agricultural systems that support environmental and human wellbeing. 

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3. Mapping potable reuse survey data using spatial statistics to inform tailored education and outreach

   https://doi.org/10.1002/aws2.1197  

   Cruz, Maurice P. ; Scruggs, Caroline E. ; Distler, Lauren N. ( October 2020 , AWWA Water Science)

   This research describes geospatial analyses of water‐related knowledge and opinion data on potable water reuse collected through a large‐scale public survey of water utility customers in Albuquerque, New Mexico. We identify key geographic areas, or statistically significant “hotspots,” of public distrust in the local water utility provider, public willingness (or lack thereof) to accept potable water reuse, and lack of knowledge or misconceptions about water‐related issues and climate change. By combining public survey data, geographic information system software, and spatial statistics for hotspot analyses, we introduce a tailored outreach method to identify geographic locations for targeted outreach and education on water‐related issues. This new approach to analyzing survey data is a promising dimension of water management, and the method could be important for tackling other resource management issues in additional cities or regions as well.

    

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4. Extending traditional water supplies in inland communities with nontraditional solutions to water scarcity

   https://doi.org/10.1002/wat2.1543  

   Scruggs, Caroline E. ; Heyne, Catherine M. ( June 2021 , WIREs Water)

   Urban communities around the world are grappling with the challenges associated with population increases, drought, and projected water shortages. With a substantial global shortfall between water supply and demand expected by 2030, water planning strategies must adapt to a new reality characterized by higher temperatures and less precipitation, requiring new ways of thinking about water management, use, and governance. Commonplace strategies such as water conservation and nonpotable water reuse might not be sufficient to adequately stretch water supplies in water‐scarce parts of the industrialized world. In the United States, planned potable water reuse (i.e., purification of domestic wastewater for reuse as drinking water) is emerging as a way forward to mitigate water shortages without significant changes to lifestyle, behavior, or infrastructure. But potable reuse is not the only solution: paradigm shifting and disruptive options that more holistically address water scarcity, such as composting toilets and market‐based approaches to water use, are also gaining traction, and they could be pursued alongside or instead of potable water reuse. However, these options would require more significant changes to lifestyles, behavior, infrastructure, and governance. While all of the options considered offer advantages, they each come with new concerns and challenges related to cost, public perception, social norms, and policy. The goal of this work is to consider a number of plausible solutions to water scarcity—partial and complete, traditional and disruptive—to stimulate forward‐looking thinking about the increasingly common global problem of water scarcity.

   This article is categorized under:

   Engineering Water > Sustainable Engineering of Water

   Engineering Water > Planning Water

    

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5. Defining and characterizing task-shifting medical devices

   https://doi.org/10.1186/s12992-021-00684-6  

   Sabet Sarvestani, Amir ; Coulentianos, Marianna ; Sienko, Kathleen H. ( May 2021 , Globalization and Health)

   Task shifting could help address limited human resources available for the delivery of quality health care services in low-resource settings. However, the role of medical devices in supporting task shifting is not fully understood. This study aimed to 1) define “task-shifting medical devices” and 2) identify product characteristics to guide the design and development of task-shifting medical devices.

   A three-part survey questionnaire comprising open-ended, rank-ordering, and multiple-choice questions was disseminated to healthcare professionals worldwide. The survey included questions to capture stakeholders’ general understanding of and preferences for task shifting in medicine and public health, and questions to define task-shifting medical devices and identify desirable product characteristics of task-shifting medical devices.

   Task-shifting medical devices were defined by respondents as “devices that can be used by a less specialized health worker”. Aside from safe and effective, both essential characteristics for medical devices, easy to use was the most cited product characteristic for a task-shifting medical device. Responses also emphasized the importance of task-shifting medical devices to enable local agency, such as peer-to-peer training and local maintenance. Several additional frequently mentioned attributes included low cost, contextually appropriate, maintainable, capable of using an alternative power source, easy to understand, easy to learn, reusable, and easy to manage throughout its use cycle.

   This study defines and characterizes task-shifting medical devices based on healthcare professionals’ responses. Ease of use was identified as the most important characteristic that defines a task-shifting medical device, alongside safe and effective, and was strongly associated with enabling peer-to-peer training and maintainability. The findings from this study can be used to inform technology product profiles for medical devices used by lower-level cadres of healthcare workers in low-resource settings.

    

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