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Characteristics of Parents Who Spent Time Away from Home during Stay-at-Home Orders and Relation to Parenting Behaviors in Ohio

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Title: Characteristics of Parents Who Spent Time Away from Home during Stay-at-Home Orders and Relation to Parenting Behaviors in Ohio
Language: English
Authors: Bridget Freisthler (ORCID 0000-0001-6993-4838), Polina Berezina, Yun Ye, Fatoumata Bah, Balalji Ramesh, Gia Barboza-Salerno, Jennifer Price Wolf
Source: Child & Youth Care Forum. 2025 54(4):817-839.
Availability: Springer. Available from: Springer Nature. One New York Plaza, Suite 4600, New York, NY 10004. Tel: 800-777-4643; Tel: 212-460-1500; Fax: 212-460-1700; e-mail: customerservice@springernature.com; Web site: https://link.springer.com/
Peer Reviewed: Y
Page Count: 23
Publication Date: 2025
Document Type: Journal Articles
Reports - Research
Descriptors: Parent Child Relationship, COVID-19, Pandemics, School Closing, Ecology, Stress Variables, Child Rearing, Family Environment, Social Distance, Neighborhoods, Discipline, Punishment, Probability
Geographic Terms: Ohio
DOI: 10.1007/s10566-024-09841-5
ISSN: 1053-1890
1573-3319
Abstract: Background: During the COVID-19 pandemic, stay-at-home (SAH) orders were instituted to limit geographic movement of the population and decrease the spread of the virus. Parents made decisions about how to keep themselves and their children safe which may have led to differing compliance with SAH orders and affected parenting. Objective: We assessed characteristics of those more likely to spend time outside the home and how time spent outside the home was related to parental use of discipline behaviors. Method: We conducted a 14-day Ecological Momentary Assessment (gEMA) during April-May 2020 in a convenience sample 245 parents with children 2-12 years old in Ohio. Participants completed the EMA three times a day on stress and parenting behaviors. Geotracking during the 14 days was used to calculate time spent away from home. Data were analyzed using multilevel models. Results: The more social distancing in a neighborhood, the less time a parent spent outside the home. Parents who spent more time away from home had lower odds of using punitive and non-punitive parenting on that day. At-the-moment stress was related to higher odds of using punitive and non-punitive parenting. Conclusions: The response to COVID no longer includes SAH orders; yet this work allowed us to begin to disentangle types of environmental stress and in what ecological systems this stress may affect parenting. Factors in the microsystem, including stress due to daily hassles, were more likely to be related to immediate parenting behaviors than stressors in the exosystem or macrosystem.
Abstractor: As Provided
Entry Date: 2025
Accession Number: EJ1477391
Database: ERIC
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  Value: <anid>AN0186677917;5jr01aug.25;2025Jul18.03:52;v2.2.500</anid> <title id="AN0186677917-1">Characteristics of Parents Who Spent Time Away from Home During Stay-at-Home Orders and Relation to Parenting Behaviors in Ohio </title> <p>Background: During the COVID-19 pandemic, stay-at-home (SAH) orders were instituted to limit geographic movement of the population and decrease the spread of the virus. Parents made decisions about how to keep themselves and their children safe which may have led to differing compliance with SAH orders and affected parenting. Objective: We assessed characteristics of those more likely to spend time outside the home and how time spent outside the home was related to parental use of discipline behaviors. Method: We conducted a 14-day Ecological Momentary Assessment (gEMA) during April–May 2020 in a convenience sample 245 parents with children 2–12 years old in Ohio. Participants completed the EMA three times a day on stress and parenting behaviors. Geotracking during the 14 days was used to calculate time spent away from home. Data were analyzed using multilevel models. Results: The more social distancing in a neighborhood, the less time a parent spent outside the home. Parents who spent more time away from home had lower odds of using punitive and non-punitive parenting on that day. At-the-moment stress was related to higher odds of using punitive and non-punitive parenting. Conclusions: The response to COVID no longer includes SAH orders; yet this work allowed us to begin to disentangle types of environmental stress and in what ecological systems this stress may affect parenting. Factors in the microsystem, including stress due to daily hassles, were more likely to be related to immediate parenting behaviors than stressors in the exosystem or macrosystem.</p> <p>Keywords: COVID-19; Pandemic; Parenting; Time outside; Punitive parenting; Nonpunitive parenting</p> <p>Copyright comment Springer Nature or its licensor (e.g. a society or other partner) holds exclusive rights to this article under a publishing agreement with the author(s) or other rightsholder(s); author self-archiving of the accepted manuscript version of this article is solely governed by the terms of such publishing agreement and applicable law.</p> <hd id="AN0186677917-2">Introduction</hd> <p>The early stages of the COVID-19 pandemic significantly changed how people were living, including time spent at home, where people worked, and how children were schooled. Stress was higher at the early stages of the pandemic for parents as they navigated a new reality that provided little respite in caring for their children. Parents made decisions about how to keep themselves and their children safe which may have led to different levels of compliance with stay-at-home orders, including time spent outside of the home (regardless of whether the child(ren) were with the parent). This decision was not made in a vacuum. Parents were likely paying attention to whether others in their local neighborhood were complying with stay-at-home orders, becoming a factor in their decision of whether to comply.</p> <p>A parent's compliance could also be related to how they parent. Parents who choose to spend more time outside than their neighbors, regardless of the type of location (e.g., parks, shopping) might use less punitive parenting practices as it breaks up the monotony of the day and provides everyone with some relief from being in close proximity to others. However, leaving the home might be viewed negatively from neighbors who feel they are skirting COVID-19 restrictions. Thus, parents may be attuned to how adherent their neighbors are to SAH policies and shape behaviors accordingly. Here, we look to understand (<reflink idref="bib1" id="ref1">1</reflink>) characteristics of parents more likely to spend time outside the home and how social distancing of their neighbors was related to a parent's time spent at home and (<reflink idref="bib2" id="ref2">2</reflink>) how time spent outside the home was related to use of discipline behaviors by parents.</p> <p>Although the initial stages of the COVID-19 pandemic were unique in that SAH orders and social distancing requirements were implemented across the country, we continue to need to understand how to support parents during times of high stress that may include being homebound with children, isolation from regular support systems, or experiencing a natural disaster. In the extant literature, stress and social isolation are known risk factors for child abuse and neglect and other problematic parenting (Younas & Gutman, [<reflink idref="bib81" id="ref3">81</reflink>]). This study advances that work by examining both global perceived stress and at-the-moment/situational stress and their association to parenting. By framing this in the Ecological-Transactional systems framework and Environmental Stress theory, we further develop these ideas as enduring and transient vulnerabilities while also identifying possible buffers and resiliency that can support parenting during these events. Spending time away from home, regardless of the activities completed during that time, would represent a novel and potentially straightforward lifestyle change that parents could make. Further, the "pressure cooker" of the SAH orders during the COVID-19 pandemic afforded us the opportunity to study in a sample of parents who were undergoing tremendous stress.</p> <hd id="AN0186677917-3">Literature Review</hd> <p></p> <hd id="AN0186677917-4">Stay-At-Home Orders in Ohio</hd> <p>As COVID-19 cases rose in the state of Ohio, various measures were implemented to contain the spread of the virus. On March 9, 2020, the governor declared a state of emergency (Executive Order, 2020-01D, [<reflink idref="bib60" id="ref4">60</reflink>]). Following this declaration, the closure of all K-12 schools in the state was ordered, effective March 17, and set to continue for several weeks (Ohio Department of Health, [<reflink idref="bib58" id="ref5">58</reflink>]). Subsequently, on March 23, 2020, Ohio authorities implemented a comprehensive "Stay-at-Home" (SAH) order, which emphasized the importance of maintaining a minimum distance of six feet between individuals in shared spaces, commonly referred to as social distancing. As part of the SAH order, non-essential businesses were required to suspend operations, with exceptions made for those capable of functioning remotely (Ohio Department of Health, [<reflink idref="bib58" id="ref6">58</reflink>]). On May 1, 2020, the SAH orders were lifted, and the state government transitioned to "Safe-at-Home" guidelines (Ohio Department of Health, [<reflink idref="bib57" id="ref7">57</reflink>]). Schools were required to remain closed, restaurants and bars were not permitted to offer dine-in services, beauty shops and recreational facilities were shuttered, and child care services were restricted (Ohio Department of Health, [<reflink idref="bib57" id="ref8">57</reflink>]). On May 20, 2020 these orders were lifted in favor of the "Urgent Health Advisory: Ohioans Protecting Ohioans" guidelines, where restrictions were loosened further (Ohio Department of Health, [<reflink idref="bib59" id="ref9">59</reflink>]).</p> <hd id="AN0186677917-5">Compliance of Stay-At-Home Orders</hd> <p>General compliance with stay-at-home orders was high, although it may have differed by location. A survey of adults from the US and Australia, found that most respondents (81.8%) reported compliance with recommended quarantine or SAH policies (Czeisler et al., [<reflink idref="bib18" id="ref10">18</reflink>]). Mandatory SAH orders issued by states or territories in the US were associated with decreased population movement in the majority of counties (Jacobsen & Jacobsen, [<reflink idref="bib36" id="ref11">36</reflink>]; Moreland et al., [<reflink idref="bib54" id="ref12">54</reflink>]). States that implemented these orders witnessed significant declines in use of retail and recreation facilities, workplaces, and grocery stores compared to states without such orders (Jacobsen & Jacobsen, [<reflink idref="bib36" id="ref13">36</reflink>]). Compliance with SAH orders was at its highest when these orders were initially issued (Gao, [<reflink idref="bib29" id="ref14">29</reflink>]). However, Lasry et al. ([<reflink idref="bib46" id="ref15">46</reflink>]) found that emergency declarations did not lead to a sustained change in population mobility in major cities and were more successful when followed by implementation of additional orders (e.g. stay-at-home orders). The closure of public schools was found to be the most effective policy for keeping people at home all day (Cronin & Evans, [<reflink idref="bib16" id="ref16">16</reflink>]). Moreover, as SAH orders began to be lifted nationwide, population movement increased both in areas where the orders were lifted and in communities where these orders were still in place (Moreland et al., [<reflink idref="bib54" id="ref17">54</reflink>]).</p> <p>Adherence to social distancing orders also appeared to vary based on sociodemographic characteristics. Although social distancing increased across all income levels in the United States (Jay et al., [<reflink idref="bib37" id="ref18">37</reflink>]), socio-economic disparities existed in adherence to SAH orders (Fu & Zhai, [<reflink idref="bib26" id="ref19">26</reflink>]; Huang et al., [<reflink idref="bib34" id="ref20">34</reflink>]; Jay et al., [<reflink idref="bib37" id="ref21">37</reflink>]). Huang et al. ([<reflink idref="bib34" id="ref22">34</reflink>]) found that income level was a significant predictor of home-dwelling time, with lower levels of compliance observed in poorer neighborhoods. Lower-income individuals experienced an 11% increase in days spent at home from January 2020 to April 2020, while the highest income group displayed a 16% increase (Jay et al., [<reflink idref="bib37" id="ref23">37</reflink>]). Poor communities displayed less compliance with SAH orders, spending less time at home compared to wealthier communities. Additionally, educational level was strongly correlated with an increased rate of home-dwelling time (Huang et al., [<reflink idref="bib34" id="ref24">34</reflink>]). In New York City, higher poverty, lower per capita income, lack of high school diploma, presence of single parents, and other demographic factors were associated with reduced SAH behaviors in communities (Fu & Zhai, [<reflink idref="bib26" id="ref25">26</reflink>]).</p> <p>Women reported higher levels of social distancing compared to men (Pedersen & Favero, [<reflink idref="bib62" id="ref26">62</reflink>]). This is not surprising as women were more likely to view COVID-19 as a serious threat leading to greater compliance with public health orders (Galasso et al., [<reflink idref="bib27" id="ref27">27</reflink>]). Likewise, Alsharawy et al. ([<reflink idref="bib2" id="ref28">2</reflink>]) discovered that women tend to adopt a higher number of preventive measures compared to men in response to the pandemic. However, the gender-based variations in behavior diminish when the element of fear is taken into account. Black individuals tended to engage in slightly less social distancing, while Asians tended to engage in slightly more (Pedersen & Favero, [<reflink idref="bib62" id="ref29">62</reflink>]). Counties with a greater non-Hispanic Black population engaged in less social distancing compared to other areas (Andersen, [<reflink idref="bib4" id="ref30">4</reflink>]).</p> <hd id="AN0186677917-6">Spending Time Outside During the Pandemic</hd> <p>Demographic factors also appear to have shaped how much time an individual spent outside in nature during the SAH orders. Community park visits in the U.S. experienced a 36.0% reduction during the COVID-19 restriction period (March to November 2020) compared to prior levels (Jay et al., [<reflink idref="bib38" id="ref31">38</reflink>]). Socioeconomic status was related to park visits, with lower socioeconomic status associated with fewer visits (Jay et al., [<reflink idref="bib38" id="ref32">38</reflink>]; Larson et al., [<reflink idref="bib45" id="ref33">45</reflink>]). Areas with a higher proportion of White and/or higher income residents experienced a more significant increase in park visits upon reopening (Jay et al., [<reflink idref="bib38" id="ref34">38</reflink>]).</p> <p>Larson et al. ([<reflink idref="bib45" id="ref35">45</reflink>]) focused on urban park use patterns in 2 North Carolina cities. Prior to COVID-19, higher-income and educated individuals were more likely to be frequent park users, and White respondents were more likely to use parks compared to other racial/ethnic groups. Although they observed a decrease in overall visits from mid-March, in late March and April the number of Twitter users identified in parks remained above their established baseline for 71 days (Jiang et al., [<reflink idref="bib39" id="ref36">39</reflink>]). Similarly, a study comparing community parks (larger than 16 acres) and neighborhood parks in a mid-sized city found significant increases in visitations during the late summer and early fall of 2020 (Song et al., [<reflink idref="bib71" id="ref37">71</reflink>]). According to Cindrich et al. ([<reflink idref="bib14" id="ref38">14</reflink>]), regardless of the level of physical activity or the extent of COVID-19-related restrictions, individuals who maintained or increased their time spent outdoors reported lower stress levels and higher levels of positive mental health. Young et al. ([<reflink idref="bib82" id="ref39">82</reflink>]) noted that this effect was more pronounced among younger participants compared to those in older age categories. Decisions about adherence to SAH orders can thus be seen as a complicated weighing of risks and benefits for individuals, who may perceive personal pleasure from activities such as spending time outside, even as they defied public health directives.</p> <hd id="AN0186677917-7">Parenting During the Pandemic</hd> <p>Parents of young and school-age children may have had uniquely challenging experiences with SAH orders. With the widespread closure of schools and workplaces across the nation, parents and their children experienced increased interactions within the home environment. The novel and uncertain nature of the COVID-19 disease led to its perception as a significant stressor for many parents and children. Moreover, recent studies have revealed that parents' subjective assessment of the impact of COVID-19 is linked to heightened levels of parenting stress, which, in turn, increased the likelihood of engaging in harsh parenting practices (Chung et al., [<reflink idref="bib12" id="ref40">12</reflink>]). Parents who experienced higher COVID-19 related stress, elevated levels of anxiety, and depressive symptoms tended to perceive higher levels of parental stress (Brown et al., [<reflink idref="bib9" id="ref41">9</reflink>]). Similarly, a study conducted in New Zealand by Swit and Breen ([<reflink idref="bib75" id="ref42">75</reflink>]) found that factors such as parental violence, family composition, unemployment, significant financial decline, and residing in a disadvantaged neighborhood were strong predictors of parental burnout.</p> <p>The stressors experienced by parents placed household members, especially children, at risk of abuse. The COVID-19 pandemic exacerbated this risk due to the limited contact abuse victims have with the outside world. As a result, many researchers predicted an increase in domestic violence and child abuse and neglect (Humphreys et al., [<reflink idref="bib35" id="ref43">35</reflink>]; Kaukinen, [<reflink idref="bib40" id="ref44">40</reflink>]). However, although there had been an increase in police calls related to domestic violence, reports of child abuse and neglect during the early pandemic decreased nationwide (Barboza et al., [<reflink idref="bib5" id="ref45">5</reflink>]; Baron et al., [<reflink idref="bib7" id="ref46">7</reflink>]; Bullinger et al., [<reflink idref="bib10" id="ref47">10</reflink>]). Bullinger et al. ([<reflink idref="bib10" id="ref48">10</reflink>]) found that SAH orders resulted in a decrease in overall calls for police service compared to the previous year. However, they also observed an increase in calls related to domestic violence (DV), specifically by 6.8–7.5% and a reduction in calls related to child maltreatment in Indiana. Despite the increase in calls for DV, the arrest rates for DV cases showed a decrease of 27.1% during the same period. Barboza et al. ([<reflink idref="bib5" id="ref49">5</reflink>]), observed a 7.95% decrease in reports of child abuse and neglect during the COVID-19 pandemic when compared to the immediately preceding period in California. This decrease in reports of child maltreatment has been linked to the heightened isolation of children resulting from the public health measures implemented in response to COVID-19. Baron et al. ([<reflink idref="bib7" id="ref50">7</reflink>]) highlighted that the reduction in child abuse allegations is mainly due to a decline in reports from school personnel, supported by evidence indicating significant drops during months with COVID-19 school closures. Furthermore, counties with higher ratios of school nurses and psychologists experienced more pronounced declines in the number of allegations (Baron et al., [<reflink idref="bib7" id="ref51">7</reflink>]). These findings suggest that the closure of schools during the pandemic had an impact on the reporting of child abuse and neglect cases, and the presence of supportive professionals in schools played a role in identifying and reporting instances of abuse and neglect. These studies could therefore be missing increased child abuse and neglect that has not been reported, or punitive parenting (i.e. parenting such as yelling, threatening, or spanking children that does not meet the threshold for official abuse or neglect). Initial research suggested that punitive parenting may have increased during the pandemic (Sari et al., [<reflink idref="bib70" id="ref52">70</reflink>]; Todorovic et al., [<reflink idref="bib77" id="ref53">77</reflink>]). Punitive parenting is itself related to physical abuse and negative outcomes for children (Gershoff, [<reflink idref="bib31" id="ref54">31</reflink>]; Gershoff et al., [<reflink idref="bib32" id="ref55">32</reflink>]; Lee et al., [<reflink idref="bib47" id="ref56">47</reflink>]; Rodriguez, [<reflink idref="bib66" id="ref57">66</reflink>]; Speyer et al., [<reflink idref="bib72" id="ref58">72</reflink>]). Understanding how parenting, including both punitive and non-punitive discipline (e.g. rewarding or praising a child), behaviors are related to parental time outside the home during the early COVID-19 pandemic can inform healthy ways in which parents adapted to circumstances as well as potential areas for future intervention.</p> <p>Initial research suggested that parental behaviors are influenced by others. For example, parental drinking decisions are shaped by social context (Wolf & Chávez, [<reflink idref="bib80" id="ref59">80</reflink>]), and drinking-related risk can be isolated to with whom a parent drinks alcohol (Price Wolf & Dellor, [<reflink idref="bib63" id="ref60">63</reflink>]). A wide variety of research has shown that community factors are related to outcomes such as child maltreatment (Freisthler et al., [<reflink idref="bib23" id="ref61">23</reflink>]), breastfeeding (Kummer et al., [<reflink idref="bib43" id="ref62">43</reflink>]), and other parenting outcomes (Rhoad-Drogalis et al., [<reflink idref="bib64" id="ref63">64</reflink>]). Thus far, however, little is known about how social or community influences might be related to SAH adherence amongst parents in particular. A recent scoping review (Noone et al., [<reflink idref="bib56" id="ref64">56</reflink>]) found that social and environmental factors were influential in adherence to social distancing policies during COVID-19. It could be that parents who view other parents spending time outside of the home may view this behavior as either safe or socially acceptable, and spend more time outside themselves as a result. In contrast, parents who see other people outside of the home might become more afraid to contract COVID-19 from someone else if they go outside, and therefore spend more time indoors.</p> <hd id="AN0186677917-8">The Present Study</hd> <p>We relied on the Ecological-Transactional systems framework (Cicchetti et al., [<reflink idref="bib13" id="ref65">13</reflink>]) and Environmental Stress theory (Gatersleben & Griffin, [<reflink idref="bib32" id="ref66">32</reflink>]) to understand how stress and other factors may affect both compliance with SAH orders and parenting behaviors (Fig. 1). Environmental stress is defined as the negative responses a person has towards factors to environmental stimuli (Gatersleben & Griffin, [<reflink idref="bib32" id="ref67">32</reflink>]). We used this theory to categorize the types of stressors faced by families, including daily hassles, life events, or cataclysmic stress. The ecological-transactional framework advanced the Ecological Systems model developed by Bronfenbrenner ([<reflink idref="bib8" id="ref68">8</reflink>]) by incorporating risk and protective factors into the models. These factors are then further broken down by whether they are enduring or transient, which we also use to characterize the types of stress listed above. As an example, the microsystem incorporates factors related to the family that may affect use of child maltreatment. Transient challenges (e.g., risk factors) would include at-the-moment stress and time of the day, where at the moment stress could be a factor of daily hassles stress (e.g., getting children up, remote learning). Time spent away from the home could provide a (transient) buffer to that stress as it represents a new activity and a change of environment. The exosystem refers to the larger aspects of communities where the families live. Here, employment could be an enduring the protective buffer that provides the family with resources even during the SAH orders during the pandemic. Perceived stress assesses current levels of experienced stress and is expected to be influenced by major life events. COVID-19 was a cataclysmic stress event that had a major impact on individuals' environments This is a macrosystem factor incorporating values and cultural beliefs, particularly in the role of community care designed to reduce contact rates for COVID. In our study, we used a measure of neighborhood social distancing as a proxy for the importance the neighborhood places on public health measures designed to keep individuals from contracting the virus. Further, social distancing in this manner could lead to social isolation, a known risk factor for child maltreatment (Younas & Gutman, [<reflink idref="bib81" id="ref69">81</reflink>]) as smaller activity spaces (where people spend their time during the course of a day) are related to more frequent use of punitive parenting (Freisthler et al., [<reflink idref="bib25" id="ref70">25</reflink>]). Finally, parents who use non-punitive discipline practices frequently are more likely to use punitive strategies as well (Straus et al., [<reflink idref="bib74" id="ref71">74</reflink>]), which may indicate an over-reactive parenting style (Rhoades & O'Leary, [<reflink idref="bib65" id="ref72">65</reflink>]). Parents with certain characteristics (e.g., alcohol use in the past year) may be more likely to engage in all types of discipline while parenting (Freisthler & Kepple, [<reflink idref="bib22" id="ref73">22</reflink>]).</p> <p>Graph: Fig. 1 Conceputual model showing key study variables in the ecological transactional systems and environmental stress models*</p> <p>The present study explored how spending time outside the home would relate to parenting behaviors. There are two research questions that were addressed. (<reflink idref="bib1" id="ref74">1</reflink>) What individual characteristics or social influences were related to the time a parent spent away from home (measured daily) during the initial COVID-19 stay-at-home orders in Ohio? We hypothesized that individuals living in neighborhoods with higher levels of social distancing will themselves spend less time outside of the home, as an assessment of the cultural values and beliefs they hold related to community care. (<reflink idref="bib2" id="ref75">2</reflink>) How did daily time away from home controlling for other individual characteristics (including daily stress) affect use of punitive and non-punitive parenting? We hypothesized that spending time away from home will be related to less punitive and non-punitive parenting. Higher at-the-moment stress, perceived stress and neighborhood social distancing would be positively related to punitive and non-punitive parenting. We do not measure other parenting strategies (e.g., positive or active parenting).</p> <hd id="AN0186677917-9">Materials and Methods</hd> <p></p> <hd id="AN0186677917-10">Study Design</hd> <p>We conducted a longitudinal geographic Ecological Momentary Assessment (gEMA) during April through May 2020, during the initial stay-at-home orders in Ohio. Participants were recruited via social media sites (e.g., Facebook) and word of mouth. Those interested in participating in the study could send an email to the study email address and complete a short screening survey assessing eligibility. We then contacted the parent or caregiver to explain the study and obtain verbal informed consent, if eligible. Individuals were eligible if they lived in a seven-county area in Central Ohio, were 18 years or older, were parent or primary caregiver for a child aged 2 to 12 years who lived with them at least 50% of the time, spoke English, and had a smart phone. In this study, we only included individuals who lived in Franklin County, Ohio due to availability of SafeGraph data. If a parent had more than one child in the targeted age range, the parent was asked to identify the child with the most recent birthday. That became the focal child for the parenting questions described below. Participation consisted of three parts: (<reflink idref="bib1" id="ref76">1</reflink>) online baseline survey; (<reflink idref="bib2" id="ref77">2</reflink>) EMA with three brief daily surveys at 10 a.m., 3 p.m., and 9 p.m. for 14 days (for a total of 42 surveys); and (<reflink idref="bib3" id="ref78">3</reflink>) geotracking via their cell phone for the 14 days of the EMA. Parents received up to $150 depending on the level of their participation. The online baseline survey was administered via Qualtrics. It took approximately 45 min to complete and parents received $50. The MetricWire app was used via cell phone to push EMAs to participants daily and enable continuous geotracking. Each EMA took less than three minutes to complete. Participants received $1 for each EMA completed and an additional $2 if they completed all three surveys on a given day (for a total of $70). Those who completed over 90% of daily surveys earned $10. An additional $20 could be earned if geotracking was enabled during the course of the study. The study procedures were approved by the Institutional Review Board at the Ohio State University.</p> <hd id="AN0186677917-11">Sample</hd> <p>We had 629 people complete the screening survey. Of those 479 were eligible to participate, 342 consented to participate in the study, 332 completed at least one study activity, and 329 of those participated all three study activities. This study only included the 245 participants whose home address was in Franklin County, due to the availability of SafeGraph data (described later). Figure 2 shows recruitment throughout the phases of the study.</p> <p>Graph: Fig. 2 Flow diagram of recruitment and participation in phases of the study</p> <hd id="AN0186677917-12">Measures</hd> <p>For our first research question, the dependent variable was the daily proportion of time the participant spent away from home. Geotracking data (GPS latitudes, longitudes, accuracies, and timestamps) from participants' phones were continuously collected through the MetricWire app, providing billions of trace points across the entire study. To identify time periods spent at home, we created buffers around geocoded home addresses that participants provided in the baseline survey with a variable 30 to 45 m radius depending on a property size. Traces that stem out and back into home buffers were used to obtain timestamps for leaving and returning home and estimated daily portion of time spent outside for each participant. Several considerations were made to account for non-reliable or missing data. First, we removed outlier coordinates with poor accuracies over 40 m. Second, three participants had several missing daily estimates as they conducted multi-day trips outside of the Central Ohio. Overall, thirty-one participants were not included in the calculation of the variable due to partial or completely missing daily geotracking records. The remainder of participants had up to 14 daily measures of time spent inside their home corresponding to the days they completed the EMA. We calculated time spent in the home using the x,y coordinates located within the specified radii and date/time stamp information. Participants had up to 14 daily measures of time spent inside their home corresponding to the days they completed the EMA.</p> <p>Punitive and non-punitive parenting behaviors from the Dimensions of Discipline (Straus & Fauchier, [<reflink idref="bib73" id="ref79">73</reflink>]) were the dependent variables for our second research question. Thirteen questions reflected the use of punitive parenting (e.g., shout or yell at the focal child) and thirteen described non-punitive parenting (e.g., praise the child for behaving well). Two punitive and two non-punitive behaviors were asked as part of the thrice daily EMAs. These parenting items were randomized into 42 question blocks. Those question blocks were then randomized within the MetricWire app so participants were not getting the same questions at the same time/day combination. Parents who responded that they had been with their child since the last assessment period would receive one of the 42 questions blocks that contained four parenting items and selected any of the behaviors they had used.</p> <p>We included a dichotomous variable that indicated whether a participant was working outside of the home during the timeframe when they were completing EMAs as an independent variable for our first research question. We identified those working outside the home through an item on the baseline survey that asked for the address or cross streets for their work location. These items were then geocoded to the address or cross streets. We then used the geotracking data to determine if participants went to those locations during the study period. Parents who had a work location but did not have evidence of going to that place during the study period were identified as not working outside of the home. We considered someone "at work" if they spent at least one hour on a given day at their work location.</p> <p>We included a measure of neighborhood "social distancing" to assess how compliant a parent's neighborhood has been in regards to SAH orders. These data were obtained by SafeGraph, Inc. To estimate the number of people who stayed at home each day, the number of mobile devices that were completely at home was divided by the total number of devices in each census block group (CBG) in Franklin County, Ohio (i.e., completely home device count divided by the device count) (Barboza et al., [<reflink idref="bib6" id="ref80">6</reflink>]). This occurred because SafeGraph, Inc. (Safegraph, Inc., 2020) collected device visit information on "places of interest" (POI) like parks, alcohol outlets and grocery stores from GPS pings of tens of millions of mobile devices. This information was then aggregated by Safegraph at the level of the Census Block Group for both the origination location and the destination location and released for free to researchers during the COVID-19 pandemic to gain insight into policy responses to stay-at-home mandates. SafeGraph defined the proportion of devices near homes as the number of devices detected in their home Census block group (destination CBG = origin census block group) divided by the number of devices associated with the CBG (device count). Higher values indicated that CBG residents spent more time at home during SAH orders. We also used this measure as an independent variable in our second research question.</p> <p>Other variables included in the analysis of time spent outside the home included demographic information about the parent: gender (male or female), age (in years), marital status (married and living in a marriage-like relationship or single, divorced, widowed), education (less than college degree, bachelor's degree, or graduate degree), and employment (full-time or part-time/no outside work). Child characteristics included gender (male or female), child age (in years) and race (White or non-White). Family characteristics included the number of children and the number of adults living in the household. We also included an indicator to determine which day (1 to 14) of the EMA the participant was completing.</p> <p>Our second research question focused on whether time spent outside the home during SAH orders was related to parent discipline practices. We included as a covariate a measure of situational stress completed during each EMA. We used a 1-item measure asking parents their level of stress since the last assessment on a scale of 1 to 10, where 1 is no stress and 10 indicates very stressed. This one item correlated highly with the Perceived Stress Scale (American Psychological Association, [<reflink idref="bib3" id="ref81">3</reflink>]). Parents were asked where they completed the survey with 88.7% noting that they were at home at the time they were completing the assessment. Time of day refers to the time the EMA was sent (10 a.m., 3 p.m., and 9 p.m.). We included the daily measures of the time spent outside the home and the day of EMA completion (1 to 14). We included the same parent and child characteristics as described above. We also included a measure of global stress obtained during the baseline survey. The Perceived Stress Scale contained 10 items developed to understand how uncontrollable or unpredictable a person's life was (Cohen et al., [<reflink idref="bib15" id="ref82">15</reflink>]). The five response options for the scale were "never," "almost never," "sometimes," "fairly often," and "often." The items were reverse coded, when needed, and summed. Internal consistency for our data was excellent (α = 0.90).</p> <hd id="AN0186677917-13">Statistical Analysis</hd> <p>We conducted bivariate statistics to assess whether those cases with missing data are different from those without. The primary reason for missing data was incomplete or no geotracking data. We used chi-square and t-tests to assess missingness across our demographic variables.</p> <p>Our first research question sought to understand what characteristics of parents are related to spending time outside the home during the early stages of the COVID-19 pandemic. Our dependent variable was the proportion of time an individual spent outside the home. We analyzed our data using hierarchical linear modeling with days nested within individuals. Hierarchical modeling allowed us to adjust for the intraclass correlations due to the clustering of time points within the same individual. This was a two-level model of days (from 1 to 14) nested within individuals.</p> <p>We used a three-level multilevel logistic model to assess how time spent outside the home was related to use of discipline by parents that addressed issues of intraclass correlations due to clustering of daily geotracking assessments and clustering of timepoints within individuals. Level 1 variables included punitive and non-punitive parenting behaviors and levels of stress that were assessed three times a day, nested within days (Level 2) that included the ratio of time spent inside and the day of their EMA (1 to 14). Level 3 included characteristics of the participants, the focal child, and the family.</p> <hd id="AN0186677917-14">Results</hd> <p>Participant Demographics. The parents in our sample were primarily female (92.9%), married (86.2%) and having at least a college degree (79%). They had been with their focal child since the last assessment period in about 76.3% of the EMA periods. Parents reported using punitive discipline in about 6.9% of EMA time periods and non-punitive parenting in almost half of EMA periods. The average caregiver stress level was 3.3 (on a 10-point scale). Slightly more male children were included in the sample (57.6%) and children were 5.9 years on average. The household had an average of 2.1 children and 1.9 adults. Parents spent an average of approximately two hours away from home each day (Table 1).</p> <p>Table 1 Descriptive statistics for study variables</p> <p> <ephtml> <table frame="hsides" rules="groups"><thead><tr><th align="left" /><th align="left"><p>% or M (SD)</p></th><th align="left"><p>n</p></th></tr></thead><tbody><tr><td align="left"><p><italic>Near real time characteristics</italic></p></td><td align="left" /><td char="." align="char" /></tr><tr><td align="left"><p>Punitive parenting</p></td><td align="left" /><td char="." align="char" /></tr><tr><td align="left"><p> Yes</p></td><td align="left"><p>6.9</p></td><td char="." align="char"><p>539</p></td></tr><tr><td align="left"><p> No</p></td><td align="left"><p>93.1</p></td><td char="." align="char"><p>7313</p></td></tr><tr><td align="left"><p>Non-punitive parenting</p></td><td align="left" /><td char="." align="char" /></tr><tr><td align="left"><p> Yes</p></td><td align="left"><p>47.1</p></td><td char="." align="char"><p>3701</p></td></tr><tr><td align="left"><p> No</p></td><td align="left"><p>52.9</p></td><td char="." align="char"><p>4151</p></td></tr><tr><td align="left"><p>Stress</p></td><td align="left"><p>3.3 (2.2)</p></td><td char="." align="char"><p>7852</p></td></tr><tr><td align="left"><p>Location when completing EMA</p></td><td align="left" /><td char="." align="char" /></tr><tr><td align="left"><p> At home</p></td><td align="left"><p>88.7</p></td><td char="." align="char"><p>6964</p></td></tr><tr><td align="left"><p> Outside the home</p></td><td align="left"><p>11.3</p></td><td char="." align="char"><p>887</p></td></tr><tr><td align="left"><p>Time of day</p></td><td align="left" /><td char="." align="char" /></tr><tr><td align="left"><p> 10 a.m. assessment</p></td><td align="left"><p>33.4</p></td><td char="." align="char"><p>2624</p></td></tr><tr><td align="left"><p> 3 p.m. assessment</p></td><td align="left"><p>32.1</p></td><td char="." align="char"><p>2519</p></td></tr><tr><td align="left"><p> 9 p.m. assessment</p></td><td align="left"><p>34.5</p></td><td char="." align="char"><p>2709</p></td></tr><tr><td align="left"><p><italic>Daily characteristics</italic></p></td><td align="left" /><td char="." align="char" /></tr><tr><td align="left"><p>Time spent away from home</p></td><td align="left"><p>0.08 (0.12)</p></td><td char="." align="char"><p>2925</p></td></tr><tr><td align="left"><p>Social distancing (neighborhood)</p></td><td align="left"><p>0.43 (0.06)</p></td><td char="." align="char"><p>2925</p></td></tr><tr><td align="left"><p><italic>Individual characteristics</italic></p></td><td align="left" /><td char="." align="char" /></tr><tr><td align="left"><p>Parent age</p></td><td align="left"><p>37.3 (5.4)</p></td><td char="." align="char"><p>209</p></td></tr><tr><td align="left"><p>Parent/caregiver gender</p></td><td align="left" /><td char="." align="char" /></tr><tr><td align="left"><p> Female</p></td><td align="left"><p>92.9</p></td><td char="." align="char"><p>195</p></td></tr><tr><td align="left"><p> Male</p></td><td align="left"><p>7.1</p></td><td char="." align="char"><p>15</p></td></tr><tr><td align="left"><p>Marital status</p></td><td align="left" /><td char="." align="char" /></tr><tr><td align="left"><p> Married or living in a marriage-like relationship</p></td><td align="left"><p>86.2</p></td><td char="." align="char"><p>181</p></td></tr><tr><td align="left"><p> Single, married, or divorced</p></td><td align="left"><p>13.8</p></td><td char="." align="char"><p>29</p></td></tr><tr><td align="left"><p>Education</p></td><td align="left" /><td char="." align="char" /></tr><tr><td align="left"><p> < Bachelor's degree</p></td><td align="left"><p>21.0</p></td><td char="." align="char"><p>62</p></td></tr><tr><td align="left"><p> Bachelor's degree</p></td><td align="left"><p>33.8</p></td><td char="." align="char"><p>41</p></td></tr><tr><td align="left"><p> Advanced degree</p></td><td align="left"><p>45.2</p></td><td char="." align="char"><p>107</p></td></tr><tr><td align="left"><p>Employment status</p></td><td align="left" /><td char="." align="char" /></tr><tr><td align="left"><p> Not employed, retired, stay-at-home parent</p></td><td align="left"><p>29.5</p></td><td char="." align="char"><p>62</p></td></tr><tr><td align="left"><p> Part-time</p></td><td align="left"><p>19.5</p></td><td char="." align="char"><p>41</p></td></tr><tr><td align="left"><p> Full time</p></td><td align="left"><p>51.0</p></td><td char="." align="char"><p>107</p></td></tr><tr><td align="left"><p>Child gender</p></td><td align="left" /><td char="." align="char" /></tr><tr><td align="left"><p> Female</p></td><td align="left"><p>42.4</p></td><td char="." align="char"><p>89</p></td></tr><tr><td align="left"><p> Male</p></td><td align="left"><p>57.6</p></td><td char="." align="char"><p>121</p></td></tr><tr><td align="left"><p>Child age</p></td><td align="left"><p>5.9 (2.9)</p></td><td char="." align="char"><p>210</p></td></tr><tr><td align="left"><p>Child race</p></td><td align="left" /><td char="." align="char" /></tr><tr><td align="left"><p> White or Caucasian</p></td><td align="left"><p>74.3</p></td><td char="." align="char"><p>156</p></td></tr><tr><td align="left"><p> People of color</p></td><td align="left"><p>25.7</p></td><td char="." align="char"><p>54</p></td></tr><tr><td align="left"><p>Number of children</p></td><td align="left"><p>2.1 (0.8)</p></td><td char="." align="char"><p>210</p></td></tr><tr><td align="left"><p>Number of adults</p></td><td align="left"><p>1.9 (0.4)</p></td><td char="." align="char"><p>210</p></td></tr><tr><td align="left"><p>Perceived stress scale</p></td><td align="left"><p>19.6 (6.5)</p></td><td char="." align="char"><p>209</p></td></tr></tbody></table> </ephtml> </p> <hd id="AN0186677917-15">Missing Data Analysis</hd> <p>Using a chi-square analysis in our assessment of differences between participants with and without missing data, there was not a significant relationship between participants with missing data and gender (<emph>X</emph><sups><emph>2</emph></sups>(<reflink idref="bib1" id="ref83">1</reflink>, N = 245) = 0.09, p = 0.764), marital status (<emph>X</emph><sups><emph>2</emph></sups>(<reflink idref="bib1" id="ref84">1</reflink>, N = 245) = 3.24, p = 0.072), employment status (<emph>X</emph><sups><emph>2</emph></sups>(<reflink idref="bib2" id="ref85">2</reflink>, N = 245) = 1.00, p = 0.608), educational attainment (<emph>X</emph><sups><emph>2</emph></sups>(<reflink idref="bib2" id="ref86">2</reflink>, N = 245) = 0.86, p = 0.651), having a male focal child (<emph>X</emph><sups><emph>2</emph></sups>(<reflink idref="bib1" id="ref87">1</reflink>, N = 245) = 0.47, p = 0.494), and child race (<emph>X</emph><sups><emph>2</emph></sups>(<reflink idref="bib1" id="ref88">1</reflink>, N = 245) = 1.12, p = 0.290. There was no significant difference by parent age, <emph>t</emph>(<reflink idref="bib242" id="ref89">242</reflink>) = 1.2, <emph>p</emph> = 0.254, where those with missing data were slightly older (<emph>M</emph> = 38.9, <emph>SD</emph> = 8.4) than those without (<emph>M</emph> = 37.2, <emph>SD</emph> = 5.5), or focal child age, <emph>t</emph>(<reflink idref="bib241" id="ref90">241</reflink>) = -0.48, <emph>p</emph> = 0.630, where those missing geotracking data were 6.7 years (<emph>SD</emph> = 3.06) compared to 5.9 years (<emph>SD</emph> = 2.9) for those with missing data. On average, families with missing data had 2.2 children (SD = 1.2), slightly higher than those without missing data (M = 2.1, SD = 0.8), but this was not significantly different, <emph>t</emph>(<reflink idref="bib243" id="ref91">243</reflink>) = -0.65, <emph>p</emph> = 0.519. The number of adults was also similar at 2.1 (SD = 1.0) for those missing data and 1.9 (SD = 0.43) for those without, <emph>t</emph>(<reflink idref="bib243" id="ref92">243</reflink>) = 0.56, <emph>p</emph> = 0.398.</p> <hd id="AN0186677917-16">Time Away from Home</hd> <p>Employment outside the home was related to spending more time outside the home (Table 2). The more social distancing in a neighborhood, the less time a parent spent outside the home. With regards to sociodemographics, older and married parents spent less time outside the home. Being employed with full or part-time (compared to unemployed or not employed) was related to more time outside the home. Having more adults in the home was related to more time spent outside the home.</p> <p>Table 2 Multilevel linear model of the relationship between sociodemographic variables and time spent outside the home during the COVID-19 pandemic</p> <p> <ephtml> <table frame="hsides" rules="groups"><thead><tr><th align="left" /><th align="left"><p>B</p></th><th align="left"><p>SE</p></th><th align="left"><p><italic>p</italic></p></th></tr></thead><tbody><tr><td align="left"><p>Intercept</p></td><td char="." align="char"><p>0.128</p></td><td char="." align="char"><p>0.016</p></td><td char="." align="char"><p> < 0.001</p></td></tr><tr><td align="left"><p><italic>Daily characteristics (Level 1, n = 2669)</italic></p></td><td char="." align="char" /><td char="." align="char" /><td char="." align="char" /></tr><tr><td align="left"><p>Day of survey (1 to 14)</p></td><td char="." align="char"><p>0.001</p></td><td char="." align="char"><p>0.0004</p></td><td char="." align="char"><p>0.232</p></td></tr><tr><td align="left"><p>Social distancing (neighborhood)</p></td><td char="." align="char"><p>− 0.126</p></td><td char="." align="char"><p>0.034</p></td><td char="." align="char"><p> < 0.001</p></td></tr><tr><td align="left"><p>Work outside the home > 1 h</p></td><td char="." align="char"><p>0.072</p></td><td char="." align="char"><p>0.293</p></td><td char="." align="char"><p>0.014</p></td></tr><tr><td align="left"><p><italic>Individual characteristics (Level 2, n = 207)</italic></p></td><td char="." align="char" /><td char="." align="char" /><td char="." align="char" /></tr><tr><td align="left"><p>Female caregiver</p></td><td char="." align="char"><p>− 0.022</p></td><td char="." align="char"><p>0.025</p></td><td char="." align="char"><p>0.380</p></td></tr><tr><td align="left"><p>Parent age</p></td><td char="." align="char"><p>− 0.002</p></td><td char="." align="char"><p>0.001</p></td><td char="." align="char"><p>0.023</p></td></tr><tr><td align="left"><p>Marital status (reference: single, widowed, divorced)</p></td><td char="." align="char" /><td char="." align="char" /><td char="." align="char" /></tr><tr><td align="left"><p> Married or living in a marriage-like relationship</p></td><td char="." align="char"><p>− 0.078</p></td><td char="." align="char"><p>0.019</p></td><td char="." align="char"><p> < 0.001</p></td></tr><tr><td align="left"><p>Education (reference: < Bachelor's degree)</p></td><td char="." align="char" /><td char="." align="char" /><td char="." align="char" /></tr><tr><td align="left"><p> Bachelor's degree</p></td><td char="." align="char"><p>− 0.001</p></td><td char="." align="char"><p>0.012</p></td><td char="." align="char"><p>0.939</p></td></tr><tr><td align="left"><p> Advanced degree</p></td><td char="." align="char"><p>− 0.003</p></td><td char="." align="char"><p>0.012</p></td><td char="." align="char"><p>0.832</p></td></tr><tr><td align="left"><p>Male child</p></td><td char="." align="char"><p>0.004</p></td><td char="." align="char"><p>0.008</p></td><td char="." align="char"><p>0.583</p></td></tr><tr><td align="left"><p>Child age</p></td><td char="." align="char"><p>0.0003</p></td><td char="." align="char"><p>0.002</p></td><td char="." align="char"><p>0.837</p></td></tr><tr><td align="left"><p>Child race (reference: people of color)</p></td><td char="." align="char" /><td char="." align="char" /><td char="." align="char" /></tr><tr><td align="left"><p> White or Caucasian</p></td><td char="." align="char"><p>0.004</p></td><td char="." align="char"><p>0.011</p></td><td char="." align="char"><p>0.715</p></td></tr><tr><td align="left"><p>Number of children</p></td><td char="." align="char"><p>0.001</p></td><td char="." align="char"><p>0.005</p></td><td char="." align="char"><p>0.868</p></td></tr><tr><td align="left"><p>Number of adults</p></td><td char="." align="char"><p>0.066</p></td><td char="." align="char"><p>0.013</p></td><td char="." align="char"><p> < 0.001</p></td></tr><tr><td align="left"><p>Employment (reference: unemployed or not employed))</p></td><td char="." align="char" /><td char="." align="char" /><td char="." align="char" /></tr><tr><td align="left"><p> Full-time employment</p></td><td char="." align="char"><p>0.024</p></td><td char="." align="char"><p>0.009</p></td><td char="." align="char"><p>0.010</p></td></tr><tr><td align="left"><p> Part-time employment</p></td><td char="." align="char"><p>0.029</p></td><td char="." align="char"><p>0.012</p></td><td char="." align="char"><p>0.013</p></td></tr></tbody></table> </ephtml> </p> <hd id="AN0186677917-17">Punitive and Nonpunitive Parenting</hd> <p>Parents who spent more time away from home had lower odds of using punitive and non-punitive parenting on that day (Table 3). However, neighborhood social distancing was not related to use of punitive or nonpunitive parenting. Higher levels of stress and assessments completed during the 9 p.m. assessment periods were related to higher odds of using nonpunitive discipline. Older children and having part-time employment were related to lower odds of using nonpunitive discipline. With regards to punitive discipline, higher stress levels and parenting behaviors reported at the 9 p.m. EMA were related to higher odds of using punitive discipline. No other covariates were related to punitive parenting.</p> <p>Table 3 Multilevel logistic model of relationship of time spend outside the home and parenting behaviors during COVID-19</p> <p> <ephtml> <table frame="hsides" rules="groups"><thead><tr><th align="left" rowspan="2" /><th align="left" colspan="3"><p>Non-punitive parenting</p></th><th align="left" colspan="3"><p>Punitive parenting</p></th></tr><tr><th align="left"><p>OR</p></th><th align="left"><p>95% CI</p></th><th align="left"><p><italic>p</italic></p></th><th align="left"><p>OR</p></th><th align="left"><p>95% CI</p></th><th align="left"><p><italic>p</italic></p></th></tr></thead><tbody><tr><td align="left"><p>Intercept</p></td><td char="." align="char"><p>0.682</p></td><td align="left"><p>(0.536, 0.867)</p></td><td char="." align="char"><p>0.002</p></td><td char="." align="char"><p>0.003</p></td><td align="left"><p>(0.002, 0.007)</p></td><td char="." align="char"><p> < 0.001</p></td></tr><tr><td align="left"><p><italic>Near real-time characteristics (Level, n = 7121)</italic></p></td><td char="." align="char" /><td align="left" /><td char="." align="char" /><td char="." align="char" /><td align="left" /><td char="." align="char" /></tr><tr><td align="left"><p>Stress</p></td><td char="." align="char"><p>1.061</p></td><td align="left"><p>(1.027, 1.096)</p></td><td char="." align="char"><p> < 0.001</p></td><td char="." align="char"><p>1.500</p></td><td align="left"><p>(1.369, 1.644)</p></td><td char="." align="char"><p> < 0.001</p></td></tr><tr><td align="left"><p>At home</p></td><td char="." align="char"><p>0.943</p></td><td align="left"><p>(0.784, 1.135)</p></td><td char="." align="char"><p>0.990</p></td><td char="." align="char"><p>0.830</p></td><td align="left"><p>(0.474, 1.452)</p></td><td char="." align="char"><p>0.513</p></td></tr><tr><td align="left"><p>Time of day (reference: 10 a.m.)</p></td><td char="." align="char" /><td align="left" /><td char="." align="char" /><td char="." align="char" /><td align="left" /><td char="." align="char" /></tr><tr><td align="left"><p> 3 p.m. assessment</p></td><td char="." align="char"><p>1.119</p></td><td align="left"><p>(0.990, 1.265)</p></td><td char="." align="char"><p>0.053</p></td><td char="." align="char"><p>1.334</p></td><td align="left"><p>(0.956, 1.862)</p></td><td char="." align="char"><p>0.090</p></td></tr><tr><td align="left"><p> 9 p.m. assessment</p></td><td char="." align="char"><p>1.201</p></td><td align="left"><p>(1.046, 1.379)</p></td><td char="." align="char"><p>0.012</p></td><td char="." align="char"><p>1.938</p></td><td align="left"><p>(1.378, 2.726)</p></td><td char="." align="char"><p> < 0.001</p></td></tr><tr><td align="left"><p><italic>Daily characteristics (Level 2, n = 2659)</italic></p></td><td char="." align="char" /><td align="left" /><td char="." align="char" /><td char="." align="char" /><td align="left" /><td char="." align="char" /></tr><tr><td align="left"><p>Time spent away from home</p></td><td char="." align="char"><p>0.350</p></td><td align="left"><p>(0.198, 0.619)</p></td><td char="." align="char"><p> < 0.001</p></td><td char="." align="char"><p>0.217</p></td><td align="left"><p>(0.059, 0.799)</p></td><td char="." align="char"><p>0.022</p></td></tr><tr><td align="left"><p>Social distancing (neighborhood)</p></td><td char="." align="char"><p>1.178</p></td><td align="left"><p>(0.457, 3.038)</p></td><td char="." align="char"><p>0.734</p></td><td char="." align="char"><p>0.224</p></td><td align="left"><p>(0.018, 2.780)</p></td><td char="." align="char"><p>0.244</p></td></tr><tr><td align="left"><p>Day of study (1–14)</p></td><td char="." align="char"><p>0.989</p></td><td align="left"><p>(0.974, 1.003)</p></td><td char="." align="char"><p>0.125</p></td><td char="." align="char"><p>1.021</p></td><td align="left"><p>(0.989, 1.055)</p></td><td char="." align="char"><p>0.195</p></td></tr><tr><td align="left"><p><italic>Individual characteristics (Level 3, n = 206)</italic></p></td><td char="." align="char" /><td align="left" /><td char="." align="char" /><td char="." align="char" /><td align="left" /><td char="." align="char" /></tr><tr><td align="left"><p>Female caregiver</p></td><td char="." align="char"><p>0.916</p></td><td align="left"><p>(0.481, 1.744)</p></td><td char="." align="char"><p>0.787</p></td><td char="." align="char"><p>0.689</p></td><td align="left"><p>(0.311, 1.524)</p></td><td char="." align="char"><p>0.355</p></td></tr><tr><td align="left"><p>Parent age</p></td><td char="." align="char"><p>0.991</p></td><td align="left"><p>(0.969, 1.013)</p></td><td char="." align="char"><p>0.406</p></td><td char="." align="char"><p>0.966</p></td><td align="left"><p>(0.924, 1.009)</p></td><td char="." align="char"><p>0.115</p></td></tr><tr><td align="left"><p>Married or living in a marriage-like relationship</p></td><td char="." align="char"><p>0.713</p></td><td align="left"><p>(0.490, 1.037)</p></td><td char="." align="char"><p>0.076</p></td><td char="." align="char"><p>1.310</p></td><td align="left"><p>(0.596, 2.878)</p></td><td char="." align="char"><p>0.500</p></td></tr><tr><td align="left"><p>Education (reference: < Bachelor's degree)</p></td><td char="." align="char" /><td align="left" /><td char="." align="char" /><td char="." align="char" /><td align="left" /><td char="." align="char" /></tr><tr><td align="left"><p> Bachelor's degree</p></td><td char="." align="char"><p>0.879</p></td><td align="left"><p>(0.626, 1.235)</p></td><td char="." align="char"><p>0.456</p></td><td char="." align="char"><p>0.985</p></td><td align="left"><p>(0.561, 1.731)</p></td><td char="." align="char"><p>0.958</p></td></tr><tr><td align="left"><p> Advanced degree</p></td><td char="." align="char"><p>0.860</p></td><td align="left"><p>(0.599, 1.234)</p></td><td char="." align="char"><p>0.410</p></td><td char="." align="char"><p>0.728</p></td><td align="left"><p>(0.403, 1.316)</p></td><td char="." align="char"><p>0.291</p></td></tr><tr><td align="left"><p>Employment (reference: Unemployed or not employed))</p></td><td char="." align="char" /><td align="left" /><td char="." align="char" /><td char="." align="char" /><td align="left" /><td char="." align="char" /></tr><tr><td align="left"><p> Full-time employment</p></td><td char="." align="char"><p>0.979</p></td><td align="left"><p>(0.738, 1.299)</p></td><td char="." align="char"><p>0.881</p></td><td char="." align="char"><p>0.976</p></td><td align="left"><p>(0.586, 1.625)</p></td><td char="." align="char"><p>0.926</p></td></tr><tr><td align="left"><p> Part-time employment</p></td><td char="." align="char"><p>0.694</p></td><td align="left"><p>(0.511, 0.943)</p></td><td char="." align="char"><p>0.020</p></td><td char="." align="char"><p>0.562</p></td><td align="left"><p>(0.314, 1.006)</p></td><td char="." align="char"><p>0.052</p></td></tr><tr><td align="left"><p>Male child</p></td><td char="." align="char"><p>0.970</p></td><td align="left"><p>(0.769, 1.225)</p></td><td char="." align="char"><p>0.801</p></td><td char="." align="char"><p>1. 473</p></td><td align="left"><p>(0.964, 2.251)</p></td><td char="." align="char"><p>0.073</p></td></tr><tr><td align="left"><p>Child age</p></td><td char="." align="char"><p>0.897</p></td><td align="left"><p>(0.855, 0.940)</p></td><td char="." align="char"><p> < 0.001</p></td><td char="." align="char"><p>1.056</p></td><td align="left"><p>(0.963, 1.158)</p></td><td char="." align="char"><p>0.242</p></td></tr><tr><td align="left"><p>Child race (reference: people of color)</p></td><td char="." align="char" /><td align="left" /><td char="." align="char" /><td char="." align="char" /><td align="left" /><td char="." align="char" /></tr><tr><td align="left"><p> White or Caucasian</p></td><td char="." align="char"><p>1.052</p></td><td align="left"><p>(0.807, 1.372)</p></td><td char="." align="char"><p>0.706</p></td><td char="." align="char"><p>1.197</p></td><td align="left"><p>(0.725, 1.976)</p></td><td char="." align="char"><p>0.479</p></td></tr><tr><td align="left"><p>Perceived stress scale</p></td><td char="." align="char"><p>0.999</p></td><td align="left"><p>(0.980, 1.019)</p></td><td char="." align="char"><p>0.924</p></td><td char="." align="char"><p>1.021</p></td><td align="left"><p>(0.988, 1.055)</p></td><td char="." align="char"><p>0.210</p></td></tr></tbody></table> </ephtml> </p> <hd id="AN0186677917-18">Discussion</hd> <p>This study examined individual characteristics associated with time spent outside of the home and parenting behaviors amongst a sample of parents of young children in one county in Ohio at the beginning of the COVID-19 pandemic. Our study was novel in that we are able to use geotracking data to assess time outside of the home during the period vs. self-reported adherence to shelter at home policies. We also examined whether the behaviors of those in neighborhoods influenced the time parents spent outside or their parenting behaviors.</p> <p>We identified several characteristics associated with spending time outside of the home. Not surprisingly, employment status and time spent at a workplace were related to spending time away from home. Many of these parents may have been essential workers, who were thus exempt from SAH orders and required to work outside of the home. In addition, older parents were less likely to spend time outside of the home. These parents may have had heightened concerns about potential ramifications of COVID-19 on their overall health which kept them indoors (Pasion et al., [<reflink idref="bib61" id="ref93">61</reflink>]; Rosi et al., [<reflink idref="bib68" id="ref94">68</reflink>]). Paradoxically, more adults in the family were positively related to time spent away from home, but being married was negatively related to time spend away from home. Our finding related to marriage differs from previous work finding that more single parents in a neighborhood was related to lower rates of social distancing (Fu & Zhai, [<reflink idref="bib26" id="ref95">26</reflink>]). As our sample was primarily women, we could be capturing a gender effect, whereby married women may have been more likely to stay at home than their partner. Parents might have also designated one parent in the family to do errands or spent time outside of the home to reduce risk of contracting the virus. We did not find differences in the amount of time spent away from home by education, race/ethnicity or gender, in contrast to other studies who did find relationships (Andersen, [<reflink idref="bib4" id="ref96">4</reflink>]; Huang et al., [<reflink idref="bib34" id="ref97">34</reflink>]; Pedersen & Favero, [<reflink idref="bib62" id="ref98">62</reflink>]).</p> <p>In addition to these individual characteristics, we identified that parents who lived in a neighborhood with more SAH adherence spent less time away from home. Parents may have been influenced by the social norm around them and not want to be seen as "the only people on the block" spending significant time outside or away from home. This suggests that community-based interventions may be effective in establishing public health norms for parents, in particular.</p> <p>We found several factors associated with punitive and nonpunitive discipline for parents, particularly in the microsystem. In support of our hypothesis, more time away from home was associated with decreased odds of parents using both punitive and nonpunitive discipline with the focal child. There may be several reasons for this finding. Using more of all types of discipline strategies may indicate a specific style of parenting (e.g., overreactive) that focuses on correcting a child when they are perceived to have misbehaved (Rhoades & O'Leary, [<reflink idref="bib65" id="ref99">65</reflink>]). Given the cataclysmic stress of the COVID-19 pandemic, parents who would normally engage in more positive parenting strategies may have relied more heavily on all types of discipline to try to reduce interruptions to online learning or remote work. A routine change that takes the parent or family outside the home may be enough to provide a bit of respite for parents who often were working while also supervising their children and their virtual schooling. If that time away from home happened to include activities in parks or playgrounds, it may have the added benefit of lowering stress and keeping children physically active (Cindrich et al., [<reflink idref="bib14" id="ref100">14</reflink>]; Young et al., [<reflink idref="bib82" id="ref101">82</reflink>]). Parents who are physically at their work location, even for a short time, may be more mindful of their parenting when they do return home. Being away from home during the day also means less time in which to discipline your children. The reverse of this finding suggests that parents who remain home during emergencies or other stressful cataclysmic events may be at higher risk of using more discipline-based parenting and in need of additional support. To be clear, we do not know what parents were doing, where they were, or who they were with when they spent time away from home. Parents may be alone picking up groceries, conducting paid work elsewhere (for those who had to leave home for work), or with their children at an outdoor venue, such as a park. That means under some scenarios, parents may have had time away from their children, where this mini parenting respite may have provided them with a boost to use more positive and fewer discipline-based parenting strategies. Thus, we are unable to understand more fine-grained nuances and mechanisms by which time spent away from home might be related to the larger continuum of parenting behaviors or how exactly it was related to lower odds of punitive and nonpunitive discipline in this study.</p> <p>The results for our hypotheses regarding stress were mixed. We found that at-the-moment stress (e.g., daily hassles) appeared to be a larger driver of parenting behaviors during the initial SAH period while perceived stress (e.g., life events) was not related to situational parenting behaviors (Freisthler et al., [<reflink idref="bib24" id="ref102">24</reflink>]). While the exact temporal relationship is unknown (e.g. whether parents are stressed and use punitive discipline or whether they become stressed after using punitive discipline) these findings suggest that periods where stress is increased may be a target for intervention.</p> <p>Neighborhood SAH adherence was not associated with parenting behaviors. We used this variable to assess cataclysmic stress in the macrosystem representing beliefs around community care. Due to its very nature, it was a measure of physical social isolation in the immediate environment. Although other neighborhood influences have been linked to parenting behaviors (Kummer et al., [<reflink idref="bib43" id="ref103">43</reflink>]; Rhoad-Drogalis et al., [<reflink idref="bib64" id="ref104">64</reflink>]), parents during the early months of the pandemic were facing an unprecedented level of social isolation. The lack of relationship with parenting could suggest parents may have used social media to help cope and alleviate social isolation due to cataclysmic COVID-19 stress. Parents frequently used humor to discuss their parenting stress and challenges on social media (Lemish & Elias, [<reflink idref="bib50" id="ref105">50</reflink>]). Parents experiencing higher levels of anxiety during the pandemic were more prone to actively engage with social media more frequently to obtain social and informational support (Drouin et al., [<reflink idref="bib19" id="ref106">19</reflink>]; Wagg et al., [<reflink idref="bib78" id="ref107">78</reflink>]), possibly making them feel less isolated despite complying with physical social distancing requests. This measure may also be an imperfect assessment of beliefs around community care and social isolation.</p> <p>Assessments completed during the 9 p.m. assessment periods had higher odds of punitive and nonpunitive discipline being used. Such association was not found in the other two earlier assessment periods. The parenting questions ask for parenting behaviors "since the last assessment", participants who have skipped one or more EMAs are reporting their parenting practices during a longer time period. With more observation time, both punitive and non-punitive parenting behaviors are more likely to happen, and the stress measurement at the beginning of the EMA may not fully reflect their stress level close to when the parenting behavior happened. The 3 p.m. assessment period had the fewest surveys completed among the three assessment periods, and the 9 p.m. had the most. It could also be that parents are more tired in the evening and thus have less tolerance for children who are acting out, or that children are in particular need of discipline during this period when parents are trying to get them to eat, bathe, and sleep. Our study suggests that these specific time periods matter, and can inform future efforts to further identify temporal relationships and risk.</p> <hd id="AN0186677917-19">Limitations</hd> <p>A major limitation of our study was the lack of diversity in our convenience sample. Our sample was primarily White, middle class, mothers. Thus, the study cannot be generalized to parents of lower socio-economic status, parents of color, and fathers. We used geotracking data to determine when parents were away from their home. We only assessed discipline-based parenting behaviors. We do not include other parenting strategies such as positive or active parenting; therefore, we cannot assess whether spending time away from home is related to those types of parenting behaviors. However, we did not generally look at what parents were doing when they were away from home and whether they were with their children at the time. This limits our ability to identify what activities are more beneficial to reduce punitive and nonpunitive discipline. Days when parents are missing geotracking data may be different from days with complete data. In particular, social desirability may be at play. Parents may turn off geotracking if they know they will be spending a great deal of time outside the home during SAH orders. The MetricWire app does not work well with early versions of Android and requires a decent GPS sensor hardware to collect stable and accurate geotracking data. The geotracking in the background also requires extra processing and battery. Some parents couldn't provide geotracking data due to low disc space or low battery on their phone. If parents were away from home for a long time and battery was low, the app may stop geotracking due to the low battery. The Safegraph data also had limitations. It did not capture devices that are out of service, were not moving, did not have a tracking app, opted out of location services and/or were not linked to a home Census block group (Klise et al., [<reflink idref="bib42" id="ref108">42</reflink>]). Further, the number of total visit counts in any origin Census block groups with a total visit count of less than five but greater than one defaulted to four (even though there may actually be two or three visits).</p> <hd id="AN0186677917-20">Conclusion</hd> <p>We found that parents who spent more time outside had lower odds of using punitive and non-punitive parenting. Factors in the microsystem, including stress due to daily hassles, were more likely to be related to immediate parenting behaviors than stressors in the exosystem or macrosystem. Interventions that seek to support parents "at-the-moment" of higher situational stress might be successful in reducing negative parenting behaviors. One such intervention might be spending time away from the home, such as taking a walk around the block, to alleviate immediate stress. These interventions could use technology (e.g., mobile phones, heart rate sensor) to monitor physiological effects that indicate stress and provide immediate feedback on possible activities to reduce that stress.</p> <p>The response to COVID no longer includes stay-at-home orders; yet this work remains relevant as it allowed us to begin to disentangle types of environmental stress and in what ecological systems this stress may affect parenting. Events such as extreme weather (e.g. freezing temperatures) may lead to conditions where a parent is spending a significant amount of time at home with their children and, in some instances, with little respite. Other situations that may leave a family more homebound, such as having a chronically ill technology-dependent child (Kirk, [<reflink idref="bib41" id="ref109">41</reflink>]) or being a parent with long COVID (Freda et al., [<reflink idref="bib21" id="ref110">21</reflink>]), may benefit from formal opportunities to spend time away from the home or respite from parenting. Time spent away from home during the day was related to less punitive and non-punitive parenting, a finding that may be relevant under different manifestations of stress. Future work could look to determine whether this holds true outside of the pandemic and under what conditions (e.g., spending time in green space vs. spending time at a grocery store) spending time away from home is related to less use of discipline towards children.</p> <hd id="AN0186677917-21">Funding</hd> <p>Funding is provided by Ohio State University through the COVID-19 seed grant program.</p> <hd id="AN0186677917-22">Declarations</hd> <p></p> <hd id="AN0186677917-23">Conflict of interest</hd> <p>The authors declared that they have no conflict of interest.</p> <hd id="AN0186677917-24">Publisher's Note</hd> <p>Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.</p> <ref id="AN0186677917-25"> <title> References </title> <blist> <bibl id="bib1" idref="ref1" type="bt">1</bibl> <bibtext> Alba C, Pan B, Yin J, Rice WL, Mitra P, Lin MS, Liang Y. 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  Data: <searchLink fieldCode="DE" term="%22Parent+Child+Relationship%22">Parent Child Relationship</searchLink><br /><searchLink fieldCode="DE" term="%22COVID-19%22">COVID-19</searchLink><br /><searchLink fieldCode="DE" term="%22Pandemics%22">Pandemics</searchLink><br /><searchLink fieldCode="DE" term="%22School+Closing%22">School Closing</searchLink><br /><searchLink fieldCode="DE" term="%22Ecology%22">Ecology</searchLink><br /><searchLink fieldCode="DE" term="%22Stress+Variables%22">Stress Variables</searchLink><br /><searchLink fieldCode="DE" term="%22Child+Rearing%22">Child Rearing</searchLink><br /><searchLink fieldCode="DE" term="%22Family+Environment%22">Family Environment</searchLink><br /><searchLink fieldCode="DE" term="%22Social+Distance%22">Social Distance</searchLink><br /><searchLink fieldCode="DE" term="%22Neighborhoods%22">Neighborhoods</searchLink><br /><searchLink fieldCode="DE" term="%22Discipline%22">Discipline</searchLink><br /><searchLink fieldCode="DE" term="%22Punishment%22">Punishment</searchLink><br /><searchLink fieldCode="DE" term="%22Probability%22">Probability</searchLink>
– Name: Subject
  Label: Geographic Terms
  Group: Su
  Data: <searchLink fieldCode="DE" term="%22Ohio%22">Ohio</searchLink>
– Name: DOI
  Label: DOI
  Group: ID
  Data: 10.1007/s10566-024-09841-5
– Name: ISSN
  Label: ISSN
  Group: ISSN
  Data: 1053-1890<br />1573-3319
– Name: Abstract
  Label: Abstract
  Group: Ab
  Data: Background: During the COVID-19 pandemic, stay-at-home (SAH) orders were instituted to limit geographic movement of the population and decrease the spread of the virus. Parents made decisions about how to keep themselves and their children safe which may have led to differing compliance with SAH orders and affected parenting. Objective: We assessed characteristics of those more likely to spend time outside the home and how time spent outside the home was related to parental use of discipline behaviors. Method: We conducted a 14-day Ecological Momentary Assessment (gEMA) during April-May 2020 in a convenience sample 245 parents with children 2-12 years old in Ohio. Participants completed the EMA three times a day on stress and parenting behaviors. Geotracking during the 14 days was used to calculate time spent away from home. Data were analyzed using multilevel models. Results: The more social distancing in a neighborhood, the less time a parent spent outside the home. Parents who spent more time away from home had lower odds of using punitive and non-punitive parenting on that day. At-the-moment stress was related to higher odds of using punitive and non-punitive parenting. Conclusions: The response to COVID no longer includes SAH orders; yet this work allowed us to begin to disentangle types of environmental stress and in what ecological systems this stress may affect parenting. Factors in the microsystem, including stress due to daily hassles, were more likely to be related to immediate parenting behaviors than stressors in the exosystem or macrosystem.
– Name: AbstractInfo
  Label: Abstractor
  Group: Ab
  Data: As Provided
– Name: DateEntry
  Label: Entry Date
  Group: Date
  Data: 2025
– Name: AN
  Label: Accession Number
  Group: ID
  Data: EJ1477391
PLink https://search.ebscohost.com/login.aspx?direct=true&site=eds-live&db=eric&AN=EJ1477391
RecordInfo BibRecord:
  BibEntity:
    Identifiers:
      – Type: doi
        Value: 10.1007/s10566-024-09841-5
    Languages:
      – Text: English
    PhysicalDescription:
      Pagination:
        PageCount: 23
        StartPage: 817
    Subjects:
      – SubjectFull: Parent Child Relationship
        Type: general
      – SubjectFull: COVID-19
        Type: general
      – SubjectFull: Pandemics
        Type: general
      – SubjectFull: School Closing
        Type: general
      – SubjectFull: Ecology
        Type: general
      – SubjectFull: Stress Variables
        Type: general
      – SubjectFull: Child Rearing
        Type: general
      – SubjectFull: Family Environment
        Type: general
      – SubjectFull: Social Distance
        Type: general
      – SubjectFull: Neighborhoods
        Type: general
      – SubjectFull: Discipline
        Type: general
      – SubjectFull: Punishment
        Type: general
      – SubjectFull: Probability
        Type: general
      – SubjectFull: Ohio
        Type: general
    Titles:
      – TitleFull: Characteristics of Parents Who Spent Time Away from Home during Stay-at-Home Orders and Relation to Parenting Behaviors in Ohio
        Type: main
  BibRelationships:
    HasContributorRelationships:
      – PersonEntity:
          Name:
            NameFull: Bridget Freisthler
      – PersonEntity:
          Name:
            NameFull: Polina Berezina
      – PersonEntity:
          Name:
            NameFull: Yun Ye
      – PersonEntity:
          Name:
            NameFull: Fatoumata Bah
      – PersonEntity:
          Name:
            NameFull: Balalji Ramesh
      – PersonEntity:
          Name:
            NameFull: Gia Barboza-Salerno
      – PersonEntity:
          Name:
            NameFull: Jennifer Price Wolf
    IsPartOfRelationships:
      – BibEntity:
          Dates:
            – D: 01
              M: 08
              Type: published
              Y: 2025
          Identifiers:
            – Type: issn-print
              Value: 1053-1890
            – Type: issn-electronic
              Value: 1573-3319
          Numbering:
            – Type: volume
              Value: 54
            – Type: issue
              Value: 4
          Titles:
            – TitleFull: Child & Youth Care Forum
              Type: main
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