How unpredictability in the home versus unpredictability in the broader environment affect toddler's socioemotional behaviors

Life history theory suggests that unpredictability in children's environments can shape their development in ways that undermine their socioemotional growth as they move through childhood and later as they become adults. There is a gap in the literature regarding the consequences of unpredictability for young children. It is important to examine the consequences of environmental unpredictability at an early age to develop interventions before more permanent learned behaviors are formed. In addition, environmental unpredictability has multiple definitions, which has caused difficulties creating consistent measurements. Therefore, there is lack of understanding about what types of unpredictability have the strongest impact on toddlers' development. The goal of this study was to address those gaps by examining the extent to which different kinds of unpredictability were associated with children's socioemotional well-being. Approximately 110 mother-toddler dyads were included in the study. Questionnaire measures of unpredictability in the broader environment (measured by changes of residence, mother's relationship status, and changes of residents) unpredictability in the home (measured using the Confusion, Hubbub, and Order Scale), and toddlers' socioemotional well-being (measured using the Infant-Toddler Social Emotional Assessment) were collected when children were 18 months old. Most of the mothers identified as non-Hispanic White, were married, had completed a 4- year college degree, and had household incomes of $50,000 or more. Most of the mother-toddler dyads had minimal unpredictability; therefore, the results can only be generalized to families with low unpredictability. More research must be done for children in environments with high unpredictability such as children in foster or congregate care. Results indicated that unpredictability in the home was positively associated with toddlers' dysregulation and was marginally associated with their externalizing behaviors. In contrast, unpredictability in the broader environment was not significantly associated with toddlers' socioemotional outcomes. These results were consistent with the idea that unpredictability has consequences for young children and suggested that unpredictability in the home may be especially impactful for toddlers' socioemotional well-being. Therefore, interventions for young children struggling with dysregulation may need to focus on the day-to-day unpredictability in their homes.

HOW UNPREDICTABILITY IN THE HOME VERSUS UNPREDICTABILITY IN THE BROADER ENVIRONMENT AFFECT TODDLERS’ SOCIOEMTIONAL BEHAVIORS by Demi Dumovich A Senior Honors Thesis Submitted to the Faculty of The University of Utah In Partial Fulfillment of the Requirements for the Honors Degree in Bachelor of Arts In Psychology Approved: _ __________ Dr. Lee Raby, PhD Thesis Faculty Supervisor __ ________ Michael B. Himle, PhD Associate Chair, Department of Psychology __ Dr. Lisa G. Aspinwall, PhD Honors Faculty Advisor _____________________________ Monisha Pasupathi, PhD Dean, Honors College ____ December 2024 Copyright © 2024 All Rights Reserved Abstract Life history theory suggests that unpredictability in children’s environments can shape their development in ways that undermine their socioemotional growth as they move through childhood and later as they become adults. There is a gap in the literature regarding the consequences of unpredictability for young children. It is important to examine the consequences of environmental unpredictability at an early age to develop interventions before more permanent learned behaviors are formed. In addition, environmental unpredictability has multiple definitions, which has caused difficulties creating consistent measurements. Therefore, there is lack of understanding about what types of unpredictability have the strongest impact on toddlers’ development. The goal of this study was to address those gaps by examining the extent to which different kinds of unpredictability were associated with children’s socioemotional well-being. Approximately 110 mother-toddler dyads were included in the study. Questionnaire measures of unpredictability in the broader environment (measured by changes of residence, mother’s relationship status, and changes of residents) unpredictability in the home (measured using the Confusion, Hubbub, and Order Scale), and toddlers’ socioemotional well-being (measured using the Infant-Toddler Social Emotional Assessment) were collected when children were 18 months old. Most of the mothers identified as non-Hispanic White, were married, had completed a 4year college degree, and had household incomes of $50,000 or more. Most of the mother-toddler dyads had minimal unpredictability; therefore, the results can only be generalized to families with low unpredictability. More research must be done for children in environments with high unpredictability such as children in foster or congregate care. Results indicated that unpredictability in the home was positively associated with toddlers’ dysregulation and was ii marginally associated with their externalizing behaviors. In contrast, unpredictability in the broader environment was not significantly associated with toddlers’ socioemotional outcomes. These results were consistent with the idea that unpredictability has consequences for young children and suggested that unpredictability in the home may be especially impactful for toddlers’ socioemotional well-being. Therefore, interventions for young children struggling with dysregulation may need to focus on the day-to-day unpredictability in their homes. iii TABLE OF CONTENTS ABSTRACT iii INTRODUCTION 1 METHODS 5 RESULTS 10 DISCUSSION 13 REFERENCES 19 iv How Unpredictability in the Home versus Unpredictability in the Broader Environment Affect Toddlers’ Socioemotional Behaviors Unpredictability is an inevitable factor of life that is experienced by people of all ages. According to life history theory (Ellis et al., 2012; Young et al., 2020), unpredictability can lead to the development of fast or slow life history strategies. A fast life history strategy is when a person is involved in more risky and aggressive behaviors, such as increased intimate partner violence, reduced effortful control, or early sexual engagement, which in turn may lead to more children and less parental investment in each child (Deater-Deckard et al., 2019; Belsky et al., 2022). In contrast, a slow life history strategy may lead to fewer children, more time and energy into each child, and less risky behaviors (Ellis et al., 2012). These strategies are based on the kinds of adaptation required in childhood and into adulthood. In particular, children who experience early unpredictability are more likely to develop a fast life history strategy (Ellis et al., 2012). For example, children living in unpredictable environments may struggle with greater externalizing behaviors in preschool such as noncompliance, aggression, and hyperactivity and internalizing symptoms in first grade such as depression, withdrawal, anxiety (Doom et al., 2015; Carter et al., 2003). These behaviors are disruptive and troublesome, but they are thought to be useful skills for navigating unpredictable environments as a child (Ellis et al., 2012). Importantly, when children are set on a track to develop a certain life history strategy, it has long-term consequences. As children become adults, even if their environments become safer and more predictable, the behaviors and strategies learned at a young age may continue into adulthood and can incorrectly predict the later environments they face (Ellis et al., 2012). There are two gaps in the current literature on the consequences of unpredictability. First, there is a lack of knowledge about how unpredictability during the earliest years of life may shape children’s development. Between birth to age 5 is thought to be a sensitive period when unpredictability may lead to more severe socioemotional behavioral issues. This is because these years are characterized by heightened neural plasticity due to rapid development of sensory, attentional, and limbic systems and the prefrontal cortex (Doom et al., 2015). In other words, the high plasticity and openness to experiences that are prevalent during these years may lead to an unpredictable environment affecting the development of neural systems that are responsible for adaptive responses to stress (Belsky et al., 2022; Doom et al., 2015). These neural systems can learn how to manage unpredictable environments while also learning how to prepare for them. Through training to deal with unpredictability, children anticipate it and may alter their responses to adjust for unpredictability in the future, even though it is not always needed (Doom et al., 2015). However, most research on the effects of unpredictability have focused on older children or on adults who retrospectively assess what their life was like as a child. These studies provide limited information on the direct links between sensitive periods and unpredictability during the first few years of life. A second gap in current literature is the lack of differentiating between the different types of unpredictability. One way of defining unpredictability focuses on changes in broader environment, such as changes in occupational status of parents, moving to a different residence, and changes within the family such as parents separating or leaving the home (Szepsenwol et al., 2022). Unpredictability can also be assessed in the home. Unpredictability that focuses on the micro level of a child’s life, such as how noisy or crowded a home is or how rushed a family constantly feels, can have a large impact on a child’s ability to self-regulate (Bridgett et al., 2015). Children who live in homes that lack stability likely are unable to predict what their home environment will look like on a day-to-day basis. Assessments of the bigger changes in a child’s 2 life, as captured by unpredictability in the broader environment, as well as the more day-to-day changes in the home are needed to understand how different types of unpredictability may uniquely shape children’s socioemotional development. As demonstrated, unpredictability in a child’s home and in their broader environment can be problematic for children in their adolescence and into adulthood, but what about children who are not living in the typical household environment? Although the central research goal of this paper was to discover how unpredictability can affect socioemotional outcomes of children living in homes with a caregiver, it originated from a desire to see what unpredictability does to children in foster or congregate care and how it may do more significant damage to them. Children in state’s custody find themselves moving from shelters to residential facilities to foster care placement repeatedly. An assessment of the creation of The Christmas Box House explores what a temporary shelter may look like for a child (Liese et al., 2008). It mentions the original goals of the shelter but lacks evidence as to how the shelter is benefitting or harming children today, as they are forced to move in and out of foster homes as well as temporary shelters and residential facilities. Bada et al. (2008) confirms how unpredictability negatively affects these children through research completed on children who had Child Protective Service involvement, changes in caretakers, and various moves. These various measures of unpredictability were found to be a significant predictor of behavioral problems and adaptive functioning in childhood. Although limited information is available on children who are in state’s custody, there is a relationship between how movement of home or family can affect a child’s socioemotional wellbeing. Other research by Hindt et al., (2018) dives into the impact of emergency shelters vs. placement with kin or fictive kin. This study demonstrates the possible consequences of being 3 placed in shelters which can create an unpredictable environment for young children. A major gap exists within the conversation about the constant movement that foster children face and the repeated uprooting of their lives every time their placement changes or falls through. Studying unpredictable environments within the homes of mother and child dyads can create the opening needed to begin to understand what unpredictability can do to a child in foster care. The goal of my study was to determine how different types of unpredictability affect children at a young age. Based on the existing literature, I hypothesized that more occurrences of unpredictability within the home and in the broader environment would be associated with a greater likelihood that the child would exhibit socioemotional behavioral problems. To test this hypothesis, I used data from the Baby Affect and Behavior Study (Lin et al., 2019). I examined how unpredictability in the home and the broader environment, throughout the children’s first 18 months, correlated with the toddler’s socioemotional behaviors. 4 Methods Participants The current study used data collected from the Baby Affect and Behavior Study (BABY), which is a longitudinal study beginning in the third trimester of pregnancy. Pregnant women were recruited by research assistants during their prenatal care appointments at offices or clinics that were affiliated with the University of Utah. Materials for recruitment were also sent out throughout the community encouraging women to apply by posting brochures, flyers, advertisements, social media posts, and handing out brochures at family specific events (Lin et al., 2019). Women were not randomly selected. Instead, women who were interested in participating first completed the Difficulties in Emotion Regulation Scale (Gratz & Roemer, 2004) and answered a questionnaire to determine their eligibility for the study. Women who reported experiencing low and high levels of emotional dysregulation were oversampled because the overarching goal of the BABY project was to examine the intergenerational transmission of emotion dysregulation. A uniform distribution of emotion dysregulation scores was achieved by recruiting a specific number of mothers with a certain level of emotional dysregulation and then stopping recruitment at that level once the goal was reached. In addition, women who belonged to racial/ethnic minority groups were also oversampled. Women were excluded due to substance use, multiple gestation, being under the age of 18 or if they were older than 40 years old due to health risks of an older pregnancy, and other health-related reasons (see Lin et al., 2019, for more information about eligibility criteria). Ultimately, the BABY project included 162 mother-child dyads. As reported by Lin et al. (2019), mothers’ ages ranged from 18 to 40 (M = 29 years), and the majority identified as nonHispanic White (54%), 27% identified as Hispanic/Latina, 9% identified as Asian, 6% identified 5 as multiracial, and less than 4% each identified as American Indian/Alaskan Native, Hawaiian Native/Pacific Islander, and Black/African American. Most of the women wanted the pregnancy (70%), did not have any diagnosed physical conditions that were related to the pregnancy (89%), were living with a romantic partner (91%), and were married (76%). In terms of educational attainment, 97% had a high school degree, 84% completed at least some college (including technical school), 52% completed a 4-year college degree, and 20% received graduate-level training. Household incomes ranged from less than $9,000 (4%) to $100,000 or more (15%), and the median annual household income was $50,000–79,999. Procedures The women who participated in the BABY project were followed from the third trimester of pregnancy until their child was 36 months old, except for a handful that had experienced fetal demise (n = 1) or had directly expressed a desire to no longer participate in the study (n = 2). The current study used data that were collected when the children were approximately 18 months old. At that time, the mothers were invited to complete a series of questionnaires through the online REDCap system, and they completed the questionnaires remotely at a time that was most convenient for them. The mothers were compensated $25 for their time. The study was approved by the University of Utah IRB. Three mothers were not contacted about participating at the 18-month visit for the reasons noted above, and forty-nine did not provide any questionnaire data at the 18-month visit. Of the 110 mothers who provided any questionnaire data, four did not complete all the questionnaires used in this study (CHAOS, demographics, and ITSEA, see below). One mother did not fill out enough of the ITSEA items related to externalizing and competence, so the 6 analyses predicting those analyses had a sample size of 105. The analyses predicting internalizing and dysregulation had a sample size of 106. Measures Unpredictability in the broader environment. Mothers completed a demographic questionnaire that was formulated from the measures used in a study by Belsky et al. (2012). The specific items used include information about unpredictability in their environment taken from surveys completed by the mothers when their child was 18-months old. The three main items included changes in the mother’s residence, who she lived with, and changes in relationship status, all which were measured since the time of the child’s birth. Unpredictability in the household. The Confusion, Hubbub, and Order Scale (CHAOS) Matheny et al. (1995) is a questionnaire that included 15 items that assess parents’ perceptions of the level of disorientation and structure in the home. The survey was titled “Family Activities” to prevent the participants from forming preconceptions about the measure. Three extra questions were added to the original version of the CHAOS to assess the child’s routines. These items were adapted from Jensen (1983). Example questions included “There is very little commotion in our home” and “There is often a fuss going on at our home.” Response options for each question were true or false (0=False, 1=True). A composite score was formed by summing the mothers’ responses for the original 15 questions along with the mothers’ responses for the three additional questions after reverse-scoring the applicable items. In this way, the CHAOS had a potential range of zero to 18. Toddler socioemotional outcomes. The Infant-Toddler Social and Emotional Assessment (ITSEA) was used to measure socioemotional well-being and competencies of children when they were approximately 18 months old. This measure was validated for children between the 7 ages of 12 and 35 months old (Carter et al., 2003). The ITSEA included questions about problem behavior typically seen during development but that could become a problem when it occurred too often or not often enough, problem behaviors that were more rarely exhibited but were natural to a standard developmental course such as aggression or high activity, as well as behaviors that could be considered signs of emerging competence. The ITSEA included 166 questions, which were organized in four composite measures. The first was externalizing behavior problems, which captured impulsivity, aggression and defiance. Example items included “Has temper tantrums” and “Hits, bites, or kicks you (or other parent).” The second was internalizing behavior problems, which captured withdrawal, depression, and anxiety. Example items included “Often seems worried or anxious when left with new people” and “Frequently clings to caregiver and avoids new situations.” The third was dysregulation, which captured sleep habits, eating habits, and emotional regulation. Example items included “Accepts new foods right away” and “Has trouble falling asleep at night and needs constant rocking or holding.” The fourth measure was competence, which captured attention, compliance, and empathy. Example items included “Likes being cuddled, hugged, or kissed by loved ones” and “Shares toys with other children.” For all questions, response options were “Not true / Rarely” (scored as 0), “Somewhat true / Sometimes” (scored as 1), “Very true / Often” (scored as 2), and “He or she is physically unable to do so” (scored as missing). Items were averaged within each of the four domains after reverse scoring as needed. The possible range for each of the ITSEA variables was zero to three. Annual family income. A common practice in research on the effect of unpredictability is to control for family income, which is conceptualized as a marker of environmental harshness 8 (Szepsenwol et al., 2022). For the current study, annual family income was reported by mothers at the time of the 18-month visit. Responses ranged from 1 to 10, with one representing the total family income per year of less than $9,000 and 10 representing $100,000 or more. 9 Results Preliminary Analyses Table 1 includes the descriptive statistics and correlations among the five measures of environmental unpredictability. Unpredictability in the broader environment included changes in residence, changes in cohabitation, changes in relationship status, and the overall environmental unpredictability composite. Unpredictability in the home included the CHAOS scale. Additionally, Table 1 includes family income, and the four outcome variables from the ITSEA (externalizing behavior problems, internalizing behavior problems, dysregulation, and socioemotional competence). The CHAOS mean score of 3.20 suggested that mothers reported low scores of environmental confusion in the home on average. However, scores varied, with mothers reporting scores ranging from a minimum of 0 (no environmental confusion in the home) to 14 (high levels of environmental confusion in the home). Therefore, there was wide diversity in the responses of mothers regarding how much environmental confusion existed within their homes. Each of the unpredictability measures was scored as zero or one. Therefore, the mean scores of 0.16 and 0.09 for changes in cohabitation and changes in relationship status, respectively, suggested that most mothers reported these changes did not happen within the given time frame. In contrast, the mean score of 0.41 for changes in residence suggested that this change was not uncommon within the given time frame. The overall environmental unpredictability composite had a potential range of zero to three and an actual range of zero to three. The mean score of annual family income 7.05 signified that most of the participants reported an annual household income between $40,000 and $49,000. 10 For toddlers’ externalizing problems the range was 0.030 to 1.42 and the mean was 0.50. For toddlers’ internalizing problems the range was 0.15 to 1.04 and the mean was 0.52. For toddler’s dysregulation the range was .060 to 1.36 and the mean was 0.41. The low mean for each subscale demonstrated that most children did not show high levels of maladaptive behaviors; however, the ranges showed there was wide variability within the reported scores. For toddlers’ competence the range was 0.39 to 1.91 and mean was 1.33. The high mean for competence signified most children did not suffer from competency issues but as with the other subscales, there was a wide diversity with the competence scores. The correlations among the variables are also included in Table 1. The CHAOS was positively correlated with changes in relationship status. Changes in cohabitation were positively correlated with changes in relationship status and residence. Family income was negatively correlated with CHAOS, experiencing a change in relationship status, and the overall environmental unpredictability composite. In terms of correlations with the ITSEA variables, the CHAOS was positively correlated with the toddlers’ externalizing problems and dysregulation, whereas family income was negatively correlated with externalizing, internalizing and dysregulation subscales. Experiencing a change in maternal relationship status, a change in residence, or a change in cohabitation were not significantly correlated with any subscales of the ITSEA. Focal Analyses For my descriptive analyses, I completed four multiple linear regression analyses: one predicting each of the four scales of the ITSEA. For each analysis, household CHAOS and the environmental unpredictability composite were included as predictor variables and family income was included as a covariate. The results of each linear regression analysis are reported in 11 Table 2. As shown in Table 2, household CHAOS was positively associated with toddlers’ dysregulation and had a marginally significant association with toddlers’ externalization problems. The environmental unpredictability composite was not significantly associated with any of the toddlers’ socioemotional outcomes. Although not the focus of the current study, it was worth noting that family income only was negatively associated with toddlers’ internalizing behavior problems. 12 Discussion The overall goal of this study was to assess how experiences of unpredictability in toddlers’ lives were related to their socioemotional behaviors. The results of the study suggested that unpredictability in the broader environment was not significantly associated with toddlers’ socioemotional outcomes. In contrast, day-to-day unpredictability within the home, as captured by the CHAOS questionnaire, was positively associated with toddlers’ dysregulation. CHAOS scores also had a marginally significant positive association with toddlers’ externalizing problems. Due to lack of significance between unpredictability in the broader environment and socioemotional outcomes, I was unable to explore which of the three types of unpredictability in the broader environment measures affected children the most significantly because neither the composite nor any individual measures were significant. Life history theory helps us understand why more unpredictability in the home is related to more socioemotional struggles for the children in this study and for adults. According to life history theory, children without early exposure to unpredictability tend to develop slow life history strategies, allowing them to develop at a slower rate and put more energy into each developmental stage (Ellis et al. 2012). On the other hand, exposure to high levels of unpredictability during a period of high neural plasticity (i.e., the first few years of life) will tend to result in children following the fast life history strategy (Belsky et al., 2022). The fast life history strategy is characterized by increased risky and aggressive behaviors such as aggression or defiance (Belsky et al., 2022; Carter et al., 2005). As demonstrated in this study, children learn to navigate the chaos and instability of their home at the cost of being able to regulate their bodies, including their sleeping and eating habits and their emotions. The long-term effects of 13 living with unpredictability in the home increase delinquency and social and emotional struggles which may continue into adulthood (Belsky et al., 2022). In general, unpredictability in the home and in the broader environment tend to be associated with poor socioemotional behaviors (Belsky et al. 2022; Ellis et al., 2012; Szepsenwol et al., 2022). However, this study found that unpredictability in the home but not the broader environment was significantly associated with socioemotional behaviors. A likely explanation for the nonsignificant findings related to unpredictability in the broader environment was the time frame allotted to assess unpredictability in the broader environment. Other studies have assessed unpredictability in the broader environment over multiple years, sometimes decades (e.g., Szepsenwol et al., 2022). In contrast, the present study only examined an 18-month time frame. To accurately measure unpredictability in the broader environment, it may be necessary to study multiple years due to the rate in which unpredictability in the broader environment occurs. Unpredictability in the home may not require the same extensive time frame because it is occurring on a weekly or daily basis. For example, the CHAOS questionnaire achieves this goal by focusing on the general, day-to-day to confusion and disorder that exists in the home (Matheny et al., 1995). A high overall CHAOS score means the child’s home is full of commotion and lacks routine and structure and children in highly chaotic environments must adapt to their environment (Bridgett et al., 2015). While this adaptation is important during stressful moments, it can change how the child functions overall and cause struggles for the child later in their life when managing behaviors and emotions. In the short-term, when children are surrounded by a high level of turbulence in the home, this may cause constant stress existing within the home. Bridgett et al. (2015) indicated that children who are exposed to consistent chaos in a home are at risk for elevated cortisol levels. Children who are in environments where 14 they are unable to relax, have routines, or feel a sense of calm cannot witness or learn the skills to practice self-regulation. While CHAOS and children’s socioemotional dysregulation were correlated as predicted, there are limitations to this study. Previous studies have reported that environmental unpredictability is an important indicator if whether a child will struggle socioemotionally (Ellis et al., 2012). Within this study, there was limited variability in children’s unpredictability in the home and especially in unpredictability in the broader environment. In other words, most of the children were not facing consistently stressful households, and most of the children did not see or live through multiple instances of unpredictability such as moving homes or living in a home with new cohabitants. To mitigate the variability of the unpredictability score, future studies can be completed with children who are living in shelters or congregate settings and who experience high rates of unpredictability because they are forced to change homes often. Children from unstable homes will need to be compared to children with more stable homes to address if environmental unpredictability affects the children’s current and future well-being. The short time frame of the study is a second limitation. This study only focused on the first 18 months of the child’s life. As noted previously, more time is needed for more unpredictability in the broader environment and in the home to occur. Unpredictability can take many months or years to happen such as divorces or moving homes. To better understand environmental unpredictability, the study needs to be longer than 18 months and continue to follow the family for an extended period. A third limitation in this study is that all the data were based on mothers’ reports. Selfreporting can lead to biased results due to the mothers not wanting to truly report the unpredictability in their home and/or to present their children in a more socially favorable way. 15 The self-reporting nature of this study may also have led to common method variance, which is the concept that people have their own tendencies for filling out questionnaires. There are other ways in which the results could be unintentionally biased by the mothers. They may have been in a certain mood that day, had a bad experience with surveys in the past, or a variety of other factors that may contribute to them unintentionally altering the results of the survey and therefore affecting the results. To limit the variability in surveying habits or potential sources of bias, future studies could observe mothers and children in the home or in a controlled setting and coders can complete the surveys for the children and their mothers during observation. To address the effects of unpredictability for children, long-term and short-term, the results of this study suggested it is pertinent that we focus on making the micro-level of a children’s life more stable. Rather than focusing on the big changes, some which may be inevitable, the focus could be placed on how the children are living day-to-day. Larger life events happen occasionally while a child must live in their home, eat dinner, and go to bed every day. Improving the stability and calm of the home on a more minute scale can lead to children being protected from the unpredictability that larger life events may cause. When children are assessed by health care providers, educators, or other professional and parents or when guardians express concerning socioemotional behaviors from their children, the CHAOS or other measurements can be used to determine the levels of unpredictability in the home. If families can see the areas of their home that are unpredictable, they can make intentional and specific adjustments to provide stability, making larger transitions feel less monumental. Therefore, when assessing how to support a child who is struggling with socioemotional behaviors such as dysregulation, the CHAOS could be used to assess how the child is faring in their everyday routines. This may create a more realistic idea of what needs to be addressed in the home to prevent instability. 16 As we develop a better understanding of how to support children with unpredictability in the home in a standard housing setting, we can then focus on children living in foster homes or congregate settings. These children have constant unpredictability in their home and in their broader environment. To support them to discover the amount of unpredictability in their environment, an evaluation of how their caregivers or other support figures can increase stability in the home to protect them from the inevitable unpredictability in the broader environment. When children are placed into environments where the children and staff are different each day, they are unable to decipher or predict what their environment will look like on a given day. This constant state of confusion leads to dysregulation which presents itself as challenges with eating or sleeping. To intervene in how children are managed in congregate settings, there must be more control over ratios between staff and children along with what kinds of children can be placed together at any given time. Children come into congregate care from multiple different trauma backgrounds. Mixing those backgrounds leads to more confusion and stress as children are exposed to second-hand trauma from their peers. To mitigate this stress and prevent dysregulation, such as difficulty eating, sleeping or regulating emotions, children should be placed with appropriate peers and staff equipped to manage certain behaviors from the designated trauma background. Including children with novel behaviors, as well as a new environment, may lead to children struggling with regulating their sleep, eating habits, or other behaviors that suffer in chaotic environments. As more research is done on what stressors cause certain dysregulated behaviors, staff working in congregate care must be aware of the damage exposure to novel environments and people can have on a child. 17 Conclusion In conclusion, this study has highlighted how toddlers living in more chaotic home environments may struggle with developing healthy sleeping and eating habits (dysregulation) and may also struggle more with noncompliance, aggression, and hyperactivity (externalizing). In contrast to my original hypothesis, unpredictability in the broader environment was not significantly associated with toddlers’ socioemotional outcomes. However, unpredictability in the home was found significant, suggesting the importance of future research that needs to focus on the unpredictability that exists in the micro level of children’s lives, rather than the big, macro, life events. Unpredictability can then be addressed with children who live in standard home environments and in children’s lives where unpredictability in the broader environment is unavoidable. If unpredictability in the home is addressed first, children may experience less adverse consequences to their socio-emotional well-being. 18 References Bada, H. S., Langer, J., Twomey, J., Bursi, C., Lagasse, L., Bauer, C. R., Shankaran, S., Lester, B. M., Higgins, R., & Maza, P. L. (2008). Importance of stability of early living arrangements on behavior outcomes of children with and without prenatal drug exposure. Journal of Developmental and Behavioral Pediatrics, 29(3), 173–182. https://doi.org/10.1097/DBP.0b013e3181644a79 Belsky, J., Ellis, B. J., Sheridan, M. A., & McLaughlin, K. A. (2022). Why and how does early adversity influence development? Toward an integrated model of dimensions of environmental experience. Development and Psychopathology, 34(2), 447-471. https://doi.org/10.1017/s0954579421001838 Belsky, J., Schlomer, G. L., & Ellis, B. J. (2012). Beyond cumulative risk: distinguishing harshness and unpredictability as determinants of parenting and early life history strategy. Developmental psychology, 48(3), 662–673. https://doi.org/10.1037/a0024454 Bridgett, D. J., Burt, N. M., Edwards, E. S., & Deater-Deckard, K. (2015). Intergenerational transmission of self-regulation: A multidisciplinary review and integrative conceptual framework. Psychological Bulletin, 141(3), 602-654. https://doi.org/10.1037/a0038662 Carter, A. S., Briggs-Gowan, M. J., Jones, S. M., & Little, T. D. (2003). The Infant–Toddler Social and Emotional Assessment (ITSEA): Factor structure, reliability, and validity. Journal of Abnormal Child Psychology, 31(5), 495-514. doi: 10.1023/A:1025449031360. Doom, J. R., Vanzomeren-Dohm, A. A., & Simpson, J. A. (2016). Early unpredictability predicts increased adolescent externalizing behaviors and substance use: A life history perspective. Development and Psychopathology, 28(4pt2), 1505-1516. https://doi.org/10.1017/s0954579415001169 19 Ellis, B. J., & Bjorklund, D. F. (2012). Beyond mental health: An evolutionary analysis of development under risky and supportive environmental conditions: An introduction to the special section. Developmental Psychology, 48(3), 591-597. https://doi.org/10.1037/a0027651 Gratz, K. L., & Roemer, L. (2004). Multidimensional assessment of emotion regulation and dysregulation: Development, factor structure, and initial validation of the Difficulties in Emotion Regulation Scale. Journal of Psychopathology and Behavioral Assessment, 26, 41-54. https://doi.org/10.1023/B:JOBA.0000007455.08539.94 Hindt, L. A., Bai, G. J., Huguenel, B. M., Fuller, A. K., & Leon, S. C. (2018). Impact of emergency shelter utilization and kinship involvement on children’s behavioral outcomes. Child Maltreatment, 24(1), 76–85. https://doi.org/10.1177/1077559518797198 Jensen, E.W., James, S.A., Boyce, W.T., Hartnett, S.A. (1983). The family routines inventory: Development and validation. Social Science and Medicine, 17(4), 201-211. doi: 10.1016/0277-9536(83)90117-X Liese, Anderson, J. L., & Evans, R. P. (2004). The Christmas Box House: Developing a best practice model for emergency shelter care and assessment. Journal of Family Social Work, 7(3), 39–48. https://doi.org/10.1300/J039v07n03_03i Lin, B., Kaliush, P. R., Conradt, E., Terrell, S., Neff, D., Allen, A. K., Smid, M. C., Monk, C., & Crowell, S. E. (2019). Intergenerational transmission of emotion dysregulation: Part I. psychopathology, self-injury, and parasympathetic responsivity among pregnant women. Development and Psychopathology, 31(3), 817-831. https://doi.org/10.1017/s0954579419000336 20 Matheny, A. P., Wachs, T. D., Ludwig, J. L., & Phillips, K. (1995). Bringing order out of chaos: Psychometric characteristics of the confusion, hubbub, and order scale. Journal of Applied Developmental Psychology, 16(3), 429-444. doi:10.1016/0193-3973(95)90028-4 Szepsenwol, O., Simpson, J. A., Griskevicius, V., Zamir, O., Young, E. S., Shoshani, A., & Doron, G. (2021). The effects of childhood unpredictability and harshness on emotional control and relationship quality: A life history perspective. Development and Psychopathology, 34(2), 607-620. https://doi.org/10.1017/s0954579421001371 Young, E. S., Frankenhuis, W. E., & Ellis, B. J. (2020). Theory and measurement of environmental unpredictability. Evolution and Human Behavior, 41(6), 550-556. https://doi.org/10.1016/j.evolhumbehav.2020.08.006 21 .11 .06 -.02 .26* -.25* .21* .18 .27* -.11 107 3.22 2.90 0.00 14.00 2. Environmental unpredictability composite 3. Changes in cohabitation 4. Changes in residence 5. Changes in relationship status 6. Family income 7. Toddler externalizing problems 8. Toddler internalizing problems 9. Toddler dysregulation 10. Toddler socioemotional competence N Mean Standard deviation Minimum Maximum Note. CHAOS = Chaos, Hubbub, and Order Scale. *p < .05. — 1. Household CHAOS 1 3.00 0.00 0.81 0.66 109 .12 .02 -.03 .04 -.29* .57* .78* .69* — 2 Table 1. Descriptive statistics and correlations among the focal variables. 1.00 0.00 0.36 0.16 109 .11 .03 .05 .02 -.12 .21* .26* — 3 1.00 0.00 0.50 0.41 110 .15 -.01 -.08 .04 -.16 .19 — 4 1.00 0.00 0.29 0.09 110 -.06 .04 .00 .02 -.38* — 5 10.00 1.00 2.82 7.05 110 -.04 -.24* .28* -.19* — 6 1.42 0.03 0.25 0.50 109 -.08 .48* .31* — 7 1.04 0.15 0.20 0.52 110 0.03 .50* — 8 1.36 0.08 0.25 0.41 110 -.26* — 9 1.91 0.39 0.26 1.33 109 — 10 22 -0.01 0.01 Family income Note: +p < .10. *p < .05. N’s between 105 and 106 -0.01 0.03 Environmental unpredictability SE 0.02+ 0.01 B (R2 = .061) 0.25 0.86 0.06 p SE p -0.02* 0.01 0.01 -0.03 0.03 0.24 0.01 0.01 0.20 B (R2 = .099) SE -0.01 0.01 -0.02 0.03 0.02* 0.01 B p 0.13 0.54 0.02 (R2 = .094) Dysregulation Internalizing Externalizing Household CHAOS Predictor Variables Regression 3: Regression 2: Regression 1: Table 2. Linear regression models predicting toddler socioemotional outcomes. SE p 0.00 0.01 0.68 0.04 0.03 0.22 -0.01 0.01 0.18 B (R2 = .033) Competence Regression 4: 23 Name of Candidate: Demi Dumovich Date of Submission: December 6th, 2024 24 Certificate Of Completion Envelope Id: B00D61D022504C4F848AA4E59A7DF8DA Status: Completed Subject: Complete with Docusign: Dumovich_Demi_Fall__2024.docx Source Envelope: Document Pages: 28 Signatures: 3 Certificate Pages: 5 Initials: 0 Envelope Originator: LISA G. ASPINWALL Ph.D. AutoNav: Enabled 102 South 200 East, Suite 110 EnvelopeId Stamping: Disabled Salt Lake City, UT 84111 Time Zone: (UTC-08:00) Pacific Time (US & Canada) [e-mail] IP Address: 24.10.251.55 Record Tracking Status: Original 12/5/2024 10:56:56 AM Signer Events Holder: LISA G. ASPINWALL Ph.D. Location: DocuSign [e-mail] Signature Timestamp LISA G. ASPINWALL Ph.D. Sent: 12/5/2024 11:02:11 AM [e-mail] Viewed: 12/5/2024 11:02:31 AM Professor of Psychology Signed: 12/5/2024 11:02:33 AM University of Utah Security Level: Email, Account Authentication (None) Signature Adoption: Pre-selected Style Using IP Address: 24.10.251.55 Electronic Record and Signature Disclosure: Not Offered via DocuSign K Lee Raby Sent: 12/5/2024 11:02:36 AM [e-mail] Viewed: 12/5/2024 11:10:13 AM Security Level: Email, Account Authentication (None) Signed: 12/5/2024 11:11:09 AM Signature Adoption: Pre-selected Style Using IP Address: 155.97.94.21 Electronic Record and Signature Disclosure: Accepted: 12/5/2024 11:10:13 AM ID: a0399a31-e450-44e1-8346-740652490939 Mike Himle Sent: 12/5/2024 11:11:12 AM [e-mail] Viewed: 12/5/2024 11:13:04 AM Security Level: Email, Account Authentication (None) Signed: 12/5/2024 11:14:11 AM Signature Adoption: Drawn on Device Using IP Address: 155.98.131.5 Signed using mobile Electronic Record and Signature Disclosure: Accepted: 12/5/2024 11:13:04 AM ID: 43f37a28-c733-4c31-8422-8d7bc86365e4 In Person Signer Events Signature Timestamp Editor Delivery Events Status Timestamp Agent Delivery Events Status Timestamp Intermediary Delivery Events Status Timestamp Certified Delivery Events Status Timestamp Carbon Copy Events Status Timestamp Demi Dumovich Sent: 12/5/2024 11:14:14 AM [e-mail] Viewed: 12/6/2024 7:30:40 AM Security Level: Email, Account Authentication (None) Electronic Record and Signature Disclosure: Not Offered via DocuSign Witness Events Signature Timestamp Notary Events Signature Timestamp Envelope Summary Events Status Timestamps Envelope Sent Hashed/Encrypted 12/5/2024 11:02:11 AM Certified Delivered Security Checked 12/5/2024 11:13:04 AM Signing Complete Security Checked 12/5/2024 11:14:11 AM Completed Security Checked 12/5/2024 11:14:14 AM Payment Events Status Timestamps Electronic Record and Signature Disclosure #! ! #$! 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