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About this paper symposium
| Panel information |
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| Panel 31. Solicited Content: Integrative Developmental Science |
| Paper #1 | |
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| Definitions, Approaches, and Measures of Early Life Unpredictability in the Developmental Context: A Scoping Review | |
| Author information | Role |
| Dr. Sihong Liu, Stanford University, United States | Presenting author |
| Seth D. Pollak, University of Wisconsin, United States | Non-presenting author |
| Abstract | |
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Introduction Unpredictability is increasingly investigated as a key dimension of early environment that bears significant impacts on child development (Davis & Glynn, 2024). As a heterogeneous construct, unpredictability has been construed in many ways: across different timescales, in various contexts, and via objective inputs or subjective impressions. This research also incorporates a broad range of constructs (e.g., chaos, economic insecurity, routines) that were only recently brought together under the umbrella of unpredictability. Given this heterogeneity, current knowledge on unpredictability impacts on child development is dispersed and disconnected. This study conducted a scoping review on the methodologies and assessments used to capture unpredictability in early experiences, aiming to develop an overarching conceptual framework with an operationalizable definition of unpredictability and to inform future research. Methods This review followed the guidelines of the PRISMA extension for Scoping Reviews (Tricco et al., 2018) and the framework developed by Arksey and O’Malley (2005). Literature search was conducted in PsyInfo and PubMed using keywords that indicate focuses on 1) unpredictability-related constructs (e.g., uncertainty, volatility, chaos), 2) in environments/contexts/experiences, 3) among children/youth/adolescents. Initial search returned 863 articles, whose titles and abstracts were then screened, yielding a final list of 192 articles. Data extraction was then conducted by coding the following metrics on assessed unpredictability-related constructs of each article: data source, reporter, ecological context, timescale, psychometric properties, and subjectivity vs. objectivity. Data were then synthesized using an iterative inductive approach to identify common patterns underlying various constructs, a crucial step towards creating the overarching conceptual framework. Results Figure 1 presents the PRISMA flowchart. Accordingly, the most predominant data source was via questionnaires/surveys, followed by observations and administrative/public records. This review highlighted a wide range of computational or modeling approaches utilized to capture the underlying statistical properties of unpredictability. Several innovative methods emerged, including using moment-to-moment video-coding of mother-child interactions (e.g., Davis et al., 2017), LENA home environment recordings (e.g., Werchan et al., 2022), GPS tracking (Depeau et al., 2017), or ecological momentary assessment (EMA; Maher, et al., 2018). These innovations reflected two trends in this field: 1) Enhancing measurement validity, and 2) exploring underlying statistical properties via collecting intensive, longitudinal data. Figure 2 presents a visualization of synthesized results. Not surprisingly, most studies captured unpredictability in children’s proximal (especially parenting & family) contexts. The distal context assessed the most was parental employment instability, and the other environments (e.g., neighborhood, broader social-culture) were rarely examined. In terms of timescale, other than the innovative methods mentioned above, most unpredictability assessment methods could only capture variations at meso- (across days/weeks or contexts) to macro- (across months/years) levels. Wide variations were found in the subjectivity/objectivity of assessed constructs that might have different implications on developmental outcomes. Lastly, we identified constructs that were captured most frequently in unpredictability research, including routines, chaos, and changes in household composition, resident, or parental employment. As a following step, these findings will be combined with evidence on child outcomes to form a comprehensive understanding of how various unpredictability aspects operate throughout the developmental course. |
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| Paper #2 | |
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| Unpredictable Maternal Signals During Infancy and Developmental Trajectories of Body Mass Index into Adolescence | |
| Author information | Role |
| LillyBelle Ku'ulei Deer, Ph.D., University of Denver, United States | Presenting author |
| Emily M. Melnick, University of Denver, United States | Non-presenting author |
| Jenalee R. Doom, University of Denver, United States | Non-presenting author |
| Laura M. Glynn, Chapman University, United States | Non-presenting author |
| Hal. S. Stern, University of California, Irvine, United States | Non-presenting author |
| Curt A. Sandman, University of California, Irvine, United States | Non-presenting author |
| Elysia P. Davis, University of Denver, University of California, Irvine | Non-presenting author |
| Abstract | |
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Introduction: Obesity in childhood and adolescence is increasingly prevalent worldwide (WHO, 2022) and is a robust predictor of poor physical and mental health across the lifespan (Jacobs et al., 2022; Sahoo et al., 2015). Early life adversity is associated with higher body mass index (BMI) and greater risk of obesity (Wiss & Brewerton, 2020). Unpredictable early life experiences are an understudied aspect of early life adversity that provide important signals to the child about their environment (Baram et al., 2012). Parental behavioral unpredictability can be measured through assessing patterns of sensory signals that are provided from parents to children. Both experimental non-human animal models and observational human research show links between unpredictable maternal sensory signals and altered offspring development across multiple systems (Chen & Baram, 2016; Davis et al., 2017; 2022), with notable sex differences (Levis et al., 2021; Bolton et al., 2018). However, no work has tested whether unpredictability of maternal sensory signals also predicts physical health outcomes, such as BMI. Objectives: To assess the contribution of unpredictable maternal sensory signals during infancy and child BMI trajectories from infancy through adolescence. Additionally, the current study aims to examine whether sex moderates the association between maternal behavioral unpredictability and BMI trajectories. Methods: In a prospective longitudinal cohort (N = 190 mother/child dyads), we quantified the unpredictability of maternal sensory signals from 10-minute free-play interactions at 6- and 12-months of age. Patterns of moment-to-moment sensory signals to the child were quantified by computing an entropy rate indexing the unpredictability of transitions between visual, auditory, and tactile signals provided by the parent to their child during these interactions (Davis et al., 2017). Child BMI was measured longitudinally at 7 time points between infancy through adolescence. General linear mixed models assessed relations between study variables, with linear and quadratic age terms to account for the typical developmental pattern of BMI. BMI is known to have a quadratic pattern from infancy through adolescence, with an increase from birth to 6 months, followed by a decrease until about 5 years of age, and another increase through adolescence (Wen et al., 2012). Child birthweight and maternal sensitivity were included as covariates in analyses. Results: Associations between unpredictable maternal sensory signals during infancy and BMI trajectories differed by sex (b = 0.08, SE = 0.04, p = .033), such that greater unpredictability of maternal sensory signals in infancy was associated with a trajectory of higher BMI into adolescence for females (b = 0.06, SE = 0.03, p = . 049), but not for males (p = .546). For females, higher entropy predicted more rapid increases in BMI in early adolescence (see Figure). Conclusions: Findings suggest that early life unpredictability may be an important signal shaping biobehavioral pathways to later child health, and the sequelae of early unpredictability may differ by sex. As such, unpredictable parenting behaviors may represent a target for future interventions. |
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| Paper #3 | |
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| Effects of unpredictability on children’s decision making behaviors | |
| Author information | Role |
| Dr. Karen E. Smith, Ph.D., Rutgers University – Newark, United States | Presenting author |
| Seth D. Pollak, University of Wisconsin, United States | Non-presenting author |
| Abstract | |
| To effectively navigate their environments, individuals need to be able to recognize and then using cues of positive and negative outcomes to make decisions (Knutson & Sirangarajan, 2019; Debiec & Olsson, 2017). Growing evidence suggests early experiences shape the development of these processes (Herzberg & Gunnar, 2020; Novick et al., 2018; Oltean, 2022), but the specific dimensions of experience most critical to learning and decision making is still not clear. Recent theoretical models have proposed that unpredictability of the early environment may be particularly important in shaping learning and decision making (Frankenhuis & Gopnik, 2023; McLaughlin et al., 2021; Smith & Pollak, 2021). But there is substantial variation in how unpredictability is conceptualized and measured, making it difficult to disentangle which components meaningfully capture variation in children’s behaviors (Frankenhuis & Nettle, 2020). This is in part because unpredictability can be studied at different levels of analysis (e.g. broader environment, family, individual child) and, within each of those levels of analysis, measured in varying ways (Ugarte & Hastings, 2023; Young et al., 2020). In the current study, we aimed to compare multiple measures of unpredictability, examining which are associated with variability in children’s decision making behaviors. To do so, we had 72 8- and 9-year-old children and caregivers complete measures of both unpredictability in the family environment and global beliefs about unpredictability. To measure unpredictability in the family environment, children completed the Questionnaire of Unpredictability in Childhood (Glynn et al., 2019), and caregivers completed the Family Unpredictability Scale (Ross & Hill, 2000). To measures global beliefs about unpredictability, children completed the Childhood Unpredictability Schema (De Baca et al., 2016), and caregivers completed the Scale of Unpredictability Beliefs (Ross et al., 2016). Children also completed a two part learning and decision making task. In the learning portion of the task, they saw neutral shapes paired with positive, negative, or neutral outcomes. In the decision making portion of the task, they saw the same neutral shapes but were asked to make decisions about whether to approach or avoid the outcomes (Figure 1). Child reports of unpredictability were associated with differences in decision making behaviors (χ2(2) = 19.80, p < 0.001), such that children reporting higher levels of unpredictability were more effective at approaching positive and avoiding negative ones (Figure 2). These effects were only apparent for children’s global beliefs about predictability. Caregiver reports of unpredictability were not associated with differences in children’s decision making behaviors (ps > 0.10). Together these results suggest that children’s beliefs about unpredictability drive changes in their decision making behaviors and relying on caregiver reports may not sufficiently capture these effects. We discuss these findings in relation to their implications for assessment of childhood unpredictability. | |
| Paper #4 | |
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| Understanding the Relationship between Childcare Precarity and Emotional Distress | |
| Author information | Role |
| Mateus Morante Mazzaferro, Stanford University, United States | Presenting author |
| Sihong Liu, Stanford University, United States | Non-presenting author |
| Philip A. Fisher, Stanford University, United States | Non-presenting author |
| Abstract | |
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Introduction: For families with young children, securing reliable childcare can be a significant challenge. Rising costs, limited resources, and the COVID-19 pandemic have exacerbated precarity in families' childcare arrangements (Grantham et al., 2021; U.S. Department of the Treasury, 2021). Defined as insecure or unreliable childcare arrangements while parents work or attend school (Duh-Leong et al., 2023), childcare precarity signals unpredictability in family life and early care and education settings (Carrillo et al., 2017; Harknett et al., 2022) and has important implications for families’ economic and psychosocial well-being (e.g., Bratsch-Hines et al., 2015; Luhr et al., 2022; Pilarz & Hill, 2014, 2017). . However, research to date has not integrated childcare precarity in the broader framework of unpredictability research (Liu & Fisher, 2022; Young et al., 2020), and often relies on one-dimensional indicators (e.g., work-care conflict). This study aims to expand the conceptualization of childcare precarity as a multidimensional marker of early life unpredictability and examine its relationship with caregiver and child emotional distress. Methods: Participants were 3,115 caregivers (88% female, 67% white) who completed the RAPID Survey between November 2022 and December 2023 and reported working or attending school. RAPID is a survey platform created in April 2020 that collects actionable data on the experiences of important adults in young children’s lives (Liu et al., 2024). We assess whether including a childcare search status as an indicator of precarity improves the cross-sectional prediction of caregiver and child emotional distress beyond commonly used indicators (unreliability and disruptions) and test for non-linear effects. Using a person-centered approach, we also conduct an exploratory latent profile analysis (LPA) to identify distinct experiences of childcare precarity and associated emotional distress. Results: In ordinary least squares regressions, childcare unreliability and disruptions were consistently linked to caregiver distress. For children, unreliability was associated with fear/anxiety, while disruptions were associated with fussiness/defiance. Childcare search status was also linked to both caregiver and child emotional distress, improving model fit compared to models using only unreliability and disruptions. Evidence of quadratic and cubic effects of search status was found for caregivers (Figure 1). In our exploratory LPA, a five-class solution emerged as optimal (Figure 2). The five classes were: low-to-absent precarity (34.8%); moderate precarity – more disruptions (40.8%); moderate precarity – higher unreliability and searching (11.7%); high precarity – highest unreliability (7.2%); and very high precarity – highest disruptions and searching (5.5%). Emotional distress outcomes differed significantly across the classes, with higher levels of precarity linked to more distress. Discussion: Our findings demonstrate that a multidimensional conceptualization of childcare precarity is crucial. We find evidence for a non-linear relationship between search status and caregiver emotional distress, with impact on ability to work possibly driving higher distress levels. Additionally, the existence of distinct precarity profiles has policy implications, underscoring the need for tailored support for families based on their profile. Future research should replicate these exploratory findings and examine additional dimensions of childcare precarity as an element of early life unpredictability. |
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Early Unpredictability and Child Development: Theoretical Considerations and Methodological Innovations Towards an Integrative Research Framework
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Paper Symposium
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| Session Title | Early Unpredictability and Child Development: Theoretical Considerations and Methodological Innovations Towards an Integrative Research Framework |