The education word gap emerges by 18 months: findings from an Australian prospective study

Screen Time and Parent-Child Talk When Children Are Aged 12 to 36 Months

Importance

Growing up in a language-rich home environment is important for children's language development in the early years. The concept of "technoference" (technology-based interference) suggests that screen time may be interfering with opportunities for talk and interactions between parent and child; however, limited longitudinal evidence exists exploring this association.

Objective

To investigate the longitudinal association between screen time and 3 measures of parent-child talk (adult words, child vocalizations, and conversational turns) when children are 12 to 36 months of age.

Design, Setting, and Participants

This Australian prospective cohort study used advanced speech recognition technology to capture young children's screen time and home language environment, on an average 16-hour day. Data were collected from 220 families once every 6 months in the family home when children were 12, 18, 24, 30, and 36 months of age, from January 1, 2018, to December 31, 2021. Statistical analysis took place from November 1, 2022, to July 31, 2023.

Exposure

Language Environment Analysis (LENA) technology provided automated counts of children's language environment and exposure to electronic noise. The exposure of interest was screen time, which was calculated based on manual coding of LENA electronic noise audio segments.

Main Outcomes and Measures

Three measures of parent-child talk were outcomes of focus: adult words, child vocalizations, and conversational turns. Separate models were run for each of the 3 outcomes and included adjustment for child sex, child age, maternal educational level, number of children at home, number of home activities, and primary caregiver's psychological distress.

Results

The study included 220 families (120 girls [54.6%]; mean [SD] gestational age of children, 39.3 [1.5] weeks; mean [SD] age of mother at childbirth, 31.3 [4.8] years). Adjusted linear mixed-effect models demonstrated that increases in screen time were associated with decreases in measures of parent-child talk. The largest decreases were seen at 36 months, when an additional minute of screen time was associated with a reduction of 6.6 (95% CI, -11.7 to -1.5) adult words, 4.9 (95% CI, -6.1 to -3.7) child vocalizations, and 1.1 (95% CI, -1.4 to -0.8) conversational turns.

Conclusion and Relevance

Findings of this study support the notion of technoference for Australian families, whereby young children's exposure to screen time is interfering with opportunities to talk and interact in their home environment. This finding has implications for interventions and supports aimed at promoting a language-rich home environment, with families needing support in understanding the potential association of screen time with opportunities for children and adults to talk and interact in their home environment.

Creating the conditions for robust early language development for all-Part 1: Evidence-informed child language surveillance in the early years

BACKGROUND

The emergence of language in the early years is a major developmental accomplishment that underpins learning, enables social interaction and, later, is an indicator of well-being. Learning language is an effortless process for most, but can be challenging for others. There is a need to act early. First, because there are several social, environmental and family factors known to influence how language develops during the critical early years. Second, there is a robust association between a child's socio-economic circumstances and language outcomes. Put simply, children living in less advantaged circumstance have poorer language outcomes, which are apparent very early and persist across the lifespan. Third, children with demonstrated weaknesses in language learning in early childhood have poorer educational, employment, mental health and quality-of-life outcomes across the lifespan. Acting early to counter these impacts is important; however, there are several well-documented challenges in accurately identifying in the early years children who are at later risk of developmental language disorder (DLD) and to deliver prevention and intervention programmes to scale. This is critical because many services do not currently reach those who need them most; as many as 50% of children in need may not be receiving support.

AIM

To determine whether an improved surveillance system, based on best evidence, could be developed for the early years.

METHODS & PROCEDURES

We summarised findings from longitudinal, population or community studies that: (1) adopted bioecological models, (2) repeatedly measured language (including the early years) and (3) adopted similar methodologies, to identify factors that influence language outcomes.

MAIN CONTRIBUTION

The evidence confirmed that language development is not always stable but is characterized by distinct trajectories and each has distinguishing social, environmental features. Children in the change or fluctuating groups tend to live in less advantageous circumstances that may not always support and enable language development. Risk factors tend to cluster and accumulate across the early years and beyond, thereby markedly increasing the likelihood of poorer language outcomes later in life.

CONCLUSIONS & IMPLICATIONS

In this the first of two papers, designed to be read together, we integrate research on the social determinants of child language and propose they be embedded into surveillance models. This has the potential to reach more children and those living in disadvantaged circumstances. In the accompanying paper we combine this information with evidence-informed early prevention/intervention approaches and propose the design and implementation of an early language public health framework.

WHAT THIS PAPER ADDS

What is already known on the subject There are several well-documented challenges in accurately identifying in the early years children who are at later risk of DLD and reaching those most in need of language support. What this study adds to existing knowledge A combination of child, family and environmental determinants, collectively and cumulatively, play out over time and dramatically increase the risk of later language problems, in particular those children living in disadvantaged circumstances. We propose an improved surveillance system that incorporates these determinants be developed and that this be part of a whole of system approach to child language in the early years. What are the potential or actual clinical implications of this work? Clinicians intuitively act to prioritize children with multiple features or risks; however, they can only do so for those who present or are identified to be at risk. Given many children with language problems are not being reached by many early language services, it is reasonable to ask if this knowledge can be integrated to improve reach. Or is a different surveillance model required?

Exploring Mothers' Experience of a Linguistic Feedback Technology for Children at Risk of Poor Language Development: Qualitative Pilot Study

BACKGROUND

The early language environment is important for language development and a child's life-course trajectory. Risk factors associated with poor language development outcomes in children include maternal anxiety and depression, low educational attainment, substance misuse, and low socioeconomic status. Language Environment Analysis (LENA) is a wearable technology designed to promote caregivers' engagement in supporting their children's language development. LENA provides quantitative linguistic feedback, which has been shown to improve caregiver language output, thus enhancing a child's language environment. There is limited research on the uptake of this technology by families with developmentally at-risk children.

OBJECTIVE

This qualitative study aims to explore the conditions under which mothers with children at risk of poor developmental outcomes are willing to adopt the use of LENA to monitor and improve caregiver language output.

METHODS

Using a qualitative interpretive design, semistructured, in-depth interviews were conducted with 8 mothers. Participants were recruited purposively to select the maximal variation of socioeconomic and ethnodemographic backgrounds. The transcribed interview data were analyzed thematically and interpretatively. Themes were mapped abductively to an extended Unified Theory of Acceptance and Use of Technology, which included contextual factors for LENA acceptance.

RESULTS

Factors that influenced the intention to use LENA included both technology-specific acceptance factors and contextual factors. Technology acceptance themes included reassurance, feeling overwhelmed, and trust. These themes were mapped to performance expectancy, effort expectancy, and social influence. Contextual themes included emergent success and the intrusion of past difficulties. These were mapped to parenting self-efficacy and perceived risk. The theme of building on success described behavioral intention. Mothers were more likely to adopt LENA when the technology was viewed as acceptable, and this was influenced by parenting self-efficacy and perceived risk.

CONCLUSIONS

LENA is a technology that is acceptable to mothers with children who are at risk of poor language development outcomes. Further studies are needed to establish LENA's effectiveness as an adjunct to strategies to enrich a child's early language environment.