Search Results (6)

The quantity of language input is a relevant predictor of children’s language development and is frequently used as a variable in child bilingualism research. Studies use various methods to measure bilingual language input quantity, but it is currently unknown what the optimal method is. We investigated the bilingual language input estimates of 31 Turkish–Dutch and 21 Polish–Dutch 3- to 5-year-old bilingual children, obtained via the questionnaire for Quantifying Bilingual Experience (Q-BEx) and day-long audio recordings made with Language Environment Analysis (LENA), and proposed a combined method that could overcome several shortcomings of the individual methods. The three methods are compared to each other in their correlation strength with receptive and expressive vocabulary scores. Each individual method correlated significantly with vocabulary scores, regardless of modality or language. Contrary to our hypothesis, the combined method did not correlate stronger with vocabulary outcomes than the Q-BEx and LENA individually did. The latter two did not differ significantly from each other in their correlational strength with vocabulary outcomes. These findings show that both the Q-BEx, LENA, and combined method can be deemed reliable to measure bilingual language input quantity. Future studies can make more informed decisions about their methodology in children’s bilingualism research. Full article

Background/Objectives: This study aimed to investigate whether day-long recordings with Language Environment Analysis (LENA) can be utilized in a hospital-based Auditory Verbal Therapy (AVT) program in Denmark for children with hearing loss and to conduct a pilot validation in the Danish language. Methods and materials: A license for the LENA system (LENA SP) was purchased, and trials were offered to three families enrolled in the AVT program. Each family made two day-long recordings with 3–4 months in between and received feedback during the therapy sessions. From 18 × 10-min clips randomly pulled out of the recordings, a comparison of adult word counts (AWC) between the LENA algorithm counts and the counts made by two human transcribers was made and used for the pilot validation. Results: LENA proved to be valuable as a guiding tool for Danish parents. Pilot validation showed good correlations and an acceptable limit of agreement (LoA). Conclusions: LENA holds the potential for Danish validation and use in AVT/clinical practice. When used in clinical practice, parents must be informed of the biases and limitations, and possible ethical issues must be considered. Because of the GDPR rules, there is a need to discuss the possibility of implementing this tool clinically in Denmark and the EU. Full article

Children’s language acquisition is underpinned by the quantity and quality of linguistic stimulation. Early diagnosis and cochlear implantation (CI), along with a family-centered intervention, are regarded as critical factors in providing appropriate language stimulation and thus supporting successful language outcomes in children with sensory neural hearing loss (SNHL). Considering the lack of tools to assess early language skills and open issues regarding the early predictors of CI outcomes, our goal was to evaluate the potential usability of the Language ENvironment Analysis (LENA) system as an early assessment and/or predictive tool. Clinical video recordings, LENA home recordings, and vocabulary scores were used to assess the progression of communication abilities of four children with CIs (6–35 m.o.). The data revealed a positive correlation between the estimated mean length of utterance (EMLU), vocal conversational turns (CT) in clinical video recordings, and receptive vocabulary, as well as the CT count in LENA being a significant predictor of productive vocabulary. These findings lead us to conclude that the LENA system has the potential to be used as an additional (tele-)measure in the early assessment of communication abilities of children with CI, as well as as a tool in the research of early predictors of CI outcomes. Full article

The home language environment is critical to early language development and subsequent skills. However, few studies have quantitatively measured the home language environment in low-income, developing settings. This study explores variations in the home language environment and child language skills among households in poor rural villages in northwestern China. Audio recordings were collected for 38 children aged 20–28 months and analyzed using Language Environment Analysis (LENA) software; language skills were measured using the MacArthur–Bates Mandarin Communicative Developmental Inventories expressive vocabulary scale. The results revealed large variability in both child language skills and home language environment measures (adult words, conversational turns, and child vocalizations) with 5- to 6-fold differences between the highest and lowest scores. Despite variation, however, the average number of adult words and conversational turns were lower than found among urban Chinese children. Correlation analyses did not identify significant correlations between demographic characteristics and the home language environment. However, the results do indicate significant correlations between the home language environment and child language skills, with conversational turns showing the strongest correlation. The results point to a need for further research on language engagement and ways to increase parent–child interactions to improve early language development among young children in rural China. Full article

Interdisciplinary approaches are needed to measure the additive or multiplicative impacts of chemical and non-chemical stressors on child development outcomes. The lack of interdisciplinary approaches to environmental health and child development has led to a gap in the development of effective intervention strategies. It is hypothesized that a broader systems approach can support more effective interventions over time. To achieve these goals, detailed study protocols are needed. Researchers in child development typically focus on psychosocial stressors. Less attention is paid to chemical and non-chemical stressors and how the interaction of these stressors may impact child development. This feasibility study aims to bridge the gap between child development and environmental epidemiology research by trialing novel methods of gathering ultrafine particle data with a wearable air sensor, while simultaneously gathering language and noise data with the Language Environment Analysis (LENA) system. Additionally, psychosocial data (e.g., parenting quality, caregiver depression, and household chaos) was gathered from parent reports. Child participants (age 3–4 years) completed cognitive tasks to assess self-regulation and receptive language skills, and provided a biospecimen analyzed for inflammatory biomarkers. Data collection was completed at two time points, roughly corresponding to fall and spring. Twenty-six participants were recruited for baseline data, and 11 participants completed a follow-up session. Preliminary results indicate that it is feasible to gather personal Particulate Matter (PM2.5), language, and noise data, cognitive assessments, and biospecimens from our sample of 3-4-year-old children. While there are obstacles to overcome when working with this age group, future studies can benefit from adapting lessons learned regarding recruitment strategies, study design, and protocol implementation. Full article

Background and Objectives: This systematic review reports the evidence from the literature concerning the potential for using an automated vocal analysis, the Language ENvironment Analysis (LENA, LENA Research Foundation, Boulder, CO, USA) in the screening process for children at risk for autism spectrum disorder (ASD) and deaf or hard of hearing (D/HH). ASD and D/HH have increased comorbidity, but current behavioral diagnostic and screening tools have limitations. The LENA Language Autism Screen (LLAS) may offer an additional tool to disambiguate ASD from D/HH in young children. Materials and Methods: We examine empirical reports that use automatic vocal analysis methods to differentiate disordered from typically developing children. Results: Consensus across the sampled scientific literature shows support for use of automatic methods for screening and disambiguation of children with ASD and D/HH. There is some evidence of vocal differentiation between ASD, D/HH, and typically-developing children warranting use of the LLAS, but additional empirical evidence is needed to better understand the strengths and weaknesses of the tool. Conclusions: The findings reported here warrant further, more substantive, methodologically-sound research that is fully powered to show a reliable difference. Findings may be useful for both clinicians and researchers in better identification and understanding of communication disorders. Full article