Validation study showed that ratings on the Welch Emotional Connection Screen at infant age six months are associated with child behavioural problems at age three years.

AIM: The emotional connection between mothers and infants born preterm has been associated with positive behaviour. The aim of this study was to examine the longitudinal association between emotional connection at six months of age and behavioural problems at three years. METHODS: This study was carried out by the University of North Texas, USA and comprised 49 mothers and infants from a longitudinal investigation of family interaction and infant development conducted in 1994-1997. Face-to-face interaction and toy-based play were videotaped and coded at six months of age using the Welch Emotional Connection Screen (WECS), a brief screening tool for relational health. When the children were three years of age, the mothers reported on child behavioural problems. RESULTS: The children from dyads that were rated as emotionally connected at six months of age had fewer externalising and internalising behavioural problems at the age of three. No links were found between emotional connection during toy-based play at six months and later child behavioural problems. CONCLUSION: We showed that when the WECS was used at six months of age it was a promising and valid relational screening tool for infants at risk of adverse behavioural outcomes at the age of three.

The influence of sample distribution on growth model output for a highly-exploited marine fish, the Gulf Corvina (Cynoscion othonopterus).

Estimating the growth of fishes is critical to understanding their life history and conducting fisheries assessments. It is imperative to sufficiently sample each size and age class of fishes to construct models that accurately reflect biological growth patterns, but this may be a challenging endeavor for highly-exploited species in which older fish are rare. Here, we use the Gulf Corvina (Cynoscion othonopterus), a vulnerable marine fish that has been persistently overfished for two decades, as a model species to compare the performance of several growth models. We fit the von Bertalanffy, Gompertz, logistic, Schnute, and Schnute-Richards growth models to length-at-age data by nonlinear least squares regression and used simple indicators to reveal biased data and ensure our results were biologically feasible. We then explored the consequences of selecting a biased growth model with a per-recruit model that estimated female spawning-stock-biomass-per-recruit and yield-per-recruit. Based on statistics alone, we found that the Schnute-Richards model described our data best. However, it was evident that our data were biased by a bimodal distribution of samples and underrepresentation of large, old individuals, and we found the Schnute-Richards model output to be biologically implausible. By simulating an equal distribution of samples across all age classes, we found that sample distribution distinctly influenced model output for all growth models tested. Consequently, we determined that the growth pattern of the Gulf Corvina was best described by the von Bertalanffy growth model, which was the most robust to biased data, comparable across studies, and statistically comparable to the Schnute-Richards model. Growth model selection had important consequences for assessment, as the per-recruit model employing the Schnute-Richards model fit to raw data predicted the stock to be in a much healthier state than per-recruit models employing other growth models. Our results serve as a reminder of the importance of complete sampling of all size and age classes when possible and transparent identification of biased data when complete sampling is not possible.