Mapping the development of facial expression recognition

Reading the non‐verbal cues from faces to infer the emotional states of others is central to our daily social interactions from very early in life. Despite the relatively well‐documented ontogeny of facial expression recognition in infancy, our understanding of the development of this critical social skill throughout childhood into adulthood remains limited. To this end, using a psychophysical approach we implemented the QUEST threshold‐seeking algorithm to parametrically manipulate the quantity of signals available in faces normalized for contrast and luminance displaying the six emotional expressions, plus neutral. We thus determined observers' perceptual thresholds for effective discrimination of each emotional expression from 5 years of age up to adulthood. Consistent with previous studies, happiness was most easily recognized with minimum signals (35% on average), whereas fear required the maximum signals (97% on average) across groups. Overall, recognition improved with age for all expressions except happiness and fear, for which all age groups including the youngest remained within the adult range. Uniquely, our findings characterize the recognition trajectories of the six basic emotions into three distinct groupings: expressions that show a steep improvement with age – disgust, neutral, and anger; expressions that show a more gradual improvement with age – sadness, surprise; and those that remain stable from early childhood – happiness and fear, indicating that the coding for these expressions is already mature by 5 years of age. Altogether, our data provide for the first time a fine‐grained mapping of the development of facial expression recognition. This approach significantly increases our understanding of the decoding of emotions across development and offers a novel tool to measure impairments for specific facial expressions in developmental clinical populations.     

Spirituality and child protection in early childhood education: a strengths approach

In recent international and Australian early childhood curriculum guidelines and child-protection policies, the need for teachers of young children to foster spirituality has been highlighted. However, what this might mean in practice has not been widely explored. This article addresses the more controversial issue of spiritual abuse and the right of children to protection in terms of spiritual development. We present a critique of current definitions taken from research and policy documents. Qualitative data provide the research background. Vignettes are presented to give examples of what spiritual harm might look like in practice. Finally, a strengths-based approach is introduced and strategies are suggested in order to explore the potential of the Strengths Approach (a social justice approach originating from social service practice) to aid early years’ teachers to create spiritually protective learning environments. This approach recognises and values children’s holistic development and wellbeing and supports them to appreciate, engage with and question the world around them with a resilient spirit.     

Accuracy of Clinician Predictions of Future Self‐Harm: A Systematic Review and Meta‐Analysis of Predictive Studies

Assessment of a patient after hospital‐treated self‐harm or psychiatric hospitalization often includes a risk assessment, resulting in a classification of high risk versus low risk for a future episode of self‐harm. Through systematic review and a series of meta‐analyses looking at unassisted clinician risk classification (eight studies; N = 22,499), we found pooled estimates for sensitivity 0.31 (95% CI: 0.18–0.50), specificity 0.85 (0.75–0.92), positive predictive value 0.22 (0.21–0.23), and negative predictive value 0.89 (0.86–0.92). Clinician classification was too inaccurate to be clinically useful. After‐care should therefore be allocated on the basis of a needs rather than risk assessment.     

Clusters of Suicidal Events Among Young People: Do Clusters from One Time Period Predict Later Clusters?

We sought to compare clusters of suicidal events between two different time periods and examine the extent to which earlier clusters predict later clusters. We included data on suicides and suicide attempts from New South Wales between July 2001 and June 2012 and Western Australia between January 2000 and December 2011. Suicide attempts included admissions to hospital for deliberate self‐harm and suicides were deaths due to deliberate self‐harm. We combined data on suicides and suicide attempts and grouped them into two equal time periods. We detected clusters in each period using Poisson discrete scan statistics adjusted for socio‐economic status. We estimated the predictive values of earlier clusters on later clusters. The results showed that clusters from earlier time period had a moderate power (36%) in predicting later clusters. During the later time period, some additional cluster areas (14%) were found and some earlier cluster areas subsided (64%). Historical clusters predict 36% of the subsequent clusters, which is probably not sufficient for targeting interventions. Our study highlights the need for other strategies to detect emerging clusters, for example, up‐to‐date data.