人工智能辅助的自闭症早期患者的筛查与诊断

自闭症谱系障碍(AutisticSpectrumDisorders,ASD)的症状早在婴幼儿期就会显现,越早发现,越早干预,治疗效果越好。传统自闭症早期筛查与诊断在评估方法、流程上存在局限,无法满足大规模筛查和诊断需求。随着人工智能技术的快速发展,使用智能化方法进行自闭症早期大规模无感筛查与诊断逐渐成为可能。近10年间,国内外对自闭症智能化识别方法的探索在经典任务行为、面部表情和情绪、眼动、脑影像、运动控制和运动模式、多模态6个领域积累了丰富的研究成果。未来研究应围绕构建国内自闭症早期智能医学筛查与诊断体系,开发针对婴幼儿患者的筛查工具,构建融合多模态数据的自闭症婴幼儿智能化识别模型,建立结合脑影像技术的自闭症精细化诊断方法等方面来开展。     

Discourse analysis: Rich pickings for counsellors and therapists

Aim: It is only relatively recently that discourse analysis has begun to rise to prominence in the fields of counselling and psychotherapy. This paper briefly explains ways of understanding discourse analysis, discussing what the approach can offer counselling research and practice. Approach: An initial categorisation of recent discourse analysis studies is offered, to demonstrate diverse ways in which this type of research can address issues relevant to counselling practice. The five categories proposed range from the examination of language use in therapy to analyses that focus on the social structures, meanings and power relations related to therapy. Implications: The paper demonstrates that through the critical analysis of counselling sessions, research interviews, written texts and other materials, discourse analysis can provide insight into ways in which counselling operates as a social practice, and so help counsellors to contextualise their work within broader social structures and processes.     

The stability of function of automatically reinforced vocal stereotypy over time

Although prior research has suggested the function of socially reinforced problem behavior can change across time, the stability of the function of automatically reinforced behavior is largely unknown. Further, some authors have suggested automatically reinforced behavior is likely to enter into socially mediated contingencies. The present study compared 2 functional analyses conducted on the same target behavior at least 1 year apart. Participants were 6 individuals diagnosed with an intellectual or developmental disability displaying automatically reinforced vocal stereotypy. Results indicated the function of each participant's vocal stereotypy remained stable over time (i.e., no new functions were acquired); however, future research on functional stability for automatically reinforced behavior of other topographies is needed.     

A methodological investigation of the Intermodal Preferential Looking paradigm: Methods of analyses,picture selection and data rejection criteria

The Intermodal Preferential Looking paradigm provides a sensitive measure of a child's online word comprehension. To complement existing recommendations (Fernald, Zangl, Portillo, & Marchman, 2008), the present study evaluates the impact of experimental noise generated by two aspects of the visual stimuli on the robustness of familiar word recognition with and without mispronunciations: the presence of a central fixation point and the level of visual noise in the pictures (as measured by luminance saliency). Twenty-month-old infants were presented with a classic word recognition IPL procedure in 3 conditions: without a fixation stimulus (No Fixation – noisiest condition), with a fixation stimulus before trial onset (Fixation, intermediate), and with a fixation stimulus, a neutral background and equally salient images (Fixation Plus – least noisy). Data were systematically analyzed considering a range of data selection criteria and dependent variables (proportion of looking time towards the target, longest look, and time-course analysis). Critically, the expected pronunciation and naming interaction was only found in the Fixation Plus condition. We discuss the impact of data selection criteria and the dependent variable choice on the modulation of these effects across the different conditions.     

Biased judgments of the effects of speed change on travel time,fuel consumption and braking: Individual differences in the use of simplifying rules producing the same biases

The main purpose of this study was to identify different cognitive rules that lead to a particular judgment bias. To fulfill this purpose, a new method Spectral analysis was introduced and applied. Participants judged time saved by driving faster, fuel saved by replacing a car and braking capacity at different speeds. These problems invite the time saving bias (e.g., time saved from speed increases at higher speeds overestimated), the miles per gallon, MPG illusion (misjudgment of fuel saved by replacing a car) and the braking capacity bias (overestimation of braking capacity after speed increase). The average results replicated the biases. Spectral analysis of individual participants and problems showed that a speed difference rule explained about half of the time saving judgments and about three fourth of the MPG judgments. A difference between speeds rule described about one third of the biased braking judgments and a ratio/proportion rule about one fifth of the time saving and MPG judgments. All rules give biased judgments in all three domains. The paper ends with a discussion of hierarchies of cognitive rules, applications of the results, and how to mitigate or avoid the biases and the risks associated with the biases.     

An overview of applied robust methods

Data in social sciences are typically non-normally distributed and characterized by heavy tails. However, most widely used methods in social sciences are still based on the analyses of sample means and sample covariances. While these conventional methods continue to be used to address new substantive issues, conclusions reached can be inaccurate or misleading. Although there is no ‘best method’ in practice, robust methods that consider the distribution of the data can perform substantially better than the conventional methods. This article gives an overview of robust procedures, emphasizing a few that have been repeatedly shown to work well for models that are widely used in social and behavioural sciences. Real data examples show how to use the robust methods for latent variable models and for moderated mediation analysis when a regression model contains categorical covariates and product terms. Results and logical analyses indicate that robust methods yield more efficient parameter estimates, more reliable model evaluation, more reliable model/data diagnostics, and more trustworthy conclusions when conducting replication studies. R and SAS programs are provided for routine applications of the recommended robust method.     

Decomposing the social gradient in children’s vocabulary skills at 3 years of age: A mediation analysis using data from a large representative cohort study

Disparities in children’s expressive language by socio-economic status are evident early in childhood and impact children’s development and educational attainment. This study investigated the processes by which maternal education, as a powerful indicator for socio-economic status, affects early expressive language. A nationally representative cohort study of 8,062 children resident in the Republic of Ireland were assessed on the British Ability Scales (BAS) Naming Vocabulary Test at 36 months. A significant difference of almost six points was found between the mean vocabulary test scores of children whose mothers had completed the minimum level of educational attainment compared with children whose mothers had a degree-level qualification. Mediation analysis revealed that 78% of the difference was explained by mediating variables, with differences in household income, parental practice, and material resources accounting for most of the variation. The findings support interventions which redress gaps in maternal education, income, and caregiving.