Subjects: Psychology >> Social Psychology submitted time 2023-03-28 Cooperative journals: 《心理科学进展》
Abstract： The purpose of screening research is to provide a comprehensive understanding about the risks of early identification of autism spectrum disorder. This study comprehensively and systematically reviewed the commonly-used screening tools for early detection of autism in infants and preschool children. Under the guidelines of the Preferred Reporting Items for Systematic review and Meta-Analysis (PRISMA), we queried the topic “screening tools for autism spectrum disorder” against the three major literature retrieval databases (WOS, Scopus, PubMed) and obtained 175 articles, of which 35 articles and 18 corresponding screening tools were further evaluated to comply with the Quality Assessment of Diagnostic Accuracy Studies-2 (QUADAS-2) checklist. These tools were analyzed from the aspects of application level, psychometric and measurement properties, cultural adaptability, diagnostic criteria and classification accuracy. From the aspect of application level, the screening tools were categorized into three levels based on the types of screening samples, wherein Level- I screening tools, totaling up to 4, focus on general-purpose screening of population and the examination of other developmental disorders, and the evaluation is mainly based on the reports from parents; Level-II screening tools, totaling up to 8, were mainly based on the clinical reports from well-trained clinicians or the observations from the interactions between trained professionals and children; the hybrid-level screening tools, totaling up to 6, were based on the Level-I general population and the Level-II clinical samples. From the aspect of psychometric and measurement properties, existing studies only adopted several metrics of reliability and validity, e.g., internal consistency reliability, rater reliability, test-retest reliability and criterion validity, to evaluate the psychometric properties of screening tools,, whereas the other metrics such as split half reliability, measurement error, content validity, structural validity, cross-cultural validity and hypothesis test were seldom adopted except in only a few studies, and one-third studies did not carry out any psychometric evaluation, potentially resulting in the high-risk bias of QUADAS-2. From the aspect of cultural adaptability, the series of M-CHAT tools（M-CHAT, M-CHAT/F,M-CHAT-R/F）, subjected to extensive evaluation in multiple languages, have demonstrated obvious cultural adaptability, and were recognized as the most widely-used and the most famous screening tool based on parent reports. However, there is an increasing trend that screening tools developed to be localized to the culture and languages in communities or countries with scarce resources. From the aspect of diagnostic standards, the DSM-IV or DSM-IV-TR (accounting for 43%) were still used as the main reference standard instead of the DSM-5 manual (accounting for 34%). It was concluded from sensitivity and specificity that the tools for preschool children outperform those for infants in terms of classification accuracy. The tools rated as good level for infants include M-CHAT-R/F and PDQ-1, and the tools rated as excellent level for children include OERA and TIDOS, wherein M-CHAT-R / F is one of the most promising screening tools for estimating the risks of autism spectrum disorder. Lastly, we discussed the limitations of QUADAS-2 and the necessity of choosing stringent quality assessment measures and the importance of further validating these measurements.
Subjects: Psychology >> Social Psychology submitted time 2023-03-28 Cooperative journals: 《心理科学进展》
Abstract： Many enterprises have adopted AI services to respond to customer needs, yet several studies indicate that users are not always satisfied with AI in service. This study explores the key factors that drive users' attitudes toward AI services and usage promotion strategies based on the generation and influence of users' mind perceptions of AI, which including (1) Mechanism analysis: How do the cues and experiential factors of users' early contact with AI lead to the perception that AI is “good at computing but not feeling”? This study argues that past frustrations with AI in emotional-social service scenarios and mass media portrayals of AI as “highly intelligent and low in emotional intelligence” have led users to develop the perception that AI is good at computation but lacks feelings. This makes users willing to use AI for functional purposes only in cognitive-analytical tasks, but not like to establish empathic connections with AI in emotional-social tasks. (2) Moderating effects: How do different internal user states and external AI features moderate the formation and activation of this mind perception toward AI? This study believes that higher frequency of AI use and technology use self-efficacy make individuals more likely to establish para-friendship relationships with AI, those two factors that inhibit the formation of mind perceptions that users believe AI is good at computing but lacks feeling. On the other hand, the degree of anthropomorphism and the degree of flexibility in the task influenced individuals' cognitive cues to AI, those two factors that inhibit the activation of the user's mind perception toward AI. (3) Facilitation strategies: With the reverse utilization of mind perception, how can the mimicry of AI as warmth animals and the provision of technical assistance enable users to accept services from AI in a wider range of scenarios? This study proposes that by designing an information framework that demonstrates the computational power of AI and at the same time, mimics AI as an animal with “high warmth” quality, it can reconcile the paradox of “AI is good at computation but lacks feeling” and promote the user's perception of AI's empathic ability. This will increase users' willingness to use AI in emotional-social tasks. On the other hand, providing users with tips and technical assistance when interacting with AI can help build a joint interaction model between AI and humans, reduce users' concerns about AI's lack of empathic capacity, and increase people's willingness to use AI in emotional-social tasks. This study attempts to construct a new model of AI service acceptance based on the theory of mind perception at the theoretical level and provide a psychological reference for theoretically explaining users' ambivalent attitudes toward AI services. At the practical level, this study attempts to propose two pathways to facilitate users' acceptance of AI services with the help of mind perception theory and provide a technical reference for enterprises to enhance the effectiveness of AI applications in their service processes.
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