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The COVID-19 pandemic has fast-tracked interest in telehealth methods to guarantee the continuity of care of children with Autism Spectrum Disorder (ASD). Store-and-forward telehealth approaches offer the opportunity to facilitate timely screening of ASD, allowing parents to record videos of their child’s behaviors, subsequently shared with clinicians that provide an assessment remotely. This study aimed to examine the psychometric properties of a new telehealth screening tool, the teleNIDA, administered in home settings for remote observation of early signs of ASD in toddlers aged 18–30 months. Results showed good psychometric properties of the teleNIDA, as compared to the gold standard in-person assessment, and the predictive validity on the diagnosis of ASD at 36 months was demonstrated. This study supports the teleNIDA as a promising level 2 screening tool for ASD able to speed up diagnostic and intervention processes.

Tumor pathology is a bio-psycho-social event that has consequences for a person's life from all points of view, physical, psychological, relational and social. The mental discomfort that chronic pain and neoplastic pathology brings with it is present in 25-40% of cases, but the request for help to a psychologist, where not provided for by a specific diagnostic therapeutic assistance path, is in the case of medical pathologies less than 3%. The Piedmont and Valle d'Aosta Oncology Network has the role of coordinating the network of services that deal with the care of the cancer patient, including those relating to psycho-oncology. The article presents data relating to the activities of psycho-oncologists of the Network in the years 2017, 2018 and 2019.A shared tool is used to collect the data, a database, made up of various variables deemed necessary to be able to photograph the activities carried out by the psycho-oncologists belonging to the Network. The database has been the subject of comparison between psychologists and has led to continuous revisions of the tool from 2017 to 2019, more accurate version.The 3-year study involved 2188 (2017), 3341 (2018) and 3457 (2019) adult patients or their families treated by psycho-oncologists. Patients are predominantly female with breast cancer, married/cohabiting, whose pre-eminent discomfort is anxiety, combined with the depressive component. The psychological intervention is mainly psychological support (level 2).Psychological management is an important intervention in the path of the cancer patient. The systematic collection of data made it possible to detect an increase in patients who accessed the psycho-oncology service, from an estimate of 1/3% in 2009 to 4.6% in 2018/2019.

Feasibility, acceptability and effectiveness data of a virtual adaptation of the WHO Caregiver Skills Training (CST; n = 25) were compared with those of a pilot RCT of CST delivered in person (n = 43) against treatment as usual (TAU; n = 43). Virtual CST was delivered with high levels of integrity, but received lower ratings in some caregiver- and facilitator-rated acceptability and feasibility dimensions. Qualitative analysis identified both benefits (flexibility, convenience, clinical usefulness) and challenges, (technological issues, distraction from family members, emotional distance). Virtual and in-person CST improved significantly more on caregiver competence than TAU; there were no other significant effects. Potential for use of virtual CST as a clinical response in contexts where in-person delivery is not possible is discussed.

In the past two decades, several screening instruments were developed to detect toddlers who may be autistic both in clinical and unselected samples. Among others, the Quantitative CHecklist for Autism in Toddlers (Q-CHAT) is a quantitative and normally distributed measure of autistic traits that demonstrates good psychometric properties in different settings and cultures. Recently, machine learning (ML) has been applied to behavioral science to improve the classification performance of autism screening and diagnostic tools, but mainly in children, adolescents, and adults. In this study, we used ML to investigate the accuracy and reliability of the Q-CHAT in discriminating young autistic children from those without. Five different ML algorithms (random forest (RF), naïve Bayes (NB), support vector machine (SVM), logistic regression (LR), and K-nearest neighbors (KNN)) were applied to investigate the complete set of Q-CHAT items. Our results showed that ML achieved an overall accuracy of 90%, and the SVM was the most effective, being able to classify autism with 95% accuracy. Furthermore, using the SVM–recursive feature elimination (RFE) approach, we selected a subset of 14 items ensuring 91% accuracy, while 83% accuracy was obtained from the 3 best discriminating items in common to ours and the previously reported Q-CHAT-10. This evidence confirms the high performance and cross-cultural validity of the Q-CHAT, and supports the application of ML to create shorter and faster versions of the instrument, maintaining high classification accuracy, to be used as a quick, easy, and high-performance tool in primary-care settings.

Background: The Quantitative Checklist for Autism in Toddlers (Q-CHAT) is parent-report screening questionnaire for detecting threshold and sub-threshold autistic features in toddlers. The Q-CHAT is a dimensional measure normally distributed in the general population sample and is able to differentiate between a group of children with a diagnosis of autism and unselected toddlers. Objectives: We aim to investigate the psychometric properties, score distribution, and external validity of the Q-CHAT in an Italian clinical sample of young children with autism versus children with developmental delay and typically developing children. Method: N = 126 typically developing children (TD), n = 139 children with autism, and n = 50 children presenting developmental delay (DD) were administered the Q-CHAT. Standardized measures of cognitive functions, language, and behaviors were also obtained. Results: The Q-CHAT scores were normally distributed and demonstrated adequate internal consistency and good item to total score correlations. The mean Q-CHAT score in the autism group was significantly higher than those found in the DD sample and TD children. No difference on the mean Q-CHAT score between DD and TD children was found. The accuracy of the Q-CHAT to discriminate between autism and TD was very good. Two different cut-points (27 and 31, respectively) maximized sensitivity and specificity for autism versus TD and DD, respectively. Finally, higher Q-CHAT scores were correlated with lower language and social communication skills. Conclusions: In clinical settings, the Q-CHAT demonstrated good psychometric properties and external validity to discriminate autism children not just from children with typical development but also from children with developmental delay.

Applied Computer technologies can address the needs of individuals with autism spectrum disorders (ASD). Data on the efficacy of assistive technology in ASD is limited, and its effectiveness in supporting and facilitating skill acquisition in this specific population must be still demonstrated. 63 Italian ASD subjects underwent learning activities administered by cardboards or a touch screen support. The support preference was evaluated in a choice trial, and quantitative analysis was performed on items regarding communication and challenging behaviours. Touch devices are attractive especially for males without intellectual disability and a lower communication and cooperation behaviours with the use of touch screen compared with paper support was shown depending on activities. Overall, our data do not confirm the hypothesis that touch screen presentation improves activity completion and behavioural performance for each individual with ASD. Data discourage an indiscriminate use of these devices and suggest analysing with more attention the core ingredients that should shape digital devices when used for people on ASD.

Background In the past decade, several screening instruments have been developed to detect toddlers at risk for autism, both in clinical and unselected samples.We aimed to assess the validity and cross-cultural stability of the Quantitative CHecklist for Autism in Toddlers (Q−CHAT), a quantitative and normally distributed measure of autistic traits, during routine paediatric developmental surveillance in a large Italian community of toddlers. Methods A group of n = 2400 unselected Italian toddlers were screened by paediatricians during routine well−CHild visits between 18 and 24 months,in three Italian regions, representative of the North, Centre and South of Italy. The psychometric properties and factor structure of the Q−CHAT were explored and compared with published literature from Asia and the UK. Results The total Q−CHAT scores in our sample confirmed a normal distribution. Mean Q−CHAT scores across regions were consistent with those reported in UK studies and likewise, a gender effect was found, with boys scoring higher than girls.We also found a remarkable consistency with the three-factor structure of the Asian Q−CHAT. Internal consistency was acceptable for both the Q−CHAT total score and the three factors. Conclusions Our results confirm the dimensional distribution of autistic traits and related symptoms in unselected populations across different cultures. The Q−CHAT is a valid and reliable dimensional screening instrument to be used within a routine paediatric setting during well-child assessments.The main normative data and factor structure replicated in our sample

It has been reported that people tend to preferentially associate phonemes like /m/, /l/, /n/ to curvilinear shapes and phonemes like /t/, /z/, /r/, /k/ to rectilinear shapes. Here we evaluated the performance of children/adolescents with autism spectrum disorders (ASD) and neurotypical controls in this audiovisual congruency phenomenon. Pairs of visual patterns (curvilinear vs rectilinear) were presented to a group of ASD participants (low- or high-functioning) and a group of age-matched neurotypical controls. Participants were asked to associate each item to non-meaningful phoneme clusters. ASD participants showed a lower proportion of expected association responses than the controls. Within the ASD group the performance varied as a function of the severity of the symptomatology. These data suggest that children/adolescents with ASD show, although at different degrees as a function of the severity of the ASD, lower phonetic-iconic congruency response patterns than neurotypical controls, pointing to poorer multisensory integration capabilities.