Child and adolescent psychiatry is in a unique position to respond to the growing public health challenges associated with the large number of mental disorders arising early in life, but some changes may be necessary to meet these challenges. In this context, the future of child and adolescent psychiatry was considered by the Section on Child and Adolescent Psychiatry of the World Psychiatric Association (WPA CAP), the International Association for Child and Adolescent Psychiatry and Allied Professions (IACAPAP), the World Association for Infant Mental Health (WAIMH), the International Society for Adolescent Psychiatry and Psychology (ISAPP), the UN Special Rapporteur on the Right to Health, representatives of the WHO Department of Mental Health and Substance Abuse, and other experts. We take this opportunity to outline four consensus priorities for child and adolescent psychiatry over the next decade: increase the workforce necessary for providing care for children, adolescents and families facing mental disorders; reorienting child and adolescent mental health services to be more responsive to broader public health needs; increasing research and research training while also integrating new research finding promptly and efficiently into clinical practice and research training; Increasing efforts in advocacy.

The aim of this present study was to compare the prevalence and type of trauma experienced by community sample with the outpatient sample with mental disorders. A total of 354 outpatients, aged 14–35 years old, with mood disorders, schizophrenia and other psychotic disorders, adjustment disorder and anxiety disorder were recruited from a tertiary psychiatric hospital. A total of 100 healthy controls were recruited from the Singapore general population by snowballing. The Childhood Trauma Questionnaire-Short Form (CTQ-SF) designed to measure childhood trauma and the severity (e.g., physical abuse, emotional abuse, sexual abuse, physical neglect and emotional neglect) was administered to participants. Socio-demographic and clinical characteristics were obtained from interviews with the participants and from outpatients’ medical records, respectively. Independent sample t tests and Chi-square tests were used to investigate the differences between the outpatient and community samples. Overall the CTQ-SF total and domain scores indicated that outpatient sample experienced higher rate of traumatic life events in childhood than community sample. Two most reported trauma types were emotional abuse (n = 81, 59.1%) and physical neglect (n = 74, 54%) reported by the mood disorder group. In the community sample, emotional neglect (n = 46, 46%) and physical neglect (n = 18, 18%) were the most commonly reported trauma type. Overall outpatient sample (n = 80, 22.6%) and community sample (n = 28, 28%) reported at least one type of trauma. The findings indicate higher rates of CTQ-SF total and domain scores in outpatient sample demonstrating a higher rate of traumatic life events in childhood compared to community sample. Further research in childhood trauma is needed to improve the knowledge in psychiatric clinic practices.

Attention Deficit Hyperactivity problem (ADHD) is a common neurodevelopment problem in children and adolescents that can lead to long-term challenges in life outcomes if left untreated. Also, ADHD is frequently associated with Conduct Disorder (CD), and multiple research have found similarities in clinical signs and behavioral symptoms between both diseases, making differentiation between ADHD, ADHD comorbid with CD (ADHD+CD), and CD a subjective diagnosis. Therefore, the goal of this pilot study is to create the first explainable deep learning (DL) model for objective ECG-based ADHD/CD diagnosis as having an objective biomarker may improve diagnostic accuracy. The dataset used in this study consist of ECG data collected from 45 ADHD, 62 ADHD+CD, and 16 CD patients at the Child Guidance Clinic in Singapore. The ECG data were segmented into 2 s epochs and directly used to train our 1-dimensional (1D) convolutional neural network (CNN) model. The proposed model yielded 96.04% classification accuracy, 96.26% precision, 95.99% sensitivity, and 96.11% F1-score. The Gradient-weighted class activation mapping (Grad-CAM) function was also used to highlight the important ECG characteristics at specific time points that most impact the classification score. In addition to achieving model performance results with our suggested DL method, Grad-CAM's implementation also offers vital temporal data that clinicians and other mental healthcare professionals can use to make wise medical judgments. We hope that by conducting this pilot study, we will be able to encourage larger-scale research with a larger biosignal dataset. Hence allowing biosignal-based computer-aided diagnostic (CAD) tools to be implemented in healthcare and ambulatory settings, as ECG can be easily obtained via wearable devices such as smartwatches.

This study aims to understand (a) the prevalence and correlates of smoking in a psychiatric population, (b) factors that encourage smoking cessation, and (c) awareness towards cessation programmes. This study captured data (n = 380) through a modified version of the Global Adult Tobacco Survey (GATS). A descriptive analysis of the data was performed. The prevalence of smoking was 39.5% (n = 150) and 52.3% of the smokers were dependent on nicotine. More than half of the smokers had made at least one attempt to quit in the past 12 months and 56% reported no immediate plans to quit smoking. The awareness towards institutional smoking cessation programmes was fair (44%), with 49.7% of smokers having indicated that they were willing to use the service upon referral. Smokers endorsed that increasing the cost of cigarettes, restricting availability, and increasing knowledge of health harms could encourage smoking cessation. Past smokers reported that self-determination/willpower followed by substitution of smoking with other types of foods and drinks were factors that helped them achieve successful cessation. Given that the readiness to quit and awareness towards cessation programmes are low among the smokers, concerted efforts through educational programmes and policy changes are crucial to achieve successful cessation.

Background: Studies on gender differences in attention-deficit/hyperactivity disorder (ADHD) comorbidities in the Asian populations have been limited and previous studies have shown inconclusive findings. Singapore is a city-state country in Southeast Asia with a population of 5.7 million. This study examined gender differences in internalizing and externalizing problems in Singaporean children and adolescents with ADHD. The plausible social factors underlying the gender differences were discussed.Methods: A total of 773 participants (aged 6 to 18, 88% males) newly diagnosed with ADHD were recruited from the largest public child and adolescent psychiatric center in Singapore. Their internalizing and externalizing problems were assessed using the Child Behavioral Checklist and Teacher’s Report Form by parents and teachers respectively. Demographics and relevant social factors were collected using parent questionnaires.Results: Females with ADHD were reported to have less delinquent and aggressive behavior but more depressive symptoms than their male counterparts, similar to findings in the Western literature. Gender remained a significant predictor of externalizing problem after controlling for other factors. Lower socioeconomic status and parental use of physical punishment were significant predictors of both internalizing and externalizing problems.Conclusions: Gender differences in ADHD comorbidities do exist in the Asian clinical population. The lack of externalizing symptoms in females with ADHD has made timely referral and diagnosis challenging. More research is needed in understanding the gender differences in ADHD and the biopsychosocial mechanism underlying the differences in order to improve the detection of ADHD in females.

Background: Automatic processes, such as attentional biases or interpretative biases, have been purported to be responsible for several psychiatric disorders. Recent reviews have highlighted that cognitive biases may be modifiable. Advances in eHealth and mHealth have been harnessed for the delivery of cognitive bias modification. While several studies have evaluated mHealth-based bias modification intervention, no review, to our knowledge, has synthesized the evidence for it. In addition, no review has looked at commercial apps and their functionalities and methods of bias modification. A review is essential in determining whether scientifically validated apps are available commercially and the proportion of commercial apps that have been evaluated scientifically. Objective: The objective of this review was primarily to determine the proportion of attention or cognitive bias modification apps that have been evaluated scientifically and secondarily to determine whether the scientifically evaluated apps were commercially available. We also sought to identify commercially available bias modification apps and determine the functionalities of these apps, the methods used for attention or cognitive bias modification, and whether these apps had been evaluated scientifically. Methods: To identify apps in the published literature, we searched PubMed, MEDLINE, PsycINFO, and Scopus for studies published from 2000 to April 17, 2018. The search terms used were “attention bias” OR “cognitive bias” AND “smartphone” OR “smartphone application” OR “smartphone app” OR “mobile phones” OR “mobile application” OR mobile app” OR “personal digital assistant.” To identify commercial apps, we conducted a manual cross-sectional search between September 15 and 25, 2017 in the Apple iTunes and Google Play app stores. The search terms used to identify the apps were “attention bias” and “cognitive bias.” We also conducted a manual search on the apps with published evaluations. Results: The effectiveness of bias modification was reported in 7 of 8 trials that we identified in the published literature. Only 1 of the 8 previously evaluated apps was commercially available. The 17 commercial apps we identified tended to use either an attention visual search or gamified task. Only 1 commercial app had been evaluated in the published literature. Conclusions: This is perhaps the first review to synthesize the evidence for published mHealth attention bias apps. Our review demonstrated that evidence for mHealth attention bias apps is inconclusive, and quite a few commercial apps have not been validated scientifically.