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Mental health is a basic need for a sustainable and developing society. The prevalence and financial burden of mental illness have increased globally, and especially in response to community and worldwide pandemic events. Children suffering from such mental disorders find it difficult to cope with educational, occupational, personal, and societal developments, and treatments are not accessible to all. Advancements in technology have resulted in much research examining the use of artificial intelligence to detect or identify characteristics of mental illness. Therefore, this paper presents a systematic review of nine developmental and mental disorders (Autism spectrum disorder, Attention deficit hyperactivity disorder, Schizophrenia, Anxiety, Depression, Dyslexia, Post-traumatic stress disorder, Tourette syndrome, and Obsessive–compulsive disorder) prominent in children and adolescents. Our paper focuses on the automated detection of these developmental and mental disorders using physiological signals. This paper also presents a detailed discussion on signal analysis, feature engineering, and decision-making with their advantages, future directions and challenges on the papers published on mental disorders of children. We have presented the details of the dataset description, validation techniques, features extracted and decision-making models. The challenges and future directions present open research questions on signal or availability, uncertainty, explainability, and hardware implementation resources for signal analysis and machine or deep learning models. Finally, the main findings of this study are presented in the conclusion section.

Additional file 1: Supplementary Figure 1. Search Terms. Supplementary Table 1. Reporting of cost effectiveness analysis. Supplementary Table 2. Assessment of reporting quality of included studies using CHEERS checklist.

Supplemental material, sj-docx-1-anp-10.1177_00048674221090174 for Mental health symptoms in children and adolescents during COVID-19 in Australia by Gemma Sicouri, Sonja March, Elizabeth Pellicano, Alex C De Young, Caroline L Donovan, Vanessa E Cobham, Arlen Rowe, Simon Brett, Jeremy K Russell, Laura Uhlman and Jennifer L Hudson in Australian & New Zealand Journal of Psychiatry

Background: Anxiety disorders in children and young people are common and bring significant personal and societal costs. Over the last two decades, there has been a substantial increase in research evaluating psychological and pharmacological treatments for anxiety disorders in children and young people and exciting and novel research has continued as the field strives to improve efficacy and effectiveness, and accessibility of interventions. This increase in research brings potential to draw together data across studies to compare treatment approaches and advance understanding of what works, how, and for whom. There are challenges to these efforts due largely to variation in studies’ outcome measures and variation in the way study characteristics are reported, making it difficult to compare and/or combine studies, and this is likely to lead to faulty conclusions. Studies particularly vary in their reliance on child, parent, and/or assessor-based ratings across a range of outcomes, including remission of anxiety diagnosis, symptom reduction, and other domains of functioning (e.g., family relationships, peer relationships). Methods: To address these challenges, we convened a series of international activities that brought together the views of key stakeholders (i.e., researchers, mental health professionals, young people, parents/caregivers) to develop recommendations for outcome measurement to be used in treatment trials for anxiety disorders in children and young people. Results and Conclusions: This article reports the results of these activities and offers recommendations for selection and reporting of outcome measures to (a) guide future research and (b) improve communication of what has been measured and reported. We offer these recommendations to promote international consistency in trial reporting and to enable the field to take full advantage of the great opportunities that come from data sharing going forward.

Background Given the substantive health inequalities in peri‐urban communities and the potential for physical activity to promote health in these communities, identifying modifiable physical activity determinants in this population is important. This study explored effects of the peri‐urban environment and psychological constructs on physical activity intentions and behavioural automaticity guided by an integrated theoretical framework. Methods Peri‐urban Australians (N = 271) completed self‐report measures of environmental (i.e. physical/social environment, and neighbourhood selection), motivational (i.e. autonomous motivation), and social cognition (i.e. attitudes, norms, and perceived behavioural control [PBC]) constructs, past behaviour, intentions, and automaticity. Results A well‐fitting path analytic model revealed that: autonomous motivation predicted all social cognition constructs; subjective norms and PBC, but not attitudes; autonomous motivation predicted intentions and automaticity; and subjective norms and PBC mediated effects of autonomous motivation on intentions. Of the environmental constructs, only neighbourhood selection was related to intentions, mediated by PBC. Conclusions Autonomous motivation is an important correlate of physical activity intentions and automaticity, and subjective norms and PBC also related to intentions. Individuals perceiving a supportive environment were more likely to report positive PBC and intentions. Targeting change in autonomous motivation, and normative and control beliefs may help enhance physical activity intentions and automaticity in peri‐urban communities. peerReviewed

Background: Clinical trials are essential for the advancement of cancer treatments; however, participation by patients is suboptimal. Currently, there is a lack of synthesized qualitative review evidence on the patient experience of trial entry from which to further develop decision support. The aim of this review is to synthesise literature reporting experiences of participants when deciding to enrol in a cancer clinical trial in order to inform practice. Methods: A systematic review and meta-synthesis of qualitative studies were conducted to describe the experiences of adult cancer patients who decided to enrol in a clinical trial of an anti-cancer treatment. Results: Forty studies met eligibility criteria for inclusion. Three themes were identified representing the overarching domains of experience when deciding to enrol in a cancer trial: 1) need for trial information; (2) trepidation towards participation; and (3) justifying the decision. The process of deciding to enrol in a clinical trial is one marked by uncertainty, emotional distress and driven by the search for a cure. Conclusion: Findings from this review show that decision support modelled by shared decision-making and the quality of a shared decision needs to be accompanied by tailored or personalised psychosocial and supportive care. Although the decision process bears similarities to theoretical processes outlined in decision-making frameworks, there are a lack of supportive interventions for cancer patients that are adapted to the clinical trial context. Theory-based interventions are urgently required to support the specific needs of patients deciding whether to participate in cancer trials.

Additional file 4. Contains a forest plot for each meta-analysis conducted on each intervention type (including those with interventions from high risk of bias studies included and excluded).

Additional file 1. Contains the PRISMA checklist.

Additional file 3. Contains full table of extracted data from each study including author, date, sample size, age and country of participants, intervention type, comparison group, key findings and risk of bias.

PRISMA checklist, file contains the completed PRISMA checklist for the systematic review. (DOC 65 kb)

Background: Internet-based cognitive behavioral therapy (iCBT) for child and adolescent anxiety has demonstrated efficacy in randomized controlled trials, but it has not yet been examined when disseminated as a public health intervention. If effective, iCBT programs could be a promising first-step, low-intensity intervention that can be easily accessed by young people. Objective: The objective of our study was to examine the feasibility and acceptability of a publicly available online, self-help iCBT program (BRAVE Self-Help) through exploration of program adherence, satisfaction, and changes in anxiety. Methods: This study was an open trial involving the analysis of data collected from 4425 children and adolescents aged 7-17 years who presented with elevated anxiety at registration (baseline) for the iCBT program that was delivered through an open-access portal with no professional support. We assessed the program satisfaction via a satisfaction scale and measured adherence via the number of completed sessions. In addition, anxiety severity was assessed via scores on the Children’s Anxiety Scale, 8-item (CAS-8) at four time points: baseline, Session 4, Session 7, and Session 10. Results: Participants reported moderate satisfaction with the program and 30% completed three or more sessions. Statistically significant reductions in anxiety were evident across all time points for both children and adolescents. For users who completed six or more sessions, there was an average 4-point improvement in CAS-8 scores (Cohen d=0.87, children; Cohen d=0.81, adolescents), indicating a moderate to large effect size. Among participants who completed nine sessions, 57.7% (94/163) achieved recovery into nonelevated levels of anxiety and 54.6% (89/163) achieved statistically reliable reductions in anxiety. Conclusions: Participant feedback was positive, and the program was acceptable to most young people. Furthermore, significant and meaningful reductions in anxiety symptoms were achieved by many children and adolescents participating in this completely open-access and self-directed iCBT program. Our results suggest that online self-help CBT may offer a feasible and acceptable first step for service delivery to children and adolescents with anxiety.

Background: Despite evidence that e-mental health services are effective, consumer preferences still appear to be in favor of face-to-face services. However, the theory of planned behavior (TPB) suggests that cognitive intentions are more proximal to behavior and thus may have a more direct influence on service use. Investigating individual characteristics that influence both preferences and intentions to use e-mental health services is important for better understanding factors that might impede or facilitate the use of these services. Objective: This study explores predictors of preferences and intentions to access e-mental health services relative to face-to-face services. Five domains were investigated (demographics, technology factors, personality, psychopathology, and beliefs), identified from previous studies and informed by the Internet interventions model. We expected that more participants would report intentions to use e-mental health services relative to reported preferences for this type of support and that these 5 domains would be significantly associated with both intentions and preferences toward online services. Methods: A mixed sample of 308 community members and university students was recruited through social media and the host institution in Australia. Ages ranged between 17 and 68 years, and 82.5% (254/308) were female. Respondents completed an online survey. Chi-square analysis and t tests were used to explore group differences, and logistic regression models were employed to explore factors predicting preferences and intentions. Results: Most respondents (85.7%, 264/308) preferred face-to-face services over e-mental health services. Relative to preferences, a larger proportion of respondents (39.6%, 122/308) endorsed intentions to use e-mental health services if experiencing mental health difficulties in the future. In terms of the 5 predictor domains, 95% CIs of odds ratios (OR) derived from bootstrapped standard errors suggested that prior experience with online services significantly predicted intentions to use self-help (95% CI 2.08-16.24) and therapist-assisted (95% CI 1.71-11.90) online services in future. Being older predicted increased intentions to use therapist-assisted online services in future (95% CI 1.01-1.06), as did more confidence using computers and the Internet (95% CI 1.06-2.69). Technology confidence was also found to predict greater preference for online services versus face-to-face options (95% CI 1.24-4.82), whereas higher doctor-related locus of control, or LOC (95% CI 0.76-0.95), and extraversion (95% CI 0.88-1.00) were predictive of lower likelihood of preferring online services relative to face-to-face services. Conclusions: Despite generally low reported preferences toward e-mental health services, intentions to access these services are higher, raising the question of how to best encourage translation of intentions into behavior (ie, actual use of programs). Strategies designed to ease people into new Internet-based mental health programs (to enhance confidence and familiarity) may be important for increasing the likelihood that they will return to such programs later. [J Med Internet Res 2018;20(2):e59]

BackgroundThe advent of eHealth interventions to address psychological concerns and health behaviors has created new opportunities, including the ability to optimize the effectiveness of intervention activities and then deliver these activities consistently to a large number of individuals in need. Given that eHealth interventions grounded in a well-delineated theoretical model for change are more likely to be effective and that eHealth interventions can be costly to develop, assuring the match of final intervention content and activities to the underlying model is a key step. We propose to apply the concept of “content validity” as a crucial checkpoint to evaluate the extent to which proposed intervention activities in an eHealth intervention program are valid (eg, relevant and likely to be effective) for the specific mechanism of change that each is intended to target and the intended target population for the intervention. ObjectiveThe aims of this paper are to define content validity as it applies to model-based eHealth intervention development, to present a feasible method for assessing content validity in this context, and to describe the implementation of this new method during the development of a Web-based intervention for children. MethodsWe designed a practical 5-step method for assessing content validity in eHealth interventions that includes defining key intervention targets, delineating intervention activity-target pairings, identifying experts and using a survey tool to gather expert ratings of the relevance of each activity to its intended target, its likely effectiveness in achieving the intended target, and its appropriateness with a specific intended audience, and then using quantitative and qualitative results to identify intervention activities that may need modification. We applied this method during our development of the Coping Coach Web-based intervention for school-age children. ResultsIn the evaluation of Coping Coach content validity, 15 experts from five countries rated each of 15 intervention activity-target pairings. Based on quantitative indices, content validity was excellent for relevance and good for likely effectiveness and age-appropriateness. Two intervention activities had item-level indicators that suggested the need for further review and potential revision by the development team. ConclusionsThis project demonstrated that assessment of content validity can be straightforward and feasible to implement and that results of this assessment provide useful information for ongoing development and iterations of new eHealth interventions, complementing other sources of information (eg, user feedback, effectiveness evaluations). This approach can be utilized at one or more points during the development process to guide ongoing optimization of eHealth interventions.