Comparing mental health disorders among sex trafficked children and three groups of youth at high-risk for trafficking: A dual retrospective cohort and scoping review

BACKGROUND Mental health disorders across the life span are a leading cause of medical disabilities. This burden is particularly significant in children and adolescents due to challenges in diagnoses and lack of precision medicine approaches. The advent and widespread adoption of wearable devices (e.g., smartwatches) that generate large volumes of passively collected data that are conducive for artificial intelligence applications to remotely diagnose and manage child and adolescent mental health disorders is promising. OBJECTIVE This study conducted a scoping review to study, characterize and identify areas of innovations with wearable devices that can augment current in-person physician assessments to individualize diagnosis and management of mental health disorders in child and adolescent psychiatry. METHODS This scoping review used PRISMA’s information as a guide. A comprehensive search of several databases from 2011 to June 25, 2021, limited to English language and excluding animal studies, was conducted. The databases included Ovid MEDLINE (R) and Epub Ahead of Print, In-Process & Other Non-Indexed Citations and Daily, Ovid Embase, Ovid Cochrane Central Register of Controlled Trials, Ovid Cochrane Database of Systematic Reviews, Web of Science, and Scopus. RESULTS The initial search yielded 344 articles. 19 articles were left on the final source list for this scoping review. Articles were divided into three main groups: Studies with the main focus on Autism Spectrum Disorder (ASD), Attention Deficit Hyperactivity Disorders (ADHD) and Internalizing disorders such as anxiety disorders. Majority of the studies used either ECG strap or wrist worn biosensor. CONCLUSIONS Our scoping review found large heterogeneity of methods and findings in artificial intelligence studies in child psychiatry. Overall, the largest gaps identified in this scoping review are the lack of randomized control trials, most available studies are pilot feasibility trials.

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High-risk sexual behaviour in young people with mental health disorders

Early Intervention in Psychiatry ◽

10.1111/eip.12688 ◽

2018 ◽

Vol 13 (4) ◽

pp. 867-873 ◽

Cited By ~ 5

Author(s):

Asiel Yair Adan Sanchez ◽

Elizabeth McMillan ◽

Amit Bhaduri ◽

Nancy Pehlivan ◽

Katherine Monson ◽

...

Keyword(s):

Mental Health ◽

High Risk ◽

Young People ◽

Sexual Behaviour ◽

Mental Health Disorders ◽

High Risk Sexual Behaviour ◽

Health Disorders ◽

Risk Sexual Behaviour

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82 Defining overdiagnosis of mental health disorders: secondary analysis of an overdiagnosis scoping review

10.1136/bmjebm-2018-111070.82 ◽

2018 ◽

Author(s):

Kimberly Turner ◽

Ian Shrier ◽

Brett Thombs

Keyword(s):

Mental Health ◽

Scoping Review ◽

Secondary Analysis ◽

Mental Health Disorders ◽

Health Disorders

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Overview of the role of big data in mental health: A scoping review (Preprint)

10.2196/preprints.32424 ◽

2021 ◽

Author(s):

Arfan Ahmed ◽

Sarah Aziz ◽

Marco Angus ◽

Mahmood Alzubaidi ◽

Alaa Abd-Alrazaq ◽

...

Keyword(s):

Mental Health ◽

Machine Learning ◽

Big Data ◽

Scoping Review ◽

Mental Health Disorders ◽

Machine Learning Techniques ◽

Support Vector ◽

Great Effort ◽

Scoping Reviews ◽

Health Disorders

BACKGROUND Big Data offers promise in the field of mental health and plays an important part when it comes to automation, analysis and prevention of mental health disorders OBJECTIVE The purpose of this scoping review is to explore how big data was exploited in mental health. This review specifically addresses both the volume, velocity, veracity and variety of collected data as well as how data was attained, stored, managed, and kept private and secure. METHODS Six databases were searched to find relevant articles. PRISMA Extension for Scoping Reviews (PRISMA-ScR) was used as a guideline methodology to develop a comprehensive scoping review. RESULTS General and Big Data features were extracted from the studies reviewed. Various technologies were noted when it comes to using Big Data in mental health with depression and anxiety being the focus of most of the studies. Some of these included Machine Learning (ML) models in 22 studies of which Random Forest (RF) was the most widely used. Logistic Regression (LR) was used in 4 studies, and Support Vector Machine (SVM) was used in 3 studies. CONCLUSIONS In order to utilize Big Data as a way to mitigate mental health disorders and prevent their appearance altogether a great effort is still needed. Integration and analysis of Big Data, doctors and researchers alike can find patterns in otherwise difficult to identify data by making use of AI and Machine Learning techniques. Similarly, machine learning and artificial intelligence can be used to automate the analytical process.

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Male farmers with mental health disorders: A scoping review

Australian Journal of Rural Health ◽

10.1111/ajr.12008 ◽

2013 ◽

Vol 21 (1) ◽

pp. 3-7 ◽

Cited By ~ 22

Author(s):

Philippe Roy ◽

Gilles Tremblay ◽

John L. Oliffe ◽

Jalila Jbilou ◽

Steve Robertson

Keyword(s):

Mental Health ◽

Scoping Review ◽

Mental Health Disorders ◽

Health Disorders

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A scoping review of evaluated interventions addressing developmental transitions for youth with mental health disorders

Child Care Health and Development ◽

10.1111/cch.12306 ◽

2015 ◽

Vol 42 (2) ◽

pp. 176-187 ◽

Cited By ~ 15

Author(s):

B. Di Rezze ◽

T. Nguyen ◽

G. Mulvale ◽

N. G. Barr ◽

C. J. Longo ◽

...

Keyword(s):

Mental Health ◽

Scoping Review ◽

Mental Health Disorders ◽

Developmental Transitions ◽

Health Disorders

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Associations between residence at birth and mental health disorders: a spatial analysis of retrospective cohort data

BMC Public Health ◽

10.1186/s12889-015-2011-z ◽

2015 ◽

Vol 15 (1) ◽

Cited By ~ 6

Author(s):

Kate Hoffman ◽

Ann Aschengrau ◽

Thomas F. Webster ◽

Scott M. Bartell ◽

Verónica M. Vieira

Keyword(s):

Mental Health ◽

Spatial Analysis ◽

Retrospective Cohort ◽

Mental Health Disorders ◽

Cohort Data ◽

Health Disorders

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Assessment of mental health in adults of the northern part of the city of Kosovska Mitrovica

Vojnosanitetski pregled ◽

10.2298/vsp1209747m ◽

2012 ◽

Vol 69 (9) ◽

pp. 747-752

Author(s):

Momcilo Mirkovic ◽

Snezana Simic ◽

Goran Trajkovic

Keyword(s):

Mental Health ◽

High Risk ◽

Mental Health Problems ◽

Mental Health Disorders ◽

Health Problems ◽

Older Age ◽

Alpha Coefficient ◽

Financial Situation ◽

Health Disorders ◽

Political Security

Background/Aim. Mental health disorders lead to disorder of effective functioning of people and deterioration of quality of life. Early detection of individuals at risk of mental health disorders is extremely important from the aspect of mental health disorders prevention. The aim of the research was to determine the frequency of mental health problems among adult residents of northern Kosovska Mitrovica and to examine the association between frequency of mental health problems and socio-demographic and other characteristics of the population obtained by the questionnaire. Methods. The cross-sectional study on the representative sample of adult residents of northern Kosovska Mitrovica was performed in October 2009. To obtain information about the characteristics of mental health the Goldberg?s General Health Questionnaire (GHQ-28) was used. For performing survey at site the method of rapid epidemiological assessment was chosen. Statistical analysis included the methods of descriptive statistics, multivariate regression analysis and calculation of the Cronbach?s alpha coefficient of internal consistency of the questionnaire. Results. Mental health problems (total score) were present in almost half of the respondents (49.2%). Psychosomatic problems were present in more than half of the respondents (55.4%), while anxiety and insomnia were present in almost half of the respondents (49.2%). Social dysfunction had more than three fifths of the respondents (63.1%) and depression more than a quarter of the respondents (28.5%). More positive responses in the questionnaire were statistically significantly associated with older age, poor financial situation, abuse and assessing of the current political-security situation as high risk. The value of Cronbach?s alpha coefficient was 0.705. Conclusions. Almost half of the respondents (49.2%) of North Kosovska Mitrovica had mental health problems. Mental health problems were associated with older age, poor financial situation, abuse and considering the current political security situation as high-risk factor.

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