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Prediction models for child and adolescent mental health: A systematic review of methodology and reporting in recent research
11 references·0 citing·46 second hopsampled
Prediction models for child and adolescent mental health: A systematic review of methodology and reporting in recent research (2021)Prediction models for child and adolescen…Predicting mental health problems in adolescence using machine learning techniques (2020)Predicting mental health prob…The epidemiology of trauma and post-traumatic stress disorder in a representative cohort of young people in England and Wales (2019)The epidemiology of trauma an…Algorithmic Justice in Child Protection: Statistical Fairness, Social Justice and the Implications for Practice (2019)Algorithmic Justice in Child …PROBAST: A Tool to Assess the Risk of Bias and Applicability of Prediction Model Studies (2018)PROBAST: A Tool to Assess the…Predicting suicide attempts in adolescents with longitudinal clinical data and machine learning (2018)Predicting suicide attempts i…Predicting Suicide Attempts and Suicide Deaths Following Outpatient Visits Using Electronic Health Records (2018)Predicting Suicide Attempts a…Transparent reporting of a multivariable prediction model for individual prognosis or diagnosis (TRIPOD): the TRIPOD statement (2015)Transparent reporting of a mu…Transparent reporting of a multivariable prediction model for individual prognosis or diagnosis (TRIPOD): The TRIPOD statement (2015)Transparent reporting of a mu…A comparative study of violence risk assessment tools: A systematic review and metaregression analysis of 68 studies involving 25,980 participants (2010)A comparative study of violen…Preferred Reporting Items for Systematic Reviews and Meta-Analyses: The PRISMA Statement (2009)Preferred Reporting Items for…Preferred reporting items for systematic reviews and meta-analyses: the PRISMA statement (2009)Preferred reporting items for…Preferred Reporting Items for Systematic Reviews and Meta-Analyses: The PRISMA Statement (2009)Preferred reporting items for systematic reviews and meta-analyses: the PRISMA Statement. 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(2020)PROBAST+AI: an updated quality, risk of bias, and applicability assessment tool for prediction models using regression or artificial intelligence methods (2025)Trauma and Posttraumatic Stress Disorder in the Community (1998)Meta-analysis of risk factors for posttraumatic stress disorder in trauma-exposed adults. (2000)Diagnostic and Statistical Manual of Mental Disorders (2013)Annual Research Review: Rethinking childhood trauma‐new research directions for measurement, study design and analytical strategies (2019)The effects of early life adversity on children’s mental health and cognitive functioning (2022)Treatment with psychedelics is psychotherapy: beyond reductionism (2023)Adolescence-limited and life-course-persistent antisocial behavior: A developmental taxonomy. 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References

  • 2009Preferred reporting items for systematic reviews and meta-analyses: the PRISMA statement83,813 cited
  • 2009Preferred Reporting Items for Systematic Reviews and Meta-Analyses: The PRISMA Statement63,979 cited
  • 2015Transparent reporting of a multivariable prediction model for individual prognosis or diagnosis (TRIPOD): the TRIPOD statement4,367 cited
  • 2015Transparent reporting of a multivariable prediction model for individual prognosis or diagnosis (TRIPOD): The TRIPOD statement3,296 cited
  • 2018PROBAST: A Tool to Assess the Risk of Bias and Applicability of Prediction Model Studies2,953 cited
  • 2010A comparative study of violence risk assessment tools: A systematic review and metaregression analysis of 68 studies involving 25,980 participants662 cited
  • 2019The epidemiology of trauma and post-traumatic stress disorder in a representative cohort of young people in England and Wales512 cited
  • 2018Predicting Suicide Attempts and Suicide Deaths Following Outpatient Visits Using Electronic Health Records399 cited
  • 2018Predicting suicide attempts in adolescents with longitudinal clinical data and machine learning263 cited
  • 2020Predicting mental health problems in adolescence using machine learning techniques189 cited
  • 2019Algorithmic Justice in Child Protection: Statistical Fairness, Social Justice and the Implications for Practice109 cited

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