15 research outputs found

    Early life predictors of adolescent suicidal thoughts and adverse outcomes in two population-based cohort studies

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    <div><p>Background</p><p>Understanding suicidality has proven challenging given the complex aetiology in early childhood. Being able to accurately predict groups at increased risk of developing suicidal thoughts may aid in the development of targeted prevention programs that mitigate increased vulnerability. Further, the predictors of suicidal thoughts may be shared with other outcomes in adolescence. Previous research has linked many factors to suicidality, so the objective of this study was to consider how these factors may act together to increase risk of suicidal thoughts and other non-mental health outcomes.</p><p>Methods</p><p>Two longitudinal datasets were used in this analysis: the <i>National Longitudinal Survey of Children and Youth</i> (NLSCY) and the <i>Avon Longitudinal Survey of Parents and Children</i> (ALSPAC). A Classification and Regression Tree model comprised of 75 factors describing early childhood was constructed to identify subgroups of adolescents at high risk of suicidal thoughts in the NLSCY and was validated in ALSPAC. These subgroups were investigated to see if they also had elevated rates of antisocial behaviour, substance misuse, poor physical health, poor mental health, risky health behaviours, and/or poor academic performance.</p><p>Results</p><p>The sensitivity was calculated to be 22·7%, specificity was 89·2%, positive predictive value 17·8%, and negative predictive value 91·8% and had similar accuracy in the validation dataset. The models were better at predicting other adverse outcomes compared to suicidal thoughts.</p><p>Conclusion</p><p>There are groups of risk factors present in early life that can predict higher risk of suicidality in adolescence. Notably, these factors were also predictive of a range of adverse outcomes in adolescence.</p></div

    Predictive factors—demographic and health characteristics, NLSCY, n = 6,388, Canada, 1994–2009.

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    <p>Predictive factors—demographic and health characteristics, NLSCY, n = 6,388, Canada, 1994–2009.</p

    Sensitivity, specificity, positive predictive value, negative predictive value for secondary outcomes for high-risk classification, NLSCY, Canada, 1994–2009.

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    <p>Sensitivity, specificity, positive predictive value, negative predictive value for secondary outcomes for high-risk classification, NLSCY, Canada, 1994–2009.</p

    Study population and analysis cohort, NLSCY CONSORT flow diagram, Canada, 1994–2009.

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    <p>Study population and analysis cohort, NLSCY CONSORT flow diagram, Canada, 1994–2009.</p

    Study population and analysis cohort, ALSPAC CONSORT flow diagram, United Kingdom, 1991–2008.

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    <p>Study population and analysis cohort, ALSPAC CONSORT flow diagram, United Kingdom, 1991–2008.</p

    Profiles of high-risk subgroups in Classification and Regression Tree model (CART), NLSCY, Canada, 1994–2009.

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    <p>Profiles of high-risk subgroups in Classification and Regression Tree model (CART), NLSCY, Canada, 1994–2009.</p

    Appendix 1 -Supplemental material for RecoverNow: A patient perspective on the delivery of mobile tablet-based stroke rehabilitation in the acute care setting

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    <p>Supplemental material, Appendix 1 for RecoverNow: A patient perspective on the delivery of mobile tablet-based stroke rehabilitation in the acute care setting by Karen Mallet, Rany Shamloul, Michael Pugliese, Emma Power, Dale Corbett, Simon Hatcher, Michel Shamy, Grant Stotts, Lise Zakutney, Sean Dukelow and Dar Dowlatshahi in International Journal of Stroke</p
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