Developing and validating a prediction model of adolescent major depressive disorder in the offspring of depressed parents / Alice STEPHENS in Journal of Child Psychology and Psychiatry, 64-3 (March 2023)  

Public ISBD [article]  inJournal of Child Psychology and Psychiatry > 64-3 (March 2023) . - p.367-375 Titre : Developing and validating a prediction model of adolescent major depressive disorder in the offspring of depressed parents Type de document : Texte imprimé et/ou numérique Auteurs : Alice STEPHENS, Auteur ; Judith ALLARDYCE, Auteur ; Bryony WEAVERS, Auteur ; Jessica LENNON, Auteur ; Rhys BEVAN JONES, Auteur ; Victoria POWELL, Auteur ; Olga EYRE, Auteur ; Robert POTTER, Auteur ; Valentina ESCOTT PRICE, Auteur ; David OSBORN, Auteur ; Anita THAPAR, Auteur ; Stephan COLLISHAW, Auteur ; Ajay K. THAPAR, Auteur ; Jon HERON, Auteur ; Frances RICE, Auteur Article en page(s) : p.367-375 Langues : Anglais (eng) Index. décimale : PER Périodiques Résumé : Background Parental depression is common and is a major risk factor for depression in adolescents. Early identification of adolescents at elevated risk of developing major depressive disorder (MDD) in this group could improve early access to preventive interventions. Methods Using longitudinal data from 337 adolescents at high familial risk of depression, we developed a risk prediction model for adolescent MDD. The model was externally validated in an independent cohort of 1,384 adolescents at high familial risk. We assessed predictors at baseline and MDD at follow-up (a median of 2-3 years later). We compared the risk prediction model to a simple comparison model based on screening for depressive symptoms. Decision curve analysis was used to identify which model-predicted risk score thresholds were associated with the greatest clinical benefit. Results The MDD risk prediction model discriminated between those adolescents who did and did not develop MDD in the development (C-statistic=.783, IQR (interquartile range)=.779, .778) and the validation samples (C-statistic=.722, IQR=â’.694, .741). Calibration in the validation sample was good to excellent (calibration intercept=.011, C-slope=.851). The MDD risk prediction model was superior to the simple comparison model where discrimination was no better than chance (C-statistic=.544, IQR=.536, .572). Decision curve analysis found that the highest clinical utility was at the lowest risk score thresholds (0.01-0.05). Conclusions The developed risk prediction model successfully discriminated adolescents who developed MDD from those who did not. In practice, this model could be further developed with user involvement into a tool to target individuals for low-intensity, selective preventive intervention. En ligne : https://doi.org/10.1111/jcpp.13704 Permalink : https://www.cra-rhone-alpes.org/cid/opac_css/index.php?lvl=notice_display&id=493 [article] Developing and validating a prediction model of adolescent major depressive disorder in the offspring of depressed parents [Texte imprimé et/ou numérique] / Alice STEPHENS, Auteur ; Judith ALLARDYCE, Auteur ; Bryony WEAVERS, Auteur ; Jessica LENNON, Auteur ; Rhys BEVAN JONES, Auteur ; Victoria POWELL, Auteur ; Olga EYRE, Auteur ; Robert POTTER, Auteur ; Valentina ESCOTT PRICE, Auteur ; David OSBORN, Auteur ; Anita THAPAR, Auteur ; Stephan COLLISHAW, Auteur ; Ajay K. THAPAR, Auteur ; Jon HERON, Auteur ; Frances RICE, Auteur . - p.367-375. Langues : Anglais (eng) in Journal of Child Psychology and Psychiatry > 64-3 (March 2023) . - p.367-375 Index. décimale : PER Périodiques Résumé : Background Parental depression is common and is a major risk factor for depression in adolescents. Early identification of adolescents at elevated risk of developing major depressive disorder (MDD) in this group could improve early access to preventive interventions. Methods Using longitudinal data from 337 adolescents at high familial risk of depression, we developed a risk prediction model for adolescent MDD. The model was externally validated in an independent cohort of 1,384 adolescents at high familial risk. We assessed predictors at baseline and MDD at follow-up (a median of 2-3 years later). We compared the risk prediction model to a simple comparison model based on screening for depressive symptoms. Decision curve analysis was used to identify which model-predicted risk score thresholds were associated with the greatest clinical benefit. Results The MDD risk prediction model discriminated between those adolescents who did and did not develop MDD in the development (C-statistic=.783, IQR (interquartile range)=.779, .778) and the validation samples (C-statistic=.722, IQR=â’.694, .741). Calibration in the validation sample was good to excellent (calibration intercept=.011, C-slope=.851). The MDD risk prediction model was superior to the simple comparison model where discrimination was no better than chance (C-statistic=.544, IQR=.536, .572). Decision curve analysis found that the highest clinical utility was at the lowest risk score thresholds (0.01-0.05). Conclusions The developed risk prediction model successfully discriminated adolescents who developed MDD from those who did not. In practice, this model could be further developed with user involvement into a tool to target individuals for low-intensity, selective preventive intervention. En ligne : https://doi.org/10.1111/jcpp.13704 Permalink : https://www.cra-rhone-alpes.org/cid/opac_css/index.php?lvl=notice_display&id=493

Practitioner review: Co-design of digital mental health technologies with children and young people / Rhys BEVAN JONES in Journal of Child Psychology and Psychiatry, 61-8 (August 2020)  

Public ISBD [article]  inJournal of Child Psychology and Psychiatry > 61-8 (August 2020) . - p.928-940 Titre : Practitioner review: Co-design of digital mental health technologies with children and young people Type de document : Texte imprimé et/ou numérique Auteurs : Rhys BEVAN JONES, Auteur ; Paul STALLARD, Auteur ; Sharifah Shameem AGHA, Auteur ; Simon RICE, Auteur ; Aliza WERNER-SEIDLER, Auteur ; Karolina STASIAK, Auteur ; Jason KAHN, Auteur ; Sharon A. SIMPSON, Auteur ; Mario ALVAREZ-JIMENEZ, Auteur ; Frances RICE, Auteur ; Rhiannon EVANS, Auteur ; Sally MERRY, Auteur Article en page(s) : p.928-940 Langues : Anglais (eng) Mots-clés : Child  adolescent  co-design  development  digital  e-health  mental health  technologies Index. décimale : PER Périodiques Résumé : BACKGROUND: There is increasing interest in digital technologies to help improve children and young people's mental health, and the evidence for the effectiveness for these approaches is rising. However, there is concern regarding levels of user engagement, uptake and adherence. Key guidance regarding digital health interventions stress the importance of early user input in the development, evaluation and implementation of technologies to help ensure they are engaging, feasible, acceptable and potentially effective. Co-design is a process of active involvement of stakeholders, requiring a change from the traditional approaches to intervention development. However, there is a lack of literature to inform the co-design of digital technologies to help child and adolescent mental health. METHODS: We reviewed the literature and practice in the co-design of digital mental health technologies with children and young people. We searched Medline, PsycInfo and Web of Science databases, guidelines, reviews and reference lists, contacted key authors for relevant studies, and extracted key themes on aspects of co-design relevant to practice. We supplemented this with case studies and methods reported by researchers working in the field. RESULTS: We identified 25 original articles and 30 digital mental health technologies that were designed/developed with children and young people. The themes identified were as follows: principles of co-design (including potential stakeholders and stages of involvement), methods of involving and engaging the range of users, co-designing the prototype and the challenges of co-design. CONCLUSIONS: Co-design involves all relevant stakeholders throughout the life and research cycle of the programme. This review helps to inform practitioners and researchers interested in the development of digital health technologies for children and young people. Future work in this field will need to consider the changing face of technology, methods of engaging with the diversity in the user group, and the evaluation of the co-design process and its impact on the technology. En ligne : http://dx.doi.org/10.1111/jcpp.13258 Permalink : https://www.cra-rhone-alpes.org/cid/opac_css/index.php?lvl=notice_display&id=429 [article] Practitioner review: Co-design of digital mental health technologies with children and young people [Texte imprimé et/ou numérique] / Rhys BEVAN JONES, Auteur ; Paul STALLARD, Auteur ; Sharifah Shameem AGHA, Auteur ; Simon RICE, Auteur ; Aliza WERNER-SEIDLER, Auteur ; Karolina STASIAK, Auteur ; Jason KAHN, Auteur ; Sharon A. SIMPSON, Auteur ; Mario ALVAREZ-JIMENEZ, Auteur ; Frances RICE, Auteur ; Rhiannon EVANS, Auteur ; Sally MERRY, Auteur . - p.928-940. Langues : Anglais (eng) in Journal of Child Psychology and Psychiatry > 61-8 (August 2020) . - p.928-940 Mots-clés : Child  adolescent  co-design  development  digital  e-health  mental health  technologies Index. décimale : PER Périodiques Résumé : BACKGROUND: There is increasing interest in digital technologies to help improve children and young people's mental health, and the evidence for the effectiveness for these approaches is rising. However, there is concern regarding levels of user engagement, uptake and adherence. Key guidance regarding digital health interventions stress the importance of early user input in the development, evaluation and implementation of technologies to help ensure they are engaging, feasible, acceptable and potentially effective. Co-design is a process of active involvement of stakeholders, requiring a change from the traditional approaches to intervention development. However, there is a lack of literature to inform the co-design of digital technologies to help child and adolescent mental health. METHODS: We reviewed the literature and practice in the co-design of digital mental health technologies with children and young people. We searched Medline, PsycInfo and Web of Science databases, guidelines, reviews and reference lists, contacted key authors for relevant studies, and extracted key themes on aspects of co-design relevant to practice. We supplemented this with case studies and methods reported by researchers working in the field. RESULTS: We identified 25 original articles and 30 digital mental health technologies that were designed/developed with children and young people. The themes identified were as follows: principles of co-design (including potential stakeholders and stages of involvement), methods of involving and engaging the range of users, co-designing the prototype and the challenges of co-design. CONCLUSIONS: Co-design involves all relevant stakeholders throughout the life and research cycle of the programme. This review helps to inform practitioners and researchers interested in the development of digital health technologies for children and young people. Future work in this field will need to consider the changing face of technology, methods of engaging with the diversity in the user group, and the evaluation of the co-design process and its impact on the technology. En ligne : http://dx.doi.org/10.1111/jcpp.13258 Permalink : https://www.cra-rhone-alpes.org/cid/opac_css/index.php?lvl=notice_display&id=429

---

1 (1 - 2 / 2)