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Predicting Mental Health Risk from Early-Life Adversity: A Population-Based Study of Canadian Adults: Prédiction du risque pour la santé mentale liée à l'adversité en début de vie : Étude fondée sur une population d'adultes canadiens

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Title: Predicting Mental Health Risk from Early-Life Adversity: A Population-Based Study of Canadian Adults: Prédiction du risque pour la santé mentale liée à l'adversité en début de vie : Étude fondée sur une population d'adultes canadiens
Authors: Johnson, Dylan (AUTHOR), Parker, Victoria (AUTHOR), Wade, Mark (AUTHOR)
Source: Canadian Journal of Psychiatry. Aug2026, Vol. 71 Issue 8, p645-655. 11p.
Subjects: Adverse childhood experiences, Predictive validity, Epidemiological research, COVID-19 pandemic, Pathological psychology, Canadians, Mental illness risk factors
Geographic Terms: Canada
Abstract (English): Objectives: Building on prior population-level studies, this replication study explored the predictive accuracy of retrospectively-reported early-life adversity (ELA) for individual psychopathology risk in a Canadian population survey, with measurements focused on direct/severe ELA and occurring during the COVID-19 pandemic. Methods: Nationally-representative, cross-sectional data from 7,608 Canadians surveyed in 2022 were analysed. Group-level differences were assessed via logistic regression, and predictive accuracy of ELA was tested via area under the curve (AUC) analyses. Results: Group-based analyses found that the odds of mental health problems rose with increasing ELA, albeit nonlinearly. Across psychopathology domains, predictive accuracy was poor (AUC = 0.62–0.67). Using a high-risk cut-off of ≥4 ELAs, sensitivity values were low (0.14–0.23), while specificity was high (0.93–0.94). Similarly, positive predictive values were low (0.08–0.22), while negative predictive values were high (0.92–0.97). Conclusions: ELA screening performs poorly at the individual level. While high-risk cut-offs may rule out poor mental health for individuals with fewer ELAs, it fails to accurately identify those with psychopathology. Predictive accuracy does not improve under conditions of collective stress or by focusing on direct/severe ELA. Presently, ELA screening is unsuitable for guiding intervention allocation. Further research is needed to determine whether screening can be refined to improve mental health risk prediction. Plain Language Summary Title: Early-life adversity and adult mental health: Is Canadian screening getting it right? Plain Language Summary: The prevention and treatment of common mental health conditions is a priority for Canadian health care providers. As experiences of childhood adversity are linked to population-level mental health problems in adults, screening individuals for these early experiences has become increasingly common. Specifically, many providers are now encouraged to incorporate questions related to early-life adversity into clinical care to guide treatment decisions. Yet, existing studies in the USA, UK, and New Zealand suggest that screening does a poor job of identifying individuals who are struggling with mental health issues. Despite this evidence, early-life adversity screening continues to be implemented in many settings, including in Canada. The current study explored if experiences of early-life adversity can accurately distinguish between Canadian adults with and without mental health problems. It is the first study to test this question in a population-level Canadian study. Researchers analysed data from a large, representative sample of Canadian adults during COVID-19, a time of heightened stress. They looked at whether reports of past early-life adversity (i.e., direct violence/abuse) could predict who met criteria for mental health problems such as anxiety or depression. Results indicate that early-life adversity was not a reliable way to identify individuals with mental health problems. Even when focusing on direct/severe types of adversity during a period of collective stress, screening did not clearly discriminate between those with and without mental health challenges. These findings suggest that early-life adversity screening is not an effective clinical tool to inform treatment allocation. This strategy risks missing those who need intervention and providing treatment to those who do not need it. More research is required to develop better screening procedures that include a wider range of risk and protective factors in order to guide appropriate care. [ABSTRACT FROM AUTHOR]
Abstract (French): S'appuyant sur des études populationnelles antérieures, cette étude de réplication a exploré la précision prédictive de l'adversité en début de vie déclarée rétrospectivement en regard du risque individuel de psychopathologie dans le cadre d'une enquête populationnelle canadienne, la mesure ayant principalement porté sur l'adversité en début de vie directe/grave survenue durant la pandémie de COVID-19. Les données transversales représentatives à l'échelle nationale provenant de 7 608 Canadiens interrogés en 2022 ont été analysées. Les différences au niveau du groupe ont été évaluées au moyen d'une régression logistique, et la précision prédictive de l'adversité en début de vie a été soumise à des analyses de l'aire sous la courbe (ASC). Des analyses au niveau de groupes ont révélé que la probabilité de problèmes de santé mentale augmentait proportionnellement à l'importance de l'adversité en début de vie, bien que de manière non linéaire. Dans tous les domaines de psychopathologie, la précision prédictive était faible (ASC = 0,62–0,67). En utilisant un seuil de risque élevé supérieur ou égal à 4 événements d'adversité en début de vie, les valeurs de sensibilité étaient faibles (0,14–0,23), tandis que celles de la spécificité étaient élevées (0,93–0,94). De même, les valeurs prédictives positives étaient faibles (0,08–0,22), alors que les valeurs prédictives négatives étaient élevées (0,92–0,97). Le dépistage de l'adversité en début de vie est associé à de mauvais résultats au niveau individuel. Bien que les seuils de risque élevé puissent exclure un mauvais état de santé mentale chez les personnes ayant subi moins d'événements d'adversité en début de vie, ceux-ci ne permettent pas d'identifier avec précision les personnes atteintes de psychopathologie. La précision prédictive ne s'améliore pas en fonction de conditions de stress collectif ou en se concentrant sur l'adversité en début de vie directe/grave. À l'heure actuelle, le dépistage de l'adversité en début de vie ne convient pas pour orienter l'affectation des interventions. Il faudra mener d'autres projets de recherche pour déterminer si l'amélioration du dépistage permet d'améliorer la prédiction des risques pour la santé mentale. [ABSTRACT FROM AUTHOR]
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Database: Psychology and Behavioral Sciences Collection
Description
Abstract:Objectives: Building on prior population-level studies, this replication study explored the predictive accuracy of retrospectively-reported early-life adversity (ELA) for individual psychopathology risk in a Canadian population survey, with measurements focused on direct/severe ELA and occurring during the COVID-19 pandemic. Methods: Nationally-representative, cross-sectional data from 7,608 Canadians surveyed in 2022 were analysed. Group-level differences were assessed via logistic regression, and predictive accuracy of ELA was tested via area under the curve (AUC) analyses. Results: Group-based analyses found that the odds of mental health problems rose with increasing ELA, albeit nonlinearly. Across psychopathology domains, predictive accuracy was poor (AUC = 0.62–0.67). Using a high-risk cut-off of ≥4 ELAs, sensitivity values were low (0.14–0.23), while specificity was high (0.93–0.94). Similarly, positive predictive values were low (0.08–0.22), while negative predictive values were high (0.92–0.97). Conclusions: ELA screening performs poorly at the individual level. While high-risk cut-offs may rule out poor mental health for individuals with fewer ELAs, it fails to accurately identify those with psychopathology. Predictive accuracy does not improve under conditions of collective stress or by focusing on direct/severe ELA. Presently, ELA screening is unsuitable for guiding intervention allocation. Further research is needed to determine whether screening can be refined to improve mental health risk prediction. Plain Language Summary Title: Early-life adversity and adult mental health: Is Canadian screening getting it right? Plain Language Summary: The prevention and treatment of common mental health conditions is a priority for Canadian health care providers. As experiences of childhood adversity are linked to population-level mental health problems in adults, screening individuals for these early experiences has become increasingly common. Specifically, many providers are now encouraged to incorporate questions related to early-life adversity into clinical care to guide treatment decisions. Yet, existing studies in the USA, UK, and New Zealand suggest that screening does a poor job of identifying individuals who are struggling with mental health issues. Despite this evidence, early-life adversity screening continues to be implemented in many settings, including in Canada. The current study explored if experiences of early-life adversity can accurately distinguish between Canadian adults with and without mental health problems. It is the first study to test this question in a population-level Canadian study. Researchers analysed data from a large, representative sample of Canadian adults during COVID-19, a time of heightened stress. They looked at whether reports of past early-life adversity (i.e., direct violence/abuse) could predict who met criteria for mental health problems such as anxiety or depression. Results indicate that early-life adversity was not a reliable way to identify individuals with mental health problems. Even when focusing on direct/severe types of adversity during a period of collective stress, screening did not clearly discriminate between those with and without mental health challenges. These findings suggest that early-life adversity screening is not an effective clinical tool to inform treatment allocation. This strategy risks missing those who need intervention and providing treatment to those who do not need it. More research is required to develop better screening procedures that include a wider range of risk and protective factors in order to guide appropriate care. [ABSTRACT FROM AUTHOR]
ISSN:07067437
DOI:10.1177/07067437261442418