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<p>Public health monitoring based on the presence or absence of discrete health diagnoses helps to&#xa0;mitigate the burden associated with some health conditions, such as infectious diseases. However, this binary approach to disease monitoring misses opportunities for the&#xa0;prevention and effective care of mental health disorders, which are characterized by fluid boundaries between diagnoses and dimensional symptoms that vary over time. In this Review, we consider the staging model as an alternative to guide public mental health monitoring. This model situates individuals on a continuum covering six stages: asymptomatic individuals who have not experienced burdensome symptoms (stage 0); individuals with mixed symptoms not meeting criteria for full-threshold disorders (stage 1a); individuals with subthreshold presentations (stage 1b); individuals with a diagnosis of full-threshold disorders (stage 2); individuals with recurrent conditions (stage 3); and individuals with treatment-resistant conditions (stage 4). We integrate the staging model into public mental health monitoring by identifying possible indicators of mental health status at each stage. On the basis of identified gaps in monitoring the risk of progression across stages, we discuss how existing indicators can be reframed to improve the logic, intensity and timing of public health interventions and therefore the estimation of service and resource needs.</p>

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Transdiagnostic stage-based monitoring of public mental health

  • 期刊论文

  • 发表日期：

    2026年1月7日

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  • Claudia Buchweitz,
  • Anna Viduani,
  • Helen Herrman,
  • Brandon A. Kohrt,
  • Patrick McGorry,
  • Giovanni Salum,
  • Claudia Sartor,
  • Shekhar Saxena,
  • Christian Kieling

摘要

Public health monitoring based on the presence or absence of discrete health diagnoses helps to mitigate the burden associated with some health conditions, such as infectious diseases. However, this binary approach to disease monitoring misses opportunities for the prevention and effective care of mental health disorders, which are characterized by fluid boundaries between diagnoses and dimensional symptoms that vary over time. In this Review, we consider the staging model as an alternative to guide public mental health monitoring. This model situates individuals on a continuum covering six stages: asymptomatic individuals who have not experienced burdensome symptoms (stage 0); individuals with mixed symptoms not meeting criteria for full-threshold disorders (stage 1a); individuals with subthreshold presentations (stage 1b); individuals with a diagnosis of full-threshold disorders (stage 2); individuals with recurrent conditions (stage 3); and individuals with treatment-resistant conditions (stage 4). We integrate the staging model into public mental health monitoring by identifying possible indicators of mental health status at each stage. On the basis of identified gaps in monitoring the risk of progression across stages, we discuss how existing indicators can be reframed to improve the logic, intensity and timing of public health interventions and therefore the estimation of service and resource needs.