Population mental health and COVID-19: Why do we know so little?
What you need to know
During the COVID-19 pandemic, the critical need to answer research questions quickly has led to studies being conducted without allowing enough time to capture appropriate sample sizes or use appropriate diagnostic tools. In this editorial, the authors offer a cautionary message about the accuracy of current mental health estimates and how best to extract data from research studies.
Administrative data or surveys are used to develop and evaluate mental health services. In Canada, we don’t have estimates of the prevalence of mental health disorders during the pandemic. The authors of this editorial present a number of methodologies that researchers are using to capture data and suggest strategies to capture and extract more accurate data during COVID-19 and beyond.
What ideas are the researchers presenting?
The authors mention three methodologies that researchers are using to capture prevalence data.
- Screening tools: Brief mental health screening tools such as the Patient Health Questionnaire (PHQ-9), the Generalized Anxiety Disorder Scale (GAD-7) and various versions of Post Traumatic Stress Disorder (PTSD) Checklist (PCL-5) are inexpensive and convenient to help identify clients with symptoms of depression, generalized anxiety and PTSD. But the studies that are using them are assessing symptom levels rather than professional diagnosis, which may result in over estimation of the prevalence rate.
- Convenience sampling: This approach, used in many surveys, can lead to lower or higher representation of various subsets of the population studied. According to the editorial, this could lead to ”opportunity costs,” where policymakers select one course of action over a more advantageous one because they must base the decision on inaccurate information.
- Generalizability: According to the editorial, the estimates in these studies cannot be generalized to other populations due to questions about bias that may result from the measurement or sampling strategies used.
The editorial’s authors note that data should be used with caution because these research practices lead to a risk of low-quality evidence but might be used as if they were high-quality evidence.
How can this information be used?
The authors suggest that policymakers and service providers take caution when interpreting data to guide policy decisions and implement mental-health related interventions.
What future research is recommended?
The authors recommend that a national initiative be implemented, led by Health Canada along with experts in psychiatric epidemiology and administrative data, to build a better foundation for gathering mental health disorder prevalence estimates.
About the researchers
Scott B. Patten,1 Stanley Kutcher,2 David Streiner,3 David Gratzer,4 Paul Kurdyak,4 and Lakshmi Yatham,5
- Department of Community Health Sciences, University of Calgary, Alberta, Canada
- Department of Psychiatry, Faculty of Medicine, Dalhousie University, Halifax, Nova Scotia, Canada
- Department of Psychiatry & Behavioural Neurosciences, McMaster University, Hamilton, Ontario, Canada
- Centre for Addiction and Mental Health, Toronto, Ontario, Canada
- The University of British Columbia, Vancouver, British Columbia, Canada
This knowledge exchange activity is supported by Evidence Exchange Network (EENet), which is part of the Provincial System Support Program at the Centre for Addiction and Mental Health - “CAMH”). EENet has been made possible through a financial contribution from the Ministry of Health (“MOH”). The views expressed herein do not necessarily represent the views of either MOH or of CAMH.