{"id":206074,"date":"2020-07-13T10:31:13","date_gmt":"2020-07-13T14:31:13","guid":{"rendered":"https:\/\/irpp-policy-options.local\/issues\/covid-19-mental-health-surveys-are-not-the-stuff-of-effective-policy\/"},"modified":"2025-04-14T04:56:29","modified_gmt":"2025-04-14T08:56:29","slug":"covid-19-mental-health-surveys-are-not-the-stuff-of-effective-policy","status":"publish","type":"issues","link":"https:\/\/potestlaunch.irpp.org\/fr\/2020\/07\/covid-19-mental-health-surveys-are-not-the-stuff-of-effective-policy\/","title":{"rendered":"COVID-19 mental health surveys are not the stuff of effective policy"},"content":{"rendered":"

The COVID-19 pandemic\u00a0has produced an\u00a0urgent\u00a0need\u00a0for\u00a0policy-relevant scientific\u00a0evidence\u00a0in Canada, as it has in\u00a0other countries. Research\u00a0funding organizations<\/a>,\u00a0providers of health data<\/a>,\u00a0and the\u00a0private\u00a0sector<\/a>\u00a0have\u00a0all\u00a0stepped up in an effort to fulfill these needs.\u00a0Mental health\u2019s importance\u00a0has not been neglected in\u00a0these\u00a0discussions,\u00a0but from the perspective of scientifically robust knowledge generation,\u00a0the\u00a0efforts so far\u00a0appear to have\u00a0mostly\u00a0missed the mark.<\/p>\n

Some of the problems relate to a \u201cone size fits all\u201d view of mental health. Mental health is a very broad term and encompasses many different emotional, cognitive, and behavioural states. It does not simply mean \u201cfeeling good all the time.\u201d Indeed, negative emotional states in appropriate situations are necessary to drive adaptation and are a normal component of mental health. Mental disorders often cause negative emotional states, but negative emotional states are not always due to mental disorders.<\/p>\n

Anxiety disorders are a good example. The hyperarousal response is a natural reaction to a circumstance of threat or danger. This response is universal, and in its healthy manifestations is adaptive, helping the body to prepare for a threatening or dangerous situation (\u201cfight or flight\u201d). Even though anxiety may be experienced as unpleasant, it reflects a healthy emotional response, and does not require treatment.\u00a0 On the other hand, anxiety disorders\u00a0<\/span><\/span>can be disabling and impairing<\/span><\/span><\/a>\u00a0and require professional attention.<\/span><\/span><\/p>\n

Determining when psychological or emotional symptoms may represent a mental disorder, adaptive failure or when they are normal responses to challenging circumstances is an important distinction necessary to develop appropriate mental health policy. Despite major efforts in recent decades to refine this determination, this progress appears to have been neglected during the current pandemic.<\/p>\n

Starting with the earliest reports from\u00a0the\u00a0outbreak in\u00a0Wuhan, China, much\u00a0of the mental health research related to the pandemic has\u00a0used\u00a0brief,\u00a0self-reported questionnaires or scales designed to measure psychological symptoms.\u00a0Such instruments are unable to make a diagnosis.\u00a0By focusing on symptoms\u00a0and not addressing\u00a0a disorder\u2019s\u00a0presence\u00a0or the presence of adaptive behaviours,\u00a0the\u00a0data produced from these\u00a0studies cannot guide policy.<\/p>\n

Psychological symptoms that do not reach the threshold for a disorder may require interventions that promote understanding of normal and expected emotional responses, or advice on self-care. On the other hand, mental disorders or the presence of substantial symptoms in the context of impaired functioning will require interventions supported by health and social services systems. These are important distinctions that impact policy development, and data must be collected and analysed with those goals in mind. Surveys that primarily ask about symptoms do not provide for such important distinctions to be made.<\/p>\n

During the pandemic, mental health surveys have most often used questionnaires or symptom scales. A questionnaire can contain questions seeking to determine whether a symptom is present (\u201cdo you feel anxious?\u201d for example), or the response can be scaled to assess the severity of a symptom (for example: \u201crate your anxious feelings from 0 to 10 where 0 means \u2018not at all\u2019 and 10 means \u2018extremely.\u2019\u201d). Symptom scales can also assess clusters of related symptoms (for example, anxiety with its various psychological and physical manifestations such as anxious feelings or a racing heart) and add up the item scores to calculate a total score for the syndrome of anxiety. A diagnostic instrument must go well beyond these levels of assessment and address other issues such as the persistence of the symptoms over time and whether they cause additional problems such as impaired functioning or severe distress, etc.<\/p>\n

Having low quality evidence is not better than having no evidence at all. Bad evidence does not reflect reality and is easily distorted by biases.<\/p><\/blockquote>\n

Questionnaires or symptom scales are therefore not policy informative. But many other surveys use measures that are even further removed from meaningful assessment of mental health states. These measures involve subjective perceptions of mental health and make use of single questions, asking respondents to provide global ratings (mild, moderate or severe, for example) for symptoms. Or they simply ask participants to summarize their mental health without making clear what the phrase \u201cmental health\u201d means. Whereas symptom scales have at least been confirmed to measure symptoms, mental health perceptions are of unknown significance for determining need for health or social services interventions and are not even a good reflection of symptoms. Nevertheless, the frequency of fair or poor perceived mental health or responses to a survey question on a single predetermined state (such as anxiety) has emerged as a core data element in studies conducted during this pandemic (examples\u00a0here<\/a>,\u00a0here<\/a>\u00a0and\u00a0here<\/a>).<\/p>\n

Having low quality evidence is not better than having no evidence at all. Bad evidence does not reflect reality and is easily distorted by biases. An example is measurement bias. Symptom rating scales have usually been designed for screening purposes, meaning that they are designed to be sensitive for detecting mental disorders, but they are non-specific, because many people experiencing the negative emotions that the scales measure do not have mental disorders. In other words, if you have an anxiety disorder, you are likely to have a high score on an anxiety screening scale, but many people with high scores do not have anxiety disorders. This can lead to overestimating<\/a> the burden of mental disorders and, consequentially, precious resources may be misdirected toward people who do not need them.<\/p>\n

Low quality sampling procedures (such as self selection into a volunteer sample) and low response rates can introduce gross distortions of estimates through selection bias. Vulnerable and high-risk populations may not be appropriately represented. Bad estimates may lead to bad policy.<\/p>\n

Extensive resources have been invested in understanding the novel coronavirus epidemiology. Canada would be well served by research that will help us better understand the mental health aspects of the pandemic. To realize this, we need high quality data. At the very least, these considerations should be applied:<\/p>\n