Survey on COVID-19 and Mental Health (SCMH)

Detailed information for February to May 2023





Record number:


The purpose of the Survey on COVID-19 and Mental Health is to collect data to assess the impacts of COVID-19 on the mental health and well-being of Canadians. Given that the pandemic has significantly altered our daily lives, it is necessary to gather information on its effects on mental health and coping skills.

Data release - December 12, 2023


Topics include behaviours and symptoms associated with depression, anxiety and post-traumatic stress disorder (PTSD), suicide risk, pressure on parents, substance use, household and intimate partner violence, as well as general mental health.

The data will be used by the Public Health Agency of Canada and may be used by other government organizations to inform the delivery of services and support to Canadians, during and after the pandemic.

Collection period: February to May


  • Crime and justice
  • Family violence
  • Health
  • Lifestyle and social conditions
  • Mental health and well-being

Data sources and methodology

Target population

The target population for the survey is non-institutionalized persons 18 years of age or older, living in Canada's ten provinces, who are not members of collectives or living on reserves.

Instrument design

The content for the Survey on COVID-19 and Mental Health electronic questionnaire was drafted in consultation with Statistics Canada's Centre for Population Health Data, as well as the Public Health Agency of Canada.

The questionnaire underwent cognitive testing in the form of in-depth interviews in both of Canada's official languages, conducted by Statistics Canada's Questionnaire Design Resource Centre. The goal of the qualitative study was to test the survey content.


This is a sample survey with a cross-sectional design.

Sampling unit
The SCMH sample has a two-stage design: the sampling unit for the first stage is the dwelling, and the sampling unit for the second stage is the person.

Stratification method
The SCMH frame was stratified by province, and a simple random sample of dwellings was selected within each province.

Sampling and sub-sampling
Sufficient sample was allocated to each of the provinces so that the survey could produce provincial level estimates. An initial sample of 36,000 dwellings was selected and sent to collection.

Data sources

Data collection for this reference period: 2023-02-23 to 2023-05-31

Responding to this survey is voluntary.

Data are collected directly from survey respondents.

Data are collected directly from survey respondents either through an electronic questionnaire (EQ) or through CATI (computer assisted telephone interviewing).

View the Questionnaire(s) and reporting guide(s) .

Error detection

Electronic files containing the daily transmissions of completed respondent survey records were combined to create the "raw" survey file. Before further processing, verification was performed to identify and eliminate potential duplicate records and to drop non-response and out-of-scope records.

In addition, some out-of-scope respondent records were found during the data clean-up stage. All respondent records that were determined to be out-of-scope and those records that contained no data were removed from the data file.

After the verification stage, editing was performed to identify errors and modify affected data at the individual variable level. The first editing step was to identify errors and determine which items from the survey output needed to be kept on the survey master file. Subsequent to this, invalid characters were deleted and the remaining data items were formatted appropriately.


For a small number of cases, the postal code of residence was not stated or was not valid in the submitted questionnaire. In those situations, it was imputed directly with the respondent's postal code from the sample file. No other variables on the master file were imputed.


The estimation of population characteristics from a sample survey is based on the premise that each person in the sample represents a certain number of other persons in addition to themselves. This number is referred to as the survey weight. The process of computing survey weights for each survey respondent involves several steps.

1) Each selected dwelling is given an initial weight equal to the inverse of its selection probability from the sampling frame. Dwellings identified as out-of-scope during collection are dropped from the sample.

2) The weights for responding households are adjusted to represent the households that did not respond. Adjustment factors are calculated separately by province and dwelling type (single-detached house / other).

3) The household weights are calibrated so that the sum of the weights match province level household size demographic counts.

4) Person weights are computed by multiplying the household level weights by the inverse of the probability of selecting the person within the household.

5) The person weights are calibrated so that the sum of the weights match demographic population counts at the province by age group by gender level. The weights are also calibrated to demographic counts for large census metropolitan areas.

Variance estimation is based on a resampling method called the bootstrap.

The Generalized Estimation System (G-Est) was used to generate the survey weights and bootstrap weights.

Quality evaluation

While quality assurance mechanisms are applied at all stages of the statistical process, the validation and review of data by statisticians is the final verification of quality prior to release. Validation measures were implemented, they include:

a) verification of estimates through cross-tabulations
b) consultation with stakeholders internal to Statistics Canada
c) consultation with external stakeholders.

Disclosure control

Statistics Canada is prohibited by law from releasing any information it collects that could identify any person, business, or organization, unless consent has been given by the respondent or as permitted by the Statistics Act. Various confidentiality rules are applied to all data that are released or published to prevent the publication or disclosure of any information deemed confidential. If necessary, data are suppressed to prevent direct or residual disclosure of identifiable data.

In order to prevent any data disclosure, confidentiality analysis is done using the Statistics Canada Generalized Disclosure Control System (G-Confid). G-Confid is used for primary suppression (direct disclosure) as well as for secondary suppression (residual disclosure). Direct disclosure occurs when the value in a tabulation cell is composed of or dominated by few enterprises while residual disclosure occurs when confidential information can be derived indirectly by piecing together information from different sources or data series.

Revisions and seasonal adjustment

This methodology type does not apply to this survey.

Data accuracy

Survey errors come from a variety of different sources. One dimension of survey error is sampling error. Sampling error is defined as the error that arises because an estimate is based on a sample rather than the entire population. Sampling error can be expressed through a confidence interval or coefficient of variation.

The following are approximate sampling error estimates for Canada level estimates. These are based on average results; these are not results for a specific variable.

-Approximate length of 95% confidence intervals for a proportion of 50% (Canada level): 2.6%
-Approximate length of 95% confidence intervals for a proportion of 10% (Canada level): 1.5%
-Approximate coefficients of variation for a proportion of 10% (Canada level): 3.8%

Response rate
The response rate for this survey was 46.5%.

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