Survey on COVID-19 and Mental Health (SCMH)

Detailed information for February to May 2021

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 - September 27, 2021

• Questionnaire(s) and reporting guide(s)
• Description
• Data sources and methodology
• Data accuracy

Description

Topics include behaviours and symptoms associated with depression, anxiety and post-traumatic stress disorder (PTSD), suicide risk, pressure on parents, substance use, household 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: September to December

Subjects

• 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 and territorial capitals, 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.

Sampling

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 and within the three territorial capital cities.

Sampling and sub-sampling
Sufficient sample was allocated to each of the provinces and territorial capital cities so that the survey could produce provincial level estimates, as well as estimates for the three territorial capital cities. An initial sample of 18,000 dwellings was selected and sent to collection.

Data sources

Data collection for this reference period: 2021-02-01 to 2021-05-07

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

The 2022 Time Use Survey used the Social Survey Processing Environment (SSPE) generalized processing steps and utilities to allow subject matter and survey support staff to specify and run the processing of the survey in a timely fashion with high quality outputs. It used a structured environment to monitor the processing of data ensuring best practices and harmonized business processes were followed.

Edits were performed automatically and manually at various stages of processing at macro and micro levels. They included consistency and flow edits. A series of checks was done to ensure the consistency of survey data. For example, checking the respondent's age against the birth date. Flow edits were used to ensure respondents followed the correct path and fix off-path situations.

Error detection was done through edits programmed into the EQ system, which allowed a valid range of codes for each question and built-in edits, and automatically followed the flow of the questionnaire.

Head office performed the same checks as the EQ system as well as more specific validation of the time diary that was beyond the scope of automated flow and consistency edits. Records with missing or incorrect information were, in a small number of cases, completed, corrected deterministically, or imputed from other information on the questionnaire.

Imputation

This methodology type does not apply to this statistical program.

Estimation

When a probability sample is used, as was the case for the Time Use Survey, the principle behind estimation is that each person selected in the sample represents (in addition to himself/herself) several other persons not in the sample. For example, in a simple random sample of 2% of the population, each person in the sample represents 50 persons in the population (himself/herself and 49 others). The number of persons represented by a given respondent is usually known as the weight or weighting factor.

The Time Use Survey, 2022 is a survey of individuals and the analytic files contain questionnaire responses and associated information from the respondents.

Two weighting factors are available on the microdata file:

WGHT_PER: This is the basic weighting factor for analysis at the person level, i.e. to calculate estimates of the number of persons (non-institutionalized and aged 15 or over) having one or several given characteristics.

WGHT_EPI: This is the basic weighting factor for the analysis at the episode level i.e., to calculate estimates on the number of time an activity is done by the Canadian population. The WGHT_EPI has the same value as the person weight; it does, however, have a different interpretation. It indicates the number of time use episodes that a record on the Episode File represents.

In addition to the estimation weights, bootstrap weights have been created for the purpose of design-based variance estimation.

Estimates based on the survey data are also adjusted (by weighting) so that they are representative of the target population with regard to certain characteristics (each month has independent estimates for various age-sex groups by province). To the extent that the characteristics are correlated with those independent estimates, this adjustment can improve the precision of estimates.

Quality evaluation

Extensive validation and comparisons with distributions of variables collected in other surveys within the GSSP were done. In addition, a cross-survey validation process was undertaken after the final weights were applied to ensure the quality of the information.

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

As the data are based on a sample of persons, they are subject to sampling error. That is, estimates based on a sample will vary from sample to sample, and typically they will be different from the results that would have been obtained from a complete census. More precise estimates of the sampling variability of estimates can be produced with the bootstrap method using bootstrap weights that have been created for this survey. The bootstrap method was used to estimate the sampling variability for all the estimates produced based on the data from the 2022 Time Use Survey.

RESPONSE RATES:
The overall response rate is 30.7%.

NON-SAMPLING ERROR:
Common sources of these errors are imperfect coverage and non-response.

Coverage errors (or imperfect coverage) arise when there are differences between the target population and the surveyed population. Dwellings without telephones and mailable addresses were not collected as we had no way to contact them. To the extent that the excluded population differs from the rest of the target population, the results may be biased. In general, since these exclusions are small, one would expect the biases introduced to be small.

Non-response could occur at several stages in this survey. There were two stages of information collection: at the household level and at the individual level. Some non-response occurred at the household level, and some at the individual level. Survey estimates were adjusted (i.e. weighted) to account for non-response cases.

Other types of non-sampling errors can include response errors and processing errors.

NON-RESPONSE BIAS:
The main method used to reduce nonresponse bias involved a series of adjustments to the survey weights to account for nonresponse as much as possible. Information was extracted from administrative sources and used to model and adjust nonresponse.

COVERAGE ERROR:
The frame for the regular sample was Dwelling Universe File (DUF), a file produced at Statistics Canada. All respondents in the ten provinces were interviewed by telephone or self-completed an electronic questionnaire. Dwellings that were identified as vacant at the time the sampling frame was created were excluded. Dwellings that had neither a mailing address nor an associated telephone number were not collected, as they could not be contacted by any of the survey collection modes. However, the survey estimates were weighted to include persons living in these dwellings.

OTHER NON-SAMPLING ERRORS:
For the 2022 TUS, significant effort was made to minimize bias by using a well-tested questionnaire, a proven methodology, specialized interviewers and strict quality control, and by following up with households that did not initially respond to the survey.

MODE EFFECT:
The 2022 TUS offered an Internet option to almost all survey respondents. This approach to data collection was in recognition of the need to adapt to the changing use of technology and the ever-present demands on Canadians' time. However, there are reasons to believe that the use of an electronic questionnaire might have an impact on the estimations. The impact of the collection mode on the estimates has been analyzed by selecting certain groups of key questions.

Users should refer to the survey user guide and codebook for details on which variables have been identified as being impacted by a strong or mild mode effect.