Canadian Internet Use Survey (CIUS)
Detailed information for 2020
The purpose of the 2020 Canadian Internet Use Survey is to gather data on how digital technologies and the Internet are transforming society, the economy, and the everyday lives of Canadians.
Data release - May 31, 2021 (Access to the Internet); June 22, 2021 (Internet use, use of digital technologies and e-commerce)
The 2020 CIUS aims to measure the adoption and use of digital technologies by individual residents of Canada 15 years of age and over, living in the provinces. The information gathered will help to better understand how the Internet and other digital technologies are changing the way we work, play and interact with others.
The CIUS examines Internet access and use, the use of Internet-connected smart devices and smartphones, social connections in the digital age, the use of government online services, e-commerce, digital skills, security, privacy and the confidence Canadians place on digital technologies, online work and the changes in use of digital tech as a result of COVID-19. The CIUS also measures barriers to: Internet access and use, online services, and using various digital technologies.
Collected data is used to inform evidence-based policymaking, research and program development, and provide internationally comparable statistics on the use of digital technologies. For example, the data of this survey is used to:
- Guide government efforts to provide households with more reliable and affordable high-speed Internet
- Develop policies to protect individuals from online privacy and security risks
- Research the impacts of digital technologies on well-being and new gig-based employment
- Better understand the digital skills needed for learning and the future of work
- Better understand how and why people use online services, like shopping and social media,
- Identify barriers that prevent people from accessing the Internet and making the most of new technology
- Improve online government services and make them more user-friendly
- Contribute to international initiatives, such as the United Nations Sustainable Development Goals and the OECD Going Digital Project, to help track and compare Canada's digital development.
The survey is built off the previous iteration of the CIUS, last conducted in 2018. The 2020 iteration has been updated to collect data to meet new data needs.
The 2020 iteration of the CIUS is sponsored by Innovation, Science and Economic Development Canada (ISED). Numerous other government departments also provided input during the questionnaire content development phase.
Reference period: Reference periods vary within the survey and include: "current or regular use", "past month", "past three months" or "past 12 months" preceding the interview date.
- Individual and household internet use
- Information and communications technology
Data sources and methodology
The target population is all persons 15 years of age and older living in the ten provinces of Canada. It excludes full-time (residing for more than six months) residents of institutions.
People living on reserves are not excluded from the survey population, but they are not targeted in the sample. As the CIUS does not collect this characteristic, there is no way to identify whether the respondents, who are selected from a telephone-based frame, reside on a reserve.
The predecessor to the CIUS, the Household Internet Use Survey (HIUS), was first conducted in 1997, and ran annually until 2003. The HIUS focused on household Internet penetration. In 2005, the CIUS replaced the HIUS. The redesign in 2005 focused more on Internet use by individuals, while conforming to international standards regarding statistical indicators for Internet access and use. From 2005 to 2009, the CIUS was conducted biennially.
In 2010, the CIUS was redesigned to meet the measurement needs of Broadband Canada: Connecting Rural Canadians Program sponsored by Industry Canada (now ISED). As a hybrid survey on access and use, the CIUS 2010 and 2012 measured the type, speed and cost of household Internet access and the individual online behaviours of a selected household member.
The 2018 questionnaire CIUS questionnaire was completely redesigned following consultations with clients at ISED (the survey sponsor), other federal departments, experts in the field and other stakeholders. The 2018 survey was no longer a hybrid survey. Instead, it focussed on measuring individual's use of digital technologies, the Internet, and online behaviours including; those related to social media, e-commerce, online government services, online work, digital skills, streaming content and security privacy and trust as it relates to the Internet. The survey also measures household access.
In order to take account of the rapid evolution of Internet-related technologies, the 2020 cycle has been revised to measure new trends. This edition includes additional content in existing modules, questions on well-being in the digital age, the impact of COVID-19 on Internet use and increased demographic variables, such as population group, perceived health, and disability status, to paint an accurate picture of the Canadian population.
To make room for this new content without adding to the response burden of respondents, some questions or modules from the 2018 edition have been rotated out.
Testing of the questionnaire:
Cognitive testing of the questionnaire content of the 2018 iteration was tested in two phases in conjunction with the Questionnaire Design Resource Center based at Statistics Canada in both official languages. The first phase included 24 interviews with potential respondents that concentrated on validating respondents' understanding of concepts, questions, terminology, the appropriateness of response categories and the availability of requested information. The second included 23 respondents to assess the updated questionnaire content (based on the results of the previous round of testing) using mock-up screen shots in an updatable PDF form to simulate an electronic questionnaire (EQ). The test confirmed that respondents could navigate through the EQ application with ease.
To ensure that respondents would be able to respond to the new content and understand the intent of the questions, experts from Statistics Canada's Questionnaire Design Resource Centre performed extensive review of the questionnaire and proposed changes to improve understanding of the statements. Cognitive testing was not conducted for the 2020 questionnaire.
This is a sample survey with a cross-sectional design.
This survey uses a frame that combines landline and cellular telephone numbers from the Census and various administrative sources with Statistics Canada's dwelling frame. Records on the frame are groups of one or several telephone numbers associated with the same address (or single telephone number in the case a link between a telephone number and an address could not be established). This sampling frame is used to obtain a better coverage of households with a telephone number.
The sample is based on a stratified design employing probability sampling. The stratification is done at the province/census metropolitan area (CMA) and census agglomeration (CA) level. Information is collected from one randomly selected household member aged 15 or older, and proxy responses are not permitted.
The CIUS uses a two-stage sampling design. The sampling units are the groups of telephone numbers. The final stage units are individuals within the identified households. Note that the CIUS only selects one eligible person per household to be interviewed.
A field sample of approximatively 44,800 units was used. Among them, about 32,300 had addresses that were attached to the telephone number in the frame, and were sent invitation letters in the mail to complete the electronic questionnaire online. The remaining 12,500 units were contacted by telephone to complete the questionnaire with an interviewer.
Data collection for this reference period: 2020-11-03 to 2021-03-03
Responding to this survey is voluntary.
Data are collected directly from survey respondents.
Data are collected through an electronic questionnaire or computer assisted telephone interviewing (CATI). No proxy reporting is allowed. The respondent has the choice to respond in French or in English. The average time to complete the survey is estimated at 30-60 minutes.
Invitation letters and reminders, containing secure access code, to complete electronic questionnaires were sent to respondents by mail. Intensive non-response follow-up will be also conducted by CATI.
The collection method is electronic questionnaire with CATI follow-up.
View the Questionnaire(s) and reporting guide(s) .
All responses to the 2020 CIUS questions were captured directly in the EQ application, both for the interviewer-led (iEQ) component and the respondent self-reporting (rEQ) component. The EQ application, just like any other computerized questionnaire, reduces processing time and costs associated with data entry, transcription errors and data transmission.
For some CIUS questions, data underwent a preliminary verification process when respondents were completing the survey. This was accomplished by means of a series of edits programmed into the EQ. That is, where a particular response appeared to be inconsistent with previous answers, the interviewer or the self-reporting respondent was notified with an on-screen warning message, providing them with an opportunity to modify the response provided.
Once the data are collected, an extensive series of processing steps are undertaken including the editing and imputation process to identify inconsistent or missing data, and to correct errors. For example, these steps consist of a top-down flow edit to correct questionnaire paths mistakenly followed.
Abnormally large reported values for household income and for the value of the amount spent on physical goods and on digital goods or services were identified as "outliers" and treated by replacing the suspicious values by ones from respondents with similar characteristics (see Imputation).
Imputation is the process that supplies valid values for those responses that have been identified as either invalid or missing on the data file. The new values are supplied in such a way as to preserve the underlying structure of the data and to ensure that the resulting records will pass all required edits. Imputation was done using a nearest-neighbor method which searches for "donor" records from individuals with complete and consistent values. The recipient records are imputed by a donor chosen from a group of records with similar demographic characteristics.
CIUS imputation was limited to item non-response for the gender of the respondent, the value of the amount spent on physical goods over the Internet and the value of the amount spent on other services on digital services over the Internet. Imputation was used for the respondents for whom the gender was of gender diverse or was missing. A gender was randomly assigned in order to respect the proportion of male and female in the population.
For the value of the amount spent on physical goods and on digital goods and services over the Internet, donor imputation was also used. Again, the donor records were chosen from a group of records with similar demographic characteristics, as well as similar Internet shopping behavior. The relative imputation rate serves as a data quality indicator. The rates for 2018, based on value-weighted estimates are the following: for every $100 spent in online orders for physical goods estimated from the survey, about $9.50 were imputed. Similarly with the value of orders for other services, for every $100 spent in online orders for digital services estimated from the survey, $13.30 was imputed. For the majority of imputed cases, the range of the amount spent by the respondent was known.
When a probability sample is used, as it was the case for this 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 2020 CIUS is a survey of individuals and the analytic files contain questionnaire responses and associated information from the respondents.
A weighting factor is available on the microdata file:
WTPM: 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.
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 we have 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.
Rigorous quality assurance mechanisms are applied at all stages of the statistical process, including questionnaire design, data collection and data processing. Measures included testing of the questionnaire with potential respondents, training provided to interviewers for specific survey concepts and procedures and observations of interviews. Finally, a validation of the results was implemented to ensure that the data is consistent with other previously published data. To do this, estimates were produced in the form of cross-tabulations and then compared with other similar data sources such as the 2018 CIUS cycle, other Statistics Canada surveys, regulatory agencies (e.g. the Canadian Radio-television and Telecommunications Commission), and national / international organizations (e.g. the OECD).
Statistics Canada is prohibited by law from releasing any information it collects which 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.
Revisions and seasonal adjustment
This methodology does not apply to this survey program.
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 of the estimates produced based on the data from 2020 CIUS.
The sample error is quantified by the coefficient of variation (CV) with the following guidelines:
- 16.5% and below: Acceptable estimate;
- 16.6% to 33.3%: Marginal estimate, with cautionary note;
- Above 33.3%: Unacceptable estimate.
Estimates that do not meet an acceptable level of quality are either flagged for caution or suppressed.
The overall response rate is 41.6%.
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. Households without telephones, as well as households with telephone services not covered by the current frame, represent a part of the target population that was excluded from the surveyed population. 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. Survey estimates will be adjusted (i.e. weighted) to account for non-response cases. Other types of non-sampling errors can include response errors and processing errors.
The main method used to reduce non-response bias involved a series of adjustments to the survey weights to account for non-response as much as possible.
The survey frame for CIUS was created using several linked sources, such as the Census, administrative data and billing files. All respondents in the ten provinces were interviewed by telephone or self-completed an electronic questionnaire. Households without telephones were therefore excluded from the survey population. Survey estimates were adjusted (weighted) to represent all persons in the target population, including those not covered by the survey frame.
Other non-sampling errors:
Significant effort was made to minimize bias by using a well-tested questionnaire, a proven methodology, specialized interviewers and strict quality control.