Canadian Internet Use Survey (CIUS)

Detailed information for 2022

The purpose of the 2022 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 - July 20, 2023

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

Description

The 2022 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 helps 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, along with the use of Internet-connected smart devices, social connections in the digital age, use of government online services, e-commerce, digital skills, security, privacy and trust, online work and the knowledge and adoption of new digital technologies such as Artificial Intelligence, digital credentials and cryptocurrencies. The CIUS also measures barriers to: Internet access and use, online services, and various digital technologies.

Collected data is used to inform evidence-based policymaking, research, program development, and provide internationally comparable statistics on the use of digital technologies. For example, the results from this survey will be 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 Canadians use online services, like shopping and banking
- Identify barriers that prevent people from accessing the Internet and making the most out of the new technologies presently available
- 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 iterations of the CIUS, last conducted in 2018 and 2020. The 2022 iteration has been updated to collect data to meet new data needs.

The 2022 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.

Subjects

• Individual and household internet use
• Information and communications technology

Data sources and methodology

Target population

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. The CIUS makes efforts to identify and exclude units on reserves based on their associated geographies on the building-unit-based frame.

Instrument design

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 CIUS questionnaire was completely redesigned following consultations with clients at ISED (the survey sponsor), other federal departments, experts in the field and other stakeholders. It was modified to no longer be a hybrid survey and focused on measuring individual's use of digital technologies, the Internet, and online behaviours. In 2020, the cycle was revised to measure new trends and included additional demographic variables, such as population group, perceived health, and disability status, to paint an accurate picture of the Canadian population.

In order to take account of the rapid evolution of Internet-related technologies, the 2022 cycle has been updated to include new content such as, information sharing online, harmful content online, digital credentials, cryptocurrencies, Artificial Intelligence and working in the Gig Economy.

For the 2020 and 2022 editions, to make room for this content without adding to the response burden of respondents, some questions or modules were rotated out.

Testing of the questionnaire:
Cognitive testing of the 2022 questionnaire content was tested in conjunction with the Questionnaire Design Resource Center (QDRC) in both official languages. It included 17 interviews with respondents, 10 in English and 7 in French. The interviewer assessed the respondents' understanding of new and old concepts, questions, terminology, the appropriateness of response categories and the availability of requested information. The interviews were done virtually on Teams. The respondent shared their screen and completed the electronic questionnaire (EQ) on their own, thinking aloud about their understanding and thoughts for each question. Modifications and updates were made based on respondents' comments and suggestions from the QDRC.

The tests confirmed that new content was well understood and that respondents could use the EQ application without problems. It also confirmed that old content, which was tested in 2018 and updated if necessary, was still relevant.

Sampling

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

For the 2022 iteration, the CIUS used a new frame consisting of a list of building units known to be residential dwellings taken from Statistics Canada's building frame supplemented with additional administrative sources. Records on the frame are building units such as houses or apartment units, which have addresses and/or telephone numbers linked to them.

The sample is based on a stratified design employing probability sampling. The stratification divides the geography of the ten provinces into rural and urban strata which are defined using the Statistical Area Classification (SAC). The three largest census metropolitan areas (CMAs), namely Montreal, Toronto and Vancouver, are separate strata. Information is collected from one randomly selected household member aged 15 or older, and proxy responses are not permitted.

Sampling unit:
The CIUS uses a two-stage sampling design. The first stage sampling unit is a building 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 55,700 units was used. Among them, about 51,400 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 4,300 units were contacted by telephone to complete the questionnaire with an interviewer.

Data sources

Data collection for this reference period: 2022-12-02 to 2023-04-05

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 was also conducted by CATI.

The collection method is electronic questionnaire with CATI follow-up.

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

Error detection

All responses to the 2022 CIUS questions were captured directly in the electronic questionnaire (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 values for reported family income and for the value of the amount spent on online purchases of goods and services were identified as "outliers" and treated by replacing the suspicious values by ones from respondents with similar characteristics (see Imputation).

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 2022, based on value-weighted estimates are the following: for every $100 spent in online orders for physical goods estimated from the survey, about $28.35 were imputed. For the value of amount spent online on peer-to-peer accommodation services, for every $100 spent, $20.11 was imputed. Similarly with the value of orders for other services, for every $100 spent in online orders for services estimated from the survey, $24.04 was imputed. For the majority of imputed cases, the range of the amount spent by the respondent was known.

Estimation

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 2022 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.

Quality evaluation

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, confrontation of the results was implemented to ensure that the data is consistent with other 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 and 2020 CIUS cycles, other Statistics Canada surveys, regulatory agencies (e.g. the Canadian Radio-television and Telecommunications Commission), and national / international organizations (e.g. the OECD).

Disclosure control

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.

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 of the estimates produced based on the data from 2022 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.

Response rate:
The overall response rate is 45.3%.

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. Households without a mailing address or at least one associated telephone number 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.

Non-response bias:
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.

Coverage error:
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. 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.