Survey of Safety in Public and Private Spaces (SSPPS)

Detailed information for 2024/2025

This survey collects information on personal experiences with unwanted behaviours and violence at home, in the workplace, at school, in public spaces and online.

Data release - March 31, 2026

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

Description

This survey collects information on personal experiences with unwanted behaviours and violence at home, in the workplace, at school, in public spaces and online.

Data collected through this survey will allow researchers, policymakers, victim service providers and other organizations to measure the effectiveness of existing support services, improve these services, and develop new programs and strategies to prevent and address victimization.

Data from previous cycles of this survey have helped to produce the most comprehensive portrait of experiences of gender-based violence in Canada to date.

Reference period: Lifetime and past 12 months preceding interview date

Collection period: October 2024 to July 2025

Subjects

• Crime and justice
• Society and community
• Victims and victimization

Data sources and methodology

Target population

The target population for the 2024/2025 Survey of Safety in Public and Private Spaces (SSPPS) is all non-institutionalized persons 15 years of age or older, not living on an Indigenous reserve, living in the 10 provinces or 3 territories of Canada.

Instrument design

This cycle of the SSPPS combines questions from three previous Statistics Canada surveys: the Survey of Safety in Public and Private Spaces (SSPPS) 2018, the Survey of Sexual Misconduct at work (SSMW) 2020, and the Survey on Individual Safety in the Postsecondary Student Population (SISPSP) 2019. The questionnaire was designed based on research and consultations with key partners and data users. Qualitative testing, conducted by Statistics Canada's Questionnaire Design Resource Center (QDRC) in the form of one-on-one interviews, was carried out with respondents from a variety of Canadian geographical locations. Questions which worked well and others that needed clarification or redesign were identified. QDRC staff compiled a detailed report of the results along with their recommendations. All comments and feedback from qualitative testing were carefully considered and the questionnaire was revised accordingly.

Sampling

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

The sample in the provinces consists of a random sample of units selected from the 2021 Census of Population (short-form and long-form questionnaires) along with the Longitudinal Immigration Database (IMDB) and the permanent resident file received from Immigration, Refugees, Citizenship Canada (IRCC).

The sample in the territories is drawn from an area frame of dwellings.

Sampling Unit:
The survey in the provinces is a targeted respondent survey. The sampling unit is the person.
The survey in the territories is a dwelling-based survey. The sampling unit is the dwelling.

Stratification method:
For the survey in the provinces, strata are defined to achieve sufficient sample sizes in each domain of estimation and optimize sample allocation. The frame for the SSPPS is stratified by province and certain characteristics of the population like age, Indigenous identity and gender identity.

Sampling and sub-sampling:
Within each stratum of the survey in the provinces, a sample is drawn using systematic sampling, after sorting the frame by dwelling identifier, to reduce the possibility of sampling more than one person per household.

The total sample size for the SSPPS in the provinces is 145,000 individuals.

For the survey in the territories, a single eligible member of each sampled household is randomly selected to complete the questionnaire. The total sample size for the SSPPS in the territories is 5,000 dwellings.

Data sources

Data collection for this reference period: 2024-10-25 to 2025-07-17

Responding to this survey is voluntary.

Data are collected either through an electronic questionnaire or through CATI (computer assisted telephone interviews). In the territories, data are also collected through in-person interviews. The first contact with respondents (in the provinces) or dwellings (in the territories) is made by an invitation letter sent through mail.

Proxy reporting is not allowed.

Respondents are offered the option of filling in the questionnaire or are interviewed in the official language of their choice.

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

Error detection

The 2024/2025 SSPPS used the Social Survey Processing Environment (SSPE), a set of 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. The SSPE is a structured environment that monitors the processing of data, ensuring best practices and harmonized business processes are followed.

Edits were performed automatically and manually at various stages of processing at macro and micro levels. Data verification was carried out using consistency and flow edits. A series of checks was conducted to ensure the consistency of the survey data, for example, by comparing respondent's reported age with their date of birth from the sample file. Flow edits were used to ensure respondents followed the correct path and to fix irregular flow patterns.

Most error detection was performed during completion of the questionnaire using pre-determined edits programmed into the EQ system. These checks allow for a valid range of responses for each question and automatically follow the flow of the questionnaire.

During post-collection clean-up, the same checks as the EQ system were performed, as well as more specific validation of edits that are 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 information collected elsewhere in the questionnaire.

Imputation

Income questions were not asked in the survey. Income information was obtained by linking to the tax data of respondents who had agreed to the linkage to the 2024 Administrative Personal Income Masterfile (APIM). Respondents were notified of the planned linkage during data collection. Any respondents who objected to the linkage of their data had their objections recorded, and no linkage to their administrative data took place. Missing information for other respondents will be imputed.

Estimation

When a probability sample is used, as is the case for the 2024/2025 SSPPS, the principle behind estimation is that each person selected in the sample represents (in addition to himself or herself) several other persons not in the sample. For example, in a simple random sample of 2% of a population size of 1,000, each person in the sample represents 50 persons in the population. The number of persons represented by a given person in the sample is usually known as the weight or weighting factor.

The weighting factor included in the microdata file for analytical purposes is the variable named WTPM. This basic weighting factor allows analysts to calculate person-level estimates (for non-institutionalized persons aged 15 and over) for 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 (age groups, gender, province). To the extent that the characteristics are correlated with those independent estimates, this adjustment can improve the precision of estimates.

Quality evaluation

While rigorous quality assurance mechanisms are applied across all steps of the statistical process, validation and scrutiny of the data by statisticians are the ultimate quality checks prior to dissemination. Many validation measures were implemented.
These include:
1) analysis of changes over time such as examining variations in variables compared to the previous cycle;
2) verification of estimates through cross-tabulations which is done at a high level of disaggregation, to ensure internal consistency of the data file; and
3) confrontation with other similar sources of data such as the General Social Survey - Canadians' Safety (Victimization) to ensure that the reported microdata and aggregate estimates are reasonable.

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 type does not apply to this statistical program.

Data accuracy

Because the data are based on a sample of persons and dwellings, they are subject to sampling error. That is, estimates based on a sample will vary from sample to sample, and typically they will differ from those obtained from a complete census. More precise estimates of the sampling variability of estimates can be produced 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 using data from the 2024/2025 SSPPS.

Response rates:
The overall response rate was 32.4% in the provinces. The overall response rate in the territories was 53.1%.

Non-sampling error:
Common sources of these errors are imperfect coverage and non-response. Coverage errors (or imperfect coverage) occur when there are differences between the target and the surveyed population. Persons without good contact information 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 resulting biases to be small.

Non-response could occur at several stages in this survey. Survey estimates are 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 as much as possible for non-response. Supporting information was extracted from the frame and used to model and adjust for non-response.

Coverage error:
The 2024/2025 SSPPS frame is based on a combination of the 2021 short-form and long-form Canadian Census of Population, as well as the Longitudinal Immigration Database (IMDB) and the permanent resident file from IRCC; the latter two were used to ensure adequate coverage of recent immigrants. By doing so, coverage was improved by enhancing the sampling frame through these two additional data sources.

All respondents in the ten provinces were either interviewed by telephone or self-completed an electronic questionnaire. All respondents in the territories were interviewed by telephone, self-completed an electronic questionnaire, or had an in-person interview. 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:
For the 2024/2025 SSPPS, significant effort was made to minimize bias by using a well-tested questionnaire, proven methodology, specialized interviewers and strict quality control.