Survey of Safety in Public and Private Spaces (SSPPS)

Detailed information for 2018




Every 5 years

Record number:


The purpose of this survey is to collect information on Canadians' experiences related to their safety in public and private spaces. Questions are asked about these personal experiences at home, in the workplace, in public spaces and online.

Data release - December 5, 2019


The purpose of this survey is to collect information on Canadians' experiences related to their safety in public and private spaces. Questions are asked about these personal experiences at home, in the workplace, in public spaces and online.

All levels of government, academics and not-for-profit organizations have expressed interest in the SSPPS results in an effort to provide a more complete and inclusive picture of the realities of gender-based violence in Canada. To help end such violence, data from this survey will be used to inform the federal government's Strategy to Prevent and Address Gender-Based Violence. The data will assist with program and policy development decisions and support research in the field of gender-based violence. Additionally, some data will facilitate comparisons with international data sources.

Reference period: Lifetime and past 12 months preceding interview date

Collection period: April through December


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

Data sources and methodology

Target population

The target population for the 2018 Survey of Safety in Public and Private Spaces is all non-institutionalized persons 15 years of age or older, living in the 10 provinces or 3 territories of Canada.

Instrument design

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), was carried out with respondents in five cities, in four provinces. 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.


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

This survey uses a frame that combines landline and cellular telephone numbers from 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, as well as telephone numbers linked to no address. This sampling frame is used to obtain better coverage of households with a telephone number.

A sample of 106,000 units was selected from the frame using stratified random sampling. The stratification is done at the province/census metropolitan area (CMA) level. The selected units were sent to the field for collection. Upon contact with a household, one household member aged 15 years of age and over was randomly selected to complete the SSPPS questionnaire. Proxy responses were not permitted.

Data sources

Data collection for this reference period: 2018-04-05 to 2018-12-31

Responding to this survey is voluntary.

Data are collected directly from survey respondents and extracted from administrative files.

Data are collected using either a respondent self-completed questionnaire or using an interviewer administered questionnaire. Contact is first made by mail for households for which an address is available. Other households are contacted via telephone only. Proxy reporting is not allowed. The respondents are provided the choice of responding between French or English.

Tax derived files (CSDD environment).

Questions relating to income typically have low response rates and the incomes reported by respondents are usually rough estimates. Instead of asking respondents to provide their income, a linkage was performed after collection to obtain the respondent's income.

The respondents were linked to their personal tax records (T1, T1FF or T4). Household information (address, postal code, and telephone number) and respondent's information (surname, name, date of birth/age, sex) were key variables for the linkage.

Linking to the tax files provides better quality data, diminishes the length of the questionnaire and decreases costs.

Respondents were notified of the planned linkage before and during the survey. Respondents who objected to the linkage of their data were excluded from the linkage.

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

Error detection

Processing used the SSPE 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.

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 family, consistency and flow edits. Family relationships were checked to ensure the integrity of data. A series of checks was done to ensure the consistency of survey data. An example was to check the respondent age against the respondent birth date. Flow edits were used to ensure respondents followed the correct path and fix off-path situations.

The flow editing carried out by head office followed a 'top down' strategy, in that whether or not a given question was considered 'on path' was based on the response codes to the previous questions. If the response codes to the previous questions indicated that the current question was 'on path', the responses, if any, to the current question were retained. If the response codes to the previous questions indicated that the current question was 'off path' because the respondent was clearly identified as belonging to a sub-population for which the current question was inappropriate or not of interest, the current question was coded as "Valid Skip", i.e. 6 (96 or 996, etc.). Due to the nature of the survey, imputation was not appropriate for most items. If a response was missing to the current question, it was coded as "Not Stated," i.e., 9 (99 or 999, etc.).

Error detection was done through edits programmed into the self-response electronic questionnaire (rEQ), as well as into the collection management system (CMP) that was used to conduct interviews either via telephone or in person (territories only).

The data capture programs allow a valid range of codes for each question and built-in edits, and automatically follow the flow of the questionnaire.

All survey records were subjected to computer edits throughout the course of the interview. The collection systems principally edit the flow of the questionnaire and identify out of range values. As a result, such problems can be immediately resolved with the respondent. If the interviewer was unable to correctly resolve the detected errors, it was possible for the interviewer to bypass the edit and forward the data to head office for resolution. Interviewer comments were reviewed and taken into account in head office editing.

Head office edits performed the same checks as the collections systems as well as more detailed edits.


To be completed when data are released


When a probability sample is used, as is the case for the SSPPS, 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 a population of 1000 people, each person in the sample represents 50 persons in the population (himself/herself and 49 others). Weighting is a process that computes a weight for each respondent. This weight appears on the microdata file, and must be used to derive meaningful estimates from the survey,

The following steps were performed to produce weights for the SSPPS:
1) Design weights were generated by computing the inverse of the probability of selection.
2) The design weights were adjusted to take into account households that were represented by more than record on the frame.
3) The weights of the households that responded to the survey were inflated to account for the households that did not respond to the survey.
4) Person level weights were computed by multiplying the household level weights by the number of eligible household members.
5) The weights were calibrated so that the sum of the weights match demographic population counts.

Quality evaluation

Quality assurance measures were implemented at every collection and processing step. Measures such as recruitment of qualified interviewers, training provided to interviewers for specific survey concepts and procedures, observations of interviews to correct questionnaire design problems and instruction misinterpretations, procedures to ensure that data captures are minimized and edit quality checks to verify the processing logics. Data are verified to ensure internal consistency and they are also compared to previous survey results to ensure historical continuity.

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 statistical program.

Data accuracy

Since the SSPPS is a sample survey, all estimates are subject to both sampling and non-sampling errors.

Non-sampling errors can be defined as errors arising during the course of virtually all survey activities, apart from sampling. These include coverage errors, non-response errors, response errors, interviewer errors, coding errors, and other types of processing errors.

The response rate for the SSPPS was 43.1%. Non-respondents often have different characteristics from respondents, which can result in bias. Attempts were made to reduce the potential nonresponse bias as much as possible through weighting adjustments.

Sampling error is defined as the error that arises because an estimate is based on a sample rather than the entire population. The sampling error for SSPPS is reported through 95% confidence intervals. The 95% confidence interval of an estimate means that if the survey were repeated over and over again, then 95% of the time (or 19 times out of 20), the confidence interval would cover the true population value.

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