Survey on Opioid Awareness (SOA)
Detailed information for November 2017
The main objective of the Survey on Opioid Awareness is to better understand the current level of knowledge of the general Canadian population regarding opioids. This survey will also collect information regarding the willingness and ability of Canadians to act in the event of an opioid overdose.
Data release - January 9, 2018
The need for timely and relevant data on opioids to help inform a coordinated response to the opioid crisis has been identified as a priority for all levels of government.
Statistics Canada is working closely with federal departments, as well as provincial and municipal governments to identify existing data gaps and opportunities to develop innovative and timely approaches to producing data in support of policy and programming activities.
The survey results could be used by government officials, social services and community organizations to help tailor future awareness campaigns with the goal of reducing risks.
- Health and well-being
Data sources and methodology
The target population for the survey is non-institutionalized persons 18 years of age or older, living in Canada's ten provinces.
The content of the Survey on Opioid Awareness electronic questionnaire was drafted in consultation with several other federal government departments such as Health Canada, the Public Health Agency of Canada and Public Safety 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.
This is a sample survey with a cross-sectional design.
The frame is the Dwelling Universe File (DUF). Dwellings in the Yukon, the Northwest Territories and Nunavut were excluded, as well as institutions, collective dwellings and dwellings on Indigenous reserves.
The SOA 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.
The SOA frame was stratified by province, and a simple random sample of dwellings was selected independently within each province.
Sufficient sample was allocated to each of the provinces so that the survey could produce province level estimates, with the exception of the four eastern provinces. Newfoundland and Labrador, Prince Edward Island, Nova Scotia and New Brunswick were grouped into one region, and sufficient sample was allocated to the region in order to produce region level estimates. An initial sample of 10,000 dwellings was selected and sent to collection.
Data collection for this reference period: November 10, 2017 to December 07, 2017
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 or through CATI (computer assisted telephone interviewing).
View the Questionnaire(s) and reporting guide(s) .
Electronic files containing the daily transmissions of completed respondent survey records were combined to create the "raw" survey file. Before further processing, verification was performed to identify and eliminate potential duplicate records and to drop non-response and out-of-scope records.
In addition, some out-of-scope respondent records were found during the data clean-up stage. All respondent records that were determined to be out-of-scope and those records that contained no data were removed from the data file.
After the verification stage, editing was performed to identify errors and modify affected data at the individual variable level. The first editing step was to identify errors and determine which items from the survey output needed to be kept on the survey master file. Subsequent to this, invalid characters were deleted and the remaining data items were formatted appropriately.
The first type of errors treated were errors in questionnaire flow. For skips based on answered questions, all skipped questions were set to "Valid skip" (6, 96, 996, etc.). For skips based on "Don't know" or "Refusal", all skipped questions were set to "Not stated" (9, 99, 999, etc.). The remaining empty items were filled with a numeric value (9, 99, 999, etc., depending on variable length). These codes are reserved for processing purposes and mean that the item was "Not stated".
This methodology type does not apply to this statistical program.
The estimation of population characteristics from a sample survey is based on the premise that each person in the sample represents a certain number of other persons in addition to themselves. This number is referred to as the survey weight. The process of computing survey weights for each survey respondent involves several steps.
1) Each selected dwelling is given an initial weight equal to the inverse of its selection probability from the sampling frame (DUF). Dwellings identified as out-of-scope during collection are dropped from the sample.
2) The weights for responding households are adjusted to represent the households that did not respond. Adjustment factors are calculated separately by province and dwelling type (single-detached house / other).
3) The household weights are calibrated so that the sum of the weights match province level household size demographic counts.
4) Person weights are computed by multiplying the household level weights by the inverse of the probability of selecting the person within the household.
5) The person weights are calibrated so that the sum of the weights match demographic population counts at the region by age group by gender level. The weights are also calibrated to demographic counts for large Census Metropolitan Areas (CMAs).
Variance estimation is based on a resampling method called the bootstrap.
The Generalized Estimation System (G-Est) was used to generate the survey weights and bootstrap weights.
Many validation measures were implemented, they include:
a. Verification of estimates through cross-tabulations
b. Consultation with stakeholders internal to Statistics Canada
c. Consultation with external stakeholders
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.
Survey errors come from a variety of different sources. One dimension of survey error is sampling error. Sampling error is defined as the error that arises because an estimate is based on a sample rather than the entire population. Sampling error can be expressed through a confidence interval (CI) or coefficient of variation (CV).
The following are approximate sampling error estimates for Canada level estimates. These are based on average results; these are not results for a specific variable.
- Approximate length of 95% confidence intervals for a proportion of 50% (Canada level): 4.0%
- Approximate length of 95% confidence intervals for a proportion of 10% (Canada level): 2.5%
- Approximate coefficients of variation (CVs) for a proportion of 10% (Canada level): 6%
The response rate for the SOA was 54%.
The survey estimates are adjusted to account for non-response through the survey weights. To the extent that the non-responding households and persons differ from the rest of the sample, the results may be biased.
Coverage errors arise when there are differences between the target population and the observed population. The observed population is persons living in dwellings with mailable addresses on the frame. Approximately 95% of the dwellings on the frame had mailable addresses. To the extent that the excluded population differs from the rest of the target population, the results may be biased.