ESDC Employee Wellness Survey (ESDC EWS)

Detailed information for 2022

Status:

Active

Frequency:

One Time

Record number:

5379

The ESDC Employee Wellness Survey (ESDC EWS) provides an assessment of the key factors in the work environment that affect the well-being of Employment and Social Development Canada (ESDC) employees. Topics include, for example, work-life balance, job satisfaction and performance, and training and development opportunities.

Data release - March 8, 2023

Description

Results from the ESDC EWS provide information on specific factors in the work environment that could affect employee well-being. This includes, for example, work-life balance, job satisfaction and performance.

The results can be used to assess conditions in the work environment at ESDC and inform strategies that meet the needs of employees and optimize their well-being.

Reference period: Varies according to the question, but mainly "in the last 6 months"

Collection period: Early Fall

Subjects

  • Hours of work and work arrangements
  • Mental health and well-being
  • Workplace organization, innovation, performance

Data sources and methodology

Target population

The target population for the ESDC EWS is active employees of ESDC, including indeterminate, term, seasonal, casual and student employees.

Instrument design

The ESDC EWS drew heavily from the Statistics Canada Employee Wellness Survey conducted in 2021. Almost all multi-item questions (grids) used in the ESDC EWS are scientifically validated and reliable measures based on leading psychological literature. The references to the literature are included in the survey questionnaire and codebooks. The survey also used content from other Statistics Canada surveys or from Statistics Canada harmonized content.

Sampling

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

Sampling unit
The sampling unit is the employee.

Stratification method
Not applicable

Sampling and sub-sampling
This survey was a census of approximately 37,000 employees. Data were collected for all units of the target population, so no sampling was done.

Data sources

Data collection for this reference period: 2022-10-03 to 2022-11-07

Responding to this survey is voluntary.

Data are collected directly from survey respondents.

The survey frame was created from lists of employees prepared by ESDC and provided to Statistics Canada.

Each person in the survey frame was contacted by email and invited to complete an electronic questionnaire on Statistics Canada's website. During collection, six reminder emails were sent on a regular basis to participants who had not submitted their completed electronic questionnaire.

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

Error detection

Some consistency edits were carried out on the ESDC EWS data files. These edits were done primarily to ensure consistency between occupational groups and levels at ESDC, and between the age of the respondent and the number of years working in their organization or in the federal public service.

Imputation

This methodology does not apply.

Estimation

The ESDC EWS is a census. Although all eligible employees were included in the survey frame, it was necessary to weight the responding units so they were representative of the target population, because of the levels of non-response. This exercise was performed on the original response file to create the master weights and on the subset of respondents who agreed to share their data with ESDC to create the share weights. There is one weight for each record on these two microdata files.

Survey weights must be used to derive estimates from the survey or they cannot be deemed representative of the survey population and will not correspond to estimates produced by Statistics Canada.

In addition to the survey weights, 1,000 bootstrap replicate weights were generated for producing variance estimates and confidence intervals for the estimates to evaluate quality.

Quality evaluation

A few edits were programmed in the ESDC EWS electronic questionnaire in case a respondent entered an unexpected value. In this case, a message appeared asking them to confirm their response.

The majority of the validation of ESDC EWS data occurred in tandem with data editing activities. The survey team reviewed the survey data at each data editing step (cleanup, recode, flow edit, coding and consistency edit) to ensure that the rules they provided were properly applied. The survey team also provided specifications for derived variables to be created, then verified that the variables were developed according to their specifications.

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.

Revisions and seasonal adjustment

This methodology does not apply.

Data accuracy

Analysis done on the pre-release data also counted as a data validation step. Any possible errors were flagged and investigated, leading to corrections of the data.

Response rate:
The overall response rate for the ESDC EWS was 49.1%.

The survey was developed in the Electronic Questionnaire Generation System and collected using the Collection Management Portal. The returned survey data were processed in the Social Survey Processing Environment.

Non-sampling error
Non-sampling errors can be defined as errors arising during the course of virtually all survey activities, apart from sampling. These errors arise primarily from the following sources: non-response, coverage, measurement and processing.

Considerable time and effort were taken to reduce non-sampling errors in the survey. Quality assurance measures were implemented at each step of the questionnaire development, data collection and processing cycle to monitor the quality of the data.

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