This guide provides the necessary definitions, protocols, and context for entering and interpreting data from the CHSCY 2023 cross-sectional file. Statistics Canada's copy of this description (the basis of this interpreted description) is also available within the data's file.

A. Core Data Source Information

• Primary Source: Statistics Canada, Canadian Health Survey on Children and Youth (CHSCY): 2023 cross-sectional file.
• Target Population: The survey covers the population aged 1 to 17 as of January 31, 2023, living in the ten Canadian provinces.
• Key Population Exclusions: The following populations are not included in this dataset and should not be considered part of the survey's scope:
  • Children and youth residing in the three Territories (Yukon, Northwest Territories, Nunavut).
  • Children and youth living on First Nation reserves and other Aboriginal settlements.
  • Children and youth living in foster homes.
  • The institutionalized population.
• Respondent: Data is reported by the "person most knowledgeable" (PMK) in the household on behalf of a child aged 1 to 17. The PMK is typically a parent or legal guardian.

B. Data Entry & Handling Protocols

This section outlines the specific rules for data entry and flagging.

1. Rounding Convention:
   • Aggregate numbers (e.g., total population counts) must be rounded to the nearest hundred.
   • Percentages must be rounded to the nearest tenth (e.g., 15.3%).
2. Handling of Missing Data:
   • All estimates (percentages, averages) are calculated by excluding non-response categories (e.g., "not stated", "refused") from the denominator. Ensure any calculations performed on the raw data follow this rule.
3. Data Quality Flags: When entering or displaying data, apply the following flags as provided in the source file:
   • (E) Use with Caution: This flag indicates an estimate with poorer quality. This is due to a high coefficient of variation (CV) or a small sample size. These data points can be used but should be interpreted with caution due to high variability.
   • (F) Suppressed: This flag indicates that the data has been withheld by Statistics Canada to meet the confidentiality requirements of the Statistics Act. These fields should be left blank or marked as "Suppressed."

C. Data Dictionary: Key Variable Definitions

Use these official definitions when labeling variables in databases and in any reports or visualizations.

• Self-Perceived Health:
  • Description: The perception of a child's general health, as reported by the PMK. "Health" is defined holistically, encompassing not only the absence of disease or injury but also physical, mental, and social well-being.
  • Categories: Typically reported as "very good or excellent" or "fair or poor."
• Self-Perceived Mental Health:
  • Description: The perception of a child's general mental health, as reported by the PMK. This provides an indication of potential mental disorders, emotional problems, or distress, which may not be captured by the general health question.
  • Categories: Typically reported as "very good or excellent" or "fair or poor."
• Learning Disability / Disorder:
  • Applies to: Children and youth aged 5 to 17.
  • Description: Indicates whether the child has been diagnosed with a learning disability or learning disorder by a health professional, as reported by the PMK.
• Regular Health Care Provider:
  • Applies to: Children and youth aged 1 to 17.
  • Description: Indicates whether the child has a regular health care provider, as reported by the PMK.

D. Methodological Notes for Analysis & Interpretation

This information is crucial for anyone analyzing the data or writing reports.

• Statistical Reliability: Estimates are accompanied by a 95% Confidence Interval (95% CI).
  • The CI illustrates the degree of variability associated with an estimate.
  • Rule of Thumb: Wide confidence intervals indicate high variability and suggest the estimate is less precise. These estimates should be used with due caution.
  • Methodology: The CIs were produced using bootstrapping techniques.
• Comparing Estimates: When comparing two values (e.g., across regions or time), it is essential to use the confidence intervals to determine if the difference between them is statistically significant. If the CIs overlap, the difference may not be significant.