Skip to content
DraconiticResearch
Search Sources API
203,234 studies31 sourcesUpdated 6 min ago
Peer-reviewedCC BY-NC 4.0Paediatrics & Child Health

Language, culture, and ethnicity data collection in pediatric healthcare in Canada: a national environmental scan

Abstract

Background and Objectives: Canada's pediatric healthcare systems serve an increasingly ethnoculturally diverse population, yet the standardized collection of language, culture, and ethnicity (LCE) data remains inconsistent. Without reliable data, health systems cannot identify inequities, monitor disparities, or design targeted interventions. Our purpose was to examine current LCE data collection practices across pediatric healthcare settings in Canada and identify perceived barriers, enablers, and opportunities to strengthen equitable data infrastructure.

Methods: A cross-sectional environmental scan was conducted between January and February 2026 using an anonymous online survey of pediatric healthcare clinicians and staff across Canada. The survey included closed- and open-ended questions on LCE data collection practices, tools, effectiveness, data use, training, and organizational supports. Quantitative data were analyzed descriptively; qualitative responses underwent inductive content analysis.

Results: A total of 237 participants from diverse pediatric settings completed the survey. Nearly 60% reported that their organization does not collect LCE data, and 56% were unsure of the effectiveness of existing practices. When collected, LCE data were primarily limited to preferred language and used to identify interpreter needs. Formal training and organizational policies were rare (both 3%). Perceived barriers included a lack of training, time constraints, and the absence of standardized tools. Qualitative findings highlighted strong conceptual support for LCE data collection but emphasized its conditional value, ethical complexity, and need for participatory approaches.

Conclusion: LCE data collection in Canadian pediatric healthcare remains fragmented and underutilized. Advancing equitable data infrastructure will require standardized protocols, targeted training, participatory co-design, and clear accountability for data use.

Related

  1. Cervical Cancer Screening Rates by Race and Ethnicity, Age, Language, and Census Region
    Yunbo Xie, Linh Nguyen, Yen-Chi Le +1
    JAMA network openPeer-reviewedCC BY-NC-NDFull textEpidemiology & public healthEurope PMCCrossref
  2. A Multi‐Objective Periodic Vehicle Routing Model for Sustainable Healthcare Waste Collection
    Hajer Ben‐Romdhane
    The International Journal of Health Planning and ManagementPeer-reviewedCC BY-NC 4.0Full text1 citedEpidemiology & public healthPMC
  3. Building a framework for successful transition from pediatric to adult healthcare in Down syndrome
    J. Hubrechts, N. Mahlaoui, H. Franckx +4
    Frontiers in pediatricsPeer-reviewedCC BYFull textGeneral medicineEurope PMC
  4. The rise of small language models in healthcare: A comprehensive survey
    Muskan Garg, Shaina Raza, Shebuti Rayana +2
    Computer Science ReviewPeer-reviewedLicence not stated58 citedEpidemiology & public healthOpenAlex
  5. Factors associated with the quality of urban geriatric healthcare services empowered by large language models and improvement pathways: a theoretical framework and cross-sectional study
    Xiaoyan Qi, Xuejiao Song, Jingkai Xu +3
    BMC Public HealthPeer-reviewedCC BY-NC-ND 4.0Epidemiology & public healthCrossref
BibTeX
@article{do2026language,
  title = {{Language, culture, and ethnicity data collection in pediatric healthcare in Canada: a national environmental scan}},
  author = {Victor Do and Amanda S Newton and Rebecca Gokiert and Geoff D C Ball},
  journal = {Paediatrics \& Child Health},
  year = {2026},
  month = jul,
  doi = {10.1093/pch/pxag069},
  url = {https://doi.org/10.1093/pch/pxag069},
  note = {CC BY-NC 4.0},
}
RIS
TY  - JOUR
TI  - Language, culture, and ethnicity data collection in pediatric healthcare in Canada: a national environmental scan
AU  - Victor Do
AU  - Amanda S Newton
AU  - Rebecca Gokiert
AU  - Geoff D C Ball
PY  - 2026
DA  - 2026/07/22
JO  - Paediatrics & Child Health
DO  - 10.1093/pch/pxag069
UR  - https://doi.org/10.1093/pch/pxag069
AB  - Background and Objectives: Canada's pediatric healthcare systems serve an increasingly ethnoculturally diverse population, yet the standardized collection of language, culture, and ethnicity (LCE) data remains inconsistent. Without reliable data, health systems cannot identify inequities, monitor disparities, or design targeted interventions. Our purpose was to examine current LCE data collection practices across pediatric healthcare settings in Canada and identify perceived barriers, enablers, and opportunities to strengthen equitable data infrastructure.  Methods: A cross-sectional environmental scan was conducted between January and February 2026 using an anonymous online survey of pediatric healthcare clinicians and staff across Canada. The survey included closed- and open-ended questions on LCE data collection practices, tools, effectiveness, data use, training, and organizational supports. Quantitative data were analyzed descriptively; qualitative responses underwent inductive content analysis.  Results: A total of 237 participants from diverse pediatric settings completed the survey. Nearly 60% reported that their organization does not collect LCE data, and 56% were unsure of the effectiveness of existing practices. When collected, LCE data were primarily limited to preferred language and used to identify interpreter needs. Formal training and organizational policies were rare (both 3%). Perceived barriers included a lack of training, time constraints, and the absence of standardized tools. Qualitative findings highlighted strong conceptual support for LCE data collection but emphasized its conditional value, ethical complexity, and need for participatory approaches.  Conclusion: LCE data collection in Canadian pediatric healthcare remains fragmented and underutilized. Advancing equitable data infrastructure will require standardized protocols, targeted training, participatory co-design, and clear accountability for data use.
SN  - 1205-7088
SN  - 1918-1485
ER  -