Menna Komeiha, Gregory Kujbida, Aideen Reynolds, Ikenna Mbagwu, Laurie Dojeiji, Joseph J O'Rourke, Shilpa Raju, Monali Varia, Helen Stylianou, Sydnee Burgess, Oluwasegun Jko Ogundele, Andrew D Pinto
{"title":"关于加拿大安大略省公共卫生单位在 COVID-19 大流行期间收集社会人口数据的促进因素和障碍的研究。","authors":"Menna Komeiha, Gregory Kujbida, Aideen Reynolds, Ikenna Mbagwu, Laurie Dojeiji, Joseph J O'Rourke, Shilpa Raju, Monali Varia, Helen Stylianou, Sydnee Burgess, Oluwasegun Jko Ogundele, Andrew D Pinto","doi":"10.1186/s12889-024-20519-4","DOIUrl":null,"url":null,"abstract":"<p><strong>Background: </strong>Collection and use of sociodemographic data (SDD), including race, ethnicity and income, are foundational to understanding health inequities. Ontario's public health units collected SDD as part of COVID-19 case management and vaccination activities. This research aimed to identify enablers and barriers to collecting SDD during COVID-19 case management and vaccination.</p><p><strong>Methods: </strong>As part of a larger mixed-method research study [1], qualitative methods were used to identify enablers and barriers to SDD collection during the COVID-19 pandemic. Purposive sampling was used to recruit participants from Ontario's 34 public health units. Sixteen focus groups and eight interviews were conducted virtually using Zoom. Interview data were transcribed and analyzed using inductive and deductive qualitative description.</p><p><strong>Results: </strong>SDD collection enablers included: legally mandating SDD collection and having dedicated data systems, technological and legal supports, senior management championing SDD collection, establishing rapport and trust between staff and clients, and gaining insight from the experiences from local communities and other jurisdictions. Identified barriers to SDD collection included: provincial data systems being perceived as lacking user-friendliness, SDD collection \"was not a priority,\" time and other constraints on building staff and client rapport, and perceived discomfort with asking and answering personal SDD questions.</p><p><strong>Conclusion: </strong>A combination of provincial and local organizational strategies including supportive data systems, training, and frameworks for data collection and use, are needed to normalize and scale up SDD collection by local health units beyond the context of the COVID-19 pandemic.</p>","PeriodicalId":9039,"journal":{"name":"BMC Public Health","volume":null,"pages":null},"PeriodicalIF":3.5000,"publicationDate":"2024-11-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11539653/pdf/","citationCount":"0","resultStr":"{\"title\":\"A study of the enablers and barriers to the collection of sociodemographic data by public health units in Ontario, Canada during the COVID-19 pandemic.\",\"authors\":\"Menna Komeiha, Gregory Kujbida, Aideen Reynolds, Ikenna Mbagwu, Laurie Dojeiji, Joseph J O'Rourke, Shilpa Raju, Monali Varia, Helen Stylianou, Sydnee Burgess, Oluwasegun Jko Ogundele, Andrew D Pinto\",\"doi\":\"10.1186/s12889-024-20519-4\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<p><strong>Background: </strong>Collection and use of sociodemographic data (SDD), including race, ethnicity and income, are foundational to understanding health inequities. Ontario's public health units collected SDD as part of COVID-19 case management and vaccination activities. This research aimed to identify enablers and barriers to collecting SDD during COVID-19 case management and vaccination.</p><p><strong>Methods: </strong>As part of a larger mixed-method research study [1], qualitative methods were used to identify enablers and barriers to SDD collection during the COVID-19 pandemic. Purposive sampling was used to recruit participants from Ontario's 34 public health units. Sixteen focus groups and eight interviews were conducted virtually using Zoom. Interview data were transcribed and analyzed using inductive and deductive qualitative description.</p><p><strong>Results: </strong>SDD collection enablers included: legally mandating SDD collection and having dedicated data systems, technological and legal supports, senior management championing SDD collection, establishing rapport and trust between staff and clients, and gaining insight from the experiences from local communities and other jurisdictions. 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A study of the enablers and barriers to the collection of sociodemographic data by public health units in Ontario, Canada during the COVID-19 pandemic.
Background: Collection and use of sociodemographic data (SDD), including race, ethnicity and income, are foundational to understanding health inequities. Ontario's public health units collected SDD as part of COVID-19 case management and vaccination activities. This research aimed to identify enablers and barriers to collecting SDD during COVID-19 case management and vaccination.
Methods: As part of a larger mixed-method research study [1], qualitative methods were used to identify enablers and barriers to SDD collection during the COVID-19 pandemic. Purposive sampling was used to recruit participants from Ontario's 34 public health units. Sixteen focus groups and eight interviews were conducted virtually using Zoom. Interview data were transcribed and analyzed using inductive and deductive qualitative description.
Results: SDD collection enablers included: legally mandating SDD collection and having dedicated data systems, technological and legal supports, senior management championing SDD collection, establishing rapport and trust between staff and clients, and gaining insight from the experiences from local communities and other jurisdictions. Identified barriers to SDD collection included: provincial data systems being perceived as lacking user-friendliness, SDD collection "was not a priority," time and other constraints on building staff and client rapport, and perceived discomfort with asking and answering personal SDD questions.
Conclusion: A combination of provincial and local organizational strategies including supportive data systems, training, and frameworks for data collection and use, are needed to normalize and scale up SDD collection by local health units beyond the context of the COVID-19 pandemic.
期刊介绍:
BMC Public Health is an open access, peer-reviewed journal that considers articles on the epidemiology of disease and the understanding of all aspects of public health. The journal has a special focus on the social determinants of health, the environmental, behavioral, and occupational correlates of health and disease, and the impact of health policies, practices and interventions on the community.