ArticleCanadian journal of psychiatry. Revue canadienne de psychiatrie2022
Reading Between the Lines: A Pursuit of Estimating the Population Prevalence of Mental Illness Using Multiple Data Sources.
Article in Canadian journal of psychiatry. Revue canadienne de psychiatrie, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers.
What it found
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
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Who cites it
6 citing papers in PubMed.
- A tutorial on the what, why, and how of Bayesian analysis: Estimating mood and anxiety disorder prevalence using a Canadian data linkage study.PLOS mental health · 2025Article
- Investigating the spatiotemporal patterns and clustering of attendances for mental health services to inform policy and resource allocation in Thailand.International journal of mental health systems · 2024Article
- Surveillance of Child and Youth Mental Disorders and Associated Service Use in Canada.Canadian journal of psychiatry. Revue canadienne de psychiatrie · 2023Article
- Characterizing Help-Seeking Searches for Substance Use Treatment From Google Trends and Assessing Their Use for Infoveillance: Longitudinal Descriptive and Validation Statistical Analysis.Journal of medical Internet research · 2022Article
- Review
- Representativeness of survey participants in relation to mental disorders: a linkage between national registers and a population-representative survey.International journal of population data science · 2022Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
2 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Population-based prevalence estimates of mental illness are foundational to health service planning, strategic resource allocation, and the development and evaluation of public mental health policy. Generating valid, reliable, and context-specific population-level estimates is of utmost importance and can be achieved by combining various data sources. This pursuit benefits from the right combination of theory, applied statistics, and the conceptualization of available data sources as a collective rather than in isolation. We believe there is a need to read between the lines as theory, methodology, and context (i.e., strengths and limitations) are what determines the meaningfulness of a combined prevalence estimate. Currently lacking is a gold standard approach to combining estimates from multiple data sources. Here, we compare and contrast various approaches to combining data and introduce an idea that leverages the strengths of pre-existing individually linked population-based survey and health administrative data sources currently available in Canada.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.