Evidence map›Paper›PMID 25630218›Full record

ArticleBMC public health2015

The validity of self-reported cancer screening history and the role of social disadvantage in Ontario, Canada.

Aisha Lofters, Mandana Vahabi, Richard H Glazier

Open access · goldAbstract readValidation Study
In one paragraph

Article in BMC public health, 2015. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 50 papers, 2 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
50citing papers in PubMed, 2 pooled it
3.4field-weighted citation impact, top 6% of its field
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

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.

2 · The registry

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.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

50 citing papers in PubMed, 2 syntheses or guidelines pooled it, 87 citations in OpenAlex.

  1. Pooled it
  2. Pooled it
  3. Article
  4. Kin KeeperJournal of cancer education : the official journal of the American Association for Cancer Education · 2026
    Article
  5. Article
  6. Accuracy of Self-Reported Cervical Screening Status Among Pregnant Women.The Australian & New Zealand journal of obstetrics & gynaecology · 2026
    Article
  7. Article
  8. Article
  9. Article
  10. Leveraging mHealth Technologies for Public Health.JMIR public health and surveillance · 2024
    Review
  11. Observational
  12. Article
  13. Article
  14. Article
  15. Gaps in Adhering to Pap Testing Recommendations and Related Barriers in a Sample of Young Adults in the US.Journal of cancer education : the official journal of the American Association for Cancer Education · 2023
    Article
  16. Article
  17. Article
  18. Lower Utilization of Colorectal Cancer Screening Among Vegetarians, Adventist Health Study-2.Journal of cancer education : the official journal of the American Association for Cancer Education · 2022
    Article
  19. Article
  20. Review
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

3 authors at 2 institutions in 1 country.

Aisha LoftersSt. Michael's Hospital Department of Family and Community Medicine, University of Toronto, Toronto, Canada. Aisha.lofters@utoronto.ca.
Mandana VahabiCentre for Research on Inner City Health, Li Ka Shing Knowledge Institute, St. Michael's Hospital, Toronto, Canada. mvahabi@ryerson.ca.
Richard H GlazierSt. Michael's Hospital Department of Family and Community Medicine, University of Toronto, Toronto, Canada. Rick.glazier@ices.on.ca.
University of Toronto · CASt. Michael's Hospital · CA

Funding

Canadian Institutes of Health Research
6 · The paper itself

Abstract

backgroundSelf-report may not be an accurate method of determining cervical, breast and colorectal cancer screening rates due to recall, acquiescence and social desirability biases, particularly for certain sociodemographic groups. Therefore, the aims of this study were to determine the validity of self-report of cancer screening in Ontario, Canada, both for people in the general population and for socially disadvantaged groups based on immigrant status, ethnicity, education, income, language ability, self-rated health, employment status, age category (for cervical cancer screening), and gender (for fecal occult blood testing).

methodsWe linked multiple data sources for this study, including the Canadian Community Health Survey and provincial-level health databases. Using administrative data as our gold standard, we calculated validity measures for self-report (i.e. sensitivity, specificity, positive and negative likelihood ratios, positive and negative predictive values), calculated report-to-record ratios, and conducted a multivariable regression analysis to determine which characteristics were independently associated with over-reporting of screening.

resultsSpecificity was less than 70% overall and for all subgroups for cervical and breast cancer screening, and sensitivity was lower than 80% overall and for all subgroups for fecal occult blood testing FOBT. Report-to-record ratios were persistently significantly greater than 1 across all cancer screening types, highest for the FOBT group: 1.246 [1.189-1.306]. Regression analyses showed no consistent patterns, but sociodemographic characteristics were associated with over-reporting for each screening type.

conclusionsWe have found that in Ontario, as in other jurisdictions, there is a pervasive tendency for people to over-report their cancer screening histories. Sociodemographic status also appears to influence over-reporting. Public health practitioners and policymakers need to be aware of the limitations of self-report and adjust their methods and interpretations accordingly.

Indexed as

Self DisclosureSelf ReportAdultColorectal NeoplasmsEarly Detection of CancerFemaleHumansMaleMass ScreeningMiddle AgedOntarioPatient ParticipationSensitivity and SpecificityUterine Cervical Neoplasms

Identifiers

PMID25630218
PMCPMC4319224
OpenAlexW1965032600

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

None linked

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.