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Coincidence analysis: a new method for causal inference in implementation science.

Rebecca Garr Whitaker1, Nina Sperber2, Michael Baumgartner3

  • 1Duke-Margolis Center for Health Policy, 100 Fuqua Drive, Box 90120, Durham, NC, 27708, USA.

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|December 14, 2020
PubMed
Summary
This summary is machine-generated.

Coincidence Analysis (CNA) revealed new insights into human papillomavirus (HPV) vaccination uptake. It identified that offering vaccines in schools or using media coverage alongside school offerings significantly increased vaccination rates.

Keywords:
Causal inferenceCoincidence analysisComparative analysisConfigurational comparative methods

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Area of Science:

  • Implementation Science
  • Public Health Research
  • Mathematical Modeling

Background:

  • Multifaceted interventions involve complex, interrelated elements.
  • Real-world implementation research requires methods to understand causal inference.
  • Coincidence Analysis (CNA) is a novel mathematical method for analyzing causal pathways.

Purpose of the Study:

  • To apply Coincidence Analysis (CNA) to human papillomavirus (HPV) vaccination data.
  • To compare CNA findings with traditional regression analysis.
  • To identify necessary and sufficient conditions for vaccination uptake.

Main Methods:

  • Applied CNA to county-level data on HPV vaccination campaigns and uptake in Sweden (2012-2014).
  • Compared results from CNA with previously published regression findings.
  • Utilized a cross-case method for causal inference.

Main Results:

  • CNA identified multiple causal paths to high vaccination uptake, unlike regression analysis.
  • High HPV vaccination rates were achieved by offering vaccines in all schools.
  • An alternative path to high uptake involved offering vaccines in some schools combined with media coverage.

Conclusions:

  • CNA provides a novel comparative approach for implementation researchers.
  • The method aids in understanding how implementation conditions interact to influence outcomes.
  • CNA can uncover empirical findings missed by other methods.