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

Publication ,  Journal Article
Whitaker, RG; Sperber, N; Baumgartner, M; Thiem, A; Cragun, D; Damschroder, L; Miech, EJ; Slade, A; Birken, S
Published in: Implement Sci
December 11, 2020

BACKGROUND: Implementation of multifaceted interventions typically involves many diverse elements working together in interrelated ways, including intervention components, implementation strategies, and features of local context. Given this real-world complexity, implementation researchers may be interested in a new mathematical, cross-case method called Coincidence Analysis (CNA) that has been designed explicitly to support causal inference, answer research questions about combinations of conditions that are minimally necessary or sufficient for an outcome, and identify the possible presence of multiple causal paths to an outcome. CNA can be applied as a standalone method or in conjunction with other approaches and can reveal new empirical findings related to implementation that might otherwise have gone undetected. METHODS: We applied CNA to a publicly available dataset from Sweden with county-level data on human papillomavirus (HPV) vaccination campaigns and vaccination uptake in 2012 and 2014 and then compared CNA results to the published regression findings. RESULTS: The original regression analysis found vaccination uptake was positively associated only with the availability of vaccines in schools. CNA produced different findings and uncovered an additional solution path: high vaccination rates were achieved by either (1) offering the vaccine in all schools or (2) a combination of offering the vaccine in some schools and media coverage. CONCLUSIONS: CNA offers a new comparative approach for researchers seeking to understand how implementation conditions work together and link to outcomes.

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Published In

Implement Sci

DOI

EISSN

1748-5908

Publication Date

December 11, 2020

Volume

15

Issue

1

Start / End Page

108

Location

England

Related Subject Headings

  • Vaccination
  • Papillomavirus Vaccines
  • Papillomavirus Infections
  • Implementation Science
  • Immunization Programs
  • Humans
  • Health Policy & Services
  • 52 Psychology
  • 32 Biomedical and clinical sciences
  • 11 Medical and Health Sciences
 

Citation

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Whitaker, R. G., Sperber, N., Baumgartner, M., Thiem, A., Cragun, D., Damschroder, L., … Birken, S. (2020). Coincidence analysis: a new method for causal inference in implementation science. Implement Sci, 15(1), 108. https://doi.org/10.1186/s13012-020-01070-3
Whitaker, Rebecca Garr, Nina Sperber, Michael Baumgartner, Alrik Thiem, Deborah Cragun, Laura Damschroder, Edward J. Miech, Alecia Slade, and Sarah Birken. “Coincidence analysis: a new method for causal inference in implementation science.Implement Sci 15, no. 1 (December 11, 2020): 108. https://doi.org/10.1186/s13012-020-01070-3.
Whitaker RG, Sperber N, Baumgartner M, Thiem A, Cragun D, Damschroder L, et al. Coincidence analysis: a new method for causal inference in implementation science. Implement Sci. 2020 Dec 11;15(1):108.
Whitaker, Rebecca Garr, et al. “Coincidence analysis: a new method for causal inference in implementation science.Implement Sci, vol. 15, no. 1, Dec. 2020, p. 108. Pubmed, doi:10.1186/s13012-020-01070-3.
Whitaker RG, Sperber N, Baumgartner M, Thiem A, Cragun D, Damschroder L, Miech EJ, Slade A, Birken S. Coincidence analysis: a new method for causal inference in implementation science. Implement Sci. 2020 Dec 11;15(1):108.
Journal cover image

Published In

Implement Sci

DOI

EISSN

1748-5908

Publication Date

December 11, 2020

Volume

15

Issue

1

Start / End Page

108

Location

England

Related Subject Headings

  • Vaccination
  • Papillomavirus Vaccines
  • Papillomavirus Infections
  • Implementation Science
  • Immunization Programs
  • Humans
  • Health Policy & Services
  • 52 Psychology
  • 32 Biomedical and clinical sciences
  • 11 Medical and Health Sciences