Implementing the actor-partner interdependence model for dyadic data analysis: an overview for the nurse researcher
Intended for healthcare professionals
Evidence and practice    

Implementing the actor-partner interdependence model for dyadic data analysis: an overview for the nurse researcher

Mahdi Shamali PhD fellow researcher, Department of Clinical Research, University of Southern Denmark, Odense, Denmark
Birte Østergaard Associate professor, University of Southern Denmark, Odense, Denmark

Background The actor-partner interdependence model (APIM) is widely used to study people with close relationships, such as patients and their partners. However, the complexity of the model has made it difficult to implement in nursing research.

Aim To provide a simplified description of the model, highlight the key assumptions of dyadic data and examine the related challenges in using statistical techniques.

Discussion Researchers must address certain assumptions when analysing dyadic data. They should select statistical techniques based on these assumptions and the research questions.

Conclusion The AIPM is the most appropriate approach for studying dyads. This article may help to create a more consistent framework for nurse researchers who incorporate the APIM into their studies.

Implications for practice This article will help in implementing APIM in dyad-focused nursing studies by addressing key assumptions of the model and using appropriate statistical techniques.

Nurse Researcher. doi: 10.7748/nr.2019.e1651

Peer review

This article has been subject to external double-blind peer review and has been checked for plagiarism using automated software

Correspondence

gezaltoshmal@yahoo.com

Conflict of interest

None declared

Shamali M, Østergaard B (2019) Implementing the actor-partner interdependence model for dyadic data analysis: an overview for the nurse researcher. Nurse Researcher. doi: 10.7748/nr.2019.e1651

Acknowledgement This work was funded by Novo Nordisk Foundation, grant number NNF17OC0027968

Published online: 25 September 2019

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