This tutorial aims to introduce Hierarchical Linear Modeling (HLM). A simple explanation of HLM is provided that describes when to use this statistical technique and identifies key factors to consider before conducting this analysis. The first section of the tutorial defines HLM, clarifies its purpose, and states its advantages. The second section explains the mathematical theory, equations, and conditions underlying HLM. HLM hypothesis testing is performed in the third section. Finally, the fourth section provides a practical example of running HLM, with which readers can follow along. Throughout this tutorial, emphasis is placed on providing a straightforward overview of the basic principles of HLM.

The relationship between FCR and health care use has been understudied. Results indicate that patients with elevated FCR may indeed use more health care services. We recommend that clinicians monitor health care use in patients who are struggling with FCR.

The English version of the FCRI is a reliable and valid measure of FCR applicable to breast, colon, prostate, and lung cancer patients. Its multi-dimensional nature makes it an attractive research and clinical tool to further our knowledge of FCR.

Establishing clinical cut-offs on FCR screening measures is crucial to tailoring individual care and conducting rigorous research. Our results suggest using a higher cut-off on the FCRI-SF than previously reported to identify clinically significant FCR. Continued evaluation and validation of the FCRI-SF cut-off is required across diverse cancer populations.

ConclusionsPatients living with advanced cancers who underwent the interprofessional prp experienced significant improvement in functioning across several domains. Program completion can be predicted by a normal level of C-reactive protein.