Process evaluation of a cluster-randomised trial testing a pressure ulcer prevention care bundle: a mixed-methods study
Related Experiment Video
Updated: Mar 7, 2026

Development of a Benchtop Model for Evaluating the Compatibility of Wound Dressing Materials with Negative Pressure Wound Therapy Systems
Published on: May 2, 2025
Shelley Roberts1, Elizabeth McInnes2, Tracey Bucknall3,4
1National Centre of Research Excellence in Nursing, Menzies Health Institute Queensland, Griffith University, Gold Coast Campus, Southport, QLD, 4222, Australia. s.roberts@griffith.edu.au.
Background:
As pressure ulcers contribute to significant patient burden and increased health care costs, their prevention is a clinical priority. Our team developed and tested a complex intervention, a pressure ulcer prevention care bundle promoting patient participation in care, in a cluster-randomised trial. The UK Medical Research Council recommends process evaluation of complex interventions to provide insight into why they work or fail and how they might be improved. This study aimed to evaluate processes underpinning implementation of the intervention and explore end-users' perceptions of it, in order to give a deeper understanding of its effects.
Methods:
A pre-specified, mixed-methods process evaluation was conducted as an adjunct to the main trial, guided by a framework for process evaluation of cluster-randomised trials. Data was collected across eight Australian hospitals but mainly focused on the four intervention hospitals. Quantitative and qualitative data were collected across the evaluation domains: recruitment, reach, intervention delivery and response to intervention, at both cluster and individual patient level. Quantitative data were analysed using descriptive and inferential statistics. Qualitative data were analysed using thematic analysis.
Results:
In the context of the main trial, which found a 42% reduction in risk of pressure ulcer with the intervention that was not significant after adjusting for clustering and covariates, this process evaluation provides important insights. Recruitment and reach among clusters and individuals was high, indicating that patients, nurses and hospitals are willing to engage with a pressure ulcer prevention care bundle. Of 799 intervention patients in the trial, 96.7% received the intervention, which took under 10 min to deliver. Patients and nurses accepted the care bundle, recognising benefits to it and describing how it enabled participation in pressure ulcer prevention (PUP) care.
Conclusions:
This process evaluation found no major failures relating to implementation of the intervention. The care bundle was found to be easy to understand and deliver, and it reached a large proportion of the target population and was found to be acceptable to patients and nurses; therefore, it may be an effective way of engaging patients in their pressure ulcer prevention care and promoting evidence-based practise.
More Related Videos
06:28E-Patient Counseling Trial E-PACO: Computer Based Education versus Nurse Counseling for Patients to Prepare for Colonoscopy
Published on: August 1, 2019
07:14A Quantitative Sensory Testing Paradigm to Obtain Measures of Pain Processing in Patients Undergoing Breast Cancer Surgery
Published on: January 18, 2018
Related Concept Videos
Nursing Process for Patient and Caregiver Teaching III: Evaluation and Documentation
Nurses can use several methods to evaluate patient outcomes. For example, oral questions can assess cognitive learning,...
Methods of Documentation III: PIE
Nursing Evaluation
Nursing Process for Patient and Caregiver Teaching II: Planning and Implementation
Nursing Process for Patient and Caregiver Teaching I: Assessment and Diagnosis
It is critical to determine the patient's learning needs during the assessment. Determination of learning needs compounds data...
The Scientific Method in Nursing Process
When using research findings to change practice, one must understand the process used to guide a study. The scientific method is a systematic, step-by-step process that supports the data's validity, reliability, and generalizability. As a result, findings can be...