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From Assessment to Action: A Research Prototype for SIPAT-Based Multidomain Psychosocial Visualization and
Aleksandra Stańska1, Wojciech Karolak2, Jacek Wojarski2
1Division of Quality of Life Research, Department of Psychology, Faculty of Health Sciences, Medical University of Gdańsk, 80-210 Gdańsk, Poland.
Journal of Clinical Medicine
|August 13, 2026
Summary
A new clinical decision-support tool helps organize psychosocial data for lung transplant candidates, identifying specific concerns like depression and social support deficits. This application aids clinicians in pinpointing areas needing further assessment for better patient care.
Area of Science:
- Medical Informatics
- Transplantation Surgery
- Psychosocial Medicine
Background:
- Psychosocial assessment is crucial for lung transplant candidate evaluation.
- Current methods using total scores and broad categories may obscure co-occurring concerns and modifiable domains.
- There is a need for structured data presentation to guide clinical attention.
Purpose of the Study:
- To develop and internally evaluate a clinical decision-support application.
- To reorganize Stanford Integrated Psychosocial Assessment for Transplantation (SIPAT) data into structured multidomain profiles.
- To identify specific psychosocial domains requiring further clinical attention in lung transplant candidates.
Main Methods:
- Development of an application using a retrospective dataset of 496 adult lung transplant candidates.
- Integration of SIPAT data with seven derived domain indicators, burden scores, z-scores, graphical displays, and ranked summaries.
- Utilized random forest algorithms for transforming data into percentage-scaled display values; analyses included descriptive statistics, correlations, and clustering.
Main Results:
- Identified specific concerns: depression (6.5%), anxiety (2.2%), nicotine (11.3%), alcohol (4.4%), illicit drugs (2.2%), social support deficits (8.1%), and non-adherence (1.4%).
- Exploratory clustering revealed a low-burden group (n=432), a nicotine-dominant group (n=53), and a small multidomain-elevation group (n=11).
- Generated indicators showed positive associations with SIPAT domains and total score, demonstrating internal alignment but not external validation.
Conclusions:
- The application offers a framework for organizing and visualizing SIPAT information.
- It aids in identifying psychosocial domains that may warrant additional clinical assessment.
- Outputs are decision-support indicators, requiring prospective studies for validation against clinical outcomes.
