Assessing user experience with services: measuring subjective well-being in oncology hospitals
Abstract Background Capturing subjective user experiences is crucial for service design, assessment, and management. However, using metrics for such experiences remains an underexplored topic in the literature. This study introduces a novel survey tool to measure service-related subjective well-bein...
Saved in:
| Main Authors: | , , , , , |
|---|---|
| Format: | Article |
| Language: | English |
| Published: |
BMC
2025-06-01
|
| Series: | BMC Health Services Research |
| Subjects: | |
| Online Access: | https://doi.org/10.1186/s12913-025-12965-6 |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
| Summary: | Abstract Background Capturing subjective user experiences is crucial for service design, assessment, and management. However, using metrics for such experiences remains an underexplored topic in the literature. This study introduces a novel survey tool to measure service-related subjective well-being (SWB) among oncology patients, encompassing the three dimensions of SWB: positive affect, negative affect, and life satisfaction. The hypotheses are that (H1) highly reliable service-related SWB metrics will be generated based on reliable tools from psychology, and (H2) perceived service experience will strongly predict positive affect and life satisfaction, but they will have less predictive power for negative affect. These hypotheses are supported by research suggesting that services can improve positive affect but may not fully counteract the negative affect evoked by cancer. Methods We conducted a cross-sectional survey of 288 oncology patients using convenience sampling. The online survey was divided into three segments: patient information, SWB measures, and perceived service experience. The SWB measures encompassed its three dimensions. The survey items were adapted from consolidated psychological research scales for this study. This theory-driven approach, known as the ‘construct method,’ involves generating hypotheses based on construct theory and testing them empirically. Participants completed the survey within seven days of hospital discharge. Our data analysis included reliability measures, exploratory factor analysis on the SWB items, and regression analyses to examine the predictive power of perceived service experience on SWB. Results The survey demonstrated high reliability (Cronbach’s Alpha = 0.946). Factor analysis indicated a two-factor model, explaining 78.01% of the total variance, with a separation of positive and negative items. Regression analysis revealed that perceived service experience substantially explained SWB. Positive affect and life satisfaction were well-predicted by perceived experiences with nursing, medical, and infrastructure, while negative affect was less well-predicted. H1 was confirmed by high-reliability metrics, and H2 was supported by the regression results. Conclusions The survey can identify areas for improvement, optimize services, and measure the relationships between perceived service experience and SWB, contributing to the literature on healthcare user experience and service design metrics. |
|---|---|
| ISSN: | 1472-6963 |