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Uncovering fluctuations in daily symptoms and well-being among people with advanced cancer: An experience sampling
Joran Geeraerts1, Lara Pivodic1, Kim de Nooijer1
1Vrije Universiteit Brussel (VUB), End-of-Life Care Research Group, Brussels, Belgium.
Background:
People with advanced cancer often experience a range of symptoms and reduced well-being. Experience sampling methods, which involve completing multiple smartphone-based questionnaires per day over several days, may offer detailed insights into how these experiences unfold in daily life.
Aim:
To evaluate feasibility and acceptability of experience sampling methods in advanced cancer, and its potential to uncover moment-to-moment symptom and well-being fluctuations.
Design:
Observational study including baseline measurement, a 7-day experience sampling period with up to 10 assessments per day of symptoms and well-being, and follow-up measurement. We evaluated feasibility through response data and acceptability through a follow-up questionnaire measuring burden, ease-of-use, instruction clarity, and measurement reactivity. We analyzed fluctuations using within-person standard deviations.
Setting/Participants:
We invited 79 people with advanced breast or lung cancer via two Belgian hospitals; 40 (51%) enrolled.
Results:
Thirty-seven participants provided 1703 valid (71% of 2400 scheduled) experience sampling assessments. On 7-point scales, participants reported low burden (M = 2.1, SD = 0.8), high ease-of-use (M = 5.6, SD = 1.2) and instruction clarity (M = 6.5, SD = 0.5), and minimal measurement reactivity (M = 1.3, SD = 0.3). On 0-100 scales, we observed the greatest means of within-person fluctuations across days for tiredness (MiSD = 16.7, SD = 7.7), feeling relaxed (MiSD = 13.0, SD = 7.3), and activity limitations (MiSD = 12.4, SD = 9.9). Higher mean symptom intensity generally corresponded with greater within-person fluctuations.
Conclusion:
Experience sampling methods proved feasible and acceptable for people with advanced cancer, effectively capturing individuals' unique symptom and well-being fluctuations in daily life. The methods are a promising avenue to enhance personalized care and improve quality of life by revealing the mechanisms behind individuals' fluctuations.
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