Key result
HRV and stress markers account for up to ~27% of pain variability in elderly individuals.
Why the study?
Mobile health systems integrating wearable devices are promising for registering pain-related factors, but their application in populations with chronic conditions has been underexplored.
Does a semi-automatic mHealth system using wearable devices predict pain qualities and thresholds in elderly individuals with suspected rheumatic disease?
Cross-Sectional (n=67)
Yes
Does a semi-automatic mHealth system using wearable devices predict pain qualities and thresholds in elderly individuals with suspected rheumatic disease?
Physiological and psychological stress measures, including heart rate variability and skin conductance, significantly predict pain qualities and thresholds in elderly patients with suspected rheumatic disease.
Supports stress marker integration in elderly pain assessment; leaves open mHealth wearable utility for rheumatic disease prediction.
BACKGROUND: Mobile health systems integrating wearable devices are emerging as promising tools for registering pain-related factors. However, their application in populations with chronic conditions has been underexplored. OBJECTIVE: To design a semi-automatic mobile health system with wearable devices for evaluating the potential predictive relationship of pain qualities and thresholds with heart rate variability, skin conductance, perceived stress, and stress vulnerability in individuals with preclinical chronic pain conditions such as suspected rheumatic disease. METHODS: A multicenter, observational, cross-sectional study was conducted with 67 elderly participants. Predicted variables were pain qualities and pain thresholds, assessed with the McGill Pain Questionnaire and a pressure algometer, respectively. Predictor variables were heart rate variability, skin conductance, perceived stress, and stress vulnerability. Multiple linear regression analyses were conducted to examine the influence of the predictor variables on the pain dimensions. RESULTS: The multiple linear regression analysis revealed that the predictor variables significantly accounted for 27% of the variability in the affective domain, 14% in the miscellaneous domain, 15% in the total pain rating index, 10% in the number of words chosen, 14% in the present pain intensity, and 16% in the Visual Analog Scale scores. CONCLUSION: The study found significant predictive values of heart rate variability, skin conductance, perceived stress, and stress vulnerability in relation to pain qualities and thresholds in the elderly population with suspected rheumatic disease. The comprehensive integration of physiological and psychological stress measures into pain assessment of elderly individuals with preclinical chronic pain conditions could be promising for developing new preventive strategies.
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Gungormus et al. (2024) conducted a cross-sectional in Preclinical chronic pain conditions such as suspected rheumatic disease (n=67). Heart rate variability, skin conductance, perceived stress, and stress vulnerability was evaluated on Pain qualities and pain thresholds. Heart rate variability, skin conductance, perceived stress, and stress vulnerability significantly accounted for 10% to 27% of the variability in pain qualities and thresholds in elderly individuals.
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