A semi-automatic mHealth system using wearable devices for identifying pain-related parameters in elderly individuals.

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.

The Impact of Upper Limb Apraxia on General and Domain-Specific Self-Efficacy in Post-Stroke Patients.

BACKGROUND: Upper limb apraxia (ULA) is a neurological syndrome characterized by the inability to perform purposeful movements. ULA could impact individuals' perceptions, including perceived self-efficacy. The aim of this study is to investigate whether ULA is related to general self-efficacy and self-efficacy for managing symptoms in post-stroke patients. METHODS: A cross-sectional study was conducted involving 82 post-stroke patients. Regression analyses were implemented using a stepwise model including seven dimensions of ULA: imitation (non-symbolic, intransitive, and transitive), pantomime (non-symbolic, intransitive, and transitive), and dimension of apraxic performance in activities of daily living. These dimensions were independent variables, while general self-efficacy and symptom management self-efficacy dimensions were dependent variables. RESULTS: The findings revealed that intransitive imitation accounted for 14% of the variance in general self-efficacy and 10% of self-efficacy for managing emotional symptoms. Transitive imitation explained 10% of the variance in self-efficacy for managing global symptoms and 5% for social-home integration symptoms. The combination of intransitive imitation, non-symbolic pantomime, and alterations in activities of daily living performance associated with ULA explained 24% of the variance in cognitive self-efficacy. CONCLUSIONS: Hence, ULA dimensions seem to be related to the levels of general perceived self-efficacy and self-efficacy for managing symptoms among post-stroke patients.