Uncovering emotional and network dynamics in the speech of patients with chronic low back pain.

BACKGROUND: Computational linguistics allows an understanding of language structure and different forms of expression of patients' perceptions. AIMS: The aims of this study were (i) to carry out a descriptive analysis of the discourse of people with chronic low back pain using sentiment analysis (SA) and network analysis; (ii) to verify the correlation between patients' profiles, pain intensity and disability levels with SA and network analysis; and (iii) to identify clusters in our sample according to language and SA using an unsupervised machine learning technique. METHODS: We performed a secondary analysis of a qualitative study including participants with chronic non-specific low back pain. We used the data related to participants' feelings when they received the diagnosis. The SA and network analysis were performed using the Valence Aware Dictionary and sEntiment Reasoner, and the Speech Graph, respectively. Clustering was performed using the K-means algorithm. RESULTS: In the SA, the mean composite score was -0.31 (Sd. = 0.58). Most participants presented a negative discourse (n = 41; 72%). Word Count (WC) and Largest Strongly connected Component (LSC) positively correlated with education. No statistically significant correlations were observed between pain intensity, disability levels, SA, and network analysis. Two clusters were identified in our sample. CONCLUSION: The SA showed that participants reported their feeling when describing the moment of the diagnosis using sentences with negative discourse. We did not find a statistically significant correlation between pain intensity, disability levels, SA, and network analysis. Education level presented positive correlation with WC and LSC.

'Your spine is so worn out' - the influence of clinical diagnosis on beliefs in patients with non-specific chronic low back pain - a qualitative study'.

BACKGROUND: Patients' beliefs have an important influence on the clinical management of low back pain and healthcare professionals should be prepared to address these beliefs. There is still a gap in the literature about the influence of patients' perceptions of their clinical diagnosis on the severity of their pain experience and disability. OBJECTIVES: To identify the perceptions of patients with chronic non-specific low back pain regarding the influence of their clinical diagnosis on pain, beliefs, and daily life activities. METHODS: Qualitative study of 70 individuals with chronic non-specific low back pain. A semi structured interview was conducted about patients' beliefs and perceptions regarding the influence of clinical diagnosis on their daily activities and pain intensity. RESULTS: Most participants believed that higher number of different clinical diagnoses for the same individual may be associated with high pain intensity and disability for daily activities and that pain and injury are directly related. Patients beliefs were grouped into four main themes: (1) pain has multifactorial explanation in physical dimension; (2) improvement expectation is extremely low in patients with chronic pain; (3) clinical diagnosis influences pain and disability levels; (4) clinical diagnosis is extremely valued by patients. CONCLUSIONS: Patients believe that there is a strong relationship between structural changes in the lower back, pain, and daily life activities; thus, providing evidence of a strong influence of the biomedical model on their beliefs.