Factors that influence the impact of Chronic Non-Cancer Pain on daily life: A partial least squares modelling approach

Abstract

Background: Chronic Non-Cancer Pain is pain of more than three months' duration and is not associated with an oncological condition. There is ample literature that recognises that Chronic Non-Cancer Pain impacts numerous areas of the life of the person who suffers from it. This impact is difficult to determine and quantify because Chronic Pain is a subjective experience.

Objective: The objective of this study was to test a recursive model of hypothesised factors that comprise the concept of Chronic Non-Cancer Pain Impact on daily life using Partial Least Squares-Structural Equation Modelling.

Design: A cross-sectional study was carried out. The sample size was calculated using G*Power V.3.1.9.4 with five parameters (two-tailed, large effect size (f2 = 0.35), power of 0.95, statistical significance of 95% (α = 0.05) and 36 predictors). The minimum number of subjects was considered to be 137.

Methods: A recursive model was built based on data from a sample of 395 people over 18 years of age with Chronic Non-Cancer Pain. Data collection was conducted between January and March 2020 at Pain Units and Primary Healthcare Centres belonging to the Spanish Public Health System in the province of Seville (Spain). Analyses were based on Partial Least Squares-Structural Equation Modelling. The internal consistency, convergent validity and discriminant validity of the internal measurement model were assessed. For the external measurement model, global model adjustment and structural validity were assessed. The predictive capacity of the final model was also evaluated. All analyses were performed using SmartPLS version 3.3.2 in consistent mode.

Results: Findings showed an adequate validity of the proposed model, which comprised nine factors: pain catastrophising, hopelessness due to pain, support network, proactivity, treatment compliance, self-care, mobility, resilience, and sleep. The internal validity of the model (Cronbach's alpha and rho_A > 0.70; Average Variance Extracted>0.50; standardised outer loadings>0.60; Heterotrait-Monotrait-Ratio < 0.85), goodness of fit (Standardised Root Mean Square Residuals<0.08; Geodesic and Euclidean distance p-value<0.05) and predictive power with out-of-sample values (Stone-Geisser test>0.5) were adequate. The hypothesised structure of the instrument has also been confirmed (path coefficients>0.3; R2 > 0.1; f2 > 0.2).

Conclusions: The results have shown an adequate internal consistency, convergent validity and discriminant validity of the model. Likewise, the model has shown an adequate goodness of fit, and the validity of its structure and the hypothesis have been confirmed. However, more research is needed in this regard as the possible interaction between the different factors evaluated in the model with the confounding or moderating variables that may exist.