Association of pain intensity and psychological factors among patients with chronic low back pain (LBP). A correlational cross-sectional study / Asociación de la intensidad del dolor y factores psicológicos entre pacientes con dolor lumbar crónico (DLC). Un estudio transversal correlacional

Introduction: Chronic low back pain (cLBP) is associated with a dynamic interaction of multiplepsychological factors that act as predictors of recovery time. Our goal was to quantify the association between pain intensity and psychological variables. Material and methods: A cross-sectional study using convenience sampling was conducted at Universidad Europea de Canarias (Spain) between January 24, 2022 and June 10, 2022. In addition, adults and children with cLBP older than 13 years with cLBP for at least 12 weeks of symptoms were included. Finally, the descriptive analysis and the calculation of the correlation coefficients of the data was carried out with SPSS v.28.0.Results: We recruited 146 subjects (n=85 women, 58.3%; n=61 men,41.7%) aged 50.4 ± 12.21years suffering from cLBP with a moderate pain intensity (7.02±0.188), kinesiophobia (22.79 ±0.559), catastrophism (13.42 ± 0.897), anxiety (24.47±0.560) and the quality of life SF36-PF(65.65±2.291), SF36-PR (48.03±2.727), SF36-BP (33.14±1.566), SF36-GH (43.98±1.873), SF36-V(48.56±1.812), SF36-SF (61.39±2.353), SF36-ER (76.29±2.043) and SF36-MH (49.76±1.666).Pain intensity in cLBP patients was negatively and moderately correlated with SF36-BP score(Pearson's r = -0.561, p < 0.001). In addition, the main variable was negatively and weaklycorrelated with SF36-PF (Pearson's r= -0.395, p<.001), SF36-PR (Pearson's r=-0.433, p<.001),SF36-V (Pearson's r = -0.260, p = 0.006), SF36-GH (Pearson's r = -0.203, p=0.032), SF36-SF(Pearson's r=-0.215, p=0.024). and SF36-MH (Pearson's r= -0.203, p = 0.032). Furthermore, painintensity showed positive and weak with kinesiophobia score (Pearson’s r=0.310, p<.001) andpositive and very weak with catastrophism (Pearson’s r=0.136, p<.001). In contrast, there was notcorrelation between pain intensity and anxiety in cLBP subjects (Pearson’s r=0.025, p=0.794). ... (AU)

Introducción: El dolor lumbar crónico (dolor lumbar crónico) está asociado a una interacción dinámica de múltiples factores psicológicos que actúan como predictores del tiempo de recuperación. Nuestro objetivo fue cuantificar la asociación entre la intensidad del dolor y las variables psicológicas. Material y métodos: Se realizó un estudio transversal mediante muestreo por conveniencia en la Universidad Europea de Canarias (España) entre el 24 de enero de 2022 y el 10 de junio de 2022. Además, adultos y niños mayores de 13 años con dolor lumbar crónico con dolor lumbar crónico durante al menos Se incluyeron 12 semanas de síntomas. Finalmente, el análisis descriptivo y el cálculo de los coeficientes de correlación de los datos se realizó con SPSS v.28.0.Resultados: Se reclutaron 146 sujetos (n=85 mujeres, 58,3 %; n=61 hombres, 41,7 %) de 50,4 ±12,21 años que sufrían dolor lumbar crónico con intensidad de dolor moderada (7,02 ± 0,188),cinesiofobia (22,79 ± 0,559), catastrofismo (13,42±0,897), ansiedad (24,47±0,560) y calidad de vida SF36-PF (65,65±2,291), SF36-PR (48,03±2,727), SF36-BP (33,14±1,566), SF36-GH (43,98±1,873), SF36-V (48,56±1,812), SF36-SF (61,39±2,353), SF36-ER (76,29±2,043) y SF36-MH(49,76±1,666). La intensidad del dolor en pacientes con dolor lumbar crónico se correlacionónegativa y moderadamente con la puntuación SF36-BP (r de Pearson = -0,561, p < 0,001). Además,la variable principal se correlacionó negativa y débilmente con SF36-PF (r de Pearson= -0.395, p<.001), SF36-PR (r de Pearson=-0.433, p<.001), SF36-V (r de Pearson=-0.433, p<.001). = -0,260, p = 0,006), SF36-GH (r de Pearson = -0,203, p=0,032), SF36-SF (r de Pearson = -0,215, p=0,024). y SF36-MH (r de Pearson = -0,203, p = 0,032). Además, la intensidad del dolor mostró puntuación positiva y débil con kinesiofobia (r de Pearson = 0,310, p < 0,001) y positiva y muy débil con catastrofismo (r de Pearson = 0,136, p < 0,001). ... (AU)

CuInS2/ZnS-based QLED design and modelling for automotive lighting systems.

This work reports the design, manufacturing and numerical simulation approach of a 6-pixel (4.5mm2/pixel) electroluminescent quantum dot light emitting device (QLED) based on CuInS2/ZnS quantum dots as an active layer. Following a conventional thin-film deposition multilayer approach, the QLED device was fabricated. In addition, the electrical I-V curve was measured for each pixel independently, observing how the fabrication process and layer thickness have an influence in the shape of the plot. This experimental device fabricated, enabled us to create a computational model for the QLED based on the Transfer Hamiltonian approach to calculate the current density J(mA/cm2), the band diagram of the system, and the accumulated charge distribution. Besides, it is worth highlighting that the simulator allows the possibility to study the influence of different parameters of the QLED structure like the junction capacitance between the distinct multilayer set. Specifically, we found that Anode-HIL interface capacitance has a greater influence in the I-V plot shape. That junction capacitance plays an important role in the current increase and the QLED turn-on value when a forward voltage is applied to the device. Thanks to the simulator, that influence could be put under control by the selection of the optimal thickness and transport layers during the experimental fabrication process. This work is remarkable since it achieves to fit simulation and experiment results in an accurate way for electroluminescent QLED devices; particularly the simulation of the device current, which is critical when designing the automotive electronics to control these new nanotechnology lighting devices in the future.