Publications by authors named "H de Sola"

Objectives: To analyse the effectiveness of a physical exercise programme guided by a mobile health technology system (COVIDReApp) for patients with post-acute COVID-19 syndrome. This syndrome is a multisystem disease that occurs in people with a history of COVID-19 between 1 and 3 months after the onset of the disease. This study will assess the impact of the intervention on fatigue, post-exertional dyspnoea, quality of life, pain severity, physical fitness, anxiety, depression and cognitive function.

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This study aims to improve college magazines, making them more engaging and user-friendly. We combined eye-tracking technology with artificial intelligence to accurately predict consumer behaviours and preferences. Our analysis included three college magazines, both online and in PDF format.

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Background: Chronic pain (CP) is a public health problem worldwide.

Aim: To update the prevalence of CP and compare the clinical and social characteristics of people with CP with those with non-chronic continuous pain and a group without pain.

Methods: An observational cross-sectional study was carried out in a representative sample of 7058 adults from the Spanish population.

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Objective: To determine the prevalence and related factors of diagnosed osteoarthrosis (DO) and undiagnosed osteoarthrosis (UO) in the general Spanish adult population.

Setting: Cross-sectional study with data from the Spanish National Health Survey 2017.

Participants: N=23,089 adults.

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This research investigates the impact of applying neuromarketing techniques to three practical examples of higher education (HE) branding: an official college website page, an official college Facebook page, and recorded online video lectures used for teaching at HE institutions. The study was conducted in three different HE institutions with a representative sample of 720 participants, with = 529 used for testing the CARE college website, = 59 for testing the HAZEF Facebook page, and = 132 for testing the emotional response of students studying online. To assess the participants' emotional responses, this study utilized automated facial coding through a webcam (15 Hz) and considered mood intensities.

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