The object of this exploratory study is to identify the positive, neutral and negative environment factors that affect users who visit Spanish hotels in order to help the hotel managers decide how to improve the quality of the services provided. To carry out the research a Sentiment Analysis was initially performed, grouping the sample of tweets (n = 14459) according to the feelings shown and then a textual analysis was used to identify the key environment factors in these feelings using the qualitative analysis software Nvivo (QSR International, Melbourne, Australia). The results of the exploratory study present the key environment factors that affect the users experience when visiting hotels in Spain, such as actions that support local traditions and products, the maintenance of rural areas respecting the local environment and nature, or respecting air quality in the areas where hotels have facilities and offer services. The conclusions of the research can help hotels improve their services and the impact on the environment, as well as improving the visitors experience based on the positive, neutral and negative environment factors which the visitors themselves identified.

Background An increasing number of mobile health (mHealth) apps are becoming available for download and use on mobile devices. Even with the increase in availability and use of mHealth apps, there has still not been a lot of research into understanding the intention to use this kind of apps. Objective The purpose of this study was to investigate a technology acceptance model (TAM) that has been specially designed for primary health care applications. Methods The proposed model is an extension of the TAM, and was empirically tested using data obtained from a survey of mHealth app users (n=310). The research analyzed 2 additional external factors: promotion of health and health benefits. Data were analyzed with a PLS–SEM software and confirmed that gender moderates the adoption of mHealth apps in Spain. The explanatory capacity (R2 for behavioral intention to use) of the proposed model was 76.4%. Likewise, the relationships of the external constructs of the extended TAM were found to be significant. Results The results show the importance of healthy habits developed by using mHealth apps. In addition, communication campaigns for these apps should be aimed at transferring the usefulness of eHealth as an agent for transforming attitudes; additionally, as more health benefits are obtained, ease of use becomes greater. Perceived usefulness (PU; β=.415, t0.001;4999=3.442, P=.001), attitude toward using (β=.301, t0.01;499=2.299, P=.02), and promotion of health (β=.210, t0.05;499=2.108, P=.03) were found to have a statistically significant impact on behavior intention to use eHealth apps (R2=76.4%). Perceived ease of use (PEOU; β=.179, t0.01;499=2.623, P=.009) and PU (β=.755, t0.001;499=12.888, P<.001) were found to have a statistically significant impact on attitude toward using (R2>=78.2%). Furthermore, PEOU (β=.203, t0.01;499=2.810, P=.005), health benefits (β=.448, t0.001;499=4.010, P<.001), and promotion of health (β=.281, t0.01;499=2.393, P=.01) exerted a significant impact on PU (R2=72.7%). Finally, health benefits (β=.640, t0.001;499=14.948, P<.001) had a statistically significant impact on PEOU (R2=40.9%), while promotion of health (β=.865, t0.001;499=29.943, P<.001) significantly influenced health benefits (R2=74.7%). Conclusions mHealth apps could be used to predict the behavior of patients in the face of recommendations to prevent pandemics, such as COVID-19 or SARS, and to track users’ symptoms while they stay at home. Gender is a determining factor that influences the intention to use mHealth apps, so perhaps different interfaces and utilities could be designed according to gender.

Resumen Las tecnologías de la Web 2.0 en ocasiones se muestran borrosas, cuando se ha de demostrar como un mayor o menor uso de estas, influyen de manera directa sobre la mejora de la reputación on-line en los hoteles. En esta ocasión, el estudio muestra un caso singular, donde un establecimiento de la ciudad de Sevilla, ocupa en los dos últimos años el puesto número uno en Tripadvisor. Singular porque el uso que se hace de las tecnologías de la Web 2.0 para mantenerse en este primer puesto, no es siempre el más adecuado.

BACKGROUND An increasing number of Mobile Health Applications (m-Health apps) are becoming available to download and use on mobile devices. Even with the increase in availability and use of m-Health apps, there has still not been a lot of research into understanding the Intention to Use this kind of applications. Therefore, the purpose of this paper is to investigate a technology acceptance model that has been specially designed for primary health care applications. The proposed model is an extension of the Technology Acceptance Model (TAM), and it was empirically tested using data obtained from a survey of m-Health apps users (n = 310). The research analyzed two additional external factors: Promotion of Health and Health Benefits. The data was analyzed with PLS-SEM software and confirmed that gender moderates the adoption of m-Health apps in Spain and the explanatory capacity of the proposed model was R2 BIU =76.4%. Likewise, the relationships of the external constructs of the extended TAM model were found to be significant. The results show the importance of healthy habits developed in m-Health apps. In addition, communication campaigns for these apps should be aimed at transferring the usefulness of e-health as an agent for transforming attitudes, and as more health benefits are obtained, ease of use is greater. Also, m-Health apps could be used to predict what the behavior of patients would be in the face of recommendations to prevent pandemics, such as COVID-19 or SARS and to track users’ symptoms while they stay at home. Gender is a determining factor in how it influences the intention to use m-Health apps, so perhaps different interfaces and utilities could be designed according to gender. OBJECTIVE The purpose of this paper is to investigate a technology acceptance model that has been specially designed for primary health care applications. METHODS The proposed model is an extension of the Technology Acceptance Model (TAM), and it was empirically tested using data obtained from a survey of m-Health apps users (n = 310). The research analyzed two additional external factors: Promotion of Health and Health Benefits. The data was analyzed with PLS-SEM analysis. RESULTS The results confirmed that gender moderates the adoption of m-Health apps in Spain and the explanatory capacity of the proposed model was R2 BIU =76.4%. Likewise, the relationships of the external constructs of the extended TAM model were found to be significant. The results show the importance of healthy habits developed in m-Health apps. In addition, communication campaigns for these apps should be aimed at transferring the usefulness of e-health as an agent for transforming attitudes, and as more health benefits are obtained, ease of use is greater. CONCLUSIONS Also, m-Health apps could be used to predict what the behavior of patients would be in the face of recommendations to prevent pandemics, such as COVID-19 or SARS and to track users’ symptoms while they stay at home. Gender is a determining factor in how it influences the intention to use m-Health apps, so perhaps different interfaces and utilities could be designed according to gender. CLINICALTRIAL _

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